Sample records for ice extent trends

  1. Trend analysis of Arctic sea ice extent

    NASA Astrophysics Data System (ADS)

    Silva, M. E.; Barbosa, S. M.; Antunes, Luís; Rocha, Conceição

    2009-04-01

    The extent of Arctic sea ice is a fundamental parameter of Arctic climate variability. In the context of climate change, the area covered by ice in the Arctic is a particularly useful indicator of recent changes in the Arctic environment. Climate models are in near universal agreement that Arctic sea ice extent will decline through the 21st century as a consequence of global warming and many studies predict a ice free Arctic as soon as 2012. Time series of satellite passive microwave observations allow to assess the temporal changes in the extent of Arctic sea ice. Much of the analysis of the ice extent time series, as in most climate studies from observational data, have been focussed on the computation of deterministic linear trends by ordinary least squares. However, many different processes, including deterministic, unit root and long-range dependent processes can engender trend like features in a time series. Several parametric tests have been developed, mainly in econometrics, to discriminate between stationarity (no trend), deterministic trend and stochastic trends. Here, these tests are applied in the trend analysis of the sea ice extent time series available at National Snow and Ice Data Center. The parametric stationary tests, Augmented Dickey-Fuller (ADF), Phillips-Perron (PP) and the KPSS, do not support an overall deterministic trend in the time series of Arctic sea ice extent. Therefore, alternative parametrizations such as long-range dependence should be considered for characterising long-term Arctic sea ice variability.

  2. A Model Assessment of Satellite Observed Trends in Polar Sea Ice Extents

    NASA Technical Reports Server (NTRS)

    Vinnikov, Konstantin Y.; Cavalieri, Donald J.; Parkinson, Claire L.

    2005-01-01

    For more than three decades now, satellite passive microwave observations have been used to monitor polar sea ice. Here we utilize sea ice extent trends determined from primarily satellite data for both the Northern and Southern Hemispheres for the period 1972(73)-2004 and compare them with results from simulations by eleven climate models. In the Northern Hemisphere, observations show a statistically significant decrease of sea ice extent and an acceleration of sea ice retreat during the past three decades. However, from the modeled natural variability of sea ice extents in control simulations, we conclude that the acceleration is not statistically significant and should not be extrapolated into the future. Observations and model simulations show that the time scale of climate variability in sea ice extent in the Southern Hemisphere is much larger than in the Northern Hemisphere and that the Southern Hemisphere sea ice extent trends are not statistically significant.

  3. Global Warming and Northern Hemisphere Sea Ice Extent.

    PubMed

    Vinnikov; Robock; Stouffer; Walsh; Parkinson; Cavalieri; Mitchell; Garrett; Zakharov

    1999-12-03

    Surface and satellite-based observations show a decrease in Northern Hemisphere sea ice extent during the past 46 years. A comparison of these trends to control and transient integrations (forced by observed greenhouse gases and tropospheric sulfate aerosols) from the Geophysical Fluid Dynamics Laboratory and Hadley Centre climate models reveals that the observed decrease in Northern Hemisphere sea ice extent agrees with the transient simulations, and both trends are much larger than would be expected from natural climate variations. From long-term control runs of climate models, it was found that the probability of the observed trends resulting from natural climate variability, assuming that the models' natural variability is similar to that found in nature, is less than 2 percent for the 1978-98 sea ice trends and less than 0.1 percent for the 1953-98 sea ice trends. Both models used here project continued decreases in sea ice thickness and extent throughout the next century.

  4. Variability and Trends in Sea Ice Extent and Ice Production in the Ross Sea

    NASA Technical Reports Server (NTRS)

    Comiso, Josefino; Kwok, Ronald; Martin, Seelye; Gordon, Arnold L.

    2011-01-01

    Salt release during sea ice formation in the Ross Sea coastal regions is regarded as a primary forcing for the regional generation of Antarctic Bottom Water. Passive microwave data from November 1978 through 2008 are used to examine the detailed seasonal and interannual characteristics of the sea ice cover of the Ross Sea and the adjacent Bellingshausen and Amundsen seas. For this period the sea ice extent in the Ross Sea shows the greatest increase of all the Antarctic seas. Variability in the ice cover in these regions is linked to changes in the Southern Annular Mode and secondarily to the Antarctic Circumpolar Wave. Over the Ross Sea shelf, analysis of sea ice drift data from 1992 to 2008 yields a positive rate of increase in the net ice export of about 30,000 sq km/yr. For a characteristic ice thickness of 0.6 m, this yields a volume transport of about 20 cu km/yr, which is almost identical, within error bars, to our estimate of the trend in ice production. The increase in brine rejection in the Ross Shelf Polynya associated with the estimated increase with the ice production, however, is not consistent with the reported Ross Sea salinity decrease. The locally generated sea ice enhancement of Ross Sea salinity may be offset by an increase of relatively low salinity of the water advected into the region from the Amundsen Sea, a consequence of increased precipitation and regional glacial ice melt.

  5. A 21-Year Record of Arctic Sea Ice Extents and Their Regional, Seasonal, and Monthly Variability and Trends

    NASA Technical Reports Server (NTRS)

    Parkinson, Claire L.; Cavalieri, Donald J.; Zukor, Dorothy J. (Technical Monitor)

    2001-01-01

    Satellite passive-microwave data have been used to calculate sea ice extents over the period 1979-1999 for the north polar sea ice cover as a whole and for each of nine regions. Over this 21-year time period, the trend in yearly average ice extents for the ice cover as a whole is -32,900 +/- 6,100 sq km/yr (-2.7 +/- 0.5 %/decade), indicating a reduction in sea ice coverage that has decelerated from the earlier reported value of -34,000 +/- 8,300 sq km/yr (-2.8 +/- 0.7 %/decade) for the period 1979-1996. Regionally, the reductions are greatest in the Arctic Ocean, the Kara and Barents Seas, and the Seas of Okhotsk and Japan, whereas seasonally, the reductions are greatest in summer, for which season the 1979-1999 trend in ice extents is -41,600 +/- 12,900 sq km/ yr (-4.9 +/- 1.5 %/decade). On a monthly basis, the reductions are greatest in July and September for the north polar ice cover as a whole, in September for the Arctic Ocean, in June and July for the Kara and Barents Seas, and in April for the Seas of Okhotsk and Japan. Only two of the nine regions show overall ice extent increases, those being the Bering Sea and the Gulf of St. Lawrence.For neither of these two regions is the increase statistically significant, whereas the 1079 - 1999 ice extent decreases are statistically significant at the 99% confidence level for the north polar region as a whole, the Arctic Ocean, the Seas of Okhotsk and Japan, and Hudson Bay.

  6. Antarctic Sea Ice Variability and Trends, 1979-2010

    NASA Technical Reports Server (NTRS)

    Parkinson, C. L.; Cavalieri, D. J.

    2012-01-01

    In sharp contrast to the decreasing sea ice coverage of the Arctic, in the Antarctic the sea ice cover has, on average, expanded since the late 1970s. More specifically, satellite passive-microwave data for the period November 1978 - December 2010 reveal an overall positive trend in ice extents of 17,100 +/- 2,300 square km/yr. Much of the increase, at 13,700 +/- 1,500 square km/yr, has occurred in the region of the Ross Sea, with lesser contributions from the Weddell Sea and Indian Ocean. One region, that of the Bellingshausen/Amundsen Seas, has, like the Arctic, instead experienced significant sea ice decreases, with an overall ice extent trend of -8,200 +/- 1,200 square km/yr. When examined through the annual cycle over the 32-year period 1979-2010, the Southern Hemisphere sea ice cover as a whole experienced positive ice extent trends in every month, ranging in magnitude from a low of 9,100 +/- 6,300 square km/yr in February to a high of 24,700 +/- 10,000 square km/yr in May. The Ross Sea and Indian Ocean also had positive trends in each month, while the Bellingshausen/Amundsen Seas had negative trends in each month, and the Weddell Sea and Western Pacific Ocean had a mixture of positive and negative trends. Comparing ice-area results to ice-extent results, in each case the ice-area trend has the same sign as the ice-extent trend, but differences in the magnitudes of the two trends identify regions with overall increasing ice concentrations and others with overall decreasing ice concentrations. The strong pattern of decreasing ice coverage in the Bellingshausen/Amundsen Seas region and increasing ice coverage in the Ross Sea region is suggestive of changes in atmospheric circulation. This is a key topic for future research.

  7. Observed and Modeled Trends in Southern Ocean Sea Ice

    NASA Technical Reports Server (NTRS)

    Parkinson, Claire L.

    2003-01-01

    Conceptual models and global climate model (GCM) simulations have both indicated the likelihood of an enhanced sensitivity to climate change in the polar regions, derived from the positive feedbacks brought about by the polar abundance of snow and ice surfaces. Some models further indicate that the changes in the polar regions can have a significant impact globally. For instance, 37% of the temperature sensitivity to a doubling of atmospheric CO2 in simulations with the GCM of the Goddard Institute for Space Studies (GISS) is attributable exclusively to inclusion of sea ice variations in the model calculations. Both sea ice thickness and sea ice extent decrease markedly in the doubled CO, case, thereby allowing the ice feedbacks to occur. Stand-alone sea ice models have shown Southern Ocean hemispherically averaged winter ice-edge retreats of 1.4 deg latitude for each 1 K increase in atmospheric temperatures. Observations, however, show a much more varied Southern Ocean ice cover, both spatially and temporally, than many of the modeled expectations. In fact, the satellite passive-microwave record of Southern Ocean sea ice since late 1978 has revealed overall increases rather than decreases in ice extents, with ice extent trends on the order of 11,000 sq km/year. When broken down spatially, the positive trends are strongest in the Ross Sea, while the trends are negative in the Bellingshausen/Amundsen Seas. Greater spatial detail can be obtained by examining trends in the length of the sea ice season, and those trends show a coherent picture of shortening sea ice seasons throughout almost the entire Bellingshausen and Amundsen Seas to the west of the Antarctic Peninsula and in the far western Weddell Sea immediately to the east of the Peninsula, with lengthening sea ice seasons around much of the rest of the continent. This pattern corresponds well with the spatial pattern of temperature trends, as the Peninsula region is the one region in the Antarctic with a strong

  8. Global Sea Ice Coverage from Satellite Data: Annual Cycle and 35-Year Trends

    NASA Technical Reports Server (NTRS)

    Parkinson, Claire L.

    2014-01-01

    Well-established satellite-derived Arctic and Antarctic sea ice extents are combined to create the global picture of sea ice extents and their changes over the 35-yr period 1979-2013. Results yield a global annual sea ice cycle more in line with the high-amplitude Antarctic annual cycle than the lower-amplitude Arctic annual cycle but trends more in line with the high-magnitude negative Arctic trends than the lower-magnitude positive Antarctic trends. Globally, monthly sea ice extent reaches a minimum in February and a maximum generally in October or November. All 12 months show negative trends over the 35-yr period, with the largest magnitude monthly trend being the September trend, at -68,200 +/- 10,500 sq km/yr (-2.62% 6 +/- 0.40%/decade), and the yearly average trend being -35,000 +/- 5900 sq km/yr (-1.47% +/- 0.25%/decade).

  9. Global Sea Ice Coverage from Satellite Data: Annual Cycle and 35-Yr Trends

    NASA Technical Reports Server (NTRS)

    Parkinson, Claire L.

    2014-01-01

    Well-established satellite-derived Arctic and Antarctic sea ice extents are combined to create the global picture of sea ice extents and their changes over the 35-yr period 1979-2013. Results yield a global annual sea ice cycle more in line with the high-amplitude Antarctic annual cycle than the lower-amplitude Arctic annual cycle but trends more in line with the high-magnitude negative Arctic trends than the lower-magnitude positive Antarctic trends. Globally, monthly sea ice extent reaches a minimum in February and a maximum generally in October or November. All 12 months show negative trends over the 35-yr period, with the largest magnitude monthly trend being the September trend, at -68200 +/- 10500 km sq yr(exp -1) (-2.62% +/- 0.40%decade(exp -1)), and the yearly average trend being -35000 +/-5900 km sq yr(exp -1) (-1.47% +/- 0.25%decade(exp -1)).

  10. Arctic sea ice decline contributes to thinning lake ice trend in northern Alaska

    USGS Publications Warehouse

    Alexeev, Vladimir; Arp, Christopher D.; Jones, Benjamin M.; Cai, Lei

    2016-01-01

    Field measurements, satellite observations, and models document a thinning trend in seasonal Arctic lake ice growth, causing a shift from bedfast to floating ice conditions. September sea ice concentrations in the Arctic Ocean since 1991 correlate well (r = +0.69,p < 0.001) to this lake regime shift. To understand how and to what extent sea ice affects lakes, we conducted model experiments to simulate winters with years of high (1991/92) and low (2007/08) sea ice extent for which we also had field measurements and satellite imagery characterizing lake ice conditions. A lake ice growth model forced with Weather Research and Forecasting model output produced a 7% decrease in lake ice growth when 2007/08 sea ice was imposed on 1991/92 climatology and a 9% increase in lake ice growth for the opposing experiment. Here, we clearly link early winter 'ocean-effect' snowfall and warming to reduced lake ice growth. Future reductions in sea ice extent will alter hydrological, biogeochemical, and habitat functioning of Arctic lakes and cause sub-lake permafrost thaw.

  11. 30-Year Satellite Record Reveals Accelerated Arctic Sea Ice Loss, Antarctic Sea Ice Trend Reversal

    NASA Technical Reports Server (NTRS)

    Cavalieri, Donald J.; Parkinson, C. L.; Vinnikov, K. Y.

    2003-01-01

    Arctic sea ice extent decreased by 0.30 plus or minus 0.03 x 10(exp 6) square kilometers per decade from 1972 through 2002, but decreased by 0.36 plus or minus 0.05 x 10(exp 6) square kilometers per decade from 1979 through 2002, indicating an acceleration of 20% in the rate of decrease. In contrast to the Arctic, the Antarctic sea ice extent decreased dramatically over the period 1973-1977, then gradually increased, with an overall 30-year trend of -0.15 plus or minus 0.08 x 10(exp 6) square kilometers per 10yr. The trend reversal is attributed to a large positive anomaly in Antarctic sea ice extent observed in the early 1970's.

  12. Variability and trends in the Arctic Sea ice cover: Results from different techniques

    NASA Astrophysics Data System (ADS)

    Comiso, Josefino C.; Meier, Walter N.; Gersten, Robert

    2017-08-01

    Variability and trend studies of sea ice in the Arctic have been conducted using products derived from the same raw passive microwave data but by different groups using different algorithms. This study provides consistency assessment of four of the leading products, namely, Goddard Bootstrap (SB2), Goddard NASA Team (NT1), EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI-SAF 1.2), and Hadley HadISST 2.2 data in evaluating variability and trends in the Arctic sea ice cover. All four provide generally similar ice patterns but significant disagreements in ice concentration distributions especially in the marginal ice zone and adjacent regions in winter and meltponded areas in summer. The discrepancies are primarily due to different ways the four techniques account for occurrences of new ice and meltponding. However, results show that the different products generally provide consistent and similar representation of the state of the Arctic sea ice cover. Hadley and NT1 data usually provide the highest and lowest monthly ice extents, respectively. The Hadley data also show the lowest trends in ice extent and ice area at -3.88%/decade and -4.37%/decade, respectively, compared to an average of -4.36%/decade and -4.57%/decade for all four. Trend maps also show similar spatial distribution for all four with the largest negative trends occurring at the Kara/Barents Sea and Beaufort Sea regions, where sea ice has been retreating the fastest. The good agreement of the trends especially with updated data provides strong confidence in the quantification of the rate of decline in the Arctic sea ice cover.Plain Language SummaryThe declining Arctic sea <span class="hlt">ice</span> cover, especially in the summer, has been the center of attention in recent years. Reports on the sea <span class="hlt">ice</span> cover have been provided by different institutions using basically the same set of satellite data but different techniques for estimating key parameters such as <span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003AGUFMOS11B..06R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003AGUFMOS11B..06R"><span>Predicting the <span class="hlt">Extent</span> of Summer Sea <span class="hlt">Ice</span> in the Arctic</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rigor, I. G.; Wallace, J. M.</p> <p>2003-12-01</p> <p>The summers of 1998 and 2002 had the least sea <span class="hlt">ice</span> <span class="hlt">extent</span> (SIE) in the Arctic. These observations seem to agree with the <span class="hlt">trends</span> noted by Parkinson, et al. (1999, hereafter P99) for the period 1979-1997, but the spatial pattern of these recent decreases in summer SIE were different. The summer <span class="hlt">trends</span> shown by P99, exhibit large decreases in SIE primarily in the East Siberian Sea (ESS), while the decreases observed during 1998 and 2002 were much larger in the Beaufort and Chukchi seas (BCS). We now show that the <span class="hlt">trends</span> for the period 1979 - 2002 are much smaller in the ESS than the <span class="hlt">trends</span> shown by P99, and the largest decreasing <span class="hlt">trends</span> have shifted from the ESS to the BCS. Rigor, et al. (2002) showed that the changes in SIE that P99 noted were driven by changes in atmospheric circulation related to the phase of the prior winter Arctic Oscillation (AO, Thompson and Wallace, 1998) index. Given that the latest <span class="hlt">trends</span> in SIE are different than those shown by P99, one could ask whether the affect of the AO on sea <span class="hlt">ice</span> noted by Rigor, et al. (2002) has also changed, and whether some large scale climate modes other than the AO has influenced the climate of the Arctic Ocean more? To answer these questions, we applied Empirical Orthogonal Function (EOF) analysis on the September SIE data from microwave satellites, and found that the first two modes SIE were most highly correlated to the prior winter AO, and the AO index of the summer months just prior to each September. These modes explain more than 45% of the variance in SIE, and show that the influence of the winter and summer AO dominates Arctic climate from 1979 - 2002. Using data from the International Arctic Buoy Programme and the National Centers for Environmental Prediction, we will show that the changes in sea <span class="hlt">ice</span> <span class="hlt">extent</span> are primarily driven by dynamic changes in sea <span class="hlt">ice</span> thickness and discuss the implications for predicting summer SIE.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4455712','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4455712"><span>Arctic sea <span class="hlt">ice</span> <span class="hlt">trends</span>, variability and implications for seasonal <span class="hlt">ice</span> forecasting</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Serreze, Mark C.; Stroeve, Julienne</p> <p>2015-01-01</p> <p>September Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> over the period of satellite observations has a strong downward <span class="hlt">trend</span>, accompanied by pronounced interannual variability with a detrended 1 year lag autocorrelation of essentially zero. We argue that through a combination of thinning and associated processes related to a warming climate (a stronger albedo feedback, a longer melt season, the lack of especially cold winters) the downward <span class="hlt">trend</span> itself is steepening. The lack of autocorrelation manifests both the inherent large variability in summer atmospheric circulation patterns and that oceanic heat loss in winter acts as a negative (stabilizing) feedback, albeit insufficient to counter the steepening <span class="hlt">trend</span>. These findings have implications for seasonal <span class="hlt">ice</span> forecasting. In particular, while advances in observing sea <span class="hlt">ice</span> thickness and assimilating thickness into coupled forecast systems have improved forecast skill, there remains an inherent limit to predictability owing to the largely chaotic nature of atmospheric variability. PMID:26032315</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26032315','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26032315"><span>Arctic sea <span class="hlt">ice</span> <span class="hlt">trends</span>, variability and implications for seasonal <span class="hlt">ice</span> forecasting.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Serreze, Mark C; Stroeve, Julienne</p> <p>2015-07-13</p> <p>September Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> over the period of satellite observations has a strong downward <span class="hlt">trend</span>, accompanied by pronounced interannual variability with a detrended 1 year lag autocorrelation of essentially zero. We argue that through a combination of thinning and associated processes related to a warming climate (a stronger albedo feedback, a longer melt season, the lack of especially cold winters) the downward <span class="hlt">trend</span> itself is steepening. The lack of autocorrelation manifests both the inherent large variability in summer atmospheric circulation patterns and that oceanic heat loss in winter acts as a negative (stabilizing) feedback, albeit insufficient to counter the steepening <span class="hlt">trend</span>. These findings have implications for seasonal <span class="hlt">ice</span> forecasting. In particular, while advances in observing sea <span class="hlt">ice</span> thickness and assimilating thickness into coupled forecast systems have improved forecast skill, there remains an inherent limit to predictability owing to the largely chaotic nature of atmospheric variability. © 2015 The Author(s) Published by the Royal Society. All rights reserved.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140005669','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140005669"><span>Computing and Representing Sea <span class="hlt">Ice</span> <span class="hlt">Trends</span>: Toward a Community Consensus</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wohlleben, T.; Tivy, A.; Stroeve, J.; Meier, Walter N.; Fetterer, F.; Wang, J.; Assel, R.</p> <p>2013-01-01</p> <p>Estimates of the recent decline in Arctic Ocean summer sea <span class="hlt">ice</span> <span class="hlt">extent</span> can vary due to differences in sea <span class="hlt">ice</span> data sources, in the number of years used to compute the <span class="hlt">trend</span>, and in the start and end years used in the <span class="hlt">trend</span> computation. Compounding such differences, estimates of the relative decline in sea <span class="hlt">ice</span> cover (given in percent change per decade) can further vary due to the choice of reference value (the initial point of the <span class="hlt">trend</span> line, a climatological baseline, etc.). Further adding to the confusion, very often when relative <span class="hlt">trends</span> are reported in research papers, the reference values used are not specified or made clear. This can lead to confusion when <span class="hlt">trend</span> studies are cited in the press and public reports.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.7955K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.7955K"><span>Springtime atmospheric transport controls Arctic summer sea-<span class="hlt">ice</span> <span class="hlt">extent</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kapsch, Marie; Graversen, Rune; Tjernström, Michael</p> <p>2013-04-01</p> <p>The sea-<span class="hlt">ice</span> <span class="hlt">extent</span> in the Arctic has been steadily decreasing during the satellite remote sensing era, 1979 to present, with the highest rate of retreat found in September. Contributing factors causing the <span class="hlt">ice</span> retreat are among others: changes in surface air temperature (SAT; Lindsay and Zhang, 2005), <span class="hlt">ice</span> circulation in response to winds/pressure patterns (Overland et al., 2008) and ocean currents (Comiso et al., 2008), as well as changes in radiative fluxes (e.g. due to changes in cloud cover; Francis and Hunter, 2006; Maksimovich and Vihma, 2012) and ocean conditions. However, large interannual variability is superimposed onto the declining <span class="hlt">trend</span> - the <span class="hlt">ice</span> <span class="hlt">extent</span> by the end of the summer varies by several million square kilometer between successive years (Serreze et al., 2007). But what are the processes causing the year-to-year <span class="hlt">ice</span> variability? A comparison of years with an anomalously large September sea-<span class="hlt">ice</span> <span class="hlt">extent</span> (HIYs - high <span class="hlt">ice</span> years) with years showing an anomalously small <span class="hlt">ice</span> <span class="hlt">extent</span> (LIYs - low <span class="hlt">ice</span> years) reveals that the <span class="hlt">ice</span> variability is most pronounced in the Arctic Ocean north of Siberia (which became almost entirely <span class="hlt">ice</span> free in September of 2007 and 2012). Significant <span class="hlt">ice</span>-concentration anomalies of up to 30% are observed for LIYs and HIYs in this area. Focusing on this area we find that the greenhouse effect associated with clouds and water-vapor in spring is crucial for the development of the sea <span class="hlt">ice</span> during the subsequent months. In years where the end-of-summer sea-<span class="hlt">ice</span> <span class="hlt">extent</span> is well below normal, a significantly enhanced transport of humid air is evident during spring into the region where the <span class="hlt">ice</span> retreat is encountered. The anomalous convergence of humidity increases the cloudiness, resulting in an enhancement of the greenhouse effect. As a result, downward longwave radiation at the surface is larger than usual. In mid May, when the <span class="hlt">ice</span> anomaly begins to appear and the surface albedo therefore becomes anomalously low, the net shortwave radiation</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170009008&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dsea','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170009008&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dsea"><span>Variability and <span class="hlt">Trends</span> in the Arctic Sea <span class="hlt">Ice</span> Cover: Results from Different Techniques</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Josefino C.; Meier, Walter N.; Gersten, Robert</p> <p>2017-01-01</p> <p>Variability and <span class="hlt">trend</span> studies of sea <span class="hlt">ice</span> in the Arctic have been conducted using products derived from the same raw passive microwave data but by different groups using different algorithms. This study provides consistency assessment of four of the leading products, namely, Goddard Bootstrap (SB2), Goddard NASA Team (NT1), EUMETSAT Ocean and Sea <span class="hlt">Ice</span> Satellite Application Facility (OSI-SAF 1.2), and Hadley HadISST 2.2 data in evaluating variability and <span class="hlt">trends</span> in the Arctic sea <span class="hlt">ice</span> cover. All four provide generally similar <span class="hlt">ice</span> patterns but significant disagreements in <span class="hlt">ice</span> concentration distributions especially in the marginal <span class="hlt">ice</span> zone and adjacent regions in winter and meltponded areas in summer. The discrepancies are primarily due to different ways the four techniques account for occurrences of new <span class="hlt">ice</span> and meltponding. However, results show that the different products generally provide consistent and similar representation of the state of the Arctic sea <span class="hlt">ice</span> cover. Hadley and NT1 data usually provide the highest and lowest monthly <span class="hlt">ice</span> <span class="hlt">extents</span>, respectively. The Hadley data also show the lowest <span class="hlt">trends</span> in <span class="hlt">ice</span> <span class="hlt">extent</span> and <span class="hlt">ice</span> area at negative 3.88 percent decade and negative 4.37 percent decade, respectively, compared to an average of negative 4.36 percent decade and negative 4.57 percent decade for all four. <span class="hlt">Trend</span> maps also show similar spatial distribution for all four with the largest negative <span class="hlt">trends</span> occurring at the Kara/Barents Sea and Beaufort Sea regions, where sea <span class="hlt">ice</span> has been retreating the fastest. The good agreement of the <span class="hlt">trends</span> especially with updated data provides strong confidence in the quantification of the rate of decline in the Arctic sea <span class="hlt">ice</span> cover.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C31A0622S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C31A0622S"><span>Probabilistic Forecasting of Arctic Sea <span class="hlt">Ice</span> <span class="hlt">Extent</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Slater, A. G.</p> <p>2013-12-01</p> <p>Sea <span class="hlt">ice</span> in the Arctic is changing rapidly. Most noticeable has been the series of record, or near-record, annual minimums in sea <span class="hlt">ice</span> <span class="hlt">extent</span> in the past six years. The changing regime of sea <span class="hlt">ice</span> has prompted much interest in seasonal prediction of sea <span class="hlt">ice</span> <span class="hlt">extent</span>, particularly as opportunities for Arctic shipping and resource exploration or extraction increase. This study presents a daily sea <span class="hlt">ice</span> <span class="hlt">extent</span> probabilistic forecast method with a 50-day lead time. A base projection is made from historical data and near-real-time sea <span class="hlt">ice</span> concentration is assimilated on the issue date of the forecast. When considering the September mean <span class="hlt">ice</span> <span class="hlt">extent</span> for the period 1995-2012, the performance of the 50-day lead time forecast is very good: correlation=0.94, Bias = 0.14 ×106 km^2 and RMSE = 0.36 ×106 km^2. Forecasts for the daily minimum contains equal skill levels. The system is highly competitive with any of the SEARCH Sea <span class="hlt">Ice</span> Outlook estimates. The primary finding of this study is that large amounts of forecast skill can be gained from knowledge of the initial conditions of concentration (perhaps more than previously thought). Given the simplicity of the forecast model, improved skill should be available from system refinement and with suitable proxies for large scale atmosphere and ocean circulation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170005812&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsea','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170005812&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsea"><span>Bellingshausen Sea <span class="hlt">Ice</span> <span class="hlt">Extent</span> Recorded in an Antarctic Peninsula <span class="hlt">Ice</span> Core</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Porter, Stacy E.; Parkinson, Claire L.; Mosley-Thompson, Ellen</p> <p>2016-01-01</p> <p>Annual net accumulation (A(sub n)) from the Bruce Plateau (BP) <span class="hlt">ice</span> core retrieved from the Antarctic Peninsula exhibits a notable relationship with sea <span class="hlt">ice</span> <span class="hlt">extent</span> (SIE) in the Bellingshausen Sea. Over the satellite era, both BP A(sub n) and Bellingshausen SIE are influenced by large-scale climatic factors such as the Amundsen Sea Low, Southern Annular Mode, and Southern Oscillation. In addition to the direct response of BP A(sub n) to Bellingshausen SIE (e.g., more open water as a moisture source), these large-scale climate phenomena also link the BP and the Bellingshausen Sea indirectly such that they exhibit similar responses (e.g., northerly wind anomalies advect warm, moist air to the Antarctic Peninsula and neighboring Bellingshausen Sea, which reduces SIE and increases A(sub n)). Comparison with a time series of fast <span class="hlt">ice</span> at South Orkney Islands reveals a relationship between BP A(sub n) and sea <span class="hlt">ice</span> in the northern Weddell Sea that is relatively consistent over the twentieth century, except when it is modulated by atmospheric wave patterns described by the Trans-Polar Index. The <span class="hlt">trend</span> of increasing accumulation on the Bruce Plateau since approximately 1970 agrees with other climate records and reconstructions in the region and suggests that the current rate of sea <span class="hlt">ice</span> loss in the Bellingshausen Sea is unrivaled in the twentieth century.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li class="active"><span>1</span></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_1 --> <div id="page_2" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li class="active"><span>2</span></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="21"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20000090513','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20000090513"><span>Update on the Greenland <span class="hlt">Ice</span> Sheet Melt <span class="hlt">Extent</span>: 1979-1999</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Abdalati, Waleed; Steffen, Konrad</p> <p>2000-01-01</p> <p>Analysis of melt <span class="hlt">extent</span> on the Greenland <span class="hlt">ice</span> sheet is updated to span the time period 1979-1999 is examined along with its spatial and temporal variability using passive microwave satellite data. In order to acquire the full record, the issue of continuity between previous passive microwave sensors (SMMR, SSM/I F-8, and SSM/I F-11), and the most recent SSM/I F-13 sensor is addressed. The F-13 Cross-polarized gradient ratio (XPGR) melt-classification threshold is determined to be -0.0154. Results show that for the 21-year record, an increasing melt <span class="hlt">trend</span> of nearly 1 %/yr is observed, and this <span class="hlt">trend</span> is driven by conditions on in the western portion of the <span class="hlt">ice</span> sheet, rather than the east, where melt appears to have decreased slightly. Moreover, the eruption of Mt. Pinatubo in 1991 is likely to have had some impact the melt, but not as much as previously suspected. The 1992 melt anomaly is 1.7 standard deviations from the mean. Finally, the relationship between coastal temperatures and melt <span class="hlt">extent</span> suggest an increase in surface runoff contribution to sea level of 0.31 mm/yr for a 1 C temperature rise.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.3020R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.3020R"><span>Determining the <span class="hlt">ice</span> seasons severity during 1982-2015 using the <span class="hlt">ice</span> <span class="hlt">extents</span> sum as a new characteristic</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rjazin, Jevgeni; Pärn, Ove</p> <p>2016-04-01</p> <p>Sea <span class="hlt">ice</span> is a key climate factor and it restricts considerably the winter navigation in sever seasons on the Baltic Sea. So determining <span class="hlt">ice</span> conditions severity and describing <span class="hlt">ice</span> cover behaviour at severe seasons interests scientists, engineers and navigation managers. The present study is carried out to determine the <span class="hlt">ice</span> seasons severity degree basing on the <span class="hlt">ice</span> seasons 1982 to 2015. A new integrative characteristic is introduced to describe the <span class="hlt">ice</span> season severity. It is the sum of <span class="hlt">ice</span> <span class="hlt">extents</span> of the <span class="hlt">ice</span> season id est the daily <span class="hlt">ice</span> <span class="hlt">extents</span> of the season are summed. The commonly used procedure to determine the <span class="hlt">ice</span> season severity degree by the maximal <span class="hlt">ice</span> <span class="hlt">extent</span> is in this research compared to the new characteristic values. The remote sensing data on the <span class="hlt">ice</span> concentrations on the Baltic Sea published in the European Copernicus Programme are used to obtain the severity characteristic values. The <span class="hlt">ice</span> <span class="hlt">extents</span> are calculated on these <span class="hlt">ice</span> concentration data. Both the maximal <span class="hlt">ice</span> <span class="hlt">extent</span> of the season and a newly introduced characteristic - the <span class="hlt">ice</span> <span class="hlt">extents</span> sum are used to classify the winters with respect of severity. The most severe winter of the reviewed period is 1986/87. Also the <span class="hlt">ice</span> seasons 1981/82, 1984/85, 1985/86, 1995/96 and 2002/03 are classified as severe. Only three seasons of this list are severe by both the criteria. They are 1984/85, 1985/86 and 1986/87. We interpret this coincidence as the evidence of enough-during extensive <span class="hlt">ice</span> cover in these three seasons. In several winters, for example 2010/11 <span class="hlt">ice</span> cover extended enough for some time, but did not endure. At few other <span class="hlt">ice</span> seasons as 2002/03 the Baltic Sea was <span class="hlt">ice</span>-covered in moderate <span class="hlt">extent</span>, but the <span class="hlt">ice</span> cover stayed long time. At 11 winters the <span class="hlt">ice</span> <span class="hlt">extents</span> sum differed considerably (> 10%) from the maximal <span class="hlt">ice</span> <span class="hlt">extent</span>. These winters yield one third of the studied <span class="hlt">ice</span> seasons. The maximal <span class="hlt">ice</span> <span class="hlt">extent</span> of the season is simple to use and enables to reconstruct the <span class="hlt">ice</span> cover history and to predict maximal <span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160007571&hterms=information&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dinformation','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160007571&hterms=information&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dinformation"><span>New Visualizations Highlight New Information on the Contrasting Arctic and Antarctic Sea-<span class="hlt">Ice</span> <span class="hlt">Trends</span> Since the Late 1970s</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.; DiGirolamo, Nicolo E.</p> <p>2016-01-01</p> <p>Month-by-month ranking of 37 years (1979-2015) of satellite-derived sea-<span class="hlt">ice</span> <span class="hlt">extents</span> in the Arctic and Antarctic reveals interesting new details in the overall <span class="hlt">trends</span> toward decreasing sea-<span class="hlt">ice</span> coverage in the Arctic and increasing sea-<span class="hlt">ice</span> coverage in the Antarctic. The Arctic decreases are so definitive that there has not been a monthly record high in Arctic sea-<span class="hlt">ice</span> <span class="hlt">extents</span> in any month since 1986, a time period during which there have been 75 monthly record lows. The Antarctic, with the opposite but weaker <span class="hlt">trend</span> toward increased <span class="hlt">ice</span> <span class="hlt">extents</span>, experienced monthly record lows in 5 months of 1986, then 6 later monthly record lows scattered through the dataset, with the last two occurring in 2006, versus 45 record highs since 1986. However, in the last three years of the 1979-2015 dataset, the downward <span class="hlt">trends</span> in Arctic sea-<span class="hlt">ice</span> <span class="hlt">extents</span> eased up, with no new record lows in any month of 2013 or 2014 and only one record low in 2015,while the upward <span class="hlt">trends</span> in Antarctic <span class="hlt">ice</span> <span class="hlt">extents</span> notably strengthened, with new record high <span class="hlt">ice</span> <span class="hlt">extents</span> in 4 months (August-November) of 2013, in 6 months (April- September) of 2014, and in 3 months (January, April, and May) of 2015. Globally, there have been only 3 monthly record highs since 1986 (only one since 1988), whereas there have been 43 record lows, although the last record lows (in the 1979-2015 dataset) occurred in 2012.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080023287','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080023287"><span>Arctic Sea <span class="hlt">Ice</span> Variability and <span class="hlt">Trends</span>, 1979-2006</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.; Cavalieri, Donald J.</p> <p>2008-01-01</p> <p>Analysis of Arctic sea <span class="hlt">ice</span> <span class="hlt">extents</span> derived from satellite passive-microwave data for the 28 years, 1979-2006 yields an overall negative <span class="hlt">trend</span> of -45,100 +/- 4,600 km2/yr (-3.7 +/- 0.4%/decade) in the yearly averages, with negative <span class="hlt">ice-extent</span> <span class="hlt">trends</span> also occurring for each of the four seasons and each of the 12 months. For the yearly averages the largest decreases occur in the Kara and Barents Seas and the Arctic Ocean, with linear least squares slopes of -10,600 +/- 2,800 km2/yr (-7.4 +/- 2.0%/decade) and -10,100 +/- 2,200 km2/yr (-1.5 +/- 0.3%/decade), respectively, followed by Baffin Bay/Labrador Sea, with a slope of -8,000 +/- 2,000 km2/yr) -9.0 +/- 2.3%/decade), the Greenland Sea, with a slope of -7,000 +/- 1,400 km2/yr (-9.3 +/- 1.9%/decade), and Hudson Bay, with a slope of -4,500 +/- 900 km2/yr (-5.3 +/- 1.1%/decade). These are all statistically significant decreases at a 99% confidence level. The Seas of Okhotsk and Japan also have a statistically significant <span class="hlt">ice</span> decrease, although at a 95% confidence level, and the three remaining regions, the Bering Sea, Canadian Archipelago, and Gulf of St. Lawrence, have negative slopes that are not statistically significant. The 28-year <span class="hlt">trends</span> in <span class="hlt">ice</span> areas for the Northern Hemisphere total are also statistically significant and negative in each season, each month, and for the yearly averages.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSHE44B1511L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSHE44B1511L"><span>Contribution of Increasing Glacial Freshwater Fluxes to Observed <span class="hlt">Trends</span> in Antarctic Sea <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Le Sommer, J.; Merino, N.; Durand, G.; Jourdain, N.; Goosse, H.; Mathiot, P.; Gurvan, M.</p> <p>2016-02-01</p> <p>Southern Ocean sea-<span class="hlt">ice</span> <span class="hlt">extent</span> has experienced an overall positive <span class="hlt">trend</span> over recent decades. While the amplitude of this <span class="hlt">trend</span> is open to debate, the geographical pattern of regional changes has been clearly identified by observations. Mechanisms driving changes in the Antarctic Sea <span class="hlt">Ice</span> <span class="hlt">Extent</span> (SIE) are not fully understood and climate models fail to simulate these <span class="hlt">trends</span>. Changes in different atmospheric features such as SAM or ENSO seem to explain the observed <span class="hlt">trend</span> of Antartic sea <span class="hlt">ice</span>, but only partly, since they can not account for the actual amplitude of the observed signal. The increasing injection of freshwater due to the accelerating <span class="hlt">ice</span> discharge from Antarctica <span class="hlt">Ice</span> Sheet (AIS) during the last two decades has been proposed as another candidate to contribute to SIE <span class="hlt">trend</span>. However, the quantity and the distribution of the extra freshwater injection were not properly constrained. Recent glaciological estimations may improve the way the glacial freshwater is injected in the model. Here, we study the role of the glacial freshwater into the observed SIE <span class="hlt">trend</span>, using the state-of-the-art Antarctic mass loss estimations. Ocean/sea-<span class="hlt">ice</span> model simulations have been carried out with two different Antarctic freshwater scenarios corresponding to 20-years of Antarctic <span class="hlt">Ice</span> Sheet evolution. The combination of an improved iceberg model with the most recent glaciological estimations has been applied to account for the most realistic possible Antarctic freshwater evolution scenarios. Results suggest that Antarctica has contributed to almost a 30% of the observed <span class="hlt">trend</span> in regions of the South Pacific and South East Indian sectors, but has little impact in the South Atlantic sector. We conclude that the observed SIE <span class="hlt">trend</span> over the last decades is due to a combination of both an atmospheric forcing and the extra freshwater injection. Our results advocates that the evolution of glacial freshwater needs to be correctly represented in climate models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000039366&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DParkinsons','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000039366&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DParkinsons"><span>Changes in the Areal <span class="hlt">Extent</span> of Arctic Sea <span class="hlt">Ice</span>: Observations from Satellites</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>2000-01-01</p> <p>Wintertime sea <span class="hlt">ice</span> covers 15 million square kilometers of the north polar region, an area exceeding one and a half times the area of the U. S. Even at the end of the summer melt season, sea <span class="hlt">ice</span> still covers 7 million square kilometers. This vast <span class="hlt">ice</span> cover is an integral component of the climate system, being moved around by winds and waves, restricting heat and other exchanges between the ocean and atmosphere, reflecting most of the solar radiation incident on it, transporting cold, relatively fresh water equatorward, and affecting the overturning of ocean waters underneath, with impacts that can be felt worldwide. Sea <span class="hlt">ice</span> also is a major factor in the Arctic ecosystem, affecting life forms ranging from minute organisms living within the <span class="hlt">ice</span>, sometimes to the tune of millions in a single <span class="hlt">ice</span> floe, to large marine mammals like walruses that rely on sea <span class="hlt">ice</span> as a platform for resting, foraging, social interaction, and breeding. Since 1978, satellite technology has allowed the monitoring of the vast Arctic sea <span class="hlt">ice</span> cover on a routine basis. The satellite observations reveal that, overall, the areal <span class="hlt">extent</span> of Arctic sea <span class="hlt">ice</span> has been decreasing since 1978, at an average rate of 2.7% per decade through the end of 1998. Through 1998, the greatest rates of decrease occurred in the Seas of Okhotsk and Japan and the Kara and Barents Seas, with most other regions of the Arctic also experiencing <span class="hlt">ice</span> <span class="hlt">extent</span> decreases. The two regions experiencing <span class="hlt">ice</span> <span class="hlt">extent</span> increases over this time period were the Bering Sea and the Gulf of St. Lawrence. Furthermore, the satellite data reveal that the sea <span class="hlt">ice</span> season shortened by over 25 days per decade in the central Sea of Okhotsk and the eastern Barents Sea, and by lesser amounts throughout much of the rest of the Arctic seasonal sea <span class="hlt">ice</span> region, although not in the Bering Sea or the Gulf of St. Lawrence. Concern has been raised that if the <span class="hlt">trends</span> toward shortened sea <span class="hlt">ice</span> seasons and lesser sea <span class="hlt">ice</span> coverage continue, this could entail major</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29806697','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29806697"><span>The Arctic's sea <span class="hlt">ice</span> cover: <span class="hlt">trends</span>, variability, predictability, and comparisons to the Antarctic.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Serreze, Mark C; Meier, Walter N</p> <p>2018-05-28</p> <p>As assessed over the period of satellite observations, October 1978 to present, there are downward linear <span class="hlt">trends</span> in Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> for all months, largest at the end of the melt season in September. The <span class="hlt">ice</span> cover is also thinning. Downward <span class="hlt">trends</span> in <span class="hlt">extent</span> and thickness have been accompanied by pronounced interannual and multiyear variability, forced by both the atmosphere and ocean. As the <span class="hlt">ice</span> thins, its response to atmospheric and oceanic forcing may be changing. In support of a busier Arctic, there is a growing need to predict <span class="hlt">ice</span> conditions on a variety of time and space scales. A major challenge to providing seasonal scale predictions is the 7-10 days limit of numerical weather prediction. While a seasonally <span class="hlt">ice</span>-free Arctic Ocean is likely well within this century, there is much uncertainty in the timing. This reflects differences in climate model structure, the unknown evolution of anthropogenic forcing, and natural climate variability. In sharp contrast to the Arctic, Antarctic sea <span class="hlt">ice</span> <span class="hlt">extent</span>, while highly variable, has increased slightly over the period of satellite observations. The reasons for this different behavior remain to be resolved, but responses to changing atmospheric circulation patterns appear to play a strong role. © 2018 New York Academy of Sciences.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19980237537','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19980237537"><span>Spatial Distribution of <span class="hlt">Trends</span> and Seasonality in the Hemispheric Sea <span class="hlt">Ice</span> Covers</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Gloersen, P.; Parkinson, C. L.; Cavalieri, D. J.; Cosmiso, J. C.; Zwally, H. J.</p> <p>1998-01-01</p> <p>We extend earlier analyses of a 9-year sea <span class="hlt">ice</span> data set that described the local seasonal and <span class="hlt">trend</span> variations in each of the hemispheric sea <span class="hlt">ice</span> covers to the recently merged 18.2-year sea <span class="hlt">ice</span> record from four satellite instruments. The seasonal cycle characteristics remain essentially the same as for the shorter time series, but the local <span class="hlt">trends</span> are markedly different, in some cases reversing sign. The sign reversal reflects the lack of a consistent long-term <span class="hlt">trend</span> and could be the result of localized long-term oscillations in the hemispheric sea <span class="hlt">ice</span> covers. By combining the separate hemispheric sea <span class="hlt">ice</span> records into a global one, we have shown that there are statistically significant net decreases in the sea <span class="hlt">ice</span> coverage on a global scale. The change in the global sea <span class="hlt">ice</span> <span class="hlt">extent</span>, is -0.01 +/- 0.003 x 10(exp 6) sq km per decade. The decrease in the areal coverage of the sea <span class="hlt">ice</span> is only slightly smaller, so that the difference in the two, the open water within the packs, has no statistically significant change.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JGRC..120.7791S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JGRC..120.7791S"><span>Seasonal and interannual variability of fast <span class="hlt">ice</span> <span class="hlt">extent</span> in the southeastern Laptev Sea between 1999 and 2013</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Selyuzhenok, V.; Krumpen, T.; Mahoney, A.; Janout, M.; Gerdes, R.</p> <p>2015-12-01</p> <p>Along with changes in sea <span class="hlt">ice</span> <span class="hlt">extent</span>, thickness, and drift speed, Arctic sea <span class="hlt">ice</span> regime is characterized by a decrease of fast <span class="hlt">ice</span> season and reduction of fast <span class="hlt">ice</span> <span class="hlt">extent</span>. The most extensive fast <span class="hlt">ice</span> cover in the Arctic develops in the southeastern Laptev Sea. Using weekly operational sea <span class="hlt">ice</span> charts produced by Arctic and Antarctic Research Institute (AARI, Russia) from 1999 to 2013, we identified five main key events that characterize the annual evolution of fast <span class="hlt">ice</span> in the southeastern Laptev Sea. Linking the occurrence of the key events with the atmospheric forcing, bathymetry, freezeup, and melt onset, we examined the processes driving annual fast <span class="hlt">ice</span> cycle. The analysis revealed that fast <span class="hlt">ice</span> in the region is sensitive to thermodynamic processes throughout a season, while the wind has a strong influence only on the first stages of fast <span class="hlt">ice</span> development. The maximal fast <span class="hlt">ice</span> <span class="hlt">extent</span> is closely linked to the bathymetry and local topography and is primarily defined by the location of shoals, where fast <span class="hlt">ice</span> is likely grounded. The annual fast <span class="hlt">ice</span> cycle shows significant changes over the period of investigation, with tendencies toward later fast <span class="hlt">ice</span> formation and earlier breakup. These tendencies result in an overall decrease of the fast <span class="hlt">ice</span> season by 2.8 d/yr, which is significantly higher than previously reported <span class="hlt">trends</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28314231','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28314231"><span>Sea salt sodium record from Talos Dome (East Antarctica) as a potential proxy of the Antarctic past sea <span class="hlt">ice</span> <span class="hlt">extent</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Severi, M; Becagli, S; Caiazzo, L; Ciardini, V; Colizza, E; Giardi, F; Mezgec, K; Scarchilli, C; Stenni, B; Thomas, E R; Traversi, R; Udisti, R</p> <p>2017-06-01</p> <p>Antarctic sea <span class="hlt">ice</span> has shown an increasing <span class="hlt">trend</span> in recent decades, but with strong regional differences from one sector to another of the Southern Ocean. The Ross Sea and the Indian sectors have seen an increase in sea <span class="hlt">ice</span> during the satellite era (1979 onwards). Here we present a record of ssNa + flux in the Talos Dome region during a 25-year period spanning from 1979 to 2003, showing that this marker could be used as a potential proxy for reconstructing the sea <span class="hlt">ice</span> <span class="hlt">extent</span> in the Ross Sea and Western Pacific Ocean at least for recent decades. After finding a positive relationship between the maxima in sea <span class="hlt">ice</span> <span class="hlt">extent</span> for a 25-year period, we used this relationship in the TALDICE record in order to reconstruct the sea <span class="hlt">ice</span> conditions over the 20th century. Our tentative reconstruction highlighted a decline in the sea <span class="hlt">ice</span> <span class="hlt">extent</span> (SIE) starting in the 1950s and pointed out a higher variability of SIE starting from the 1960s and that the largest sea <span class="hlt">ice</span> <span class="hlt">extents</span> of the last century occurred during the 1990s. Copyright © 2017 Elsevier Ltd. All rights reserved.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC32B..02P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC32B..02P"><span>Contrasting <span class="hlt">Trends</span> in Arctic and Antarctic Sea <span class="hlt">Ice</span> Coverage Since the Late 1970s</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Parkinson, C. L.</p> <p>2016-12-01</p> <p>Satellite observations have allowed a near-continuous record of Arctic and Antarctic sea <span class="hlt">ice</span> coverage since late 1978. This record has revealed considerable interannual variability in both polar regions but also significant long-term <span class="hlt">trends</span>, with the Arctic losing, the Antarctic gaining, and the Earth as a whole losing sea <span class="hlt">ice</span> coverage. Over the period 1979-2015, the <span class="hlt">trend</span> in yearly average sea <span class="hlt">ice</span> <span class="hlt">extents</span> in the Arctic is -53,100 km2/yr (-4.3 %/decade) and in the Antarctic is 23,800 km2/yr (2.1 %/decade). For all 12 months, <span class="hlt">trends</span> are negative in the Arctic and positive in the Antarctic, with the highest magnitude monthly <span class="hlt">trend</span> being for September in the Arctic, at -85,300 km2/yr (-10.9 %/decade). The decreases in Arctic sea <span class="hlt">ice</span> <span class="hlt">extents</span> have been so dominant that not a single month since 1986 registered a new monthly record high, whereas 75 months registered new monthly record lows between 1987 and 2015 and several additional record lows were registered in 2016. The Antarctic sea <span class="hlt">ice</span> record highs and lows are also out of balance, in the opposite direction, although not in such dramatic fashion. Geographic details on the changing <span class="hlt">ice</span> covers, down to the level of individual pixels, can be seen by examining changes in the length of the sea <span class="hlt">ice</span> season. Results reveal (and quantify) shortening <span class="hlt">ice</span> seasons throughout the bulk of the Arctic marginal <span class="hlt">ice</span> zone, the main exception being within the Bering Sea, and lengthening sea <span class="hlt">ice</span> seasons through much of the Southern Ocean but shortening seasons in the Bellingshausen Sea, southern Amundsen Sea, and northwestern Weddell Sea. The decreasing Arctic sea <span class="hlt">ice</span> coverage was widely anticipated and fits well with a large array of environmental changes in the Arctic, whereas the increasing Antarctic sea <span class="hlt">ice</span> coverage was not widely anticipated and explaining it remains an area of active research by many scientists exploring a variety of potential explanations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1813508S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1813508S"><span>The Impact of Geothermal Heat on the Scandinavian <span class="hlt">Ice</span> Sheet's LGM <span class="hlt">Extent</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Szuman, Izabela; Ewertowski, Marek W.; Kalita, Jakub Z.</p> <p>2016-04-01</p> <p>The last Scandinavian <span class="hlt">ice</span> sheet attained its most southern <span class="hlt">extent</span> over Poland and Germany, protruding c. 200 km south of the main <span class="hlt">ice</span> sheet mass. There are number of factors that may control <span class="hlt">ice</span> sheet dynamics and <span class="hlt">extent</span>. One of the less recognised is geothermal heat, which is heat that is supplied to the base of the <span class="hlt">ice</span> sheet. A heat at the <span class="hlt">ice</span>/bed interface plays a crucial role in controlling <span class="hlt">ice</span> sheet stability, as well as impacting basal temperatures, melting, and <span class="hlt">ice</span> flow velocities. However, the influence of geothermal heat is still virtually neglected in reconstructions and modelling of paleo-<span class="hlt">ice</span> sheets behaviour. Only in a few papers is geothermal heat recalled though often in the context of past climatic conditions. Thus, the major question is if and how spatial differences in geothermal heat had influenced paleo-<span class="hlt">ice</span> sheet dynamics and in consequence their <span class="hlt">extent</span>. Here, we assumed that the configuration of the <span class="hlt">ice</span> sheet along its southern margin was moderately to strongly correlated with geothermal heat for Poland and non or negatively correlated for Germany.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy...50.4599S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy...50.4599S"><span>Tropically driven and externally forced patterns of Antarctic sea <span class="hlt">ice</span> change: reconciling observed and modeled <span class="hlt">trends</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schneider, David P.; Deser, Clara</p> <p>2018-06-01</p> <p>Recent work suggests that natural variability has played a significant role in the increase of Antarctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> during 1979-2013. The <span class="hlt">ice</span> <span class="hlt">extent</span> has responded strongly to atmospheric circulation changes, including a deepened Amundsen Sea Low (ASL), which in part has been driven by tropical variability. Nonetheless, this increase has occurred in the context of externally forced climate change, and it has been difficult to reconcile observed and modeled Antarctic sea <span class="hlt">ice</span> <span class="hlt">trends</span>. To understand observed-model disparities, this work defines the internally driven and radiatively forced patterns of Antarctic sea <span class="hlt">ice</span> change and exposes potential model biases using results from two sets of historical experiments of a coupled climate model compared with observations. One ensemble is constrained only by external factors such as greenhouse gases and stratospheric ozone, while the other explicitly accounts for the influence of tropical variability by specifying observed SST anomalies in the eastern tropical Pacific. The latter experiment reproduces the deepening of the ASL, which drives an increase in regional <span class="hlt">ice</span> <span class="hlt">extent</span> due to enhanced <span class="hlt">ice</span> motion and sea surface cooling. However, the overall sea <span class="hlt">ice</span> <span class="hlt">trend</span> in every ensemble member of both experiments is characterized by <span class="hlt">ice</span> loss and is dominated by the forced pattern, as given by the ensemble-mean of the first experiment. This pervasive <span class="hlt">ice</span> loss is associated with a strong warming of the ocean mixed layer, suggesting that the ocean model does not locally store or export anomalous heat efficiently enough to maintain a surface environment conducive to sea <span class="hlt">ice</span> expansion. The pervasive upper-ocean warming, not seen in observations, likely reflects ocean mean-state biases.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy..tmp..676S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy..tmp..676S"><span>Tropically driven and externally forced patterns of Antarctic sea <span class="hlt">ice</span> change: reconciling observed and modeled <span class="hlt">trends</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schneider, David P.; Deser, Clara</p> <p>2017-09-01</p> <p>Recent work suggests that natural variability has played a significant role in the increase of Antarctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> during 1979-2013. The <span class="hlt">ice</span> <span class="hlt">extent</span> has responded strongly to atmospheric circulation changes, including a deepened Amundsen Sea Low (ASL), which in part has been driven by tropical variability. Nonetheless, this increase has occurred in the context of externally forced climate change, and it has been difficult to reconcile observed and modeled Antarctic sea <span class="hlt">ice</span> <span class="hlt">trends</span>. To understand observed-model disparities, this work defines the internally driven and radiatively forced patterns of Antarctic sea <span class="hlt">ice</span> change and exposes potential model biases using results from two sets of historical experiments of a coupled climate model compared with observations. One ensemble is constrained only by external factors such as greenhouse gases and stratospheric ozone, while the other explicitly accounts for the influence of tropical variability by specifying observed SST anomalies in the eastern tropical Pacific. The latter experiment reproduces the deepening of the ASL, which drives an increase in regional <span class="hlt">ice</span> <span class="hlt">extent</span> due to enhanced <span class="hlt">ice</span> motion and sea surface cooling. However, the overall sea <span class="hlt">ice</span> <span class="hlt">trend</span> in every ensemble member of both experiments is characterized by <span class="hlt">ice</span> loss and is dominated by the forced pattern, as given by the ensemble-mean of the first experiment. This pervasive <span class="hlt">ice</span> loss is associated with a strong warming of the ocean mixed layer, suggesting that the ocean model does not locally store or export anomalous heat efficiently enough to maintain a surface environment conducive to sea <span class="hlt">ice</span> expansion. The pervasive upper-ocean warming, not seen in observations, likely reflects ocean mean-state biases.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.4898V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.4898V"><span>Reconstruction of past equilibrium line altitude using <span class="hlt">ice</span> <span class="hlt">extent</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Visnjevic, Vjeran; Herman, Frederic; Podladchikov, Yuri</p> <p>2017-04-01</p> <p>With the end of the Last Glacial Maximum (LGM), about 20 000 years ago, ended the most recent long-lasting cold phase in Earth's history. This last glacial advance left a strong observable imprint on the landscape, such as abandoned moraines, trimlines and other glacial geomorphic features. These features provide a valuable record of past continental climate. In particular, terminal moraines reflect the <span class="hlt">extent</span> of glaciers and <span class="hlt">ice</span>-caps, which itself reflects past temperature and precipitation conditions. Here we present an inverse approach, based on a Tikhonov regularization, we have recently developed to reconstruct the LGM mass balance from observed <span class="hlt">ice</span> <span class="hlt">extent</span> data. The <span class="hlt">ice</span> flow model is developed using the shallow <span class="hlt">ice</span> approximation and solved explicitly using Graphical Processing Units (GPU). The mass balance field, b, is the constrained variable defined by the <span class="hlt">ice</span> surface S, balance rate β and the spatially variable equilibrium line altitude field (ELA): b = min (β ṡ(S(x,y)- ELA (x,y)),c). (1) where c is a maximum accumulation rate. We show that such a mass balance, and thus the spatially variable ELA field, can be inferred from the observed past <span class="hlt">ice</span> <span class="hlt">extent</span> and <span class="hlt">ice</span> thickness at high resolution and very efficiently. The GPU implementation allows us solve one 1024x1024 grid points forward model run under 0.5s, which significantly reduces the time needed for our inverse method to converge. We start with synthetic test to demonstrate the method. We then apply the method to LGM <span class="hlt">ice</span> <span class="hlt">extents</span> of South Island of New Zealand, the Patagonian Andes, where we can see a clear influence of Westerlies on the ELA, and the European Alps. These examples show that the method is capable of constraining spatial variations in mass balance at the scale of a mountain range, and provide us with information on past continental climate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170007774&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsea','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170007774&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsea"><span>Skillful Spring Forecasts of September Arctic Sea <span class="hlt">Ice</span> <span class="hlt">Extent</span> Using Passive Microwave Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Petty, A. A.; Schroder, D.; Stroeve, J. C.; Markus, Thorsten; Miller, Jeffrey A.; Kurtz, Nathan Timothy; Feltham, D. L.; Flocco, D.</p> <p>2017-01-01</p> <p>In this study, we demonstrate skillful spring forecasts of detrended September Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> using passive microwave observations of sea <span class="hlt">ice</span> concentration (SIC) and melt onset (MO). We compare these to forecasts produced using data from a sophisticated melt pond model, and find similar to higher skill values, where the forecast skill is calculated relative to linear <span class="hlt">trend</span> persistence. The MO forecasts shows the highest skill in March-May, while the SIC forecasts produce the highest skill in June-August, especially when the forecasts are evaluated over recent years (since 2008). The high MO forecast skill in early spring appears to be driven primarily by the presence and timing of open water anomalies, while the high SIC forecast skill appears to be driven by both open water and surface melt processes. Spatial maps of detrended anomalies highlight the drivers of the different forecasts, and enable us to understand regions of predictive importance. Correctly capturing sea <span class="hlt">ice</span> state anomalies, along with changes in open water coverage appear to be key processes in skillfully forecasting summer Arctic sea <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016TCry...10.2721E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016TCry...10.2721E"><span>Estimating the <span class="hlt">extent</span> of Antarctic summer sea <span class="hlt">ice</span> during the Heroic Age of Antarctic Exploration</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Edinburgh, Tom; Day, Jonathan J.</p> <p>2016-11-01</p> <p>In stark contrast to the sharp decline in Arctic sea <span class="hlt">ice</span>, there has been a steady increase in <span class="hlt">ice</span> <span class="hlt">extent</span> around Antarctica during the last three decades, especially in the Weddell and Ross seas. In general, climate models do not to capture this <span class="hlt">trend</span> and a lack of information about sea <span class="hlt">ice</span> coverage in the pre-satellite period limits our ability to quantify the sensitivity of sea <span class="hlt">ice</span> to climate change and robustly validate climate models. However, evidence of the presence and nature of sea <span class="hlt">ice</span> was often recorded during early Antarctic exploration, though these sources have not previously been explored or exploited until now. We have analysed observations of the summer sea <span class="hlt">ice</span> edge from the ship logbooks of explorers such as Robert Falcon Scott, Ernest Shackleton and their contemporaries during the Heroic Age of Antarctic Exploration (1897-1917), and in this study we compare these to satellite observations from the period 1989-2014, offering insight into the <span class="hlt">ice</span> conditions of this period, from direct observations, for the first time. This comparison shows that the summer sea <span class="hlt">ice</span> edge was between 1.0 and 1.7° further north in the Weddell Sea during this period but that <span class="hlt">ice</span> conditions were surprisingly comparable to the present day in other sectors.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21D1155C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21D1155C"><span>Role of the Tropical Pacific in recent Antarctic Sea-<span class="hlt">Ice</span> <span class="hlt">Trends</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Codron, F.; Bardet, D.; Allouache, C.; Gastineau, G.; Friedman, A. R.; Douville, H.; Voldoire, A.</p> <p>2017-12-01</p> <p>The recent (up to 2016) <span class="hlt">trends</span> in Antarctic sea-<span class="hlt">ice</span> cover - a global increase masking a dipole between the Ross and Bellingshausen-Weddel seas - are still not well understood, and not reproduced by CMIP5 coupled climate models. We here explore the potential role of atmospheric circulation changes around the Amundsen Sea, themselves possibly forced by tropical SSTs, an explanation that has been recently advanced. As a first check on this hypothesis, we compare the atmospheric circulation <span class="hlt">trends</span> simulated by atmospheric GCMs coupled with an ocean or with imposed SSTs (AMIP experiment from CMIP5); the latter being in theory able to reproduce changes caused by natural SST variability. While coupled models simulate in aggregate <span class="hlt">trends</span> that project on the SAM structure, strongest in summer, the AMIP simulations add in the winter season a pronounced Amundsen Sea Low signature (and a PNA signature in the northern hemisphere) both consistent with a Niña-like <span class="hlt">trend</span> in the tropical Pacific. We then use a specific coupled GCM setup, in which surface wind anomalies over the tropical Pacific are strongly nudged towards the observed ones, including their interannual variability, but the model is free to evolve elsewhere. The two GCMs used then simulate a deepening <span class="hlt">trend</span> in the Amundsen-Sea Low in winter, and are able to reproduce a dipole in sea-<span class="hlt">ice</span> cover. Further analysis shows that the sea-<span class="hlt">ice</span> dipole is partially forced by surface heat flux anomalies in early winter - the <span class="hlt">extent</span> varying with the region and GCM used. The turbulent heat fluxes then act to damp the anomalies in late winter, which may however be maintained by <span class="hlt">ice</span>-albedo feedbacks.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140005670','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140005670"><span>Sea <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Perovich, D.; Gerland, S.; Hendricks, S.; Meier, Walter N.; Nicolaus, M.; Richter-Menge, J.; Tschudi, M.</p> <p>2013-01-01</p> <p>During 2013, Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> remained well below normal, but the September 2013 minimum <span class="hlt">extent</span> was substantially higher than the record-breaking minimum in 2012. Nonetheless, the minimum was still much lower than normal and the long-term <span class="hlt">trend</span> Arctic September <span class="hlt">extent</span> is -13.7 per decade relative to the 1981-2010 average. The less extreme conditions this year compared to 2012 were due to cooler temperatures and wind patterns that favored retention of <span class="hlt">ice</span> through the summer. Sea <span class="hlt">ice</span> thickness and volume remained near record-low levels, though indications are of slightly thicker <span class="hlt">ice</span> compared to the record low of 2012.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeoRL..44.9761D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeoRL..44.9761D"><span>Modulation of the Seasonal Cycle of Antarctic Sea <span class="hlt">Ice</span> <span class="hlt">Extent</span> Related to the Southern Annular Mode</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Doddridge, Edward W.; Marshall, John</p> <p>2017-10-01</p> <p>Through analysis of remotely sensed sea surface temperature (SST) and sea <span class="hlt">ice</span> concentration data, we investigate the impact of winds related to the Southern Annular Mode (SAM) on sea <span class="hlt">ice</span> <span class="hlt">extent</span> around Antarctica. We show that positive SAM anomalies in the austral summer are associated with anomalously cold SSTs that persist and lead to anomalous <span class="hlt">ice</span> growth in the following autumn, while negative SAM anomalies precede warm SSTs and a reduction in sea <span class="hlt">ice</span> <span class="hlt">extent</span> during autumn. The largest effect occurs in April, when a unit change in the detrended summertime SAM is followed by a 1.8±0.6 ×105 km2 change in detrended sea <span class="hlt">ice</span> <span class="hlt">extent</span>. We find no evidence that sea <span class="hlt">ice</span> <span class="hlt">extent</span> anomalies related to the summertime SAM affect the wintertime sea <span class="hlt">ice</span> <span class="hlt">extent</span> maximum. Our analysis shows that the wind anomalies related to the negative SAM during the 2016/2017 austral summer contributed to the record minimum Antarctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> observed in March 2017.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li class="active"><span>2</span></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_2 --> <div id="page_3" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li class="active"><span>3</span></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="41"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1342069','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1342069"><span>Moving beyond the total sea <span class="hlt">ice</span> <span class="hlt">extent</span> in gauging model biases</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Ivanova, Detelina P.; Gleckler, Peter J.; Taylor, Karl E.</p> <p></p> <p>Here, reproducing characteristics of observed sea <span class="hlt">ice</span> <span class="hlt">extent</span> remains an important climate modeling challenge. This study describes several approaches to improve how model biases in total sea <span class="hlt">ice</span> distribution are quantified, and applies them to historically forced simulations contributed to phase 5 of the Coupled Model Intercomparison Project (CMIP5). The quantity of hemispheric total sea <span class="hlt">ice</span> area, or some measure of its equatorward <span class="hlt">extent</span>, is often used to evaluate model performance. A new approach is introduced that investigates additional details about the structure of model errors, with an aim to reduce the potential impact of compensating errors when gauging differencesmore » between simulated and observed sea <span class="hlt">ice</span>. Using multiple observational datasets, several new methods are applied to evaluate the climatological spatial distribution and the annual cycle of sea <span class="hlt">ice</span> cover in 41 CMIP5 models. It is shown that in some models, error compensation can be substantial, for example resulting from too much sea <span class="hlt">ice</span> in one region and too little in another. Error compensation tends to be larger in models that agree more closely with the observed total sea <span class="hlt">ice</span> area, which may result from model tuning. The results herein suggest that consideration of only the total hemispheric sea <span class="hlt">ice</span> area or <span class="hlt">extent</span> can be misleading when quantitatively comparing how well models agree with observations. Further work is needed to fully develop robust methods to holistically evaluate the ability of models to capture the finescale structure of sea <span class="hlt">ice</span> characteristics; however, the “sector scale” metric used here aids in reducing the impact of compensating errors in hemispheric integrals.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1342069-moving-beyond-total-sea-ice-extent-gauging-model-biases','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1342069-moving-beyond-total-sea-ice-extent-gauging-model-biases"><span>Moving beyond the total sea <span class="hlt">ice</span> <span class="hlt">extent</span> in gauging model biases</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Ivanova, Detelina P.; Gleckler, Peter J.; Taylor, Karl E.; ...</p> <p>2016-11-29</p> <p>Here, reproducing characteristics of observed sea <span class="hlt">ice</span> <span class="hlt">extent</span> remains an important climate modeling challenge. This study describes several approaches to improve how model biases in total sea <span class="hlt">ice</span> distribution are quantified, and applies them to historically forced simulations contributed to phase 5 of the Coupled Model Intercomparison Project (CMIP5). The quantity of hemispheric total sea <span class="hlt">ice</span> area, or some measure of its equatorward <span class="hlt">extent</span>, is often used to evaluate model performance. A new approach is introduced that investigates additional details about the structure of model errors, with an aim to reduce the potential impact of compensating errors when gauging differencesmore » between simulated and observed sea <span class="hlt">ice</span>. Using multiple observational datasets, several new methods are applied to evaluate the climatological spatial distribution and the annual cycle of sea <span class="hlt">ice</span> cover in 41 CMIP5 models. It is shown that in some models, error compensation can be substantial, for example resulting from too much sea <span class="hlt">ice</span> in one region and too little in another. Error compensation tends to be larger in models that agree more closely with the observed total sea <span class="hlt">ice</span> area, which may result from model tuning. The results herein suggest that consideration of only the total hemispheric sea <span class="hlt">ice</span> area or <span class="hlt">extent</span> can be misleading when quantitatively comparing how well models agree with observations. Further work is needed to fully develop robust methods to holistically evaluate the ability of models to capture the finescale structure of sea <span class="hlt">ice</span> characteristics; however, the “sector scale” metric used here aids in reducing the impact of compensating errors in hemispheric integrals.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70024935','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70024935"><span>Historical <span class="hlt">trend</span> in river <span class="hlt">ice</span> thickness and coherence in hydroclimatological <span class="hlt">trends</span> in Maine</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Huntington, T.G.; Hodgkins, G.A.; Dudley, R.W.</p> <p>2003-01-01</p> <p>We analyzed long-term records of <span class="hlt">ice</span> thickness on the Piscataquis River in central Maine and air temperature in Maine to determine whether there were temporal <span class="hlt">trends</span> that were associated with climate warming. The <span class="hlt">trend</span> in <span class="hlt">ice</span> thickness was compared and correlated with regional time series of winter air temperature, heating degree days (HDD), date of river <span class="hlt">ice</span>-out, seasonal center-of-volume date (SCVD) (date on which half of the stream runoff volume during the period 1 Jan. to 31 May has occurred), water temperature, and lake <span class="hlt">ice</span>-out date. All of these variables except lake <span class="hlt">ice</span>-out date showed significant temporal <span class="hlt">trends</span> during the 20th century. Average <span class="hlt">ice</span> thickness around 28 February decreased by about 23 cm from 1912 to 2001. Over the period 1900 to 1999, winter air temperature increased by 1.7??C and HDD decreased by about 7.5%. Final <span class="hlt">ice</span>-out date on the Piscataquis River occurred earlier (advanced), by 0.21 days yr-1 over the period 1931 to 2002, and the SCVD advanced by 0.11 days yr-1 over the period 1903 to 2001. <span class="hlt">Ice</span> thickness was significantly correlated (P-value < 0.01) with winter air temperature, HDD, river <span class="hlt">ice</span>-out, and SCVD. These systematic temporal <span class="hlt">trends</span> in multiple hydrologic indicator variables indicate a coherent response to climate forcing.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.9330N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.9330N"><span>Recalculated Areas for Maximum <span class="hlt">Ice</span> <span class="hlt">Extents</span> of the Baltic Sea During Winters 1971-2008</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Niskanen, T.; Vainio, J.; Eriksson, P.; Heiler, I.</p> <p>2009-04-01</p> <p>Publication of operational <span class="hlt">ice</span> charts in Finland was started from the Baltic Sea in a year 1915. Until year 1993 all <span class="hlt">ice</span> charts were hand drawn paper copies but in the year 1993 <span class="hlt">ice</span> charting software <span class="hlt">Ice</span>Map was introduced. Since then all <span class="hlt">ice</span> charts were produced digitally. Since the year 1996 <span class="hlt">Ice</span>Map has had an option that user can calculate areas of single <span class="hlt">ice</span> area polygons in the chart. Using this option the area of the maximum <span class="hlt">ice</span> <span class="hlt">extent</span> can be easily solved fully automatically. Before this option was introduced (and in full operation) all maximum <span class="hlt">extent</span> areas were calculated manually by a planimeter. During recent years it has become clear that some areas calculated before 1996 don't give the same result as <span class="hlt">Ice</span>Map. Differences can come from for example inaccuracy of old coastlines, map projections, the calibration of the planimeter or interpretation of old <span class="hlt">ice</span> area symbols. Old <span class="hlt">ice</span> charts since winter 1970-71 have now been scanned, rectified and re-drawn. New maximum <span class="hlt">ice</span> <span class="hlt">extent</span> areas for Baltic Sea have now been re-calculated. By these new technological tools it can be concluded that in some cases clear differences can be found.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010100393','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010100393"><span>Variability of Antarctic Sea <span class="hlt">Ice</span> 1979-1998</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zwally, H. Jay; Comiso, Josefino C.; Parkinson, Claire L.; Cavalieri, Donald J.; Gloersen, Per; Koblinsky, Chester J. (Technical Monitor)</p> <p>2001-01-01</p> <p>The principal characteristics of the variability of Antarctic sea <span class="hlt">ice</span> cover as previously described from satellite passive-microwave observations are also evident in a systematically-calibrated and analyzed data set for 20.2 years (1979-1998). The total Antarctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> (concentration > 15 %) increased by 13,440 +/- 4180 sq km/year (+1.18 +/- 0.37%/decade). The area of sea <span class="hlt">ice</span> within the <span class="hlt">extent</span> boundary increased by 16,960 +/- 3,840 sq km/year (+1.96 +/- 0.44%/decade). Regionally, the <span class="hlt">trends</span> in <span class="hlt">extent</span> are positive in the Weddell Sea (1.5 +/- 0.9%/decade), Pacific Ocean (2.4 +/- 1.4%/decade), and Ross (6.9 +/- 1.1 %/decade) sectors, slightly negative in the Indian Ocean (-1.5 +/- 1.8%/decade, and strongly negative in the Bellingshausen-Amundsen Seas sector (-9.5 +/- 1.5%/decade). For the entire <span class="hlt">ice</span> pack, small <span class="hlt">ice</span> increases occur in all seasons with the largest increase during autumn. On a regional basis, the <span class="hlt">trends</span> differ season to season. During summer and fall, the <span class="hlt">trends</span> are positive or near zero in all sectors except the Bellingshausen-Amundsen Seas sector. During winter and spring, the <span class="hlt">trends</span> are negative or near zero in all sectors except the Ross Sea, which has positive <span class="hlt">trends</span> in all seasons. Components of interannual variability with periods of about 3 to 5 years are regionally large, but tend to counterbalance each other in the total <span class="hlt">ice</span> pack. The interannual variability of the annual mean sea-<span class="hlt">ice</span> <span class="hlt">extent</span> is only 1.6% overall, compared to 5% to 9% in each of five regional sectors. Analysis of the relation between regional sea <span class="hlt">ice</span> <span class="hlt">extents</span> and spatially-averaged surface temperatures over the <span class="hlt">ice</span> pack gives an overall sensitivity between winter <span class="hlt">ice</span> cover and temperature of -0.7% change in sea <span class="hlt">ice</span> <span class="hlt">extent</span> per K. For summer, some regional <span class="hlt">ice</span> <span class="hlt">extents</span> vary positively with temperature and others negatively. The observed increase in Antarctic sea <span class="hlt">ice</span> cover is counter to the observed decreases in the Arctic. It is also qualitatively consistent with the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC12A..01S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC12A..01S"><span>Towards Improving Sea <span class="hlt">Ice</span> Predictabiity: Evaluating Climate Models Against Satellite Sea <span class="hlt">Ice</span> Observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stroeve, J. C.</p> <p>2014-12-01</p> <p>The last four decades have seen a remarkable decline in the spatial <span class="hlt">extent</span> of the Arctic sea <span class="hlt">ice</span> cover, presenting both challenges and opportunities to Arctic residents, government agencies and industry. After the record low <span class="hlt">extent</span> in September 2007 effort has increased to improve seasonal, decadal-scale and longer-term predictions of the sea <span class="hlt">ice</span> cover. Coupled global climate models (GCMs) consistently project that if greenhouse gas concentrations continue to rise, the eventual outcome will be a complete loss of the multiyear <span class="hlt">ice</span> cover. However, confidence in these projections depends o HoHoweon the models ability to reproduce features of the present-day climate. Comparison between models participating in the World Climate Research Programme Coupled Model Intercomparison Project Phase 5 (CMIP5) and observations of sea <span class="hlt">ice</span> <span class="hlt">extent</span> and thickness show that (1) historical <span class="hlt">trends</span> from 85% of the model ensemble members remain smaller than observed, and (2) spatial patterns of sea <span class="hlt">ice</span> thickness are poorly represented in most models. Part of the explanation lies with a failure of models to represent details of the mean atmospheric circulation pattern that governs the transport and spatial distribution of sea <span class="hlt">ice</span>. These results raise concerns regarding the ability of CMIP5 models to realistically represent the processes driving the decline of Arctic sea <span class="hlt">ice</span> and to project the timing of when a seasonally <span class="hlt">ice</span>-free Arctic may be realized. On shorter time-scales, seasonal sea <span class="hlt">ice</span> prediction has been challenged to predict the sea <span class="hlt">ice</span> <span class="hlt">extent</span> from Arctic conditions a few months to a year in advance. Efforts such as the Sea <span class="hlt">Ice</span> Outlook (SIO) project, originally organized through the Study of Environmental Change (SEARCH) and now managed by the Sea <span class="hlt">Ice</span> Prediction Network project (SIPN) synthesize predictions of the September sea <span class="hlt">ice</span> <span class="hlt">extent</span> based on a variety of approaches, including heuristic, statistical and dynamical modeling. Analysis of SIO contributions reveals that when the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC53E0931P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC53E0931P"><span>Dynamic and thermodynamic impacts of the winter Arctic Oscillation on summer sea <span class="hlt">ice</span> <span class="hlt">extent</span>.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Park, H. S.; Stewart, A.</p> <p>2017-12-01</p> <p>Arctic summer sea <span class="hlt">ice</span> <span class="hlt">extent</span> exhibits substantial interannual variability, as is highlighted by the remarkable recovery in sea <span class="hlt">ice</span> <span class="hlt">extent</span> in 2013 following the record minimum in the summer of 2012. Here, we explore the mechanism via which Arctic Oscillation (AO)-induced <span class="hlt">ice</span> thickness changes impact summer sea <span class="hlt">ice</span>, using observations and reanalysis data. A positive AO weakens the basin-scale anticyclonic sea <span class="hlt">ice</span> drift and decreases the winter <span class="hlt">ice</span> thickness by 15cm and 10cm in the Eurasian and the Pacific sectors of the Arctic respectively. Three reanalysis datasets show that the (upward) surface heat fluxes are reduced over wide areas of the Arctic, suppressing the <span class="hlt">ice</span> growth during the positive AO winters. The winter dynamic and thermodynamic thinning preconditions the <span class="hlt">ice</span> for enhanced radiative forcing via the <span class="hlt">ice</span>-albedo feedback in late spring-summer, leading to an additional 8-10 cm of thinning over the Pacific sector of the Arctic. Because of these winter AO-induced dynamic and thermodynamics effects, the winter AO explains about 22% (r = -0.48) of the interannual variance of September sea <span class="hlt">ice</span> <span class="hlt">extent</span> from year 1980 to 2015.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C54A..04T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C54A..04T"><span><span class="hlt">Trends</span> in Arctic Sea <span class="hlt">Ice</span> Volume 2010-2013 from CryoSat-2</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tilling, R.; Ridout, A.; Wingham, D.; Shepherd, A.; Haas, C.; Farrell, S. L.; Schweiger, A. J.; Zhang, J.; Giles, K.; Laxon, S.</p> <p>2013-12-01</p> <p>Satellite records show a decline in Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> over the past three decades with a record minimum in September 2012, and results from the Pan-Arctic <span class="hlt">Ice</span>-Ocean Modelling and Assimilation System (PIOMAS) suggest that this has been accompanied by a reduction in volume. We use three years of measurements recorded by the European Space Agency CryoSat-2 (CS-2) mission, validated with in situ data, to generate estimates of seasonal variations and inter-annual <span class="hlt">trends</span> in Arctic sea <span class="hlt">ice</span> volume between 2010 and 2013. The CS-2 estimates of sea <span class="hlt">ice</span> thickness agree with in situ estimates derived from upward looking sonar measurements of <span class="hlt">ice</span> draught and airborne measurements of <span class="hlt">ice</span> thickness and freeboard to within 0.1 metres. Prior to the record minimum in summer 2012, autumn and winter Arctic sea <span class="hlt">ice</span> volume had fallen by ~1300 km3 relative to the previous year. Using the full 3-year period of CS-2 observations, we estimate that winter Arctic sea <span class="hlt">ice</span> volume has decreased by ~700 km3/yr since 2010, approximately twice the average rate since 1980 as predicted by the PIOMAS.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70040729','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70040729"><span>The impact of lower sea-<span class="hlt">ice</span> <span class="hlt">extent</span> on Arctic greenhouse-gas exchange</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Parmentier, Frans-Jan W.; Christensen, Torben R.; Sørensen, Lise Lotte; Rysgaard, Søren; McGuire, A. David; Miller, Paul A.; Walker, Donald A.</p> <p>2013-01-01</p> <p>In September 2012, Arctic sea-<span class="hlt">ice</span> <span class="hlt">extent</span> plummeted to a new record low: two times lower than the 1979–2000 average. Often, record lows in sea-<span class="hlt">ice</span> cover are hailed as an example of climate change impacts in the Arctic. Less apparent, however, are the implications of reduced sea-<span class="hlt">ice</span> cover in the Arctic Ocean for marine–atmosphere CO2 exchange. Sea-<span class="hlt">ice</span> decline has been connected to increasing air temperatures at high latitudes. Temperature is a key controlling factor in the terrestrial exchange of CO2 and methane, and therefore the greenhouse-gas balance of the Arctic. Despite the large potential for feedbacks, many studies do not connect the diminishing sea-<span class="hlt">ice</span> <span class="hlt">extent</span> with changes in the interaction of the marine and terrestrial Arctic with the atmosphere. In this Review, we assess how current understanding of the Arctic Ocean and high-latitude ecosystems can be used to predict the impact of a lower sea-<span class="hlt">ice</span> cover on Arctic greenhouse-gas exchange.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040035786&hterms=ships+location&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dships%2Blocation','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040035786&hterms=ships+location&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dships%2Blocation"><span>Studies of the Antarctic Sea <span class="hlt">Ice</span> Edges and <span class="hlt">Ice</span> <span class="hlt">Extents</span> from Satellite and Ship Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Worby, Anthony P.; Comiso, Josefino C.</p> <p>2003-01-01</p> <p>Passive-microwave derived <span class="hlt">ice</span> edge locations in Antarctica are assessed against other satellite data as well as in situ observations of <span class="hlt">ice</span> edge location made between 1989 and 2000. The passive microwave data generally agree with satellite and ship data but the <span class="hlt">ice</span> concentration at the observed <span class="hlt">ice</span> edge varies greatly with averages of 14% for the TEAM algorithm and 19% for the Bootstrap algorithm. The comparisons of passive microwave with the field data show that in the <span class="hlt">ice</span> growth season (March - October) the agreement is extremely good, with r(sup 2) values of 0.9967 and 0.9797 for the Bootstrap and TEAM algorithms respectively. In the melt season however (November - February) the passive microwave <span class="hlt">ice</span> edge is typically 1-2 degrees south of the observations due to the low concentration and saturated nature of the <span class="hlt">ice</span>. Sensitivity studies show that these results can have significant impact on <span class="hlt">trend</span> and mass balance studies of the sea <span class="hlt">ice</span> cover in the Southern Ocean.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19820036704&hterms=Parkinsons+circulation&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DParkinsons%2Bcirculation','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19820036704&hterms=Parkinsons+circulation&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DParkinsons%2Bcirculation"><span>Large-scale variations in observed Antarctic Sea <span class="hlt">ice</span> <span class="hlt">extent</span> and associated atmospheric circulation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cavalieri, D. J.; Parkinson, C. L.</p> <p>1981-01-01</p> <p>The 1974 Antarctic large scale sea <span class="hlt">ice</span> <span class="hlt">extent</span> is studied from data from Nimbus 2 and 5 and temperature and sea level pressure fields from the Australian Meteorological Data Set. Electrically Scanning Microwave Radiometer data were three-day averaged and compared with 1000 mbar atmospheric pressure and sea level pressure data, also in three-day averages. Each three-day period was subjected to a Fourier analysis and included the mean latitude of the <span class="hlt">ice</span> <span class="hlt">extent</span> and the phases and percent variances in terms of the first six Fourier harmonics. Centers of low pressure were found to be generally east of regions which displayed rapid <span class="hlt">ice</span> growth, and winds acted to extend the <span class="hlt">ice</span> equatorward. An atmospheric response was also noted as caused by the changing <span class="hlt">ice</span> cover.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.C14A..04H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.C14A..04H"><span>Use and Limitations of a Climate-Quality Data Record to Study Temperature <span class="hlt">Trends</span> on the Greenland <span class="hlt">Ice</span> Sheet</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hall, D. K.; Comiso, J. C.; Shuman, C. A.; Koenig, L.; DiGirolamo, N. E.</p> <p>2011-12-01</p> <p>Enhanced melting of the Greenland <span class="hlt">Ice</span> Sheet has been documented in recent literature along with surface-temperature increases measured using infrared satellite data since 1981. Using a recently-developed climate-quality data record, 11- and 12-year <span class="hlt">trends</span> in the clear-sky <span class="hlt">ice</span>-surface temperature (IST) of the Greenland <span class="hlt">Ice</span> Sheet have been studied using the Moderate-Resolution Imaging Spectroradiometer (MODIS) IST product. Daily and monthly MODIS ISTs of the Greenland <span class="hlt">Ice</span> Sheet beginning on 1 March 2000 and continuing through 31 December 2010 are now available at 6.25-km spatial resolution on a polar stereographic grid as described in Hall et al. (submitted). This record will be elevated in status to a climate-data record (CDR) when more years of data become available either from the MODIS on the Terra or Aqua satellites, or from the Visible Infrared Imager Radiometer Suite (VIIRS) to be launched in October 2011. Maps showing the maximum <span class="hlt">extent</span> of melt for the entire <span class="hlt">ice</span> sheet and for the six major drainage basins have been developed from the MODIS IST dataset. Twelve-year <span class="hlt">trends</span> in the <span class="hlt">extent</span> of melt and duration of the melt season on the <span class="hlt">ice</span> sheet vary in different drainage basins with some basins melting progressively earlier over the course of the study period. Some (but not all) of the basins also show a progressively-longer duration of melt. Twelve-year <span class="hlt">trends</span> in IST are compared with in-situ data, and climate data from the Modern Era Retrospective-Analysis for Research and Applications (MERRA) Reanalysis. Hall, D.K., J.C. Comiso, N.E. DiGirolamo, C.A. Shuman, J. Key and L.S. Koenig, submitted for journal publication: A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland <span class="hlt">Ice</span> Sheet.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFMSA33B..07L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFMSA33B..07L"><span>Stratospheric effects on <span class="hlt">trends</span> of mesospheric <span class="hlt">ice</span> clouds (Invited)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Luebken, F.; Baumgarten, G.; Berger, U.</p> <p>2009-12-01</p> <p><span class="hlt">Ice</span> layers in the summer mesosphere at middle and polar latitudes appear as `noctilucent clouds' (NLC) and `polar mesosphere clouds'(PMC) when observed by optical methods from the ground or from satellites, respectively. A newly developed model of the atmosphere called LIMA (Leibniz Institute Middle Atmosphere Model) nicely reproduces the mean conditions of the summer mesopause region and is used to study the <span class="hlt">ice</span> layer morphology (LIMA/<span class="hlt">ice</span>). LIMA nudges to ECMWF data in the troposphere and lower stratosphere which influences the background conditions in the mesosphere and <span class="hlt">ice</span> cloud morphology. Since <span class="hlt">ice</span> layer formation is very sensitive to the thermal structure of the mesopause region the morphology of NLC and PMC is frequently discussed in terms of long term variations. Model runs of LIMA/<span class="hlt">ice</span> are now available for 1961 until 2008. A strong correlation between temperatures and PMC altitudes is observed. Applied to historical measurements this gives negligible temperature <span class="hlt">trends</span> at PMC altitudes (approximately 0.01-0.02 K/y). Trace gas concentrations are kept constant in LIMA except for water vapor which is modified by variable solar radiation. Still, long term <span class="hlt">trends</span> in temperatures and <span class="hlt">ice</span> layer parameters are observed, consistent with observations. We present results regarding inter-annual variability of upper mesosphere temperatures, water vapor, and <span class="hlt">ice</span> clouds, and also long term variations. We compare our model results with satellite borne and lidar observations including some record high NLC parameters measured in the summer season of 2009. The latitudinal dependence of <span class="hlt">trends</span> and <span class="hlt">ice</span> layer parameters is discussed, including a NH/SH comparison. We will present an explanation of the <span class="hlt">trends</span> in the background atmosphere and <span class="hlt">ice</span> layer parameters.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C33A0663K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C33A0663K"><span>Evidence for smaller <span class="hlt">extents</span> of the northwestern Greenland <span class="hlt">Ice</span> Sheet and North <span class="hlt">Ice</span> Cap during the Holocene</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kelly, M. A.; Osterberg, E. C.; Axford, Y.; Bigl, M.; Birkel, S. D.; Corbett, L. B.; Roy, E. P.; Thompson, J. T.; Whitecloud, S.</p> <p>2013-12-01</p> <p>The Greenland <span class="hlt">Ice</span> Sheet (GrIS) and local glaciers on Greenland are responding dynamically to warming temperatures with widespread retreat. GRACE satellite data (e.g., Kahn et al., 2010) and the Petermann Glacier calving events document the recent expansion of <span class="hlt">ice</span> loss into northwestern Greenland. To improve the ability to estimate future <span class="hlt">ice</span> loss in a warming climate, we are developing records of the response of the northwestern Greenlandic cryosphere to Holocene climatic conditions, with a focus on past warm periods. Our ongoing research includes analyses of glacial geology, sub-fossil vegetation, lake sediment cores, chironomid assemblages and <span class="hlt">ice</span> cores combined with glaciological modeling. To constrain past <span class="hlt">ice</span> <span class="hlt">extents</span> that were as small as, or smaller than, at present, we recovered sub-fossil vegetation exposed at the receding margins of the GrIS and North <span class="hlt">Ice</span> Cap (NIC) in the Nunatarssuaq region (~76.7°N, 67.4°W) and of the GrIS near Thule (~76.5°N, 68.7°W). We present vegetation types and radiocarbon ages of 30 plant samples collected in August 2012. In the Nunatarssuaq region, five ages of in situ (rooted) vegetation including Polytrichum moss, Saxifraga nathorstii and grasses located <5 m outboard of the GrIS margin are ~120-200 cal yr BP (range of medians of the 2-sigma calibrated age ranges). Nine ages of in situ Polytrichum, Saxifraga oppositafolia and grasses from ~1-5 m inboard of the NIC margin (excavated from beneath <span class="hlt">ice</span>) range from ~50 to 310 cal yr BP. The growth of these plants occurred when the GrIS and NIC were at least as small as at present and their ages suggest that <span class="hlt">ice</span> advances occurred in the last 50-120 yrs. In addition to the in situ samples, we collected plants from well-preserved ground material exposed along shear planes in the GrIS margins. In Nunatarssuaq, two Polytrichum mosses rooted in ground material and exposed along a shear plane in the GrIS margin date to 4680 and 4730 cal yr BP. Near Thule, three ages of Salix arctica</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GeoRL..45.4114P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GeoRL..45.4114P"><span>Bedrock Erosion Surfaces Record Former East Antarctic <span class="hlt">Ice</span> Sheet <span class="hlt">Extent</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Paxman, Guy J. G.; Jamieson, Stewart S. R.; Ferraccioli, Fausto; Bentley, Michael J.; Ross, Neil; Armadillo, Egidio; Gasson, Edward G. W.; Leitchenkov, German; DeConto, Robert M.</p> <p>2018-05-01</p> <p>East Antarctica hosts large subglacial basins into which the East Antarctic <span class="hlt">Ice</span> Sheet (EAIS) likely retreated during past warmer climates. However, the <span class="hlt">extent</span> of retreat remains poorly constrained, making quantifying past and predicted future contributions to global sea level rise from these marine basins challenging. Geomorphological analysis and flexural modeling within the Wilkes Subglacial Basin are used to reconstruct the <span class="hlt">ice</span> margin during warm intervals of the Oligocene-Miocene. Flat-lying bedrock plateaus are indicative of an <span class="hlt">ice</span> sheet margin positioned >400-500 km inland of the modern grounding zone for extended periods of the Oligocene-Miocene, equivalent to a 2-m rise in global sea level. Our findings imply that if major EAIS retreat occurs in the future, isostatic rebound will enable the plateau surfaces to act as seeding points for extensive <span class="hlt">ice</span> rises, thus limiting extensive <span class="hlt">ice</span> margin retreat of the scale seen during the early EAIS.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010037608','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010037608"><span><span class="hlt">Trends</span> in the Length of the Southern Ocean Sea <span class="hlt">Ice</span> Season: 1979-1999</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.; Zukor, Dorothy J. (Technical Monitor)</p> <p>2001-01-01</p> <p>Satellite data can be used to observe the sea <span class="hlt">ice</span> distribution around the continent of Antarctica on a daily basis and hence to determine how many days a year have sea <span class="hlt">ice</span> at each location. This has been done for each of the 21 years 1979-1999. Mapping the <span class="hlt">trends</span> in these data over the 21-year period reveals a detailed pattern of changes in the length of the sea <span class="hlt">ice</span> season around Antarctica. Most of the Ross Sea <span class="hlt">ice</span> cover has undergone a lengthening of the sea <span class="hlt">ice</span> season, whereas most of the Amundsen Sea <span class="hlt">ice</span> cover and almost the entire Bellingshausen Sea <span class="hlt">ice</span> cover have undergone a shortening of the sea <span class="hlt">ice</span> season. Results around the rest of the continent, including in the Weddell Sea, are more mixed, but overall, more of the Southern Ocean experienced a lengthening of the sea <span class="hlt">ice</span> season than a shortening. For instance, the area experiencing a lengthening of the sea <span class="hlt">ice</span> season by at least 1 day per year is 5.8 x 10(exp 6) sq km, whereas the area experiencing a shortening of the sea <span class="hlt">ice</span> season by at least 1 day per year is less than half that, at 2.8 x 10(exp 6) sq km. This contrasts sharply with what is happened over the same period in the Arctic, where, overall, there has been some depletion of the <span class="hlt">ice</span> cover, including shortened sea <span class="hlt">ice</span> seasons and decreased <span class="hlt">ice</span> <span class="hlt">extents</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.C41A0425S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.C41A0425S"><span>Precipitation Impacts of a Shrinking Arctic Sea <span class="hlt">Ice</span> Cover</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stroeve, J. C.; Frei, A.; Gong, G.; Ghatak, D.; Robinson, D. A.; Kindig, D.</p> <p>2009-12-01</p> <p>Since the beginning of the modern satellite record in October 1978, the <span class="hlt">extent</span> of Arctic sea <span class="hlt">ice</span> has declined in all months, with the strongest downward <span class="hlt">trend</span> at the end of the melt season in September. Recently the September <span class="hlt">trends</span> have accelerated. Through 2001, the <span class="hlt">extent</span> of September sea <span class="hlt">ice</span> was decreasing at a rate of -7 per cent per decade. By 2006, the rate of decrease had risen to -8.9 per cent per decade. In September 2007, Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> fell to its lowest level recorded, 23 per cent below the previous record set in 2005, boosting the downward <span class="hlt">trend</span> to -10.7 per cent per decade. <span class="hlt">Ice</span> <span class="hlt">extent</span> in September 2008 was the second lowest in the satellite record. Including 2008, the <span class="hlt">trend</span> in September sea <span class="hlt">ice</span> <span class="hlt">extent</span> stands at -11.8 percent per decade. Compared to the 1970s, September <span class="hlt">ice</span> <span class="hlt">extent</span> has retreated by 40 per cent. Summer 2009 looks to repeat the anomalously low <span class="hlt">ice</span> conditions that characterized the last couple of years. Scientists have long expected that a shrinking Arctic sea <span class="hlt">ice</span> cover will lead to strong warming of the overlying atmosphere, and as a result, affect atmospheric circulation and precipitation patterns. Recent results show clear evidence of Arctic warming linked to declining <span class="hlt">ice</span> <span class="hlt">extent</span>, yet observational evidence for responses of atmospheric circulation and precipitation patterns is just beginning to emerge. Rising air temperatures should lead to an increase in the moisture holding capacity of the atmosphere, with the potential to impact autumn precipitation. Although climate models predict a hemispheric wide decrease in snow cover as atmospheric concentrations of GHGs increase, increased precipitation, particular in autumn and winter may result as the Arctic transitions towards a seasonally <span class="hlt">ice</span> free state. In this study we use atmospheric reanalysis data and a cyclone tracking algorithm to investigate the influence of recent extreme <span class="hlt">ice</span> loss years on precipitation patterns in the Arctic and the Northern Hemisphere. Results show</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20070034825','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20070034825"><span><span class="hlt">Trends</span> in the Sea <span class="hlt">Ice</span> Cover Using Enhanced and Compatible AMSR-E, SSM/I and SMMR Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Josefino C.; Nishio, Fumihiko</p> <p>2007-01-01</p> <p>Arguably, the most remarkable manifestation of change in the polar regions is the rapid decline (of about -10 %/decade) in the Arctic perennial <span class="hlt">ice</span> cover. Changes in the global sea <span class="hlt">ice</span> cover, however, are more modest, being slightly positive in the Southern Hemisphere and slightly negative in the Northern Hemisphere, the significance of which has not been adequately assessed because of unknown errors in the satellite historical data. We take advantage of the recent and more accurate AMSR-E data to evaluate the true seasonal and interannual variability of the sea <span class="hlt">ice</span> cover, assess the accuracy of historical data, and determine the real <span class="hlt">trend</span>. Consistently derived <span class="hlt">ice</span> concentrations from AMSR-E, SSM/I, and SMMR data were analyzed and a slight bias is observed between AMSR-E and SSM/I data mainly because of differences in resolution. Analysis of the combine SMMR, SSM/I and AMSR-E data set, with the bias corrected, shows that the <span class="hlt">trends</span> in <span class="hlt">extent</span> and area of sea <span class="hlt">ice</span> in the Arctic region is -3.4 +/- 0.2 and -4.0 +/- 0.2 % per decade, respectively, while the corresponding values for the Antarctic region is 0.9 +/- 0.2 and 1.7 .+/- 0.3 % per decade. The higher resolution of the AMSR-E provides an improved determination of the location of the <span class="hlt">ice</span> edge while the SSM/I data show an <span class="hlt">ice</span> edge about 6 to 12 km further away from the <span class="hlt">ice</span> pack. Although the current record of AMSR-E is less than 5 years, the data can be utilized in combination with historical data for more accurate determination of the variability and <span class="hlt">trends</span> in the <span class="hlt">ice</span> cover.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1810332R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1810332R"><span><span class="hlt">Trends</span> in annual minimum exposed snow and <span class="hlt">ice</span> cover in High Mountain Asia from MODIS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rittger, Karl; Brodzik, Mary J.; Painter, Thomas H.; Racoviteanu, Adina; Armstrong, Richard; Dozier, Jeff</p> <p>2016-04-01</p> <p>Though a relatively short record on climatological scales, data from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2000-2014 can be used to evaluate changes in the cryosphere and provide a robust baseline for future observations from space. We use the MODIS Snow Covered Area and Grain size (MODSCAG) algorithm, based on spectral mixture analysis, to estimate daily fractional snow and <span class="hlt">ice</span> cover and the MODICE Persistent <span class="hlt">Ice</span> (MODICE) algorithm to estimate the annual minimum snow and <span class="hlt">ice</span> fraction (fSCA) for each year from 2000 to 2014 in High Mountain Asia. We have found that MODSCAG performs better than other algorithms, such as the Normalized Difference Index (NDSI), at detecting snow. We use MODICE because it minimizes false positives (compared to maximum <span class="hlt">extents</span>), for example, when bright soils or clouds are incorrectly classified as snow, a common problem with optical satellite snow mapping. We analyze changes in area using the annual MODICE maps of minimum snow and <span class="hlt">ice</span> cover for over 15,000 individual glaciers as defined by the Randolph Glacier Inventory (RGI) Version 5, focusing on the Amu Darya, Syr Darya, Upper Indus, Ganges, and Brahmaputra River basins. For each glacier with an area of at least 1 km2 as defined by RGI, we sum the total minimum snow and <span class="hlt">ice</span> covered area for each year from 2000 to 2014 and estimate the <span class="hlt">trends</span> in area loss or gain. We find the largest loss in annual minimum snow and <span class="hlt">ice</span> <span class="hlt">extent</span> for 2000-2014 in the Brahmaputra and Ganges with 57% and 40%, respectively, of analyzed glaciers with significant losses (p-value<0.05). In the Upper Indus River basin, we see both gains and losses in minimum snow and <span class="hlt">ice</span> <span class="hlt">extent</span>, but more glaciers with losses than gains. Our analysis shows that a smaller proportion of glaciers in the Amu Darya and Syr Darya are experiencing significant changes in minimum snow and <span class="hlt">ice</span> <span class="hlt">extent</span> (3.5% and 12.2%), possibly because more of the glaciers in this region are smaller than 1 km2 than in the Indus</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.5758P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.5758P"><span>The Impact of a Lower Sea <span class="hlt">Ice</span> <span class="hlt">Extent</span> on Arctic Greenhouse Gas Exchange</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Parmentier, Frans-Jan W.; Christensen, Torben R.; Lotte Sørensen, Lise; Rysgaard, Søren; McGuire, A. David; Miller, Paul A.; Walker, Donald A.</p> <p>2013-04-01</p> <p>Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> hit a new record low in September 2012, when it fell to a level about two times lower than the 1979-2000 average. Record low sea <span class="hlt">ice</span> <span class="hlt">extents</span> such as these are often hailed as an obvious example of the impact of climate change on the Arctic. Less obvious, however, are the further implications of a lower sea <span class="hlt">ice</span> <span class="hlt">extent</span> on Arctic greenhouse gas exchange. For example, a reduction in sea <span class="hlt">ice</span>, in consort with a lower snow cover, has been connected to higher surface temperatures in the terrestrial part of the Arctic (Screen et al., 2012). These higher temperatures and longer growing seasons have the potential to alter the CO2 balance of Arctic tundra through enhanced photosynthesis and respiration, as well as the magnitude of methane emissions. In fact, large changes are already observed in terrestrial ecosystems (Post et al., 2009), and concerns have been raised of large releases of carbon through permafrost thaw (Schuur et al., 2011). While these changes in the greenhouse gas balance of the terrestrial Arctic are described in numerous studies, a connection with a decline in sea <span class="hlt">ice</span> <span class="hlt">extent</span> is nonetheless seldom made. In addition to these changes on land, a lower sea <span class="hlt">ice</span> <span class="hlt">extent</span> also has a direct effect on the exchange of greenhouse gases between the ocean and the atmosphere. For example, due to sea <span class="hlt">ice</span> retreat, more ocean surface remains in contact with the atmosphere, and this has been suggested to increase the oceanic uptake of CO2 (Bates et al., 2006). However, the sustainability of this increased uptake is uncertain (Cai et al., 2010), and carbon fluxes related directly to the sea <span class="hlt">ice</span> itself add much uncertainty to the oceanic uptake of CO2 (Nomura et al., 2006; Rysgaard et al., 2007). Furthermore, significant emissions of methane from the Arctic Ocean have been observed (Kort et al., 2012; Shakhova et al., 2010), but the consequence of a lower sea <span class="hlt">ice</span> <span class="hlt">extent</span> thereon is still unclear. Overall, the decline in sea <span class="hlt">ice</span> that has been seen in recent</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li class="active"><span>3</span></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_3 --> <div id="page_4" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li class="active"><span>4</span></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="61"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.C23B0489B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.C23B0489B"><span>Response of Arctic Snow and Sea <span class="hlt">Ice</span> <span class="hlt">Extents</span> to Melt Season Atmospheric Forcing Across the Land-Ocean Boundary</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bliss, A. C.; Anderson, M. R.</p> <p>2011-12-01</p> <p>Little research has gone into studying the concurrent variations in the annual loss of continental snow cover and sea <span class="hlt">ice</span> <span class="hlt">extent</span> across the land-ocean boundary, however, the analysis of these data averaged spatially over three study regions located in North America and Eastern and Western Russia, reveals a distinct difference in the response of anomalous snow and sea <span class="hlt">ice</span> conditions to the atmospheric forcing. This study compares the monthly continental snow cover and sea <span class="hlt">ice</span> <span class="hlt">extent</span> loss in the Arctic, during the melt season months (May-August) for the period 1979-2007, with regional atmospheric conditions known to influence summer melt including: mean sea level pressures, 925 hPa air temperatures, and mean 2 m U and V wind vectors from NCEP/DOE Reanalysis 2. The monthly hemispheric snow cover <span class="hlt">extent</span> data used are from the Rutgers University Global Snow Lab and sea <span class="hlt">ice</span> <span class="hlt">extents</span> for this study are derived from the monthly passive microwave satellite Bootstrap algorithm sea <span class="hlt">ice</span> concentrations available from the National Snow and <span class="hlt">Ice</span> Data Center. Three case study years (1985, 1996, and 2007) are used to compare the direct response of monthly anomalous sea <span class="hlt">ice</span> and snow cover areal <span class="hlt">extents</span> to monthly mean atmospheric forcing averaged spatially over the <span class="hlt">extent</span> of each study region. This comparison is then expanded for all summer months over the 29 year study period where the monthly persistence of sea <span class="hlt">ice</span> and snow cover <span class="hlt">extent</span> anomalies and changes in the sea <span class="hlt">ice</span> and snow conditions under differing atmospheric conditions are explored further. The monthly anomalous atmospheric conditions are classified into four categories including: warmer temperatures with higher pressures, warmer temperatures with lower pressures, cooler temperatures with higher pressures, and cooler temperatures with lower pressures. Analysis of the atmospheric conditions surrounding anomalous loss of snow and <span class="hlt">ice</span> cover over the independent study regions indicates that conditions of warmer temperatures</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050179461','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050179461"><span>Sea <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.; Cavalieri, Donald J.</p> <p>2005-01-01</p> <p>Sea <span class="hlt">ice</span> covers vast areas of the polar oceans, with <span class="hlt">ice</span> <span class="hlt">extent</span> in the Northern Hemisphere ranging from approximately 7 x 10(exp 6) sq km in September to approximately 15 x 10(exp 6) sq km in March and <span class="hlt">ice</span> <span class="hlt">extent</span> in the Southern Hemisphere ranging from approximately 3 x 10(exp 6) sq km in February to approximately 18 x 10(exp 6) sq km in September. These <span class="hlt">ice</span> covers have major impacts on the atmosphere, oceans, and ecosystems of the polar regions, and so as changes occur in them there are potential widespread consequences. Satellite data reveal considerable interannual variability in both polar sea <span class="hlt">ice</span> covers, and many studies suggest possible connections between the <span class="hlt">ice</span> and various oscillations within the climate system, such as the Arctic Oscillation, North Atlantic Oscillation, and Antarctic Oscillation, or Southern Annular Mode. Nonetheless, statistically significant long-term <span class="hlt">trends</span> are also apparent, including overall <span class="hlt">trends</span> of decreased <span class="hlt">ice</span> coverage in the Arctic and increased <span class="hlt">ice</span> coverage in the Antarctic from late 1978 through the end of 2003, with the Antarctic <span class="hlt">ice</span> increases following marked decreases in the Antarctic <span class="hlt">ice</span> during the 1970s. For a detailed picture of the seasonally varying <span class="hlt">ice</span> cover at the start of the 21st century, this chapter includes <span class="hlt">ice</span> concentration maps for each month of 2001 for both the Arctic and the Antarctic, as well as an overview of what the satellite record has revealed about the two polar <span class="hlt">ice</span> covers from the 1970s through 2003.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018TCry...12.1157M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018TCry...12.1157M"><span>Canadian snow and sea <span class="hlt">ice</span>: historical <span class="hlt">trends</span> and projections</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mudryk, Lawrence R.; Derksen, Chris; Howell, Stephen; Laliberté, Fred; Thackeray, Chad; Sospedra-Alfonso, Reinel; Vionnet, Vincent; Kushner, Paul J.; Brown, Ross</p> <p>2018-04-01</p> <p>The Canadian Sea <span class="hlt">Ice</span> and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state of the art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea <span class="hlt">ice</span> in Canada and the circumpolar Arctic. Here, we present an assessment from the CanSISE Network on <span class="hlt">trends</span> in the historical record of snow cover (fraction, water equivalent) and sea <span class="hlt">ice</span> (area, concentration, type, and thickness) across Canada. We also assess projected changes in snow cover and sea <span class="hlt">ice</span> likely to occur by mid-century, as simulated by the Coupled Model Intercomparison Project Phase 5 (CMIP5) suite of Earth system models. The historical datasets show that the fraction of Canadian land and marine areas covered by snow and <span class="hlt">ice</span> is decreasing over time, with seasonal and regional variability in the <span class="hlt">trends</span> consistent with regional differences in surface temperature <span class="hlt">trends</span>. In particular, summer sea <span class="hlt">ice</span> cover has decreased significantly across nearly all Canadian marine regions, and the rate of multi-year <span class="hlt">ice</span> loss in the Beaufort Sea and Canadian Arctic Archipelago has nearly doubled over the last 8 years. The multi-model consensus over the 2020-2050 period shows reductions in fall and spring snow cover fraction and sea <span class="hlt">ice</span> concentration of 5-10 % per decade (or 15-30 % in total), with similar reductions in winter sea <span class="hlt">ice</span> concentration in both Hudson Bay and eastern Canadian waters. Peak pre-melt terrestrial snow water equivalent reductions of up to 10 % per decade (30 % in total) are projected across southern Canada.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFMGC23H..08S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMGC23H..08S"><span>Correlating <span class="hlt">Ice</span> Cores from Quelccaya <span class="hlt">Ice</span> Cap with Chronology from Little <span class="hlt">Ice</span> Age Glacial <span class="hlt">Extents</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stroup, J. S.; Kelly, M. A.; Lowell, T. V.</p> <p>2010-12-01</p> <p>Proxy records indicate Southern Hemisphere climatic changes during the Little <span class="hlt">Ice</span> Age (LIA; ~1300-1850 AD). In particular, records of change in and around the tropical latitudes require attention because these areas are sensitive to climatic change and record the dynamic interplay between hemispheres (Oerlemans, 2005). Despite this significance, relatively few records exist for the southern tropics. Here we present a reconstruction of glacial fluctuations of Quelccaya <span class="hlt">Ice</span> Cap (QIC), Peruvian Andes, from pre-LIA up to the present day. In the Qori Kalis valley, extensive sets of moraines exist beginning with the 1963 AD <span class="hlt">ice</span> margin (Thompson et al., 2006) and getting progressively older down valley. Several of these older moraines can be traced and are continuous with moraines in the Challpa Cocha valley. These moraines have been dated at <1050-1350-AD (Mercer and Palacios, 1977) and interpreted to have been deposited during the Little <span class="hlt">Ice</span> Age. We present a new suite of surface exposure and radiocarbon dates collected in 2008 and 2009 that constrain the ages of these moraines. Preliminary 10Be ages of boulder surfaces atop the moraines range from ~350-1370 AD. Maximum and minimum-limiting radiocarbon ages bracketing the moraines are ~0-1800 AD. The chronology of past <span class="hlt">ice</span> cap <span class="hlt">extents</span> are correlated with <span class="hlt">ice</span> core records from QIC which show an accumulation increase during ~1500-1700 AD and an accumulation decrease during ~1720-1860 AD (Thompson et al., 1985; 1986; 2006). In addition, other proxy records from Peru and the tropics are correlated with the records at QIC as a means to understand climate conditions during the LIA. This work forms the basis for future modeling of the glacial system during the LIA at QIC and for modeling of past temperature and precipitation regimes at high altitude in the tropics.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015207','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015207"><span>Regional Changes in the Sea <span class="hlt">Ice</span> Cover and <span class="hlt">Ice</span> Production in the Antarctic</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Josefino C.</p> <p>2011-01-01</p> <p>Coastal polynyas around the Antarctic continent have been regarded as sea <span class="hlt">ice</span> factories because of high <span class="hlt">ice</span> production rates in these regions. The observation of a positive <span class="hlt">trend</span> in the <span class="hlt">extent</span> of Antarctic sea <span class="hlt">ice</span> during the satellite era has been intriguing in light of the observed rapid decline of the <span class="hlt">ice</span> <span class="hlt">extent</span> in the Arctic. The results of analysis of the time series of passive microwave data indicate large regional variability with the <span class="hlt">trends</span> being strongly positive in the Ross Sea, strongly negative in the Bellingshausen/Amundsen Seas and close to zero in the other regions. The atmospheric circulation in the Antarctic is controlled mainly by the Southern Annular Mode (SAM) and the marginal <span class="hlt">ice</span> zone around the continent shows an alternating pattern of advance and retreat suggesting the presence of a propagating wave (called Antarctic Circumpolar Wave) around the circumpolar region. The results of analysis of the passive microwave data suggest that the positive <span class="hlt">trend</span> in the Antarctic sea <span class="hlt">ice</span> cover could be caused primarily by enhanced <span class="hlt">ice</span> production in the Ross Sea that may be associated with more persistent and larger coastal polynyas in the region. Over the Ross Sea shelf, analysis of sea <span class="hlt">ice</span> drift data from 1992 to 2008 yields a positive rate-of-increase in the net <span class="hlt">ice</span> export of about 30,000 km2 per year. For a characteristic <span class="hlt">ice</span> thickness of 0.6 m, this yields a volume transport of about 20 km3/year, which is almost identical, within error bars, to our estimate of the <span class="hlt">trend</span> in <span class="hlt">ice</span> production. In addition to the possibility of changes in SAM, modeling studies have also indicated that the ozone hole may have a role in that it causes the deepening of the lows in the western Antarctic region thereby causing strong winds to occur offthe Ross-<span class="hlt">ice</span> shelf.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1912539S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1912539S"><span>Analysis on variability and <span class="hlt">trend</span> in Antarctic sea <span class="hlt">ice</span> albedo between 1983 and 2009</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Seo, Minji; Kim, Hyun-cheol; Choi, Sungwon; Lee, Kyeong-sang; Han, Kyung-soo</p> <p>2017-04-01</p> <p>Sea <span class="hlt">ice</span> is key parameter in order to understand the cryosphere climate change. Several studies indicate the different <span class="hlt">trend</span> of sea <span class="hlt">ice</span> between Antarctica and Arctic. Albedo is important factor for understanding the energy budget and factors for observing of environment changes of Cryosphere such as South Pole, due to it mainly covered by <span class="hlt">ice</span> and snow with high albedo value. In this study, we analyzed variability and <span class="hlt">trend</span> of long-term sea <span class="hlt">ice</span> albedo data to understand the changes of sea <span class="hlt">ice</span> over Antarctica. In addiction, sea <span class="hlt">ice</span> albedo researched the relationship with Antarctic oscillation in order to determine the atmospheric influence. We used the sea <span class="hlt">ice</span> albedo data at The Satellite Application Facility on Climate Monitoring and Antarctic Oscillation data at NOAA Climate Prediction Center (CPC). We analyzed the annual <span class="hlt">trend</span> in albedo using linear regression to understand the spatial and temporal tendency. Antarctic sea <span class="hlt">ice</span> albedo has two spatial <span class="hlt">trend</span>. Weddle sea / Ross sea sections represent a positive <span class="hlt">trend</span> (0.26% ˜ 0.04% yr-1) and Bellingshausen Amundsen sea represents a negative <span class="hlt">trend</span> (- 0.14 ˜ -0.25%yr-1). Moreover, we performed the correlation analysis between albedo and Antarctic oscillation. As a results, negative area indicate correlation coefficient of - 0.3639 and positive area indicates correlation coefficient of - 0.0741. Theses results sea <span class="hlt">ice</span> albedo has regional <span class="hlt">trend</span> according to ocean. Decreasing sea <span class="hlt">ice</span> <span class="hlt">trend</span> has negative relationship with Antarctic oscillation, its represent a possibility that sea <span class="hlt">ice</span> influence atmospheric factor.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20070035024','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20070035024"><span>Arctic Sea <span class="hlt">Ice</span> Parameters from AMSR-E Data using Two Techniques, and Comparisons with Sea <span class="hlt">Ice</span> from SSM</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Josefino C.; Parkinson, Claire L.</p> <p>2007-01-01</p> <p>We use two algorithms to process AMSR-E data in order to determine algorithm dependence, if any, on the estimates of sea <span class="hlt">ice</span> concentration, <span class="hlt">ice</span> <span class="hlt">extent</span> and area, and <span class="hlt">trends</span> and to evaluate how AMSR-E data compare with historical SSM/I data. The monthly <span class="hlt">ice</span> concentrations derived from the two algorithms from AMSR-E data (the AMSR-E Bootstrap Algorithm, or ABA, and the enhanced NASA Team algorithm, or NT2) differ on average by about 1 to 3%, with data from the consolidated <span class="hlt">ice</span> region being generally comparable for ABA and NT2 retrievals while data in the marginal <span class="hlt">ice</span> zones and thin <span class="hlt">ice</span> regions show higher values when the NT2 algorithm is used. The <span class="hlt">ice</span> <span class="hlt">extents</span> and areas derived separately from AMSR-E using these two algorithms are, however, in good agreement, with the differences (ABA-NT2) being about 6.6 x 10(exp 4) square kilometers on average for <span class="hlt">ice</span> <span class="hlt">extents</span> and -6.6 x 10(exp 4) square kilometers for <span class="hlt">ice</span> area which are small compared to mean seasonal values of 10.5 x 10(exp 6) and 9.8 x 10(exp 6) for <span class="hlt">ice</span> <span class="hlt">extent</span> and area: respectively. Likewise, <span class="hlt">extents</span> and areas derived from the same algorithm but from AMSR-E and SSM/I data are consistent but differ by about -24.4 x 10(exp 4) square kilometers and -13.9 x 10(exp 4) square kilometers, respectively. The discrepancies are larger with the estimates of <span class="hlt">extents</span> than area mainly because of differences in channel selection and sensor resolutions. <span class="hlt">Trends</span> in <span class="hlt">extent</span> during the AMSR-E era were also estimated and results from all three data sets are shown to be in good agreement (within errors).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19..795D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19..795D"><span>Response of Antarctic <span class="hlt">ice</span> shelf melt to SAM <span class="hlt">trend</span> and possible feedbacks with the <span class="hlt">ice</span>-dynamics</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Donat-Magnin, Marion; Jourdain, Nicolas C.; Gallée, Hubert; Spence, Paul; Cornford, Stephen L.; Le Sommer, Julien; Durand, Gaël</p> <p>2017-04-01</p> <p>The observed positive <span class="hlt">trend</span> in the Southern Annular Mode (SAM) may warm the Southern Ocean sub-surface through decreased Ekman downward pumping. Subsequent change in <span class="hlt">ice</span>-shelves melt has been suggested to trigger glacier acceleration in West Antarctica. Here we use a regional ocean model configuration of the Amundsen Sea that includes interactive <span class="hlt">ice</span>-shelf cavities. Our results show that the inclusion of <span class="hlt">ice</span>-shelves changes the ocean response to the projected SAM <span class="hlt">trend</span>, i.e. it typically inhibits a part of the SAM-induced subsurface warming. Heat budget analysis has been used to propose responsible mechanisms. Regarding Thwaites and Pine Island, sub <span class="hlt">ice</span>-shelf melt increases above 400m by approximately 40% for Thwaites and 10% for Pine Island and decreases by up to 10% below in response to ocean temperature changes driven by the projected SAM <span class="hlt">trend</span>. The melt sensitivity to poleward shifting winds is nonetheless small compared to the sensitivity to an <span class="hlt">ice</span>-sheet instability, i.e. to a projected change in the shape of <span class="hlt">ice</span>-shelf cavities. For instance, the sub <span class="hlt">ice</span>-shelf melt are doubled near the grounding line of some glaciers in response to the largest grounding line retreat projected for 2100. Large increase in basal melt close to the grounding line could largely impact instability and glacier acceleration. Our work suggests the need for including <span class="hlt">ice</span> shelves into ocean models, and to couple ocean models to <span class="hlt">ice</span>-sheet models in climate projections.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990064613&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DParkinsons','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990064613&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DParkinsons"><span>Variability of Arctic Sea <span class="hlt">Ice</span> as Determined from Satellite Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>1999-01-01</p> <p>The compiled, quality-controlled satellite multichannel passive-microwave record of polar sea <span class="hlt">ice</span> now spans over 18 years, from November 1978 through December 1996, and is revealing considerable information about the Arctic sea <span class="hlt">ice</span> cover and its variability. The information includes data on <span class="hlt">ice</span> concentrations (percent areal coverages of <span class="hlt">ice</span>), <span class="hlt">ice</span> <span class="hlt">extents</span>, <span class="hlt">ice</span> melt, <span class="hlt">ice</span> velocities, the seasonal cycle of the <span class="hlt">ice</span>, the interannual variability of the <span class="hlt">ice</span>, the frequency of <span class="hlt">ice</span> coverage, and the length of the sea <span class="hlt">ice</span> season. The data reveal marked regional and interannual variabilities, as well as some statistically significant <span class="hlt">trends</span>. For the north polar <span class="hlt">ice</span> cover as a whole, maximum <span class="hlt">ice</span> <span class="hlt">extents</span> varied over a range of 14,700,000 - 15,900,000 sq km, while individual regions experienced much greater percent variations, for instance, with the Greenland Sea having a range of 740,000 - 1,110,000 sq km in its yearly maximum <span class="hlt">ice</span> coverage. In spite of the large variations from year to year and region to region, overall the Arctic <span class="hlt">ice</span> <span class="hlt">extents</span> showed a statistically significant, 2.80% / decade negative <span class="hlt">trend</span> over the 18.2-year period. <span class="hlt">Ice</span> season lengths, which vary from only a few weeks near the <span class="hlt">ice</span> margins to the full year in the large region of perennial <span class="hlt">ice</span> coverage, also experienced interannual variability, along with spatially coherent overall <span class="hlt">trends</span>. Linear least squares <span class="hlt">trends</span> show the sea <span class="hlt">ice</span> season to have lengthened in much of the Bering Sea, Baffin Bay, the Davis Strait, and the Labrador Sea, but to have shortened over a much larger area, including the Sea of Okhotsk, the Greenland Sea, the Barents Sea, and the southeastern Arctic.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC53E0944A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC53E0944A"><span>Record low lake <span class="hlt">ice</span> thickness and bedfast <span class="hlt">ice</span> <span class="hlt">extent</span> on Alaska's Arctic Coastal Plain in 2017 exemplify the value of monitoring freshwater <span class="hlt">ice</span> to understand sea-<span class="hlt">ice</span> forcing and predict permafrost dynamics</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Arp, C. D.; Alexeev, V. A.; Bondurant, A. C.; Creighton, A.; Engram, M. J.; Jones, B. M.; Parsekian, A.</p> <p>2017-12-01</p> <p>The winter of 2016/2017 was exceptionally warm and snowy along the coast of Arctic Alaska partly due to low fall sea <span class="hlt">ice</span> <span class="hlt">extent</span>. Based on several decades of field measurements, we documented a new record low maximum <span class="hlt">ice</span> thickness (MIT) for lakes on the Barrow Peninsula, averaging 1.2 m. This is in comparison to a long-term average MIT of 1.7 m stretching back to 1962 with a maximum of 2.1 m in 1970 and previous minimum of 1.3 m in 2014. The relevance of thinner lake <span class="hlt">ice</span> in arctic coastal lowlands, where thermokarst lakes cover greater than 20% of the land area, is that permafrost below lakes with bedfast <span class="hlt">ice</span> is typically preserved. Lakes deeper than the MIT warm and thaw sub-lake permafrost forming taliks. Remote sensing analysis using synthetic aperture radar (SAR) is a valuable tool for scaling the field observations of MIT to the entire freshwater landscape to map bedfast <span class="hlt">ice</span>. A new, long-term time-series of late winter multi-platform SAR from 1992 to 2016 shows a large dynamic range of bedfast <span class="hlt">ice</span> <span class="hlt">extent</span>, 29% of lake area or 6% of the total land area over this period, and adding 2017 to this record is expected to extend this range further. Empirical models of lake mean annual bed temperature suggest that permafrost begins to thaw at depths less than 60% of MIT. Based on this information and knowledge of average lake <span class="hlt">ice</span> growth trajectories, we suggest that future SAR analysis of lake <span class="hlt">ice</span> should focus on mid-winter (January) to evaluate the <span class="hlt">extent</span> of bedfast <span class="hlt">ice</span> and corresponding zones of sub-lake permafrost thaw. Tracking changes in these areas from year to year in mid-winter may provide the best landscape-scale evaluation of changing permafrost conditions in lake-rich arctic lowlands. Because observed changes in MIT coupled with mid-winter bedfast <span class="hlt">ice</span> <span class="hlt">extent</span> provide much information on permafrost stability, we suggest that these measurements can serve as Essential Climate Variables (EVCs) to indicate past and future changes in lake-rich arctic regions. The</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/20020695-arctic-sea-ice-variability-context-recent-atmospheric-circulation-trends','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/20020695-arctic-sea-ice-variability-context-recent-atmospheric-circulation-trends"><span>Arctic sea <span class="hlt">ice</span> variability in the context of recent atmospheric circulation <span class="hlt">trends</span></span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Deser, C.; Walsh, J.E.; Timlin, M.S.</p> <p></p> <p>Sea <span class="hlt">ice</span> is a sensitive component of the climate system, influenced by conditions in both the atmosphere and ocean. Variations in sea <span class="hlt">ice</span> may in turn modulate climate by altering the surface albedo; the exchange of heat, moisture, and momentum between the atmosphere and ocean; and the upper ocean stratification in areas of deep water formation. The surface albedo effect is considered to be one of the dominant factors in the poleward amplification of global warming due to increased greenhouse gas concentrations simulated in many climate models. Forty years (1958--97) of reanalysis products and corresponding sea <span class="hlt">ice</span> concentration data aremore » used to document Arctic sea <span class="hlt">ice</span> variability and its association with surface air temperature (SAT) and sea level pressure (SLP) throughout the Northern Hemisphere extratropics. The dominant mode of winter (January-March) sea <span class="hlt">ice</span> variability exhibits out-of-phase fluctuations between the western and eastern North Atlantic, together with a weaker dipole in the North Pacific. The time series of this mode has a high winter-to-winter autocorrelation (0.69) and is dominated by decadal-scale variations and a longer-term <span class="hlt">trend</span> of diminishing <span class="hlt">ice</span> cover east of Greenland and increasing <span class="hlt">ice</span> cover west of Greenland. Associated with the dominant pattern of winter sea <span class="hlt">ice</span> variability are large-scale changes in SAT and SLP that closely resemble the North Atlantic oscillation. The associated SAT and surface sensible and latent heat flux anomalies are largest over the portions of the marginal sea <span class="hlt">ice</span> zone in which the <span class="hlt">trends</span> of <span class="hlt">ice</span> coverage have been greatest, although the well-documented warming of the northern continental regions is also apparent. the temporal and spatial relationships between the SLP and <span class="hlt">ice</span> anomaly fields are consistent with the notion that atmospheric circulation anomalies force the sea <span class="hlt">ice</span> variations. However, there appears to be a local response of the atmospheric circulation to the changing sea <span class="hlt">ice</span> variations. However</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFMED43A0925B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFMED43A0925B"><span>Visualizing Glaciers and Sea <span class="hlt">Ice</span> via Google Earth</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ballagh, L. M.; Fetterer, F.; Haran, T. M.; Pharris, K.</p> <p>2006-12-01</p> <p>The NOAA team at NSIDC manages over 60 distinct cryospheric and related data products. With an emphasis on data rescue and in situ data, these products hold value for both the scientific and non-scientific user communities. The overarching goal of this presentation is to promote products from two components of the cryosphere (glaciers and sea <span class="hlt">ice</span>). Our Online Glacier Photograph Database contains approximately 3,000 photographs taken over many decades, exemplifying change in the glacier terminus over time. The sea <span class="hlt">ice</span> product shows sea <span class="hlt">ice</span> <span class="hlt">extent</span> and concentration along with anomalies and <span class="hlt">trends</span>. This Sea <span class="hlt">Ice</span> Index product, which starts in 1979 and is updated monthly, provides visuals of the current state of sea <span class="hlt">ice</span> in both hemispheres with <span class="hlt">trends</span> and anomalies. The long time period covered by the data set means that many of the <span class="hlt">trends</span> in <span class="hlt">ice</span> <span class="hlt">extent</span> and concentration shown in this product are statistically significant despite the large natural variability in sea <span class="hlt">ice</span>. The minimum arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> has been a record low in September 2002 and 2005, contributing to an accelerated <span class="hlt">trend</span> in sea <span class="hlt">ice</span> reduction. With increasing world-wide interest in indicators of global climate change, and the upcoming International Polar Year, these data products are of interest to a broad audience. To further extend the impact of these data, we have made them viewable through Google Earth via the Keyhole Markup Language (KML). This presents an opportunity to branch out to a more diverse audience by using a new and innovative tool that allows spatial representation of data of significant scientific and educational interest.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C31B0283C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C31B0283C"><span>Change in the <span class="hlt">Extent</span> of Baffin Island's Penny <span class="hlt">Ice</span> Cap in Response to Regional Warming, 1969 - 2014</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cox, M. C.; Cormier, H. M.; Gardner, A. S.</p> <p>2014-12-01</p> <p>Glaciers are retreating globally in response to warmer atmospheric temperatures, adding large volumes of melt water to the world's oceans. The largest glacierized region and present-day contributor to sea level rise outside of the massive <span class="hlt">ice</span> sheets is the Canadian Arctic. Recent work has shown that the glaciers of the southern Canadian Arctic (Baffin and Bylot Island) have experienced accelerated rates of <span class="hlt">ice</span> loss in recent decades, but little is known regarding the spatial and temporal variations in rates of loss. For this study we examine in detail changes in the <span class="hlt">extent</span> of the Penny <span class="hlt">Ice</span> Cap (a proxy for <span class="hlt">ice</span> loss) between 1969 and 2014 to better understand the climatic drivers of the recently observed accelerated rates of <span class="hlt">ice</span> loss on Baffin Island. To do this, we reconstruct the <span class="hlt">extent</span> of the <span class="hlt">ice</span> cap for the year 1969 from historical maps and for the years 1985, 1995, 2010, and 2014 from Landsat 5 TM and Landsat 8 OLI imagery. We use 2009 SPOT HRS imagery and a novel <span class="hlt">extent</span> comparison algorithm to assess the accuracy of glacier <span class="hlt">extents</span> derived from Landsat imagery. Regional temperature and precipitation records were used to explain the spatial pattern of change. Due to large variation in elevations, hypsometry was also investigated as a contributor to differences in rates of change across the <span class="hlt">ice</span> cap. Preliminary results show overall retreat throughout the <span class="hlt">ice</span> cap but with regional differences in area and length change on either side of the <span class="hlt">Ice</span> Cap divide.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.usgs.gov/of/2010/1176/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/of/2010/1176/"><span>Arctic sea <span class="hlt">ice</span> decline: Projected changes in timing and <span class="hlt">extent</span> of sea <span class="hlt">ice</span> in the Bering and Chukchi Seas</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Douglas, David C.</p> <p>2010-01-01</p> <p>The Arctic region is warming faster than most regions of the world due in part to increasing greenhouse gases and positive feedbacks associated with the loss of snow and <span class="hlt">ice</span> cover. One consequence has been a rapid decline in Arctic sea <span class="hlt">ice</span> over the past 3 decades?a decline that is projected to continue by state-of-the-art models. Many stakeholders are therefore interested in how global warming may change the timing and <span class="hlt">extent</span> of sea <span class="hlt">ice</span> Arctic-wide, and for specific regions. To inform the public and decision makers of anticipated environmental changes, scientists are striving to better understand how sea <span class="hlt">ice</span> influences ecosystem structure, local weather, and global climate. Here, projected changes in the Bering and Chukchi Seas are examined because sea <span class="hlt">ice</span> influences the presence of, or accessibility to, a variety of local resources of commercial and cultural value. In this study, 21st century sea <span class="hlt">ice</span> conditions in the Bering and Chukchi Seas are based on projections by 18 general circulation models (GCMs) prepared for the fourth reporting period by the Intergovernmental Panel on Climate Change (IPCC) in 2007. Sea <span class="hlt">ice</span> projections are analyzed for each of two IPCC greenhouse gas forcing scenarios: the A1B `business as usual? scenario and the A2 scenario that is somewhat more aggressive in its CO2 emissions during the second half of the century. A large spread of uncertainty among projections by all 18 models was constrained by creating model subsets that excluded GCMs that poorly simulated the 1979-2008 satellite record of <span class="hlt">ice</span> <span class="hlt">extent</span> and seasonality. At the end of the 21st century (2090-2099), median sea <span class="hlt">ice</span> projections among all combinations of model ensemble and forcing scenario were qualitatively similar. June is projected to experience the least amount of sea <span class="hlt">ice</span> loss among all months. For the Chukchi Sea, projections show extensive <span class="hlt">ice</span> melt during July and <span class="hlt">ice</span>-free conditions during August, September, and October by the end of the century, with high agreement</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000758.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000758.html"><span>2015 Arctic Sea <span class="hlt">Ice</span> Maximum Annual <span class="hlt">Extent</span> Is Lowest On Record</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2015-03-19</p> <p>The sea <span class="hlt">ice</span> cap of the Arctic appeared to reach its annual maximum winter <span class="hlt">extent</span> on Feb. 25, according to data from the NASA-supported National Snow and <span class="hlt">Ice</span> Data Center (NSIDC) at the University of Colorado, Boulder. At 5.61 million square miles (14.54 million square kilometers), this year’s maximum <span class="hlt">extent</span> was the smallest on the satellite record and also one of the earliest. Read more: 1.usa.gov/1Eyvelz Credit: NASA's Goddard Space Flight Center NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120013478','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120013478"><span>Variability and Anomalous <span class="hlt">Trends</span> in the Global Sea <span class="hlt">Ice</span> Cover</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Josefino C.</p> <p>2012-01-01</p> <p>The advent of satellite data came fortuitously at a time when the global sea <span class="hlt">ice</span> cover has been changing rapidly and new techniques are needed to accurately assess the true state and characteristics of the global sea <span class="hlt">ice</span> cover. The <span class="hlt">extent</span> of the sea <span class="hlt">ice</span> in the Northern Hemisphere has been declining by about -4% per decade for the period 1979 to 2011 but for the period from 1996 to 2010, the rate of decline became even more negative at -8% per decade, indicating an acceleration in the decline. More intriguing is the drastically declining perennial sea <span class="hlt">ice</span> area, which is the <span class="hlt">ice</span> that survives the summer melt and observed to be retreating at the rate of -14% per decade during the 1979 to 2012 period. Although a slight recovery occurred in the last three years from an abrupt decline in 2007, the perennial <span class="hlt">ice</span> <span class="hlt">extent</span> was almost as low as in 2007 in 2011. The multiyear <span class="hlt">ice</span>, which is the thick component of the perennial <span class="hlt">ice</span> and regarded as the mainstay of the Arctic sea <span class="hlt">ice</span> cover is declining at an even higher rate of -19% per decade. The more rapid decline of the <span class="hlt">extent</span> of this thicker <span class="hlt">ice</span> type means that the volume of the <span class="hlt">ice</span> is also declining making the survival of the Arctic <span class="hlt">ice</span> in summer highly questionable. The slight recovery in 2008, 2009 and 2010 for the perennial <span class="hlt">ice</span> in summer was likely associated with an apparent cycle in the time series with a period of about 8 years. Results of analysis of concurrent MODIS and AMSR-E data in summer also provide some evidence of more extensive summer melt and meltponding in 2007 and 2011 than in other years. Meanwhile, the Antarctic sea <span class="hlt">ice</span> cover, as observed by the same set of satellite data, is showing an unexpected and counter intuitive increase of about 1 % per decade over the same period. Although a strong decline in <span class="hlt">ice</span> <span class="hlt">extent</span> is apparent in the Bellingshausen/ Amundsen Seas region, such decline is more than compensated by increases in the <span class="hlt">extent</span> of the sea <span class="hlt">ice</span> cover in the Ross Sea region. The results of analysis of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.2905L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.2905L"><span>Temperature and <span class="hlt">ice</span> layer <span class="hlt">trends</span> in the summer middle atmosphere</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lübken, F.-J.; Berger, U.</p> <p>2012-04-01</p> <p>We present results from our LIMA model (Leibniz Institute Middle Atmosphere Model) which nicely reproduces mean conditions of the summer mesopause region and also mean characteristics of <span class="hlt">ice</span> layers known as noctilucent clouds. LIMA nudges to ECMWF data in the troposphere and lower stratosphere which influences the background conditions in the mesosphere. We study temperature <span class="hlt">trends</span> in the mesosphere at middle and polar latitudes and compared with temperature <span class="hlt">trends</span> from satellites, lidar, and phase height observations. For the first time large observed temperature <span class="hlt">trends</span> in the summer mesosphere can be reproduced and explained by a model. As will be shown, stratospheric ozone has a major impact on temperature <span class="hlt">trends</span> in the summer mesosphere. The temperature <span class="hlt">trend</span> is not uniform in time: it is moderate from 1961 (the beginning of our record) until the beginning of the 1980s. Thereafter, temperatures decrease much stronger until the mid 1990s. Thereafter, temperatures are nearly constant or even increase with time. As will be shown, <span class="hlt">trends</span> in ozone and carbon dioxide explain most of this behavior. <span class="hlt">Ice</span> layers in the summer mesosphere are very sensitive to background conditions and are therefore considered to be appropriate tracers for long term variations in the middle atmosphere. We use LIMA background conditions to determine <span class="hlt">ice</span> layer characteristics in the mesopause region. We compare our results with measurements, for example with albedos from the SBUV satellites, and show that we can nicely reproduce observed <span class="hlt">trends</span>. It turns out that temperature <span class="hlt">trends</span> are positive (negative) in the upper (lower) part of the <span class="hlt">ice</span> layer regime. This complicates an interpretation of NLC long term variations in terms of temperature <span class="hlt">trends</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28378830','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28378830"><span>Possible connections of the opposite <span class="hlt">trends</span> in Arctic and Antarctic sea-<span class="hlt">ice</span> cover.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Yu, Lejiang; Zhong, Shiyuan; Winkler, Julie A; Zhou, Mingyu; Lenschow, Donald H; Li, Bingrui; Wang, Xianqiao; Yang, Qinghua</p> <p>2017-04-05</p> <p>Sea <span class="hlt">ice</span> is an important component of the global climate system and a key indicator of climate change. A decreasing <span class="hlt">trend</span> in Arctic sea-<span class="hlt">ice</span> concentration is evident in recent years, whereas Antarctic sea-<span class="hlt">ice</span> concentration exhibits a generally increasing <span class="hlt">trend</span>. Various studies have investigated the underlying causes of the observed <span class="hlt">trends</span> for each region, but possible linkages between the regional <span class="hlt">trends</span> have not been studied. Here, we hypothesize that the opposite <span class="hlt">trends</span> in Arctic and Antarctic sea-<span class="hlt">ice</span> concentration may be linked, at least partially, through interdecadal variability of the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO). Although evaluation of this hypothesis is constrained by the limitations of the sea-<span class="hlt">ice</span> cover record, preliminary statistical analyses of one short-term and two long-term time series of observed and reanalysis sea-<span class="hlt">ice</span> concentrations data suggest the possibility of the hypothesized linkages. For all three data sets, the leading mode of variability of global sea-<span class="hlt">ice</span> concentration is positively correlated with the AMO and negatively correlated with the PDO. Two wave trains related to the PDO and the AMO appear to produce anomalous surface-air temperature and low-level wind fields in the two polar regions that contribute to the opposite changes in sea-<span class="hlt">ice</span> concentration.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5381096','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5381096"><span>Possible connections of the opposite <span class="hlt">trends</span> in Arctic and Antarctic sea-<span class="hlt">ice</span> cover</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Yu, Lejiang; Zhong, Shiyuan; Winkler, Julie A.; Zhou, Mingyu; Lenschow, Donald H.; Li, Bingrui; Wang, Xianqiao; Yang, Qinghua</p> <p>2017-01-01</p> <p>Sea <span class="hlt">ice</span> is an important component of the global climate system and a key indicator of climate change. A decreasing <span class="hlt">trend</span> in Arctic sea-<span class="hlt">ice</span> concentration is evident in recent years, whereas Antarctic sea-<span class="hlt">ice</span> concentration exhibits a generally increasing <span class="hlt">trend</span>. Various studies have investigated the underlying causes of the observed <span class="hlt">trends</span> for each region, but possible linkages between the regional <span class="hlt">trends</span> have not been studied. Here, we hypothesize that the opposite <span class="hlt">trends</span> in Arctic and Antarctic sea-<span class="hlt">ice</span> concentration may be linked, at least partially, through interdecadal variability of the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO). Although evaluation of this hypothesis is constrained by the limitations of the sea-<span class="hlt">ice</span> cover record, preliminary statistical analyses of one short-term and two long-term time series of observed and reanalysis sea-<span class="hlt">ice</span> concentrations data suggest the possibility of the hypothesized linkages. For all three data sets, the leading mode of variability of global sea-<span class="hlt">ice</span> concentration is positively correlated with the AMO and negatively correlated with the PDO. Two wave trains related to the PDO and the AMO appear to produce anomalous surface-air temperature and low-level wind fields in the two polar regions that contribute to the opposite changes in sea-<span class="hlt">ice</span> concentration. PMID:28378830</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeoRL..44.9008S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeoRL..44.9008S"><span>Conditions leading to the unprecedented low Antarctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> during the 2016 austral spring season</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stuecker, Malte F.; Bitz, Cecilia M.; Armour, Kyle C.</p> <p>2017-09-01</p> <p>The 2016 austral spring was characterized by the lowest Southern Hemisphere (SH) sea <span class="hlt">ice</span> <span class="hlt">extent</span> seen in the satellite record (1979 to present) and coincided with anomalously warm surface waters surrounding most of Antarctica. We show that two distinct processes contributed to this event: First, the extreme El Niño event peaking in December-February 2015/2016 contributed to pronounced extratropical SH sea surface temperature and sea <span class="hlt">ice</span> <span class="hlt">extent</span> anomalies in the eastern Ross, Amundsen, and Bellingshausen Seas that persisted in part until the following 2016 austral spring. Second, internal unforced atmospheric variability of the Southern Annular Mode promoted the exceptional low sea <span class="hlt">ice</span> <span class="hlt">extent</span> in November-December 2016. These results suggest that a combination of tropically forced and internal SH atmospheric variability contributed to the unprecedented sea <span class="hlt">ice</span> decline during the 2016 austral spring, on top of a background of slow changes expected from greenhouse gas and ozone forcing.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li class="active"><span>4</span></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_4 --> <div id="page_5" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li class="active"><span>5</span></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="81"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110020768','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110020768"><span>Use and Limitations of a Climate-Quality Data Record to Study Temperature <span class="hlt">Trends</span> on the Greenland <span class="hlt">Ice</span> Sheet</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Comiso, Josefino C.; Shuman, Christopher A.; Koenig, Lora S.; DiGirolamo, Nicolo E.</p> <p>2011-01-01</p> <p>Enhanced melting of the Greenland <span class="hlt">Ice</span> Sheet has been documented in recent literature along with surface-temperature increases measured using infrared satellite data since 1981. Using a recently-developed climate-quality data record, 11- and 12-year <span class="hlt">trends</span> in the clear-sky <span class="hlt">ice</span>-surface temperature (IST) of the Greenland <span class="hlt">Ice</span> Sheet have been studied using the Moderate-Resolution Imaging Spectroradiometer (MODIS) IST product. Daily and monthly MODIS ISTs of the Greenland <span class="hlt">Ice</span> Sheet beginning on 1 March 2000 and continuing through 31 December 2010 are now available at 6.25-km spatial resolution on a polar stereographic grid as described in Hall et al. (submitted). This record will be elevated in status to a climate-data record (CDR) when more years of data become available either from the MODIS on the Terra or Aqua satellites, or from the Visible Infrared Imager Radiometer Suite (VIIRS) to be launched in October 2011. Maps showing the maximum <span class="hlt">extent</span> of melt for the entire <span class="hlt">ice</span> sheet and for the six major drainage basins have been developed from the MODIS IST dataset. Twelve-year <span class="hlt">trends</span> of the duration of the melt season on the <span class="hlt">ice</span> sheet vary in different drainage basins with some basins melting progressively earlier over the course of the study period. Some (but not all) of the basins also show a progressively-longer duration of melt. IST 12-year <span class="hlt">trends</span> are compared with in-situ data, and climate data from the Modern Era Retrospective-Analysis for Research and Applications (MERRA) Reanalysis.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22259152','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22259152"><span>Arctic <span class="hlt">ice</span> cover, <span class="hlt">ice</span> thickness and tipping points.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wadhams, Peter</p> <p>2012-02-01</p> <p>We summarize the latest results on the rapid changes that are occurring to Arctic sea <span class="hlt">ice</span> thickness and <span class="hlt">extent</span>, the reasons for them, and the methods being used to monitor the changing <span class="hlt">ice</span> thickness. Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> had been shrinking at a relatively modest rate of 3-4% per decade (annually averaged) but after 1996 this speeded up to 10% per decade and in summer 2007 there was a massive collapse of <span class="hlt">ice</span> <span class="hlt">extent</span> to a new record minimum of only 4.1 million km(2). Thickness has been falling at a more rapid rate (43% in the 25 years from the early 1970s to late 1990s) with a specially rapid loss of mass from pressure ridges. The summer 2007 event may have arisen from an interaction between the long-term retreat and more rapid thinning rates. We review thickness monitoring techniques that show the greatest promise on different spatial and temporal scales, and for different purposes. We show results from some recent work from submarines, and speculate that the <span class="hlt">trends</span> towards retreat and thinning will inevitably lead to an eventual loss of all <span class="hlt">ice</span> in summer, which can be described as a 'tipping point' in that the former situation, of an Arctic covered with mainly multi-year <span class="hlt">ice</span>, cannot be retrieved.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1158459-critical-mechanisms-formation-extreme-arctic-sea-ice-extent-summers','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1158459-critical-mechanisms-formation-extreme-arctic-sea-ice-extent-summers"><span>Critical Mechanisms for the Formation of Extreme Arctic Sea-<span class="hlt">Ice</span> <span class="hlt">Extent</span> in the Summers of 2007 and 1996</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Dong, Xiquan; Zib, Benjamin J.; Xi, Baike</p> <p></p> <p>A warming Arctic climate is undergoing significant e 21 nvironmental change, most evidenced by the reduction of Arctic sea-<span class="hlt">ice</span> <span class="hlt">extent</span> during the summer. In this study, we examine two extreme anomalies of September sea-<span class="hlt">ice</span> <span class="hlt">extent</span> in 2007 and 1996, and investigate the impacts of cloud fraction (CF), atmospheric precipitable water vapor (PWV), downwelling longwave flux (DLF), surface air temperature (SAT), pressure and winds on the sea-<span class="hlt">ice</span> variation in 2007 and 1996 using both satellite-derived sea-<span class="hlt">ice</span> products and MERRA reanalysis. The area of the Laptev, East Siberian and West Chukchi seas (70-90oN, 90-180oE) has experienced the largest variation in sea-<span class="hlt">ice</span> extentmore » from year-to-year and defined here as the Area Of Focus (AOF). The record low September sea-<span class="hlt">ice</span> <span class="hlt">extent</span> in 2007 was associated with positive anomalies 30 of CF, PWV, DLF, and SAT over the AOF. Persistent anti-cyclone positioned over the Beaufort Sea coupled with low pressure over Eurasia induced easterly zonal and southerly meridional winds. In contrast, negative CF, PWV, DLF and SAT anomalies, as well as opposite wind patterns to those in 2007, characterized the 1996 high September sea-<span class="hlt">ice</span> <span class="hlt">extent</span>. Through this study, we hypothesize the following positive feedbacks of clouds, water vapor, radiation and atmospheric variables on the sea-<span class="hlt">ice</span> retreat during the summer 2007. The record low sea-<span class="hlt">ice</span> <span class="hlt">extent</span> during the summer 2007 is initially triggered by the atmospheric circulation anomaly. The southerly winds across the Chukchi and East Siberian seas transport warm, moist air from the north Pacific, which is not only enhancing sea-<span class="hlt">ice</span> melt across the AOF, but also increasing clouds. The positive cloud feedback results in higher SAT and more sea-<span class="hlt">ice</span> melt. Therefore, 40 more water vapor could be evaporated from open seas and higher SAT to form more clouds, which will enhance positive cloud feedback. This enhanced positive cloud feedback will then further increase SAT and accelerate the sea-<span class="hlt">ice</span> retreat</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1813243V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1813243V"><span>Insight into glacier climate interaction: reconstruction of the mass balance field using <span class="hlt">ice</span> <span class="hlt">extent</span> data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Visnjevic, Vjeran; Herman, Frédéric; Licul, Aleksandar</p> <p>2016-04-01</p> <p>With the end of the Last Glacial Maximum (LGM), about 20 000 years ago, ended the most recent long-lasting cold phase in Earth's history. We recently developed a model that describes large-scale erosion and its response to climate and dynamical changes with the application to the Alps for the LGM period. Here we will present an inverse approach we have recently developed to infer the LGM mass balance from known <span class="hlt">ice</span> <span class="hlt">extent</span> data, focusing on a glacier or <span class="hlt">ice</span> cap. The <span class="hlt">ice</span> flow model is developed using the shallow <span class="hlt">ice</span> approximation and the developed codes are accelerated using GPUs capabilities. The mass balance field is the constrained variable defined by the balance rate β and the equilibrium line altitude (ELA), where c is the cutoff value: b = max(βṡ(S(z) - ELA), c) We show that such a mass balance can be constrained from the observed past <span class="hlt">ice</span> <span class="hlt">extent</span> and <span class="hlt">ice</span> thickness. We are also investigating several different geostatistical methods to constrain spatially variable mass balance, and derive uncertainties on each of the mass balance parameters.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011JGRD..116.0P03L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011JGRD..116.0P03L"><span>Latitudinal and interhemispheric variation of stratospheric effects on mesospheric <span class="hlt">ice</span> layer <span class="hlt">trends</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lübken, F.-J.; Berger, U.</p> <p>2011-02-01</p> <p>Latitudinal and interhemispheric differences of model results on <span class="hlt">trends</span> in mesospheric <span class="hlt">ice</span> layers and background conditions are analyzed. The model nudges to European Centre for Medium-Range Weather Forecasts data below ˜45 km. Greenhouse gas concentrations in the mesosphere are kept constant. Temperature <span class="hlt">trends</span> in the mesosphere mainly come from shrinking of the stratosphere and from dynamical effects. Water vapor increases at noctilucent cloud (NLC) heights and decreases above due to increased freeze drying caused by temperature <span class="hlt">trends</span>. There is no tendency for <span class="hlt">ice</span> clouds in the Northern Hemisphere for extending farther southward with time. <span class="hlt">Trends</span> of NLC albedo are similar to satellite measurements, but only if a time period longer than observations is considered. <span class="hlt">Ice</span> cloud <span class="hlt">trends</span> get smaller if albedo thresholds relevant to satellite instruments are applied, in particular at high polar latitudes. This implies that weak and moderate NLC is favored when background conditions improve for NLC formation, whereas strong NLC benefits less. <span class="hlt">Trends</span> of <span class="hlt">ice</span> cloud parameters are generally smaller in the Southern Hemisphere (SH) compared to the Northern Hemisphere (NH), consistent with observations. <span class="hlt">Trends</span> in background conditions have counteracting effects on NLC: temperature <span class="hlt">trends</span> would suggest stronger <span class="hlt">ice</span> increase in the SH, and water vapor <span class="hlt">trends</span> would suggest a weaker increase. Larger <span class="hlt">trends</span> in NLC brightness or occurrence rates are not necessarily associated with larger (more negative) temperature <span class="hlt">trends</span>. They can also be caused by larger <span class="hlt">trends</span> of water vapor caused by larger freeze drying, which in turn can be caused by generally lower temperatures and/or more background water. <span class="hlt">Trends</span> of NLC brightness and occurrence rates decrease with decreasing latitude in both hemispheres. The latitudinal variation of these <span class="hlt">trends</span> is primarily determined by induced water vapor <span class="hlt">trends</span>. <span class="hlt">Trends</span> in NLC altitudes are generally small. Stratospheric temperature <span class="hlt">trends</span> vary</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014GeoRL..41.2411S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014GeoRL..41.2411S"><span>Predicting September sea <span class="hlt">ice</span>: Ensemble skill of the SEARCH Sea <span class="hlt">Ice</span> Outlook 2008-2013</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stroeve, Julienne; Hamilton, Lawrence C.; Bitz, Cecilia M.; Blanchard-Wrigglesworth, Edward</p> <p>2014-04-01</p> <p>Since 2008, the Study of Environmental Arctic Change Sea <span class="hlt">Ice</span> Outlook has solicited predictions of September sea-<span class="hlt">ice</span> <span class="hlt">extent</span> from the Arctic research community. Individuals and teams employ a variety of modeling, statistical, and heuristic approaches to make these predictions. Viewed as monthly ensembles each with one or two dozen individual predictions, they display a bimodal pattern of success. In years when observed <span class="hlt">ice</span> <span class="hlt">extent</span> is near its <span class="hlt">trend</span>, the median predictions tend to be accurate. In years when the observed <span class="hlt">extent</span> is anomalous, the median and most individual predictions are less accurate. Statistical analysis suggests that year-to-year variability, rather than methods, dominate the variation in ensemble prediction success. Furthermore, ensemble predictions do not improve as the season evolves. We consider the role of initial <span class="hlt">ice</span>, atmosphere and ocean conditions, and summer storms and weather in contributing to the challenge of sea-<span class="hlt">ice</span> prediction.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.4236K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.4236K"><span>Data-adaptive Harmonic Decomposition and Real-time Prediction of Arctic Sea <span class="hlt">Ice</span> <span class="hlt">Extent</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kondrashov, Dmitri; Chekroun, Mickael; Ghil, Michael</p> <p>2017-04-01</p> <p>Decline in the Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> (SIE) has profound socio-economic implications and is a focus of active scientific research. Of particular interest is prediction of SIE on subseasonal time scales, i.e. from early summer into fall, when sea <span class="hlt">ice</span> coverage in Arctic reaches its minimum. However, subseasonal forecasting of SIE is very challenging due to the high variability of ocean and atmosphere over Arctic in summer, as well as shortness of observational data and inadequacies of the physics-based models to simulate sea-<span class="hlt">ice</span> dynamics. The Sea <span class="hlt">Ice</span> Outlook (SIO) by Sea <span class="hlt">Ice</span> Prediction Network (SIPN, http://www.arcus.org/sipn) is a collaborative effort to facilitate and improve subseasonal prediction of September SIE by physics-based and data-driven statistical models. Data-adaptive Harmonic Decomposition (DAH) and Multilayer Stuart-Landau Models (MSLM) techniques [Chekroun and Kondrashov, 2017], have been successfully applied to the nonlinear stochastic modeling, as well as retrospective and real-time forecasting of Multisensor Analyzed Sea <span class="hlt">Ice</span> <span class="hlt">Extent</span> (MASIE) dataset in key four Arctic regions. In particular, DAH-MSLM predictions outperformed most statistical models and physics-based models in real-time 2016 SIO submissions. The key success factors are associated with DAH ability to disentangle complex regional dynamics of MASIE by data-adaptive harmonic spatio-temporal patterns that reduce the data-driven modeling effort to elemental MSLMs stacked per frequency with fixed and small number of model coefficients to estimate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMPP12C..06S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMPP12C..06S"><span>Reconstruction of the <span class="hlt">extent</span> and variability of late Quaternary <span class="hlt">ice</span> sheets and Arctic sea <span class="hlt">ice</span>: Insights from new mineralogical and geochemical proxy records</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stein, R. H.; Niessen, F.; Fahl, K.; Forwick, M.; Kudriavtseva, A.; Ponomarenko, E.; Prim, A. K.; Quatmann-Hense, A.; Spielhagen, R. F.; Zou, H.</p> <p>2016-12-01</p> <p>The Arctic Ocean and surrounding continents are key areas within the Earth system and very sensitive to present and past climate change. In this context, the timing and <span class="hlt">extent</span> of circum-Arctic <span class="hlt">ice</span> sheets and its interaction with oceanic and sea-<span class="hlt">ice</span> dynamics are major interest and focus of international research. New sediment cores recovered during the Polarstern Expeditions PS87 (Lomonosov Ridge/2014) and PS93.1 (Fram Strait/2015) together with several sediment cores available from previous Polarstern expeditions allow to carry out a detailed sedimentological and geochemical study that may help to unravel the changes in Arctic sea <span class="hlt">ice</span> and circum-Arctic <span class="hlt">ice</span> sheets during late Quaternary times. Our new data include biomarkers indicative for past sea-<span class="hlt">ice</span> <span class="hlt">extent</span>, phytoplankton productivity and terrigenous input as well as grain size, physical property, XRD and XRF data indicative for sources and pathways of terrigenous sediments (<span class="hlt">ice</span>-rafted debris/IRD) related to glaciations in Eurasia, East Siberia, Canada and Greenland. Here, we present examples from selected sediment cores that give new insights into the timing and <span class="hlt">extent</span> of sea <span class="hlt">ice</span> and glaciations during MIS 6 to MIS 2. To highlight one example: SE-NW oriented, streamlined landforms have been mapped on top of the southern Lomonosov Ridge (LR) at water depths between 800 and 1000 m over long distances during Polarstern Expedition PS87, interpreted to be glacial lineations that formed beneath grounded <span class="hlt">ice</span> sheets and <span class="hlt">ice</span> streams. The orientations of the lineations identified are similar to those on the East Siberian continental margin, suggesting an East Siberian Chukchi <span class="hlt">Ice</span> Sheet extended far to the north on LR during times of extreme Quaternary glaciations. Based on our new biomarker records from Core PS2757 (located on LR near 81°N) indicating a MIS 6 <span class="hlt">ice</span>-edge situation with some open-water phytoplankton productivity, the glacial erosional event should have been older than MIS 6 (e.g., MIS 12?).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140017422','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140017422"><span>Sea <span class="hlt">Ice</span> Prediction Has Easy and Difficult Years</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hamilton, Lawrence C.; Bitz, Cecilia M.; Blanchard-Wrigglesworth, Edward; Cutler, Matthew; Kay, Jennifer; Meier, Walter N.; Stroeve, Julienne; Wiggins, Helen</p> <p>2014-01-01</p> <p>Arctic sea <span class="hlt">ice</span> follows an annual cycle, reaching its low point in September each year. The <span class="hlt">extent</span> of sea <span class="hlt">ice</span> remaining at this low point has been <span class="hlt">trending</span> downwards for decades as the Arctic warms. Around the long-term downward <span class="hlt">trend</span>, however, there is significant variation in the minimum <span class="hlt">extent</span> from one year to the next. Accurate forecasts of yearly conditions would have great value to Arctic residents, shipping companies, and other stakeholders and are the subject of much current research. Since 2008 the Sea <span class="hlt">Ice</span> Outlook (SIO) (http://www.arcus.org/search-program/seaiceoutlook) organized by the Study of Environmental Arctic Change (SEARCH) (http://www.arcus.org/search-program) has invited predictions of the September Arctic sea <span class="hlt">ice</span> minimum <span class="hlt">extent</span>, which are contributed from the Arctic research community. Individual predictions, based on a variety of approaches, are solicited in three cycles each year in early June, July, and August. (SEARCH 2013).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70193618','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70193618"><span>Holocene sea surface temperature and sea <span class="hlt">ice</span> <span class="hlt">extent</span> in the Okhotsk and Bering Seas</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Harada, Naomi; Katsuki, Kota; Nakagawa, Mitsuhiro; Matsumoto, Akiko; Seki, Osamu; Addison, Jason A.; Finney, Bruce P.; Sato, Miyako</p> <p>2014-01-01</p> <p>Accurate prediction of future climate requires an understanding of the mechanisms of the Holocene climate; however, the driving forces, mechanisms, and processes of climate change in the Holocene associated with different time scales remain unclear. We investigated the drivers of Holocene sea surface temperature (SST) and sea <span class="hlt">ice</span> <span class="hlt">extent</span> in the North Pacific Ocean, and the Okhotsk and Bering Seas, as inferred from sediment core records, by using the alkenone unsaturation index as a biomarker of SST and abundances of sea <span class="hlt">ice</span>-related diatoms (F. cylindrus and F. oceanica) as an indicator of sea <span class="hlt">ice</span> <span class="hlt">extent</span> to explore controlling mechanisms in the high-latitude Pacific. Temporal changes in alkenone content suggest that alkenone production was relatively high during the middle Holocene in the Okhotsk Sea and the western North Pacific, but highest in the late Holocene in the eastern Bering Sea and the eastern North Pacific. The Holocene variations of alkenone-SSTs at sites near Kamchatka in the Northwest Pacific, as well as in the western and eastern regions of the Bering Sea, and in the eastern North Pacific track the changes of Holocene summer insolation at 50°N, but at other sites in the western North Pacific, in the southern Okhotsk Sea, and the eastern Bering Sea they do not. In addition to insolation, other atmosphere and ocean climate drivers, such as sea <span class="hlt">ice</span> distribution and changes in the position and activity of the Aleutian Low, may have systematically influenced the timing and magnitude of warming and cooling during the Holocene within the subarctic North Pacific. Periods of high sea <span class="hlt">ice</span> <span class="hlt">extent</span> in both the Okhotsk and Bering Seas may correspond to some periods of frequent or strong winter–spring dust storms in the Mongolian Gobi Desert, particularly one centered at ∼4–3 thousand years before present (kyr BP). Variation in storm activity in the Mongolian Gobi Desert region may reflect changes in the strength and positions of the Aleutian Low and Siberian</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140017193','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140017193"><span>Anomalous Variability in Antarctic Sea <span class="hlt">Ice</span> <span class="hlt">Extents</span> During the 1960s With the Use of Nimbus Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Gallaher, David W.; Campbell, G. Garrett; Meier, Walter N.</p> <p>2014-01-01</p> <p>The Nimbus I, II, and III satellites provide a new opportunity for climate studies in the 1960s. The rescue of the visible and infrared imager data resulted in the utilization of the early Nimbus data to determine sea <span class="hlt">ice</span> <span class="hlt">extent</span>. A qualitative analysis of the early NASA Nimbus missions has revealed Antarctic sea <span class="hlt">ice</span> <span class="hlt">extents</span> that are signicant larger and smaller than the historic 1979-2012 passive microwave record. The September 1964 <span class="hlt">ice</span> mean area is 19.7x10 km +/- 0.3x10 km. This is more the 250,000 km greater than the 19.44x10 km seen in the new 2012 historic maximum. However, in August 1966 the maximum sea <span class="hlt">ice</span> <span class="hlt">extent</span> fell to 15.9x10 km +/- 0.3x10 km. This is more than 1.5x10 km below the passive microwave record of 17.5x10 km set in September of 1986. This variation between 1964 and 1966 represents a change of maximum sea <span class="hlt">ice</span> of over 3x10 km in just two years. These inter-annual variations while large, are small when compared to the Antarctic seasonal cycle.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21E1165W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21E1165W"><span>A Detailed Geophysical Investigation of the Grounding of Henry <span class="hlt">Ice</span> Rise, with Implications for Holocene <span class="hlt">Ice</span>-Sheet <span class="hlt">Extent</span>.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wearing, M.; Kingslake, J.</p> <p>2017-12-01</p> <p>It is generally assumed that since the Last Glacial Maximum the West Antarctic <span class="hlt">Ice</span> Sheet (WAIS) has experienced monotonic retreat of the grounding line (GL). However, recent studies have cast doubt on this assumption, suggesting that the retreat of the WAIS grounding line may have been followed by a significant advance during the Holocene in the Weddell and Ross Sea sectors. Constraining this evolution is important as reconstructions of past <span class="hlt">ice</span>-sheet <span class="hlt">extent</span> are used to spin-up predictive <span class="hlt">ice</span>-sheet models and correct mass-balance observations for glacial isostatic adjustment. Here we examine in detail the formation of the Henry <span class="hlt">Ice</span> Rise (HIR), which <span class="hlt">ice</span>-sheet model simulations suggest played a key role in Holocene <span class="hlt">ice</span>-mass changes in the Weddell Sea sector. Observations from a high-resolution ground-based, <span class="hlt">ice</span>-penetrating radar survey are best explained if the <span class="hlt">ice</span> rise formed when the Ronne <span class="hlt">Ice</span> Shelf grounded on a submarine high, underwent a period of <span class="hlt">ice</span>-rumple flow, before the GL migrated outwards to form the present-day <span class="hlt">ice</span> rise. We constrain the relative chronology of this evolution by comparing the alignment and intersection of isochronal internal layers, relic crevasses, surface features and investigating the dynamic processes leading to their complex structure. We also draw analogies between HIR and the neighbouring Doake <span class="hlt">Ice</span> Rumples. The date of formation is estimated using vertical velocities derived with a phase-sensitive radio-echo sounder (pRES). <span class="hlt">Ice</span>-sheet models suggest that the formation of the HIR and other <span class="hlt">ice</span> rises may have halted and reversed large-scale GL retreat. Hence the small-scale dynamics of these crucial regions could have wide-reaching consequences for future <span class="hlt">ice</span>-sheet mass changes and constraining their formation and evolution further would be beneficial. One stringent test of our geophysics-based conclusions would be to drill to the bed of HIR to sample the <span class="hlt">ice</span> for isotopic analysis and the bed for radiocarbon analysis.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20110008453&hterms=Influence+clouds+climate&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DInfluence%2Bclouds%2Bclimate','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20110008453&hterms=Influence+clouds+climate&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DInfluence%2Bclouds%2Bclimate"><span>Influence of Arctic Sea <span class="hlt">Ice</span> <span class="hlt">Extent</span> on Polar Cloud Fraction and Vertical Structure and Implications for Regional Climate</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Palm, Stephen P.; Strey, Sara T.; Spinhirne, James; Markus, Thorsten</p> <p>2010-01-01</p> <p>Recent satellite lidar measurements of cloud properties spanning a period of 5 years are used to examine a possible connection between Arctic sea <span class="hlt">ice</span> amount and polar cloud fraction and vertical distribution. We find an anticorrelation between sea <span class="hlt">ice</span> <span class="hlt">extent</span> and cloud fraction with maximum cloudiness occurring over areas with little or no sea <span class="hlt">ice</span>. We also find that over <span class="hlt">ice</span>!free regions, there is greater low cloud frequency and average optical depth. Most of the optical depth increase is due to the presence of geometrically thicker clouds over water. In addition, our analysis indicates that over the last 5 years, October and March average polar cloud fraction has increased by about 7% and 10%, respectively, as year average sea <span class="hlt">ice</span> <span class="hlt">extent</span> has decreased by 5% 7%. The observed cloud changes are likely due to a number of effects including, but not limited to, the observed decrease in sea <span class="hlt">ice</span> <span class="hlt">extent</span> and thickness. Increasing cloud amount and changes in vertical distribution and optical properties have the potential to affect the radiative balance of the Arctic region by decreasing both the upwelling terrestrial longwave radiation and the downward shortwave solar radiation. Because longwave radiation dominates in the long polar winter, the overall effect of increasing low cloud cover is likely a warming of the Arctic and thus a positive climate feedback, possibly accelerating the melting of Arctic sea <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21141043','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21141043"><span>Loss of sea <span class="hlt">ice</span> in the Arctic.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Perovich, Donald K; Richter-Menge, Jacqueline A</p> <p>2009-01-01</p> <p>The Arctic sea <span class="hlt">ice</span> cover is in decline. The areal <span class="hlt">extent</span> of the <span class="hlt">ice</span> cover has been decreasing for the past few decades at an accelerating rate. Evidence also points to a decrease in sea <span class="hlt">ice</span> thickness and a reduction in the amount of thicker perennial sea <span class="hlt">ice</span>. A general global warming <span class="hlt">trend</span> has made the <span class="hlt">ice</span> cover more vulnerable to natural fluctuations in atmospheric and oceanic forcing. The observed reduction in Arctic sea <span class="hlt">ice</span> is a consequence of both thermodynamic and dynamic processes, including such factors as preconditioning of the <span class="hlt">ice</span> cover, overall warming <span class="hlt">trends</span>, changes in cloud coverage, shifts in atmospheric circulation patterns, increased export of older <span class="hlt">ice</span> out of the Arctic, advection of ocean heat from the Pacific and North Atlantic, enhanced solar heating of the ocean, and the <span class="hlt">ice</span>-albedo feedback. The diminishing Arctic sea <span class="hlt">ice</span> is creating social, political, economic, and ecological challenges.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.H33A0989G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.H33A0989G"><span>Paleo <span class="hlt">ice</span>-cap surfaces and <span class="hlt">extents</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gillespie, A.; Pieri, D.</p> <p>2008-12-01</p> <p>The distribution, equilibrium-line altitude (ELA) and timing of Pleistocene alpine glaciers are used to constrain paleoclimatic reconstructions. Attention has largely focused on the geomorphic evidence for the former presence of simple valley glaciers; paleo alpine <span class="hlt">ice</span> caps and their outlet glaciers have proven to be more problematical. This is especially so in the remote continental interior of Asia, where the research invested in the Alps or Rocky Mountains has yet to be duplicated. Even the putative existence and size of paleo <span class="hlt">ice</span> caps in Tibet and the Kyrgyz Tien Shan is controversial. Remote sensing offers the opportunity to assess vast tracts of land quickly, with images and co-registered digital elevation models (DEMs) offering the most information for studies of paleoglaciers. We pose several questions: (1) With what confidence can nunataks be identified remotely? (2) What insights do their physiographic characteristics offer? (3) What characteristics of the bed of a paleo <span class="hlt">ice</span> cap can be used to identify its former presence remotely? and (4) Can the geomorphic signatures of the edges of paleo <span class="hlt">ice</span> caps be recognized and mapped? Reconstruction of the top surface of a paleo <span class="hlt">ice</span> cap depends on the recognition of nunataks, typically rougher at 1 m to 100 m scales than their surroundings. Nunataks in southern Siberia are commonly notched by multiple sub- horizontal bedrock terraces. These step terraces appear to originate from freeze-thaw action on the rock-<span class="hlt">ice</span> interface during periods of stability, and presence of multiple terraces suggests stepwise lowering of <span class="hlt">ice</span> surfaces during deglaciation. An older generation of step-terraced nunataks, distinguished by degraded and eroded terraces, delineates a larger paleo <span class="hlt">ice</span> cap in the Sayan Range (Siberian - Mongolian border) that significantly pre-dates the last glacial maximum (LGM). Large <span class="hlt">ice</span> caps can experience pressure melting at their base and can manifest <span class="hlt">ice</span> streams within the <span class="hlt">ice</span> cap. Valleys left behind differ</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014PhDT........69M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014PhDT........69M"><span>Arctic Sea <span class="hlt">Ice</span>: <span class="hlt">Trends</span>, Stability and Variability</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Moon, Woosok</p> <p></p> <p>A stochastic Arctic sea-<span class="hlt">ice</span> model is derived and analyzed in detail to interpret the recent decay and associated variability of Arctic sea-<span class="hlt">ice</span> under changes in greenhouse gas forcing widely referred to as global warming. The approach begins from a deterministic model of the heat flux balance through the air/sea/<span class="hlt">ice</span> system, which uses observed monthly-averaged heat fluxes to drive a time evolution of sea-<span class="hlt">ice</span> thickness. This model reproduces the observed seasonal cycle of the <span class="hlt">ice</span> cover and it is to this that stochastic noise---representing high frequency variability---is introduced. The model takes the form of a single periodic non-autonomous stochastic ordinary differential equation. Following an introductory chapter, the two that follow focus principally on the properties of the deterministic model in order to identify the main properties governing the stability of the <span class="hlt">ice</span> cover. In chapter 2 the underlying time-dependent solutions to the deterministic model are analyzed for their stability. It is found that the response time-scale of the system to perturbations is dominated by the destabilizing sea-<span class="hlt">ice</span> albedo feedback, which is operative in the summer, and the stabilizing long wave radiative cooling of the <span class="hlt">ice</span> surface, which is operative in the winter. This basic competition is found throughout the thesis to define the governing dynamics of the system. In particular, as greenhouse gas forcing increases, the sea-<span class="hlt">ice</span> albedo feedback becomes more effective at destabilizing the system. Thus, any projections of the future state of Arctic sea-<span class="hlt">ice</span> will depend sensitively on the treatment of the <span class="hlt">ice</span>-albedo feedback. This in turn implies that the treatment a fractional <span class="hlt">ice</span> cover as the <span class="hlt">ice</span> areal <span class="hlt">extent</span> changes rapidly, must be handled with the utmost care. In chapter 3, the idea of a two-season model, with just winter and summer, is revisited. By breaking the seasonal cycle up in this manner one can simplify the interpretation of the basic dynamics. Whereas in the fully</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.osti.gov/sciencecinema/biblio/987230','SCIGOVIMAGE-SCICINEMA'); return false;" href="http://www.osti.gov/sciencecinema/biblio/987230"><span>The Role of Snow and <span class="hlt">Ice</span> in the Climate System</span></a></p> <p><a target="_blank" href="http://www.osti.gov/sciencecinema/">ScienceCinema</a></p> <p>Barry, Roger G.</p> <p>2017-12-09</p> <p>Global snow and <span class="hlt">ice</span> cover (the 'cryosphere') plays a major role in global climate and hydrology through a range of complex interactions and feedbacks, the best known of which is the <span class="hlt">ice</span> - albedo feedback. Snow and <span class="hlt">ice</span> cover undergo marked seasonal and long term changes in <span class="hlt">extent</span> and thickness. The perennial elements - the major <span class="hlt">ice</span> sheets and permafrost - play a role in present-day regional and local climate and hydrology, but the large seasonal variations in snow cover and sea <span class="hlt">ice</span> are of importance on continental to hemispheric scales. The characteristics of these variations, especially in the Northern Hemisphere, and evidence for recent <span class="hlt">trends</span> in snow and <span class="hlt">ice</span> <span class="hlt">extent</span> are discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012GeoRL..39.8502N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012GeoRL..39.8502N"><span>Observations reveal external driver for Arctic sea-<span class="hlt">ice</span> retreat</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Notz, Dirk; Marotzke, Jochem</p> <p>2012-04-01</p> <p>The very low summer <span class="hlt">extent</span> of Arctic sea <span class="hlt">ice</span> that has been observed in recent years is often casually interpreted as an early-warning sign of anthropogenic global warming. For examining the validity of this claim, previously IPCC model simulations have been used. Here, we focus on the available observational record to examine if this record allows us to identify either internal variability, self-acceleration, or a specific external forcing as the main driver for the observed sea-<span class="hlt">ice</span> retreat. We find that the available observations are sufficient to virtually exclude internal variability and self-acceleration as an explanation for the observed long-term <span class="hlt">trend</span>, clustering, and magnitude of recent sea-<span class="hlt">ice</span> minima. Instead, the recent retreat is well described by the superposition of an externally forced linear <span class="hlt">trend</span> and internal variability. For the externally forced <span class="hlt">trend</span>, we find a physically plausible strong correlation only with increasing atmospheric CO2 concentration. Our results hence show that the observed evolution of Arctic sea-<span class="hlt">ice</span> <span class="hlt">extent</span> is consistent with the claim that virtually certainly the impact of an anthropogenic climate change is observable in Arctic sea <span class="hlt">ice</span> already today.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140010704','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140010704"><span>Anomalous Variability in Antarctic Sea <span class="hlt">Ice</span> <span class="hlt">Extents</span> During the 1960s With the Use of Nimbus Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Gallaher, David W.; Campbell, G. Garrett; Meier, Walter N.</p> <p>2013-01-01</p> <p>The Nimbus I, II, and III satellites provide a new opportunity for climate studies in the 1960s. The rescue of the visible and infrared imager data resulted in the utilization of the early Nimbus data to determine sea <span class="hlt">ice</span> <span class="hlt">extent</span>. A qualitative analysis of the early NASA Nimbus missions has revealed Antarctic sea <span class="hlt">ice</span> <span class="hlt">extents</span> that are significant larger and smaller than the historic 1979-2012 passive microwave record. The September 1964 <span class="hlt">ice</span> mean area is 19.7x10(exp 6) sq. km +/- 0.3x10(exp 6) sq. km. This is more the 250,000 sq. km greater than the 19.44x10(exp 6) sq. km seen in the new 2012 historic maximum. However, in August 1966 the maximum sea <span class="hlt">ice</span> <span class="hlt">extent</span> fell to 15.9x10(exp 6) sq. km +/- 0.3x10(exp 6) sq. km. This is more than 1.5x10(exp 6) sq. km below the passive microwave record of 17.5x10(exp 6) sq. km set in September of 1986. This variation between 1964 and 1966 represents a change of maximum sea <span class="hlt">ice</span> of over 3x10(exp 6) sq. km in just two years. These inter-annual variations while large, are small when compared to the Antarctic seasonal cycle.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA480564','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA480564"><span>Navy Sea <span class="hlt">Ice</span> Prediction Systems</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2002-01-01</p> <p>for the IABP drifting buoys (red), the model (green), and the model with assimilation (black). 55 Oceanography • Vol. 15 • No. 1/2002 trate the need...SPECIAL ISSUE – NAVY OPERATIONAL MODELS : TEN YEARS LATER Oceanography • Vol. 15 • No. 1/2002 44 <span class="hlt">ice</span> <span class="hlt">extent</span> and/or <span class="hlt">ice</span> thickness. A general <span class="hlt">trend</span>...most often based on a combination of models and data. Modeling sea <span class="hlt">ice</span> can be a difficult problem, as it exists in many different forms (Figure 1). It</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li class="active"><span>5</span></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_5 --> <div id="page_6" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active"><span>6</span></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="101"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990064090&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DParkinsons','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990064090&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DParkinsons"><span>Variability of Arctic Sea <span class="hlt">Ice</span> as Viewed from Space</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>1998-01-01</p> <p>Over the past 20 years, satellite passive-microwave radiometry has provided a marvelous means for obtaining information about the variability of the Arctic sea <span class="hlt">ice</span> cover and particularly about sea <span class="hlt">ice</span> concentrations (% areal coverages) and from them <span class="hlt">ice</span> <span class="hlt">extents</span> and the lengths of the sea <span class="hlt">ice</span> season. This ability derives from the sharp contrast between the microwave emissions of sea <span class="hlt">ice</span> versus liquid water and allows routine monitoring of the vast Arctic sea <span class="hlt">ice</span> cover, which typically varies in <span class="hlt">extent</span> from a minimum of about 8,000,000 sq km in September to a maximum of about 15,000,000 sq km in March, the latter value being over 1.5 times the area of either the United States or Canada. The vast Arctic <span class="hlt">ice</span> cover has many impacts, including hindering heat, mass, and y momentum exchanges between the oceans and the atmosphere, reducing the amount of solar radiation absorbed at the Earth's surface, affecting freshwater transports and ocean circulation, and serving as a vital surface for many species of polar animals. These direct impacts also lead to indirect impacts, including effects on local and perhaps global atmospheric temperatures, effects that are being examined in general circulation modeling studies, where preliminary results indicate that changes on the order of a few percent sea <span class="hlt">ice</span> concentration can lead to temperature changes of 1 K or greater even in local areas outside of the sea <span class="hlt">ice</span> region. Satellite passive-microwave data for November 1978 through December 1996 reveal marked regional and interannual variabilities in both the <span class="hlt">ice</span> <span class="hlt">extents</span> and the lengths of the sea <span class="hlt">ice</span> season, as well as some statistically significant <span class="hlt">trends</span>. For the north polar <span class="hlt">ice</span> cover as a whole, maximum <span class="hlt">ice</span> <span class="hlt">extents</span> varied over a range of 14,700,000 - 15,900,000 km(2), while individual regions showed much greater percentage variations, e.g., with the Greenland Sea experiencing a range of 740,000 - 1,1110,000 km(2) in its yearly maximum <span class="hlt">ice</span> coverage. Although variations from year to</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C21C0703A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C21C0703A"><span><span class="hlt">Trends</span> in Arctic Sea <span class="hlt">Ice</span> Leads Detection</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ackerman, S. A.; Hoffman, J.; Liu, Y.; Key, J. R.</p> <p>2016-12-01</p> <p>Sea <span class="hlt">ice</span> leads (fractures) play a critical role in the exchange of mass and energy between the ocean and atmosphere in the polar regions, particularly in the Arctic. Leads result in warming water and accelerated melting because leads absorb more solar energy than the surrounding <span class="hlt">ice</span>. In the autumn, winter, and spring leads impact the local atmospheric structure and cloud properties because of the large flux of heat and moisture into the atmosphere. Given the rapid thinning and loss of Arctic sea <span class="hlt">ice</span> over the last few decades, changes in the distribution of leads can be expected in response. Leads are largely wind driven, so their distributions will also be affected by the changes in atmospheric circulation that have occurred. From a climate perspective, identifying <span class="hlt">trends</span> in lead characteristics (width, orientation, and spatial distribution) will advance our understanding of both thermodynamic and mechanical processes. This study presents the spatial and temporal distributions of Arctic sea <span class="hlt">ice</span> leads since 2002 using a new method to detect and characterize sea <span class="hlt">ice</span> leads with optical (visible, infrared) satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS). Using reflective and emissive channels, <span class="hlt">ice</span> concentration is derived in cloud-free regions and used to create a mask of potential leads. An algorithm then uses a combination of image processing techniques to identify and characterizes leads. The results show interannual variability of leads positioning as well as parameters such as area, length, orientation and width.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110008601','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110008601"><span>The Influence of Arctic Sea <span class="hlt">Ice</span> <span class="hlt">Extent</span> on Polar Cloud Fraction and Vertical Structure and Implications for Regional Climate</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Palm, Stephen P.; Strey, Sara T.; Spinhirne, James; Markus, Thorsten</p> <p>2010-01-01</p> <p>Recent satellite lidar measurements of cloud properties spanning a period of five years are used to examine a possible connection between Arctic sea <span class="hlt">ice</span> amount and polar cloud fraction and vertical distribution. We find an anti-correlation between sea <span class="hlt">ice</span> <span class="hlt">extent</span> and cloud fraction with maximum cloudiness occurring over areas with little or no sea <span class="hlt">ice</span>. We also find that over <span class="hlt">ice</span> free regions, there is greater low cloud frequency and average optical depth. Most of the optical depth increase is due to the presence of geometrically thicker clouds over water. In addition, our analysis indicates that over the last 5 years, October and March average polar cloud fraction has increased by about 7 and 10 percent, respectively, as year average sea <span class="hlt">ice</span> <span class="hlt">extent</span> has decreased by 5 to 7 percent. The observed cloud changes are likely due to a number of effects including, but not limited to, the observed decrease in sea <span class="hlt">ice</span> <span class="hlt">extent</span> and thickness. Increasing cloud amount and changes in vertical distribution and optical properties have the potential to affect the radiative balance of the Arctic region by decreasing both the upwelling terrestrial longwave radiation and the downward shortwave solar radiation. Since longwave radiation dominates in the long polar winter, the overall effect of increasing low cloud cover is likely a warming of the Arctic and thus a positive climate feedback, possibly accelerating the melting of Arctic sea <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160003692&hterms=BALANCE+SHEET&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DBALANCE%2BSHEET','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160003692&hterms=BALANCE+SHEET&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DBALANCE%2BSHEET"><span>The Darkening of the Greenland <span class="hlt">Ice</span> Sheet: <span class="hlt">Trends</span>, Drivers and Projections (1981-2100)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tedesco, Marco; Doherty, Sarah; Fettweis, Xavier; Alexander, Patrick; Jeyaratnam, Jeyavinoth; Stroeve, Julienne</p> <p>2016-01-01</p> <p>The surface energy balance and meltwater production of the Greenland <span class="hlt">ice</span> sheet (GrIS) are modulated by snow and <span class="hlt">ice</span> albedo through the amount of absorbed solar radiation. Here we show, using space-borne multispectral data collected during the 3 decades from 1981 to 2012, that summertime surface albedo over the GrIS decreased at a statistically significant (99 %) rate of 0.02 decade(sup -1) between 1996 and 2012. Over the same period, albedo modelled by the Modele Atmospherique Regionale (MAR) also shows a decrease, though at a lower rate (approximately -0.01 decade(sup -1)) than that obtained from space-borne data. We suggest that the discrepancy between modelled and measured albedo <span class="hlt">trends</span> can be explained by the absence in the model of processes associated with the presence of light-absorbing impurities. The negative <span class="hlt">trend</span> in observed albedo is confined to the regions of the GrIS that undergo melting in summer, with the dry snow zone showing no <span class="hlt">trend</span>. The period 1981-1996 also showed no statistically significant <span class="hlt">trend</span> over the whole GrIS. Analysis of MAR outputs indicates that the observed albedo decrease is attributable to the combined effects of increased near-surface air temperatures, which enhanced melt and promoted growth in snow grain size and the expansion of bare <span class="hlt">ice</span> areas, and to <span class="hlt">trends</span> in light-absorbing impurities (LAI) on the snow and <span class="hlt">ice</span> surfaces. Neither aerosol models nor in situ and remote sensing observations indicate increasing <span class="hlt">trends</span> in LAI in the atmosphere over Greenland. Similarly, an analysis of the number of fires and BC emissions from fires points to the absence of <span class="hlt">trends</span> for such quantities. This suggests that the apparent increase of LAI in snow and <span class="hlt">ice</span> might be related to the exposure of a "dark band" of dirty <span class="hlt">ice</span> and to increased consolidation of LAI at the surface with melt, not to increased aerosol deposition. Albedo projections through to the end of the century under different warming scenarios consistently point to continued</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMPA13A0223V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMPA13A0223V"><span>New Tools for Sea <span class="hlt">Ice</span> Data Analysis and Visualization: NSIDC's Arctic Sea <span class="hlt">Ice</span> News and Analysis</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Vizcarra, N.; Stroeve, J.; Beam, K.; Beitler, J.; Brandt, M.; Kovarik, J.; Savoie, M. H.; Skaug, M.; Stafford, T.</p> <p>2017-12-01</p> <p>Arctic sea <span class="hlt">ice</span> has long been recognized as a sensitive climate indicator and has undergone a dramatic decline over the past thirty years. Antarctic sea <span class="hlt">ice</span> continues to be an intriguing and active field of research. The National Snow and <span class="hlt">Ice</span> Data Center's Arctic Sea <span class="hlt">Ice</span> News & Analysis (ASINA) offers researchers and the public a transparent view of sea <span class="hlt">ice</span> data and analysis. We have released a new set of tools for sea <span class="hlt">ice</span> analysis and visualization. In addition to Charctic, our interactive sea <span class="hlt">ice</span> <span class="hlt">extent</span> graph, the new Sea <span class="hlt">Ice</span> Data and Analysis Tools page provides access to Arctic and Antarctic sea <span class="hlt">ice</span> data organized in seven different data workbooks, updated daily or monthly. An interactive tool lets scientists, or the public, quickly compare changes in <span class="hlt">ice</span> <span class="hlt">extent</span> and location. Another tool allows users to map <span class="hlt">trends</span>, anomalies, and means for user-defined time periods. Animations of September Arctic and Antarctic monthly average sea <span class="hlt">ice</span> <span class="hlt">extent</span> and concentration may also be accessed from this page. Our tools help the NSIDC scientists monitor and understand sea <span class="hlt">ice</span> conditions in near real time. They also allow the public to easily interact with and explore sea <span class="hlt">ice</span> data. Technical innovations in our data center helped NSIDC quickly build these tools and more easily maintain them. The tools were made publicly accessible to meet the desire from the public and members of the media to access the numbers and calculations that power our visualizations and analysis. This poster explores these tools and how other researchers, the media, and the general public are using them.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMPP23B1398E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMPP23B1398E"><span>A 100-year Reconstruction of Regional Sea <span class="hlt">Ice</span> <span class="hlt">Extent</span> in the Ross and Amundsen-Bellingshausen Seas as Derived from the RICE <span class="hlt">Ice</span> Core, Coastal West Antarctica</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Emanuelsson, D. B.; Bertler, N. A. N.; Baisden, W. T.; Keller, E. D.</p> <p>2014-12-01</p> <p>Antarctic sea <span class="hlt">ice</span> increased over the past decades. This increase is the result of an increase in the Ross Sea (RS) and along the coast of East Antarctica, whereas the Amundsen-Bellingshausen Seas (ABS) and the Antarctic Peninsula has seen a general decline. Several mechanisms have been suggested as drivers for the regional, complex sea <span class="hlt">ice</span> pattern, which include changes in ocean currents, wind pattern, as well as ocean and atmospheric temperature. As part of the Roosevelt Island Climate Evolution (RICE) project, a 763 m deep <span class="hlt">ice</span> core was retrieved from Roosevelt Island (RI; W161° 21', S79°41', 560 m a.s.l.), West Antarctica. The new record provides a unique opportunity to investigate mechanism driving sea <span class="hlt">ice</span> variability in the RS and ABS sectors. Here we present the water stable isotope record (δD) from the upper part of the RICE core 0-40 m, spanning the time period from 1894 to 2011 (Fig. 1a). Annual δD are correlated with Sea <span class="hlt">Ice</span> Concentration (SIC). A significant negative (r= -0.45, p≤ 0.05) correlation was found between annual δD and SIC in the eastern RS sector (boxed region in Fig. 1b) for the following months NDJFMA (austral summer and fall). During NDJFMA, RI receives local moisture input from the RS, while during the rest of the year a large <span class="hlt">extent</span> of this local moisture source area will be covered with sea <span class="hlt">ice</span> with the exception of the RS Polynya. Concurrently, we observe positive δD and SIC correlations in the ABS, showing a dipole pattern with the eastern RS. For this reason, we suggest that the RICE δD might be used as a proxy for past SIC for the RS and ABS region. There is no overall <span class="hlt">trend</span> in δD over 100 years (r= -0.08 ‰ dec-1, p= 0.81, 1894-2011). However, we observe a strong increase from 2000-2011 of 17.7 ‰ dec-1(p≤ 0.1), yet the recent δD values and <span class="hlt">trend</span> of the last decade are not unprecedented (Fig. 1a). We investigate changes in sea surface temperature, atmospheric temperature, inferred surface ocean currents and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C32B..05B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C32B..05B"><span>Expanding Antarctic Sea <span class="hlt">Ice</span>: Anthropogenic or Natural Variability?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bitz, C. M.</p> <p>2016-12-01</p> <p>Antarctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> has increased over the last 36 years according to the satellite record. Concurrent with Antarctic sea-<span class="hlt">ice</span> expansion has been broad cooling of the Southern Ocean sea-surface temperature. Not only are Southern Ocean sea <span class="hlt">ice</span> and SST <span class="hlt">trends</span> at odds with expectations from greenhouse gas-induced warming, the <span class="hlt">trend</span> patterns are not reproduced in historical simulations with comprehensive global climate models. While a variety of different factors may have contributed to the observed <span class="hlt">trends</span> in recent decades, we propose that it is atmospheric circulation changes - and the changes in ocean circulation they induce - that have emerged as the most likely cause of the observed Southern Ocean sea <span class="hlt">ice</span> and SST <span class="hlt">trends</span>. I will discuss deficiencies in models that could explain their incorrect response. In addition, I will present results from a series of experiments where the Antarctic sea <span class="hlt">ice</span> and ocean are forced by atmospheric perturbations imposed within a coupled climate model. Figure caption: Linear <span class="hlt">trends</span> of annual-mean SST (left) and annual-mean sea-<span class="hlt">ice</span> concentration (right) over 1980-2014. SST is from NOAA's Optimum Interpolation SST dataset (version 2; Reynolds et al. 2002). Sea-<span class="hlt">ice</span> concentration is from passive microwave observations using the NASA Team algorithm. Only the annual means are shown here for brevity and because the signal to noise is greater than in the seasonal means. Figure from Armour and Bitz (2015).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C11D..03S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C11D..03S"><span>The Impact of Stratospheric Circulation Extremes on Minimum Arctic Sea <span class="hlt">Ice</span> <span class="hlt">Extent</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Smith, K. L.; Polvani, L. M.; Tremblay, B.</p> <p>2017-12-01</p> <p>The interannual variability of summertime Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> (SIE) is anti-correlated with the leading mode of extratropical atmospheric variability in preceding winter, the Arctic Oscillation (AO). Given this relationship and the need for better seasonal predictions of Arctic SIE, we here examine the role of stratospheric circulation extremes and stratosphere-troposphere coupling in linking the AO and Arctic SIE variability. We show that extremes in the stratospheric circulation during the winter season, namely stratospheric sudden warming (SSW) and strong polar vortex (SPV) events, are associated with significant anomalies in sea <span class="hlt">ice</span> concentration in the Bering Straight and the Sea of Okhotsk in winter, the Barents Sea in spring and along the Eurasian coastline in summer in both observations and a fully-coupled, stratosphere-resolving general circulation model. The accompanying figure shows the composite mean sea <span class="hlt">ice</span> concentration anomalies from the Whole Atmosphere Community Climate Model (WACCM) for SSWs (N = 126, top row) and SPVs (N = 99, bottom row) for winter (a,d), spring (b,e) and summer (c,f). Consistent with previous work on the AO, we find that SSWs, which are followed by the negative phase of the AO at the surface, result in sea <span class="hlt">ice</span> growth, whereas SPVs, which are followed by the positive phase of the AO at the surface, result in sea <span class="hlt">ice</span> loss, although the dynamic and thermodynamic processes driving these sea <span class="hlt">ice</span> anomalies in the three Arctic regions, noted above, are different. Our analysis suggests that the presence or absence of stratospheric circulation extremes in winter may play a non-trivial role in determining total September Arctic SIE when combined with other factors.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC41H..08H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC41H..08H"><span>The role of declining summer sea <span class="hlt">ice</span> <span class="hlt">extent</span> in increasing Arctic winter precipitation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hamman, J.; Roberts, A.; Cassano, J. J.; Nijssen, B.</p> <p>2016-12-01</p> <p>In the past three decades, the Arctic has experienced large declines in summer sea <span class="hlt">ice</span> cover, permafrost <span class="hlt">extent</span>, and spring snow cover, and increases in winter precipitation. This study explores the relationship between declining Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> (IE) and winter precipitation (WP) across the Arctic land masses. The first part of this presentation presents the observed relationship between IE and WP. Using satellite estimates of IE and WP data based on a combination of in-situ observations and global reanalyses, we show that WP is negatively correlated with summer IE and that this relationship is strongest before the year 2000. After 2000, around the time IE minima began to decline most rapidly, the relationship between IE and WP degenerates. This indicates that other processes are driving changes in IE and WP. We hypothesize that positive anomalies in poleward moisture transport have historically driven anomalously low IE and high WP, and that since the significant decline in IE, moisture divergence from the central Arctic has been a larger contributor to WP over land. To better understand the physical mechanisms driving the observed changes in the Arctic climate system and the sensitivity of the Arctic climate system to declining sea <span class="hlt">ice</span>, we have used the fully-coupled Regional Arctic System Model (RASM) to simulate two distinct sea <span class="hlt">ice</span> climates. The first climate represents normal IE, while the second includes reduced summer IE. The second portion of this presentation analyzes these two RASM simulations, in conjunction with our observation-based analysis, to understand the coupled relationship between poleward moisture transport, IE, evaporation from the Arctic Ocean, and precipitation. We will present the RASM-simulated Arctic water budget and demonstrate the role of IE in driving WP anomalies. Finally, a spatial correlation analysis identifies characteristic patterns in IE, ocean evaporation, and polar cap convergence that contribute to anomalies in WP.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70048257','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70048257"><span>Extreme events, <span class="hlt">trends</span>, and variability in Northern Hemisphere lake-<span class="hlt">ice</span> phenology (1855-2005)</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Benson, Barbara J.; Magnuson, John J.; Jensen, Olaf P.; Card, Virginia M.; Hodgkins, Glenn; Korhonen, Johanna; Livingstone, David M.; Stewart, Kenton M.; Weyhenmeyer, Gesa A.; Granin, Nick G.</p> <p>2012-01-01</p> <p>Often extreme events, more than changes in mean conditions, have the greatest impact on the environment and human well-being. Here we examine changes in the occurrence of extremes in the timing of the annual formation and disappearance of lake <span class="hlt">ice</span> in the Northern Hemisphere. Both changes in the mean condition and in variability around the mean condition can alter the probability of extreme events. Using long-term <span class="hlt">ice</span> phenology data covering two periods 1855–6 to 2004–5 and 1905–6 to 2004–5 for a total of 75 lakes, we examined patterns in long-term <span class="hlt">trends</span> and variability in the context of understanding the occurrence of extreme events. We also examined patterns in <span class="hlt">trends</span> for a 30-year subset (1975–6 to 2004–5) of the 100-year data set. <span class="hlt">Trends</span> for <span class="hlt">ice</span> variables in the recent 30-year period were steeper than those in the 100- and 150-year periods, and <span class="hlt">trends</span> in the 150-year period were steeper than in the 100-year period. Ranges of rates of change (days per decade) among time periods based on linear regression were 0.3−1.6 later for freeze, 0.5−1.9 earlier for breakup, and 0.7−4.3 shorter for duration. Mostly, standard deviation did not change, or it decreased in the 150-year and 100-year periods. During the recent 50-year period, standard deviation calculated in 10-year windows increased for all <span class="hlt">ice</span> measures. For the 150-year and 100-year periods changes in the mean <span class="hlt">ice</span> dates rather than changes in variability most strongly influenced the significant increases in the frequency of extreme lake <span class="hlt">ice</span> events associated with warmer conditions and decreases in the frequency of extreme events associated with cooler conditions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016TCry...10.1823S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016TCry...10.1823S"><span>Mapping and assessing variability in the Antarctic marginal <span class="hlt">ice</span> zone, pack <span class="hlt">ice</span> and coastal polynyas in two sea <span class="hlt">ice</span> algorithms with implications on breeding success of snow petrels</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stroeve, Julienne C.; Jenouvrier, Stephanie; Campbell, G. Garrett; Barbraud, Christophe; Delord, Karine</p> <p>2016-08-01</p> <p>Sea <span class="hlt">ice</span> variability within the marginal <span class="hlt">ice</span> zone (MIZ) and polynyas plays an important role for phytoplankton productivity and krill abundance. Therefore, mapping their spatial <span class="hlt">extent</span> as well as seasonal and interannual variability is essential for understanding how current and future changes in these biologically active regions may impact the Antarctic marine ecosystem. Knowledge of the distribution of MIZ, consolidated pack <span class="hlt">ice</span> and coastal polynyas in the total Antarctic sea <span class="hlt">ice</span> cover may also help to shed light on the factors contributing towards recent expansion of the Antarctic <span class="hlt">ice</span> cover in some regions and contraction in others. The long-term passive microwave satellite data record provides the longest and most consistent record for assessing the proportion of the sea <span class="hlt">ice</span> cover that is covered by each of these <span class="hlt">ice</span> categories. However, estimates of the amount of MIZ, consolidated pack <span class="hlt">ice</span> and polynyas depend strongly on which sea <span class="hlt">ice</span> algorithm is used. This study uses two popular passive microwave sea <span class="hlt">ice</span> algorithms, the NASA Team and Bootstrap, and applies the same thresholds to the sea <span class="hlt">ice</span> concentrations to evaluate the distribution and variability in the MIZ, the consolidated pack <span class="hlt">ice</span> and coastal polynyas. Results reveal that the seasonal cycle in the MIZ and pack <span class="hlt">ice</span> is generally similar between both algorithms, yet the NASA Team algorithm has on average twice the MIZ and half the consolidated pack <span class="hlt">ice</span> area as the Bootstrap algorithm. <span class="hlt">Trends</span> also differ, with the Bootstrap algorithm suggesting statistically significant <span class="hlt">trends</span> towards increased pack <span class="hlt">ice</span> area and no statistically significant <span class="hlt">trends</span> in the MIZ. The NASA Team algorithm on the other hand indicates statistically significant positive <span class="hlt">trends</span> in the MIZ during spring. Potential coastal polynya area and amount of broken <span class="hlt">ice</span> within the consolidated <span class="hlt">ice</span> pack are also larger in the NASA Team algorithm. The timing of maximum polynya area may differ by as much as 5 months between algorithms. These</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030102176','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030102176"><span>30-Year Satellite Record Reveals Contrasting Arctic and Antarctic Decadal Sea <span class="hlt">Ice</span> Variability</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cavalieri, D. J.; Parkinson, C. L.; Vinnikov, K. Y.</p> <p>2003-01-01</p> <p>A 30-year satellite record of sea <span class="hlt">ice</span> <span class="hlt">extents</span> derived mostly from satellite microwave radiometer observations reveals that the Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> decreased by 0.30+0.03 x 10(exp 6) square kilometers per 10 yr from 1972 through 2002, but by 0.36 plus or minus 0.05 x 10(exp 6) square kilometers per 10yr from 1979 through 2002, indicating an acceleration of 20% in the rate of decrease. In contrast, the Antarctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> decreased dramatically over the period 1973-1977, then gradually increased. Over the full 30-year period, the Antarctic <span class="hlt">ice</span> <span class="hlt">extent</span> decreased by 0.15 plus or minus 0.08 x 10(exp 6) square kilometers per 10 yr. The <span class="hlt">trend</span> reversal is attributed to a large positive anomaly in Antarctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> in the early 1970's, an anomaly that apparently began in the late 1960's, as observed in early visible and infrared satellite images.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70033649','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70033649"><span><span class="hlt">Extent</span> of the last <span class="hlt">ice</span> sheet in northern Scotland tested with cosmogenic 10Be exposure ages</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Phillips, W.M.; Hall, A.M.; Ballantyne, C.K.; Binnie, S.; Kubik, P.W.; Freeman, S.</p> <p>2008-01-01</p> <p>The <span class="hlt">extent</span> of the last British-Irish <span class="hlt">Ice</span> Sheet (BIIS) in northern Scotland is disputed. A restricted <span class="hlt">ice</span> sheet model holds that at the global Last Glacial Maximum (LGM; ca. 23-19 ka) the BIIS terminated on land in northern Scotland, leaving Buchan, Caithness and the Orkney Islands <span class="hlt">ice</span>-free. An alternative model implies that these three areas were <span class="hlt">ice</span>-covered at the LGM, with the BIIS extending offshore onto the adjacent shelves. We test the two models using cosmogenic 10Be surface exposure dating of erratic boulders and glacially eroded bedrock from the three areas. Our results indicate that the last BIIS covered all of northern Scotland during the LGM, but that widespread deglaciation of Caithness and Orkney occurred prior to rapid warming at ca. 14.5 ka. Copyright ?? 2008 John Wiley & Sons, Ltd.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950045752&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DParkinsons','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950045752&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DParkinsons"><span>The role of sea <span class="hlt">ice</span> in 2 x CO2 climate model sensitivity. Part 1: The total influence of sea <span class="hlt">ice</span> thickness and <span class="hlt">extent</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Rind, D.; Healy, R.; Parkinson, C.; Martinson, D.</p> <p>1995-01-01</p> <p>As a first step in investigating the effects of sea <span class="hlt">ice</span> changes on the climate sensitivity to doubled atmospheric CO2, the authors use a standard simple sea <span class="hlt">ice</span> model while varying the sea <span class="hlt">ice</span> distributions and thicknesses in the control run. Thinner <span class="hlt">ice</span> amplifies the atmospheric temperature senstivity in these experiments by about 15% (to a warming of 4.8 C), because it is easier for the thinner <span class="hlt">ice</span> to be removed as the climate warms. Thus, its impact on sensitivity is similar to that of greater sea <span class="hlt">ice</span> <span class="hlt">extent</span> in the control run, which provides more opportunity for sea <span class="hlt">ice</span> reduction. An experiment with sea <span class="hlt">ice</span> not allowed to change between the control and doubled CO2 simulations illustrates that the total effect of sea <span class="hlt">ice</span> on surface air temperature changes, including cloud cover and water vapor feedbacks that arise in response to sea <span class="hlt">ice</span> variations, amounts to 37% of the temperature sensitivity to the CO2 doubling, accounting for 1.56 C of the 4.17 C global warming. This is about four times larger than the sea <span class="hlt">ice</span> impact when no feedbacks are allowed. The different experiments produce a range of results for southern high latitudes with the hydrologic budget over Antarctica implying sea level increases of varying magnitude or no change. These results highlight the importance of properly constraining the sea <span class="hlt">ice</span> response to climate perturbations, necessitating the use of more realistic sea <span class="hlt">ice</span> and ocean models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AnGla..46..443P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AnGla..46..443P"><span>River-<span class="hlt">ice</span> break-up/freeze-up: a review of climatic drivers, historical <span class="hlt">trends</span> and future predictions</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Prowse, T. D.; Bonsal, B. R.; Duguay, C. R.; Lacroix, M. P.</p> <p>2007-10-01</p> <p>River <span class="hlt">ice</span> plays a fundamental role in biological, chemical and physical processes that control freshwater regimes of the cold regions. Moreover, it can have enormous economic implications for river-based developments. All such activities and processes can be modified significantly by any changes to river-<span class="hlt">ice</span> thickness, composition or event timing and severity. This paper briefly reviews some of the major hydraulic, mechanical and thermodynamic processes controlling river-<span class="hlt">ice</span> events and how these are influenced by variations in climate. A regional and temporal synthesis is also made of the observed historical <span class="hlt">trends</span> in river-<span class="hlt">ice</span> break-up/freeze-up occurrence from the Eurasian and North American cold regions. This involves assessment of several hydroclimatic variables that have influenced past <span class="hlt">trends</span> and variability in river-<span class="hlt">ice</span> break-up/freeze-up dates including air-temperature indicators (e.g. seasonal temperature, 0°C isotherm dates and various degree-days) and large-scale atmospheric circulation patterns or teleconnections. Implications of future climate change on the timing and severity of river-<span class="hlt">ice</span> events are presented and discussed in relation to the historical <span class="hlt">trends</span>. Attention is drawn to the increasing <span class="hlt">trends</span> towards the occurrence of mid-winter break-up events that can produce especially severe flood conditions but prove to be the most difficult type of event to model and predict.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4742833','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4742833"><span>Evidence for link between modelled <span class="hlt">trends</span> in Antarctic sea <span class="hlt">ice</span> and underestimated westerly wind changes</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Purich, Ariaan; Cai, Wenju; England, Matthew H.; Cowan, Tim</p> <p>2016-01-01</p> <p>Despite global warming, total Antarctic sea <span class="hlt">ice</span> coverage increased over 1979–2013. However, the majority of Coupled Model Intercomparison Project phase 5 models simulate a decline. Mechanisms causing this discrepancy have so far remained elusive. Here we show that weaker <span class="hlt">trends</span> in the intensification of the Southern Hemisphere westerly wind jet simulated by the models may contribute to this disparity. During austral summer, a strengthened jet leads to increased upwelling of cooler subsurface water and strengthened equatorward transport, conducive to increased sea <span class="hlt">ice</span>. As the majority of models underestimate summer jet <span class="hlt">trends</span>, this cooling process is underestimated compared with observations and is insufficient to offset warming in the models. Through the sea <span class="hlt">ice</span>-albedo feedback, models produce a high-latitude surface ocean warming and sea <span class="hlt">ice</span> decline, contrasting the observed net cooling and sea <span class="hlt">ice</span> increase. A realistic simulation of observed wind changes may be crucial for reproducing the recent observed sea <span class="hlt">ice</span> increase. PMID:26842498</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26842498','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26842498"><span>Evidence for link between modelled <span class="hlt">trends</span> in Antarctic sea <span class="hlt">ice</span> and underestimated westerly wind changes.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Purich, Ariaan; Cai, Wenju; England, Matthew H; Cowan, Tim</p> <p>2016-02-04</p> <p>Despite global warming, total Antarctic sea <span class="hlt">ice</span> coverage increased over 1979-2013. However, the majority of Coupled Model Intercomparison Project phase 5 models simulate a decline. Mechanisms causing this discrepancy have so far remained elusive. Here we show that weaker <span class="hlt">trends</span> in the intensification of the Southern Hemisphere westerly wind jet simulated by the models may contribute to this disparity. During austral summer, a strengthened jet leads to increased upwelling of cooler subsurface water and strengthened equatorward transport, conducive to increased sea <span class="hlt">ice</span>. As the majority of models underestimate summer jet <span class="hlt">trends</span>, this cooling process is underestimated compared with observations and is insufficient to offset warming in the models. Through the sea <span class="hlt">ice</span>-albedo feedback, models produce a high-latitude surface ocean warming and sea <span class="hlt">ice</span> decline, contrasting the observed net cooling and sea <span class="hlt">ice</span> increase. A realistic simulation of observed wind changes may be crucial for reproducing the recent observed sea <span class="hlt">ice</span> increase.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.1690J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.1690J"><span>Antarctic Climate Variability: Covariance of Ozone and Sea <span class="hlt">Ice</span> in Atmosphere - Ocean Coupled Model Simulations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jrrar, Amna; Abraham, N. Luke; Pyle, John A.; Holland, David</p> <p>2014-05-01</p> <p>Changes in sea <span class="hlt">ice</span> significantly modulate climate change because of its high reflective and insulating nature. While Arctic Sea <span class="hlt">Ice</span> <span class="hlt">Extent</span> (SIE) shows a negative <span class="hlt">trend</span>. Antarctic SIE shows a weak but positive <span class="hlt">trend</span>, estimated at 0.127 x 106 km2 per decade. The <span class="hlt">trend</span> results from large regional cancellations, more <span class="hlt">ice</span> in the Weddell and the Ross seas, and less <span class="hlt">ice</span> in the Amundsen - Bellingshausen seas. A number of studies had demonstrated that stratospheric ozone depletion has had a major impact on the atmospheric circulation, causing a positive <span class="hlt">trend</span> in the Southern Annular Mode (SAM), which has been linked to the observed positive <span class="hlt">trend</span> in autumn sea <span class="hlt">ice</span> in the Ross Sea. However, other modelling studies show that models forced with prescribed ozone hole simulate decreased sea <span class="hlt">ice</span> in all regions comparative to a control run. A recent study has also shown that stratospheric ozone recovery will mitigate Antarctic sea <span class="hlt">ice</span> loss. To verify this assumed relationship, it is important first to investigate the covariance between ozone's natural (dynamical) variability and Antarctic sea <span class="hlt">ice</span> distribution in pre-industrial climate, to estimate the <span class="hlt">trend</span> due to natural variability. We investigate the relationship between anomalous Antarctic ozone years and the subsequent changes in Antarctic sea <span class="hlt">ice</span> distribution in a multidecadal control simulation using the AO-UMUKCA model. The model has a horizontal resolution of 3.75 X 2.5 degrees in longitude and latitude; and 60 hybrid height levels in the vertical, from the surface up to a height of 84 km. The ocean component is the NEMO ocean model on the ORCA2 tripolar grid, and the sea <span class="hlt">ice</span> model is CICE. We evaluate the model's performance in terms of sea <span class="hlt">ice</span> distribution, and we calculate sea <span class="hlt">ice</span> <span class="hlt">extent</span> <span class="hlt">trends</span> for composites of anomalously low versus anomalously high SH polar ozone column. We apply EOF analysis to the seasonal anomalies of sea <span class="hlt">ice</span> concentration, MSLP, and Z 500, and identify the leading climate modes controlling the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000038175&hterms=balance+sheet&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dbalance%2Bsheet','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000038175&hterms=balance+sheet&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dbalance%2Bsheet"><span>Snowmelt on the Greenland <span class="hlt">Ice</span> Sheet as Derived From Passive Microwave Satellite Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Abdalati, Waleed; Steffen, Konrad</p> <p>1997-01-01</p> <p>The melt <span class="hlt">extent</span> of the snow on the Greenland <span class="hlt">ice</span> sheet is of considerable importance to the <span class="hlt">ice</span> sheet's mass and energy balance, as well as Arctic and global climates. By comparing passive microwave satellite data to field observations, variations in melt <span class="hlt">extent</span> have been detected by establishing melt thresholds in the cross-polarized gradient ratio (XPGR). The XPGR, defined as the normalized difference between the 19-GHz horizontal channel and the 37-GHz vertical channel of the Special Sensor Microwave/Imager (SSM/I), exploits the different effects of snow wetness on different frequencies and polarizations and establishes a distinct melt signal. Using this XPGR melt signal, seasonal and interannual variations in snowmelt <span class="hlt">extent</span> of the <span class="hlt">ice</span> sheet are studied. The melt is found to be most extensive on the western side of the <span class="hlt">ice</span> sheet and peaks in late July. Moreover, there is a notable increasing <span class="hlt">trend</span> in melt area between the years 1979 and 1991 of 4.4% per year, which came to an abrupt halt in 1992 after the eruption of Mt. Pinatubo. A similar <span class="hlt">trend</span> is observed in the temperatures at six coastal stations. The relationship between the warming <span class="hlt">trend</span> and increasing melt <span class="hlt">trend</span> between 1979 and 1991 suggests that a 1 C temperature rise corresponds to an increase in melt area of 73000 sq km, which in general exceeds one standard deviation of the natural melt area variability.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002AGUFM.U72A0009M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002AGUFM.U72A0009M"><span>Recent <span class="hlt">Trends</span> in the Arctic Navigable <span class="hlt">Ice</span> Season and Links to Atmospheric Circulation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Maslanik, J.; Drobot, S.</p> <p>2002-12-01</p> <p>One of the potential effects of Arctic climate warming is an increase in the navigable <span class="hlt">ice</span> season, perhaps resulting in development of the Arctic as a major shipping route. The distance from western North American ports to Europe through the Northwest Passage (NWP) or the Northern Sea Route (NSR) is typically 20 to 60 percent shorter than travel through the Panama Canal, while travel between Europe and the Far East may be reduced by as much as three weeks compared to transport through the Suez Canal. An increase in the navigable <span class="hlt">ice</span> season would also improve commercial opportunities within the Arctic region, such as mineral and oil exploration and tourism, which could potentially expand the economic base of Arctic residents and companies, but which would also have negative environmental impacts. Utilizing daily passive-microwave derived sea <span class="hlt">ice</span> concentrations, <span class="hlt">trends</span> and variability in the Arctic navigable <span class="hlt">ice</span> season are examined from 1979 through 2001. <span class="hlt">Trend</span> analyses suggest large increases in the length of the navigable <span class="hlt">ice</span> season in the Kara and Barents seas, the Sea of Okhotsk, and the Beaufort Sea, with decreases in the length of the navigable <span class="hlt">ice</span> season in the Bering Sea. Interannual variations in the navigable <span class="hlt">ice</span> season largely are governed by fluctuations in low-frequency atmospheric circulation, although the specific annular modes affecting the length of the navigable <span class="hlt">ice</span> season vary by region. In the Beaufort and East Siberian seas, variations in the North Atlantic Oscillation/Arctic Oscillation control the navigable <span class="hlt">ice</span> season, while variations in the East Pacific anomaly play an important role in controlling the navigable <span class="hlt">ice</span> season in the Kara and Barents seas. In Hudson Bay, the Canadian Arctic Archipelago, and Baffin Bay, interannual variations in the navigable <span class="hlt">ice</span> season are strongly related to the Pacific Decadal Oscillation.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active"><span>6</span></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_6 --> <div id="page_7" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="121"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011JGRC..116.3007T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011JGRC..116.3007T"><span><span class="hlt">Trends</span> and variability in summer sea <span class="hlt">ice</span> cover in the Canadian Arctic based on the Canadian <span class="hlt">Ice</span> Service Digital Archive, 1960-2008 and 1968-2008</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tivy, Adrienne; Howell, Stephen E. L.; Alt, Bea; McCourt, Steve; Chagnon, Richard; Crocker, Greg; Carrieres, Tom; Yackel, John J.</p> <p>2011-03-01</p> <p>The Canadian <span class="hlt">Ice</span> Service Digital Archive (CISDA) is a compilation of weekly <span class="hlt">ice</span> charts covering Canadian waters from the early 1960s to present. The main sources of uncertainty in the database are reviewed and the data are validated for use in climate studies before <span class="hlt">trends</span> and variability in summer averaged sea <span class="hlt">ice</span> cover are investigated. These data revealed that between 1968 and 2008, summer sea <span class="hlt">ice</span> cover has decreased by 11.3% ± 2.6% decade-1 in Hudson Bay, 2.9% ± 1.2% decade-1 in the Canadian Arctic Archipelago (CAA), 8.9% ± 3.1% decade-1 in Baffin Bay, and 5.2% ± 2.4% decade-1 in the Beaufort Sea with no significant reductions in multiyear <span class="hlt">ice</span>. Reductions in sea <span class="hlt">ice</span> cover are linked to increases in early summer surface air temperature (SAT); significant increases in SAT were observed in every season and they are consistently greater than the pan-Arctic change by up to ˜0.2°C decade-1. Within the CAA and Baffin Bay, the El Niño-Southern Oscillation index correlates well with multiyear <span class="hlt">ice</span> coverage (positive) and first-year <span class="hlt">ice</span> coverage (negative) suggesting that El Niño episodes precede summers with more multiyear <span class="hlt">ice</span> and less first-year <span class="hlt">ice</span>. Extending the <span class="hlt">trend</span> calculations back to 1960 along the major shipping routes revealed significant decreases in summer sea <span class="hlt">ice</span> coverage ranging between 11% and 15% decade-1 along the route through Hudson Bay and 6% and 10% decade-1 along the southern route of the Northwest Passage, the latter is linked to increases in SAT. Between 1960 and 2008, no significant <span class="hlt">trends</span> were found along the northern western Parry Channel route of the Northwest Passage.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.C43C0628B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.C43C0628B"><span>Assessing the <span class="hlt">Extent</span> of Influence Subglacial Hydrology Has on Dynamic <span class="hlt">Ice</span> Sheet Behavior</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Babonis, G. S.; Csatho, B. M.</p> <p>2012-12-01</p> <p> for generating potentiometric maps for each region of interest. Using these potentiometric maps, along with surficial DEMs, supra- and subglacial routing paths, as well as potential sites for discrete supraglacial hydrologic input sources are identified. Comparison of hydrologic drainage networks with the spatial distribution of recent rapid dynamic changes detected by altimetry allows for the assessment of the <span class="hlt">extent</span> of influence that subglacial hydrology has on <span class="hlt">ice</span> sheet behavior.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23713125','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23713125"><span><span class="hlt">Ice</span> sheets and nitrogen.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wolff, Eric W</p> <p>2013-07-05</p> <p>Snow and <span class="hlt">ice</span> play their most important role in the nitrogen cycle as a barrier to land-atmosphere and ocean-atmosphere exchanges that would otherwise occur. The inventory of nitrogen compounds in the polar <span class="hlt">ice</span> sheets is approximately 260 Tg N, dominated by nitrate in the much larger Antarctic <span class="hlt">ice</span> sheet. <span class="hlt">Ice</span> cores help to inform us about the natural variability of the nitrogen cycle at global and regional scale, and about the <span class="hlt">extent</span> of disturbance in recent decades. Nitrous oxide concentrations have risen about 20 per cent in the last 200 years and are now almost certainly higher than at any time in the last 800 000 years. Nitrate concentrations recorded in Greenland <span class="hlt">ice</span> rose by a factor of 2-3, particularly between the 1950s and 1980s, reflecting a major change in NOx emissions reaching the background atmosphere. Increases in <span class="hlt">ice</span> cores drilled at lower latitudes can be used to validate or constrain regional emission inventories. Background ammonium concentrations in Greenland <span class="hlt">ice</span> show no significant recent <span class="hlt">trend</span>, although the record is very noisy, being dominated by spikes of input from biomass burning events. Neither nitrate nor ammonium shows significant recent <span class="hlt">trends</span> in Antarctica, although their natural variations are of biogeochemical and atmospheric chemical interest. Finally, it has been found that photolysis of nitrate in the snowpack leads to significant re-emissions of NOx that can strongly impact the regional atmosphere in snow-covered areas.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3682747','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3682747"><span><span class="hlt">Ice</span> sheets and nitrogen</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Wolff, Eric W.</p> <p>2013-01-01</p> <p>Snow and <span class="hlt">ice</span> play their most important role in the nitrogen cycle as a barrier to land–atmosphere and ocean–atmosphere exchanges that would otherwise occur. The inventory of nitrogen compounds in the polar <span class="hlt">ice</span> sheets is approximately 260 Tg N, dominated by nitrate in the much larger Antarctic <span class="hlt">ice</span> sheet. <span class="hlt">Ice</span> cores help to inform us about the natural variability of the nitrogen cycle at global and regional scale, and about the <span class="hlt">extent</span> of disturbance in recent decades. Nitrous oxide concentrations have risen about 20 per cent in the last 200 years and are now almost certainly higher than at any time in the last 800 000 years. Nitrate concentrations recorded in Greenland <span class="hlt">ice</span> rose by a factor of 2–3, particularly between the 1950s and 1980s, reflecting a major change in NOx emissions reaching the background atmosphere. Increases in <span class="hlt">ice</span> cores drilled at lower latitudes can be used to validate or constrain regional emission inventories. Background ammonium concentrations in Greenland <span class="hlt">ice</span> show no significant recent <span class="hlt">trend</span>, although the record is very noisy, being dominated by spikes of input from biomass burning events. Neither nitrate nor ammonium shows significant recent <span class="hlt">trends</span> in Antarctica, although their natural variations are of biogeochemical and atmospheric chemical interest. Finally, it has been found that photolysis of nitrate in the snowpack leads to significant re-emissions of NOx that can strongly impact the regional atmosphere in snow-covered areas. PMID:23713125</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1815826M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1815826M"><span>Evaluating Antarctic sea <span class="hlt">ice</span> predictability at seasonal to interannual timescales in global climate models</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Marchi, Sylvain; Fichefet, Thierry; Goosse, Hugues; Zunz, Violette; Tietsche, Steffen; Day, Jonny; Hawkins, Ed</p> <p>2016-04-01</p> <p>Unlike the rapid sea <span class="hlt">ice</span> losses reported in the Arctic, satellite observations show an overall increase in Antarctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> over recent decades. Although many processes have already been suggested to explain this positive <span class="hlt">trend</span>, it remains the subject of current investigations. Understanding the evolution of the Antarctic sea <span class="hlt">ice</span> turns out to be more complicated than for the Arctic for two reasons: the lack of observations and the well-known biases of climate models in the Southern Ocean. Irrespective of those issues, another one is to determine whether the positive <span class="hlt">trend</span> in sea <span class="hlt">ice</span> <span class="hlt">extent</span> would have been predictable if adequate observations and models were available some decades ago. This study of Antarctic sea <span class="hlt">ice</span> predictability is carried out using 6 global climate models (HadGEM1.2, MPI-ESM-LR, GFDL CM3, EC-Earth V2, MIROC 5.2 and ECHAM 6-FESOM) which are all part of the APPOSITE project. These models are used to perform hindcast simulations in a perfect model approach. The predictive skill is estimated thanks to the PPP (Potential Prognostic Predictability) and the ACC (Anomaly Correlation Coefficient). The former is a measure of the uncertainty of the ensemble while the latter assesses the accuracy of the prediction. These two indicators are applied to different variables related to sea <span class="hlt">ice</span>, in particular the total sea <span class="hlt">ice</span> <span class="hlt">extent</span> and the <span class="hlt">ice</span> edge location. This first model intercomparison study about sea <span class="hlt">ice</span> predictability in the Southern Ocean aims at giving a general overview of Antarctic sea <span class="hlt">ice</span> predictability in current global climate models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C54A..08S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C54A..08S"><span>Tropical pacing of Antarctic sea <span class="hlt">ice</span> increase</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schneider, D. P.</p> <p>2015-12-01</p> <p>One reason why coupled climate model simulations generally do not reproduce the observed increase in Antarctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> may be that their internally generated climate variability does not sync with the observed phases of phenomena like the Pacific Decadal Oscillation (PDO) and ENSO. For example, it is unlikely for a free-running coupled model simulation to capture the shift of the PDO from its positive to negative phase during 1998, and the subsequent ~15 year duration of the negative PDO phase. In previously presented work based on atmospheric models forced by observed tropical SSTs and stratospheric ozone, we demonstrated that tropical variability is key to explaining the wind <span class="hlt">trends</span> over the Southern Ocean during the past ~35 years, particularly in the Ross, Amundsen and Bellingshausen Seas, the regions of the largest <span class="hlt">trends</span> in sea <span class="hlt">ice</span> <span class="hlt">extent</span> and <span class="hlt">ice</span> season duration. Here, we extend this idea to coupled model simulations with the Community Earth System Model (CESM) in which the evolution of SST anomalies in the central and eastern tropical Pacific is constrained to match the observations. This ensemble of 10 "tropical pacemaker" simulations shows a more realistic evolution of Antarctic sea <span class="hlt">ice</span> anomalies than does its unconstrained counterpart, the CESM Large Ensemble (both sets of runs include stratospheric ozone depletion and other time-dependent radiative forcings). In particular, the pacemaker runs show that increased sea <span class="hlt">ice</span> in the eastern Ross Sea is associated with a deeper Amundsen Sea Low (ASL) and stronger westerlies over the south Pacific. These circulation patterns in turn are linked with the negative phase of the PDO, characterized by negative SST anomalies in the central and eastern Pacific. The timing of tropical decadal variability with respect to ozone depletion further suggests a strong role for tropical variability in the recent acceleration of the Antarctic sea <span class="hlt">ice</span> <span class="hlt">trend</span>, as ozone depletion stabilized by late 1990s, prior to the most</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1346837','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1346837"><span>A New Discrete Element Sea-<span class="hlt">Ice</span> Model for Earth System Modeling</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Turner, Adrian Keith</p> <p></p> <p>Sea <span class="hlt">ice</span> forms a frozen crust of sea water oating in high-latitude oceans. It is a critical component of the Earth system because its formation helps to drive the global thermohaline circulation, and its seasonal waxing and waning in the high north and Southern Ocean signi cantly affects planetary albedo. Usually 4{6% of Earth's marine surface is covered by sea <span class="hlt">ice</span> at any one time, which limits the exchange of heat, momentum, and mass between the atmosphere and ocean in the polar realms. Snow accumulates on sea <span class="hlt">ice</span> and inhibits its vertical growth, increases its albedo, and contributes to pooledmore » water in melt ponds that darken the Arctic <span class="hlt">ice</span> surface in the spring. <span class="hlt">Ice</span> <span class="hlt">extent</span> and volume are subject to strong seasonal, inter-annual and hemispheric variations, and climatic <span class="hlt">trends</span>, which Earth System Models (ESMs) are challenged to simulate accurately (Stroeve et al., 2012; Stocker et al., 2013). This is because there are strong coupled feedbacks across the atmosphere-<span class="hlt">ice</span>-ocean boundary layers, including the <span class="hlt">ice</span>-albedo feedback, whereby a reduced <span class="hlt">ice</span> cover leads to increased upper ocean heating, further enhancing sea-<span class="hlt">ice</span> melt and reducing incident solar radiation re ected back into the atmosphere (Perovich et al., 2008). A reduction in perennial Arctic sea-<span class="hlt">ice</span> during the satellite era has been implicated in mid-latitude weather changes, including over North America (Overland et al., 2015). Meanwhile, most ESMs have been unable to simulate observed inter-annual variability and <span class="hlt">trends</span> in Antarctic sea-<span class="hlt">ice</span> <span class="hlt">extent</span> during the same period (Gagne et al., 2014).« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29371633','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29371633"><span>Contrasting temperature <span class="hlt">trends</span> across the <span class="hlt">ice</span>-free part of Greenland.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Westergaard-Nielsen, Andreas; Karami, Mojtaba; Hansen, Birger Ulf; Westermann, Sebastian; Elberling, Bo</p> <p>2018-01-25</p> <p>Temperature changes in the Arctic have notable impacts on ecosystem structure and functioning, on soil carbon dynamics, and on the stability of permafrost, thus affecting ecosystem functions and putting man-built infrastructure at risk. Future warming in the Arctic could accelerate important feedbacks in permafrost degradation processes. Therefore it is important to map vulnerable areas most likely to be impacted by temperature changes and at higher risk of degradation, particularly near communities, to assist adaptation to climate change. Currently, these areas are poorly assessed, especially in Greenland. Here we quantify <span class="hlt">trends</span> in satellite-derived land surface temperatures and modelled air temperatures, validated against observations, across the entire <span class="hlt">ice</span>-free Greenland. Focus is on the past 30 years, to characterize significant changes and potentially vulnerable regions at a 1 km resolution. We show that recent temperature <span class="hlt">trends</span> in Greenland vary significantly between seasons and regions and that data with resolutions down to single km 2 are critical to map temperature changes for guidance of further local studies and decision-making. Only a fraction of the <span class="hlt">ice</span>-free Greenland seems vulnerable due to warming when analyzing year 2001-2015, but the most pronounced changes are found in the most populated parts of Greenland. As Greenland represents important gradients of north/south coast/inland/distance to large <span class="hlt">ice</span> sheets, the conclusions are also relevant in an upscaling to greater Arctic areas.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19870060024&hterms=Parkinsons+circulation&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DParkinsons%2Bcirculation','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19870060024&hterms=Parkinsons+circulation&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DParkinsons%2Bcirculation"><span>On the relationship between atmospheric circulation and the fluctuations in the sea <span class="hlt">ice</span> <span class="hlt">extents</span> of the Bering and Okhotsk Seas</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cavalieri, D. J.; Parkinson, C. L.</p> <p>1987-01-01</p> <p>The influence of the hemispheric atmospheric circulation on the sea <span class="hlt">ice</span> covers of the Bering Sea and the Sea of Okhotsk is examined using data obtained with the Nimbus 5 electrically scanning microwave radiometer for the four winters of the 1973-1976 period. The 3-day averaged sea <span class="hlt">ice</span> <span class="hlt">extent</span> data were used to establish periods for which there is an out-of-phase relationship between fluctuations of the two <span class="hlt">ice</span> covers. A comparison of the sea-level atmospheric pressure field with the seasonal, interannual, and short-term sea <span class="hlt">ice</span> fluctuations reveal an association between changes in the phase and the amplitude of the long waves in the atmosphere and advance and retreat of Arctic <span class="hlt">ice</span> covers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25225380','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25225380"><span>Leveraging scientific credibility about Arctic sea <span class="hlt">ice</span> <span class="hlt">trends</span> in a polarized political environment.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Jamieson, Kathleen Hall; Hardy, Bruce W</p> <p>2014-09-16</p> <p>This work argues that, in a polarized environment, scientists can minimize the likelihood that the audience's biased processing will lead to rejection of their message if they not only eschew advocacy but also, convey that they are sharers of knowledge faithful to science's way of knowing and respectful of the audience's intelligence; the sources on which they rely are well-regarded by both conservatives and liberals; and the message explains how the scientist arrived at the offered conclusion, is conveyed in a visual form that involves the audience in drawing its own conclusions, and capsulizes key inferences in an illustrative analogy. A pilot experiment raises the possibility that such a leveraging-involving-visualizing-analogizing message structure can increase acceptance of the scientific claims about the downward cross-decade <span class="hlt">trend</span> in Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> and elicit inferences consistent with the scientific consensus on climate change among conservatives exposed to misleadingly selective data in a partisan news source.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4183171','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4183171"><span>Leveraging scientific credibility about Arctic sea <span class="hlt">ice</span> <span class="hlt">trends</span> in a polarized political environment</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Hall Jamieson, Kathleen; Hardy, Bruce W.</p> <p>2014-01-01</p> <p>This work argues that, in a polarized environment, scientists can minimize the likelihood that the audience’s biased processing will lead to rejection of their message if they not only eschew advocacy but also, convey that they are sharers of knowledge faithful to science’s way of knowing and respectful of the audience’s intelligence; the sources on which they rely are well-regarded by both conservatives and liberals; and the message explains how the scientist arrived at the offered conclusion, is conveyed in a visual form that involves the audience in drawing its own conclusions, and capsulizes key inferences in an illustrative analogy. A pilot experiment raises the possibility that such a leveraging–involving–visualizing–analogizing message structure can increase acceptance of the scientific claims about the downward cross-decade <span class="hlt">trend</span> in Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> and elicit inferences consistent with the scientific consensus on climate change among conservatives exposed to misleadingly selective data in a partisan news source. PMID:25225380</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21D1156T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21D1156T"><span>Seasonal regional forecast of the minimum sea <span class="hlt">ice</span> <span class="hlt">extent</span> in the LapteV Sea</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tremblay, B.; Brunette, C.; Newton, R.</p> <p>2017-12-01</p> <p>Late winter anomaly of sea <span class="hlt">ice</span> export from the peripheral seas of the Atctic Ocean was found to be a useful predictor for the minimum sea <span class="hlt">ice</span> <span class="hlt">extent</span> (SIE) in the Arctic Ocean (Williams et al., 2017). In the following, we present a proof of concept for a regional seasonal forecast of the min SIE for the Laptev Sea based on late winter coastal divergence quantified using a Lagrangian <span class="hlt">Ice</span> Tracking System (LITS) forced with satellite derived sea-<span class="hlt">ice</span> drifts from the Polar Pathfinder. Following Nikolaeva and Sesterikov (1970), we track an imaginary line just offshore of coastal polynyas in the Laptev Sea from December of the previous year to May 1 of the following year using LITS. Results show that coastal divergence in the Laptev Sea between February 1st and May 1st is best correlated (r = -0.61) with the following September minimum SIE in accord with previous results from Krumpen et al. (2013, for the Laptev Sea) and Williams et a. (2017, for the pan-Arctic). This gives a maximum seasonal predictability of Laptev Sea min SIE anomalies from observations of approximately 40%. Coastal <span class="hlt">ice</span> divergence leads to formation of thinner <span class="hlt">ice</span> that melts earlier in early summer, hence creating areas of open water that have a lower albedo and trigger an <span class="hlt">ice</span>-albedo feedback. In the Laptev Sea, we find that anomalies of coastal divergence in late winter are amplified threefold to result in the September SIE. We also find a correlation coefficient r = 0.49 between February-March-April (FMA) anomalies of coastal divergence with the FMA averaged AO index. Interestingly, the correlation is stronger, r = 0.61, when comparing the FMA coastal divergence anomalies to the DJFMA averaged AO index. It is hypothesized that the AO index at the beginning of the winter (and the associated anomalous sea <span class="hlt">ice</span> export) also contains information that impact the magnitude of coastal divergence opening later in the winter. Our approach differs from previous approaches (e.g. Krumpen et al and Williams et al</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GMD....10.3105P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GMD....10.3105P"><span>Sea-<span class="hlt">ice</span> evaluation of NEMO-Nordic 1.0: a NEMO-LIM3.6-based ocean-sea-<span class="hlt">ice</span> model setup for the North Sea and Baltic Sea</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pemberton, Per; Löptien, Ulrike; Hordoir, Robinson; Höglund, Anders; Schimanke, Semjon; Axell, Lars; Haapala, Jari</p> <p>2017-08-01</p> <p>The Baltic Sea is a seasonally <span class="hlt">ice</span>-covered marginal sea in northern Europe with intense wintertime ship traffic and a sensitive ecosystem. Understanding and modeling the evolution of the sea-<span class="hlt">ice</span> pack is important for climate effect studies and forecasting purposes. Here we present and evaluate the sea-<span class="hlt">ice</span> component of a new NEMO-LIM3.6-based ocean-sea-<span class="hlt">ice</span> setup for the North Sea and Baltic Sea region (NEMO-Nordic). The setup includes a new depth-based fast-<span class="hlt">ice</span> parametrization for the Baltic Sea. The evaluation focuses on long-term statistics, from a 45-year long hindcast, although short-term daily performance is also briefly evaluated. We show that NEMO-Nordic is well suited for simulating the mean sea-<span class="hlt">ice</span> <span class="hlt">extent</span>, concentration, and thickness as compared to the best available observational data set. The variability of the annual maximum Baltic Sea <span class="hlt">ice</span> <span class="hlt">extent</span> is well in line with the observations, but the 1961-2006 <span class="hlt">trend</span> is underestimated. Capturing the correct <span class="hlt">ice</span> thickness distribution is more challenging. Based on the simulated <span class="hlt">ice</span> thickness distribution we estimate the undeformed and deformed <span class="hlt">ice</span> thickness and concentration in the Baltic Sea, which compares reasonably well with observations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160001390','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160001390"><span>Revisiting the Potential of Melt Pond Fraction as a Predictor for the Seasonal Arctic Sea <span class="hlt">Ice</span> <span class="hlt">Extent</span> Minimum</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Liu, Jiping; Song, Mirong; Horton, Radley M.; Hu, Yongyun</p> <p>2015-01-01</p> <p>The rapid change in Arctic sea <span class="hlt">ice</span> in recent decades has led to a rising demand for seasonal sea <span class="hlt">ice</span> prediction. A recent modeling study that employed a prognostic melt pond model in a stand-alone sea <span class="hlt">ice</span> model found that September Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> can be accurately predicted from the melt pond fraction in May. Here we show that satellite observations show no evidence of predictive skill in May. However, we find that a significantly strong relationship (high predictability) first emerges as the melt pond fraction is integrated from early May to late June, with a persistent strong relationship only occurring after late July. Our results highlight that late spring to mid summer melt pond information is required to improve the prediction skill of the seasonal sea <span class="hlt">ice</span> minimum. Furthermore, satellite observations indicate a much higher percentage of melt pond formation in May than does the aforementioned model simulation, which points to the need to reconcile model simulations and observations, in order to better understand key mechanisms of melt pond formation and evolution and their influence on sea <span class="hlt">ice</span> state.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/16826993','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/16826993"><span><span class="hlt">Trends</span> in sea <span class="hlt">ice</span> cover within habitats used by bowhead whales in the western Arctic.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Moore, Sue E; Laidre, Kristin L</p> <p>2006-06-01</p> <p>We examined <span class="hlt">trends</span> in sea <span class="hlt">ice</span> cover between 1979 and 2002 in four months (March, June, September, and November) for four large (approximately 100,000 km2) and 12 small (approximately 10,000 km2) regions of the western Arctic in habitats used by bowhead whales (Balaena mysticetus). Variation in open water with year was significant in all months except March, but interactions between region and year were not. Open water increased in both large and small regions, but <span class="hlt">trends</span> were weak with least-squares regression accounting for < or =34% of the total variation. In large regions, positive <span class="hlt">trends</span> in open water were strongest in September. Linear fits were poor, however, even in the East Siberian, Chukchi, and Beaufort seas, where basin-scale analyses have emphasized dramatic sea <span class="hlt">ice</span> loss. Small regions also showed weak positive <span class="hlt">trends</span> in open water and strong interannual variability. Open water increased consistently in five small regions where bowhead whales have been observed feeding or where oceanographic models predict prey entrainment, including: (1) June, along the northern Chukotka coast, near Wrangel Island, and along the Beaufort slope; (2) September, near Wrangel Island, the Barrow Arc, and the Chukchi Borderland; and (3) November, along the Barrow Arc. Conversely, there was very little consistent change in sea <span class="hlt">ice</span> cover in four small regions considered winter refugia for bowhead whales in the northern Bering Sea, nor in two small regions that include the primary springtime migration corridor in the Chukchi Sea. The effects of sea <span class="hlt">ice</span> cover on bowhead whale prey availability are unknown but can be modeled via production and advection pathways. Our conceptual model suggests that reductions in sea <span class="hlt">ice</span> cover will increase prey availability along both pathways for this population. This analysis elucidates the variability inherent in the western Arctic marine ecosystem at scales relevant to bowhead whales and contrasts basin-scale depictions of extreme sea <span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20070017895','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20070017895"><span>Abrupt Decline in the Arctic Winter Sea <span class="hlt">Ice</span> Cover</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Josefino C.</p> <p>2007-01-01</p> <p>Maximum <span class="hlt">ice</span> <span class="hlt">extents</span> in the Arctic in 2005 and 2006 have been observed to be significantly lower (by about 6%) than the average of those of previous years starting in 1979. Since the winter maxima had been relatively stable with the <span class="hlt">trend</span> being only about -1.5% per decade (compared to about -10% per decade for the perennial <span class="hlt">ice</span> area), this is a significant development since signals from greenhouse warming are expected to be most prominent in winter. Negative <span class="hlt">ice</span> anomalies are shown to be dominant in 2005 and 2006 especially in the Arctic basin and correlated with winds and surface temperature anomalies during the same period. Progressively increasing winter temperatures in the central Arctic starting in 1997 is observed with significantly higher rates of increase in 2005 and 2006. The Atlantic Oscillation (AO) indices correlate weakly with the sea <span class="hlt">ice</span> and surface temperature anomaly data but may explain the recent shift in the perennial <span class="hlt">ice</span> cover towards the western region. Results suggest that the <span class="hlt">trend</span> in winter <span class="hlt">ice</span> is finally in the process of catching up with that of the summer <span class="hlt">ice</span> cover.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5459986','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5459986"><span>Sea-level records from the U.S. mid-Atlantic constrain Laurentide <span class="hlt">Ice</span> Sheet <span class="hlt">extent</span> during Marine Isotope Stage 3</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Pico, T; Creveling, J. R.; Mitrovica, J. X.</p> <p>2017-01-01</p> <p>The U.S. mid-Atlantic sea-level record is sensitive to the history of the Laurentide <span class="hlt">Ice</span> Sheet as the coastline lies along the <span class="hlt">ice</span> sheet's peripheral bulge. However, paleo sea-level markers on the present-day shoreline of Virginia and North Carolina dated to Marine Isotope Stage (MIS) 3, from 50 to 35 ka, are surprisingly high for this glacial interval, and remain unexplained by previous models of <span class="hlt">ice</span> age adjustment or other local (for example, tectonic) effects. Here, we reconcile this sea-level record using a revised model of glacial isostatic adjustment characterized by a peak global mean sea level during MIS 3 of approximately −40 m, and far less <span class="hlt">ice</span> volume within the eastern sector of the Laurentide <span class="hlt">Ice</span> Sheet than traditional reconstructions for this interval. We conclude that the Laurentide <span class="hlt">Ice</span> Sheet experienced a phase of very rapid growth in the 15 kyr leading into the Last Glacial Maximum, thus highlighting the potential of mid-field sea-level records to constrain areal <span class="hlt">extent</span> of <span class="hlt">ice</span> cover during glacial intervals with sparse geological observables. PMID:28555637</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21G1187P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21G1187P"><span>Spatial and Temporal Means and Variability of Arctic Sea <span class="hlt">Ice</span> Climate Indicators from Satellite Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Peng, G.; Meier, W.; Bliss, A. C.; Steele, M.; Dickinson, S.</p> <p>2017-12-01</p> <p>Arctic sea <span class="hlt">ice</span> has been undergoing rapid and accelerated loss since satellite-based measurements became available in late 1970s, especially the summer <span class="hlt">ice</span> coverage. For the Arctic as a whole, the long-term <span class="hlt">trend</span> for the annual sea <span class="hlt">ice</span> <span class="hlt">extent</span> (SIE) minimum is about -13.5±2.93 % per decade change relative to the 1979-2015 climate average, while the <span class="hlt">trends</span> of the annual SIE minimum for the local regions can range from 0 to up to -42 % per decade. This presentation aims to examine and baseline spatial and temporal means and variability of Arctic sea <span class="hlt">ice</span> climate indicators, such as the annual SIE minimum and maximum, snow/<span class="hlt">ice</span> melt onset, etc., from a consistent, inter-calibrated, long-term time series of remote sensing sea <span class="hlt">ice</span> data for understanding regional vulnerability and monitoring <span class="hlt">ice</span> state for climate adaptation and risk mitigation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33C1210S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33C1210S"><span>Towards development of an operational snow on sea <span class="hlt">ice</span> product</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stroeve, J.; Liston, G. E.; Barrett, A. P.; Tschudi, M. A.; Stewart, S.</p> <p>2017-12-01</p> <p>Sea <span class="hlt">ice</span> has been visibly changing over the past couple of decades; most notably the annual minimum <span class="hlt">extent</span> which has shown a distinct downward, and recently accelerating, <span class="hlt">trend</span>. September mean sea <span class="hlt">ice</span> <span class="hlt">extent</span> was over 7×106 km2 in the 1980's, but has averaged less than 5×106 km2 in the last decade. Should this loss continue, there will be wide-ranging impacts on marine ecosystems, coastal communities, prospects for resource extraction and marine activity, and weather conditions in the Arctic and beyond. While changes in the spatial <span class="hlt">extent</span> of sea <span class="hlt">ice</span> have been routinely monitored since the 1970s, less is known about how the thickness of the <span class="hlt">ice</span> cover has changed. While estimates of <span class="hlt">ice</span> thickness across the Arctic Ocean have become available over the past 20 years based on data from ERS-1/2, Envisat, ICESat, CryoSat-2 satellites and Operation <span class="hlt">Ice</span>Bridge aircraft campaigns, the variety of these different measurement approaches, sensor technologies and spatial coverage present formidable challenges. Key among these is that measurement techniques do not measure <span class="hlt">ice</span> thickness directly - retrievals also require snow depth and density. Towards that end, a sophisticated snow accumulation model is tested in a Lagrangian framework to map daily snow depths across the Arctic sea <span class="hlt">ice</span> cover using atmospheric reanalysis data as input. Accuracy of the snow accumulation is assessed through comparison with Operation <span class="hlt">Ice</span>Bridge data and <span class="hlt">ice</span> mass balance buoys (IMBs). Impacts on <span class="hlt">ice</span> thickness retrievals are further discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.5977S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.5977S"><span><span class="hlt">Trends</span> in <span class="hlt">ice</span> formation at Lake Neusiedl since 1931 and large-scale oscillation patterns</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Soja, Anna-Maria; Maracek, Karl; Soja, Gerhard</p> <p>2013-04-01</p> <p><span class="hlt">Ice</span> formation at Lake Neusiedl (Neusiedler See, Fertitó), a shallow steppe lake (area 320 km2, mean depth 1.2 m) at the border of Austria/Hungary, is of ecological and economic importance. <span class="hlt">Ice</span> sailing and skating help to keep a touristic off-season alive. Reed harvest to maintain the ecological function of the reed belt (178 km2) is facilitated when lake surface is frozen. Changes in <span class="hlt">ice</span> formation were analysed in the frame of the EULAKES-project (European Lakes under Environmental Stressors, www.eulakes.eu), financed by the Central Europe Programme of the EU. Data records of <span class="hlt">ice</span>-on, <span class="hlt">ice</span> duration and <span class="hlt">ice</span>-off at Lake Neusiedl starting with the year 1931, and air temperature (nearby monitoring station Eisenstadt - Sopron (HISTALP database and ZAMG)) were used to investigate nearly 80 winters. Additionally, influences of 8 teleconnection patterns, i.e. the Atlantic Multidecadal Oscillation (AMO), the East Atlantic pattern (EAP), the East Atlantic/West Russia pattern (EA/WR), the Eastern Mediterranean Pattern (EMP), the Mediterranean Oscillation (MO) for Algiers and Cairo, and for Israel and Gibraltar, resp., the North Atlantic Oscillation (NAO) and the Scandinavia pattern (SCA) were assessed. <span class="hlt">Ice</span> cover of Lake Neusiedl showed a high variability between the years (mean duration 71±27 days). Significant <span class="hlt">trends</span> for later <span class="hlt">ice</span>-on (p=0.02), shorter <span class="hlt">ice</span> duration (p=0.07) and earlier <span class="hlt">ice</span>-off (p=0.02) for the period 1931-2011 were found by regression analysis and <span class="hlt">trend</span> analysis tests. On an average, freezing of Lake Neusiedl started 2 days later per decade and <span class="hlt">ice</span> melting began 2 days earlier per decade. Close relationships between mean air temperature and <span class="hlt">ice</span> formation could be found: <span class="hlt">ice</span>-on showed a dependency on summer (R=+0.28) and autumn air temperatures (R=+0.51), <span class="hlt">ice</span> duration and <span class="hlt">ice</span> off was related to autumn (R=-0.36 and -0.24), winter (R=-0.73 and -0.61) and concurrent spring air temperatures (R=-0.44). Increases of air temperature by 1° C caused an 8.4 days later</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_7 --> <div id="page_8" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="141"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170007832&hterms=sensors&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsensors','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170007832&hterms=sensors&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsensors"><span>Impact of MODIS Sensor Calibration Updates on Greenland <span class="hlt">Ice</span> Sheet Surface Reflectance and Albedo <span class="hlt">Trends</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Casey, Kimberly A.; Polashenski, Chris M.; Chen, Justin; Tedesco, Marco</p> <p>2017-01-01</p> <p>We evaluate Greenland <span class="hlt">Ice</span> Sheet (GrIS) surface reflectance and albedo <span class="hlt">trends</span> using the newly released Collection 6 (C6) MODIS (Moderate Resolution Imaging Spectroradiometer) products over the period 2001-2016. We find that the correction of MODIS sensor degradation provided in the new C6 data products reduces the magnitude of the surface reflectance and albedo decline <span class="hlt">trends</span> obtained from previous MODIS data (i.e., Collection 5, C5). Collection 5 and 6 data product analysis over GrIS is characterized by surface (i.e., wet vs. dry) and elevation (i.e., 500-2000 m, 2000 m and greater) conditions over the summer season from 1 June to 31 August. Notably, the visible-wavelength declining reflectance <span class="hlt">trends</span> identified in several bands of MODIS C5 data from previous studies are only slightly detected at reduced magnitude in the C6 versions over the dry snow area. Declining albedo in the wet snow and <span class="hlt">ice</span> area remains over the MODIS record in the C6 product, albeit at a lower magnitude than obtained using C5 data. Further analyses of C6 spectral reflectance <span class="hlt">trends</span> show both reflectance increases and decreases in select bands and regions, suggesting that several competing processes are contributing to Greenland <span class="hlt">Ice</span> Sheet albedo change. Investigators using MODIS data for other ocean, atmosphere and/or land analyses are urged to consider similar re-examinations of <span class="hlt">trends</span> previously established using C5 data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C33E0858T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C33E0858T"><span>Multi-resolution Changes in the Spatial <span class="hlt">Extent</span> of Perennial Arctic Alpine Snow and <span class="hlt">Ice</span> Fields with Potential Archaeological Significance in the Central Brooks Range, Alaska</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tedesche, M. E.; Freeburg, A. K.; Rasic, J. T.; Ciancibelli, C.; Fassnacht, S. R.</p> <p>2015-12-01</p> <p>Perennial snow and <span class="hlt">ice</span> fields could be an important archaeological and paleoecological resource for Gates of the Arctic National Park and Preserve in the central Brooks Range mountains of Arctic Alaska. These features may have cultural significance, as prehistoric artifacts may be frozen within the snow and <span class="hlt">ice</span>. Globally significant discoveries have been made recently as ancient artifacts and animal dung have been found in melting alpine snow and <span class="hlt">ice</span> patches in the Southern Yukon and Northwest Territories in Canada, the Wrangell mountains in Alaska, as well as in other areas. These sites are melting rapidly, which results in quick decay of biological materials. The summer of 2015 saw historic lows in year round snow cover <span class="hlt">extent</span> for most of Alaska. Twenty mid to high elevation sites, including eighteen perennial snow and <span class="hlt">ice</span> fields, and two glaciers, were surveyed in July 2015 to quantify their areal <span class="hlt">extent</span>. This survey was accomplished by using both low flying aircraft (helicopter), as well as with on the ground in-situ (by foot) measurements. By helicopter, visual surveys were conducted within tens of meters of the surface. Sites visited by foot were surveyed for <span class="hlt">extent</span> of snow and <span class="hlt">ice</span> coverage, melt water hydrologic parameters and chemistry, and initial estimates of depths and delineations between snow, firn, and <span class="hlt">ice</span>. Imagery from both historic aerial photography and from 5m resolution IKONOS satellite information were correlated with the field data. Initial results indicate good agreement in permanent snow and <span class="hlt">ice</span> cover between field surveyed data and the 1985 to 2011 Landsat imagery-based Northwest Alaska snow persistence map created by Macander et al. (2015). The most deviation between the Macander et al. model and the field surveyed results typically occurred as an overestimate of perennial <span class="hlt">extent</span> on the steepest aspects. These differences are either a function of image classification or due to accelerated ablation rates in perennial snow and <span class="hlt">ice</span> coverage</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy...49.1813H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy...49.1813H"><span>Sensitivity of Antarctic sea <span class="hlt">ice</span> to the Southern Annular Mode in coupled climate models</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Holland, Marika M.; Landrum, Laura; Kostov, Yavor; Marshall, John</p> <p>2017-09-01</p> <p>We assess the sea <span class="hlt">ice</span> response to Southern Annular Mode (SAM) anomalies for pre-industrial control simulations from the Coupled Model Intercomparison Project (CMIP5). Consistent with work by Ferreira et al. (J Clim 28:1206-1226, 2015. doi: 10.1175/JCLI-D-14-00313.1), the models generally simulate a two-timescale response to positive SAM anomalies, with an initial increase in <span class="hlt">ice</span> followed by an eventual sea <span class="hlt">ice</span> decline. However, the models differ in the cross-over time at which the change in <span class="hlt">ice</span> response occurs, in the overall magnitude of the response, and in the spatial distribution of the response. Late twentieth century Antarctic sea <span class="hlt">ice</span> <span class="hlt">trends</span> in CMIP5 simulations are related in part to different modeled responses to SAM variability acting on different time-varying transient SAM conditions. This explains a significant fraction of the spread in simulated late twentieth century southern hemisphere sea <span class="hlt">ice</span> <span class="hlt">extent</span> <span class="hlt">trends</span> across the model simulations. Applying the modeled sea <span class="hlt">ice</span> response to SAM variability but driven by the observed record of SAM suggests that variations in the austral summer SAM, which has exhibited a significant positive <span class="hlt">trend</span>, have driven a modest sea <span class="hlt">ice</span> decrease. However, additional work is needed to narrow the considerable model uncertainty in the climate response to SAM variability and its implications for 20th-21st century <span class="hlt">trends</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A21Q..08F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A21Q..08F"><span>Response of Antarctic sea surface temperature and sea <span class="hlt">ice</span> to ozone depletion</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ferreira, D.; Gnanadesikan, A.; Kostov, Y.; Marshall, J.; Seviour, W.; Waugh, D.</p> <p>2017-12-01</p> <p>The influence of the Antarctic ozone hole extends all the way from the stratosphere through the troposphere down to the surface, with clear signatures on surface winds, and SST during summer. In this talk we discuss the impact of these changes on the ocean circulation and sea <span class="hlt">ice</span> state. We are notably motivated by the observed cooling of the surface Southern Ocean and associated increase in Antarctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> since the 1970s. These <span class="hlt">trends</span> are not reproduced by CMIP5 climate models, and the underlying mechanism at work in nature and the models remain unexplained. Did the ozone hole contribute to the observed <span class="hlt">trends</span>?Here, we review recent advances toward answering these issues using "abrupt ozone depletion" experiments. The ocean and sea <span class="hlt">ice</span> response is rather complex, comprising two timescales: a fast ( 1-2y) cooling of the surface ocean and sea <span class="hlt">ice</span> cover increase, followed by a slower warming <span class="hlt">trend</span>, which, depending on models, flip the sign of the SST and sea <span class="hlt">ice</span> responses on decadal timescale. Although the basic mechanism seems robust, comparison across climate models reveal large uncertainties in the timescales and amplitude of the response to the <span class="hlt">extent</span> that even the sign of the ocean and sea <span class="hlt">ice</span> response to ozone hole and recovery remains unconstrained. After briefly describing the dynamics and thermodynamics behind the two-timescale response, we will discuss the main sources of uncertainties in the modeled response, namely cloud effects and air-sea heat exchanges, surface wind stress response and ocean eddy transports. Finally, we will consider the implications of our results on the ability of coupled climate models to reproduce observed Southern Ocean changes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C24A..01N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C24A..01N"><span>Arctic and Antarctic Sea <span class="hlt">Ice</span> Changes and Impacts (Invited)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nghiem, S. V.</p> <p>2013-12-01</p> <p>The <span class="hlt">extent</span> of springtime Arctic perennial sea <span class="hlt">ice</span>, important to preconditioning summer melt and to polar sunrise photochemistry, continues its precipitous reduction in the last decade marked by a record low in 2012, as the Bromine, Ozone, and Mercury Experiment (BROMEX) was conducted around Barrow, Alaska, to investigate impacts of sea <span class="hlt">ice</span> reduction on photochemical processes, transport, and distribution in the polar environment. In spring 2013, there was further loss of perennial sea <span class="hlt">ice</span>, as it was not observed in the ocean region adjacent to the Alaskan north coast, where there was a stretch of perennial sea <span class="hlt">ice</span> in 2012 in the Beaufort Sea and Chukchi Sea. In contrast to the rapid and extensive loss of sea <span class="hlt">ice</span> in the Arctic, Antarctic sea <span class="hlt">ice</span> has a <span class="hlt">trend</span> of a slight increase in the past three decades. Given the significant variability in time and in space together with uncertainties in satellite observations, the increasing <span class="hlt">trend</span> of Antarctic sea <span class="hlt">ice</span> may arguably be considered as having a low confidence level; however, there was no overall reduction of Antarctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> anywhere close to the decreasing rate of Arctic sea <span class="hlt">ice</span>. There exist publications presenting various factors driving changes in Arctic and Antarctic sea <span class="hlt">ice</span>. After a short review of these published factors, new observations and atmospheric, oceanic, hydrological, and geological mechanisms contributed to different behaviors of sea <span class="hlt">ice</span> changes in the Arctic and Antarctic are presented. The contribution from of hydrologic factors may provide a linkage to and enhance thermal impacts from lower latitudes. While geological factors may affect the sensitivity of sea <span class="hlt">ice</span> response to climate change, these factors can serve as the long-term memory in the system that should be exploited to improve future projections or predictions of sea <span class="hlt">ice</span> changes. Furthermore, similarities and differences in chemical impacts of Arctic and Antarctic sea <span class="hlt">ice</span> changes are discussed. Understanding sea <span class="hlt">ice</span> changes and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C43B0760A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C43B0760A"><span>Do Atmospheric Circulation Patterns Explain Variability and <span class="hlt">Trends</span> in The Seasonality of Oulu-Hailuoto <span class="hlt">Ice</span> Road in Northern Finland?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ahmadi, B.; Kiani, S.; Irannezhad, M.; Ronkanen, A. K.; Kløve, B.; Moradkhani, H.</p> <p>2016-12-01</p> <p>In cold climate regions, <span class="hlt">ice</span> roads are engineered as temporary winter transportation routes on the frozen seas, lakes and rivers. The <span class="hlt">ice</span> road season parameters (start, end and length) are principally dependent on the thickness of <span class="hlt">ice</span>, which is naturally controlled by temperature in terms of freezing (FDDs) and thawing (TDDs) degree-days. It has been shown that the variations in FDDs and TDDs are influenced by large-scale atmospheric circulation patterns (ACPs). Therefore, this study aims at understanding the role of ACPs in variability and <span class="hlt">trends</span> in the seasonality of Oulu-Hailuoto <span class="hlt">ice</span> road in northern Finland during 1974-2009. The Mann-Kendall nonparametric <span class="hlt">trend</span> test determined significant shortening in the length of <span class="hlt">ice</span> road season over the study period of 1974-2009, which can be attributed to later start and earlier end days. In the study area, the maximum <span class="hlt">ice</span> thickness of the Baltic Sea also showed significant declines over time. Such sea <span class="hlt">ice</span> thinning can be associated with the wintertime temperature warming manifested by the decreasing <span class="hlt">trend</span> found in the cumulative FDD during October-January in the water year (September-August). The increased cumulative TDD during February-April also reflects warmer climate in spring, which has resulted in the earlier end day of the <span class="hlt">ice</span> road season. Measuring the Spearman's rank correlation identified the Arctic Oscillation as the most significant ACP influencing variations in the cumulative FDD, and accordingly in the <span class="hlt">ice</span> thickness and the start day. However, the cumulative TDD during February-April shows significant positive correlation with the East Atlantic (EA) pattern, which appears to control the end day of the Oulu-Hailuoto <span class="hlt">ice</span> road season.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040171463&hterms=SSM&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DSSM','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040171463&hterms=SSM&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DSSM"><span>Analysis of Summer 2002 Melt <span class="hlt">Extent</span> on the Greenland <span class="hlt">Ice</span> Sheet using MODIS and SSM/I Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Williams, Richard S., Jr.; Steffen, Konrad; Chien, Y. L.; Foster, James L.; Robinson, David A.; Riggs, George A.</p> <p>2004-01-01</p> <p>Previous work has shown that the summer of 2002 had the greatest area of snow melt <span class="hlt">extent</span> on the Greenland <span class="hlt">ice</span> sheet ever recorded using passive-microwave data. In this paper, we compare the 0 degree isotherm derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument, with Special Sensor Microwave/Imager (SSM/I)-derived melt, at the time of the maximum melt <span class="hlt">extent</span> in 2002. To validate the MODIS-derived land-surface temperatures (LSTs), we compared the MODIS LSTs with air temperatures from nine stations (using 11 different data points) and found that they agreed to within 2.3 plus or minus 2.09 C, with station temperatures consistently lower than the MODIS LSTs. According to the MODIS LST, the maximum surface melt extended to approximately 2300 m in southern Greenland; while the SSM/I measurements showed that the maximum melt extended to nearly 2700 m in southeastern Greenland. The MODIS and SSM/I data are complementary in providing detailed information about the progression of surface and near-surface melt on the Greenland <span class="hlt">ice</span> sheet.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040171217','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040171217"><span>Analysis of Summer 2002 Melt <span class="hlt">Extent</span> on the Greenland <span class="hlt">Ice</span> Sheet using MODIS and SSM/I Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Williams, Richard S.; Steffen, Konrad; Chien, Janet Y. L.</p> <p>2004-01-01</p> <p>Previous work has shown that the summer of 2002 had the greatest area of snow melt <span class="hlt">extent</span> on the Greenland <span class="hlt">ice</span> sheet ever recorded using passive-microwave data. In this paper, we compare the 0 deg. isotherm derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument, with Special Sensor Microwave/Imager (SSM/I)-derived melt, at the time of the maximum melt <span class="hlt">extent</span> in 2002. To validate the MODIS derived land-surface temperatures (LSTs), we compared the MODIS LSTs with air temperatures from nine stations (using 11 different data points) and found that they agreed to within 2.3 +/- 2.09 C, with station temperatures consistently lower than the MODIS LSTs. According to the MODIS LST, the maximum surface melt extended to approx. 2300 m in southern Greenland; while the SSM/I measurements showed that the maximum melt extended to nearly 2700 m in southeastern Greenland. The MODIS and SSM/I data are complementary in providing detailed information about the progression of surface and near- surface melt on the Greenland <span class="hlt">ice</span> sheet.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70026165','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70026165"><span>Analysis of summer 2002 melt <span class="hlt">extent</span> on the Greenland <span class="hlt">ice</span> sheet using MODIS and SSM/I data</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Hall, D.K.; Williams, R.S.; Steffen, K.; Chien, Janet Y.L.</p> <p>2004-01-01</p> <p>Previous work has shown that the summer of 2002 had the greatest area of snow melt <span class="hlt">extent</span> on the Greenland <span class="hlt">ice</span> sheet ever recorded using passive-microwave data. In this paper, we compare the 0?? isotherm derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument, with Special Sensor Microwave/Imager (SSM/I)-derived melt, at the time of the maximum melt <span class="hlt">extent</span> in 2002. To validate the MODIS-derived land-surface temperatures (LSTs), we compared the MODIS LSTs with air temperatures from nine stations (using 11 different data points) and found that they agreed to within 2.3??2.09??C, with station temperatures consistently lower than the MODIS LSTs. According to the MODIS LST, the maximum surface melt extended to ???2300 m in southern Greenland; while the SSM/I measurements showed that the maximum melt extended to nearly 2700 m in southeastern Greenland. The MODIS and SSM/I data are complementary in providing detailed information about the progression of surface and near-surface melt on the Greenland <span class="hlt">ice</span> sheet.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70191437','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70191437"><span>Analysis of summer 2002 melt <span class="hlt">extent</span> on the Greenland <span class="hlt">ice</span> sheet using MODIS and SSM/I data</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Hall, D. K.; Williams, R.S.; Steffen, K.; Chien, Janet Y.L.</p> <p>2004-01-01</p> <p>Previous work has shown that the summer of 2002 had the greatest area of snow melt <span class="hlt">extent</span> on the Greenland <span class="hlt">ice</span> sheet ever recorded using passive-microwave data. In this paper, we compare the 0deg isotherm derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument, with Special Sensor Microwave/Imager (SSM/I)-derived melt, at the time of the maximum melt <span class="hlt">extent</span> in 2002. To validate the MODIS-derived land-surface temperatures (LSTs), we compared the MODIS LSTs with air temperatures from nine stations (using 11 different data points) and found that they agreed to within 2.3 plusmn 2.09 degC, with station temperatures consistently lower than the MODIS LSTs. According to the MODIS LST, the maximum surface melt extended to ~2300 m in southern Greenland; while the SSM/I measurements showed that the maximum melt extended to nearly 2700 m in southeastern Greenland. The MODIS and SSM/I data are complementary in providing detailed information about the progression of surface and near-surface melt on the Greenland <span class="hlt">ice</span> sheet.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19544867','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19544867"><span>Mercury <span class="hlt">trends</span> in ringed seals (Phoca hispida) from the western Canadian Arctic since 1973: associations with length of <span class="hlt">ice</span>-free season.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Gaden, A; Ferguson, S H; Harwood, L; Melling, H; Stern, G A</p> <p>2009-05-15</p> <p>We examined a unique time series of ringed seal (Phoca hispida) samples collected from a single location in the western Canadian Arctic between 1973 and 2007 to test for changes in total mercury (THg) in muscle tissue associated with (1) year and (2) length of <span class="hlt">ice</span>-free season. We found no temporal <span class="hlt">trend</span> with muscle THg whereas a curvilinear relationship existed with the length of <span class="hlt">ice</span>-free season: seals attaimed higher THg in short (2 months) and long (5 months) <span class="hlt">ice</span>-free seasons. delta 15N and delta13C in muscle tissue did not illustrate significant <span class="hlt">trends</span> with <span class="hlt">ice</span>-free days. We estimated that the turnover time of THg in muscle was about twice as long as stable isotope turnover in muscle, possibly explaining the lack of <span class="hlt">trend</span> with stable isotopes in association with <span class="hlt">ice</span>-free duration. Our discussion explains how summer environmental conditions may influence the composition of prey (mercury exposure) available to ringed seals. Results offer insight into how marine mammals may respond to directional changes in the Arctic <span class="hlt">ice</span>-free season.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27582222','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27582222"><span>Sea-<span class="hlt">ice</span> transport driving Southern Ocean salinity and its recent <span class="hlt">trends</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Haumann, F Alexander; Gruber, Nicolas; Münnich, Matthias; Frenger, Ivy; Kern, Stefan</p> <p>2016-09-01</p> <p>Recent salinity changes in the Southern Ocean are among the most prominent signals of climate change in the global ocean, yet their underlying causes have not been firmly established. Here we propose that <span class="hlt">trends</span> in the northward transport of Antarctic sea <span class="hlt">ice</span> are a major contributor to these changes. Using satellite observations supplemented by sea-<span class="hlt">ice</span> reconstructions, we estimate that wind-driven northward freshwater transport by sea <span class="hlt">ice</span> increased by 20 ± 10 per cent between 1982 and 2008. The strongest and most robust increase occurred in the Pacific sector, coinciding with the largest observed salinity changes. We estimate that the additional freshwater for the entire northern sea-<span class="hlt">ice</span> edge entails a freshening rate of -0.02 ± 0.01 grams per kilogram per decade in the surface and intermediate waters of the open ocean, similar to the observed freshening. The enhanced rejection of salt near the coast of Antarctica associated with stronger sea-<span class="hlt">ice</span> export counteracts the freshening of both continental shelf and newly formed bottom waters due to increases in glacial meltwater. Although the data sources underlying our results have substantial uncertainties, regional analyses and independent data from an atmospheric reanalysis support our conclusions. Our finding that northward sea-<span class="hlt">ice</span> freshwater transport is also a key determinant of the mean salinity distribution in the Southern Ocean further underpins the importance of the sea-<span class="hlt">ice</span>-induced freshwater flux. Through its influence on the density structure of the ocean, this process has critical consequences for the global climate by affecting the exchange of heat, carbon and nutrients between the deep ocean and surface waters.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25712272','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25712272"><span><span class="hlt">Ice</span> cover <span class="hlt">extent</span> drives phytoplankton and bacterial community structure in a large north-temperate lake: implications for a warming climate.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Beall, B F N; Twiss, M R; Smith, D E; Oyserman, B O; Rozmarynowycz, M J; Binding, C E; Bourbonniere, R A; Bullerjahn, G S; Palmer, M E; Reavie, E D; Waters, Lcdr M K; Woityra, Lcdr W C; McKay, R M L</p> <p>2016-06-01</p> <p>Mid-winter limnological surveys of Lake Erie captured extremes in <span class="hlt">ice</span> <span class="hlt">extent</span> ranging from expansive <span class="hlt">ice</span> cover in 2010 and 2011 to nearly <span class="hlt">ice</span>-free waters in 2012. Consistent with a warming climate, <span class="hlt">ice</span> cover on the Great Lakes is in decline, thus the <span class="hlt">ice</span>-free condition encountered may foreshadow the lakes future winter state. Here, we show that pronounced changes in annual <span class="hlt">ice</span> cover are accompanied by equally important shifts in phytoplankton and bacterial community structure. Expansive <span class="hlt">ice</span> cover supported phytoplankton blooms of filamentous diatoms. By comparison, <span class="hlt">ice</span> free conditions promoted the growth of smaller sized cells that attained lower total biomass. We propose that isothermal mixing and elevated turbidity in the absence of <span class="hlt">ice</span> cover resulted in light limitation of the phytoplankton during winter. Additional insights into microbial community dynamics were gleaned from short 16S rRNA tag (Itag) Illumina sequencing. UniFrac analysis of Itag sequences showed clear separation of microbial communities related to presence or absence of <span class="hlt">ice</span> cover. Whereas the ecological implications of the changing bacterial community are unclear at this time, it is likely that the observed shift from a phytoplankton community dominated by filamentous diatoms to smaller cells will have far reaching ecosystem effects including food web disruptions. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010cosp...38.1213L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010cosp...38.1213L"><span><span class="hlt">Trends</span> and solar cycle effects in mesospheric <span class="hlt">ice</span> clouds</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lübken, Franz-Josef; Berger, Uwe; Fiedler, Jens; Baumgarten, Gerd; Gerding, Michael</p> <p></p> <p>Lidar observations of mesospheric <span class="hlt">ice</span> layers (noctilucent clouds, NLC) are now available since 12 years which allows to study solar cycle effects on NLC parameters such as altitudes, bright-ness, and occurrence rates. We present observations from our lidar stations in Kuehlungsborn (54N) and ALOMAR (69N). Different from general expectations the mean layer characteris-tics at ALOMAR do not show a persistent anti-correlation with solar cycle. Although a nice anti-correlation of Ly-alpha and occurrence rates is detected in the first half of the solar cycle, occurrence rates decreased with decreasing solar activity thereafter. Interestingly, in summer 2009 record high NLC parameters were detected as expected in solar minimum conditions. The morphology of NLC suggests that other processes except solar radiation may affect NLC. We have recently applied our LIMA model to study in detail the solar cycle effects on tempera-tures and water vapor concentration the middle atmosphere and its subsequent influence on mesospheric <span class="hlt">ice</span> clouds. Furthermore, lower atmosphere effects are implicitly included because LIMA nudges to the conditions in the troposphere and lower stratosphere. We compare LIMA results regarding solar cycle effects on temperatures and <span class="hlt">ice</span> layers with observations at ALO-MAR as well as satellite borne measurements. We will also present LIMA results regarding the latitude variation of solar cycle and <span class="hlt">trends</span>, including a comparison of northern and southern hemisphere. We have adapted the observation conditions from SBUV (wavelength and scatter-ing angle) in LIMA for a detailed comparison with long term observations of <span class="hlt">ice</span> clouds from satellites.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140006590','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140006590"><span>Large Decadal Decline of the Arctic Multiyear <span class="hlt">Ice</span> Cover</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Josefino C.</p> <p>2012-01-01</p> <p>The perennial <span class="hlt">ice</span> area was drastically reduced to 38% of its climatological average in 2007 but recovered slightly in 2008, 2009, and 2010 with the areas being 10%, 24%, and 11% higher than in 2007, respectively. However, <span class="hlt">trends</span> in <span class="hlt">extent</span> and area remained strongly negative at -12.2% and -13.5% decade (sup -1), respectively. The thick component of the perennial <span class="hlt">ice</span>, called multiyear <span class="hlt">ice</span>, as detected by satellite data during the winters of 1979-2011 was studied, and results reveal that the multiyear <span class="hlt">ice</span> <span class="hlt">extent</span> and area are declining at an even more rapid rate of -15.1% and -17.2% decade(sup -1), respectively, with a record low value in 2008 followed by higher values in 2009, 2010, and 2011. Such a high rate in the decline of the thick component of the Arctic <span class="hlt">ice</span> cover means a reduction in the average <span class="hlt">ice</span> thickness and an even more vulnerable perennial <span class="hlt">ice</span> cover. The decline of the multiyear <span class="hlt">ice</span> area from 2007 to 2008 was not as strong as that of the perennial <span class="hlt">ice</span> area from 2006 to 2007, suggesting a strong role of second-year <span class="hlt">ice</span> melt in the latter. The sea <span class="hlt">ice</span> cover is shown to be strongly correlated with surface temperature, which is increasing at about 3 times the global average in the Arctic but appears weakly correlated with the Arctic Oscillation (AO), which controls the atmospheric circulation in the region. An 8-9-yr cycle is apparent in the multiyear <span class="hlt">ice</span> record, which could explain, in part, the slight recovery in the last 3 yr.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110008253','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110008253"><span>Large Decadal Decline of the Arctic Multiyear <span class="hlt">Ice</span> Cover</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Josefino C.</p> <p>2011-01-01</p> <p>The perennial <span class="hlt">ice</span> area was drastically reduced to 38% of its climatological average in 2007 but recovered somewhat in 2008, 2009 and 2010 with the areas being 10%, 24%, and 11% higher than in 2007, respectively. However, the <span class="hlt">trends</span> in the <span class="hlt">extent</span> and area remain strongly negative at -12.2% and -13.5 %/decade, respectively. The thick component of the perennial <span class="hlt">ice</span>, called multiyear <span class="hlt">ice</span>, as detected by satellite data in the winters of 1979 to 2011 was studied and results reveal that the multiyear <span class="hlt">ice</span> <span class="hlt">extent</span> and area are declining at an even more rapid rate of -15.1% and -17.2 % per decade, respectively, with record low value in 2008 followed by higher values in 2009, 2010 and 2011. Such high rate in the decline of the thick component of the Arctic <span class="hlt">ice</span> cover means a reduction in average <span class="hlt">ice</span> thickness and an even more vulnerable perennial <span class="hlt">ice</span> cover. The decline of the multiyear <span class="hlt">ice</span> area from 2007 to 2008 was not as strong as that of the perennial <span class="hlt">ice</span> area from 2006 to 2007 suggesting a strong role of second year <span class="hlt">ice</span> melt in the latter. The sea <span class="hlt">ice</span> cover is shown to be strongly correlated with surface temperature which is increasing at about three times global average in the Arctic but appears weakly correlated with the AO which controls the dynamics of the region. An 8 to 9-year cycle is apparent in the multiyear <span class="hlt">ice</span> record which could explain in part the slight recovery in the last three years.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/AD1031019','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD1031019"><span>Emerging <span class="hlt">Trends</span> in the Sea State of the Beaufort and Chukchi Seas</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2016-07-06</p> <p>Beaufort and Chukchi seas is controlled by the wind forcing and the amount of <span class="hlt">ice</span>-free water available to generate surface waves. Clear <span class="hlt">trends</span> in...the annual duration of the open water season and in the <span class="hlt">extent</span> of the seasonal sea <span class="hlt">ice</span> minimum suggest that the sea state should be increasing...In particular, larger waves are more common in years with less summer sea <span class="hlt">ice</span> and/or a longer open water season, and peak wave periods are generally</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1811086D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1811086D"><span>Atmospheric forcing of sea <span class="hlt">ice</span> anomalies in the Ross Sea Polynya region</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dale, Ethan; McDonald, Adrian; Rack, Wolfgang</p> <p>2016-04-01</p> <p>Despite warming <span class="hlt">trends</span> in global temperatures, sea <span class="hlt">ice</span> <span class="hlt">extent</span> in the southern hemisphere has shown an increasing <span class="hlt">trend</span> over recent decades. Wind-driven sea <span class="hlt">ice</span> export from coastal polynyas is an important source of sea <span class="hlt">ice</span> production. Areas of major polynyas in the Ross Sea, the region with largest increase in sea <span class="hlt">ice</span> <span class="hlt">extent</span>, have been suggested to produce the vast amount of the sea <span class="hlt">ice</span> in the region. We investigate the impacts of strong wind events on polynyas and the subsequent sea <span class="hlt">ice</span> production. We utilize Bootstrap sea <span class="hlt">ice</span> concentration (SIC) measurements derived from satellite based, Special Sensor Microwave Imager (SSM/I) brightness temperature images. These are compared with surface wind measurements made by automatic weather stations of the University of Wisconsin-Madison Antarctic Meteorology Program. Our analysis focusses on the winter period defined as 1st April to 1st November in this study. Wind data was used to classify each day into characteristic regimes based on the change of wind speed. For each regime, a composite of SIC anomaly was formed for the Ross Sea region. We found that persistent weak winds near the edge of the Ross <span class="hlt">Ice</span> Shelf are generally associated with positive SIC anomalies in the Ross Sea polynya area (RSP). Conversely we found negative SIC anomalies in this area during persistent strong winds. By analyzing sea <span class="hlt">ice</span> motion vectors derived from SSM/I brightness temperatures, we find significant sea <span class="hlt">ice</span> motion anomalies throughout the Ross Sea during strong wind events. These anomalies persist for several days after the strong wing event. Strong, negative correlations are found between SIC within the RSP and wind speed indicating that strong winds cause significant advection of sea <span class="hlt">ice</span> in the RSP. This rapid decrease in SIC is followed by a more gradual recovery in SIC. This increase occurs on a time scale greater than the average persistence of strong wind events and the resulting Sea <span class="hlt">ice</span> motion anomalies, highlighting the production</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C21C0372G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C21C0372G"><span>McMurdo <span class="hlt">Ice</span> Shelf Sounding and Radar Statistical Reconnaissance at 60-MHz: Brine Infiltration <span class="hlt">Extent</span> and Surface Properties</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Grima, C.; Rosales, A.; Blankenship, D. D.; Young, D. A.</p> <p>2014-12-01</p> <p>McMurdo <span class="hlt">Ice</span> Shelf, Antarctica, is characterized by two particular geophysical processes. (1) Marine <span class="hlt">ice</span> accretion supplies most of the <span class="hlt">ice</span> shelf material rather than meteoric <span class="hlt">ice</span> from glacier outflow and snow-falls. (2) A brine layer infiltrates the <span class="hlt">ice</span> shelf laterally up to 20-km inward. The infiltration mainly initiates at the <span class="hlt">ice</span>-front from sea water percolation when the firn/snow transition is below sea-level. A better characterization of the McMurdo <span class="hlt">ice</span> shelf could constrain our knowledges of these mechanisms and assess the stability of the region that hosts numerous human activities from the close McMurdo station (USA) and Scott base (New-Zealand). McMurdo <span class="hlt">ice</span> shelf is also an analog for the Jovian icy moon Europa where brine pockets are supposed to reside in the <span class="hlt">ice</span> crust and accretion to occur at the 10-30-km deep <span class="hlt">ice</span>-ocean interface.The University of Texas Institute for Geophysics (UTIG) acquired two radar survey grids over the McMurdo <span class="hlt">Ice</span> Shelf during southern summers 2011-2012 and 2012-2013 with the High Capability Radar Sounder (HiCARS) on-board a Basler DC-3 aircraft. HiCARS transmits a chirped signal at 60-MHz central frequency and 15-MHz bandwidth. The corresponding vertical resolution in <span class="hlt">ice</span> is 5-10 m. An important design goal of the radar was to maintain sufficient dynamic range to correctly measure echo intensities.Here we present the brine infiltration <span class="hlt">extent</span> and bathymetry derived from its dielectric horizon well distinguishable on the HiCARS radargram. We complement the <span class="hlt">ice</span>-shelf characterization by classifying its surface thanks to the novel Radar Statistical Reconnaissance (RSR) methodology. The RSR observable is the statistical distribution of the surface echo amplitudes from successive areas defined along-track. The distributions are best-fitted with a theoretical stochastic envelop parameterized with the signal reflectance and scattering. Once those two components are deduced from the fit, they are used in a backscattering model to invert</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/18566098','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/18566098"><span>High latitude changes in <span class="hlt">ice</span> dynamics and their impact on polar marine ecosystems.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Moline, Mark A; Karnovsky, Nina J; Brown, Zachary; Divoky, George J; Frazer, Thomas K; Jacoby, Charles A; Torres, Joseph J; Fraser, William R</p> <p>2008-01-01</p> <p>Polar regions have experienced significant warming in recent decades. Warming has been most pronounced across the Arctic Ocean Basin and along the Antarctic Peninsula, with significant decreases in the <span class="hlt">extent</span> and seasonal duration of sea <span class="hlt">ice</span>. Rapid retreat of glaciers and disintegration of <span class="hlt">ice</span> sheets have also been documented. The rate of warming is increasing and is predicted to continue well into the current century, with continued impacts on <span class="hlt">ice</span> dynamics. Climate-mediated changes in <span class="hlt">ice</span> dynamics are a concern as <span class="hlt">ice</span> serves as primary habitat for marine organisms central to the food webs of these regions. Changes in the timing and <span class="hlt">extent</span> of sea <span class="hlt">ice</span> impose temporal asynchronies and spatial separations between energy requirements and food availability for many higher trophic levels. These mismatches lead to decreased reproductive success, lower abundances, and changes in distribution. In addition to these direct impacts of <span class="hlt">ice</span> loss, climate-induced changes also facilitate indirect effects through changes in hydrography, which include introduction of species from lower latitudes and altered assemblages of primary producers. Here, we review recent changes and <span class="hlt">trends</span> in <span class="hlt">ice</span> dynamics and the responses of marine ecosystems. Specifically, we provide examples of <span class="hlt">ice</span>-dependent organisms and associated species from the Arctic and Antarctic to illustrate the impacts of the temporal and spatial changes in <span class="hlt">ice</span> dynamics.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_8 --> <div id="page_9" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="161"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016OcMod.105....1T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016OcMod.105....1T"><span>Emerging <span class="hlt">trends</span> in the sea state of the Beaufort and Chukchi seas</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Thomson, Jim; Fan, Yalin; Stammerjohn, Sharon; Stopa, Justin; Rogers, W. Erick; Girard-Ardhuin, Fanny; Ardhuin, Fabrice; Shen, Hayley; Perrie, Will; Shen, Hui; Ackley, Steve; Babanin, Alex; Liu, Qingxiang; Guest, Peter; Maksym, Ted; Wadhams, Peter; Fairall, Chris; Persson, Ola; Doble, Martin; Graber, Hans; Lund, Bjoern; Squire, Vernon; Gemmrich, Johannes; Lehner, Susanne; Holt, Benjamin; Meylan, Mike; Brozena, John; Bidlot, Jean-Raymond</p> <p>2016-09-01</p> <p>The sea state of the Beaufort and Chukchi seas is controlled by the wind forcing and the amount of <span class="hlt">ice</span>-free water available to generate surface waves. Clear <span class="hlt">trends</span> in the annual duration of the open water season and in the <span class="hlt">extent</span> of the seasonal sea <span class="hlt">ice</span> minimum suggest that the sea state should be increasing, independent of changes in the wind forcing. Wave model hindcasts from four selected years spanning recent conditions are consistent with this expectation. In particular, larger waves are more common in years with less summer sea <span class="hlt">ice</span> and/or a longer open water season, and peak wave periods are generally longer. The increase in wave energy may affect both the coastal zones and the remaining summer <span class="hlt">ice</span> pack, as well as delay the autumn <span class="hlt">ice</span>-edge advance. However, <span class="hlt">trends</span> in the amount of wave energy impinging on the <span class="hlt">ice</span>-edge are inconclusive, and the associated processes, especially in the autumn period of new <span class="hlt">ice</span> formation, have yet to be well-described by in situ observations. There is an implicit <span class="hlt">trend</span> and evidence for increasing wave energy along the coast of northern Alaska, and this coastal signal is corroborated by satellite altimeter estimates of wave energy.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy...50...51R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy...50...51R"><span>Automated parameter tuning applied to sea <span class="hlt">ice</span> in a global climate model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Roach, Lettie A.; Tett, Simon F. B.; Mineter, Michael J.; Yamazaki, Kuniko; Rae, Cameron D.</p> <p>2018-01-01</p> <p>This study investigates the hypothesis that a significant portion of spread in climate model projections of sea <span class="hlt">ice</span> is due to poorly-constrained model parameters. New automated methods for optimization are applied to historical sea <span class="hlt">ice</span> in a global coupled climate model (HadCM3) in order to calculate the combination of parameters required to reduce the difference between simulation and observations to within the range of model noise. The optimized parameters result in a simulated sea-<span class="hlt">ice</span> time series which is more consistent with Arctic observations throughout the satellite record (1980-present), particularly in the September minimum, than the standard configuration of HadCM3. Divergence from observed Antarctic <span class="hlt">trends</span> and mean regional sea <span class="hlt">ice</span> distribution reflects broader structural uncertainty in the climate model. We also find that the optimized parameters do not cause adverse effects on the model climatology. This simple approach provides evidence for the contribution of parameter uncertainty to spread in sea <span class="hlt">ice</span> <span class="hlt">extent</span> <span class="hlt">trends</span> and could be customized to investigate uncertainties in other climate variables.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19890025240&hterms=wind+monitor&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dwind%2Bmonitor','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19890025240&hterms=wind+monitor&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dwind%2Bmonitor"><span>Wind, current and swell influences on the <span class="hlt">ice</span> <span class="hlt">extent</span> and flux in the Grand Banks-Labrador sea area as observed in the LIMEX '87 experiment</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Argus, Susan Digby; Carsey, Frank; Holt, Benjamin</p> <p>1988-01-01</p> <p>This paper presents data collected by airborne and satellite instruments during the Labrador <span class="hlt">Ice</span> Margin Experiment, that demonstrate the effects of oceanic and atmospheric processes on the <span class="hlt">ice</span> conditions in the Grand Banks-Labrador sea area. Special consideration is given to the development of algorithms for extracting information from SAR data. It is shown that SAR data can be used to monitor <span class="hlt">ice</span> <span class="hlt">extent</span>, determine <span class="hlt">ice</span> motion, locate shear zones, monitor the penetration of swell into the <span class="hlt">ice</span>, estimate floe sizes, and establish the dimensions of the <span class="hlt">ice</span> velocity zones. It is also shown that the complex interaction of the <span class="hlt">ice</span> cover with winds, currents, swell, and coastlines is similar to the dynamics established for a number of sites in both polar regions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018TCry...12..675O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018TCry...12..675O"><span>Mechanisms influencing seasonal to inter-annual prediction skill of sea <span class="hlt">ice</span> <span class="hlt">extent</span> in the Arctic Ocean in MIROC</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ono, Jun; Tatebe, Hiroaki; Komuro, Yoshiki; Nodzu, Masato I.; Ishii, Masayoshi</p> <p>2018-02-01</p> <p>To assess the skill of seasonal to inter-annual predictions of the detrended sea <span class="hlt">ice</span> <span class="hlt">extent</span> in the Arctic Ocean (SIEAO) and to clarify the underlying physical processes, we conducted ensemble hindcasts, started on 1 January, 1 April, 1 July and 1 October for each year from 1980 to 2011, for lead times up to three years, using the Model for Interdisciplinary Research on Climate (MIROC) version 5 initialised with the observed atmosphere and ocean anomalies and sea <span class="hlt">ice</span> concentration. Significant skill is found for the winter months: the December SIEAO can be predicted up to 11 months ahead (anomaly correlation coefficient is 0.42). This skill might be attributed to the subsurface ocean heat content originating in the North Atlantic. A plausible mechanism is as follows: the subsurface water flows into the Barents Sea from spring to fall and emerges at the surface in winter by vertical mixing, and eventually affects the sea <span class="hlt">ice</span> variability there. Meanwhile, the September SIEAO predictions are skillful for lead times of up to two months, due to the persistence of sea <span class="hlt">ice</span> in the Beaufort, Chukchi, and East Siberian seas initialised in July, as suggested by previous studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33D1232R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33D1232R"><span>The Contribution to High Asia Runoff from <span class="hlt">Ice</span> and Snow (CHARIS): Understanding the source and <span class="hlt">trends</span> of cryospheric contributions to the water balance</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rittger, K.; Armstrong, R. L.; Bair, N.; Racoviteanu, A.; Brodzik, M. J.; Hill, A. F.; Wilson, A. M.; Khan, A. L.; Ramage, J. M.; Khalsa, S. J. S.; Barrett, A. P.; Raup, B. H.; Painter, T. H.</p> <p>2017-12-01</p> <p>The Contribution to High Asia Runoff from <span class="hlt">Ice</span> and Snow, or CHARIS, project is systematically assessing the role that glaciers and seasonal snow play in the freshwater resources of Central and South Asia. The study area encompasses roughly 3 million square kilometers of the Himalaya, Karakoram, Hindu Kush, Pamir and Tien Shan mountain ranges that drain to five major rivers: the Ganges, Brahmaputra, Indus, Amu Darya and Syr Darya. We estimate daily snow and glacier <span class="hlt">ice</span> contributions to the water balance. Our automated partitioning method generates daily maps of 1) snow over <span class="hlt">ice</span> (SOI), 2) exposed glacier <span class="hlt">ice</span> (EGI), 3) debris covered glacier <span class="hlt">ice</span> (DGI) and 4) snow over land (SOL) using fractional snow cover, snow grain size, and annual minimum <span class="hlt">ice</span> and snow from the 500 m MODIS-derived MODSCAG and MODICE products. Maps of snow and <span class="hlt">ice</span> cover are validated using high-resolution (30 m) maps of snow, <span class="hlt">ice</span>, and debris cover from Landsat. The probability of detection is 0.91 and precision is 0.85 for MODICE. We examine <span class="hlt">trends</span> in annual and monthly snow and <span class="hlt">ice</span> maps and use daily maps as inputs to a calibrated temperature-index model and an uncalibrated energy balance model, ParBal. Melt model results and measurements of isotopes and specific ions used as an independent validation of melt modeling indicate a sharp geographic contrast in the role of snow and <span class="hlt">ice</span> melt to downstream water supplies between the arid Tien Shan and Pamir ranges of Central Asia, where melt water dominates dry season flows, and the monsoon influenced central and eastern Himalaya where rain controls runoff. We also compare melt onset and duration from the melt models to the Calibrated, Enhanced Resolution Passive Microwave Brightness Temperature Earth Science Data Record. <span class="hlt">Trend</span> analysis of annual and monthly area of permanent snow and <span class="hlt">ice</span> (the union of SOI and EGI) for 2000 to 2016 shows statistically significant negative <span class="hlt">trends</span> in the Ganges and Brahmaputra basins. There are no statistically significant</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19930066535&hterms=sea+ice+albedo&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dsea%2Bice%2Balbedo','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19930066535&hterms=sea+ice+albedo&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dsea%2Bice%2Balbedo"><span>Operational satellites and the global monitoring of snow and <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Walsh, John E.</p> <p>1991-01-01</p> <p>The altitudinal dependence of the global warming projected by global climate models is at least partially attributable to the albedo-temperature feedback involving snow and <span class="hlt">ice</span>, which must be regarded as key variables in the monitoring for global change. Statistical analyses of data from IR and microwave sensors monitoring the areal coverage and <span class="hlt">extent</span> of sea <span class="hlt">ice</span> have led to mixed conclusions about recent <span class="hlt">trends</span> of hemisphere sea <span class="hlt">ice</span> coverage. Seasonal snow cover has been mapped for over 20 years by NOAA/NESDIS on the basis of imagery from a variety of satellite sensors. Multichannel passive microwave data show some promise for the routine monitoring of snow depth over unforested land areas.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70014676','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70014676"><span>ARCTIC SEA <span class="hlt">ICE</span> <span class="hlt">EXTENT</span> AND DRIFT, MODELED AS A VISCOUS FLUID.</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Ling, Chi-Hai; Parkinson, Claire L.</p> <p>1986-01-01</p> <p>A dynamic/thermodynamic numerical model of sea <span class="hlt">ice</span> has been used to calculate the yearly cycle of sea <span class="hlt">ice</span> thicknesses, concentrations, and velocities in the Arctic Ocean and surrounding seas. The model combines the formulations of two previous models, taking the thermodynamics and momentum equations from the model of Parkinson and Washington and adding the constitutive equation and equation of state from the model of Ling, Rasmussen, and Campbell. Simulated annually averaged <span class="hlt">ice</span> drift vectors compare well with observed <span class="hlt">ice</span> drift from the Arctic Ocean Buoy Program.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1912428I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1912428I"><span>September Arctic Sea <span class="hlt">Ice</span> minimum prediction - a new skillful statistical approach</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ionita-Scholz, Monica; Grosfeld, Klaus; Scholz, Patrick; Treffeisen, Renate; Lohmann, Gerrit</p> <p>2017-04-01</p> <p>Sea <span class="hlt">ice</span> in both Polar Regions is an important indicator for the expression of global climate change and its polar amplification. Consequently, a broad interest exists on sea <span class="hlt">ice</span>, its coverage, variability and long term change. Knowledge on sea <span class="hlt">ice</span> requires high quality data on <span class="hlt">ice</span> <span class="hlt">extent</span>, thickness and its dynamics. However, its predictability is complex and it depends on various climate and oceanic parameters and conditions. In order to provide insights into the potential development of a monthly/seasonal signal of sea <span class="hlt">ice</span> evolution, we developed a robust statistical model based on ocean heat content, sea surface temperature and different atmospheric variables to calculate an estimate of the September Sea <span class="hlt">ice</span> <span class="hlt">extent</span> (SSIE) on monthly time scale. Although previous statistical attempts at monthly/seasonal forecasts of SSIE show a relatively reduced skill, we show here that more than 92% (r = 0.96) of the September sea <span class="hlt">ice</span> <span class="hlt">extent</span> can be predicted at the end of May by using previous months' climate and oceanic conditions. The skill of the model increases with a decrease in the time lag used for the forecast. At the end of August, our predictions are even able to explain 99% of the SSIE. Our statistical model captures both the general <span class="hlt">trend</span> as well as the interannual variability of the SSIE. Moreover, it is able to properly forecast the years with extreme high/low SSIE (e.g. 1996/ 2007, 2012, 2013). Besides its forecast skill for SSIE, the model could provide a valuable tool for identifying relevant regions and climate parameters that are important for the sea <span class="hlt">ice</span> development in the Arctic and for detecting sensitive and critical regions in global coupled climate models with focus on sea <span class="hlt">ice</span> formation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19884496','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19884496"><span>The future of <span class="hlt">ice</span> sheets and sea <span class="hlt">ice</span>: between reversible retreat and unstoppable loss.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Notz, Dirk</p> <p>2009-12-08</p> <p>We discuss the existence of cryospheric "tipping points" in the Earth's climate system. Such critical thresholds have been suggested to exist for the disappearance of Arctic sea <span class="hlt">ice</span> and the retreat of <span class="hlt">ice</span> sheets: Once these <span class="hlt">ice</span> masses have shrunk below an anticipated critical <span class="hlt">extent</span>, the <span class="hlt">ice</span>-albedo feedback might lead to the irreversible and unstoppable loss of the remaining <span class="hlt">ice</span>. We here give an overview of our current understanding of such threshold behavior. By using conceptual arguments, we review the recent findings that such a tipping point probably does not exist for the loss of Arctic summer sea <span class="hlt">ice</span>. Hence, in a cooler climate, sea <span class="hlt">ice</span> could recover rapidly from the loss it has experienced in recent years. In addition, we discuss why this recent rapid retreat of Arctic summer sea <span class="hlt">ice</span> might largely be a consequence of a slow shift in <span class="hlt">ice</span>-thickness distribution, which will lead to strongly increased year-to-year variability of the Arctic summer sea-<span class="hlt">ice</span> <span class="hlt">extent</span>. This variability will render seasonal forecasts of the Arctic summer sea-<span class="hlt">ice</span> <span class="hlt">extent</span> increasingly difficult. We also discuss why, in contrast to Arctic summer sea <span class="hlt">ice</span>, a tipping point is more likely to exist for the loss of the Greenland <span class="hlt">ice</span> sheet and the West Antarctic <span class="hlt">ice</span> sheet.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1818420I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1818420I"><span>Reaching and abandoning the furthest <span class="hlt">ice</span> <span class="hlt">extent</span> during the Last Glacial Maximum in the Alps</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ivy-Ochs, Susan; Wirsig, Christian; Zasadni, Jerzy; Hippe, Kristina; Christl, Marcus; Akçar, Naki; Schluechter, Christian</p> <p>2016-04-01</p> <p>During the Last Glacial Maximum (LGM) in the European Alps (late Würm) local <span class="hlt">ice</span> caps and extensive <span class="hlt">ice</span> fields in the high Alps fed huge outlet glaciers that occupied the main valleys and extended onto the forelands as piedmont lobes. Records from numerous sites suggest advance of glaciers beyond the mountain front by around 30 ka (Ivy-Ochs 2015 and references therein). Reaching of the maximum <span class="hlt">extent</span> occurred by about 27-26 ka, as exemplified by dates from the Rhein glacier area (Keller and Krayss, 2005). Abandonment of the outermost moraines at sites north and south of the Alps was underway by about 24 ka. In the high Alps, systems of transection glaciers with transfluences over many of the Alpine passes dominated, for example, at Grimsel Pass in the Central Alps (Switzerland). 10Be exposure ages of 23 ± 1 ka for glacially sculpted bedrock located just a few meters below the LGM trimline in the Haslital near Grimsel Pass suggest a pulse of <span class="hlt">ice</span> surface lowering at about the same time that the foreland moraines were being abandoned (Wirsig et al., 2016). Widespread <span class="hlt">ice</span> surface lowering in the high Alps was underway by no later than 18 ka. Thereafter, glaciers oscillated at stillstand and minor re-advance positions on the northern forelands for several thousand years forming the LGM stadial moraines. Final recession back within the mountain front took place by 19-18 ka. Recalculation to a common basis of all published 10Be exposure dates for boulders situated on LGM moraines suggests a strong degree of synchrony for the timing of onset of <span class="hlt">ice</span> decay both north and south of the Alps. Ivy-Ochs, S., 2015, Cuadernos de investigación geográfica 41: 295-315. Keller, O., Krayss, E., 2005, Vierteljahrschr. Naturforsch. Gesell. Zürich 150: 69-85. Wirsig, C. et al., 2016, J. Quat. Sci. 31: 46-59.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017TCry...11.2491T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017TCry...11.2491T"><span>Dark <span class="hlt">ice</span> dynamics of the south-west Greenland <span class="hlt">Ice</span> Sheet</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tedstone, Andrew J.; Bamber, Jonathan L.; Cook, Joseph M.; Williamson, Christopher J.; Fettweis, Xavier; Hodson, Andrew J.; Tranter, Martyn</p> <p>2017-11-01</p> <p>Runoff from the Greenland <span class="hlt">Ice</span> Sheet (GrIS) has increased in recent years due largely to changes in atmospheric circulation and atmospheric warming. Albedo reductions resulting from these changes have amplified surface melting. Some of the largest declines in GrIS albedo have occurred in the ablation zone of the south-west sector and are associated with the development of dark <span class="hlt">ice</span> surfaces. Field observations at local scales reveal that a variety of light-absorbing impurities (LAIs) can be present on the surface, ranging from inorganic particulates to cryoconite materials and <span class="hlt">ice</span> algae. Meanwhile, satellite observations show that the areal <span class="hlt">extent</span> of dark <span class="hlt">ice</span> has varied significantly between recent successive melt seasons. However, the processes that drive such large interannual variability in dark <span class="hlt">ice</span> <span class="hlt">extent</span> remain essentially unconstrained. At present we are therefore unable to project how the albedo of bare <span class="hlt">ice</span> sectors of the GrIS will evolve in the future, causing uncertainty in the projected sea level contribution from the GrIS over the coming decades. Here we use MODIS satellite imagery to examine dark <span class="hlt">ice</span> dynamics on the south-west GrIS each year from 2000 to 2016. We quantify dark <span class="hlt">ice</span> in terms of its annual <span class="hlt">extent</span>, duration, intensity and timing of first appearance. Not only does dark <span class="hlt">ice</span> <span class="hlt">extent</span> vary significantly between years but so too does its duration (from 0 to > 80 % of June-July-August, JJA), intensity and the timing of its first appearance. Comparison of dark <span class="hlt">ice</span> dynamics with potential meteorological drivers from the regional climate model MAR reveals that the JJA sensible heat flux, the number of positive minimum-air-temperature days and the timing of bare <span class="hlt">ice</span> appearance are significant interannual synoptic controls. We use these findings to identify the surface processes which are most likely to explain recent dark <span class="hlt">ice</span> dynamics. We suggest that whilst the spatial distribution of dark <span class="hlt">ice</span> is best explained by outcropping of particulates from</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www1.ncdc.noaa.gov/pub/data/cmb/bams-sotc/climate-assessment-2004.pdf','USGSPUBS'); return false;" href="http://www1.ncdc.noaa.gov/pub/data/cmb/bams-sotc/climate-assessment-2004.pdf"><span>Polar Climate: Arctic sea <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Stone, R.S.; Douglas, David C.; Belchansky, G.I.; Drobot, S.D.</p> <p>2005-01-01</p> <p>Recent decreases in snow and sea <span class="hlt">ice</span> cover in the high northern latitudes are among the most notable indicators of climate change. Northern Hemisphere sea <span class="hlt">ice</span> <span class="hlt">extent</span> for the year as a whole was the third lowest on record dating back to 1973, behind 1995 (lowest) and 1990 (second lowest; Hadley Center–NCEP). September sea <span class="hlt">ice</span> <span class="hlt">extent</span>, which is at the end of the summer melt season and is typically the month with the lowest sea <span class="hlt">ice</span> <span class="hlt">extent</span> of the year, has decreased by about 19% since the late 1970s (Fig. 5.2), with a record minimum observed in 2002 (Serreze et al. 2003). A record low <span class="hlt">extent</span> also occurred in spring (Chapman 2005, personal communication), and 2004 marked the third consecutive year of anomalously extreme sea <span class="hlt">ice</span> retreat in the Arctic (Stroeve et al. 2005). Some model simulations indicate that <span class="hlt">ice</span>-free summers will occur in the Arctic by the year 2070 (ACIA 2004).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C31A..03A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C31A..03A"><span>Interactions Between <span class="hlt">Ice</span> Thickness, Bottom <span class="hlt">Ice</span> Algae, and Transmitted Spectral Irradiance in the Chukchi Sea</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Arntsen, A. E.; Perovich, D. K.; Polashenski, C.; Stwertka, C.</p> <p>2015-12-01</p> <p>The amount of light that penetrates the Arctic sea <span class="hlt">ice</span> cover impacts sea-<span class="hlt">ice</span> mass balance as well as ecological processes in the upper ocean. The seasonally evolving macro and micro spatial variability of transmitted spectral irradiance observed in the Chukchi Sea from May 18 to June 17, 2014 can be primarily attributed to variations in snow depth, <span class="hlt">ice</span> thickness, and bottom <span class="hlt">ice</span> algae concentrations. This study characterizes the interactions among these dominant variables using observed optical properties at each sampling site. We employ a normalized difference index to compute estimates of Chlorophyll a concentrations and analyze the increased attenuation of incident irradiance due to absorption by biomass. On a kilometer spatial scale, the presence of bottom <span class="hlt">ice</span> algae reduced the maximum transmitted irradiance by about 1.5 orders of magnitude when comparing floes of similar snow and <span class="hlt">ice</span> thicknesses. On a meter spatial scale, the combined effects of disparities in the depth and distribution of the overlying snow cover along with algae concentrations caused maximum transmittances to vary between 0.0577 and 0.282 at a single site. Temporal variability was also observed as the average integrated transmitted photosynthetically active radiation increased by one order of magnitude to 3.4% for the last eight measurement days compared to the first nine. Results provide insight on how interrelated physical and ecological parameters of sea <span class="hlt">ice</span> in varying time and space may impact new <span class="hlt">trends</span> in Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> and the progression of melt.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2791593','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2791593"><span>The future of <span class="hlt">ice</span> sheets and sea <span class="hlt">ice</span>: Between reversible retreat and unstoppable loss</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Notz, Dirk</p> <p>2009-01-01</p> <p>We discuss the existence of cryospheric “tipping points” in the Earth's climate system. Such critical thresholds have been suggested to exist for the disappearance of Arctic sea <span class="hlt">ice</span> and the retreat of <span class="hlt">ice</span> sheets: Once these <span class="hlt">ice</span> masses have shrunk below an anticipated critical <span class="hlt">extent</span>, the ice–albedo feedback might lead to the irreversible and unstoppable loss of the remaining <span class="hlt">ice</span>. We here give an overview of our current understanding of such threshold behavior. By using conceptual arguments, we review the recent findings that such a tipping point probably does not exist for the loss of Arctic summer sea <span class="hlt">ice</span>. Hence, in a cooler climate, sea <span class="hlt">ice</span> could recover rapidly from the loss it has experienced in recent years. In addition, we discuss why this recent rapid retreat of Arctic summer sea <span class="hlt">ice</span> might largely be a consequence of a slow shift in <span class="hlt">ice</span>-thickness distribution, which will lead to strongly increased year-to-year variability of the Arctic summer sea-<span class="hlt">ice</span> <span class="hlt">extent</span>. This variability will render seasonal forecasts of the Arctic summer sea-<span class="hlt">ice</span> <span class="hlt">extent</span> increasingly difficult. We also discuss why, in contrast to Arctic summer sea <span class="hlt">ice</span>, a tipping point is more likely to exist for the loss of the Greenland <span class="hlt">ice</span> sheet and the West Antarctic <span class="hlt">ice</span> sheet. PMID:19884496</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRC..121..267B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRC..121..267B"><span>Physical processes contributing to an <span class="hlt">ice</span> free Beaufort Sea during September 2012</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Babb, D. G.; Galley, R. J.; Barber, D. G.; Rysgaard, S.</p> <p>2016-01-01</p> <p>During the record September 2012 sea <span class="hlt">ice</span> minimum, the Beaufort Sea became <span class="hlt">ice</span> free for the first time during the observational record. Increased dynamic activity during late winter enabled increased open water and seasonal <span class="hlt">ice</span> coverage that contributed to negative sea <span class="hlt">ice</span> anomalies and positive solar absorption anomalies which drove rapid bottom melt and sea <span class="hlt">ice</span> loss. As had happened in the Beaufort Sea during previous years of exceptionally low September sea <span class="hlt">ice</span> <span class="hlt">extent</span>, anomalous solar absorption developed during May, increased during June, peaked during July, and persisted into October. However in situ observations from a single floe reveal less than 78% of the energy required for bottom melt during 2012 was available from solar absorption. We show that the 2012 sea <span class="hlt">ice</span> minimum in the Beaufort was the result of anomalously large solar absorption that was compounded by an arctic cyclone and other sources of heat such as solar transmission, oceanic upwelling, and riverine inputs, but was ultimately made possible through years of preconditioning toward a younger, thinner <span class="hlt">ice</span> pack. Significant negative <span class="hlt">trends</span> in sea <span class="hlt">ice</span> concentration between 1979 and 2012 from June to October, coupled with a tendency toward earlier sea <span class="hlt">ice</span> reductions have fostered a significant <span class="hlt">trend</span> of +12.9 MJ m-2 yr-1 in cumulative solar absorption, sufficient to melt an additional 4.3 cm m-2 yr-1. Overall through preconditioning toward a younger, thinner <span class="hlt">ice</span> pack the Beaufort Sea has become increasingly susceptible to increased sea <span class="hlt">ice</span> loss that may render it <span class="hlt">ice</span> free more frequently in coming years.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C43B0748B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C43B0748B"><span>Physical Processes contributing to an <span class="hlt">ice</span> free Beaufort Sea during September 2012</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Babb, D.; Galley, R.; Barber, D. G.; Rysgaard, S.</p> <p>2016-12-01</p> <p>During the record September 2012 sea <span class="hlt">ice</span> minimum the Beaufort Sea became <span class="hlt">ice</span> free for the first time during the observational record. Increased dynamic activity during late winter enabled increased open water and seasonal <span class="hlt">ice</span> coverage that contributed to negative sea <span class="hlt">ice</span> anomalies and positive solar absorption anomalies which drove rapid bottom melt and sea <span class="hlt">ice</span> loss. As had happened in the Beaufort Sea during previous years of exceptionally low September sea <span class="hlt">ice</span> <span class="hlt">extent</span>, anomalous solar absorption developed during May, increased during June, peaked during July and persisted into October. However in situ observations from a single floe reveal less than 78% of the energy required for bottom melt during 2012 was available from solar absorption. We show that the 2012 sea <span class="hlt">ice</span> minimum in the Beaufort was the result of anomalously large solar absorption that was compounded by an arctic cyclone and other sources of heat such as solar transmission, oceanic upwelling and riverine inputs, but was ultimately made possible through years of preconditioning towards a younger, thinner <span class="hlt">ice</span> pack. Significant negative <span class="hlt">trends</span> in sea <span class="hlt">ice</span> concentration between 1979 and 2012 from June to October, coupled with a tendency towards earlier sea <span class="hlt">ice</span> reductions have fostered a significant <span class="hlt">trend</span> of +12.9 MJ m-2 year-1 in cumulative solar absorption, sufficient to melt an additional 4.3 cm m-2 year-1. Overall through preconditioning towards a younger, thinner <span class="hlt">ice</span> pack the Beaufort Sea has become increasingly susceptible to increased sea <span class="hlt">ice</span> loss that may render it <span class="hlt">ice</span> free more frequently in coming years.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AdAtS..35..106Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AdAtS..35..106Z"><span>Record low sea-<span class="hlt">ice</span> concentration in the central Arctic during summer 2010</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhao, Jinping; Barber, David; Zhang, Shugang; Yang, Qinghua; Wang, Xiaoyu; Xie, Hongjie</p> <p>2018-01-01</p> <p>The Arctic sea-<span class="hlt">ice</span> <span class="hlt">extent</span> has shown a declining <span class="hlt">trend</span> over the past 30 years. <span class="hlt">Ice</span> coverage reached historic minima in 2007 and again in 2012. This <span class="hlt">trend</span> has recently been assessed to be unique over at least the last 1450 years. In the summer of 2010, a very low sea-<span class="hlt">ice</span> concentration (SIC) appeared at high Arctic latitudes—even lower than that of surrounding pack <span class="hlt">ice</span> at lower latitudes. This striking low <span class="hlt">ice</span> concentration—referred to here as a record low <span class="hlt">ice</span> concentration in the central Arctic (CARLIC)—is unique in our analysis period of 2003-15, and has not been previously reported in the literature. The CARLIC was not the result of <span class="hlt">ice</span> melt, because sea <span class="hlt">ice</span> was still quite thick based on in-situ <span class="hlt">ice</span> thickness measurements. Instead, divergent <span class="hlt">ice</span> drift appears to have been responsible for the CARLIC. A high correlation between SIC and wind stress curl suggests that the sea <span class="hlt">ice</span> drift during the summer of 2010 responded strongly to the regional wind forcing. The drift trajectories of <span class="hlt">ice</span> buoys exhibited a transpolar drift in the Atlantic sector and an eastward drift in the Pacific sector, which appeared to benefit the CARLIC in 2010. Under these conditions, more solar energy can penetrate into the open water, increasing melt through increased heat flux to the ocean. We speculate that this divergence of sea <span class="hlt">ice</span> could occur more often in the coming decades, and impact on hemispheric SIC and feed back to the climate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007GeoRL..3422504D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007GeoRL..3422504D"><span>Recent Northern Hemisphere snow cover <span class="hlt">extent</span> <span class="hlt">trends</span> and implications for the snow-albedo feedback</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Déry, Stephen J.; Brown, Ross D.</p> <p>2007-11-01</p> <p>Monotonic <span class="hlt">trend</span> analysis of Northern Hemisphere snow cover <span class="hlt">extent</span> (SCE) over the period 1972-2006 with the Mann-Kendall test reveals significant declines in SCE during spring over North America and Eurasia, with lesser declines during winter and some increases in fall SCE. The weekly mean <span class="hlt">trend</span> attains -1.28, -0.78, and -0.48 × 106 km2 (35 years)-1 over the Northern Hemisphere, North America, and Eurasia, respectively. The standardized SCE time series vary and <span class="hlt">trend</span> coherently over Eurasia and North America, with evidence of a poleward amplification of decreasing SCE <span class="hlt">trends</span> during spring. Multiple linear regression analyses reveal a significant dependence of the retreat of the spring continental SCE on latitude and elevation. The poleward amplification is consistent with an enhanced snow-albedo feedback over northern latitudes that acts to reinforce an initial anomaly in the cryospheric system.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19920073994&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3DParkinsons','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19920073994&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3DParkinsons"><span>Spatial patterns of increases and decreases in the length of the sea <span class="hlt">ice</span> season in the north polar region, 1979-1986</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>1992-01-01</p> <p>Recently it was reported that sea <span class="hlt">ice</span> <span class="hlt">extents</span> in the Northern Hemisphere showed a very slight but statistically significant decrease over the 8.8-year period of the Nimbus 7 scanning multichannel microwave radiometer (SMMR) data set. In this paper the same SMMR data are used to reveal spatial patterns in increasing and decreasing sea <span class="hlt">ice</span> coverage. Specifically, the length of the <span class="hlt">ice</span> season is mapped for each full year of the SMMR data set (1979-1986), and the <span class="hlt">trends</span> over the 8 years in these <span class="hlt">ice</span> season lengths are also mapped. These <span class="hlt">trends</span> show considerable spatial coherence, with a shortening in the sea <span class="hlt">ice</span> season apparent in much of the eastern hemisphere of the north polar <span class="hlt">ice</span> cover, particularly in the Sea of Okhotsk, the Barents Sea, and the Kara Sea, and a lengthening of the sea <span class="hlt">ice</span> season apparent in much of the western hemisphere of the north polar <span class="hlt">ice</span> cover, particularly in Davis Strait, the Labrador Sea, and the Beaufort Sea.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.T51K..01J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.T51K..01J"><span>New aerogeophysical data reveal the <span class="hlt">extent</span> of the Weddell Sea Rift beneath the Institute and Möller <span class="hlt">ice</span> streams</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jordan, T. A.; Ferraccioli, F.; Siegert, M. J.; Ross, N.; Corr, H.; Bingham, R. G.; Rippin, D. M.; Le Brocq, A. M.</p> <p>2011-12-01</p> <p>Significant continental rifting associated with Gondwana breakup has been widely recognised in the Weddell Sea region. However, plate reconstructions and the <span class="hlt">extent</span> of this rift system onshore beneath the West Antarctic <span class="hlt">Ice</span> Sheet (WAIS) are ambiguous, due to the paucity of modern geophysical data across the Institute and Möller <span class="hlt">ice</span> stream catchments. Understanding this region is key to unravelling Gondwana breakup and the possible kinematic links between the Weddell Sea and the West Antarctic Rift System. The nature of the underlying tectonic structure is also critical, as it provides the template for <span class="hlt">ice</span>-flow draining ~20% of the West Antarctic <span class="hlt">Ice</span> Sheet (WAIS). During the 2010/11 Antarctic field season ~25,000 km of new airborne radar, aerogravity and aeromagnetic data were collected to help unveil the crustal structure and geological boundary conditions beneath the Institute and Möller <span class="hlt">ice</span> streams. Our new potential field maps delineate varied subglacial geology beneath the glacial catchments, including Jurassic intrusive rocks, sedimentary basins, and Precambrian basement rocks of the Ellsworth Mountains. Inversion of airborne gravity data reveal significant crustal thinning directly beneath the faster flowing coastal parts of the Institute and Möller <span class="hlt">ice</span> streams. We suggest that continental rifting focussed along the Weddell Sea margin of the Ellsworth-Whitmore Mountains block, providing geological controls for the fast flowing <span class="hlt">ice</span> streams of the Weddell Sea Embayment. Further to the south we suggest that strike-slip motion between the East Antarctica and the Ellsworth-Whitmore Mountains block may provide a kinematic link between Cretaceous-Cenozoic extension in the West Antarctic Rift System and deformation in the Weddell Sea Embayment.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_9 --> <div id="page_10" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="181"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140006604','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140006604"><span><span class="hlt">Extent</span> of Low-accumulation 'Wind Glaze' Areas on the East Antarctic Plateau: Implications for Continental <span class="hlt">Ice</span> Mass Balance</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Scambos, Theodore A.; Frezzotti, Massimo; Haran, T.; Bohlander, J.; Lenaerts, J. T. M.; Van Den Broeke, M. R.; Jezek, K.; Long, D.; Urbini, S.; Farness, K.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20140006604'); toggleEditAbsImage('author_20140006604_show'); toggleEditAbsImage('author_20140006604_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20140006604_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20140006604_hide"></p> <p>2012-01-01</p> <p>Persistent katabatic winds form widely distributed localized areas of near-zero net surface accumulation on the East Antarctic <span class="hlt">ice</span> sheet (EAIS) plateau. These areas have been called 'glaze' surfaces due to their polished appearance. They are typically 2-200 square kilometers in area and are found on leeward slopes of <span class="hlt">ice</span>-sheet undulations and megadunes. Adjacent, leeward high-accumulation regions (isolated dunes) are generally smaller and do not compensate for the local low in surface mass balance (SMB). We use a combination of satellite remote sensing and field-gathered datasets to map the <span class="hlt">extent</span> of wind glaze in the EAIS above 1500m elevation. Mapping criteria are derived from distinctive surface and subsurface characteristics of glaze areas resulting from many years of intense annual temperature cycling without significant burial. Our results show that 11.2 plus or minus 1.7%, or 950 plus or minus 143 x 10(exp 3) square kilometers, of the EAIS above 1500m is wind glaze. Studies of SMB interpolate values across glaze regions, leading to overestimates of net mass input. Using our derived wind-glaze <span class="hlt">extent</span>, we estimate this excess in three recent models of Antarctic SMB at 46-82 Gt. The lowest-input model appears to best match the mean in regions of extensive wind glaze.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C23E..04A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C23E..04A"><span>What Models and Satellites Tell Us (and Don't Tell Us) About Arctic Sea <span class="hlt">Ice</span> Melt Season Length</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ahlert, A.; Jahn, A.</p> <p>2017-12-01</p> <p>Melt season length—the difference between the sea <span class="hlt">ice</span> melt onset date and the sea <span class="hlt">ice</span> freeze onset date—plays an important role in the radiation balance of the Arctic and the predictability of the sea <span class="hlt">ice</span> cover. However, there are multiple possible definitions for sea <span class="hlt">ice</span> melt and freeze onset in climate models, and none of them exactly correspond to the remote sensing definition. Using the CESM Large Ensemble model simulations, we show how this mismatch between model and remote sensing definitions of melt and freeze onset limits the utility of melt season remote sensing data for bias detection in models. It also opens up new questions about the precise physical meaning of the melt season remote sensing data. Despite these challenges, we find that the increase in melt season length in the CESM is not as large as that derived from remote sensing data, even when we account for internal variability and different definitions. At the same time, we find that the CESM ensemble members that have the largest <span class="hlt">trend</span> in sea <span class="hlt">ice</span> <span class="hlt">extent</span> over the period 1979-2014 also have the largest melt season <span class="hlt">trend</span>, driven primarily by the <span class="hlt">trend</span> towards later freeze onsets. This might be an indication that an underestimation of the melt season length <span class="hlt">trend</span> is one factor contributing to the generally underestimated sea <span class="hlt">ice</span> loss within the CESM, and potentially climate models in general.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150021053','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150021053"><span>Sea <span class="hlt">Ice</span> Outlook for September 2015 June Report - NASA Global Modeling and Assimilation Office</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cullather, Richard I.; Keppenne, Christian L.; Marshak, Jelena; Pawson, Steven; Schubert, Siegfried D.; Suarez, Max J.; Vernieres, Guillaume; Zhao, Bin</p> <p>2015-01-01</p> <p>The recent decline in perennial sea <span class="hlt">ice</span> cover in Arctic Ocean is a topic of enormous scientific interest and has relevance to a broad variety of scientific disciplines and human endeavors including biological and physical oceanography, atmospheric circulation, high latitude ecology, the sustainability of indigenous communities, commerce, and resource exploration. A credible seasonal prediction of sea <span class="hlt">ice</span> <span class="hlt">extent</span> would be of substantial use to many of the stakeholders in these fields and may also reveal details on the physical processes that result in the current <span class="hlt">trends</span> in the <span class="hlt">ice</span> cover. Forecasts are challenging due in part to limitations in the polar observing network, the large variability in the climate system, and an incomplete knowledge of the significant processes. Nevertheless it is a useful to understand the current capabilities of high latitude seasonal forecasting and identify areas where such forecasts may be improved. Since 2008 the Arctic Research Consortium of the United States (ARCUS) has conducted a seasonal forecasting contest in which the average Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> for the month of September (the month of the annual <span class="hlt">extent</span> minimum) is predicted from available forecasts in early June, July, and August. The competition is known as the Sea <span class="hlt">Ice</span> Outlook (SIO) but recently came under the auspices of the Sea <span class="hlt">Ice</span> Prediction Network (SIPN), and multi-agency funded project to evaluate the SIO. The forecasts are submitted based on modeling, statistical, and heuristic methods. Forecasts of Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> from the GMAO are derived from seasonal prediction system of the NASA Goddard Earth Observing System model, version 5 (GEOS 5) coupled atmosphere and ocean general circulation model (AOGCM). The projections are made in order to understand the relative skill of the forecasting system and to determine the effects of future improvements to the system. This years prediction is for a September average Arctic <span class="hlt">ice</span> <span class="hlt">extent</span> of 5.030.41 million km2.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRC..121.7308S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRC..121.7308S"><span>Variability, <span class="hlt">trends</span>, and predictability of seasonal sea <span class="hlt">ice</span> retreat and advance in the Chukchi Sea</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Serreze, Mark C.; Crawford, Alex D.; Stroeve, Julienne C.; Barrett, Andrew P.; Woodgate, Rebecca A.</p> <p>2016-10-01</p> <p>As assessed over the period 1979-2014, the date that sea <span class="hlt">ice</span> retreats to the shelf break (150 m contour) of the Chukchi Sea has a linear <span class="hlt">trend</span> of -0.7 days per year. The date of seasonal <span class="hlt">ice</span> advance back to the shelf break has a steeper <span class="hlt">trend</span> of about +1.5 days per year, together yielding an increase in the open water period of 80 days. Based on detrended time series, we ask how interannual variability in advance and retreat dates relate to various forcing parameters including radiation fluxes, temperature and wind (from numerical reanalyses), and the oceanic heat inflow through the Bering Strait (from in situ moorings). Of all variables considered, the retreat date is most strongly correlated (r ˜ 0.8) with the April through June Bering Strait heat inflow. After testing a suite of statistical linear models using several potential predictors, the best model for predicting the date of retreat includes only the April through June Bering Strait heat inflow, which explains 68% of retreat date variance. The best model predicting the <span class="hlt">ice</span> advance date includes the July through September inflow and the date of retreat, explaining 67% of advance date variance. We address these relationships by discussing heat balances within the Chukchi Sea, and the hypothesis of oceanic heat transport triggering ocean heat uptake and <span class="hlt">ice</span>-albedo feedback. Developing an operational prediction scheme for seasonal retreat and advance would require timely acquisition of Bering Strait heat inflow data. Predictability will likely always be limited by the chaotic nature of atmospheric circulation patterns.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015E%26PSL.429...69R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015E%26PSL.429...69R"><span>Surface exposure chronology of the Waimakariri glacial sequence in the Southern Alps of New Zealand: Implications for MIS-2 <span class="hlt">ice</span> <span class="hlt">extent</span> and LGM glacial mass balance</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rother, Henrik; Shulmeister, James; Fink, David; Alexander, David; Bell, David</p> <p>2015-11-01</p> <p>During the late Quaternary, the Southern Alps of New Zealand experienced multiple episodes of glaciation with large piedmont glaciers reaching the coastal plains in the west and expanding into the eastern alpine forelands. Here, we present a new 10Be exposure age chronology for a moraine sequence in the Waimakariri Valley (N-Canterbury), which has long been used as a reference record for correlating glacial events across New Zealand and the wider Southern Hemisphere. Our data indicate that the Waimakariri glacier reached its maximum last glaciation <span class="hlt">extent</span> prior to ∼26 ka well before the global last glaciation maximum (LGM). This was followed by a gradual reduction in <span class="hlt">ice</span> volume and the abandonment of the innermost LGM moraines at about 17.5 ka. Significantly, we find that during its maximum <span class="hlt">extent</span>, the Waimakariri glacier overflowed the Avoca Plateau, previously believed to represent a mid-Pleistocene glacial surface (i.e. MIS 8). At the same time, the glacier extended to a position downstream of the Waimakariri Gorge, some 15 km beyond the previously mapped LGM <span class="hlt">ice</span> limit. We use a simple steady-state mass balance model to test the sensitivity of past glacial accumulation to various climatic parameters, and to evaluate possible climate scenarios capable of generating the <span class="hlt">ice</span> volume required to reach the full local-LGM <span class="hlt">extent</span>. Model outcomes indicate that under New Zealand's oceanic setting, a cooling of 5 °C, assuming modern precipitation levels, or a cooling of 6.5 °C, assuming a one third reduction in precipitation, would suffice to drive the Waimakariri glacier to the eastern alpine forelands (Canterbury Plains). Our findings demonstrate that the scale of LGM glaciation in the Waimakariri Valley and adjacent major catchments, both in terms of <span class="hlt">ice</span> volume and downvalley <span class="hlt">ice</span> <span class="hlt">extent</span>, has been significantly underestimated. Our observation that high-lying glacial surfaces, so far believed to represent much older glacial episodes, were glaciated during the LGM</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/6760381-iceberg-severity-off-eastern-north-america-its-relationship-sea-ice-variability-climate-change','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/6760381-iceberg-severity-off-eastern-north-america-its-relationship-sea-ice-variability-climate-change"><span>Iceberg severity off eastern North America: Its relationship to sea <span class="hlt">ice</span> variability and climate change</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Marko, J.R.; Fissel, D.B.; Wadhams, P.</p> <p>1994-09-01</p> <p>Iceberg trajectory, deterioration (mass loss), and sea <span class="hlt">ice</span> data are reviewed to identify the sources of observed interannual and seasonal variations in the numbers of icebergs passing south of 48[degrees]N off eastern North America. The results show the dominant role of sea <span class="hlt">ice</span> in the observed variations. Important mechanisms involved include both seasonal modulation of the southerly iceberg flow by <span class="hlt">ice</span> cover control of probabilities for entrapment and decay in shallow water, and the suppression of iceberg melt/deterioration rates by high concentrations of sea <span class="hlt">ice</span>. The Labrador spring <span class="hlt">ice</span> <span class="hlt">extent</span>, shown to be the critical parameter in interannual iceberg numbermore » variability, was found to be either determined by or closely correlated with midwinter Davis Strait <span class="hlt">ice</span> <span class="hlt">extents</span>. Agreement obtained between observed year-to-year and seasonal number variations with computations based upon a simple iceberg dissipation model suggests that downstream iceberg numbers are relatively insensitive to iceberg production rates and to fluctuations in southerly iceberg fluxes in areas north of Baffin Island. Past variations in the Davis Strait <span class="hlt">ice</span> index and annual <span class="hlt">ice</span> <span class="hlt">extents</span> are studied to identify <span class="hlt">trends</span> and relationships between regional and larger-scale global climate parameters. It was found that, on decadal timescales in the post-1960 period of reasonable data quality, regional climate parameters have varied, roughly, out of phase with corresponding global and hemispheric changes. These observations are compared with expectations in terms of model results to evaluate current GCM-based capabilities for simulating recent regional behavior. 64 refs., 11 figs., 3 tabs.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C11C0930W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C11C0930W"><span>The Sea <span class="hlt">Ice</span> Index: A Resource for Cryospheric Knowledge Mobilization</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Windnagel, A. K.; Fetterer, F. M.</p> <p>2017-12-01</p> <p>The Sea <span class="hlt">Ice</span> Index is a popular source of information about Arctic and Antarctic sea <span class="hlt">ice</span> data and <span class="hlt">trends</span> created at the National Snow and <span class="hlt">Ice</span> Data Center (NSIDC) in 2002. It has been used by cryospheric scientists, cross-discipline scientists, the press, policy makers, and the public for the past 15 years. The Index started as a prototype sea <span class="hlt">ice</span> <span class="hlt">extent</span> product in 2001 and was envisioned as a website that would meet a need for readily accessible, easy-to-use information on sea <span class="hlt">ice</span> <span class="hlt">trends</span> and anomalies, with products that would assist in monitoring and diagnosing the <span class="hlt">ice</span> <span class="hlt">extent</span> minima that were gaining increasing attention in the research community in the late 1990s. The goal was to easily share these valuable data with everyone that needed them, which is the essence of knowledge mobilization. As time has progressed, we have found new ways of disseminating the information carried by the data by providing simple pictures on a website, animating those images, creating Google Earth animations that show the data on a globe, providing simple text files of data values that do not require special software to read, writing a monthly blog about the data that has over 1.7 million readers annually, providing the data to NOAA's Science on Sphere to be seen in museums and classrooms across 23 countries, and creating geo-registered images for use in geospatial software. The Index helps to bridge the gap between sea <span class="hlt">ice</span> science and the public. Through NSIDC's User Services Office, we receive feedback on the Index and have endeavored to meet the changing needs of our stakeholder communities to best mobilize this knowledge in their direction. We have learned through trial-by-fire the best practices for delivering these data and data services. This tells the tale of managing an unassuming data set as it has journeyed from a simple product consisting of images of sea <span class="hlt">ice</span> to one that is robust enough to be used in the IPCC Climate Change Report but easy enough to be understood by K-12</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140017491','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140017491"><span>NASA Team 2 Sea <span class="hlt">Ice</span> Concentration Algorithm Retrieval Uncertainty</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Brucker, Ludovic; Cavalieri, Donald J.; Markus, Thorsten; Ivanoff, Alvaro</p> <p>2014-01-01</p> <p>Satellite microwave radiometers are widely used to estimate sea <span class="hlt">ice</span> cover properties (concentration, <span class="hlt">extent</span>, and area) through the use of sea <span class="hlt">ice</span> concentration (IC) algorithms. Rare are the algorithms providing associated IC uncertainty estimates. Algorithm uncertainty estimates are needed to assess accurately global and regional <span class="hlt">trends</span> in IC (and thus <span class="hlt">extent</span> and area), and to improve sea <span class="hlt">ice</span> predictions on seasonal to interannual timescales using data assimilation approaches. This paper presents a method to provide relative IC uncertainty estimates using the enhanced NASA Team (NT2) IC algorithm. The proposed approach takes advantage of the NT2 calculations and solely relies on the brightness temperatures (TBs) used as input. NT2 IC and its associated relative uncertainty are obtained for both the Northern and Southern Hemispheres using the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) TB. NT2 IC relative uncertainties estimated on a footprint-by-footprint swath-by-swath basis were averaged daily over each 12.5-km grid cell of the polar stereographic grid. For both hemispheres and throughout the year, the NT2 relative uncertainty is less than 5%. In the Southern Hemisphere, it is low in the interior <span class="hlt">ice</span> pack, and it increases in the marginal <span class="hlt">ice</span> zone up to 5%. In the Northern Hemisphere, areas with high uncertainties are also found in the high IC area of the Central Arctic. Retrieval uncertainties are greater in areas corresponding to NT2 <span class="hlt">ice</span> types associated with deep snow and new <span class="hlt">ice</span>. Seasonal variations in uncertainty show larger values in summer as a result of melt conditions and greater atmospheric contributions. Our analysis also includes an evaluation of the NT2 algorithm sensitivity to AMSR-E sensor noise. There is a 60% probability that the IC does not change (to within the computed retrieval precision of 1%) due to sensor noise, and the cumulated probability shows that there is a 90% chance that the IC varies by less than</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016TCry...10.2275T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016TCry...10.2275T"><span>The EUMETSAT sea <span class="hlt">ice</span> concentration climate data record</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tonboe, Rasmus T.; Eastwood, Steinar; Lavergne, Thomas; Sørensen, Atle M.; Rathmann, Nicholas; Dybkjær, Gorm; Toudal Pedersen, Leif; Høyer, Jacob L.; Kern, Stefan</p> <p>2016-09-01</p> <p>An Arctic and Antarctic sea <span class="hlt">ice</span> area and <span class="hlt">extent</span> dataset has been generated by EUMETSAT's Ocean and Sea <span class="hlt">Ice</span> Satellite Application Facility (OSISAF) using the record of microwave radiometer data from NASA's Nimbus 7 Scanning Multichannel Microwave radiometer (SMMR) and the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager and Sounder (SSMIS) satellite sensors. The dataset covers the period from October 1978 to April 2015 and updates and further developments are planned for the next phase of the project. The methodology for computing the sea <span class="hlt">ice</span> concentration uses (1) numerical weather prediction (NWP) data input to a radiative transfer model for reduction of the impact of weather conditions on the measured brightness temperatures; (2) dynamical algorithm tie points to mitigate <span class="hlt">trends</span> in residual atmospheric, sea <span class="hlt">ice</span>, and water emission characteristics and inter-sensor differences/biases; and (3) a hybrid sea <span class="hlt">ice</span> concentration algorithm using the Bristol algorithm over <span class="hlt">ice</span> and the Bootstrap algorithm in frequency mode over open water. A new sea <span class="hlt">ice</span> concentration uncertainty algorithm has been developed to estimate the spatial and temporal variability in sea <span class="hlt">ice</span> concentration retrieval accuracy. A comparison to US National <span class="hlt">Ice</span> Center sea <span class="hlt">ice</span> charts from the Arctic and the Antarctic shows that <span class="hlt">ice</span> concentrations are higher in the <span class="hlt">ice</span> charts than estimated from the radiometer data at intermediate sea <span class="hlt">ice</span> concentrations between open water and 100 % <span class="hlt">ice</span>. The sea <span class="hlt">ice</span> concentration climate data record is available for download at <a href=" http://www.osi-saf.org"target="_blank">www.osi-saf.org</a>, including documentation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GeoRL..43.1642G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GeoRL..43.1642G"><span>Predictability of the Arctic sea <span class="hlt">ice</span> edge</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Goessling, H. F.; Tietsche, S.; Day, J. J.; Hawkins, E.; Jung, T.</p> <p>2016-02-01</p> <p>Skillful sea <span class="hlt">ice</span> forecasts from days to years ahead are becoming increasingly important for the operation and planning of human activities in the Arctic. Here we analyze the potential predictability of the Arctic sea <span class="hlt">ice</span> edge in six climate models. We introduce the integrated <span class="hlt">ice</span>-edge error (IIEE), a user-relevant verification metric defined as the area where the forecast and the "truth" disagree on the <span class="hlt">ice</span> concentration being above or below 15%. The IIEE lends itself to decomposition into an absolute <span class="hlt">extent</span> error, corresponding to the common sea <span class="hlt">ice</span> <span class="hlt">extent</span> error, and a misplacement error. We find that the often-neglected misplacement error makes up more than half of the climatological IIEE. In idealized forecast ensembles initialized on 1 July, the IIEE grows faster than the absolute <span class="hlt">extent</span> error. This means that the Arctic sea <span class="hlt">ice</span> edge is less predictable than sea <span class="hlt">ice</span> <span class="hlt">extent</span>, particularly in September, with implications for the potential skill of end-user relevant forecasts.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19840019240','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19840019240"><span>Satellite remote sensing over <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Thomas, R. H.</p> <p>1984-01-01</p> <p>Satellite remote sensing provides unique opportunities for observing <span class="hlt">ice</span>-covered terrain. Passive-microwave data give information on snow <span class="hlt">extent</span> on land, sea-<span class="hlt">ice</span> <span class="hlt">extent</span> and type, and zones of summer melting on the polar <span class="hlt">ice</span> sheets, with the potential for estimating snow-accumulation rates on these <span class="hlt">ice</span> sheets. All weather, high-resolution imagery of sea <span class="hlt">ice</span> is obtained using synthetic aperture radars, and <span class="hlt">ice</span>-movement vectors can be deduced by comparing sequential images of the same region. Radar-altimetry data provide highly detailed information on <span class="hlt">ice</span>-sheet topography, with the potential for deducing thickening/thinning rates from repeat surveys. The coastline of Antarctica can be mapped accurately using altimetry data, and the size and spatial distribution of icebergs can be monitored. Altimetry data also distinguish open ocean from pack <span class="hlt">ice</span> and they give an indication of sea-<span class="hlt">ice</span> characteristics.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19860043882&hterms=Antarctic+icebergs&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DAntarctic%2Bicebergs','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19860043882&hterms=Antarctic+icebergs&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DAntarctic%2Bicebergs"><span>Satellite remote sensing over <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Thomas, R. H.</p> <p>1986-01-01</p> <p>Satellite remote sensing provides unique opportunities for observing <span class="hlt">ice</span>-covered terrain. Passive-microwave data give information on snow <span class="hlt">extent</span> on land, sea-<span class="hlt">ice</span> <span class="hlt">extent</span> and type, and zones of summer melting on the polar <span class="hlt">ice</span> sheets, with the potential for estimating snow-accumulation rates on these <span class="hlt">ice</span> sheets. All weather, high-resolution imagery of sea <span class="hlt">ice</span> is obtained using synthetic aperture radars, and <span class="hlt">ice</span>-movement vectors can be deduced by comparing sequential images of the same region. Radar-altimetry data provide highly detailed information on <span class="hlt">ice</span>-sheet topography, with the potential for deducing thickening/thinning rates from repeat surveys. The coastline of Antarctica can be mapped accurately using altimetry data, and the size and spatial distribution of icebergs can be monitored. Altimetry data also distinguish open ocean from pack <span class="hlt">ice</span> and they give an indication of sea-<span class="hlt">ice</span> characteristics.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5371420','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5371420"><span>The frequency and <span class="hlt">extent</span> of sub-<span class="hlt">ice</span> phytoplankton blooms in the Arctic Ocean</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Horvat, Christopher; Jones, David Rees; Iams, Sarah; Schroeder, David; Flocco, Daniela; Feltham, Daniel</p> <p>2017-01-01</p> <p>In July 2011, the observation of a massive phytoplankton bloom underneath a sea ice–covered region of the Chukchi Sea shifted the scientific consensus that regions of the Arctic Ocean covered by sea <span class="hlt">ice</span> were inhospitable to photosynthetic life. Although the impact of widespread phytoplankton blooms under sea <span class="hlt">ice</span> on Arctic Ocean ecology and carbon fixation is potentially marked, the prevalence of these events in the modern Arctic and in the recent past is, to date, unknown. We investigate the timing, frequency, and evolution of these events over the past 30 years. Although sea <span class="hlt">ice</span> strongly attenuates solar radiation, it has thinned significantly over the past 30 years. The thinner summertime Arctic sea <span class="hlt">ice</span> is increasingly covered in melt ponds, which permit more light penetration than bare or snow-covered <span class="hlt">ice</span>. Our model results indicate that the recent thinning of Arctic sea <span class="hlt">ice</span> is the main cause of a marked increase in the prevalence of light conditions conducive to sub-<span class="hlt">ice</span> blooms. We find that as little as 20 years ago, the conditions required for sub-<span class="hlt">ice</span> blooms may have been uncommon, but their frequency has increased to the point that nearly 30% of the <span class="hlt">ice</span>-covered Arctic Ocean in July permits sub-<span class="hlt">ice</span> blooms. Recent climate change may have markedly altered the ecology of the Arctic Ocean. PMID:28435859</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMIN11C1538S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMIN11C1538S"><span>The Timing of Arctic Sea <span class="hlt">Ice</span> Advance and Retreat as an Indicator of <span class="hlt">Ice</span>-Dependent Marine Mammal Habitat</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stern, H. L.; Laidre, K. L.</p> <p>2013-12-01</p> <p>The Arctic is widely recognized as the front line of climate change. Arctic air temperature is rising at twice the global average rate, and the sea-<span class="hlt">ice</span> cover is shrinking and thinning, with total disappearance of summer sea <span class="hlt">ice</span> projected to occur in a matter of decades. Arctic marine mammals such as polar bears, seals, walruses, belugas, narwhals, and bowhead whales depend on the sea-<span class="hlt">ice</span> cover as an integral part of their existence. While the downward <span class="hlt">trend</span> in sea-<span class="hlt">ice</span> <span class="hlt">extent</span> in a given month is an often-used metric for quantifying physical changes in the <span class="hlt">ice</span> cover, it is not the most relevant measure for characterizing changes in the sea-<span class="hlt">ice</span> habitat of marine mammals. Species that depend on sea <span class="hlt">ice</span> are behaviorally tied to the annual retreat of sea <span class="hlt">ice</span> in the spring and advance in the fall. Changes in the timing of the spring retreat and the fall advance are more relevant to Arctic marine species than changes in the areal sea-<span class="hlt">ice</span> coverage in a particular month of the year. Many ecologically important regions of the Arctic are essentially <span class="hlt">ice</span>-covered in winter and <span class="hlt">ice</span>-free in summer, and will probably remain so for a long time into the future. But the dates of sea-<span class="hlt">ice</span> retreat in spring and advance in fall are key indicators of climate change for <span class="hlt">ice</span>-dependent marine mammals. We use daily sea-<span class="hlt">ice</span> concentration data derived from satellite passive microwave sensors to calculate the dates of sea-<span class="hlt">ice</span> retreat in spring and advance in fall in 12 regions of the Arctic for each year from 1979 through 2013. The regions include the peripheral seas around the Arctic Ocean (Beaufort, Chukchi, East Siberian, Laptev, Kara, Barents), the Canadian Arctic Archipelago, and the marginal seas (Okhotsk, Bering, East Greenland, Baffin Bay, Hudson Bay). We find that in 11 of the 12 regions (all except the Bering Sea), sea <span class="hlt">ice</span> is retreating earlier in spring and advancing later in fall. Rates of spring retreat range from -5 to -8 days/decade, and rates of fall advance range from +5 to +9</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMGC21D0992B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMGC21D0992B"><span>Surface Exposure Dating of the Huancané III Moraines in Peru: A Record of Quelccaya <span class="hlt">Ice</span> Cap's Maximum <span class="hlt">Extent</span> during the Last Glacial Period</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Baranes, H. E.; Kelly, M. A.; Stroup, J. S.; Howley, J. A.; Lowell, T. V.</p> <p>2012-12-01</p> <p>The climatic conditions that influenced the tropics during the height of the last glacial period are not well defined and controversial. There are disparities in estimates of temperature anomalies (e.g., MARGO, 2009; Rind and Peteet, 1985; CLIMAP, 1976), and critical terrestrial paleotemperature proxy records in tropical regions are poorly dated (e.g., Porter, 2001). Defining these conditions is important for understanding the mechanisms that cause major shifts in climate, as the tropics are a primary driver of atmospheric and oceanic circulation. This study aims to constrain the timing of maximum glacier <span class="hlt">extents</span> in the Cordillera Oriental in southern Peru during the last glacial period by applying surface exposure (beryllium-10) dating to the Huancané III (Hu-III) moraines. The Hu-III moraines mark the maximum <span class="hlt">extent</span> of Quelccaya <span class="hlt">Ice</span> Cap (QIC) (13.93°S, 70.83°W), the largest tropical <span class="hlt">ice</span> cap, during the last <span class="hlt">ice</span> age. The eight beryllium-10 ages presented here yield 17,056 ± 520 yrs ago as a minimum age for the onset of recession from the <span class="hlt">ice</span> cap advance marked by the Hu-III moraines. Comparing this age to other paleoclimate records indicates that the <span class="hlt">ice</span> cap advance marked by the Hu-III moraines is more likely associated with a North Atlantic climate event known as Heinrich I (H1; 16,800 yrs ago, Bond et al., 1992, 1993) than with global cooling at the Last Glacial Maximum (LGM; ~21,000 yrs ago, Denton and Hughes, 1981). This result suggests that climate processes in the North Atlantic region are linked to climatic conditions in the tropical Andes. A mesoscale climate model and an <span class="hlt">ice</span>-flow model are currently being developed for QIC. The moraine data presented in this study will be used with these two models to test response of QIC to North Atlantic and global climate events.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.C41C0478A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.C41C0478A"><span>Controls on Arctic sea <span class="hlt">ice</span> from first-year and multi-year <span class="hlt">ice</span> survival rates</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Armour, K.; Bitz, C. M.; Hunke, E. C.; Thompson, L.</p> <p>2009-12-01</p> <p>The recent decrease in Arctic sea <span class="hlt">ice</span> cover has transpired with a significant loss of multi-year (MY) <span class="hlt">ice</span>. The transition to an Arctic that is populated by thinner first-year (FY) sea <span class="hlt">ice</span> has important implications for future <span class="hlt">trends</span> in area and volume. We develop a reduced model for Arctic sea <span class="hlt">ice</span> with which we investigate how the survivability of FY and MY <span class="hlt">ice</span> control various aspects of the sea-<span class="hlt">ice</span> system. We demonstrate that Arctic sea-<span class="hlt">ice</span> area and volume behave approximately as first-order autoregressive processes, which allows for a simple interpretation of September sea-<span class="hlt">ice</span> in which its mean state, variability, and sensitivity to climate forcing can be described naturally in terms of the average survival rates of FY and MY <span class="hlt">ice</span>. This model, used in concert with a sea-<span class="hlt">ice</span> simulation that traces FY and MY <span class="hlt">ice</span> areas to estimate the survival rates, reveals that small <span class="hlt">trends</span> in the <span class="hlt">ice</span> survival rates explain the decline in total Arctic <span class="hlt">ice</span> area, and the relatively larger loss of MY <span class="hlt">ice</span> area, over the period 1979-2006. Additionally, our model allows for a calculation of the persistence time scales of September area and volume anomalies. A relatively short memory time scale for <span class="hlt">ice</span> area (~ 1 year) implies that Arctic <span class="hlt">ice</span> area is nearly in equilibrium with long-term climate forcing at all times, and therefore observed <span class="hlt">trends</span> in area are a clear indication of a changing climate. A longer memory time scale for <span class="hlt">ice</span> volume (~ 5 years) suggests that volume can be out of equilibrium with climate forcing for long periods of time, and therefore <span class="hlt">trends</span> in <span class="hlt">ice</span> volume are difficult to distinguish from its natural variability. With our reduced model, we demonstrate the connection between memory time scale and sensitivity to climate forcing, and discuss the implications that a changing memory time scale has on the trajectory of <span class="hlt">ice</span> area and volume in a warming climate. Our findings indicate that it is unlikely that a “tipping point” in September <span class="hlt">ice</span> area and volume will be</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100033640','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100033640"><span>The Satellite Passive-Microwave Record of Sea <span class="hlt">Ice</span> in the Ross Sea Since Late 1978</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>2009-01-01</p> <p>Satellites have provided us with a remarkable ability to monitor many aspects of the globe day-in and day-out and sea <span class="hlt">ice</span> is one of numerous variables that by now have quite substantial satellite records. Passive-microwave data have been particularly valuable in sea <span class="hlt">ice</span> monitoring, with a record that extends back to August 1987 on daily basis (for most of the period), to November 1970 on a less complete basis (again for most of the period), and to December 1972 on a less complete basis. For the period since November 1970, Ross Sea sea <span class="hlt">ice</span> imagery is available at spatial resolution of approximately 25 km. This allows good depictions of the seasonal advance and retreat of the <span class="hlt">ice</span> cover each year, along with its marked interannual variability. The Ross Sea <span class="hlt">ice</span> <span class="hlt">extent</span> typically reaches a minimum of approximately 0.7 x 10(exp 6) square kilometers in February, rising to a maximum of approximately 4.0 x 10(exp 6) square kilometers in September, with much variability among years for both those numbers. The Ross Sea images show clearly the day-by-day activity greatly from year to year. Animations of the data help to highlight the dynamic nature of the Ross Sea <span class="hlt">ice</span> cover. The satellite data also allow calculation of <span class="hlt">trends</span> in the <span class="hlt">ice</span> cover over the period of the satellite record. Using linear least-squares fits, the Ross Sea <span class="hlt">ice</span> <span class="hlt">extent</span> increased at an average rate of 12,600 plus or minus 1,800 square kilometers per year between November 1978 and December 2007, with every month exhibiting increased <span class="hlt">ice</span> <span class="hlt">extent</span> and the rates of increase ranging from a low of 7,500 plus or minus 5,000 square kilometers per year for the February <span class="hlt">ice</span> <span class="hlt">extents</span> to a high of 20,300 plus or minus 6,100 kilometers per year for the October <span class="hlt">ice</span> <span class="hlt">extents</span>. On a yearly average basis, for 1979-2007 the Ross Sea <span class="hlt">ice</span> <span class="hlt">extent</span> increased at a rate of 4.8 plus or minus 1.6 % per decade. Placing the Ross Sea in the context of the Southern Ocean as a whole, over the November 1978-December 2007 period the Ross Sea had</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C41C1237P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C41C1237P"><span>Sensitivity of Totten Glacier <span class="hlt">Ice</span> Shelf <span class="hlt">extent</span> and grounding line to oceanic forcing</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pelle, T.; Morlighem, M.; Choi, Y.</p> <p>2017-12-01</p> <p>Totten Glacier is a major outlet glacier of the East Antarctic <span class="hlt">Ice</span> Sheet and has been shown to be vulnerable to ocean-induced melt in both its past and present states. The intrusion of warm, circumpolar deep water beneath the Totten Glacier <span class="hlt">Ice</span> Shelf (TGIS) has been observed to accelerate <span class="hlt">ice</span> shelf thinning and promote iceberg calving, a primary mechanism of mass discharge from Totten. As such, accurately simulating TGIS's <span class="hlt">ice</span> front dynamics is crucial to the predictive capabilities of <span class="hlt">ice</span> sheet models in this region. Here, we study the TGIS using the <span class="hlt">Ice</span> Sheet System Model (ISSM) and test the applicability of three calving laws: Crevasse Formation calving, Eigen calving, and Tensile Stress calving. We simulate the evolution of Totten Glacier through 2100 under enhanced oceanic forcing in order to investigate both future changes in <span class="hlt">ice</span> front dynamics and possible thresholds of instability. In addition, we artificially retreat Totten's <span class="hlt">ice</span> front position and allow the model to proceed dynamically in order to analyze the response of the glacier to calving events. Our analyses show that Tensile Stress calving most accurately reproduces Totten Glacier's observed <span class="hlt">ice</span> front position. Furthermore, unstable grounding line retreat is projected when Totten is simulated under stronger oceanic thermal forcing scenarios and when the calving front is significantly retreated.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009JGRA..114.0I06L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009JGRA..114.0I06L"><span>Stratospheric and solar cycle effects on long-term variability of mesospheric <span class="hlt">ice</span> clouds</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lübken, F.-J.; Berger, U.; Baumgarten, G.</p> <p>2009-11-01</p> <p>Model results of mesospheric <span class="hlt">ice</span> layers and background conditions at 69°N from 1961 to 2008 are analyzed. The model nudges to European Centre for Medium-Range Weather Forecasts data below ˜45 km. Greenhouse gas concentrations in the mesosphere are kept constant. At polar mesospheric cloud (PMC) altitudes (83 km) temperatures decrease until the mid 1990s by -0.08 K/yr resulting in <span class="hlt">trends</span> of PMC brightness, occurrence rates, and, to a lesser <span class="hlt">extent</span>, in PMC altitudes (-0.0166 km/yr). <span class="hlt">Ice</span> layer <span class="hlt">trends</span> are consistent with observations by ground-based and satellite instruments. Water vapor increases at PMC heights and decreases above due to increased freeze-drying caused by the temperature <span class="hlt">trend</span>. Temperature <span class="hlt">trends</span> in the mesosphere mainly come from shrinking of the stratosphere and from dynamical effects. A solar cycle modulation of H2O is observed in the model consistent with satellite observations. The effect on <span class="hlt">ice</span> layers is reduced because of redistribution of H2O by freeze-drying. The accidental coincidence of low temperatures and solar cycle minimum in the mid 1990s leads to an overestimation of solar effects on <span class="hlt">ice</span> layers. A strong correlation between temperatures and PMC altitudes is observed. Applied to historical measurements this gives negligible temperature <span class="hlt">trends</span> at PMC altitudes (˜0.01-0.02 K/yr). Strong correlations between PMC parameters and background conditions deduced from the model confirm the standard scenario of PMC formation. The PMC sensitivity on temperatures, water vapor, and Ly-α is investigated. PMC heights show little variation with background parameters whereas brightness and occurrence rates show large variations. None of the background parameters can be ignored regarding its influence on <span class="hlt">ice</span> layers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009JGRD..114.0I06L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009JGRD..114.0I06L"><span>Stratospheric and solar cycle effects on long-term variability of mesospheric <span class="hlt">ice</span> clouds</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lübken, F.-J.; Berger, U.; Baumgarten, G.</p> <p>2009-01-01</p> <p>Model results of mesospheric <span class="hlt">ice</span> layers and background conditions at 69°N from 1961 to 2008 are analyzed. The model nudges to European Centre for Medium-Range Weather Forecasts data below ˜45 km. Greenhouse gas concentrations in the mesosphere are kept constant. At polar mesospheric cloud (PMC) altitudes (83 km) temperatures decrease until the mid 1990s by -0.08 K/yr resulting in <span class="hlt">trends</span> of PMC brightness, occurrence rates, and, to a lesser <span class="hlt">extent</span>, in PMC altitudes (-0.0166 km/yr). <span class="hlt">Ice</span> layer <span class="hlt">trends</span> are consistent with observations by ground-based and satellite instruments. Water vapor increases at PMC heights and decreases above due to increased freeze-drying caused by the temperature <span class="hlt">trend</span>. Temperature <span class="hlt">trends</span> in the mesosphere mainly come from shrinking of the stratosphere and from dynamical effects. A solar cycle modulation of H2O is observed in the model consistent with satellite observations. The effect on <span class="hlt">ice</span> layers is reduced because of redistribution of H2O by freeze-drying. The accidental coincidence of low temperatures and solar cycle minimum in the mid 1990s leads to an overestimation of solar effects on <span class="hlt">ice</span> layers. A strong correlation between temperatures and PMC altitudes is observed. Applied to historical measurements this gives negligible temperature <span class="hlt">trends</span> at PMC altitudes (˜0.01-0.02 K/yr). Strong correlations between PMC parameters and background conditions deduced from the model confirm the standard scenario of PMC formation. The PMC sensitivity on temperatures, water vapor, and Ly-α is investigated. PMC heights show little variation with background parameters whereas brightness and occurrence rates show large variations. None of the background parameters can be ignored regarding its influence on <span class="hlt">ice</span> layers.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_10 --> <div id="page_11" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="201"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120009093','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120009093"><span>The Antarctic <span class="hlt">Ice</span> Sheet, Sea <span class="hlt">Ice</span>, and the Ozone Hole: Satellite Observations of how they are Changing</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>2012-01-01</p> <p>Antarctica is the Earth's coldest and highest continent and has major impacts on the climate and life of the south polar vicinity. It is covered almost entirely by the Earth's largest <span class="hlt">ice</span> sheet by far, with a volume of <span class="hlt">ice</span> so great that if all the Antarctic <span class="hlt">ice</span> were to go into the ocean (as <span class="hlt">ice</span> or liquid water), this would produce a global sea level rise of about 60 meters (197 feet). The continent is surrounded by sea <span class="hlt">ice</span> that in the wintertime is even more expansive than the continent itself and in the summertime reduces to only about a sixth of its wintertime <span class="hlt">extent</span>. Like the continent, the expansive sea <span class="hlt">ice</span> cover has major impacts, reflecting the sun's radiation back to space, blocking exchanges between the ocean and the atmosphere, and providing a platform for some animal species while impeding other species. Far above the continent, the Antarctic ozone hole is a major atmospheric phenomenon recognized as human-caused and potentially quite serious to many different life forms. Satellites are providing us with remarkable information about the <span class="hlt">ice</span> sheet, the sea <span class="hlt">ice</span>, and the ozone hole. Satellite visible and radar imagery are providing views of the large scale structure of the <span class="hlt">ice</span> sheet never seen before; satellite laser altimetry has produced detailed maps of the topography of the <span class="hlt">ice</span> sheet; and an innovative gravity-measuring two-part satellite has allowed mapping of regions of mass loss and mass gain on the <span class="hlt">ice</span> sheet. The surrounding sea <span class="hlt">ice</span> cover has a satellite record that goes back to the 1970s, allowing <span class="hlt">trend</span> studies that show a decreasing sea <span class="hlt">ice</span> presence in the region of the Bellingshausen and Amundsen seas, to the west of the prominent Antarctic Peninsula, but increasing sea <span class="hlt">ice</span> presence around much of the rest of the continent. Overall, sea <span class="hlt">ice</span> <span class="hlt">extent</span> around Antarctica has increased at an average rate of about 17,000 square kilometers per year since the late 1970s, as determined from satellite microwave data that can be collected under both light and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMGC51F1065F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMGC51F1065F"><span><span class="hlt">Trends</span> in Sea <span class="hlt">Ice</span> Cover, Sea Surface Temperature, and Chlorophyll Biomass Across a Marine Distributed Biological Observatory in the Pacific Arctic Region</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Frey, K. E.; Grebmeier, J. M.; Cooper, L. W.; Wood, C.; Panday, P. K.</p> <p>2011-12-01</p> <p>The northern Bering and Chukchi Seas in the Pacific Arctic Region (PAR) are among the most productive marine ecosystems in the world and act as important carbon sinks, particularly during May and June when seasonal sea <span class="hlt">ice</span>-associated phytoplankton blooms occur throughout the region. Recent dramatic shifts in seasonal sea <span class="hlt">ice</span> cover across the PAR should have profound consequences for this seasonal phytoplankton production as well as the intimately linked higher trophic levels. In order to investigate ecosystem responses to these observed recent shifts in sea <span class="hlt">ice</span> cover, the development of a prototype Distributed Biological Observatory (DBO) is now underway in the PAR. The DBO is being developed as an internationally-coordinated change detection array that allows for consistent sampling and monitoring at five spatially explicit biologically productive locations across a latitudinal gradient: (1) DBO-SLP (south of St. Lawrence Island (SLI)), (2) DBO-NBS (north of SLI), (3) DBO-SCS (southern Chukchi Sea), (4) DBO-CCS (central Chukchi Sea), and (5) DBO-BCA (Barrow Canyon Arc). Standardized measurements at many of the DBO sites were made by multiple research cruises during the 2010 and 2011 pilot years, and will be expanded with the development of the DBO in coming years. In order to provide longer-term context for the changes occurring across the PAR, we utilize multi-sensor satellite data to investigate recent <span class="hlt">trends</span> in sea <span class="hlt">ice</span> cover, chlorophyll biomass, and sea surface temperatures for each of the five DBO sites, as well as a sixth long-term observational site in the Bering Strait. Satellite observations show that over the past three decades, <span class="hlt">trends</span> in sea <span class="hlt">ice</span> cover in the PAR have been heterogeneous, with significant declines in the Chukchi Sea, slight declines in the Bering Strait region, but increases in the northern Bering Sea south of SLI. Declines in the persistence of seasonal sea <span class="hlt">ice</span> cover in the Chukchi Sea and Bering Strait region are due to both earlier sea</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5008214','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5008214"><span>Arctic marine mammal population status, sea <span class="hlt">ice</span> habitat loss, and conservation recommendations for the 21st century</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Stern, Harry; Kovacs, Kit M.; Lowry, Lloyd; Moore, Sue E.; Regehr, Eric V.; Ferguson, Steven H.; Wiig, Øystein; Boveng, Peter; Angliss, Robyn P.; Born, Erik W.; Litovka, Dennis; Quakenbush, Lori; Lydersen, Christian; Vongraven, Dag; Ugarte, Fernando</p> <p>2015-01-01</p> <p>Abstract Arctic marine mammals (AMMs) are icons of climate change, largely because of their close association with sea <span class="hlt">ice</span>. However, neither a circumpolar assessment of AMM status nor a standardized metric of sea <span class="hlt">ice</span> habitat change is available. We summarized available data on abundance and <span class="hlt">trend</span> for each AMM species and recognized subpopulation. We also examined species diversity, the <span class="hlt">extent</span> of human use, and temporal <span class="hlt">trends</span> in sea <span class="hlt">ice</span> habitat for 12 regions of the Arctic by calculating the dates of spring sea <span class="hlt">ice</span> retreat and fall sea <span class="hlt">ice</span> advance from satellite data (1979–2013). Estimates of AMM abundance varied greatly in quality, and few studies were long enough for <span class="hlt">trend</span> analysis. Of the AMM subpopulations, 78% (61 of 78) are legally harvested for subsistence purposes. Changes in sea <span class="hlt">ice</span> phenology have been profound. In all regions except the Bering Sea, the duration of the summer (i.e., reduced <span class="hlt">ice</span>) period increased by 5–10 weeks and by >20 weeks in the Barents Sea between 1979 and 2013. In light of generally poor data, the importance of human use, and forecasted environmental changes in the 21st century, we recommend the following for effective AMM conservation: maintain and improve comanagement by local, federal, and international partners; recognize spatial and temporal variability in AMM subpopulation response to climate change; implement monitoring programs with clear goals; mitigate cumulative impacts of increased human activity; and recognize the limits of current protected species legislation. PMID:25783745</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/17018089','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/17018089"><span><span class="hlt">Extent</span>, <span class="hlt">trends</span>, and perpetrators of prostitution-related homicide in the United States.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Brewer, Devon D; Dudek, Jonathan A; Potterat, John J; Muth, Stephen Q; Roberts, John M; Woodhouse, Donald E</p> <p>2006-09-01</p> <p>Prostitute women have the highest homicide victimization rate of any set of women ever studied. We analyzed nine diverse homicide data sets to examine the <span class="hlt">extent</span>, <span class="hlt">trends</span>, and perpetrators of prostitution-related homicide in the United States. Most data sources substantially under-ascertained prostitute homicides. As estimated from a conservative capture-recapture analysis, 2.7% of female homicide victims in the United States between 1982 and 2000 were prostitutes. Frequencies of recorded prostitute and client homicides increased substantially in the late 1980s and early 1990s; nearly all of the few observed pimp homicides occurred before the late 1980s. These <span class="hlt">trends</span> may be linked to the rise of crack cocaine use. Prostitutes were killed primarily by clients, clients were killed mainly by prostitutes, and pimps were killed predominantly by pimps. Another conservative estimate suggests that serial killers accounted for 35% of prostitute homicides. Proactive surveillance of, and evidence collection from, clients and prostitutes might enhance the investigation of prostitution-related homicide.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.P31A2081H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.P31A2081H"><span>Monitoring Subsurface <span class="hlt">Ice</span>-Ocean Processes Using Underwater Acoustics in the Ross Sea</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Haxel, J. H.; Dziak, R. P.; Matsumoto, H.; Lee, W. S.; Yun, S.</p> <p>2016-12-01</p> <p>The Ross Sea is a dynamic area of <span class="hlt">ice</span>-ocean interaction, where a large component of the Southern Ocean's sea <span class="hlt">ice</span> formation occurs within regional polynyas in addition to the destructive processes happening at the seaward boundary of the Ross <span class="hlt">Ice</span> Shelf. Recent studies show the sea-<span class="hlt">ice</span> season has been lengthening and the sea <span class="hlt">ice</span> <span class="hlt">extent</span> has been growing with more persistent and larger regional polynyas. These <span class="hlt">trends</span> have important implications for the Ross Sea ecosystem with polynyas supporting high rates of primary productivity in the area. Monitoring <span class="hlt">trends</span> in sea <span class="hlt">ice</span> and <span class="hlt">ice</span> shelf dynamics in the Southern Ocean has relied heavily on satellite imagery and remote sensing methods despite a significant portion of these physical processes occurring beneath the ocean surface. In January 2014, an ocean bottom hydrophone (OBH) was moored on the seafloor in the polynya area of Terra Nova Bay in the northwest region of the Ross Sea, north of the Drygalski <span class="hlt">Ice</span> Tongue. The OBH recorded a year long record of the underwater low frequency acoustic spectrum up to 500 Hz from January 29 until it was recovered the following December 17, 2014. The acoustic records reveal a complex annual history of <span class="hlt">ice</span> generated signals with over 50,000 detected events. These <span class="hlt">ice</span> generated events related to collisions and cracking provide important insight for the timing and intensity of the <span class="hlt">ice</span>-ocean dynamics happening below the sea surface as the polynya grows and expands and the nearby Drygalski <span class="hlt">ice</span> tongue flows into Terra Nova Bay. Additionally, high concentrations of baleen whale vocalizations in frequencies ranging from 200-400 Hz from September - December suggest a strong seasonal presence of whales in this ecologically important polynya region.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19910063773&hterms=1087&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3D%2526%25231087','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19910063773&hterms=1087&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3D%2526%25231087"><span>Antarctic Sea <span class="hlt">ice</span> variations and seasonal air temperature relationships</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Weatherly, John W.; Walsh, John E.; Zwally, H. J.</p> <p>1991-01-01</p> <p>Data through 1987 are used to determine the regional and seasonal dependencies of recent <span class="hlt">trends</span> of Antarctic temperature and sea <span class="hlt">ice</span>. Lead-lag relationships involving regional sea <span class="hlt">ice</span> and air temperature are systematically evaluated, with an eye toward the <span class="hlt">ice</span>-temperature feedbacks that may influence climatic change. Over the 1958-1087 period the temperature <span class="hlt">trends</span> are positive in all seasons. For the 15 years (l973-l987) for which <span class="hlt">ice</span> data are available, the <span class="hlt">trends</span> are predominantly positive only in winter and summer, and are most strongly positive over the Antarctic Peninsula. The spatially aggregated <span class="hlt">trend</span> of temperature for this latter period is small but positive, while the corresponding <span class="hlt">trend</span> of <span class="hlt">ice</span> coverage is small but negative. Lag correlations between seasonal anomalies of the two variables are generally stronger with <span class="hlt">ice</span> lagging the summer temperatures and with <span class="hlt">ice</span> leading the winter temperatures. The implication is that summer temperatures predispose the near-surface waters to above-or below-normal <span class="hlt">ice</span> coverage in the following fall and winter.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSMG44B2001H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSMG44B2001H"><span>Reliable radiocarbon evidence for the maximum <span class="hlt">extent</span> of the West Antarctic <span class="hlt">Ice</span> Sheet in the easternmost Amundsen Sea Embayment during the Last Glacial Maximum</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hillenbrand, C. D.; Klages, J. P.; Kuhn, G.; Smith, J.; Graham, A. G. C.; Gohl, K.; Wacker, L.</p> <p>2016-02-01</p> <p>We present the first age control and sedimentological data for the upper part of a stratified seismic unit that is unusually thick ( 6-9 m) for the outer shelf of the ASE and overlies an acoustically transparent unit. The transparent unit probably consists of soft till deposited during the last advance of grounded <span class="hlt">ice</span> onto the outer shelf. We mapped subtle mega-scale glacial lineations (MSGL) on the seafloor and suggest that these are probably the expressions of bedforms originally moulded into the surface of the underlying till layer. We note that the lineations are less distinct when compared to MSGLs recorded in bathymetric data collected further upstream and suggest that this is because of the blanketing influence of the thick overlying drape. The uppermost part (≤ 3 m) of the stratified drape was sampled by two of our sediment cores and contains sufficient amounts of calcareous foraminifera throughout to establish reliable age models by radiocarbon dating. In combination with facies analysis of the recovered sediments the obtained radiocarbon dates suggest deposition of the draping unit in a sub-<span class="hlt">ice</span> shelf/sub-sea <span class="hlt">ice</span> to seasonal-open marine environment that existed on the outer shelf from well before (>45 ka BP) the Last Glacial Maximum until today. This indicates the maximum <span class="hlt">extent</span> of grounded <span class="hlt">ice</span> at the LGM must have been situated south of the two core locations, where a well-defined grounding-zone wedge (`GZWa') was deposited. The third sediment core was recovered from the toe of this wedge and retrieved grounding-line proximal glaciogenic debris flow sediments that were deposited by 14 cal. ka BP. Our new data therefore provide direct evidence for 1) the maximum <span class="hlt">extent</span> of grounded <span class="hlt">ice</span> in the easternmost ASE at the LGM (=GZWa), 2) the existence of a large shelf area seawards the wedge that was not covered by grounded <span class="hlt">ice</span> during that time, and 3) landward grounding line retreat from GZWa prior to 14 cal. ka BP. This knowledge will help to improve LGM <span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70042056','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70042056"><span>Establishing water body areal <span class="hlt">extent</span> <span class="hlt">trends</span> in interior Alaska from multi-temporal Landsat data</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Rover, Jennifer R.; Ji, Lei; Wylie, Bruce K.; Tieszen, Larry L.</p> <p>2012-01-01</p> <p>An accurate approach is needed for monitoring, quantifying and understanding surface water variability due to climate change. Separating inter- and intra-annual variances from longer-term shifts in surface water <span class="hlt">extents</span> due to contemporary climate warming requires repeat measurements spanning a several-decade period. Here, we show that <span class="hlt">trends</span> developed from multi-date measurements of the <span class="hlt">extents</span> of more than 15,000 water bodies in central Alaska using Landsat Multispectral Scanner (MSS), Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) data (1979–2009) were highly influenced by the quantity and timing of the data. Over the 30-year period from 1979 to 2009, the study area had a net decrease (p < 0.05) in the <span class="hlt">extents</span> of 3.4% of water bodies whereas 86% of water bodies exhibited no significant change. The Landsat-derived dataset provides an opportunity for additional research assessing the drivers of lake and wetland change in this region.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMNG31A1833A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMNG31A1833A"><span>The statistical properties of sea <span class="hlt">ice</span> velocity fields</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Agarwal, S.; Wettlaufer, J. S.</p> <p>2016-12-01</p> <p>Thorndike and Colony (1982) showed that more than 70% of the variance of the <span class="hlt">ice</span> motion can be explained by the geostrophic winds. This conclusion was reached by analyzing only 2 years of data. Due to the importance of <span class="hlt">ice</span> motion in Arctic climate we ask how persistent is such a prediction. In so doing, we study and develop a stochastic model for the Arctic sea <span class="hlt">ice</span> velocity fields based on the observed sea <span class="hlt">ice</span> velocity fields from satellites and buoys for the period 1978 - 2012. Having previously found that the Arctic Sea Equivalent <span class="hlt">Ice</span> <span class="hlt">Extent</span> (EIE) has a white noise structure on annual to bi-annual time scales (Agarwal et. al. 2012), we assess the connection to <span class="hlt">ice</span> motion. We divide the Arctic into dynamic and thermodynamic components, with focus on the dynamic part i.e. the velocity fields of sea <span class="hlt">ice</span> driven by the geostrophic winds over the Arctic. We show (1) the stationarity of the spatial correlation structure of the velocity fields, and (2) the robustness of white noise structure present in the velocity fields on annual to bi-annual time scales, which combine to explain the white noise characteristics of the EIE on these time scales. S. Agarwal, W. Moon and J.S. Wettlaufer, <span class="hlt">Trends</span>, noise and reentrant long-term persistence in Arctic sea <span class="hlt">ice</span>, Proc. R. Soc. A, 468, 2416 (2012). A.S. Thorndike and R. Colony, Sea <span class="hlt">ice</span> motion in response to geostrophic winds, J. Geophys. Res. 87, 5845 (1982).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19870061487&hterms=correlation+coefficient&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dcorrelation%2Bcoefficient','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19870061487&hterms=correlation+coefficient&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dcorrelation%2Bcoefficient"><span>Evaluation of <span class="hlt">icing</span> drag coefficient correlations applied to <span class="hlt">iced</span> propeller performance prediction</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Miller, Thomas L.; Shaw, R. J.; Korkan, K. D.</p> <p>1987-01-01</p> <p>Evaluation of three empirical <span class="hlt">icing</span> drag coefficient correlations is accomplished through application to a set of propeller <span class="hlt">icing</span> data. The various correlations represent the best means currently available for relating drag rise to various flight and atmospheric conditions for both fixed-wing and rotating airfoils, and the work presented here ilustrates and evaluates one such application of the latter case. The origins of each of the correlations are discussed, and their apparent capabilities and limitations are summarized. These correlations have been made to be an integral part of a computer code, ICEPERF, which has been designed to calculate <span class="hlt">iced</span> propeller performance. Comparison with experimental propeller <span class="hlt">icing</span> data shows generally good agreement, with the quality of the predicted results seen to be directly related to the radial <span class="hlt">icing</span> <span class="hlt">extent</span> of each case. The code's capability to properly predict thrust coefficient, power coefficient, and propeller efficiency is shown to be strongly dependent on the choice of correlation selected, as well as upon proper specificatioon of radial <span class="hlt">icing</span> <span class="hlt">extent</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150002337','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150002337"><span>Possible Mechanisms for Turbofan Engine <span class="hlt">Ice</span> Crystal <span class="hlt">Icing</span> at High Altitude</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tsao, Jen-Ching; Struk, Peter M.; Oliver, Michael</p> <p>2014-01-01</p> <p>A thermodynamic model is presented to describe possible mechanisms of <span class="hlt">ice</span> formation on unheated surfaces inside a turbofan engine compression system from fully glaciated <span class="hlt">ice</span> crystal clouds often formed at high altitude near deep convective weather systems. It is shown from the analysis that generally there could be two distinct types of <span class="hlt">ice</span> formation: (1) when the "surface freezing fraction" is in the range of 0 to 1, dominated by the freezing of water melt from fully or partially melted <span class="hlt">ice</span> crystals, the <span class="hlt">ice</span> structure is formed from accretion with strong adhesion to the surface, and (2) when the "surface melting fraction" is the range of 0 to 1, dominated by the further melting of <span class="hlt">ice</span> crystals, the <span class="hlt">ice</span> structure is formed from accumulation of un-melted <span class="hlt">ice</span> crystals with relatively weak bonding to the surface. The model captures important qualitative <span class="hlt">trends</span> of the fundamental <span class="hlt">ice</span>-crystal <span class="hlt">icing</span> phenomenon reported earlier1,2 from the research collaboration work by NASA and the National Research Council (NRC) of Canada. Further, preliminary analysis of test data from the 2013 full scale turbofan engine <span class="hlt">ice</span> crystal <span class="hlt">icing</span> test3 conducted in the NASA Glenn Propulsion Systems Laboratory (PSL) has also suggested that (1) both types of <span class="hlt">ice</span> formation occurred during the test, and (2) the model has captured some important qualitative <span class="hlt">trend</span> of turning on (or off) the <span class="hlt">ice</span> crystal <span class="hlt">ice</span> formation process in the tested engine low pressure compressor (LPC) targeted area under different <span class="hlt">icing</span> conditions that ultimately would lead to (or suppress) an engine core roll back (RB) event.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160011109','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160011109"><span>Possible Mechanisms for Turbofan Engine <span class="hlt">Ice</span> Crystal <span class="hlt">Icing</span> at High Altitude</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tsao, Jen-Ching; Struk, Peter M.; Oliver, Michael J.</p> <p>2016-01-01</p> <p>A thermodynamic model is presented to describe possible mechanisms of <span class="hlt">ice</span> formation on unheated surfaces inside a turbofan engine compression system from fully glaciated <span class="hlt">ice</span> crystal clouds often formed at high altitude near deep convective weather systems. It is shown from the analysis that generally there could be two distinct types of <span class="hlt">ice</span> formation: (1) when the "surface freezing fraction" is in the range of 0 to 1, dominated by the freezing of water melt from fully or partially melted <span class="hlt">ice</span> crystals, the <span class="hlt">ice</span> structure is formed from accretion with strong adhesion to the surface, and (2) when the "surface melting fraction" is the range of 0 to 1, dominated by the further melting of <span class="hlt">ice</span> crystals, the <span class="hlt">ice</span> structure is formed from accumulation of un-melted <span class="hlt">ice</span> crystals with relatively weak bonding to the surface. The model captures important qualitative <span class="hlt">trends</span> of the fundamental <span class="hlt">ice</span>-crystal <span class="hlt">icing</span> phenomenon reported earlier (Refs. 1 and 2) from the research collaboration work by NASA and the National Research Council (NRC) of Canada. Further, preliminary analysis of test data from the 2013 full scale turbofan engine <span class="hlt">ice</span> crystal <span class="hlt">icing</span> test (Ref. 3) conducted in the NASA Glenn Propulsion Systems Laboratory (PSL) has also suggested that (1) both types of <span class="hlt">ice</span> formation occurred during the test, and (2) the model has captured some important qualitative <span class="hlt">trend</span> of turning on (or off) the <span class="hlt">ice</span> crystal <span class="hlt">ice</span> formation process in the tested engine low pressure compressor (LPC) targeted area under different <span class="hlt">icing</span> conditions that ultimately would lead to (or suppress) an engine core roll back (RB) event.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21G1188D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21G1188D"><span>Estimation of Melt Ponds over Arctic Sea <span class="hlt">Ice</span> using MODIS Surface Reflectance Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ding, Y.; Cheng, X.; Liu, J.</p> <p>2017-12-01</p> <p>Melt ponds over Arctic sea <span class="hlt">ice</span> is one of the main factors affecting variability of surface albedo, increasing absorption of solar radiation and further melting of snow and <span class="hlt">ice</span>. In recent years, a large number of melt ponds have been observed during the melt season in Arctic. Moreover, some studies have suggested that late spring to mid summer melt ponds information promises to improve the prediction skill of seasonal Arctic sea <span class="hlt">ice</span> minimum. In the study, we extract the melt pond fraction over Arctic sea <span class="hlt">ice</span> since 2000 using three bands MODIS weekly surface reflectance data by considering the difference of spectral reflectance in ponds, <span class="hlt">ice</span> and open water. The preliminary comparison shows our derived Arctic-wide melt ponds are in good agreement with that derived by the University of Hamburg, especially at the pond distribution. We analyze seasonal evolution, interannual variability and <span class="hlt">trend</span> of the melt ponds, as well as the changes of onset and re-freezing. The melt pond fraction shows an asymmetrical growth and decay pattern. The observed melt ponds fraction is almost within 25% in early May and increases rapidly in June and July with a high fraction of more than 40% in the east of Greenland and Beaufort Sea. A significant increasing <span class="hlt">trend</span> in the melt pond fraction is observed for the period of 2000-2017. The relationship between melt pond fraction and sea <span class="hlt">ice</span> <span class="hlt">extent</span> will be also discussed. Key Words: melt ponds, sea <span class="hlt">ice</span>, Arctic</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017CliPa..13...39M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017CliPa..13...39M"><span>Sea <span class="hlt">ice</span> and pollution-modulated changes in Greenland <span class="hlt">ice</span> core methanesulfonate and bromine</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Maselli, Olivia J.; Chellman, Nathan J.; Grieman, Mackenzie; Layman, Lawrence; McConnell, Joseph R.; Pasteris, Daniel; Rhodes, Rachael H.; Saltzman, Eric; Sigl, Michael</p> <p>2017-01-01</p> <p>Reconstruction of past changes in Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> may be critical for understanding its future evolution. Methanesulfonate (MSA) and bromine concentrations preserved in <span class="hlt">ice</span> cores have both been proposed as indicators of past sea <span class="hlt">ice</span> conditions. In this study, two <span class="hlt">ice</span> cores from central and north-eastern Greenland were analysed at sub-annual resolution for MSA (CH3SO3H) and bromine, covering the time period 1750-2010. We examine correlations between <span class="hlt">ice</span> core MSA and the HadISST1 <span class="hlt">ICE</span> sea <span class="hlt">ice</span> dataset and consult back trajectories to infer the likely source regions. A strong correlation between the low-frequency MSA and bromine records during pre-industrial times indicates that both chemical species are likely linked to processes occurring on or near sea <span class="hlt">ice</span> in the same source regions. The positive correlation between <span class="hlt">ice</span> core MSA and bromine persists until the mid-20th century, when the acidity of Greenland <span class="hlt">ice</span> begins to increase markedly due to increased fossil fuel emissions. After that time, MSA levels decrease as a result of declining sea <span class="hlt">ice</span> <span class="hlt">extent</span> but bromine levels increase. We consider several possible explanations and ultimately suggest that increased acidity, specifically nitric acid, of snow on sea <span class="hlt">ice</span> stimulates the release of reactive Br from sea <span class="hlt">ice</span>, resulting in increased transport and deposition on the Greenland <span class="hlt">ice</span> sheet.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016TCry...10.2027S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016TCry...10.2027S"><span>Sea-<span class="hlt">ice</span> indicators of polar bear habitat</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stern, Harry L.; Laidre, Kristin L.</p> <p>2016-09-01</p> <p>Nineteen subpopulations of polar bears (Ursus maritimus) are found throughout the circumpolar Arctic, and in all regions they depend on sea <span class="hlt">ice</span> as a platform for traveling, hunting, and breeding. Therefore polar bear phenology - the cycle of biological events - is linked to the timing of sea-<span class="hlt">ice</span> retreat in spring and advance in fall. We analyzed the dates of sea-<span class="hlt">ice</span> retreat and advance in all 19 polar bear subpopulation regions from 1979 to 2014, using daily sea-<span class="hlt">ice</span> concentration data from satellite passive microwave instruments. We define the dates of sea-<span class="hlt">ice</span> retreat and advance in a region as the dates when the area of sea <span class="hlt">ice</span> drops below a certain threshold (retreat) on its way to the summer minimum or rises above the threshold (advance) on its way to the winter maximum. The threshold is chosen to be halfway between the historical (1979-2014) mean September and mean March sea-<span class="hlt">ice</span> areas. In all 19 regions there is a <span class="hlt">trend</span> toward earlier sea-<span class="hlt">ice</span> retreat and later sea-<span class="hlt">ice</span> advance. <span class="hlt">Trends</span> generally range from -3 to -9 days decade-1 in spring and from +3 to +9 days decade-1 in fall, with larger <span class="hlt">trends</span> in the Barents Sea and central Arctic Basin. The <span class="hlt">trends</span> are not sensitive to the threshold. We also calculated the number of days per year that the sea-<span class="hlt">ice</span> area exceeded the threshold (termed <span class="hlt">ice</span>-covered days) and the average sea-<span class="hlt">ice</span> concentration from 1 June through 31 October. The number of <span class="hlt">ice</span>-covered days is declining in all regions at the rate of -7 to -19 days decade-1, with larger <span class="hlt">trends</span> in the Barents Sea and central Arctic Basin. The June-October sea-<span class="hlt">ice</span> concentration is declining in all regions at rates ranging from -1 to -9 percent decade-1. These sea-<span class="hlt">ice</span> metrics (or indicators of habitat change) were designed to be useful for management agencies and for comparative purposes among subpopulations. We recommend that the National Climate Assessment include the timing of sea-<span class="hlt">ice</span> retreat and advance in future reports.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140008666','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140008666"><span>A New Normal for the Sea <span class="hlt">Ice</span> Index</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Fetterer, Florence; Windnagel, Ann; Meier, Walter N.</p> <p>2014-01-01</p> <p>The NSIDC Sea <span class="hlt">Ice</span> Index is a popular data product that shows users how <span class="hlt">ice</span> <span class="hlt">extent</span> and concentration have changed since the beginning of the passive microwave satellite record in 1978. It shows time series of monthly <span class="hlt">ice</span> <span class="hlt">extent</span> anomalies rather than actual <span class="hlt">extent</span> values, in order to emphasize the information the data are carrying. Along with the time series, an image of average <span class="hlt">extent</span> for the previous month is shown as a white field, with a pink line showing the median <span class="hlt">extent</span> for that month. These are updated monthly; corresponding daily products are updated daily.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21E1171K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21E1171K"><span>New details about the LGM <span class="hlt">extent</span> and subsequent retreat of the West Antarctic <span class="hlt">Ice</span> Sheet from the easternmost Amundsen Sea Embayment shelf</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Klages, J. P.; Hillenbrand, C. D.; Kuhn, G.; Smith, J. A.; Graham, A. G. C.; Nitsche, F. O.; Frederichs, T.; Arndt, J. E.; Gebhardt, C.; Robin, Z.; Uenzelmann-Neben, G.; Gohl, K.; Jernas, P.; Wacker, L.</p> <p>2017-12-01</p> <p>In recent years several previously undiscovered grounding-zone wedges (GZWs) have been described within the Abbot-Cosgrove palaeo-<span class="hlt">ice</span> stream trough on the easternmost Amundsen Sea Embayment shelf. These GZWs document both the Last Glacial Maximum (LGM; 26.5-19 cal. ka BP) grounding-line <span class="hlt">extent</span> and the subsequent episodic retreat within this trough that neighbors the larger Pine Island-Thwaites trough to the west. Here we combine bathymetric, seismic, and geologic data showing that 1) the grounding line in Abbot Trough did not reach the continental shelf break at any time during the last glacial period, and 2) a prominent stacked GZW constructed from six individual wedges lying upon another was deposited 100 km upstream from the LGM grounding-line position. The available data allow for calculating volumes for most of these individual GZWs and for the entire stack. Sediment cores were recovered seawards from the outermost GZW in the trough, and from the individual wedges of the stacked GZW in order to define the LGM grounding-line <span class="hlt">extent</span>, and provide minimum grounding-line retreat ages for the respective positions on the stacked GZW. We present implications of a grounded-<span class="hlt">ice</span> free outer shelf throughout the last glacial period. Furthermore, we assess the significance of the grounding-line stillstand period recorded by the stacked GZW in Abbot Trough for the timing of post-LGM retreat of the West Antarctic <span class="hlt">Ice</span> Sheet from the Amundsen Sea Embayment shelf.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017NatCo...814991L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017NatCo...814991L"><span>On the discrepancy between observed and CMIP5 multi-model simulated Barents Sea winter sea <span class="hlt">ice</span> decline</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Dawei; Zhang, Rong; Knutson, Thomas R.</p> <p>2017-04-01</p> <p>This study aims to understand the relative roles of external forcing versus internal climate variability in causing the observed Barents Sea winter sea <span class="hlt">ice</span> <span class="hlt">extent</span> (SIE) decline since 1979. We identify major discrepancies in the spatial patterns of winter Northern Hemisphere sea <span class="hlt">ice</span> concentration <span class="hlt">trends</span> over the satellite period between observations and CMIP5 multi-model mean externally forced response. The CMIP5 externally forced decline in Barents Sea winter SIE is much weaker than that observed. Across CMIP5 ensemble members, March Barents Sea SIE <span class="hlt">trends</span> have little correlation with global mean surface air temperature <span class="hlt">trends</span>, but are strongly anti-correlated with <span class="hlt">trends</span> in Atlantic heat transport across the Barents Sea Opening (BSO). Further comparison with control simulations from coupled climate models suggests that enhanced Atlantic heat transport across the BSO associated with regional internal variability may have played a leading role in the observed decline in winter Barents Sea SIE since 1979.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSHE44C1528D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSHE44C1528D"><span>The Effect of Recent Decreases in Sea <span class="hlt">Ice</span> <span class="hlt">Extent</span> and Increases in SST on the Seasonal Availability of Arctic Cod (Boreogadus saida) to Seabirds in the Beaufort Sea</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Divoky, G.; Druckenmiller, M. L.</p> <p>2016-02-01</p> <p>With major decreases in pan-Arctic summer sea <span class="hlt">ice</span> <span class="hlt">extent</span> steadily underway, the Beaufort Sea has been nearly <span class="hlt">ice</span>-free in five of the last eight summers. This loss of a critical arctic marine habitat and the concurrent warming of the recently <span class="hlt">ice</span>-free waters could potentially cause major changes in the biological oceanography of the Beaufort Sea and alter the distribution, abundance and condition of the region's upper trophic level predators that formerly relied on prey associated with sea <span class="hlt">ice</span> or cold (<2°C) surface waters. Arctic cod (Boreogadus saida), the primary forage fish for seabirds in the Beaufort Sea, is part of the cryopelagic fauna associated with sea <span class="hlt">ice</span> and is also found in adjacent <span class="hlt">ice</span>-free waters. In the extreme western Beaufort Sea near Cooper Island, Arctic cod availability to breeding Black Guillemots (Cepphus grylle), a diving seabird, has declined since 2002. Guillemots are a good indicator of Arctic cod availability in surface waters and the upper water column as they feed at depths of 1-20m. Currently, when sea <span class="hlt">ice</span> is absent from the nearshore and SST exceeds 4°C, guillemots are observed to seasonally shift from Arctic cod to nearshore demersal prey, with a resulting decrease in nestling survival and quality. Arctic cod is the primary prey for many of the seabirds utilizing the Beaufort Sea as a post-breeding staging area and migratory corridor in late summer and early fall. The loss of approximately 200-300 thousand sq km of summer sea <span class="hlt">ice</span> habitat in recent years could be expected to affect the distribution, abundance, and movements of these species as there are few alternative fish resources in the region. We examine temporal and spatial variation in August sea <span class="hlt">ice</span> <span class="hlt">extent</span> and SST in the Beaufort Sea to determine the regions, periods and bird species that are potentially most affected as the Beaufort Sea transitions to becoming regularly <span class="hlt">ice</span>-free in late summer.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A31D0050O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A31D0050O"><span>The role of summer surface wind anomalies in the summer Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> in 2010 and 2011</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ogi, M.; Wallace, J. M.</p> <p>2012-12-01</p> <p>Masayo Ogi 1 and John M. Wallace 2 masayo.ogi@jamstec.go.jp wallace@atmos.washington.edu 1Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan 2 Department of Atmospheric Sciences, University of Washington, Seattle, Washington The seasonal evolutions of Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> (SIE) during the summers of 2010 and 2011 are contrasted with that in 2007. The June SIE in 2010 was lower than that in 2007 and was the lowest for that calendar month in the 32-year (1979-2010) record. The September SIE in 2010 would have set a new record low had it not been for the fact that the <span class="hlt">ice</span> retreated more slowly during the summer months in that year than it did in 2007. Hence from early July onward, the SIE in 2010 remained at levels above those observed in 2007. The SIE minimum in September 2010 proved to be the third lowest on record, eclipsed by values in both 2007 and 2008. In spring and summer of 2011, the Arctic SIE was as low as it was in 2007, but the SIE in September 2011 did not reach record low levels. The SIE minimum in 2011 proved to be the second lowest on record for the period of 1979-2011. Summertime atmospheric conditions play an important role in controlling the variations in Arctic SIE. In a previous study based on statistical analysis of data collected prior to 2007, we showed that anticyclonic summertime circulation anomalies over the Arctic Ocean during the summer months favor low September SIE. We also found that the record-low <span class="hlt">ice</span> summer year 2007 was characterized by a strong anticyclonic circulation anomaly, accompanied by an Ekman drift of <span class="hlt">ice</span> out of the marginal seas toward the central Arctic and eventually toward the Fram Strait, as evidenced by the tracks of drifting buoys. Here we assess the <span class="hlt">extent</span> to which year-to-year differences in summer winds over the Arctic might have contributed to the differing rates of retreat of <span class="hlt">ice</span> during the summers of 2007, 2010, and 2011. Our results show that the May-June (MJ) pattern in 2010 is</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_11 --> <div id="page_12" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="221"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27650478','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27650478"><span>Canadian Arctic sea <span class="hlt">ice</span> reconstructed from bromine in the Greenland NEEM <span class="hlt">ice</span> core.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Spolaor, Andrea; Vallelonga, Paul; Turetta, Clara; Maffezzoli, Niccolò; Cozzi, Giulio; Gabrieli, Jacopo; Barbante, Carlo; Goto-Azuma, Kumiko; Saiz-Lopez, Alfonso; Cuevas, Carlos A; Dahl-Jensen, Dorthe</p> <p>2016-09-21</p> <p>Reconstructing the past variability of Arctic sea <span class="hlt">ice</span> provides an essential context for recent multi-year sea <span class="hlt">ice</span> decline, although few quantitative reconstructions cover the Holocene period prior to the earliest historical records 1,200 years ago. Photochemical recycling of bromine is observed over first-year, or seasonal, sea <span class="hlt">ice</span> in so-called "bromine explosions" and we employ a 1-D chemistry transport model to quantify processes of bromine enrichment over first-year sea <span class="hlt">ice</span> and depositional transport over multi-year sea <span class="hlt">ice</span> and land <span class="hlt">ice</span>. We report bromine enrichment in the Northwest Greenland Eemian NEEM <span class="hlt">ice</span> core since the end of the Eemian interglacial 120,000 years ago, finding the maximum extension of first-year sea <span class="hlt">ice</span> occurred approximately 9,000 years ago during the Holocene climate optimum, when Greenland temperatures were 2 to 3 °C above present values. First-year sea <span class="hlt">ice</span> <span class="hlt">extent</span> was lowest during the glacial stadials suggesting complete coverage of the Arctic Ocean by multi-year sea <span class="hlt">ice</span>. These findings demonstrate a clear relationship between temperature and first-year sea <span class="hlt">ice</span> <span class="hlt">extent</span> in the Arctic and suggest multi-year sea <span class="hlt">ice</span> will continue to decline as polar amplification drives Arctic temperatures beyond the 2 °C global average warming target of the recent COP21 Paris climate agreement.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/AD1026542','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD1026542"><span>Ocean Profile Measurements During the Seasonal <span class="hlt">Ice</span> Zone Reconnaissance Surveys Ocean Profiles</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2017-01-01</p> <p>repeated ocean, <span class="hlt">ice</span>, and atmospheric measurements across the Beaufort-Chukchi sea seasonal sea <span class="hlt">ice</span> zone (SIZ) utilizing US Coast Guard Arctic Domain...contributing to the rapid decline in summer <span class="hlt">ice</span> <span class="hlt">extent</span> that has occurred in recent years. The SIZ is the region between maximum winter sea <span class="hlt">ice</span> <span class="hlt">extent</span> and...minimum summer sea <span class="hlt">ice</span> <span class="hlt">extent</span>. As such, it contains the full range of positions of the marginal <span class="hlt">ice</span> zone (MIZ) where sea <span class="hlt">ice</span> interacts with open water</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003EAEJA....13008H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003EAEJA....13008H"><span>Glaciological constraints on current <span class="hlt">ice</span> mass changes from modelling the <span class="hlt">ice</span> sheets over the glacial cycles</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Huybrechts, P.</p> <p>2003-04-01</p> <p>The evolution of continental <span class="hlt">ice</span> sheets introduces a long time scale in the climate system. Large <span class="hlt">ice</span> sheets have a memory of millenia, hence the present-day <span class="hlt">ice</span> sheets of Greenland and Antarctica are still adjusting to climatic variations extending back to the last glacial period. This <span class="hlt">trend</span> is separate from the direct response to mass-balance changes on decadal time scales and needs to be correctly accounted for when assessing current and future contributions to sea level. One way to obtain estimates of current <span class="hlt">ice</span> mass changes is to model the past history of the <span class="hlt">ice</span> sheets and their underlying beds over the glacial cycles. Such calculations assist to distinguish between the longer-term <span class="hlt">ice</span>-dynamic evolution and short-term mass-balance changes when interpreting altimetry data, and are helpful to isolate the effects of postglacial rebound from gravity and altimetry <span class="hlt">trends</span>. The presentation will discuss results obtained from 3-D thermomechanical <span class="hlt">ice</span>-sheet/lithosphere/bedrock models applied to the Antarctic and Greenland <span class="hlt">ice</span> sheets. The simulations are forced by time-dependent boundary conditions derived from sediment and <span class="hlt">ice</span> core records and are constrained by geomorphological and glacial-geological data of past <span class="hlt">ice</span> sheet and sea-level stands. Current simulations suggest that the Greenland <span class="hlt">ice</span> sheet is close to balance, while the Antarctic <span class="hlt">ice</span> sheet is still losing mass, mainly due to incomplete grounding-line retreat of the West Antarctic <span class="hlt">ice</span> sheet since the LGM. The results indicate that altimetry <span class="hlt">trends</span> are likely dominated by <span class="hlt">ice</span> thickness changes but that the gravitational signal mainly reflects postglacial rebound.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25783745','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25783745"><span>Arctic marine mammal population status, sea <span class="hlt">ice</span> habitat loss, and conservation recommendations for the 21st century.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Laidre, Kristin L; Stern, Harry; Kovacs, Kit M; Lowry, Lloyd; Moore, Sue E; Regehr, Eric V; Ferguson, Steven H; Wiig, Øystein; Boveng, Peter; Angliss, Robyn P; Born, Erik W; Litovka, Dennis; Quakenbush, Lori; Lydersen, Christian; Vongraven, Dag; Ugarte, Fernando</p> <p>2015-06-01</p> <p>Arctic marine mammals (AMMs) are icons of climate change, largely because of their close association with sea <span class="hlt">ice</span>. However, neither a circumpolar assessment of AMM status nor a standardized metric of sea <span class="hlt">ice</span> habitat change is available. We summarized available data on abundance and <span class="hlt">trend</span> for each AMM species and recognized subpopulation. We also examined species diversity, the <span class="hlt">extent</span> of human use, and temporal <span class="hlt">trends</span> in sea <span class="hlt">ice</span> habitat for 12 regions of the Arctic by calculating the dates of spring sea <span class="hlt">ice</span> retreat and fall sea <span class="hlt">ice</span> advance from satellite data (1979-2013). Estimates of AMM abundance varied greatly in quality, and few studies were long enough for <span class="hlt">trend</span> analysis. Of the AMM subpopulations, 78% (61 of 78) are legally harvested for subsistence purposes. Changes in sea <span class="hlt">ice</span> phenology have been profound. In all regions except the Bering Sea, the duration of the summer (i.e., reduced <span class="hlt">ice</span>) period increased by 5-10 weeks and by >20 weeks in the Barents Sea between 1979 and 2013. In light of generally poor data, the importance of human use, and forecasted environmental changes in the 21st century, we recommend the following for effective AMM conservation: maintain and improve comanagement by local, federal, and international partners; recognize spatial and temporal variability in AMM subpopulation response to climate change; implement monitoring programs with clear goals; mitigate cumulative impacts of increased human activity; and recognize the limits of current protected species legislation. © 2015 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/AD1035130','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD1035130"><span>Air-Sea Interactions in the Marginal <span class="hlt">Ice</span> Zone</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2016-03-31</p> <p>Arctic Ocean has increased with the significant retreat of the seasonal sea-<span class="hlt">ice</span> <span class="hlt">extent</span>. Here, we use wind, wave, turbulence, and <span class="hlt">ice</span> measurements to...which has experienced a significant retreat of the seasonal <span class="hlt">ice</span> <span class="hlt">extent</span> (Comiso and Nishio, 2008; Comiso et al., 2008). Thomson and Rogers (2014) showed</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013QSRv...79..168A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013QSRv...79..168A"><span>A review of sea <span class="hlt">ice</span> proxy information from polar <span class="hlt">ice</span> cores</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Abram, Nerilie J.; Wolff, Eric W.; Curran, Mark A. J.</p> <p>2013-11-01</p> <p>Sea <span class="hlt">ice</span> plays an important role in Earth's climate system. The lack of direct indications of past sea <span class="hlt">ice</span> coverage, however, means that there is limited knowledge of the sensitivity and rate at which sea <span class="hlt">ice</span> dynamics are involved in amplifying climate changes. As such, there is a need to develop new proxy records for reconstructing past sea <span class="hlt">ice</span> conditions. Here we review the advances that have been made in using chemical tracers preserved in <span class="hlt">ice</span> cores to determine past changes in sea <span class="hlt">ice</span> cover around Antarctica. <span class="hlt">Ice</span> core records of sea salt concentration show promise for revealing patterns of sea <span class="hlt">ice</span> <span class="hlt">extent</span> particularly over glacial-interglacial time scales. In the coldest climates, however, the sea salt signal appears to lose sensitivity and further work is required to determine how this proxy can be developed into a quantitative sea <span class="hlt">ice</span> indicator. Methane sulphonic acid (MSA) in near-coastal <span class="hlt">ice</span> cores has been used to reconstruct quantified changes and interannual variability in sea <span class="hlt">ice</span> <span class="hlt">extent</span> over shorter time scales spanning the last ˜160 years, and has potential to be extended to produce records of Antarctic sea <span class="hlt">ice</span> changes throughout the Holocene. However the MSA <span class="hlt">ice</span> core proxy also requires careful site assessment and interpretation alongside other palaeoclimate indicators to ensure reconstructions are not biased by non-sea <span class="hlt">ice</span> factors, and we summarise some recommended strategies for the further development of sea <span class="hlt">ice</span> histories from <span class="hlt">ice</span> core MSA. For both proxies the limited information about the production and transfer of chemical markers from the sea <span class="hlt">ice</span> zone to the Antarctic <span class="hlt">ice</span> sheets remains an issue that requires further multidisciplinary study. Despite some exploratory and statistical work, the application of either proxy as an indicator of sea <span class="hlt">ice</span> change in the Arctic also remains largely unknown. As information about these new <span class="hlt">ice</span> core proxies builds, so too does the potential to develop a more comprehensive understanding of past changes in sea</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22538614','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22538614"><span>Antarctic <span class="hlt">ice</span>-sheet loss driven by basal melting of <span class="hlt">ice</span> shelves.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Pritchard, H D; Ligtenberg, S R M; Fricker, H A; Vaughan, D G; van den Broeke, M R; Padman, L</p> <p>2012-04-25</p> <p>Accurate prediction of global sea-level rise requires that we understand the cause of recent, widespread and intensifying glacier acceleration along Antarctic <span class="hlt">ice</span>-sheet coastal margins. Atmospheric and oceanic forcing have the potential to reduce the thickness and <span class="hlt">extent</span> of floating <span class="hlt">ice</span> shelves, potentially limiting their ability to buttress the flow of grounded tributary glaciers. Indeed, recent <span class="hlt">ice</span>-shelf collapse led to retreat and acceleration of several glaciers on the Antarctic Peninsula. But the <span class="hlt">extent</span> and magnitude of <span class="hlt">ice</span>-shelf thickness change, the underlying causes of such change, and its link to glacier flow rate are so poorly understood that its future impact on the <span class="hlt">ice</span> sheets cannot yet be predicted. Here we use satellite laser altimetry and modelling of the surface firn layer to reveal the circum-Antarctic pattern of <span class="hlt">ice</span>-shelf thinning through increased basal melt. We deduce that this increased melt is the primary control of Antarctic <span class="hlt">ice</span>-sheet loss, through a reduction in buttressing of the adjacent <span class="hlt">ice</span> sheet leading to accelerated glacier flow. The highest thinning rates occur where warm water at depth can access thick <span class="hlt">ice</span> shelves via submarine troughs crossing the continental shelf. Wind forcing could explain the dominant patterns of both basal melting and the surface melting and collapse of Antarctic <span class="hlt">ice</span> shelves, through ocean upwelling in the Amundsen and Bellingshausen seas, and atmospheric warming on the Antarctic Peninsula. This implies that climate forcing through changing winds influences Antarctic <span class="hlt">ice</span>-sheet mass balance, and hence global sea level, on annual to decadal timescales.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.7897M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.7897M"><span>Recent <span class="hlt">trends</span> in energy flows through the Arctic climate system</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mayer, Michael; Haimberger, Leo</p> <p>2016-04-01</p> <p>While Arctic climate change can be diagnosed in many parameters, a comprehensive assessment of long-term changes and low frequency variability in the coupled Arctic energy budget still remains challenging due to the complex physical processes involved and the lack of observations. Here we draw on strongly improved observational capabilities of the past 15 years and employ observed radiative fluxes from CERES along with state-of-the-art atmospheric as well as coupled ocean-<span class="hlt">ice</span> reanalyses to explore recent changes in energy flows through the Arctic climate system. Various estimates of <span class="hlt">ice</span> volume and ocean heat content <span class="hlt">trends</span> imply that the energy imbalance of the Arctic climate system was >1 Wm-2 during the 2000-2015 period, where most of the extra heat warmed the ocean and a comparatively small fraction was used to melt sea <span class="hlt">ice</span>. The energy imbalance was partly fed by enhanced oceanic heat transports into the Arctic, especially in the mid 2000s. Seasonal <span class="hlt">trends</span> of net radiation show a very clear signal of the <span class="hlt">ice</span>-albedo feedback. Stronger radiative energy input during summer means increased seasonal oceanic heat uptake and accelerated sea <span class="hlt">ice</span> melt. In return, lower minimum sea <span class="hlt">ice</span> <span class="hlt">extent</span> and higher SSTs lead to enhanced heat release from the ocean during fall season. These results are consistent with modeling studies finding an enhancement of the annual cycle of surface energy exchanges in a warming Arctic. Moreover, stronger heat fluxes from the ocean to the atmosphere in fall tend to warm the arctic boundary layer and reduce meridional temperature gradients, thereby reducing atmospheric energy transports into the polar cap. Although the observed results are a robust finding, extended high-quality datasets are needed to reliably separate <span class="hlt">trends</span> from low frequency variability.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1918401P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1918401P"><span>Drivers of Antarctic sea-<span class="hlt">ice</span> expansion and Southern Ocean surface cooling over the past four decades</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Purich, Ariaan; England, Matthew</p> <p>2017-04-01</p> <p>Despite global warming, total Antarctic sea-<span class="hlt">ice</span> coverage has increased overall during the past four decades. In contrast, the majority of CMIP5 models simulate a decline. In addition, Southern Ocean surface waters have largely cooled, in stark contrast to almost all historical CMIP5 simulations. Subantarctic Surface Waters have cooled and freshened while waters to the north of the Antarctic Circumpolar Current have warmed and increased in salinity. It remains unclear as to what <span class="hlt">extent</span> the cooling and Antarctic sea-<span class="hlt">ice</span> expansion is due to natural variability versus anthropogenic forcing; due for example to changes in the Southern Annular Mode (SAM). It is also unclear what the respective role of surface buoyancy fluxes is compared to internal ocean circulation changes, and what the implications are for longer-term climate change in the region. In this presentation we will outline three distinct drivers of recent Southern Ocean surface <span class="hlt">trends</span> that have each made a significant contribution to regional cooling: (1) wind-driven surface cooling and sea-<span class="hlt">ice</span> expansion due to shifted westerly winds, (2) teleconnections of decadal variability from the tropical Pacific, and (3) surface cooling and <span class="hlt">ice</span> expansion due to large-scale Southern Ocean freshening, most likely driven by SAM-related precipitation <span class="hlt">trends</span> over the open ocean. We will also outline the main reasons why climate models for the most part miss these Southern Ocean cooling <span class="hlt">trends</span>, despite capturing overall <span class="hlt">trends</span> in the SAM.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002AGUFMOS21B0197M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002AGUFMOS21B0197M"><span>Biologically-Oriented Processes in the Coastal Sea <span class="hlt">Ice</span> Zone of the White Sea</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Melnikov, I. A.</p> <p>2002-12-01</p> <p>The annual advance and retreat of sea <span class="hlt">ice</span> is a major physical determinant of spatial and temporal changes in the structure and function of marine coastal biological communities. Sea <span class="hlt">ice</span> biological data obtained in the tidal zone of Kandalaksha Gulf (White Sea) during 1996-2001 period will be presented. Previous observations in this area were mainly conducted during the <span class="hlt">ice</span>-free summer season. However, there is little information on the <span class="hlt">ice</span>-covered winter season (6-7 months duration), and, especially, on the sea-<span class="hlt">ice</span> biology in the coastal zone within tidal regimes. During the January-May period time-series observations were conducted on transects along shorelines with coastal and fast <span class="hlt">ice</span>. <span class="hlt">Trends</span> in the annual <span class="hlt">extent</span> of sea <span class="hlt">ice</span> showed significant impacts on <span class="hlt">ice</span>-associated biological communities. Three types of sea <span class="hlt">ice</span> impact on kelps, balanoides, littorinas and amphipods are distinguished: (i) positive, when sea <span class="hlt">ice</span> protects these populations from grinding (ii) negative, when <span class="hlt">ice</span> grinds both fauna and flora, and (iii) a combined effect, when fast <span class="hlt">ice</span> protects, but anchored <span class="hlt">ice</span> grinds plant and animals. To understand the full spectrum of ecological problems caused by pollution on the coastal zone, as well as the problems of sea <span class="hlt">ice</span> melting caused by global warming, an integrated, long-term study of the physical, chemical, and biological processes is needed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160013876','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160013876"><span>Dramatic Contrasts in Arctic vs Antarctic Sea <span class="hlt">Ice</span> <span class="hlt">Trends</span> in 3-D Visualizations and Compilations of Monthly Record Highs and Lows</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.; DiGirolamo, Nicolo E.</p> <p>2016-01-01</p> <p>New visualizations dramatically display the decreases in Arctic sea <span class="hlt">ice</span> coverage over the years 1979-2015, apparent in each month of the year, with not a single record high in <span class="hlt">ice</span> <span class="hlt">extents</span> occurring in any month since 1986, a time period with 75 monthly record lows. Results are less dramatic in the Antarctic, but intriguingly in the opposite direction, with only 6 record lows since 1986 and 45 record highs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C43B0761S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C43B0761S"><span>Current Status and Future Plan of Arctic Sea <span class="hlt">Ice</span> monitoring in South Korea</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Shin, J.; Park, J.</p> <p>2016-12-01</p> <p>Arctic sea <span class="hlt">ice</span> is one of the most important parameters in climate. For monitoring of sea <span class="hlt">ice</span> changes, the National Meteorological Satellite Center (NMSC) of Korea Metrological Administration has developed the "Arctic sea <span class="hlt">ice</span> monitoring system" to retrieve the sea <span class="hlt">ice</span> <span class="hlt">extent</span> and surface roughness using microwave sensor data, and statistical prediction model for Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span>. This system has been implemented to the web site for real-time public service. The sea <span class="hlt">ice</span> information can be retrieved using the spaceborne microwave sensor-Special Sensor Microwave Imager/Sounder (SSMI/S). The sea <span class="hlt">ice</span> information like sea <span class="hlt">ice</span> <span class="hlt">extent</span>, sea <span class="hlt">ice</span> surface roughness, and predictive sea <span class="hlt">ice</span> <span class="hlt">extent</span> are produced weekly base since 2007. We also publish the "Analysis report of the Arctic sea <span class="hlt">ice</span>" twice a year. We are trying to add more sea <span class="hlt">ice</span> information into this system. Details of current status and future plan of Arctic sea <span class="hlt">ice</span> monitoring and the methodology of the sea <span class="hlt">ice</span> information retrievals will be presented in the meeting.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70121037','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70121037"><span>Glacial landforms on German Bank, Scotian Shelf: evidence for Late Wisconsinan <span class="hlt">ice</span>-sheet dynamics and implications for the formation of De Geer moraines</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Todd, Brian J.; Valentine, Page C.; Longva, Oddvar; Shaw, John</p> <p>2007-01-01</p> <p>The <span class="hlt">extent</span> and behaviour of the southeast margin of the Laurentide <span class="hlt">Ice</span> Sheet in Atlantic Canada is of significance in the study of Late Wisconsinan <span class="hlt">ice</span> sheet-ocean interactions. Multibeam sonar imagery of subglacial, <span class="hlt">ice</span>-marginal and glaciomarine landforms on German Bank, Scotian Shelf, provides evidence of the pattern of glacial-dynamic events in the eastern Gulf of Maine. Northwest-southeast <span class="hlt">trending</span> drumlins and megaflutes dominate northern German Bank. On southern German Bank, megaflutes of thin glacial deposits create a distinct northwest-southeast grain. Lobate regional moraines (>10km long) are concave to the northwest, up-<span class="hlt">ice</span> direction and strike southwest-northeast, normal to the direction of <span class="hlt">ice</span> flow. Ubiquitous, overlying De Geer moraines (</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4455714','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4455714"><span>Regional variability in sea <span class="hlt">ice</span> melt in a changing Arctic</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Perovich, Donald K.; Richter-Menge, Jacqueline A.</p> <p>2015-01-01</p> <p>In recent years, the Arctic sea <span class="hlt">ice</span> cover has undergone a precipitous decline in summer <span class="hlt">extent</span>. The sea <span class="hlt">ice</span> mass balance integrates heat and provides insight on atmospheric and oceanic forcing. The amount of surface melt and bottom melt that occurs during the summer melt season was measured at 41 sites over the time period 1957 to 2014. There are large regional and temporal variations in both surface and bottom melting. Combined surface and bottom melt ranged from 16 to 294 cm, with a mean of 101 cm. The mean <span class="hlt">ice</span> equivalent surface melt was 48 cm and the mean bottom melt was 53 cm. On average, surface melting decreases moving northward from the Beaufort Sea towards the North Pole; however interannual differences in atmospheric forcing can overwhelm the influence of latitude. Substantial increases in bottom melting are a major contributor to <span class="hlt">ice</span> losses in the Beaufort Sea, due to decreases in <span class="hlt">ice</span> concentration. In the central Arctic, surface and bottom melting demonstrate interannual variability, but show no strong temporal <span class="hlt">trends</span> from 2000 to 2014. This suggests that under current conditions, summer melting in the central Arctic is not large enough to completely remove the sea <span class="hlt">ice</span> cover. PMID:26032323</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26032323','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26032323"><span>Regional variability in sea <span class="hlt">ice</span> melt in a changing Arctic.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Perovich, Donald K; Richter-Menge, Jacqueline A</p> <p>2015-07-13</p> <p>In recent years, the Arctic sea <span class="hlt">ice</span> cover has undergone a precipitous decline in summer <span class="hlt">extent</span>. The sea <span class="hlt">ice</span> mass balance integrates heat and provides insight on atmospheric and oceanic forcing. The amount of surface melt and bottom melt that occurs during the summer melt season was measured at 41 sites over the time period 1957 to 2014. There are large regional and temporal variations in both surface and bottom melting. Combined surface and bottom melt ranged from 16 to 294 cm, with a mean of 101 cm. The mean <span class="hlt">ice</span> equivalent surface melt was 48 cm and the mean bottom melt was 53 cm. On average, surface melting decreases moving northward from the Beaufort Sea towards the North Pole; however interannual differences in atmospheric forcing can overwhelm the influence of latitude. Substantial increases in bottom melting are a major contributor to <span class="hlt">ice</span> losses in the Beaufort Sea, due to decreases in <span class="hlt">ice</span> concentration. In the central Arctic, surface and bottom melting demonstrate interannual variability, but show no strong temporal <span class="hlt">trends</span> from 2000 to 2014. This suggests that under current conditions, summer melting in the central Arctic is not large enough to completely remove the sea <span class="hlt">ice</span> cover. © 2015 The Author(s) Published by the Royal Society. All rights reserved.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160004954&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dsea','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160004954&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dsea"><span>Arctic Sea <span class="hlt">Ice</span> Simulation in the PlioMIP Ensemble</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Howell, Fergus W.; Haywood, Alan M.; Otto-Bliesner, Bette L.; Bragg, Fran; Chan, Wing-Le; Chandler, Mark A.; Contoux, Camille; Kamae, Youichi; Abe-Ouchi, Ayako; Rosenbloom, Nan A.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20160004954'); toggleEditAbsImage('author_20160004954_show'); toggleEditAbsImage('author_20160004954_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20160004954_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20160004954_hide"></p> <p>2016-01-01</p> <p>Eight general circulation models have simulated the mid-Pliocene warm period (mid-Pliocene, 3.264 to 3.025 Ma) as part of the Pliocene Modelling Intercomparison Project (PlioMIP). Here, we analyse and compare their simulation of Arctic sea <span class="hlt">ice</span> for both the pre-industrial period and the mid-Pliocene. Mid-Pliocene sea <span class="hlt">ice</span> thickness and <span class="hlt">extent</span> is reduced, and the model spread of <span class="hlt">extent</span> is more than twice the pre-industrial spread in some summer months. Half of the PlioMIP models simulate <span class="hlt">ice</span>-free conditions in the mid-Pliocene. This spread amongst the ensemble is in line with the uncertainties amongst proxy reconstructions for mid-Pliocene sea <span class="hlt">ice</span> <span class="hlt">extent</span>. Correlations between mid-Pliocene Arctic temperatures and sea <span class="hlt">ice</span> <span class="hlt">extents</span> are almost twice as strong as the equivalent correlations for the pre-industrial simulations. The need for more comprehensive sea <span class="hlt">ice</span> proxy data is highlighted, in order to better compare model performances.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120008192','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120008192"><span>Variability of Surface Temperature and Melt on the Greenland <span class="hlt">Ice</span> Sheet, 2000-2011</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Comiso, Josefino, C.; Shuman, Christopher A.; Koenig, Lora S.; DiGirolamo, Nicolo E.</p> <p>2012-01-01</p> <p>Enhanced melting along with surface-temperature increases measured using infrared satellite data, have been documented for the Greenland <span class="hlt">Ice</span> Sheet. Recently we developed a climate-quality data record of <span class="hlt">ice</span>-surface temperature (IST) of the Greenland <span class="hlt">Ice</span> Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) 1ST product -- http://modis-snow-<span class="hlt">ice</span>.gsfc.nasa.gov. Using daily and mean monthly MODIS 1ST maps from the data record we show maximum <span class="hlt">extent</span> of melt for the <span class="hlt">ice</span> sheet and its six major drainage basins for a 12-year period extending from March of 2000 through December of 2011. The duration of the melt season on the <span class="hlt">ice</span> sheet varies in different drainage basins with some basins melting progressively earlier over the study period. Some (but not all) of the basins also show a progressively-longer duration of melt. The short time of the study period (approximately 12 years) precludes an evaluation of statistically-significant <span class="hlt">trends</span>. However the dataset provides valuable information on natural variability of IST, and on the ability of the MODIS instrument to capture changes in IST and melt conditions indifferent drainage basins of the <span class="hlt">ice</span> sheet.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFMPP31A1300S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFMPP31A1300S"><span>Little <span class="hlt">Ice</span> Age Fluctuations of Quelccaya <span class="hlt">Ice</span> Cap, Peru</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stroup, J. S.; Kelly, M. A.; Lowell, T.</p> <p>2009-12-01</p> <p>A record of the past <span class="hlt">extents</span> of Quelccaya <span class="hlt">Ice</span> Cap (QIC) provides valuable information about tropical climate change from late glacial to recent time. Here, we examine the timing and regional significance of fluctuations of QIC during the Little <span class="hlt">Ice</span> Age (LIA; ~1300-1850 AD). One prominent set of moraines, known as the Huancane I moraines, is located ~1 km from the present-day western <span class="hlt">ice</span> cap margin and provides a near-continuous outline of the most recent advance of QIC. This moraine set was radiocarbon dated (~298 ± 134 and 831 ± 87 yr BP) by Mercer and Palacios (1977) and presented as some of the first evidence for cooling in the tropics during the Little <span class="hlt">Ice</span> Age. Recent field investigations in the QIC region focused on refining the chronology of the Huancane I moraines. In 2008, new stratigraphic sections exposed by local lake-flooding events revealed multiple layers of peat within the Huancane I moraines. In both 2008 and 2009, samples were obtained for 10Be dating of boulders on Huancane I moraines. A combination of radiocarbon and 10Be ages indicate that the Huancane I moraines were deposited by <span class="hlt">ice</span> cap expansion after ~3800 yr BP and likely by multiple advances at approximately 1000, 600, 400, and 200 yr BP. Radiocarbon and 10Be chronologies of the Huancane I moraines are compared with the Quelccaya <span class="hlt">ice</span> core records (Thompson et al., 1985; 1986; 2006). Accumulation data from the <span class="hlt">ice</span> core records are interpreted to indicate a significant wet period at ~1500-1700 AD followed by a significant drought at ~1720-1860 AD. We examine <span class="hlt">ice</span> marginal fluctuations during these times to determine influence of such events on the <span class="hlt">ice</span> cap <span class="hlt">extent</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C33C1203F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C33C1203F"><span>Fragmentation and melting of the seasonal sea <span class="hlt">ice</span> cover</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Feltham, D. L.; Bateson, A.; Schroeder, D.; Ridley, J. K.; Aksenov, Y.</p> <p>2017-12-01</p> <p>Recent years have seen a rapid reduction in the summer <span class="hlt">extent</span> of Arctic sea <span class="hlt">ice</span>. This <span class="hlt">trend</span> has implications for navigation, oil exploration, wildlife, and local communities. Furthermore the Arctic sea <span class="hlt">ice</span> cover impacts the exchange of heat and momentum between the ocean and atmosphere with significant teleconnections across the climate system, particularly mid to low latitudes in the Northern Hemisphere. The treatment of melting and break-up processes of the seasonal sea <span class="hlt">ice</span> cover within climate models is currently limited. In particular floes are assumed to have a uniform size which does not evolve with time. Observations suggest however that floe sizes can be modelled as truncated power law distributions, with different exponents for smaller and larger floes. This study aims to examine factors controlling the floe size distribution in the seasonal and marginal <span class="hlt">ice</span> zone. This includes lateral melting, wave induced break-up of floes, and the feedback between floe size and the mixed ocean layer. These results are then used to quantify the proximate mechanisms of seasonal sea <span class="hlt">ice</span> reduction in a sea ice—ocean mixed layer model. Observations are used to assess and calibrate the model. The impacts of introducing these processes to the model will be discussed and the preliminary results of sensitivity and feedback studies will also be presented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018QSRv..182...93K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018QSRv..182...93K"><span>Changes in sea <span class="hlt">ice</span> cover and <span class="hlt">ice</span> sheet <span class="hlt">extent</span> at the Yermak Plateau during the last 160 ka - Reconstructions from biomarker records</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kremer, A.; Stein, R.; Fahl, K.; Ji, Z.; Yang, Z.; Wiers, S.; Matthiessen, J.; Forwick, M.; Löwemark, L.; O'Regan, M.; Chen, J.; Snowball, I.</p> <p>2018-02-01</p> <p>The Yermak Plateau is located north of Svalbard at the entrance to the Arctic Ocean, i.e. in an area highly sensitive to climate change. A multi proxy approach was carried out on Core PS92/039-2 to study glacial-interglacial environmental changes at the northern Barents Sea margin during the last 160 ka. The main emphasis was on the reconstruction of sea <span class="hlt">ice</span> cover, based on the sea <span class="hlt">ice</span> proxy IP25 and the related phytoplankton - sea <span class="hlt">ice</span> index PIP25. Sea <span class="hlt">ice</span> was present most of the time but showed significant temporal variability decisively affected by movements of the Svalbard Barents Sea <span class="hlt">Ice</span> Sheet. For the first time, we prove the occurrence of seasonal sea <span class="hlt">ice</span> at the eastern Yermak Plateau during glacial intervals, probably steered by a major northward advance of the <span class="hlt">ice</span> sheet and the formation of a coastal polynya in front of it. Maximum accumulation of terrigenous organic carbon, IP25 and the phytoplankton biomarkers (brassicasterol, dinosterol, HBI III) can be correlated to distinct deglaciation events. More severe, but variable sea <span class="hlt">ice</span> cover prevailed at the Yermak Plateau during interglacials. The general proximity to the sea <span class="hlt">ice</span> margin is further indicated by biomarker (GDGT) - based sea surface temperatures below 2.5 °C.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_12 --> <div id="page_13" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="241"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C33B0821P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C33B0821P"><span>RADARSAT-2 Polarimetric Radar Imaging for Lake <span class="hlt">Ice</span> Mapping</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pan, F.; Kang, K.; Duguay, C. R.</p> <p>2016-12-01</p> <p>Changes in lake <span class="hlt">ice</span> dates and duration are useful indicators for assessing long-term climate <span class="hlt">trends</span> and variability in northern countries. Lake <span class="hlt">ice</span> cover observations are also a valuable data source for predictions with numerical <span class="hlt">ice</span> and weather forecasting models. In recent years, satellite remote sensing has assumed a greater role in providing observations of lake <span class="hlt">ice</span> cover <span class="hlt">extent</span> for both modeling and climate monitoring purposes. Polarimetric radar imaging has become a promising tool for lake <span class="hlt">ice</span> mapping at high latitudes where meteorological conditions and polar darkness severely limit observations from optical sensors. In this study, we assessed and characterized the physical scattering mechanisms of lake <span class="hlt">ice</span> from fully polarimetric RADARSAT-2 datasets obtained over Great Bear Lake, Canada, with the intent of classifying open water and different <span class="hlt">ice</span> types during the freeze-up and break-up periods. Model-based and eigen-based decompositions were employed to construct the coherency matrix into deterministic scattering mechanisms. These procedures as well as basic polarimetric parameters were integrated into modified convolutional neural networks (CNN). The CNN were modified via introduction of a Markov random field into the higher iterative layers of networks for acquiring updated priors and classifying <span class="hlt">ice</span> and open water areas over the lake. We show that the selected polarimetric parameters can help with interpretation of radar-<span class="hlt">ice</span>/water interactions and can be used successfully for water-<span class="hlt">ice</span> segmentation, including different <span class="hlt">ice</span> types. As more satellite SAR sensors are being launched or planned, such as the Sentinel-1a/b series and the upcoming RADARSAT Constellation Mission, the rapid volume growth of data and their analysis require the development of robust automated algorithms. The approach developed in this study was therefore designed with the intent of moving towards fully automated mapping of lake <span class="hlt">ice</span> for consideration by <span class="hlt">ice</span> services.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=GL-2002-001454&hterms=ice+antarctica&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dice%2Bantarctica','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=GL-2002-001454&hterms=ice+antarctica&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dice%2Bantarctica"><span>Breakup of the Larsen <span class="hlt">Ice</span> Shelf, Antarctica</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2002-01-01</p> <p>Recent Moderate-resolution Imaging Spectroradiometer (MODIS) satellite imagery analyzed at the University of Colorado's National Snow and <span class="hlt">Ice</span> Data Center revealed that the northern section of the Larsen B <span class="hlt">ice</span> shelf, a large floating <span class="hlt">ice</span> mass on the eastern side of the Antarctic Peninsula, has shattered and separated from the continent. This particular image was taken on March 5, 2002. The shattered <span class="hlt">ice</span> formed a plume of thousands of icebergs adrift in the Weddell Sea. A total of about 3,250 square kilometers of shelf area disintegrated in a 35-day period beginning on January 31, 2002. Over the last five years, the shelf has lost a total of 5,700 square kilometers and is now about 40 percent the size of its previous minimum stable <span class="hlt">extent</span>. <span class="hlt">Ice</span> shelves are thick plates of <span class="hlt">ice</span>, fed by glaciers, that float on the ocean around much of Antarctica. The Larsen B shelf was about 220 meters thick. Based on studies of <span class="hlt">ice</span> flow and sediment thickness beneath the <span class="hlt">ice</span> shelf, scientists believe that it existed for at least 400 years prior to this event and likely existed since the end of the last major glaciation 12,000 years ago. For reference, the area lost in this most recent event dwarfs Rhode Island (2,717 square kilometers) in size. In terms of volume, the amount of <span class="hlt">ice</span> released in this short time is 720 billion tons--enough <span class="hlt">ice</span> for about 12 trillion 10-kilogram bags. This is the largest single event in a series of retreats by <span class="hlt">ice</span> shelves along the peninsula over the last 30 years. The retreats are attributed to a strong climate warming in the region. The rate of warming is approximately 0.5 degrees Celsius per decade, and the <span class="hlt">trend</span> has been present since at least the late 1940s. Overall in the peninsula, the <span class="hlt">extent</span> of seven <span class="hlt">ice</span> shelves has declined by a total of about 13,500 square kilometers since 1974. This value excludes areas that would be expected to calve under stable conditions. Ted Scambos, a researcher with the National Snow and <span class="hlt">Ice</span> Data Center (NSIDC) at</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24015900','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24015900"><span>Sea <span class="hlt">ice</span> ecosystems.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Arrigo, Kevin R</p> <p>2014-01-01</p> <p>Polar sea <span class="hlt">ice</span> is one of the largest ecosystems on Earth. The liquid brine fraction of the <span class="hlt">ice</span> matrix is home to a diverse array of organisms, ranging from tiny archaea to larger fish and invertebrates. These organisms can tolerate high brine salinity and low temperature but do best when conditions are milder. Thriving <span class="hlt">ice</span> algal communities, generally dominated by diatoms, live at the <span class="hlt">ice</span>/water interface and in recently flooded surface and interior layers, especially during spring, when temperatures begin to rise. Although protists dominate the sea <span class="hlt">ice</span> biomass, heterotrophic bacteria are also abundant. The sea <span class="hlt">ice</span> ecosystem provides food for a host of animals, with crustaceans being the most conspicuous. Uneaten organic matter from the <span class="hlt">ice</span> sinks through the water column and feeds benthic ecosystems. As sea <span class="hlt">ice</span> <span class="hlt">extent</span> declines, <span class="hlt">ice</span> algae likely contribute a shrinking fraction of the total amount of organic matter produced in polar waters.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110005552','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110005552"><span>ICESat Observations of Seasonal and Interannual Variations of Sea-<span class="hlt">Ice</span> Freeboard and Estimated Thickness in the Weddell Sea, Antarctica (2003-2009)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Yi, Donghui; Robbins, John W.</p> <p>2010-01-01</p> <p>Sea-<span class="hlt">ice</span> freeboard heights for 17 ICESat campaign periods from 2003 to 2009 are derived from ICESat data. Freeboard is combined with snow depth from Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) data and nominal densities of snow, water and sea <span class="hlt">ice</span>, to estimate sea-<span class="hlt">ice</span> thickness. Sea-<span class="hlt">ice</span> freeboard and thickness distributions show clear seasonal variations that reflect the yearly cycle of growth and decay of the Weddell Sea (Antarctica) pack <span class="hlt">ice</span>. During October-November, sea <span class="hlt">ice</span> grows to its seasonal maximum both in area and thickness; the mean freeboards are 0.33-0.41 m and the mean thicknesses are 2.10-2.59 m. During February-March, thinner sea <span class="hlt">ice</span> melts away and the sea-<span class="hlt">ice</span> pack is mainly distributed in the west Weddell Sea; the mean freeboards are 0.35-0.46 m and the mean thicknesses are 1.48-1.94 m. During May-June, the mean freeboards and thicknesses are 0.26-0.29 m and 1.32-1.37 m, respectively. The 6 year <span class="hlt">trends</span> in sea-<span class="hlt">ice</span> <span class="hlt">extent</span> and volume are (0.023+/-0.051) x 10(exp 6)sq km/a (0.45%/a) and (0.007+/-1.0.092) x 10(exp 3)cu km/a (0.08%/a); however, the large standard deviations indicate that these positive <span class="hlt">trends</span> are not statistically significant.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004AGUSM.C42A..02D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004AGUSM.C42A..02D"><span>Operationally Monitoring Sea <span class="hlt">Ice</span> at the Canadian <span class="hlt">Ice</span> Service</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>de Abreu, R.; Flett, D.; Carrieres, T.; Falkingham, J.</p> <p>2004-05-01</p> <p>The Canadian <span class="hlt">Ice</span> Service (CIS) of the Meteorological Service of Canada promotes safe and efficient maritime operations and protects Canada's environment by providing reliable and timely information about <span class="hlt">ice</span> and iceberg conditions in Canadian waters. Daily and seasonal charts describing the <span class="hlt">extent</span>, type and concentration of sea <span class="hlt">ice</span> and icebergs are provided to support navigation and other activities (e.g. oil and gas) in coastal waters. The CIS relies on a suite of spaceborne visible, infrared and microwave sensors to operationally monitor <span class="hlt">ice</span> conditions in Canadian coastal and inland waterways. These efforts are complemented by operational sea <span class="hlt">ice</span> models that are customized and run at the CIS. The archive of these data represent a 35 year archive of <span class="hlt">ice</span> conditions and have proven to be a valuable dataset for historical sea <span class="hlt">ice</span> analysis. This presentation will describe the daily integration of remote sensing observations and modelled <span class="hlt">ice</span> conditions used to produce <span class="hlt">ice</span> and iceberg products. A review of the decadal evolution of this process will be presented, as well as a glimpse into the future of <span class="hlt">ice</span> and iceberg monitoring. Examples of the utility of the CIS digital sea <span class="hlt">ice</span> archive for climate studies will also be presented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19930013511','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19930013511"><span>The influence of the hydrologic cycle on the <span class="hlt">extent</span> of sea <span class="hlt">ice</span> with climatic implications</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Dean, Kenneson G.; Stringer, William J.; Searcy, Craig</p> <p>1993-01-01</p> <p>Multi-temporal satellite images, field observations, and field measurements were used to investigate the mechanisms by which sea <span class="hlt">ice</span> melts offshore from the Mackenzie River delta. Advanced Very High Resolution Radiometer (AVHRR) satellite data recorded in 1986 were analyzed. The satellite data were geometrically corrected and radiometrically calibrated so that albedo and temperature values could be extracted. The investigation revealed that sea <span class="hlt">ice</span> melted approximately 2 weeks earlier offshore from the Mackenzie River delta than along coasts where river discharge is minimal or non-existent. There is significant intra-delta variability in the timing and patterns of <span class="hlt">ice</span> melt. An estimation of energy flux indicates that 30 percent more of the visible wavelength energy and 25 percent more of the near-infrared wavelength energy is absorbed by water offshore of the delta compared to coastal areas with minimal river discharge. The analysis also revealed that the removal of sea <span class="hlt">ice</span> involves the following: over-<span class="hlt">ice</span>-flooding along the coast offshore from river delta channels; under-<span class="hlt">ice</span> flow of 'warm' river water; melting and calving of the fast <span class="hlt">ice</span>; and, the formation of a bight in the pack <span class="hlt">ice</span> edge. Two stages in the melting of sea <span class="hlt">ice</span> were identified: (1) an early stage where heat is supplied to overflows largely by solar radiation, and (2) a later stage where heat is supplied by river discharge in addition to solar radiation. A simple thermodynamic model of the thaw process in the fast <span class="hlt">ice</span> zone was developed and parameterized based on events recorded by the satellite images. The model treats river discharge as the source of sensible heat at the base of the <span class="hlt">ice</span> cover. The results of a series of sensitivity tests to assess the influence of river discharge on the near shore <span class="hlt">ice</span> are presented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000037980&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DParkinsons','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000037980&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3DParkinsons"><span>Observed Hemispheric Asymmetry in Global Sea <span class="hlt">Ice</span> Changes</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cavalieri, D. J.; Gloersen, P.; Parkinson, C. L.; Comiso, J. C.; Zwally, H. J.</p> <p>1997-01-01</p> <p>From November 1978 through December 1996, the areal <span class="hlt">extent</span> of sea <span class="hlt">ice</span> decreased by 2.9 +/- 0.4 percent per decade in the Arctic and increased by 1.3 +/- 0.2 percent per decade in the Antarctic. The observed hemispheric asymmetry in these <span class="hlt">trends</span> is consistent with a modeled response to a carbon dioxide-induced climate warming. The interannual variations, which are 2.3 percent of the annual mean in the Arctic, with a predominant period of about 5 years, and 3.4 percent of the annual mean in the Antarctic, with a predominant period of about 3 years, are uncorrelated.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3535660','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3535660"><span><span class="hlt">Extent</span> and relevance of stacking disorder in “<span class="hlt">ice</span> Ic”</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Kuhs, Werner F.; Sippel, Christian; Falenty, Andrzej; Hansen, Thomas C.</p> <p>2012-01-01</p> <p>A solid water phase commonly known as “cubic ice” or “<span class="hlt">ice</span> Ic” is frequently encountered in various transitions between the solid, liquid, and gaseous phases of the water substance. It may form, e.g., by water freezing or vapor deposition in the Earth’s atmosphere or in extraterrestrial environments, and plays a central role in various cryopreservation techniques; its formation is observed over a wide temperature range from about 120 K up to the melting point of <span class="hlt">ice</span>. There was multiple and compelling evidence in the past that this phase is not truly cubic but composed of disordered cubic and hexagonal stacking sequences. The complexity of the stacking disorder, however, appears to have been largely overlooked in most of the literature. By analyzing neutron diffraction data with our stacking-disorder model, we show that correlations between next-nearest layers are clearly developed, leading to marked deviations from a simple random stacking in almost all investigated cases. We follow the evolution of the stacking disorder as a function of time and temperature at conditions relevant to atmospheric processes; a continuous transformation toward normal hexagonal <span class="hlt">ice</span> is observed. We establish a quantitative link between the crystallite size established by diffraction and electron microscopic images of the material; the crystallite size evolves from several nanometers into the micrometer range with progressive annealing. The crystallites are isometric with markedly rough surfaces parallel to the stacking direction, which has implications for atmospheric sciences. PMID:23236184</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000266.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000266.html"><span>NASA Science Flights Target Melting Arctic Sea <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2017-12-08</p> <p>This summer, with sea <span class="hlt">ice</span> across the Arctic Ocean shrinking to below-average levels, a NASA airborne survey of polar <span class="hlt">ice</span> just completed its first flights. Its target: aquamarine pools of melt water on the <span class="hlt">ice</span> surface that may be accelerating the overall sea <span class="hlt">ice</span> retreat. NASA’s Operation <span class="hlt">Ice</span>Bridge completed the first research flight of its new 2016 Arctic summer campaign on July 13. The science flights, which continue through July 25, are collecting data on sea <span class="hlt">ice</span> in a year following a record-warm winter in the Arctic. Read more: go.nasa.gov/29T6mxc Caption: A large pool of melt water over sea <span class="hlt">ice</span>, as seen from an Operation <span class="hlt">Ice</span>Bridge flight over the Beaufort Sea on July 14, 2016. During this summer campaign, <span class="hlt">Ice</span>Bridge will map the <span class="hlt">extent</span>, frequency and depth of melt ponds like these to help scientists forecast the Arctic sea <span class="hlt">ice</span> yearly minimum <span class="hlt">extent</span> in September. Credit: NASA/Operation <span class="hlt">Ice</span>Bridge</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014TCD.....8.5227I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014TCD.....8.5227I"><span>The melt pond fraction and spectral sea <span class="hlt">ice</span> albedo retrieval from MERIS data: validation and <span class="hlt">trends</span> of sea <span class="hlt">ice</span> albedo and melt pond fraction in the Arctic for years 2002-2011</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Istomina, L.; Heygster, G.; Huntemann, M.; Schwarz, P.; Birnbaum, G.; Scharien, R.; Polashenski, C.; Perovich, D.; Zege, E.; Malinka, A.; Prikhach, A.; Katsev, I.</p> <p>2014-10-01</p> <p>The presence of melt ponds on the Arctic sea <span class="hlt">ice</span> strongly affects the energy balance of the Arctic Ocean in summer. It affects albedo as well as transmittance through the sea <span class="hlt">ice</span>, which has consequences on the heat balance and mass balance of sea <span class="hlt">ice</span>. An algorithm to retrieve melt pond fraction and sea <span class="hlt">ice</span> albedo (Zege et al., 2014) from the MEdium Resolution Imaging Spectrometer (MERIS) data is validated against aerial, ship borne and in situ campaign data. The result show the best correlation for landfast and multiyear <span class="hlt">ice</span> of high <span class="hlt">ice</span> concentrations (albedo: R = 0.92, RMS = 0.068, melt pond fraction: R = 0.6, RMS = 0.065). The correlation for lower <span class="hlt">ice</span> concentrations, subpixel <span class="hlt">ice</span> floes, blue <span class="hlt">ice</span> and wet <span class="hlt">ice</span> is lower due to complicated surface conditions and <span class="hlt">ice</span> drift. Combining all aerial observations gives a mean albedo RMS equal to 0.089 and a mean melt pond fraction RMS equal to 0.22. The in situ melt pond fraction correlation is R = 0.72 with an RMS = 0.14. Ship cruise data might be affected by documentation of varying accuracy within the ASPeCT protocol, which is the reason for discrepancy between the satellite value and observed value: mean R = 0.21, mean RMS = 0.16. An additional dynamic spatial cloud filter for MERIS over snow and <span class="hlt">ice</span> has been developed to assist with the validation on swath data. The case studies and <span class="hlt">trend</span> analysis for the whole MERIS period (2002-2011) show pronounced and reasonable spatial features of melt pond fractions and sea <span class="hlt">ice</span> albedo. The most prominent feature is the melt onset shifting towards spring (starting already in weeks 3 and 4 of June) within the multiyear <span class="hlt">ice</span> area, north to the Queen Elizabeth Islands and North Greenland.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24966705','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24966705"><span><span class="hlt">Trends</span> in reporting of mechanisms and incidence of hip injuries in males playing minor <span class="hlt">ice</span> hockey in Canada: a cross-sectional study.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Ayeni, Olufemi R; Kowalczuk, Marcin; Farag, Jordan; Farrokhyar, Forough; Chu, Raymond; Bedi, Asheesh; Willits, Kevin; Bhandari, Mohit</p> <p>2014-01-01</p> <p>There has been a noted increase in the diagnosis and reporting of sporting hip injuries and conditions in the medical literature but reporting at the minor hockey level is unknown. The purpose of this study is to investigate the <span class="hlt">trend</span> of reporting hip injuries in amateur <span class="hlt">ice</span> hockey players in Canada with a focus on injury type and mechanism. A retrospective review of the Hockey Canada insurance database was performed and data on <span class="hlt">ice</span> hockey hip injuries reported between January 2005 and June 2011 were collected. The study population included all male hockey players from Peewee (aged 11-12 years) to Senior (aged 20+ years) participating in amateur level competition sanctioned by Hockey Canada. Reported cases of <span class="hlt">ice</span> hockey hip injuries were analyzed according to age, mechanism of injury, and injury subtype. Annual injury reporting rates were determined and using a linear regression analysis <span class="hlt">trended</span> to determine the change in <span class="hlt">ice</span> hockey hip injury reporting rate over time. One hundred and six cases of <span class="hlt">ice</span> hockey-related hip injuries were reported in total. The majority of injuries (75.5%) occurred in players aged 15-20 years playing at the Junior level. Most injuries were caused by a noncontact mechanism (40.6%) and strains were the most common subtype (50.0%). From 2005 to 2010, the number of reported hip injuries increased by 5.31 cases per year and the rate of reported hip injury per 1,000 registered players increased by 0.02 cases annually. Reporting of hip injuries in amateur <span class="hlt">ice</span> hockey players is increasing. A more accurate injury reporting system is critical for future epidemiologic studies to accurately document the rate and mechanism of hip injury in amateur <span class="hlt">ice</span> hockey players.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120003985','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120003985"><span>Seafloor Control on Sea <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Nghiem, S. V.; Clemente-Colon, P.; Rigor, I. G.; Hall, D. K.; Neumann, G.</p> <p>2011-01-01</p> <p>The seafloor has a profound role in Arctic sea <span class="hlt">ice</span> formation and seasonal evolution. Ocean bathymetry controls the distribution and mixing of warm and cold waters, which may originate from different sources, thereby dictating the pattern of sea <span class="hlt">ice</span> on the ocean surface. Sea <span class="hlt">ice</span> dynamics, forced by surface winds, are also guided by seafloor features in preferential directions. Here, satellite mapping of sea <span class="hlt">ice</span> together with buoy measurements are used to reveal the bathymetric control on sea <span class="hlt">ice</span> growth and dynamics. Bathymetric effects on sea <span class="hlt">ice</span> formation are clearly observed in the conformation between sea <span class="hlt">ice</span> patterns and bathymetric characteristics in the peripheral seas. Beyond local features, bathymetric control appears over extensive <span class="hlt">ice</span>-prone regions across the Arctic Ocean. The large-scale conformation between bathymetry and patterns of different synoptic sea <span class="hlt">ice</span> classes, including seasonal and perennial sea <span class="hlt">ice</span>, is identified. An implication of the bathymetric influence is that the maximum <span class="hlt">extent</span> of the total sea <span class="hlt">ice</span> cover is relatively stable, as observed by scatterometer data in the decade of the 2000s, while the minimum <span class="hlt">ice</span> <span class="hlt">extent</span> has decreased drastically. Because of the geologic control, the sea <span class="hlt">ice</span> cover can expand only as far as it reaches the seashore, the continental shelf break, or other pronounced bathymetric features in the peripheral seas. Since the seafloor does not change significantly for decades or centuries, sea <span class="hlt">ice</span> patterns can be recurrent around certain bathymetric features, which, once identified, may help improve short-term forecast and seasonal outlook of the sea <span class="hlt">ice</span> cover. Moreover, the seafloor can indirectly influence cloud cover by its control on sea <span class="hlt">ice</span> distribution, which differentially modulates the latent heat flux through <span class="hlt">ice</span> covered and open water areas.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.C43E0592P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.C43E0592P"><span>The Last Arctic Sea <span class="hlt">Ice</span> Refuge</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pfirman, S. L.; Tremblay, B.; Newton, R.; Fowler, C.</p> <p>2010-12-01</p> <p>Summer sea <span class="hlt">ice</span> may persist along the northern flank of Canada and Greenland for decades longer than the rest of the Arctic, raising the possibility of a naturally formed refugium for <span class="hlt">ice</span>-associated species. Observations and models indicate that some <span class="hlt">ice</span> in this region forms locally, while some is transported to the area by winds and ocean currents. Depending on future changes in melt patterns and sea <span class="hlt">ice</span> transport rates, both the central Arctic and Siberian shelf seas may be sources of <span class="hlt">ice</span> to the region. An international system of monitoring and management of the sea <span class="hlt">ice</span> refuge, along with the <span class="hlt">ice</span> source regions, has the potential to maintain viable habitat for <span class="hlt">ice</span>-associated species, including polar bears, for decades into the future. Issues to consider in developing a strategy include: + the likely duration and <span class="hlt">extent</span> of summer sea <span class="hlt">ice</span> in this region based on observations, models and paleoenvironmental information + the <span class="hlt">extent</span> and characteristics of the “<span class="hlt">ice</span> shed” contributing sea <span class="hlt">ice</span> to the refuge, including its dynamics, physical and biological characteristics as well as potential for contamination from local or long-range sources + likely assemblages of <span class="hlt">ice</span>-associated species and their habitats + potential stressors such as transportation, tourism, resource extraction, contamination + policy, governance, and development issues including management strategies that could maintain the viability of the refuge.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSHE24A1423M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSHE24A1423M"><span>Aircraft Surveys of the Beaufort Sea Seasonal <span class="hlt">Ice</span> Zone</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Morison, J.</p> <p>2016-02-01</p> <p>The Seasonal <span class="hlt">Ice</span> Zone Reconnaissance Surveys (SIZRS) is a program of repeated ocean, <span class="hlt">ice</span>, and atmospheric measurements across the Beaufort-Chukchi sea seasonal sea <span class="hlt">ice</span> zone (SIZ) utilizing US Coast Guard Arctic Domain Awareness (ADA) flights of opportunity. The SIZ is the region between maximum winter sea <span class="hlt">ice</span> <span class="hlt">extent</span> and minimum summer sea <span class="hlt">ice</span> <span class="hlt">extent</span>. As such, it contains the full range of positions of the marginal <span class="hlt">ice</span> zone (MIZ) where sea <span class="hlt">ice</span> interacts with open water. The increasing size and changing air-<span class="hlt">ice</span>-ocean properties of the SIZ are central to recent reductions in Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span>. The changes in the interplay among the atmosphere, <span class="hlt">ice</span>, and ocean require a systematic SIZ observational effort of coordinated atmosphere, <span class="hlt">ice</span>, and ocean observations covering up to interannual time-scales, Therefore, every year beginning in late Spring and continuing to early Fall, SIZRS makes monthly flights across the Beaufort Sea SIZ aboard Coast Guard C-130H aircraft from USCG Air Station Kodiak dropping Aircraft eXpendable CTDs (AXCTD) and Aircraft eXpendable Current Profilers (AXCP) for profiles of ocean temperature, salinity and shear, dropsondes for atmospheric temperature, humidity, and velocity profiles, and buoys for atmosphere and upper ocean time series. Enroute measurements include IR imaging, radiometer and lidar measurements of the sea surface and cloud tops. SIZRS also cooperates with the International Arctic Buoy Program for buoy deployments and with the NOAA Earth System Research Laboratory atmospheric chemistry sampling program on board the aircraft. Since 2012, SIZRS has found that even as SIZ <span class="hlt">extent</span>, <span class="hlt">ice</span> character, and atmospheric forcing varies year-to-year, the pattern of ocean freshening and radiative warming south of the <span class="hlt">ice</span> edge is consistent. The experimental approach, observations and extensions to other projects will be discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26132925','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26132925"><span>Hg Stable Isotope Time <span class="hlt">Trend</span> in Ringed Seals Registers Decreasing Sea <span class="hlt">Ice</span> Cover in the Alaskan Arctic.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Masbou, Jérémy; Point, David; Sonke, Jeroen E; Frappart, Frédéric; Perrot, Vincent; Amouroux, David; Richard, Pierre; Becker, Paul R</p> <p>2015-08-04</p> <p>Decadal time <span class="hlt">trends</span> of mercury (Hg) concentrations in Arctic biota suggest that anthropogenic Hg is not the single dominant factor modulating Hg exposure to Arctic wildlife. Here, we present Hg speciation (monomethyl-Hg) and stable isotopic composition (C, N, Hg) of 53 Alaskan ringed seal liver samples covering a period of 14 years (1988-2002). In vivo metabolic effects and foraging ecology explain most of the observed 1.6 ‰ variation in liver δ(202)Hg, but not Δ(199)Hg. Ringed seal habitat use and migration were the most likely factors explaining Δ(199)Hg variations. Average Δ(199)Hg in ringed seal liver samples from Barrow increased significantly from +0.38 ± 0.08‰ (±SE, n = 5) in 1988 to +0.59 ± 0.07‰ (±SE, n = 7) in 2002 (4.1 ± 1.2% per year, p < 0.001). Δ(199)Hg in marine biological tissues is thought to reflect marine Hg photochemistry before biouptake and bioaccumulation. A spatiotemporal analysis of sea <span class="hlt">ice</span> cover that accounts for the habitat of ringed seals suggests that the observed increase in Δ(199)Hg may have been caused by the progressive summer sea <span class="hlt">ice</span> disappearance between 1988 and 2002. While changes in seal liver Δ(199)Hg values suggests a mild sea <span class="hlt">ice</span> control on marine MMHg breakdown, the effect is not large enough to induce measurable HgT changes in biota. This suggests that Hg <span class="hlt">trends</span> in biota in the context of a warming Arctic are likely controlled by other processes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140011036','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140011036"><span>Improving Surface Mass Balance Over <span class="hlt">Ice</span> Sheets and Snow Depth on Sea <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Koenig, Lora Suzanne; Box, Jason; Kurtz, Nathan</p> <p>2013-01-01</p> <p>Surface mass balance (SMB) over <span class="hlt">ice</span> sheets and snow on sea <span class="hlt">ice</span> (SOSI) are important components of the cryosphere. Large knowledge gaps remain in scientists' abilities to monitor SMB and SOSI, including insufficient measurements and difficulties with satellite retrievals. On <span class="hlt">ice</span> sheets, snow accumulation is the sole mass gain to SMB, and meltwater runoff can be the dominant single loss factor in extremely warm years such as 2012. SOSI affects the growth and melt cycle of the Earth's polar sea <span class="hlt">ice</span> cover. The summer of 2012 saw the largest satellite-recorded melt area over the Greenland <span class="hlt">ice</span> sheet and the smallest satellite-recorded Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span>, making this meeting both timely and relevant.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/AD1005076','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD1005076"><span>Sunlight, Sea <span class="hlt">Ice</span>, and the <span class="hlt">Ice</span> Albedo Feedback in a Changing Artic Sea <span class="hlt">Ice</span> Cover</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2015-11-30</p> <p>information from the PIOMAS model [J. Zhang], melt pond coverage from MODIS [Rösel et al., 2012], and <span class="hlt">ice</span>-age estimates [Maslanik et al., 2011] to...determined from MODIS satellite data using an artificial neural network, Cryosph., 6(2), 431–446, doi:10.5194/tc- 6-431-2012. PUBLICATIONS Carmack...from MODIS , and <span class="hlt">ice</span>-age estimates to this dataset. We have used this <span class="hlt">extented</span> dataset to build a climatology of the partitioning of solar heat between</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A34E..06F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A34E..06F"><span>Response of mixed-phase boundary layer clouds with rapid and slow <span class="hlt">ice</span> nucleation processes to cloud-top temperature <span class="hlt">trend</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fridlind, A. M.; Avramov, A.; Ackerman, A. S.; Alpert, P. A.; Knopf, D. A.; DeMott, P. J.; Brooks, S. D.; Glen, A.</p> <p>2015-12-01</p> <p>It has been argued on the basis of some laboratory data sets, observed mixed-phase cloud systems, and numerical modeling studies that weakly active or slowly consumed <span class="hlt">ice</span> forming nuclei (IFN) may be important to natural cloud systems. It has also been argued on the basis of field measurements that <span class="hlt">ice</span> nucleation under mixed-phase conditions appears to occur predominantly via a liquid-phase mechanism, requiring the presence of liquid droplets prior to substantial <span class="hlt">ice</span> nucleation. Here we analyze the response of quasi-Lagrangian large-eddy simulations of mixed-phase cloud layers to IFN operating via a liquid-phase mode using assumptions that result in either slow or rapid depletion of IFN from the cloudy boundary layer. Using several generalized case studies that do not exhibit riming or drizzle, based loosely on field campaign data, we vary environmental conditions such that the cloud-top temperature <span class="hlt">trend</span> varies. One objective of this work is to identify differing patterns in <span class="hlt">ice</span> formation intensity that may be distinguishable from ground-based or satellite platforms.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC23D1175M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC23D1175M"><span>Sea <span class="hlt">ice</span>-induced cold air advection as a mechanism controlling tundra primary productivity</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Macias-Fauria, M.; Karlsen, S. R.</p> <p>2015-12-01</p> <p>The recent sharp decline in Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span>, concentration, and volume leaves urgent questions regarding its effects on ecological processes. Changes in tundra productivity have been associated with sea <span class="hlt">ice</span> dynamics on the basis that most tundra ecosystems lay close to the sea. Although some studies have addressed the potential effect of sea <span class="hlt">ice</span> decline on the primary productivity of terrestrial arctic ecosystems (Bhatt et al., 2010), a clear picture of the mechanisms and patterns linking both processes remains elusive. We hypothesised that sea <span class="hlt">ice</span> might influence tundra productivity through 1) cold air advection during the growing season (direct/weather effect) or 2) changes in regional climate induced by changes in sea <span class="hlt">ice</span> (indirect/climate effect). We present a test on the direct/weather effect hypothesis: that is, tundra productivity is coupled with sea <span class="hlt">ice</span> when sea <span class="hlt">ice</span> remains close enough from land vegetation during the growing season for cold air advection to limit temperatures locally. We employed weekly MODIS-derived Normalised Difference Vegetation Index (as a proxy for primary productivity) and sea <span class="hlt">ice</span> data at a spatial resolution of 232m for the period 2000-2014 (included), covering the Svalbard Archipelago. Our results suggest that sea <span class="hlt">ice</span>-induced cold air advection is a likely mechanism to explain patterns of NDVI <span class="hlt">trends</span> and heterogeneous spatial dynamics in the Svalbard archipelago. The mechanism offers the potential to explain sea <span class="hlt">ice</span>/tundra productivity dynamics in other Arctic areas.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1913380R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1913380R"><span>Extreme cyclone events in the Arctic during wintertime: Variability and <span class="hlt">Trends</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rinke, Annette; Maturilli, Marion; Graham, Robert; Matthes, Heidrun; Handorf, Doerthe; Cohen, Lana; Hudson, Stephen; Moore, John</p> <p>2017-04-01</p> <p>Extreme cyclone events are of significant interest as they can transport much heat, moisture, and momentum poleward. Associated impacts are warming and sea-<span class="hlt">ice</span> breakup. Recently, several examples of such extreme weather events occurred in winter (e.g. during the N-<span class="hlt">ICE</span>2015 campaign north of Svalbard and the Frank North Atlantic storm during the end of December 2015). With Arctic amplification and associated reduced sea-<span class="hlt">ice</span> cover and warmer sea surface temperatures, the occurrence of extreme cyclones events could be a plausible scenario. We calculate the spatial patterns, and changes and <span class="hlt">trends</span> of the number of extreme cyclone events in the Arctic based on ERA-Interim six-hourly sea level pressure (SLP) data for winter (November-February) 1979-2015. Further, we analyze the SLP data from the Ny Alesund station for the same 37 year period. We define an extreme cyclone event by a extreme low central pressure (SLP below 985 hPa, which is the 5th percentile of the Ny Alesund/N-<span class="hlt">ICE</span>2015 SLP data) and a deepening of at least 6 hPa/6 hours. Areas of highest frequency of occurrence of extreme cyclones are south/southeast of Greenland (corresponding to the Islandic low), between Norway and Svalbard and in the Barents/Kara Seas. The time series of the number of occurrence of extreme cyclone events for Ny Alesund/N-<span class="hlt">ICE</span> show considerable interannual variability. The <span class="hlt">trend</span> is not consistent through the winter, but we detect an increase in early winter and a slight decrease in late winter. The former is due to the increased occurrence of longer events at the expense of short events. Furthermore, the difference patterns of the frequency of events for months following the September with high and low Arctic sea-<span class="hlt">ice</span> <span class="hlt">extent</span> ("Low minus high sea <span class="hlt">ice</span>") conforms with the change patterns of extreme cyclones numbers (frequency of events "2000-2015 minus 1979-1994") and with the <span class="hlt">trend</span> patterns. This indicates that the changes in extreme cyclone occurrence in early winter are associated with</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_13 --> <div id="page_14" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="261"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C53B0574L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C53B0574L"><span><span class="hlt">Ice</span> Shelf-Ocean Interactions Near <span class="hlt">Ice</span> Rises and <span class="hlt">Ice</span> Rumples</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lange, M. A.; Rückamp, M.; Kleiner, T.</p> <p>2013-12-01</p> <p>The stability of <span class="hlt">ice</span> shelves depends on the existence of embayments and is largely influenced by <span class="hlt">ice</span> rises and <span class="hlt">ice</span> rumples, which act as 'pinning-points' for <span class="hlt">ice</span> shelf movement. Of additional critical importance are interactions between <span class="hlt">ice</span> shelves and the water masses underlying them in <span class="hlt">ice</span> shelf cavities, particularly melting and refreezing processes. The present study aims to elucidate the role of <span class="hlt">ice</span> rises and <span class="hlt">ice</span> rumples in the context of climate change impacts on Antarctic <span class="hlt">ice</span> shelves. However, due to their smaller spatial <span class="hlt">extent</span>, <span class="hlt">ice</span> rumples react more sensitively to climate change than <span class="hlt">ice</span> rises. Different forcings are at work and need to be considered separately as well as synergistically. In order to address these issues, we have decided to deal with the following three issues explicitly: oceanographic-, cryospheric and general topics. In so doing, we paid particular attention to possible interrelationships and feedbacks in a coupled <span class="hlt">ice</span>-shelf-ocean system. With regard to oceanographic issues, we have applied the ocean circulation model ROMBAX to ocean water masses adjacent to and underneath a number of idealized <span class="hlt">ice</span> shelf configurations: wide and narrow as well as laterally restrained and unrestrained <span class="hlt">ice</span> shelves. Simulations were performed with and without small <span class="hlt">ice</span> rises located close to the calving front. For larger configurations, the impact of the <span class="hlt">ice</span> rises on melt rates at the <span class="hlt">ice</span> shelf base is negligible, while for smaller configurations net melting rates at the <span class="hlt">ice</span>-shelf base differ by a factor of up to eight depending on whether <span class="hlt">ice</span> rises are considered or not. We employed the thermo-coupled <span class="hlt">ice</span> flow model TIM-FD3 to simulate the effects of several <span class="hlt">ice</span> rises and one <span class="hlt">ice</span> rumple on the dynamics of <span class="hlt">ice</span> shelf flow. We considered the complete un-grounding of the <span class="hlt">ice</span> shelf in order to investigate the effect of pinning points of different characteristics (interior or near calving front, small and medium sized) on the resulting flow and stress fields</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C32B..02S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C32B..02S"><span>Structural Uncertainty in Antarctic sea <span class="hlt">ice</span> simulations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schneider, D. P.</p> <p>2016-12-01</p> <p>The inability of the vast majority of historical climate model simulations to reproduce the observed increase in Antarctic sea <span class="hlt">ice</span> has motivated many studies about the quality of the observational record, the role of natural variability versus forced changes, and the possibility of missing or inadequate forcings in the models (such as freshwater discharge from thinning <span class="hlt">ice</span> shelves or an inadequate magnitude of stratospheric ozone depletion). In this presentation I will highlight another source of uncertainty that has received comparatively little attention: Structural uncertainty, that is, the systematic uncertainty in simulated sea <span class="hlt">ice</span> <span class="hlt">trends</span> that arises from model physics and mean-state biases. Using two large ensembles of experiments from the Community Earth System Model (CESM), I will show that the model is predisposed towards producing negative Antarctic sea <span class="hlt">ice</span> <span class="hlt">trends</span> during 1979-present, and that this outcome is not simply because the model's decadal variability is out-of-synch with that in nature. In the "Tropical Pacific Pacemaker" ensemble, in which observed tropical Pacific SST anomalies are prescribed, the model produces very realistic atmospheric circulation <span class="hlt">trends</span> over the Southern Ocean, yet the sea <span class="hlt">ice</span> <span class="hlt">trend</span> is negative in every ensemble member. However, if the ensemble-mean <span class="hlt">trend</span> (commonly interpreted as the forced response) is removed, some ensemble members show a sea <span class="hlt">ice</span> increase that is very similar to the observed. While this results does confirm the important role of natural variability, it also suggests a strong bias in the forced response. I will discuss the reasons for this systematic bias and explore possible remedies. This an important problem to solve because projections of 21st -Century changes in the Antarctic climate system (including <span class="hlt">ice</span> sheet surface mass balance changes and related changes in the sea level budget) have a strong dependence on the mean state of and changes in the Antarctic sea <span class="hlt">ice</span> cover. This problem is not unique to</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120010403','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120010403"><span>Satellite Observations of Antarctic Sea <span class="hlt">Ice</span> Thickness and Volume</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kurtz, Nathan; Markus, Thorsten</p> <p>2012-01-01</p> <p>We utilize satellite laser altimetry data from ICESat combined with passive microwave measurements to analyze basin-wide changes in Antarctic sea <span class="hlt">ice</span> thickness and volume over a 5 year period from 2003-2008. Sea <span class="hlt">ice</span> thickness exhibits a small negative <span class="hlt">trend</span> while area increases in the summer and fall balanced losses in thickness leading to small overall volume changes. Using a five year time-series, we show that only small <span class="hlt">ice</span> thickness changes of less than -0.03 m/yr and volume changes of -266 cu km/yr and 160 cu km/yr occurred for the spring and summer periods, respectively. The calculated thickness and volume <span class="hlt">trends</span> are small compared to the observational time period and interannual variability which masks the determination of long-term <span class="hlt">trend</span> or cyclical variability in the sea <span class="hlt">ice</span> cover. These results are in stark contrast to the much greater observed losses in Arctic sea <span class="hlt">ice</span> volume and illustrate the different hemispheric changes of the polar sea <span class="hlt">ice</span> covers in recent years.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUFM.A12B..01M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUFM.A12B..01M"><span>Overview of Sea-<span class="hlt">Ice</span> Properties, Distribution and Temporal Variations, for Application to <span class="hlt">Ice</span>-Atmosphere Chemical Processes.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Moritz, R. E.</p> <p>2005-12-01</p> <p>The properties, distribution and temporal variation of sea-<span class="hlt">ice</span> are reviewed for application to problems of <span class="hlt">ice</span>-atmosphere chemical processes. Typical vertical structure of sea-<span class="hlt">ice</span> is presented for different <span class="hlt">ice</span> types, including young <span class="hlt">ice</span>, first-year <span class="hlt">ice</span> and multi-year <span class="hlt">ice</span>, emphasizing factors relevant to surface chemistry and gas exchange. Time average annual cycles of large scale variables are presented, including <span class="hlt">ice</span> concentration, <span class="hlt">ice</span> <span class="hlt">extent</span>, <span class="hlt">ice</span> thickness and <span class="hlt">ice</span> age. Spatial and temporal variability of these large scale quantities is considered on time scales of 1-50 years, emphasizing recent and projected changes in the Arctic pack <span class="hlt">ice</span>. The amount and time evolution of open water and thin <span class="hlt">ice</span> are important factors that influence ocean-<span class="hlt">ice</span>-atmosphere chemical processes. Observations and modeling of the sea-<span class="hlt">ice</span> thickness distribution function are presented to characterize the range of variability in open water and thin <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014TCry....8.2293A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014TCry....8.2293A"><span>Assessing spatio-temporal variability and <span class="hlt">trends</span> in modelled and measured Greenland <span class="hlt">Ice</span> Sheet albedo (2000-2013)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Alexander, P. M.; Tedesco, M.; Fettweis, X.; van de Wal, R. S. W.; Smeets, C. J. P. P.; van den Broeke, M. R.</p> <p>2014-12-01</p> <p>Accurate measurements and simulations of Greenland <span class="hlt">Ice</span> Sheet (GrIS) surface albedo are essential, given the role of surface albedo in modulating the amount of absorbed solar radiation and meltwater production. In this study, we assess the spatio-temporal variability of GrIS albedo during June, July, and August (JJA) for the period 2000-2013. We use two remote sensing products derived from data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS), as well as outputs from the Modèle Atmosphérique Régionale (MAR) regional climate model (RCM) and data from in situ automatic weather stations. Our results point to an overall consistency in spatio-temporal variability between remote sensing and RCM albedo, but reveal a difference in mean albedo of up to ~0.08 between the two remote sensing products north of 70° N. At low elevations, albedo values simulated by the RCM are positively biased with respect to remote sensing products by up to ~0.1 and exhibit low variability compared with observations. We infer that these differences are the result of a positive bias in simulated bare <span class="hlt">ice</span> albedo. MODIS albedo, RCM outputs, and in situ observations consistently indicate a decrease in albedo of -0.03 to -0.06 per decade over the period 2003-2013 for the GrIS ablation area. Nevertheless, satellite products show a decline in JJA albedo of -0.03 to -0.04 per decade for regions within the accumulation area that is not confirmed by either the model or in situ observations. These findings appear to contradict a previous study that found an agreement between in situ and MODIS <span class="hlt">trends</span> for individual months. The results indicate a need for further evaluation of high elevation albedo <span class="hlt">trends</span>, a reconciliation of MODIS mean albedo at high latitudes, and the importance of accurately simulating bare <span class="hlt">ice</span> albedo in RCMs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19930061578&hterms=madison+wisconsin&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dmadison%2Bwisconsin','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19930061578&hterms=madison+wisconsin&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dmadison%2Bwisconsin"><span>Satellite observation of lake <span class="hlt">ice</span> as a climate indicator - Initial results from statewide monitoring in Wisconsin</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wynne, Randolph H.; Lillesand, Thomas M.</p> <p>1993-01-01</p> <p>The research reported herein focused on the general hypothesis that satellite remote sensing of large-area, long-term <span class="hlt">trends</span> in lake <span class="hlt">ice</span> phenology (formation and breakup) is a robust, integrated measure of regional and global climate change. To validate this hypothesis, we explored the use of data from the Advanced Very High Resolution Radiometer (AVHRR) to discriminate the presence and <span class="hlt">extent</span> of lake <span class="hlt">ice</span> during the winter of 1990-1991 on the 45 lakes and reservoirs in Wisconsin with a surface area greater than 1,000 hectares. Our results suggest both the feasibility of using the AVHRR to determine the date of lake <span class="hlt">ice</span> breakup as well as the strong correlation (R= -0.87) of the date so derived with local surface-based temperature measurements. These results suggest the potential of using current and archival satellite data to monitor changes in the date of lake <span class="hlt">ice</span> breakup as a means of detecting regional 'signals' of greenhouse warming.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70036603','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70036603"><span>Integration of MODIS-derived metrics to assess interannual variability in snowpack, lake <span class="hlt">ice</span>, and NDVI in southwest Alaska</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Reed, Bradley C.; Budde, Michael E.; Spencer, Page; Miller, Amy E.</p> <p>2009-01-01</p> <p>Impacts of global climate change are expected to result in greater variation in the seasonality of snowpack, lake <span class="hlt">ice</span>, and vegetation dynamics in southwest Alaska. All have wide-reaching physical and biological ecosystem effects in the region. We used Moderate Resolution Imaging Spectroradiometer (MODIS) calibrated radiance, snow cover <span class="hlt">extent</span>, and vegetation index products for interpreting interannual variation in the duration and <span class="hlt">extent</span> of snowpack, lake <span class="hlt">ice</span>, and vegetation dynamics for southwest Alaska. The approach integrates multiple seasonal metrics across large ecological regions. Throughout the observation period (2001-2007), snow cover duration was stable within ecoregions, with variable start and end dates. The start of the lake <span class="hlt">ice</span> season lagged the snow season by 2 to 3??months. Within a given lake, freeze-up dates varied in timing and duration, while break-up dates were more consistent. Vegetation phenology varied less than snow and <span class="hlt">ice</span> metrics, with start-of-season dates comparatively consistent across years. The start of growing season and snow melt were related to one another as they are both temperature dependent. Higher than average temperatures during the El Ni??o winter of 2002-2003 were expressed in anomalous <span class="hlt">ice</span> and snow season patterns. We are developing a consistent, MODIS-based dataset that will be used to monitor temporal <span class="hlt">trends</span> of each of these seasonal metrics and to map areas of change for the study area.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.C53B..02O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.C53B..02O"><span>Collaborative, International Efforts at Estimating Arctic Sea <span class="hlt">Ice</span> Processes During IPY (Invited)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Overland, J. E.; Eicken, H.; Wiggins, H. V.</p> <p>2009-12-01</p> <p>Planning for the fourth IPY was conducted during a time of moderate decadal change in the Arctic. However, after this initial planning was completed, further rapid changes were seen, including a 39 % reduction in summer sea <span class="hlt">ice</span> <span class="hlt">extent</span> in 2007 and 2008 relative to the 1980s-1990s, loss of multi-year sea <span class="hlt">ice</span>, and increased sea <span class="hlt">ice</span> mobility. The SEARCH and DAMOCLES Programs endeavored to increase communication within the research community to promote observations and understanding of rapidly changing Arctic sea <span class="hlt">ice</span> conditions during IPY. In May 2008 a web-based Sea <span class="hlt">Ice</span> Outlook was initiated, an international collaborative effort that synthesizes, on a monthly basis throughout the summer, the community’s projections for September arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span>. Each month, participating investigators provided a projection for the mean September sea <span class="hlt">ice</span> <span class="hlt">extent</span> based on spring and early summer data, along with a rationale for their estimates. The Outlook continued in summer of 2009. The Outlook is a method of rapidly synthesizing a broad range of remote sensing and field observations collected at the peak of the IPY, with analysis methods ranging from heuristic to statistical to <span class="hlt">ice</span>-ocean model ensemble runs. The 2008 Outlook was a success with 20 groups participating and providing a median sea <span class="hlt">ice</span> <span class="hlt">extent</span> projection from June 2008 data of 4.4 million square kilometers (MSQK)—near the observed <span class="hlt">extent</span> in September 2008 of 4.7 MSQK, and well below the 1979-2007 climatological <span class="hlt">extent</span> of 6.7 MSQK. More importantly, the contrast of sea <span class="hlt">ice</span> conditions and atmospheric forcing in 2008 compared to 2007 provided clues to the future fate of arctic sea <span class="hlt">ice</span>. The question was whether the previous loss of multi-year <span class="hlt">ice</span> and delay in autumn freeze-up in 2007 would allow sufficient winter thickening of sea <span class="hlt">ice</span> to last through the summer 2008, promoting recovery from the 2007 minimum, or whether most first-year sea <span class="hlt">ice</span> would melt out as in 2005 and 2007, resulting in a new record minimum <span class="hlt">extent</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C13E..04H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C13E..04H"><span>Towards decadal time series of Arctic and Antarctic sea <span class="hlt">ice</span> thickness from radar altimetry</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hendricks, S.; Rinne, E. J.; Paul, S.; Ricker, R.; Skourup, H.; Kern, S.; Sandven, S.</p> <p>2016-12-01</p> <p>The CryoSat-2 mission has demonstrated the value of radar altimetry to assess the interannual variability and short-term <span class="hlt">trends</span> of Arctic sea <span class="hlt">ice</span> over the existing observational record of 6 winter seasons. CryoSat-2 is a particular successful mission for sea <span class="hlt">ice</span> mass balance assessment due to its novel radar altimeter concept and orbit configuration, but radar altimetry data is available since 1993 from the ERS-1/2 and Envisat missions. Combining these datasets promises a decadal climate data record of sea <span class="hlt">ice</span> thickness, but inter-mission biases must be taken into account due to the evolution of radar altimeters and the impact of changing sea <span class="hlt">ice</span> conditions on retrieval algorithm parametrizations. The ESA Climate Change Initiative on Sea <span class="hlt">Ice</span> aims to <span class="hlt">extent</span> the list of data records for Essential Climate Variables (ECV's) with a consistent time series of sea <span class="hlt">ice</span> thickness from available radar altimeter data. We report on the progress of the algorithm development and choices for auxiliary data sets for sea <span class="hlt">ice</span> thickness retrieval in the Arctic and Antarctic Oceans. Particular challenges are the classification of surface types and freeboard retrieval based on radar waveforms with significantly varying footprint sizes. In addition, auxiliary data sets, e.g. for snow depth, are far less developed in the Antarctic and we will discuss the expected skill of the sea <span class="hlt">ice</span> thickness ECV's in both hemispheres.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018CliPa..14..619B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018CliPa..14..619B"><span>Simulation of the Greenland <span class="hlt">Ice</span> Sheet over two glacial-interglacial cycles: investigating a sub-<span class="hlt">ice</span>-shelf melt parameterization and relative sea level forcing in an <span class="hlt">ice-sheet-ice</span>-shelf model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bradley, Sarah L.; Reerink, Thomas J.; van de Wal, Roderik S. W.; Helsen, Michiel M.</p> <p>2018-05-01</p> <p>Observational evidence, including offshore moraines and sediment cores, confirm that at the Last Glacial Maximum (LGM) the Greenland <span class="hlt">ice</span> sheet (GrIS) expanded to a significantly larger spatial <span class="hlt">extent</span> than seen at present, grounding into Baffin Bay and out onto the continental shelf break. Given this larger spatial <span class="hlt">extent</span> and its close proximity to the neighbouring Laurentide <span class="hlt">Ice</span> Sheet (LIS) and Innuitian <span class="hlt">Ice</span> Sheet (IIS), it is likely these <span class="hlt">ice</span> sheets will have had a strong non-local influence on the spatial and temporal behaviour of the GrIS. Most previous paleo <span class="hlt">ice</span>-sheet modelling simulations recreated an <span class="hlt">ice</span> sheet that either did not extend out onto the continental shelf or utilized a simplified marine <span class="hlt">ice</span> parameterization which did not fully include the effect of <span class="hlt">ice</span> shelves or neglected the sensitivity of the GrIS to this non-local bedrock signal from the surrounding <span class="hlt">ice</span> sheets. In this paper, we investigated the evolution of the GrIS over the two most recent glacial-interglacial cycles (240 ka BP to the present day) using the <span class="hlt">ice-sheet-ice</span>-shelf model IMAU-<span class="hlt">ICE</span>. We investigated the solid earth influence of the LIS and IIS via an offline relative sea level (RSL) forcing generated by a glacial isostatic adjustment (GIA) model. The RSL forcing governed the spatial and temporal pattern of sub-<span class="hlt">ice</span>-shelf melting via changes in the water depth below the <span class="hlt">ice</span> shelves. In the ensemble of simulations, at the glacial maximums, the GrIS coalesced with the IIS to the north and expanded to the continental shelf break to the southwest but remained too restricted to the northeast. In terms of the global mean sea level contribution, at the Last Interglacial (LIG) and LGM the <span class="hlt">ice</span> sheet added 1.46 and -2.59 m, respectively. This LGM contribution by the GrIS is considerably higher (˜ 1.26 m) than most previous studies whereas the contribution to the LIG highstand is lower (˜ 0.7 m). The spatial and temporal behaviour of the northern margin was highly variable in all simulations</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014PhDT.......122B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014PhDT.......122B"><span>Greenland <span class="hlt">ice</span> sheet retreat since the Little <span class="hlt">Ice</span> Age</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Beitch, Marci J.</p> <p></p> <p>Late 20th century and 21st century satellite imagery of the perimeter of the Greenland <span class="hlt">Ice</span> Sheet (GrIS) provide high resolution observations of the <span class="hlt">ice</span> sheet margins. Examining changes in <span class="hlt">ice</span> margin positions over time yield measurements of GrIS area change and rates of margin retreat. However, longer records of <span class="hlt">ice</span> sheet margin change are needed to establish more accurate predictions of the <span class="hlt">ice</span> sheet's future response to global conditions. In this study, the trimzone, the area of deglaciated terrain along the <span class="hlt">ice</span> sheet edge that lacks mature vegetation cover, is used as a marker of the maximum <span class="hlt">extent</span> of the <span class="hlt">ice</span> from its most recent major advance during the Little <span class="hlt">Ice</span> Age. We compile recently acquired Landsat ETM+ scenes covering the perimeter of the GrIS on which we map area loss on land-, lake-, and marine-terminating margins. We measure an area loss of 13,327 +/- 830 km2, which corresponds to 0.8% shrinkage of the <span class="hlt">ice</span> sheet. This equates to an averaged horizontal retreat of 363 +/- 69 m across the entire GrIS margin. Mapping the areas exposed since the Little <span class="hlt">Ice</span> Age maximum, circa 1900 C.E., yields a century-scale rate of change. On average the <span class="hlt">ice</span> sheet lost an area of 120 +/- 16 km 2/yr, or retreated at a rate of 3.3 +/- 0.7 m/yr since the LIA maximum.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EaFut...2..315O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EaFut...2..315O"><span>Global warming releases microplastic legacy frozen in Arctic Sea <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Obbard, Rachel W.; Sadri, Saeed; Wong, Ying Qi; Khitun, Alexandra A.; Baker, Ian; Thompson, Richard C.</p> <p>2014-06-01</p> <p>When sea <span class="hlt">ice</span> forms it scavenges and concentrates particulates from the water column, which then become trapped until the <span class="hlt">ice</span> melts. In recent years, melting has led to record lows in Arctic Sea <span class="hlt">ice</span> <span class="hlt">extent</span>, the most recent in September 2012. Global climate models, such as that of Gregory et al. (2002), suggest that the decline in Arctic Sea <span class="hlt">ice</span> volume (3.4% per decade) will actually exceed the decline in sea <span class="hlt">ice</span> <span class="hlt">extent</span>, something that Laxon et al. (2013) have shown supported by satellite data. The <span class="hlt">extent</span> to which melting <span class="hlt">ice</span> could release anthropogenic particulates back to the open ocean has not yet been examined. Here we show that Arctic Sea <span class="hlt">ice</span> from remote locations contains concentrations of microplastics at least two orders of magnitude greater than those that have been previously reported in highly contaminated surface waters, such as those of the Pacific Gyre. Our findings indicate that microplastics have accumulated far from population centers and that polar sea <span class="hlt">ice</span> represents a major historic global sink of man-made particulates. The potential for substantial quantities of legacy microplastic contamination to be released to the ocean as the <span class="hlt">ice</span> melts therefore needs to be evaluated, as do the physical and toxicological effects of plastics on marine life.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://dx.doi.org/10.1126/science.1209299','USGSPUBS'); return false;" href="http://dx.doi.org/10.1126/science.1209299"><span>Interhemispheric <span class="hlt">ice</span>-sheet synchronicity during the last glacial maximum</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Weber, Michael E.; Clark, Peter U.; Ricken, Werner; Mitrovica, Jerry X.; Hostetler, Steven W.; Kuhn, Gerhard</p> <p>2011-01-01</p> <p>The timing of the last maximum <span class="hlt">extent</span> of the Antarctic <span class="hlt">ice</span> sheets relative to those in the Northern Hemisphere remains poorly understood. We develop a chronology for the Weddell Sea sector of the East Antarctic <span class="hlt">Ice</span> Sheet that, combined with ages from other Antarctic <span class="hlt">ice</span>-sheet sectors, indicates that the advance to and retreat from their maximum <span class="hlt">extent</span> was within dating uncertainties synchronous with most sectors of Northern Hemisphere <span class="hlt">ice</span> sheets. Surface climate forcing of Antarctic mass balance would probably cause an opposite response, whereby a warming climate would increase accumulation but not surface melting. Our new data support teleconnections involving sea-level forcing from Northern Hemisphere <span class="hlt">ice</span> sheets and changes in North Atlantic deep-water formation and attendant heat flux to Antarctic grounding lines to synchronize the hemispheric <span class="hlt">ice</span> sheets.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22144623','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22144623"><span>Interhemispheric <span class="hlt">ice</span>-sheet synchronicity during the Last Glacial Maximum.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Weber, Michael E; Clark, Peter U; Ricken, Werner; Mitrovica, Jerry X; Hostetler, Steven W; Kuhn, Gerhard</p> <p>2011-12-02</p> <p>The timing of the last maximum <span class="hlt">extent</span> of the Antarctic <span class="hlt">ice</span> sheets relative to those in the Northern Hemisphere remains poorly understood. We develop a chronology for the Weddell Sea sector of the East Antarctic <span class="hlt">Ice</span> Sheet that, combined with ages from other Antarctic <span class="hlt">ice</span>-sheet sectors, indicates that the advance to and retreat from their maximum <span class="hlt">extent</span> was within dating uncertainties synchronous with most sectors of Northern Hemisphere <span class="hlt">ice</span> sheets. Surface climate forcing of Antarctic mass balance would probably cause an opposite response, whereby a warming climate would increase accumulation but not surface melting. Our new data support teleconnections involving sea-level forcing from Northern Hemisphere <span class="hlt">ice</span> sheets and changes in North Atlantic deep-water formation and attendant heat flux to Antarctic grounding lines to synchronize the hemispheric <span class="hlt">ice</span> sheets.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018TCry...12..433P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018TCry...12..433P"><span>The Arctic sea <span class="hlt">ice</span> cover of 2016: a year of record-low highs and higher-than-expected lows</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Petty, Alek A.; Stroeve, Julienne C.; Holland, Paul R.; Boisvert, Linette N.; Bliss, Angela C.; Kimura, Noriaki; Meier, Walter N.</p> <p>2018-02-01</p> <p>The Arctic sea <span class="hlt">ice</span> cover of 2016 was highly noteworthy, as it featured record low monthly sea <span class="hlt">ice</span> <span class="hlt">extents</span> at the start of the year but a summer (September) <span class="hlt">extent</span> that was higher than expected by most seasonal forecasts. Here we explore the 2016 Arctic sea <span class="hlt">ice</span> state in terms of its monthly sea <span class="hlt">ice</span> cover, placing this in the context of the sea <span class="hlt">ice</span> conditions observed since 2000. We demonstrate the sensitivity of monthly Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> and area estimates, in terms of their magnitude and annual rankings, to the <span class="hlt">ice</span> concentration input data (using two widely used datasets) and to the averaging methodology used to convert concentration to <span class="hlt">extent</span> (daily or monthly <span class="hlt">extent</span> calculations). We use estimates of sea <span class="hlt">ice</span> area over sea <span class="hlt">ice</span> <span class="hlt">extent</span> to analyse the relative "compactness" of the Arctic sea <span class="hlt">ice</span> cover, highlighting anomalously low compactness in the summer of 2016 which contributed to the higher-than-expected September <span class="hlt">ice</span> <span class="hlt">extent</span>. Two cyclones that entered the Arctic Ocean during August appear to have driven this low-concentration/compactness <span class="hlt">ice</span> cover but were not sufficient to cause more widespread melt-out and a new record-low September <span class="hlt">ice</span> <span class="hlt">extent</span>. We use concentration budgets to explore the regions and processes (thermodynamics/dynamics) contributing to the monthly 2016 <span class="hlt">extent</span>/area estimates highlighting, amongst other things, rapid <span class="hlt">ice</span> intensification across the central eastern Arctic through September. Two different products show significant early melt onset across the Arctic Ocean in 2016, including record-early melt onset in the North Atlantic sector of the Arctic. Our results also show record-late 2016 freeze-up in the central Arctic, North Atlantic and the Alaskan Arctic sector in particular, associated with strong sea surface temperature anomalies that appeared shortly after the 2016 minimum (October onwards). We explore the implications of this low summer <span class="hlt">ice</span> compactness for seasonal forecasting, suggesting that sea <span class="hlt">ice</span> area could be a more reliable</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.C23C0646G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.C23C0646G"><span>Numerical model of <span class="hlt">ice</span> melange expansion during abrupt <span class="hlt">ice</span>-shelf collapse</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Guttenberg, N.; Abbot, D. S.; Amundson, J. M.; Burton, J. C.; Cathles, L. M.; Macayeal, D. R.; Zhang, W.</p> <p>2010-12-01</p> <p>Satellite imagery of the February 2008 Wilkins <span class="hlt">Ice</span>-Shelf Collapse event reveals that a large percentage of the involved <span class="hlt">ice</span> shelf was converted to capsized icebergs and broken fragments of icebergs over a relatively short period of time, possibly less than 24 hours. The extreme violence and short time scale of the event, and the considerable reduction of gravitational potential energy between upright and capsized icebergs, suggests that iceberg capsize might be an important driving mechanism controlling both the rate and spatial <span class="hlt">extent</span> of <span class="hlt">ice</span> shelf collapse. To investigate this suggestion, we have constructed an idealized, 2-dimensional model of a disintegrating <span class="hlt">ice</span> shelf composed of a large number (N~100 to >1000) of initially well-packed icebergs of rectangular cross section. The model geometry consists of a longitudinal cross section of the idealized <span class="hlt">ice</span> shelf from grounding line (or the upstream <span class="hlt">extent</span> of <span class="hlt">ice</span>-shelf fragmentation) to seaward <span class="hlt">ice</span> front, and includes the region beyond the initial <span class="hlt">ice</span> front to cover the open, <span class="hlt">ice</span>-free water into which the collapsing <span class="hlt">ice</span> shelf expands. The seawater in which the icebergs float is treated as a hydrostatic fluid in the computation of iceberg orientation (e.g., the evaluation of buoyancy forces and torques), thereby eliminating the complexities of free-surface waves, but net horizontal drift of the icebergs is resisted by a linear drag law designed to energy dissipation by viscous forces and surface-gravity-wave radiation. Icebergs interact via both elastic and inelastic contacts (typically a corner of one iceberg will scrape along the face of its neighbor). <span class="hlt">Ice</span>-shelf collapse in the model is embodied by the mass capsize of a large proportion of the initially packed icebergs and the consequent advancement of the <span class="hlt">ice</span> front (leading edge). Model simulations are conducted to examine (a) the threshold of stability (e.g., what density of initially capsizable icebergs is needed to allow a small perturbation to the system</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012PhDT.......190H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012PhDT.......190H"><span>The influence of sea <span class="hlt">ice</span> on Antarctic <span class="hlt">ice</span> core sulfur chemistry and on the future evolution of Arctic snow depth: Investigations using global models</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hezel, Paul J.</p> <p></p> <p>Observational studies have examined the relationship between methanesulfonic acid (MSA) measured in Antarctic <span class="hlt">ice</span> cores and sea <span class="hlt">ice</span> <span class="hlt">extent</span> measured by satellites with the aim of producing a proxy for past sea <span class="hlt">ice</span> <span class="hlt">extent</span>. MSA is an oxidation product of dimethylsulfide (DMS) and is potentially linked to sea <span class="hlt">ice</span> based on observations of very high surface seawater DMS in the sea <span class="hlt">ice</span> zone. Using a global chemical transport model, we present the first modeling study that specifically examines this relationship on interannual and on glacial-interglacial time scales. On interannual time scales, the model shows no robust relationship between MSA deposited in Antarctica and sea <span class="hlt">ice</span> <span class="hlt">extent</span>. We show that lifetimes of MSA and DMS are longer in the high latitudes than in the global mean, interannual variability of sea <span class="hlt">ice</span> is small (<25%) as a fraction of sea <span class="hlt">ice</span> area, and sea <span class="hlt">ice</span> determines only a fraction of the variability (<30%) of DMS emissions from the ocean surface. A potentially larger fraction of the variability in DMS emissions is determined by surface wind speed (up to 46%) via the parameterization for ocean-to-atmosphere gas exchange. Furthermore, we find that a significant fraction (up to 74%) of MSA deposited in Antarctica originates from north of 60°S, north of the seasonal sea <span class="hlt">ice</span> zone. We then examine the deposition of MSA and non-sea-salt sulfate (nss SO2-4 ) on glacial-interglacial time scales. <span class="hlt">Ice</span> core observations on the East Antarctic Plateau suggest that MSA increases much more than nss SO2-4 during the last glacial maximum (LGM) compared to the modern period. It has been suggested that high MSA during the LGM is indicative of higher primary productivity and DMS emissions in the LGM compared to the modern day. Studies have also shown that MSA is subject to post-depositional volatilization, especially during the modern period. Using the same chemical transport model driven by meteorology from a global climate model, we examine the sensitivity of MSA and nss</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1611876G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1611876G"><span>Towards an <span class="hlt">Ice</span>-Free Arctic Ocean in Summertime</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gascard, Jean Claude</p> <p>2014-05-01</p> <p>Dividing the Arctic Ocean in two parts, the so-called Atlantic versus the Pacific sector, two distinct modes of variability appear for characterizing the Arctic sea-<span class="hlt">ice</span> <span class="hlt">extent</span> from 70°N up to 80°N in both sectors. The Atlantic sector seasonal sea-<span class="hlt">ice</span> <span class="hlt">extent</span> is characterized by a longer time scale than the Pacific sector with a break up melting season starting in May and reaching a peak in June-July, one month earlier than the Pacific sector of the Arctic Ocean revealing a faster time evolution and a larger spatial amplitude than the Atlantic sector. During recent years like 2007, sea-<span class="hlt">ice</span> <span class="hlt">extent</span> with sea-<span class="hlt">ice</span> concentration above 15% retreated from 4 millions km2 to about 1 million km2 in the Arctic Pacific sector between 70° and 80°N except for 2012 when most of sea-<span class="hlt">ice</span> melted away in this region. That explained most of the differences between the two extreme years 2007 and 2012. In the Atlantic sector, Arctic sea-<span class="hlt">ice</span> retreated from 2 millions km2 to nearly 0 during recent years including 2007 and 2012. The Atlantic inflow North of Svalbard and Franz Josef Land is more likely responsible for a northward retreat of the <span class="hlt">ice</span> edge in that region. The important factor is not only that the Arctic summer sea-<span class="hlt">ice</span> minimum <span class="hlt">extent</span> decreased by 3 or 4 millions km2 over the past 10 years but also that the melting period was steadily increasing by one to two days every year during that period. An important factor concerns the strength of the freezing that can be quantified in terms of Freezing Degree Days FDD accumulated during the winter-spring season and the strength of the melting (MDD) that can be accumulated during the summer season. FDD and MDD have been calculated for the past 30 years all over the Arctic Ocean using ERA Interim Reanalysis surface temperature at 2m height in the atmosphere. It is clear that FDD decreased significantly by more than 2000 FDD between 1980 and 2012 which is equivalent to the sensible heat flux corresponding to more than a meter of sea-<span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C24B..06D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C24B..06D"><span>Arctic Sea <span class="hlt">Ice</span> Structure and Texture over Four Decades Using Landsat Archive Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Doulgeris, A. P.; Scambos, T.; Tiampo, K. F.</p> <p>2017-12-01</p> <p>Arctic sea <span class="hlt">ice</span> cover is a sensitive indicator of Arctic climate change, and has shown dramatic changes in recent decades, having thinned by 70% ( 3.5 m to 1.2 m between 1980 and 2015). Age distribution of the <span class="hlt">ice</span> has changed in a similar fashion, with over 90% of the <span class="hlt">ice</span> older than 5 winters now lost relative to 1985. To date, most of the data have been based on the continuous passive microwave record that began in 1978, which has 25 km grid resolution, or on SAR imagery with somewhat less frequent, less continuous observations. Landsat image data exist for the Arctic sea <span class="hlt">ice</span> region north of Alaska and the MacKenzie River Delta area in Canada, the Canadian Archipelago, and Baffin Bay, extending back over 40 years. Resolution of the earliest Landsat MSS data is 56-70 m per pixel, and after 1984 many additional images at 30 m resolution are available. This 40+ year time period is used to investigate long-term changes in sea <span class="hlt">ice</span> properties, such as comparing image-based snapshots with the <span class="hlt">trend</span> in seasonal <span class="hlt">extents</span> today, as well as more novel properties like sea <span class="hlt">ice</span> roughness, lead structure and texture. The proposed study will initially investigate Landsat image analysis techniques to extract quantitative measures of <span class="hlt">ice</span> roughness, lead fraction and perhaps morphological measures like lead linearity (which potentially indicate strength and compression history within the <span class="hlt">ice</span>), and to explore these measures over the 40+ year time frame.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C32B..05A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C32B..05A"><span>Spatial variability and <span class="hlt">trends</span> of seasonal snowmelt processes over Antarctic sea <span class="hlt">ice</span> observed by satellite scatterometers</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Arndt, S.; Haas, C.</p> <p>2017-12-01</p> <p> 1992 to 2014. The subsequent regression analysis showed that no significant temporal <span class="hlt">trend</span> in the retrieved snowmelt onset dates can be observed, but strong inter-annual variability. This absence of any notable changes in snowmelt behavior is in line with the small observed temporal changes of the Antarctic sea <span class="hlt">ice</span> cover and atmospheric warming</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_14 --> <div id="page_15" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="281"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/981847','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/981847"><span>Controls on Arctic sea <span class="hlt">ice</span> from first-year and multi-year survival rates</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Hunke, Jes</p> <p>2009-01-01</p> <p>The recent decrease in Arctic sea <span class="hlt">ice</span> cover has transpired with a significant loss of multi year <span class="hlt">ice</span>. The transition to an Arctic that is populated by thinner first year sea <span class="hlt">ice</span> has important implications for future <span class="hlt">trends</span> in area and volume. Here we develop a reduced model for Arctic sea <span class="hlt">ice</span> with which we investigate how the survivability of first year and multi year <span class="hlt">ice</span> control the mean state, variability, and <span class="hlt">trends</span> in <span class="hlt">ice</span> area and volume.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/12154613','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/12154613"><span>Ecology of southern ocean pack <span class="hlt">ice</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Brierley, Andrew S; Thomas, David N</p> <p>2002-01-01</p> <p> aggregating there. As a result, much of the Southern Ocean pelagic whaling was concentrated at the edge of the marginal <span class="hlt">ice</span> zone. The <span class="hlt">extent</span> and duration of sea <span class="hlt">ice</span> fluctuate periodically under the influence of global climatic phenomena including the El Niño Southern Oscillation. Life cycles of some associated species may reflect this periodicity. With evidence for climatic warming in some regions of Antarctica, there is concern that ecosystem change may be induced by changes in sea-<span class="hlt">ice</span> <span class="hlt">extent</span>. The relative abundance of krill and salps appears to change interannually with sea-<span class="hlt">ice</span> <span class="hlt">extent</span>, and in warm years, when salps proliferate, krill are scarce and dependent predators suffer severely. Further research on the Southern Ocean sea-<span class="hlt">ice</span> system is required, not only to further our basic understanding of the ecology, but also to provide ecosystem managers with the information necessary for the development of strategies in response to short- and medium-term environmental changes in Antarctica. Technological advances are delivering new sampling platforms such as autonomous underwater vehicles that are improving vastly our ability to sample the Antarctic under sea-<span class="hlt">ice</span> environment. Data from such platforms will enhance greatly our understanding of the globally important Southern Ocean sea-<span class="hlt">ice</span> ecosystem.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1616930P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1616930P"><span>The <span class="hlt">extent</span> and timing of the last British-Irish <span class="hlt">Ice</span> Sheet offshore of west Ireland-preliminary findings</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Peters, Jared; Benetti, Sara; Dunlop, Paul; Cofaigh, Colm Ó.</p> <p>2014-05-01</p> <p>Recently interpreted marine geophysical data from the western Irish shelf has provided the first direct evidence that the last British-Irish <span class="hlt">Ice</span> Sheet (BIIS) extended westwards onto the Irish continental shelf as a grounded <span class="hlt">ice</span> mass composed of several lobes with marine-terminating margins. Marine terminating <span class="hlt">ice</span> margins are known to be sensitive to external forcing mechanisms and currently there is concern regarding the future stability of marine based <span class="hlt">ice</span> sheets, such as the West Antarctic <span class="hlt">Ice</span> Sheet, in a warming world. Given its position, the glaciated western Irish continental shelf is a prime location to investigate the processes of how marine-based <span class="hlt">ice</span> sheets responded to past climatic and oceanic events, which may in turn help us better predict the future trajectory of the marine sectors of modern <span class="hlt">Ice</span> Sheets. However, despite the potential importance of the former Irish <span class="hlt">ice</span> margin to our understanding of <span class="hlt">ice</span> sheet behaviour, the timing and nature of its advance and retreat is currently poorly understood. This study aims to describe the depositional history of the last BIIS on the continental shelf west of Ireland and age-constrain the rate of retreat of two <span class="hlt">ice</span> lobes that extended from Galway Bay and Clew Bay. This is being accomplished through a multifaceted analysis of at least 29 sediment cores gathered across the continental shelf offshore of counties Galway and Mayo, Ireland. This poster shows results from initial sedimentological descriptions of cores from the mid to outer shelf, which support previous geomorphic interpretations of BIIS history. Preliminary palaeoenvironmental results from ongoing micropaleontological analyses are also discussed and provide new data that verifies sedimentary interpretations on <span class="hlt">ice</span> proximity. Finally, results from several radiocarbon dates are discussed, which limit these deposits to the last glacial maximum and constrain the timings of <span class="hlt">ice</span> advance and retreat on the continental shelf west of Ireland.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014GeoRL..41.7566D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014GeoRL..41.7566D"><span>Will Arctic sea <span class="hlt">ice</span> thickness initialization improve seasonal forecast skill?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Day, J. J.; Hawkins, E.; Tietsche, S.</p> <p>2014-11-01</p> <p>Arctic sea <span class="hlt">ice</span> thickness is thought to be an important predictor of Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span>. However, coupled seasonal forecast systems do not generally use sea <span class="hlt">ice</span> thickness observations in their initialization and are therefore missing a potentially important source of additional skill. To investigate how large this source is, a set of ensemble potential predictability experiments with a global climate model, initialized with and without knowledge of the sea <span class="hlt">ice</span> thickness initial state, have been run. These experiments show that accurate knowledge of the sea <span class="hlt">ice</span> thickness field is crucially important for sea <span class="hlt">ice</span> concentration and <span class="hlt">extent</span> forecasts up to 8 months ahead, especially in summer. Perturbing sea <span class="hlt">ice</span> thickness also has a significant impact on the forecast error in Arctic 2 m temperature a few months ahead. These results suggest that advancing capabilities to observe and assimilate sea <span class="hlt">ice</span> thickness into coupled forecast systems could significantly increase skill.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GeoRL..4311295S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GeoRL..4311295S"><span>Greenland <span class="hlt">Ice</span> Sheet flow response to runoff variability</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stevens, Laura A.; Behn, Mark D.; Das, Sarah B.; Joughin, Ian; Noël, Brice P. Y.; Broeke, Michiel R.; Herring, Thomas</p> <p>2016-11-01</p> <p>We use observations of <span class="hlt">ice</span> sheet surface motion from a Global Positioning System network operating from 2006 to 2014 around North Lake in west Greenland to investigate the dynamical response of the Greenland <span class="hlt">Ice</span> Sheet's ablation area to interannual variability in surface melting. We find no statistically significant relationship between runoff season characteristics and <span class="hlt">ice</span> flow velocities within a given year or season. Over the 7 year time series, annual velocities at North Lake decrease at an average rate of -0.9 ± 1.1 m yr-2, consistent with the negative <span class="hlt">trend</span> in annual velocities observed in neighboring regions over recent decades. We find that net runoff integrated over several preceding years has a negative correlation with annual velocities, similar to findings from the two other available decadal records of <span class="hlt">ice</span> velocity in western Greenland. However, we argue that this correlation is not necessarily evidence for a direct hydrologic mechanism acting on the timescale of multiple years but could be a statistical construct. Finally, we stress that neither the decadal slowdown <span class="hlt">trend</span> nor the negative correlation between velocity and integrated runoff is predicted by current <span class="hlt">ice</span>-sheet models, underscoring that these models do not yet capture all the relevant feedbacks between runoff and <span class="hlt">ice</span> dynamics needed to predict long-term <span class="hlt">trends</span> in <span class="hlt">ice</span> sheet flow.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4778018','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4778018"><span>Holocene <span class="hlt">ice</span> marginal fluctuations of the Qassimiut lobe in South Greenland</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Larsen, Nicolaj K.; Find, Jesper; Kristensen, Anders; Bjørk, Anders A.; Kjeldsen, Kristian K.; Odgaard, Bent V.; Olsen, Jesper; Kjær, Kurt H.</p> <p>2016-01-01</p> <p>Knowledge about the Holocene evolution of the Greenland <span class="hlt">ice</span> sheet (GrIS) is important to put the recent observations of <span class="hlt">ice</span> loss into a longer-term perspective. In this study, we use six new threshold lake records supplemented with two existing lake records to reconstruct the Holocene <span class="hlt">ice</span> marginal fluctuations of the Qassimiut lobe (QL) – one of the most dynamic parts of the GrIS in South Greenland. Times when the <span class="hlt">ice</span> margin was close to present <span class="hlt">extent</span> are characterized by clastic input from the glacier meltwater, whereas periods when the <span class="hlt">ice</span> margin was behind its present day <span class="hlt">extent</span> comprise organic-rich sediments. We find that the overall pattern suggests that the central part of the <span class="hlt">ice</span> lobe in low-lying areas experienced the most prolonged <span class="hlt">ice</span> retreat from ~9–0.4 cal. ka BP, whereas the more distal parts of the <span class="hlt">ice</span> lobe at higher elevation re-advanced and remained close to the present <span class="hlt">extent</span> during the Neoglacial between ~4.4 and 1.8 cal. ka BP. These results demonstrate that the QL was primarily driven by Holocene climate changes, but also emphasises the role of local topography on the <span class="hlt">ice</span> marginal fluctuations. PMID:26940998</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JGRC..123.1406T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JGRC..123.1406T"><span>An Examination of the Sea <span class="hlt">Ice</span> Rheology for Seasonal <span class="hlt">Ice</span> Zones Based on <span class="hlt">Ice</span> Drift and Thickness Observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Toyota, Takenobu; Kimura, Noriaki</p> <p>2018-02-01</p> <p>The validity of the sea <span class="hlt">ice</span> rheological model formulated by Hibler (1979), which is widely used in present numerical sea <span class="hlt">ice</span> models, is examined for the Sea of Okhotsk as an example of the seasonal <span class="hlt">ice</span> zone (SIZ), based on satellite-derived sea <span class="hlt">ice</span> velocity, concentration and thickness. Our focus was the formulation of the yield curve, the shape of which can be estimated from <span class="hlt">ice</span> drift pattern based on the energy equation of deformation, while the strength of the <span class="hlt">ice</span> cover that determines its magnitude was evaluated using <span class="hlt">ice</span> concentration and thickness data. <span class="hlt">Ice</span> drift was obtained with a grid spacing of 37.5 km from the AMSR-E 89 GHz brightness temperature using a maximum cross-correlation method. The <span class="hlt">ice</span> thickness was obtained with a spatial resolution of 100 m from a regression of the PALSAR backscatter coefficients with <span class="hlt">ice</span> thickness. To assess scale dependence, the <span class="hlt">ice</span> drift data derived from a coastal radar covering a 70 km range in the southernmost Sea of Okhotsk were similarly analyzed. The results obtained were mostly consistent with Hibler's formulation that was based on the Arctic Ocean on both scales with no dependence on a time scale, and justify the treatment of sea <span class="hlt">ice</span> as a plastic material, with an elliptical shaped yield curve to some <span class="hlt">extent</span>. However, it also highlights the difficulty in parameterizing sub-grid scale ridging in the model because grid scale <span class="hlt">ice</span> velocities reduce the deformation magnitude by half due to the large variation of the deformation field in the SIZ.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.C43E0603G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.C43E0603G"><span>Fast <span class="hlt">ice</span> in the Canadian Arctic: Climatology, Atmospheric Forcing and Relation to Bathymetry</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Galley, R. J.; Barber, D. G.</p> <p>2010-12-01</p> <p>Mobile sea <span class="hlt">ice</span> in the northern hemisphere has experienced significant reductions in both <span class="hlt">extent</span> and thickness over the last thirty years, and global climate models agree that these decreases will continue. However, the Canadian Arctic Archipelago (CAA) creates a much different icescape than in the central Arctic Ocean due to its distinctive topographic, bathymetric and climatological conditions. Of particular interest is the continued viability of landfast sea <span class="hlt">ice</span> as a means of transportation and platform for transportation and hunting for the Canadian Inuit that reside in the region, as is the possibility of the Northwest Passage becoming a viable shipping lane in the future. Here we determine the climatological average landfast <span class="hlt">ice</span> conditions in the Canadian Arctic Archipelago over the last 27 years, we investigate variability and <span class="hlt">trends</span> in these landfast <span class="hlt">ice</span> conditions, and we attempt to elucidate the physical parameters conducive to landfast sea <span class="hlt">ice</span> formation in sub-regions of the CAA during different times of the year. We use the Canadian <span class="hlt">Ice</span> Service digital sea <span class="hlt">ice</span> charts between 1983 and 2009 on a 2x2km grid to determine the sea <span class="hlt">ice</span> concentration-by-type and whether the sea <span class="hlt">ice</span> in a grid cell was landfast on a weekly, bi-weekly or monthly basis depending on the time of year. North American Regional Reanalysis (NARR) atmospheric data were used in this work, including air temperature, surface level pressure and wind speed and direction. The bathymetric data employed was from the International Bathymetric Chart of the Arctic Ocean. Results indicate that the CAA sea <span class="hlt">ice</span> regime is not climatologically analogous to the mobile sea <span class="hlt">ice</span> of the central Arctic Ocean. The sea <span class="hlt">ice</span> and the atmospheric and bathymetric properties that control the amount and timing of landfast sea <span class="hlt">ice</span> within the CAA are regionally variable.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.4286W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.4286W"><span>Interhemispheric <span class="hlt">ice</span>-sheet synchronicity during the Last Glacial Maximum</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Weber, M. E.; Clark, P. U.; Ricken, W.; Mitrovica, J. X.; Hostetler, S. W.; Kuhn, G.</p> <p>2012-04-01</p> <p>The timing of the last maximum <span class="hlt">extent</span> of the Antarctic <span class="hlt">ice</span> sheets relative to those in the Northern Hemisphere remains poorly understood because only a few findings with robust chronologies exist for Antarctic <span class="hlt">ice</span> sheets. We developed a chronology for the Weddell Sea sector of the East Antarctic <span class="hlt">ice</span> sheet that, combined with ages from other Antarctic <span class="hlt">ice</span>-sheet sectors, indicates the advance to their maximum <span class="hlt">extent</span> at 29 -28 ka, and retreat from their maximum <span class="hlt">extent</span> at 19 ka was nearly synchronous with Northern Hemisphere <span class="hlt">ice</span> sheets (Weber, M.E., Clark, P. U., Ricken, W., Mitrovica, J. X., Hostetler, S. W., and Kuhn, G. (2011): Interhemispheric <span class="hlt">ice</span>-sheet synchronicity during the Last Glacial Maximum. - Science, 334, 1265-1269, doi: 10.1126:science.1209299). As for the deglaciation, modeling studies suggest a late <span class="hlt">ice</span>-sheet retreat starting around 14 ka BP and ending around 7 ka BP with a large impact of an unstable West Antarctic <span class="hlt">Ice</span> Sheet (WAIS) and a small impact of a stable East Antarctic <span class="hlt">Ice</span> Sheet (EAIS). However, the Weddell Sea sites studied here, as well as sites from the Scotia Sea, provide evidence that specifically the EAIS responded much earlier, possibly provided a significant contribution to the last sea-level rise, and was much more dynamic than previously thought. Using the results of an atmospheric general circulation we conclude that surface climate forcing of Antarctic <span class="hlt">ice</span> mass balance would likely cause an opposite response, whereby a warming climate would increase accumulation but not surface melting. Furthermore, our new data support teleconnections involving a sea-level fingerprint forced from Northern Hemisphere <span class="hlt">ice</span> sheets as indicated by gravitational modeling. Also, changes in North Atlantic Deepwater formation and attendant heat flux to Antarctic grounding lines may have contributed to synchronizing the hemispheric <span class="hlt">ice</span> sheets.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28135412','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28135412"><span><span class="hlt">Ice</span> Nucleation Efficiency of Hydroxylated Organic Surfaces Is Controlled by Their Structural Fluctuations and Mismatch to <span class="hlt">Ice</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Qiu, Yuqing; Odendahl, Nathan; Hudait, Arpa; Mason, Ryan; Bertram, Allan K; Paesani, Francesco; DeMott, Paul J; Molinero, Valeria</p> <p>2017-03-01</p> <p>Heterogeneous nucleation of <span class="hlt">ice</span> induced by organic materials is of fundamental importance for climate, biology, and industry. Among organic <span class="hlt">ice</span>-nucleating surfaces, monolayers of long chain alcohols are particularly effective, while monolayers of fatty acids are significantly less so. As these monolayers expose to water hydroxyl groups with an order that resembles the one in the basal plane of <span class="hlt">ice</span>, it was proposed that lattice matching between <span class="hlt">ice</span> and the surface controls their <span class="hlt">ice</span>-nucleating efficiency. Organic monolayers are soft materials and display significant fluctuations. It has been conjectured that these fluctuations assist in the nucleation of <span class="hlt">ice</span>. Here we use molecular dynamic simulations and laboratory experiments to investigate the relationship between the structure and fluctuations of hydroxylated organic surfaces and the temperature at which they nucleate <span class="hlt">ice</span>. We find that these surfaces order interfacial water to form domains with <span class="hlt">ice</span>-like order that are the birthplace of <span class="hlt">ice</span>. Both mismatch and fluctuations decrease the size of the preordered domains and monotonously decrease the <span class="hlt">ice</span> freezing temperature. The simulations indicate that fluctuations depress the freezing efficiency of monolayers of alcohols or acids to half the value predicted from lattice mismatch alone. The model captures the experimental <span class="hlt">trend</span> in freezing efficiencies as a function of chain length and predicts that alcohols have higher freezing efficiency than acids of the same chain length. These <span class="hlt">trends</span> are mostly controlled by the modulation of the structural mismatch to <span class="hlt">ice</span>. We use classical nucleation theory to show that the freezing efficiencies of the monolayers are directly related to their free energy of binding to <span class="hlt">ice</span>. This study provides a general framework to relate the equilibrium thermodynamics of <span class="hlt">ice</span> binding to a surface and the nonequilibrium <span class="hlt">ice</span> freezing temperature and suggests that these could be predicted from the structure of interfacial water.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24950115','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24950115"><span>A review of the physics of <span class="hlt">ice</span> surface friction and the development of <span class="hlt">ice</span> skating.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Formenti, Federico</p> <p>2014-01-01</p> <p>Our walking and running movement patterns require friction between shoes and ground. The surface of <span class="hlt">ice</span> is characterised by low friction in several naturally occurring conditions, and compromises our typical locomotion pattern. <span class="hlt">Ice</span> skates take advantage of this slippery nature of <span class="hlt">ice</span>; the first <span class="hlt">ice</span> skates were made more than 4000 years ago, and afforded the development of a very efficient form of human locomotion. This review presents an overview of the physics of <span class="hlt">ice</span> surface friction, and discusses the most relevant factors that can influence <span class="hlt">ice</span> skates' dynamic friction coefficient. It also presents the main stages in the development of <span class="hlt">ice</span> skating, describes the associated implications for exercise physiology, and shows the <span class="hlt">extent</span> to which <span class="hlt">ice</span> skating performance improved through history. This article illustrates how technical and materials' development, together with empirical understanding of muscle biomechanics and energetics, led to one of the fastest forms of human powered locomotion.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.G23B..01S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.G23B..01S"><span><span class="hlt">Trends</span> in <span class="hlt">ice</span> sheet mass balance, 1992 to 2017</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Shepherd, A.; Ivins, E. R.; Smith, B.; Velicogna, I.; Whitehouse, P. L.; Rignot, E. J.; van den Broeke, M. R.; Briggs, K.; Hogg, A.; Krinner, G.; Joughin, I. R.; Nowicki, S.; Payne, A. J.; Scambos, T.; Schlegel, N.; Moyano, G.; Konrad, H.</p> <p>2017-12-01</p> <p>The <span class="hlt">Ice</span> Sheet Mass Balance Inter-Comparison Exercise (IMBIE) is a community effort, jointly supported by ESA and NASA, that aims to provide a consensus estimate of <span class="hlt">ice</span> sheet mass balance from satellite gravimetry, altimetry and mass budget assessments, on an annual basis. The project has five experiment groups, one for each of the satellite techniques and two others to analyse surface mass balance (SMB) and glacial isostatic adjustment (GIA). The basic premise for the exercise is that individual <span class="hlt">ice</span> sheet mass balance datasets are generated by project participants using common spatial and temporal domains to allow meaningful inter-comparison, and this controlled comparison in turn supports aggregation of the individual datasets over their full period. Participation is open to the full community, and the quality and consistency of submissions is regulated through a series of data standards and documentation requirements. The second phase of IMBIE commenced in 2015, with participant data submitted in 2016 and a combined estimate due for public release in 2017. Data from 48 participant groups were submitted to one of the three satellite mass balance technique groups or to the ancillary dataset groups. The individual mass balance estimates and ancillary datasets have been compared and combined within the respective groups. Following this, estimates of <span class="hlt">ice</span> sheet mass balance derived from the individual techniques were then compared and combined. The result is single estimates of <span class="hlt">ice</span> sheet mass balance for Greenland, East Antarctica, West Antarctica, and the Antarctic Peninsula. The participants, methodology and results of the exercise will be presented in this paper.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010EGUGA..12.5422T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010EGUGA..12.5422T"><span>The 'dark' side of the Greenland <span class="hlt">Ice</span> Sheet: 2009 updated long term melting <span class="hlt">trends</span>, remotely controlled boats on supraglacial lakes and cryokonite holes.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tedesco, Marco</p> <p>2010-05-01</p> <p>In this talk I will report recent results from different projects concerning melting over the Greenland <span class="hlt">Ice</span> Sheet.

In particular, I will focus on three aspects: first, I will show results updating the long-term melting <span class="hlt">trends</span> (1979 - 2009) derived with spaceborne satellite data will discuss the 2009 melting season. 
Second, I will present results of an experiment aiming at improving the monitoring of supraglacial lakes from visible and near-infrared satellite data and will present seasonal <span class="hlt">trends</span> of these surface features. At the beginning of July 2009, we collected lake depth data and satellites-like data to evaluate satellites products used to study supraglacial lakes and improve monitoring techniques. We used a remotely controlled boat equipped with a GPS, fishfinder, spectrometer and microcomputer to collect these data. 
Third, while on the <span class="hlt">ice</span> sheet, we also collected samples of cryoconite (that dark powdered material responsible for dark holes in the <span class="hlt">ice</span>). I will report the results of preliminary analysis of this material by using Scanning Electronic Microscopy (SEM, for analyzing the composition) and a spectrometer (to characterize the visible and near-infrared properties). 

The following people contributed to the results here reported: Nick Steiner (CUNY), M. Jenkins (National Geographic), X. Fettweis (University of Liege), Adam Lewinter and James Balog (Extreme <span class="hlt">Ice</span> Survey), Gina Stovall and Gordon Green (CCNY).
The World Wildlife Foundation (WWF) and Martin Sommerkorn are deeply acknowledged for the financial support provided for the experiment.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050041627','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050041627"><span><span class="hlt">Ice</span> Shelves and Landfast <span class="hlt">Ice</span> on the Antarctic Perimeter: Revised Scope of Work</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Abdalati, Waleed (Technical Monitor); Scambos, Ted</p> <p>2004-01-01</p> <p><span class="hlt">Ice</span> shelves respond quickly and profoundly to a warming climate. Within a decade after mean summertime temperature reaches approximately 0 deg C and persistent melt ponding is observed, a rapid retreat and disintegration begins. This link was documented for <span class="hlt">ice</span> shelves in the Antarctic Peninsula region (the Larsen 'A', B', and Wilkins <span class="hlt">Ice</span> shelves) in the results of a previous grant under ADRO-1. Modeling of shelf <span class="hlt">ice</span> flow and the effects of meltwater indicated that melt ponding accelerates shelf breakup by increasing fracturing. The ADRO-2 funding (topic of this report) supported further inquiry into the evolution of <span class="hlt">ice</span> shelves under warming conditions, and the post-breakup effects on their feeder glaciers. Also, this grant considered fast <span class="hlt">ice</span> and sea <span class="hlt">ice</span> characteristics, to the <span class="hlt">extent</span> that they provide information regarding shelf stability. A major component of this work was in the form of NSIDC image data support and in situ sea <span class="hlt">ice</span> research on the Aurora Australis 'ARISE' cruise of September 9 2003 through October 28 2003.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/16782603','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/16782603"><span>Mass balance of the Antarctic <span class="hlt">ice</span> sheet.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wingham, D J; Shepherd, A; Muir, A; Marshall, G J</p> <p>2006-07-15</p> <p>The Antarctic contribution to sea-level rise has long been uncertain. While regional variability in <span class="hlt">ice</span> dynamics has been revealed, a picture of mass changes throughout the continental <span class="hlt">ice</span> sheet is lacking. Here, we use satellite radar altimetry to measure the elevation change of 72% of the grounded <span class="hlt">ice</span> sheet during the period 1992-2003. Depending on the density of the snow giving rise to the observed elevation fluctuations, the <span class="hlt">ice</span> sheet mass <span class="hlt">trend</span> falls in the range -5-+85Gtyr-1. We find that data from climate model reanalyses are not able to characterise the contemporary snowfall fluctuation with useful accuracy and our best estimate of the overall mass <span class="hlt">trend</span>-growth of 27+/-29Gtyr-1-is based on an assessment of the expected snowfall variability. Mass gains from accumulating snow, particularly on the Antarctic Peninsula and within East Antarctica, exceed the <span class="hlt">ice</span> dynamic mass loss from West Antarctica. The result exacerbates the difficulty of explaining twentieth century sea-level rise.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170002775&hterms=inversion&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dinversion','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170002775&hterms=inversion&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dinversion"><span>Spatial and Temporal Antarctic <span class="hlt">Ice</span> Sheet Mass <span class="hlt">Trends</span>, Glacio-Isostatic Adjustment, and Surface Processes from a Joint Inversion of Satellite Altimeter, Gravity, and GPS Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Martin-Espanol, Alba; Zammit-Mangion, Andrew; Clarke, Peter J.; Flament, Thomas; Helm, Veit; King, Matt A.; Luthcke, Scott B.; Petrie, Elizabeth; Remy, Frederique; Schon, Nana; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20170002775'); toggleEditAbsImage('author_20170002775_show'); toggleEditAbsImage('author_20170002775_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20170002775_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20170002775_hide"></p> <p>2016-01-01</p> <p>We present spatiotemporal mass balance <span class="hlt">trends</span> for the Antarctic <span class="hlt">Ice</span> Sheet from a statistical inversion of satellite altimetry, gravimetry, and elastic-corrected GPS data for the period 2003-2013. Our method simultaneously determines annual <span class="hlt">trends</span> in <span class="hlt">ice</span> dynamics, surface mass balance anomalies, and a time-invariant solution for glacio-isostatic adjustment while remaining largely independent of forward models. We establish that over the period 2003-2013, Antarctica has been losing mass at a rateof -84 +/- 22 Gt per yr, with a sustained negative mean <span class="hlt">trend</span> of dynamic imbalance of -111 +/- 13 Gt per yr. West Antarctica is the largest contributor with -112 +/- 10 Gt per yr, mainly triggered by high thinning rates of glaciers draining into the Amundsen Sea Embayment. The Antarctic Peninsula has experienced a dramatic increase in mass loss in the last decade, with a mean rate of -28 +/- 7 Gt per yr and significantly higher values for the most recent years following the destabilization of the Southern Antarctic Peninsula around 2010. The total mass loss is partly compensated by a significant mass gain of 56 +/- 18 Gt per yr in East Antarctica due to a positive <span class="hlt">trend</span> of surface mass balance anomalies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29507286','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29507286"><span>Sea <span class="hlt">ice</span> dynamics across the Mid-Pleistocene transition in the Bering Sea.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Detlef, H; Belt, S T; Sosdian, S M; Smik, L; Lear, C H; Hall, I R; Cabedo-Sanz, P; Husum, K; Kender, S</p> <p>2018-03-05</p> <p>Sea <span class="hlt">ice</span> and associated feedback mechanisms play an important role for both long- and short-term climate change. Our ability to predict future sea <span class="hlt">ice</span> <span class="hlt">extent</span>, however, hinges on a greater understanding of past sea <span class="hlt">ice</span> dynamics. Here we investigate sea <span class="hlt">ice</span> changes in the eastern Bering Sea prior to, across, and after the Mid-Pleistocene transition (MPT). The sea <span class="hlt">ice</span> record, based on the Arctic sea <span class="hlt">ice</span> biomarker IP 25 and related open water proxies from the International Ocean Discovery Program Site U1343, shows a substantial increase in sea <span class="hlt">ice</span> <span class="hlt">extent</span> across the MPT. The occurrence of late-glacial/deglacial sea <span class="hlt">ice</span> maxima are consistent with sea <span class="hlt">ice</span>/land <span class="hlt">ice</span> hysteresis and land-glacier retreat via the temperature-precipitation feedback. We also identify interactions of sea <span class="hlt">ice</span> with phytoplankton growth and ocean circulation patterns, which have important implications for glacial North Pacific Intermediate Water formation and potentially North Pacific abyssal carbon storage.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004JMS....50..113B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004JMS....50..113B"><span>Effects of lead structure in Bering Sea pack <span class="hlt">ice</span> on the flight costs of wintering spectacled eiders</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bump, Joseph K.; Lovvorn, James R.</p> <p>2004-10-01</p> <p>In polar regions, sea <span class="hlt">ice</span> is critical habitat for many marine birds and mammals. The quality of pack <span class="hlt">ice</span> habitat depends on the duration and spacing of leads (openings in the <span class="hlt">ice</span>), which determine access to water and air for diving endotherms, and how often and how far they must move as leads open and close. Recent warming <span class="hlt">trends</span> have caused major changes in the <span class="hlt">extent</span> and nature of sea <span class="hlt">ice</span> at large scales used in climate models. However, no studies have analyzed lead structure in terms of habitat for <span class="hlt">ice</span>-dependent endotherms, or effects of climate on <span class="hlt">ice</span> habitat at scales relevant to their daily movements. Based on observations from an icebreaker and synthetic aperture radar (SAR) images, we developed methods to describe the dynamics and thermodynamics of lead structure relative to use by spectacled eiders ( Somateria fischeri) wintering in pack <span class="hlt">ice</span> of the Bering Sea. By correlating lead structure with weather variables, we then used these methods to estimate changes in lead dynamics from 1945 to 2002, and effects of such changes on flight costs of the eiders. For 1991-1992, when images were available about every 3 days throughout winter, SAR images were divided among five weather regimes defined by wind speed, wind direction, and air temperature. Based on 12.5-m pixels, lead shape, compass orientation, and fetch across leads did not differ among the weather regimes. However, the five regimes differed in total area of open water, leads per unit area, and distance between leads. Lead duration was modeled based on air temperature, wind, and fetch. Estimates of mean daily flight time for eiders, based on lead duration and distance between neighboring leads, differed among regimes by 0 to 15 min. Resulting flight costs varied from 0 to 158 kJ day -1, or from 0% to 11% of estimated field metabolic rate. Over 57 winters (1945-2002), variation among years in mean daily flight time was most influenced by the north-south wind component, which determined pack divergence</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140013007','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140013007"><span>Arctic Sea <span class="hlt">Ice</span> in Transformation: A Review of Recent Observed Changes and Impacts on Biology and Human Activity</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Meier, Walter N.; Hovelsrud, Greta K.; van Oort, Bob E. H.; Key, Jeffrey R.; Kovacs, Kit M.; Michel, Christine; Haas, Christian; Granskog, Mats A.; Gerland, Sebastian; Perovich, Donald K.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20140013007'); toggleEditAbsImage('author_20140013007_show'); toggleEditAbsImage('author_20140013007_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20140013007_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20140013007_hide"></p> <p>2014-01-01</p> <p>Sea <span class="hlt">ice</span> in the Arctic is one of the most rapidly changing components of the global climate system. Over the past few decades, summer areal <span class="hlt">extent</span> has declined over 30, and all months show statistically significant declining <span class="hlt">trends</span>. New satellite missions and techniques have greatly expanded information on sea <span class="hlt">ice</span> thickness, but many uncertainties remain in the satellite data and long-term records are sparse. However, thickness observations and other satellite-derived data indicate a 40 decline in thickness, due in large part to the loss of thicker, older <span class="hlt">ice</span> cover. The changes in sea <span class="hlt">ice</span> are happening faster than models have projected. With continued increasing temperatures, summer <span class="hlt">ice</span>-free conditions are likely sometime in the coming decades, though there are substantial uncertainties in the exact timing and high interannual variability will remain as sea <span class="hlt">ice</span> decreases. The changes in Arctic sea <span class="hlt">ice</span> are already having an impact on flora and fauna in the Arctic. Some species will face increasing challenges in the future, while new habitat will open up for other species. The changes are also affecting peoples living and working in the Arctic. Native communities are facing challenges to their traditional ways of life, while new opportunities open for shipping, fishing, and natural resource extraction.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1813180M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1813180M"><span>Constraining East Antarctic mass <span class="hlt">trends</span> using a Bayesian inference approach</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Martin-Español, Alba; Bamber, Jonathan L.</p> <p>2016-04-01</p> <p>East Antarctica is an order of magnitude larger than its western neighbour and the Greenland <span class="hlt">ice</span> sheet. It has the greatest potential to contribute to sea level rise of any source, including non-glacial contributors. It is, however, the most challenging <span class="hlt">ice</span> mass to constrain because of a range of factors including the relative paucity of in-situ observations and the poor signal to noise ratio of Earth Observation data such as satellite altimetry and gravimetry. A recent study using satellite radar and laser altimetry (Zwally et al. 2015) concluded that the East Antarctic <span class="hlt">Ice</span> Sheet (EAIS) had been accumulating mass at a rate of 136±28 Gt/yr for the period 2003-08. Here, we use a Bayesian hierarchical model, which has been tested on, and applied to, the whole of Antarctica, to investigate the impact of different assumptions regarding the origin of elevation changes of the EAIS. We combined GRACE, satellite laser and radar altimeter data and GPS measurements to solve simultaneously for surface processes (primarily surface mass balance, SMB), <span class="hlt">ice</span> dynamics and glacio-isostatic adjustment over the period 2003-13. The hierarchical model partitions mass <span class="hlt">trends</span> between SMB and <span class="hlt">ice</span> dynamics based on physical principles and measures of statistical likelihood. Without imposing the division between these processes, the model apportions about a third of the mass <span class="hlt">trend</span> to <span class="hlt">ice</span> dynamics, +18 Gt/yr, and two thirds, +39 Gt/yr, to SMB. The total mass <span class="hlt">trend</span> for that period for the EAIS was 57±20 Gt/yr. Over the period 2003-08, we obtain an <span class="hlt">ice</span> dynamic <span class="hlt">trend</span> of 12 Gt/yr and a SMB <span class="hlt">trend</span> of 15 Gt/yr, with a total mass <span class="hlt">trend</span> of 27 Gt/yr. We then imposed the condition that the surface mass balance is tightly constrained by the regional climate model RACMO2.3 and allowed height changes due to <span class="hlt">ice</span> dynamics to occur in areas of low surface velocities (<10 m/yr) , such as those in the interior of East Antarctica (a similar condition as used in Zwally 2015). The model must find a solution that</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_15 --> <div id="page_16" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="301"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040171197','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040171197"><span>MODIS Snow and Sea <span class="hlt">Ice</span> Products</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.</p> <p>2004-01-01</p> <p>In this chapter, we describe the suite of Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua snow and sea <span class="hlt">ice</span> products. Global, daily products, developed at Goddard Space Flight Center, are archived and distributed through the National Snow and <span class="hlt">Ice</span> Data Center at various resolutions and on different grids useful for different communities Snow products include binary snow cover, snow albedo, and in the near future, fraction of snow in a 5OO-m pixel. Sea <span class="hlt">ice</span> products include <span class="hlt">ice</span> <span class="hlt">extent</span> determined with two different algorithms, and sea <span class="hlt">ice</span> surface temperature. The algorithms used to develop these products are described. Both the snow and sea <span class="hlt">ice</span> products, available since February 24,2000, are useful for modelers. Validation of the products is also discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C21B0326B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C21B0326B"><span>Antarctic <span class="hlt">Ice</span> Mass Balance from GRACE</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Boening, C.; Firing, Y. L.; Wiese, D. N.; Watkins, M. M.; Schlegel, N.; Larour, E. Y.</p> <p>2014-12-01</p> <p>The Antarctic <span class="hlt">ice</span> mass balance and rates of change of <span class="hlt">ice</span> mass over the past decade are analyzed based on observations from the Gravity Recovery and Climate Experiment (GRACE) satellites, in the form of JPL RL05M mascon solutions. Surface mass balance (SMB) fluxes from ERA-Interim and other atmospheric reanalyses successfully account for the seasonal GRACE-measured mass variability, and explain 70-80% of the continent-wide mass variance at interannual time scales. <span class="hlt">Trends</span> in the residual (GRACE mass - SMB accumulation) mass time series in different Antarctic drainage basins are consistent with time-mean <span class="hlt">ice</span> discharge rates based on radar-derived <span class="hlt">ice</span> velocities and thicknesses. GRACE also resolves accelerations in regional <span class="hlt">ice</span> mass change rates, including increasing rates of mass gain in East Antarctica and accelerating <span class="hlt">ice</span> mass loss in West Antarctica. The observed East Antarctic mass gain is only partially explained by anomalously large SMB events in the second half of the record, potentially implying that <span class="hlt">ice</span> discharge rates are also decreasing in this region. Most of the increasing mass loss rate in West Antarctica, meanwhile, is explained by decreasing SMB (principally precipitation) over this time period, part of the characteristic decadal variability in regional SMB. The residual acceleration of 2+/-1 Gt/yr, which is concentrated in the Amundsen Sea Embayment (ASE) basins, represents the contribution from increasing <span class="hlt">ice</span> discharge rates. An <span class="hlt">Ice</span> Sheet System Model (ISSM) run with constant ocean forcing and stationary grounding lines both underpredicts the largest <span class="hlt">trends</span> in the ASE and produces negligible acceleration or interannual variability in discharge, highlighting the potential importance of ocean forcing for setting <span class="hlt">ice</span> discharge rates at interannual to decadal time scales.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA601202','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA601202"><span>Seasonal <span class="hlt">Ice</span> Zone Reconnaissance Surveys Coordination</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2013-09-30</p> <p>of SIZRS are covered in separate reports. Our long-term goal is to track and understand the interplay among the <span class="hlt">ice</span>, atmosphere, and ocean...OMB control number. 1. REPORT DATE 30 SEP 2013 2. REPORT TYPE 3. DATES COVERED 00-00-2013 to 00-00-2013 4. TITLE AND SUBTITLE Seasonal <span class="hlt">Ice</span> Zone...sensing resources include MODIS visible and IR imagery, NSIDC <span class="hlt">ice</span> <span class="hlt">extent</span> charts based on a composite of passive microwave products (http://nsidc.org</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160012483','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160012483"><span>Modeling the Thickness of Perennial <span class="hlt">Ice</span> Covers on Stratified Lakes of the Taylor Valley, Antarctica</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Obryk, M. K.; Doran, P. T.; Hicks, J. A.; McKay, C. P.; Priscu, J. C.</p> <p>2016-01-01</p> <p>A one-dimensional <span class="hlt">ice</span> cover model was developed to predict and constrain drivers of long term <span class="hlt">ice</span> thickness <span class="hlt">trends</span> in chemically stratified lakes of Taylor Valley, Antarctica. The model is driven by surface radiative heat fluxes and heat fluxes from the underlying water column. The model successfully reproduced 16 years (between 1996 and 2012) of <span class="hlt">ice</span> thickness changes for west lobe of Lake Bonney (average <span class="hlt">ice</span> thickness = 3.53 m; RMSE = 0.09 m, n = 118) and Lake Fryxell (average <span class="hlt">ice</span> thickness = 4.22 m; RMSE = 0.21 m, n = 128). Long-term <span class="hlt">ice</span> thickness <span class="hlt">trends</span> require coupling with the thermal structure of the water column. The heat stored within the temperature maximum of lakes exceeding a liquid water column depth of 20 m can either impede or facilitate <span class="hlt">ice</span> thickness change depending on the predominant climatic <span class="hlt">trend</span> (temperature cooling or warming). As such, shallow (< 20 m deep water columns) perennially <span class="hlt">ice</span>-covered lakes without deep temperature maxima are more sensitive indicators of climate change. The long-term <span class="hlt">ice</span> thickness <span class="hlt">trends</span> are a result of surface energy flux and heat flux from the deep temperature maximum in the water column, the latter of which results from absorbed solar radiation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C33B0793I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C33B0793I"><span>Spatiotemporal Patterns of <span class="hlt">Ice</span> Mass Variations and the Local Climatic Factors in the Riparian Zone of Central Valley, California</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Inamdar, P.; Ambinakudige, S.</p> <p>2016-12-01</p> <p>Californian icefields are natural basins of fresh water. They provide irrigation water to the farms in the central valley. We analyzed the <span class="hlt">ice</span> mass loss rates, air temperature and land surface temperature (LST) in Sacramento and San Joaquin basins in California. The digital elevation models from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used to calculate <span class="hlt">ice</span> mass loss rate between the years 2002 and 2015. Additionally, Landsat TIR data were used to extract the land surface temperature. Data from local weather stations were analyzed to understand the spatiotemporal <span class="hlt">trends</span> in air temperature. The results showed an overall mass recession of -0.8 ± 0.7 m w.e.a-1. We also noticed an about 60% loss in areal <span class="hlt">extent</span> of the glaciers in the study basins between 2000 and 2015. Local climatic factors, along with the global climate patterns might have influenced the negative <span class="hlt">trends</span> in the <span class="hlt">ice</span> mass loss. Overall, there was an increase in the air temperature by 0.07± 0.02 °C in the central valley between 2000 and 2015. Furthermore, LST increased by 0.34 ± 0.4 °C and 0.55± 0.1 °C in the Sacramento and San Joaquin basins. Our preliminary results show the decrease in area and mass of <span class="hlt">ice</span> mass in the basins, and changing agricultural practices in the valley.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19930082126','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19930082126"><span>The Calculation of the Heat Required for Wing Thermal <span class="hlt">Ice</span> Prevention in Specified <span class="hlt">Icing</span> Conditions</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Bergrun, Norman R.; Jukoff, David; Schlaff, Bernard A.; Neel, Carr B., Jr.</p> <p>1947-01-01</p> <p>Flight tests were made in natural <span class="hlt">icing</span> conditions with two 8-ft-chord heated airfoils of different sections. Measurements of meteorological variables conducive to <span class="hlt">ice</span> formation were made simultaneously with the procurement of airfoil thermal data. The <span class="hlt">extent</span> of knowledge on the meteorology of <span class="hlt">icing</span>, the impingement of water drops on airfoil surfaces, and the processes of heat transfer and evaporation from a wetted airfoil surface have been increased to a point where the design of heated wings on a fundamental, wet-air basis now can be undertaken with reasonable certainty.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.6054P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.6054P"><span>The Navy's First Seasonal <span class="hlt">Ice</span> Forecasts using the Navy's Arctic Cap Nowcast/Forecast System</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Preller, Ruth</p> <p>2013-04-01</p> <p>As conditions in the Arctic continue to change, the Naval Research Laboratory (NRL) has developed an interest in longer-term seasonal <span class="hlt">ice</span> <span class="hlt">extent</span> forecasts. The Arctic Cap Nowcast/Forecast System (ACNFS), developed by the Oceanography Division of NRL, was run in forward model mode, without assimilation, to estimate the minimum sea <span class="hlt">ice</span> <span class="hlt">extent</span> for September 2012. The model was initialized with varying assimilative ACNFS analysis fields (June 1, July 1, August 1 and September 1, 2012) and run forward for nine simulations using the archived Navy Operational Global Atmospheric Prediction System (NOGAPS) atmospheric forcing fields from 2003-2011. The mean <span class="hlt">ice</span> <span class="hlt">extent</span> in September, averaged across all ensemble members was the projected summer <span class="hlt">ice</span> <span class="hlt">extent</span>. These results were submitted to the Study of Environmental Arctic Change (SEARCH) Sea <span class="hlt">Ice</span> Outlook project (http://www.arcus.org/search/seaiceoutlook). The ACNFS is a ~3.5 km coupled <span class="hlt">ice</span>-ocean model that produces 5 day forecasts of the Arctic sea <span class="hlt">ice</span> state in all <span class="hlt">ice</span> covered areas in the northern hemisphere (poleward of 40° N). The ocean component is the HYbrid Coordinate Ocean Model (HYCOM) and is coupled to the Los Alamos National Laboratory Community <span class="hlt">Ice</span> CodE (CICE) via the Earth System Modeling Framework (ESMF). The ocean and <span class="hlt">ice</span> models are run in an assimilative cycle with the Navy's Coupled Ocean Data Assimilation (NCODA) system. Currently the ACNFS is being transitioned to operations at the Naval Oceanographic Office.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMOS14A..04Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMOS14A..04Z"><span>Local Effects of <span class="hlt">Ice</span> Floes on Skin Sea Surface Temperature in the Marginal <span class="hlt">Ice</span> Zone from UAVs</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zappa, C. J.; Brown, S.; Emery, W. J.; Adler, J.; Wick, G. A.; Steele, M.; Palo, S. E.; Walker, G.; Maslanik, J. A.</p> <p>2013-12-01</p> <p>Recent years have seen extreme changes in the Arctic. Particularly striking are changes within the Pacific sector of the Arctic Ocean, and especially in the seas north of the Alaskan coast. These areas have experienced record warming, reduced sea <span class="hlt">ice</span> <span class="hlt">extent</span>, and loss of <span class="hlt">ice</span> in areas that had been <span class="hlt">ice</span>-covered throughout human memory. Even the oldest and thickest <span class="hlt">ice</span> types have failed to survive through the summer melt period in areas such as the Beaufort Sea and Canada Basin, and fundamental changes in ocean conditions such as earlier phytoplankton blooms may be underway. Marginal <span class="hlt">ice</span> zones (MIZ), or areas where the "<span class="hlt">ice</span>-albedo feedback" driven by solar warming is highest and <span class="hlt">ice</span> melt is extensive, may provide insights into the <span class="hlt">extent</span> of these changes. Airborne remote sensing, in particular InfraRed (IR), offers a unique opportunity to observe physical processes at sea-<span class="hlt">ice</span> margins. It permits monitoring the <span class="hlt">ice</span> <span class="hlt">extent</span> and coverage, as well as the <span class="hlt">ice</span> and ocean temperature variability. It can also be used for derivation of surface flow field allowing investigation of turbulence and mixing at the <span class="hlt">ice</span>-ocean interface. Here, we present measurements of visible and IR imagery of melting <span class="hlt">ice</span> floes in the marginal <span class="hlt">ice</span> zone north of Oliktok Point AK in the Beaufort Sea made during the Marginal <span class="hlt">Ice</span> Zone Ocean and <span class="hlt">Ice</span> Observations and Processes EXperiment (MIZOPEX) in July-August 2013. The visible and IR imagery were taken from the unmanned airborne vehicle (UAV) ScanEagle. The visible imagery clearly defines the scale of the <span class="hlt">ice</span> floes. The IR imagery show distinct cooling of the skin sea surface temperature (SST) as well as a intricate circulation and mixing pattern that depends on the surface current, wind speed, and near-surface vertical temperature/salinity structure. Individual <span class="hlt">ice</span> floes develop turbulent wakes as they drift and cause transient mixing of an influx of colder surface (fresh) melt water. The upstream side of the <span class="hlt">ice</span> floe shows the coldest skin SST, and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20150021521&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dsea','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20150021521&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dsea"><span>An Assessment of Southern Ocean Water Masses and Sea <span class="hlt">Ice</span> During 1988-2007 in a Suite of Interannual CORE-II Simulations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Downes, Stephanie M.; Farneti, Riccardo; Uotila, Petteri; Griffies, Stephen M.; Marsland, Simon J.; Bailey, David; Behrens, Erik; Bentsen, Mats; Bi, Daohua; Biastoch, Arne; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20150021521'); toggleEditAbsImage('author_20150021521_show'); toggleEditAbsImage('author_20150021521_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20150021521_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20150021521_hide"></p> <p>2015-01-01</p> <p>We characterise the representation of the Southern Ocean water mass structure and sea <span class="hlt">ice</span> within a suite of 15 global ocean-<span class="hlt">ice</span> models run with the Coordinated Ocean-<span class="hlt">ice</span> Reference Experiment Phase II (CORE-II) protocol. The main focus is the representation of the present (1988-2007) mode and intermediate waters, thus framing an analysis of winter and summer mixed layer depths; temperature, salinity, and potential vorticity structure; and temporal variability of sea <span class="hlt">ice</span> distributions. We also consider the interannual variability over the same 20 year period. Comparisons are made between models as well as to observation-based analyses where available. The CORE-II models exhibit several biases relative to Southern Ocean observations, including an underestimation of the model mean mixed layer depths of mode and intermediate water masses in March (associated with greater ocean surface heat gain), and an overestimation in September (associated with greater high latitude ocean heat loss and a more northward winter sea-<span class="hlt">ice</span> <span class="hlt">extent</span>). In addition, the models have cold and fresh/warm and salty water column biases centred near 50 deg S. Over the 1988-2007 period, the CORE-II models consistently simulate spatially variable <span class="hlt">trends</span> in sea-<span class="hlt">ice</span> concentration, surface freshwater fluxes, mixed layer depths, and 200-700 m ocean heat content. In particular, sea-<span class="hlt">ice</span> coverage around most of the Antarctic continental shelf is reduced, leading to a cooling and freshening of the near surface waters. The shoaling of the mixed layer is associated with increased surface buoyancy gain, except in the Pacific where sea <span class="hlt">ice</span> is also influential. The models are in disagreement, despite the common CORE-II atmospheric state, in their spatial pattern of the 20-year <span class="hlt">trends</span> in the mixed layer depth and sea-<span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C43B0750J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C43B0750J"><span>Landfast Sea <span class="hlt">Ice</span> Breakouts: Stabilizing <span class="hlt">Ice</span> Features, Oceanic and Atmospheric Forcing at Barrow, Alaska</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jones, J.; Eicken, H.; Mahoney, A. R.; MV, R.; Kambhamettu, C.; Fukamachi, Y.; Ohshima, K. I.; George, C.</p> <p>2016-12-01</p> <p>Landfast sea <span class="hlt">ice</span> is an important seasonal feature along most Arctic coastlines, such as that of the Chukchi Sea near Barrow, Alaska. Its stability throughout the <span class="hlt">ice</span> season is determined by many factors but grounded pressure ridges are the primary stabilizing component. Landfast <span class="hlt">ice</span> breakouts occur when these grounded ridges fail or unground, and previously stationary <span class="hlt">ice</span> detaches from the coast and drifts away. Using ground-based radar imagery from a coastal <span class="hlt">ice</span> and ocean observatory at Barrow, we have developed a method to estimate the <span class="hlt">extent</span> of grounded ridges by tracking <span class="hlt">ice</span> motion and deformation over the course of winter and have derived <span class="hlt">ice</span> keel depth and potential for grounding from cumulative convergent <span class="hlt">ice</span> motion. Estimates of landfast <span class="hlt">ice</span> grounding strength have been compared to the atmospheric and oceanic stresses acting on the landfast <span class="hlt">ice</span> before and during breakout events to determine prevailing causes for the failure of stabilizing features. Applying this approach to two case studies in 2008 and 2010, we conclude that a combination of atmospheric and oceanic stresses may have caused the breakouts analyzed in this study, with the latter as the dominant force. Preconditioning (as weakening) of grounded ridges by sea level variations may facilitate failure of the <span class="hlt">ice</span> sheet leading to breakout events.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016CSR...126...50J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016CSR...126...50J"><span>Landfast sea <span class="hlt">ice</span> breakouts: Stabilizing <span class="hlt">ice</span> features, oceanic and atmospheric forcing at Barrow, Alaska</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jones, Joshua; Eicken, Hajo; Mahoney, Andrew; MV, Rohith; Kambhamettu, Chandra; Fukamachi, Yasushi; Ohshima, Kay I.; George, J. Craig</p> <p>2016-09-01</p> <p>Landfast sea <span class="hlt">ice</span> is an important seasonal feature along most Arctic coastlines, such as that of the Chukchi Sea near Barrow, Alaska. Its stability throughout the <span class="hlt">ice</span> season is determined by many factors but grounded pressure ridges are the primary stabilizing component. Landfast <span class="hlt">ice</span> breakouts occur when these grounded ridges fail or unground, and previously stationary <span class="hlt">ice</span> detaches from the coast and drifts away. Using ground-based radar imagery from a coastal <span class="hlt">ice</span> and ocean observatory at Barrow, we have developed a method to estimate the <span class="hlt">extent</span> of grounded ridges by tracking <span class="hlt">ice</span> motion and deformation over the course of winter and have derived <span class="hlt">ice</span> keel depth and potential for grounding from cumulative convergent <span class="hlt">ice</span> motion. Estimates of landfast <span class="hlt">ice</span> grounding strength have been compared to the atmospheric and oceanic stresses acting on the landfast <span class="hlt">ice</span> before and during breakout events to determine prevailing causes for the failure of stabilizing features. Applying this approach to two case studies in 2008 and 2010, we conclude that a combination of atmospheric and oceanic stresses may have caused the breakouts analyzed in this study, with the latter as the dominant force. Preconditioning (as weakening) of grounded ridges by sea level variations may facilitate failure of the <span class="hlt">ice</span> sheet leading to breakout events.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20060044030&hterms=SLP&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DSLP','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20060044030&hterms=SLP&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DSLP"><span>Ross sea <span class="hlt">ice</span> motion, area flux, and deformation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>kwok, Ron</p> <p>2005-01-01</p> <p>The sea <span class="hlt">ice</span> motion, area export, and deformation of the Ross Sea <span class="hlt">ice</span> cover are examined with satellite passive microwave and RADARSAT observations. The record of high-resolution synthetic aperture radar (SAR) data, from 1998 and 2000, allows the estimation of the variability of <span class="hlt">ice</span> deformation at the small scale (10 km) and to assess the quality of the longer record of passive microwave <span class="hlt">ice</span> motion. Daily and subdaily deformation fields and RADARSAT imagery highlight the variability of motion and deformation in the Ross Sea. With the passive microwave <span class="hlt">ice</span> motion, the area export at a flux gate positioned between Cape Adare and Land Bay is estimated. Between 1992 and 2003, a positive <span class="hlt">trend</span> can be seen in the winter (March-November) <span class="hlt">ice</span> area flux that has a mean of 990 x 103 km2 and ranges from a low of 600 x 103 km2 in 1992 to a peak of 1600 x 103 km2 in 2001. In the mean, the southern Ross Sea produces almost twice its own area of sea <span class="hlt">ice</span> during the winter. Cross-gate sea level pressure (SLP) gradients explain 60% of the variance in the <span class="hlt">ice</span> area flux. A positive <span class="hlt">trend</span> in this gradient, from reanalysis products, suggests a 'spinup' of the Ross Sea Gyre over the past 12 yr. In both the NCEP-NCAR and ERA-40 surface pressure fields, longer-term <span class="hlt">trends</span> in this gradient and mean SLP between 1979 and 2002 are explored along with positive anomalies in the monthly cross-gate SLP gradient associated with the positive phase of the Southern Hemisphere annular mode and the extrapolar Southern Oscillation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C14A..01W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C14A..01W"><span>Oceans Melting Greenland (OMG): 2017 Observations and the First Look at Yearly Ocean/<span class="hlt">Ice</span> Changes</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Willis, J. K.; Rignot, E. J.; Fenty, I. G.; Khazendar, A.; Moller, D.; Tinto, K. J.; Morison, J.; Schodlok, M.; Thompson, A. F.; Fukumori, I.; Holland, D.; Forsberg, R.; Jakobsson, M.; Dinardo, S. J.</p> <p>2017-12-01</p> <p>Oceans Melting Greenland (OMG) is an airborne NASA Mission to investigate the role of the oceans in <span class="hlt">ice</span> loss around the margins of the Greenland <span class="hlt">Ice</span> Sheet. A five-year campaign, OMG will directly measure ocean warming and glacier retreat around all of Greenland. By relating these two, we will explore one of the most pressing open questions about how climate change drives sea level rise: How quickly are the warming oceans melting the Greenland <span class="hlt">Ice</span> Sheet from the edges? This year, OMG collected its second set of both elevation maps of marine terminating glaciers and ocean temperature and salinity profiles around all of Greenland. This give us our first look at year-to-year changes in both <span class="hlt">ice</span> volume at the margins, as well as the volume and <span class="hlt">extent</span> of warm, salty Atlantic water present on the continental shelf. In addition, we will compare recent data in east Greenland waters with historical ocean observations that suggest a long-term warming <span class="hlt">trend</span> there. Finally, we will briefly review the multi-beam sonar and airborne gravity campaigns—both of which were completed last year—and the dramatic improvement they had on bathymetry maps over the continental shelf around Greenland.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014NatGe...7..497B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014NatGe...7..497B"><span>Deformation, warming and softening of Greenland’s <span class="hlt">ice</span> by refreezing meltwater</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bell, Robin E.; Tinto, Kirsteen; Das, Indrani; Wolovick, Michael; Chu, Winnie; Creyts, Timothy T.; Frearson, Nicholas; Abdi, Abdulhakim; Paden, John D.</p> <p>2014-07-01</p> <p>Meltwater beneath the large <span class="hlt">ice</span> sheets can influence <span class="hlt">ice</span> flow by lubrication at the base or by softening when meltwater refreezes to form relatively warm <span class="hlt">ice</span>. Refreezing has produced large basal <span class="hlt">ice</span> units in East Antarctica. Bubble-free basal <span class="hlt">ice</span> units also outcrop at the edge of the Greenland <span class="hlt">ice</span> sheet, but the <span class="hlt">extent</span> of refreezing and its influence on Greenland’s <span class="hlt">ice</span> flow dynamics are unknown. Here we demonstrate that refreezing of meltwater produces distinct basal <span class="hlt">ice</span> units throughout northern Greenland with thicknesses of up to 1,100 m. We compare airborne gravity data with modelled gravity anomalies to show that these basal units are <span class="hlt">ice</span>. Using radar data we determine the <span class="hlt">extent</span> of the units, which significantly disrupt the overlying <span class="hlt">ice</span> sheet stratigraphy. The units consist of refrozen basal water commonly surrounded by heavily deformed meteoric <span class="hlt">ice</span> derived from snowfall. We map these units along the <span class="hlt">ice</span> sheet margins where surface melt is the largest source of water, as well as in the interior where basal melting is the only source of water. Beneath Petermann Glacier, basal units coincide with the onset of fast flow and channels in the floating <span class="hlt">ice</span> tongue. We suggest that refreezing of meltwater and the resulting deformation of the surrounding basal <span class="hlt">ice</span> warms the Greenland <span class="hlt">ice</span> sheet, modifying the temperature structure of the <span class="hlt">ice</span> column and influencing <span class="hlt">ice</span> flow and grounding line melting.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1918039N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1918039N"><span>ICESat-2, its retrievals of <span class="hlt">ice</span> sheet elevation change and sea <span class="hlt">ice</span> freeboard, and potential synergies with CryoSat-2</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Neumann, Thomas; Markus, Thorsten; Smith, Benjamin; Kwok, Ron</p> <p>2017-04-01</p> <p>Understanding the causes and magnitudes of changes in the cryosphere remains a priority for Earth science research. Over the past decade, NASA's and ESA's Earth-observing satellites have documented a decrease in both the areal <span class="hlt">extent</span> and thickness of Arctic sea <span class="hlt">ice</span>, and an ongoing loss of grounded <span class="hlt">ice</span> from the Greenland and Antarctic <span class="hlt">ice</span> sheets. Understanding the pace and mechanisms of these changes requires long-term observations of <span class="hlt">ice</span>-sheet mass, sea-<span class="hlt">ice</span> thickness, and sea-<span class="hlt">ice</span> <span class="hlt">extent</span>. NASA's ICESat-2 mission is the next-generation space-borne laser altimeter mission and will use three pairs of beams, each pair separated by about 3 km across-track with a pair spacing of 90 m. The spot size is 17 m with an along-track sampling interval of 0.7 m. This measurement concept is a result of the lessons learned from the original ICESat mission. The multi-beam approach is critical for removing the effects of <span class="hlt">ice</span> sheet surface slope from the elevation change measurements of most interest. For sea <span class="hlt">ice</span>, the dense spatial sampling (eliminating along-track gaps) and the small footprint size are especially useful for sea surface height measurements in the, often narrow, leads needed for sea <span class="hlt">ice</span> freeboard and <span class="hlt">ice</span> thickness retrievals. Currently, algorithms are being developed to calculate <span class="hlt">ice</span> sheet elevation change and sea <span class="hlt">ice</span> freeboard from ICESat-2 data. The orbits of ICESat-2 and Cryosat-2 both converge at 88 degrees of latitude, though the orbit altitude differences result in different ground track patterns between the two missions. This presentation will present an overview of algorithm approaches and how ICESat-2 and Cryosat-2 data may augment each other.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C42B..02D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C42B..02D"><span>Will sea <span class="hlt">ice</span> thickness initialisation improve Arctic seasonal-to-interannual forecast skill?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Day, J. J.; Hawkins, E.; Tietsche, S.</p> <p>2014-12-01</p> <p>A number of recent studies have suggested that Arctic sea <span class="hlt">ice</span> thickness is an important predictor of Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span>. However, coupled forecast systems do not currently use sea <span class="hlt">ice</span> thickness observations in their initialization and are therefore missing a potentially important source of additional skill. A set of ensemble potential predictability experiments, with a global climate model, initialized with and without knowledge of the sea <span class="hlt">ice</span> thickness initial state, have been run to investigate this. These experiments show that accurate knowledge of the sea <span class="hlt">ice</span> thickness field is crucially important for sea <span class="hlt">ice</span> concentration and <span class="hlt">extent</span> forecasts up to eight months ahead. Perturbing sea <span class="hlt">ice</span> thickness also has a significant impact on the forecast error in the 2m temperature and surface pressure fields a few months ahead. These results show that advancing capabilities to observe and assimilate sea <span class="hlt">ice</span> thickness into coupled forecast systems could significantly increase skill.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000751.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000751.html"><span>Sea <span class="hlt">Ice</span> off the Princess Astrid Coast</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2015-04-08</p> <p>On April 5, 2015, the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite acquired this natural-color image of sea <span class="hlt">ice</span> off the coast of East Antarctica’s Princess Astrid Coast. White areas close to the continent are sea <span class="hlt">ice</span>, while white areas in the northeast corner of the image are clouds. One way to better distinguish <span class="hlt">ice</span> from clouds is with false-color imagery. In the false-color view of the scene here, <span class="hlt">ice</span> is blue and clouds are white. The image was acquired after Antarctic sea <span class="hlt">ice</span> had passed its annual minimum <span class="hlt">extent</span> (reached on February 20, 2015), and had resumed expansion toward its maximum <span class="hlt">extent</span> (usually reached in September). Credit: NASA image by Jeff Schmaltz, LANCE/EOSDIS Rapid Response. Caption by Kathryn Hansen via NASA's Earth Observatory Read more: www.nasa.gov/content/sea-<span class="hlt">ice</span>-off-east-antarcticas-princes... NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016TCry...10.1463H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016TCry...10.1463H"><span>Landfast <span class="hlt">ice</span> thickness in the Canadian Arctic Archipelago from observations and models</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Howell, Stephen E. L.; Laliberté, Frédéric; Kwok, Ron; Derksen, Chris; King, Joshua</p> <p>2016-07-01</p> <p>Observed and modelled landfast <span class="hlt">ice</span> thickness variability and <span class="hlt">trends</span> spanning more than 5 decades within the Canadian Arctic Archipelago (CAA) are summarized. The observed sites (Cambridge Bay, Resolute, Eureka and Alert) represent some of the Arctic's longest records of landfast <span class="hlt">ice</span> thickness. Observed end-of-winter (maximum) <span class="hlt">trends</span> of landfast <span class="hlt">ice</span> thickness (1957-2014) were statistically significant at Cambridge Bay (-4.31 ± 1.4 cm decade-1), Eureka (-4.65 ± 1.7 cm decade-1) and Alert (-4.44 ± 1.6 cm -1) but not at Resolute. Over the 50+-year record, the <span class="hlt">ice</span> thinned by ˜ 0.24-0.26 m at Cambridge Bay, Eureka and Alert with essentially negligible change at Resolute. Although statistically significant warming in spring and fall was present at all sites, only low correlations between temperature and maximum <span class="hlt">ice</span> thickness were present; snow depth was found to be more strongly associated with the negative <span class="hlt">ice</span> thickness <span class="hlt">trends</span>. Comparison with multi-model simulations from Coupled Model Intercomparison project phase 5 (CMIP5), Ocean Reanalysis Intercomparison (ORA-IP) and Pan-Arctic <span class="hlt">Ice</span>-Ocean Modeling and Assimilation System (PIOMAS) show that although a subset of current generation models have a "reasonable" climatological representation of landfast <span class="hlt">ice</span> thickness and distribution within the CAA, <span class="hlt">trends</span> are unrealistic and far exceed observations by up to 2 orders of magnitude. ORA-IP models were found to have positive correlations between temperature and <span class="hlt">ice</span> thickness over the CAA, a feature that is inconsistent with both observations and coupled models from CMIP5.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC23D1173L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC23D1173L"><span>Sparse <span class="hlt">ice</span>: Geophysical, biological and Indigenous knowledge perspectives on a habitat for <span class="hlt">ice</span>-associated fauna</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lee, O. A.; Eicken, H.; Weyapuk, W., Jr.; Adams, B.; Mohoney, A. R.</p> <p>2015-12-01</p> <p>The significance of highly dispersed, remnant Arctic sea <span class="hlt">ice</span> as a platform for marine mammals and indigenous hunters in spring and summer may have increased disproportionately with changes in the <span class="hlt">ice</span> cover. As dispersed remnant <span class="hlt">ice</span> becomes more common in the future it will be increasingly important to understand its ecological role for upper trophic levels such as marine mammals and its role for supporting primary productivity of <span class="hlt">ice</span>-associated algae. Potential sparse <span class="hlt">ice</span> habitat at sea <span class="hlt">ice</span> concentrations below 15% is difficult to detect using remote sensing data alone. A combination of high resolution satellite imagery (including Synthetic Aperture Radar), data from the Barrow sea <span class="hlt">ice</span> radar, and local observations from indigenous sea <span class="hlt">ice</span> experts was used to detect sparse sea <span class="hlt">ice</span> in the Alaska Arctic. Traditional knowledge on sea <span class="hlt">ice</span> use by marine mammals was used to delimit the scales where sparse <span class="hlt">ice</span> could still be used as habitat for seals and walrus. Potential sparse <span class="hlt">ice</span> habitat was quantified with respect to overall spatial <span class="hlt">extent</span>, size of <span class="hlt">ice</span> floes, and density of floes. Sparse <span class="hlt">ice</span> persistence offshore did not prevent the occurrence of large coastal walrus haul outs, but the lack of sparse <span class="hlt">ice</span> and early sea <span class="hlt">ice</span> retreat coincided with local observations of ringed seal pup mortality. Observations from indigenous hunters will continue to be an important source of information for validating remote sensing detections of sparse <span class="hlt">ice</span>, and improving understanding of marine mammal adaptations to sea <span class="hlt">ice</span> change.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GeoRL..45.5204H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GeoRL..45.5204H"><span>The Unprecedented 2016-2017 Arctic Sea <span class="hlt">Ice</span> Growth Season: The Crucial Role of Atmospheric Rivers and Longwave Fluxes</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hegyi, Bradley M.; Taylor, Patrick C.</p> <p>2018-05-01</p> <p>The 2016-2017 Arctic sea <span class="hlt">ice</span> growth season (October-March) exhibited one of the lowest values for end-of-season sea <span class="hlt">ice</span> volume and <span class="hlt">extent</span> of any year since 1979. An analysis of Modern-Era Retrospective Analysis for Research and Applications, Version 2 atmospheric reanalysis data and Clouds and the Earth's Radiant Energy System radiative flux data reveals that a record warm and moist Arctic atmosphere supported the reduced sea <span class="hlt">ice</span> growth. Numerous regional episodes of increased atmospheric temperature and moisture, transported from lower latitudes, increased the cumulative energy input from downwelling longwave surface fluxes. In those same episodes, the efficiency of the atmosphere cooling radiatively to space was reduced, increasing the amount of energy retained in the Arctic atmosphere and reradiated back toward the surface. Overall, the Arctic radiative cooling efficiency shows a decreasing <span class="hlt">trend</span> since 2000. The results presented highlight the increasing importance of atmospheric forcing on sea <span class="hlt">ice</span> variability demonstrating that episodic Arctic atmospheric rivers, regions of elevated poleward water vapor transport, and the subsequent surface energy budget response is a critical mechanism actively contributing to the evolution of Arctic sea <span class="hlt">ice</span>.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_16 --> <div id="page_17" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="321"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1990JGR....9513411C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1990JGR....9513411C"><span>Arctic multiyear <span class="hlt">ice</span> classification and summer <span class="hlt">ice</span> cover using passive microwave satellite data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Comiso, J. C.</p> <p>1990-08-01</p> <p>The ability to classify and monitor Arctic multiyear sea <span class="hlt">ice</span> cover using multispectral passive microwave data is studied. Sea <span class="hlt">ice</span> concentration maps during several summer minima have been analyzed to obtain estimates of <span class="hlt">ice</span> surviving the summer. The results are compared with multiyear <span class="hlt">ice</span> concentrations derived from data the following winter, using an algorithm that assumes a certain emissivity for multiyear <span class="hlt">ice</span>. The multiyear <span class="hlt">ice</span> cover inferred from the winter data is approximately 25 to 40% less than the summer <span class="hlt">ice</span> cover minimum, suggesting that even during winter when the emissivity of sea <span class="hlt">ice</span> is most stable, passive microwave data may account for only a fraction of the total multiyear <span class="hlt">ice</span> cover. The difference of about 2×106 km2 is considerably more than estimates of advection through Fram Strait during the intervening period. It appears that as in the Antarctic, some multiyear <span class="hlt">ice</span> floes in the Arctic, especially those near the summer marginal <span class="hlt">ice</span> zone, have first-year <span class="hlt">ice</span> or intermediate signatures in the subsequent winter. A likely mechanism for this is the intrusion of seawater into the snow-<span class="hlt">ice</span> interface, which often occurs near the marginal <span class="hlt">ice</span> zone or in areas where snow load is heavy. Spatial variations in melt and melt ponding effects also contribute to the complexity of the microwave emissivity of multiyear <span class="hlt">ice</span>. Hence the multiyear <span class="hlt">ice</span> data should be studied in conjunction with the previous summer <span class="hlt">ice</span> data to obtain a more complete characterization of the state of the Arctic <span class="hlt">ice</span> cover. The total <span class="hlt">extent</span> and actual areas of the summertime Arctic pack <span class="hlt">ice</span> were estimated to be 8.4×106 km2 and 6.2×106 km2, respectively, and exhibit small interannual variability during the years 1979 through 1985, suggesting a relatively stable <span class="hlt">ice</span> cover.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27134805','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27134805"><span>Spatial and temporal Antarctic <span class="hlt">Ice</span> Sheet mass <span class="hlt">trends</span>, glacio-isostatic adjustment, and surface processes from a joint inversion of satellite altimeter, gravity, and GPS data.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Martín-Español, Alba; Zammit-Mangion, Andrew; Clarke, Peter J; Flament, Thomas; Helm, Veit; King, Matt A; Luthcke, Scott B; Petrie, Elizabeth; Rémy, Frederique; Schön, Nana; Wouters, Bert; Bamber, Jonathan L</p> <p>2016-02-01</p> <p>We present spatiotemporal mass balance <span class="hlt">trends</span> for the Antarctic <span class="hlt">Ice</span> Sheet from a statistical inversion of satellite altimetry, gravimetry, and elastic-corrected GPS data for the period 2003-2013. Our method simultaneously determines annual <span class="hlt">trends</span> in <span class="hlt">ice</span> dynamics, surface mass balance anomalies, and a time-invariant solution for glacio-isostatic adjustment while remaining largely independent of forward models. We establish that over the period 2003-2013, Antarctica has been losing mass at a rate of -84 ± 22 Gt yr -1 , with a sustained negative mean <span class="hlt">trend</span> of dynamic imbalance of -111 ± 13 Gt yr -1 . West Antarctica is the largest contributor with -112 ± 10 Gt yr -1 , mainly triggered by high thinning rates of glaciers draining into the Amundsen Sea Embayment. The Antarctic Peninsula has experienced a dramatic increase in mass loss in the last decade, with a mean rate of -28 ± 7 Gt yr -1 and significantly higher values for the most recent years following the destabilization of the Southern Antarctic Peninsula around 2010. The total mass loss is partly compensated by a significant mass gain of 56 ± 18 Gt yr -1 in East Antarctica due to a positive <span class="hlt">trend</span> of surface mass balance anomalies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19..187K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19..187K"><span>Last Glacial-Interglacial Transition <span class="hlt">ice</span> dynamics in the Wicklow Mountains, Ireland</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Knight, Lauren; Boston, Clare; Lovell, Harold; Pepin, Nick</p> <p>2017-04-01</p> <p>Understanding of the <span class="hlt">extent</span> and dynamics of former <span class="hlt">ice</span> masses in the Wicklow Mountains, Ireland, during the Last Glacial-Interglacial Transition (LGIT; 15-10 ka BP) is currently unresolved. Whilst it is acknowledged that the region hosted a local <span class="hlt">ice</span> cap within the larger British-Irish <span class="hlt">Ice</span> Sheet at the Last Glacial Maximum (LGM; 27 ka BP), there has been little consideration of <span class="hlt">ice</span> cap disintegration to a topographically constrained <span class="hlt">ice</span> mass during the LGIT. This research has produced the first regional glacial geomorphological map, through remote sensing (aerial photograph and digital terrain model interrogation) and field mapping. This has allowed both the style and <span class="hlt">extent</span> of mountain glaciation and <span class="hlt">ice</span> recession dynamics during the LGIT to be established. This geomorphological mapping has highlighted that evidence for local glaciation in the Wicklow Mountains is more extensive than previously recognised, and that small icefields and associated outlet valley glaciers existed during the LGIT following disintegration of the Wicklow <span class="hlt">Ice</span> Cap. A relative chronology based on morphostratigraphic principles is developed, which indicates complex patterns of <span class="hlt">ice</span> mass oscillation characterised by periods of both sustained retreat and minor readvance. Variations in the pattern of recession across the Wicklow Mountains are evident and appear to be influenced, in part, by topographic controls (e.g. slope, aspect, glacier hypsometry). In summary, this research establishes a relative chronology of glacial events in the region during the LGIT and presents constraints on <span class="hlt">ice</span> mass <span class="hlt">extent</span>, dynamics and retreat patterns, offering an insight into small <span class="hlt">ice</span> mass behaviour in a warming climate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19920040056&hterms=data+types&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Ddata%2Btypes','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19920040056&hterms=data+types&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Ddata%2Btypes"><span>Effects of weather on the retrieval of sea <span class="hlt">ice</span> concentration and <span class="hlt">ice</span> type from passive microwave data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Maslanik, J. A.</p> <p>1992-01-01</p> <p>Effects of wind, water vapor, and cloud liquid water on <span class="hlt">ice</span> concentration and <span class="hlt">ice</span> type calculated from passive microwave data are assessed through radiative transfer calculations and observations. These weather effects can cause overestimates in <span class="hlt">ice</span> concentration and more substantial underestimates in multi-year <span class="hlt">ice</span> percentage by decreasing polarization and by decreasing the gradient between frequencies. The effect of surface temperature and air temperature on the magnitudes of weather-related errors is small for <span class="hlt">ice</span> concentration and substantial for multiyear <span class="hlt">ice</span> percentage. The existing weather filter in the NASA Team Algorithm addresses only weather effects over open ocean; the additional use of local open-ocean tie points and an alternative weather correction for the marginal <span class="hlt">ice</span> zone can further reduce errors due to weather. <span class="hlt">Ice</span> concentrations calculated using 37 versus 18 GHz data show little difference in total <span class="hlt">ice</span> covered area, but greater differences in intermediate concentration classes. Given the magnitude of weather-related errors in <span class="hlt">ice</span> classification from passive microwave data, corrections for weather effects may be necessary to detect small <span class="hlt">trends</span> in <span class="hlt">ice</span> covered area and <span class="hlt">ice</span> type for climate studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140010420','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140010420"><span>Sea <span class="hlt">Ice</span> Thickness, Freeboard, and Snow Depth products from Operation <span class="hlt">Ice</span>Bridge Airborne Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kurtz, N. T.; Farrell, S. L.; Studinger, M.; Galin, N.; Harbeck, J. P.; Lindsay, R.; Onana, V. D.; Panzer, B.; Sonntag, J. G.</p> <p>2013-01-01</p> <p>The study of sea <span class="hlt">ice</span> using airborne remote sensing platforms provides unique capabilities to measure a wide variety of sea <span class="hlt">ice</span> properties. These measurements are useful for a variety of topics including model evaluation and improvement, assessment of satellite retrievals, and incorporation into climate data records for analysis of interannual variability and long-term <span class="hlt">trends</span> in sea <span class="hlt">ice</span> properties. In this paper we describe methods for the retrieval of sea <span class="hlt">ice</span> thickness, freeboard, and snow depth using data from a multisensor suite of instruments on NASA's Operation <span class="hlt">Ice</span>Bridge airborne campaign. We assess the consistency of the results through comparison with independent data sets that demonstrate that the <span class="hlt">Ice</span>Bridge products are capable of providing a reliable record of snow depth and sea <span class="hlt">ice</span> thickness. We explore the impact of inter-campaign instrument changes and associated algorithm adaptations as well as the applicability of the adapted algorithms to the ongoing <span class="hlt">Ice</span>Bridge mission. The uncertainties associated with the retrieval methods are determined and placed in the context of their impact on the retrieved sea <span class="hlt">ice</span> thickness. Lastly, we present results for the 2009 and 2010 <span class="hlt">Ice</span>Bridge campaigns, which are currently available in product form via the National Snow and <span class="hlt">Ice</span> Data Center</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.P33A2867S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.P33A2867S"><span>Surfaces of Ganymede and Callisto: H2O-<span class="hlt">ice</span> particle sizes and composition of non-<span class="hlt">ice</span> materials</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stephan, K.; Hoffmann, H.; Hibbitts, C.; Wagner, R. J.; Jaumann, R.</p> <p>2017-12-01</p> <p>Band depth ratios (BDRs) of the major H2O-<span class="hlt">ice</span> absorptions in the NIMS spectra of the Galilean satellites Ganymede and Callisto have been found to be mainly unaffected by the abundance of the dark non-<span class="hlt">ice</span> material(s) and can be leveraged to provide semi-quantitative indicators of variations in the H2O-<span class="hlt">ice</span> particle sizes across their surfaces. Interestingly, the derived H2O-<span class="hlt">ice</span> particle sizes vary continuously with geographic latitude on both satellites. H2O-<span class="hlt">ice</span> particles on Callisto appear slightly larger at low and mid latitude than observed on Ganymede, whereas the BDR values converge toward the poles indicating similarly small H2O-<span class="hlt">ice</span> particle sizes for both satellites. This smooth latitudinal <span class="hlt">trend</span> on both satellites may be related to their surface temperatures and the possible thermal migration of water vapor to higher latitudes and grain welding at lower latitudes. It is not expected that the observed relationship between the BDRs and H2O-<span class="hlt">ice</span> particle sizes occurs for mixtures with every non-<span class="hlt">ice</span> material expected to exist on planetary surfaces. Therefore, <span class="hlt">ice</span> mixtures with a variety of considered non-<span class="hlt">ice</span> materials such as carbon-rich materials, phyllosilicates and salts have been investigated and the validity of this relationship tested depending on different H2O-<span class="hlt">ice</span> abundances and particle sizes. The relationship seems to be valid for most materials if the amount of the non-<span class="hlt">ice</span> material in the mixture does not exceed a few percent or the non-<span class="hlt">ice</span> component is not hydrated, i.e. does not itself possess water-related bands near 1.4 and 1.9 microns. Best results across the nearly full range of percentage could be achieved for carbon-rich material, iron sulfides, and hydroxylated phyllosilicates, which are expected to be the major constituent of carbonaceous chondrites. In contrast, significant amounts of hydrated material, as identified on Europa, significantly changes the BDRs and cannot fully explain the global <span class="hlt">trend</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.4366H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.4366H"><span>Deciphering the evolution of the last Eurasian <span class="hlt">ice</span> sheets</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hughes, Anna; Gyllencreutz, Richard; Mangerud, Jan; Svendsen, John Inge</p> <p>2016-04-01</p> <p>Glacial geologists need <span class="hlt">ice</span> sheet-scale chronological reconstructions of former <span class="hlt">ice</span> <span class="hlt">extent</span> to set individual records in a wider context and compare interpretations of <span class="hlt">ice</span> sheet response to records of past environmental changes. <span class="hlt">Ice</span> sheet modellers require empirical reconstructions on size and volume of past <span class="hlt">ice</span> sheets that are fully documented, specified in time and include uncertainty estimates for model validation or constraints. Motivated by these demands, in 2005 we started a project (Database of the Eurasian Deglaciation, DATED) to compile and archive all published dates relevant to constraining the build-up and retreat of the last Eurasian <span class="hlt">ice</span> sheets, including the British-Irish, Scandinavian and Svalbard-Barents-Kara Seas <span class="hlt">ice</span> sheets (BIIS, SIS and SBKIS respectively). Over 5000 dates were assessed for reliability and used together with published <span class="hlt">ice</span>-sheet margin positions to reconstruct time-slice maps of the <span class="hlt">ice</span> sheets' <span class="hlt">extent</span>, with uncertainty bounds, every 1000 years between 25-10 kyr ago and at four additional periods back to 40 kyr ago. Ten years after the idea for a database was conceived, the first version of results (DATED-1) has now been released (Hughes et al. 2016). We observe that: i) both the BIIS and SBKIS achieve maximum <span class="hlt">extent</span>, and commence retreat earlier than the larger SIS; ii) the eastern terrestrial margin of the SIS reached its maximum <span class="hlt">extent</span> up to 7000 years later than the westernmost marine margin; iii) the combined maximum <span class="hlt">ice</span> volume (~24 m sea-level equivalent) was reached c. 21 ka; iv) large uncertainties exist; predominantly across marine sectors (e.g. the timing of coalescence and separation of the SIS and BKIS) but also in well-studied areas due to conflicting yet equally robust data. In just three years since the DATED-1 census (1 January 2013), the volume of new information (from both dates and mapped glacial geomorphology) has grown significantly (~1000 new dates). Here, we present the DATED-1 results in the context of the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015PrOce.136..151D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015PrOce.136..151D"><span>Effects of recent decreases in arctic sea <span class="hlt">ice</span> on an <span class="hlt">ice</span>-associated marine bird</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Divoky, George J.; Lukacs, Paul M.; Druckenmiller, Matthew L.</p> <p>2015-08-01</p> <p>Recent major reductions in summer arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> could be expected to be affecting the distributions and life histories of arctic marine biota adapted to living adjacent to sea <span class="hlt">ice</span>. Of major concern are the effects of <span class="hlt">ice</span> reductions, and associated increasing SST, on the most abundant forage fish in the Arctic, Arctic cod (Boreogadus saida), the primary prey for the region's upper trophic level marine predators. The black guillemot (Cepphus grylle mandtii) is an <span class="hlt">ice</span>-obligate diving seabird specializing in feeding on Arctic cod and has been studied annually since 1975 at a breeding colony in the western Beaufort Sea. The data set is one of the few allowing assessment of the response of an upper trophic marine predator to recent decadal changes in the region's cryosphere. Analysis of oceanographic conditions north of the colony from 1975 to 2012 for the annual period when parents provision young (mid-July to early September), found no major regime shifts in <span class="hlt">ice</span> <span class="hlt">extent</span> or SST until the late 1990s with major decreases in <span class="hlt">ice</span> and increases in SST in the first decade of the 21st Century. We examined decadal variation in late summer oceanographic conditions, nestling diet and success, and overwinter adult survival, comparing a historical period (1975-1984) with a recent (2003-2012) one. In the historical period sea <span class="hlt">ice</span> retreated an average of 1.8 km per day from 15 July to 1 September to an average distance of 95.8 km from the colony, while in the recent period <span class="hlt">ice</span> retreat averaged 9.8 km per day to an average distance of 506.9 km for the same time period. SST adjacent to the island increased an average of 2.9 °C between the two periods. While Arctic cod comprised over 95% of the prey provided to nestlings in the historical period, in the recent period 80% of the years had seasonal decreases, with Arctic cod decreasing to <5% of the nestling diet, and nearshore demersals, primarily sculpin (Cottidae), comprising the majority of the diet. A five-fold increase in</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70012715','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70012715"><span>Time-dependence of sea-<span class="hlt">ice</span> concentration and multiyear <span class="hlt">ice</span> fraction in the Arctic Basin</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Gloersen, P.; Zwally, H.J.; Chang, A.T.C.; Hall, D.K.; Campbell, W.J.; Ramseier, R.O.</p> <p>1978-01-01</p> <p>The time variation of the sea-<span class="hlt">ice</span> concentration and multiyear <span class="hlt">ice</span> fraction within the pack <span class="hlt">ice</span> in the Arctic Basin is examined, using microwave images of sea <span class="hlt">ice</span> recently acquired by the Nimbus-5 spacecraft and the NASA CV-990 airborne laboratory. The images used for these studies were constructed from data acquired from the Electrically Scanned Microwave Radiometer (ESMR) which records radiation from earth and its atmosphere at a wavelength of 1.55 cm. Data are analyzed for four seasons during 1973-1975 to illustrate some basic differences in the properties of the sea <span class="hlt">ice</span> during those times. Spacecraft data are compared with corresponding NASA CV-990 airborne laboratory data obtained over wide areas in the Arctic Basin during the Main Arctic <span class="hlt">Ice</span> Dynamics Joint Experiment (1975) to illustrate the applicability of passive-microwave remote sensing for monitoring the time dependence of sea-<span class="hlt">ice</span> concentration (divergence). These observations indicate significant variations in the sea-<span class="hlt">ice</span> concentration in the spring, late fall and early winter. In addition, deep in the interior of the Arctic polar sea-<span class="hlt">ice</span> pack, heretofore unobserved large areas, several hundred kilometers in <span class="hlt">extent</span>, of sea-<span class="hlt">ice</span> concentrations as low as 50% are indicated. ?? 1978 D. Reidel Publishing Company.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170003213&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dsea','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170003213&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dsea"><span>A Review of Recent Changes in Southern Ocean Sea <span class="hlt">Ice</span>, Their Drivers and Forcings</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hobbs, William R.; Massom, Rob; Stammerjohn, Sharon; Reid, Phillip; Williams, Guy; Meier, Walter</p> <p>2016-01-01</p> <p>Over the past 37years, satellite records show an increase in Antarctic sea <span class="hlt">ice</span> cover that is most pronounced in the period of sea <span class="hlt">ice</span> growth. This <span class="hlt">trend</span> is dominated by increased sea <span class="hlt">ice</span> coverage in the western Ross Sea, and is mitigated by a strong decrease in the Bellingshausen and Amundsen seas. The <span class="hlt">trends</span> in sea <span class="hlt">ice</span> areal coverage are accompanied by related <span class="hlt">trends</span> in yearly duration. These changes have implications for ecosystems, as well as global and regional climate. In this review, we summarize the researchto date on observing these <span class="hlt">trends</span>, identifying their drivers, and assessing the role of anthropogenic climate change. Whilst the atmosphere is thought to be the primary driver, the ocean is also essential in explaining the seasonality of the <span class="hlt">trend</span> patterns. Detecting an anthropogenic signal in Antarctic sea <span class="hlt">ice</span> is particularly challenging for a number of reasons: the expected response is small compared to the very high natural variability of the system; the observational record is relatively short; and the ability of global coupled climate models to faithfully represent the complex Antarctic climate system is in doubt.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C42B..03D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C42B..03D"><span>Assessing deformation and morphology of Arctic landfast sea <span class="hlt">ice</span> using InSAR to support use and management of coastal <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dammann, D. O.; Eicken, H.; Meyer, F. J.; Mahoney, A. R.</p> <p>2016-12-01</p> <p>Arctic landfast sea <span class="hlt">ice</span> provides important services to people, including coastal communities and industry, as well as key marine biota. In many regions of the Arctic, the use of landfast sea <span class="hlt">ice</span> by all stakeholders is increasingly limited by reduced stability of the <span class="hlt">ice</span> cover, which results in more deformation and rougher <span class="hlt">ice</span> conditions as well as reduced <span class="hlt">extent</span> and an increased likelihood of detachment from the shore. Here, we use Synthetic Aperture Radar Interferometry (InSAR) to provide stakeholder-relevant data on key constraints for sea <span class="hlt">ice</span> use, in particular <span class="hlt">ice</span> stability and morphology, which are difficult to assess using conventional SAR. InSAR has the capability to detect small-scale landfast <span class="hlt">ice</span> displacements, which are linked to important coastal hazards, including the formation of cracks, ungrounding of <span class="hlt">ice</span> pressure ridges, and catastrophic breakout events. While InSAR has previously been used to identify the <span class="hlt">extent</span> of landfast <span class="hlt">ice</span> and regions of deformation within, quantitative analysis of small-scale <span class="hlt">ice</span> motion has yet to be thoroughly validated and its potential remains largely underutilized in sea <span class="hlt">ice</span> science. Using TanDEM-X interferometry, we derive surface displacements of landfast <span class="hlt">ice</span> within Elson Lagoon near Barrow, Alaska, which we validate using in-situ DGPS data. We then apply an inverse model to estimate rates and patterns of shorefast <span class="hlt">ice</span> deformation in other regions of landfast <span class="hlt">ice</span> using interferograms generated with long-temporal baseline L-band ALOS-1 PALSAR-1 data. The model is able to correctly identify deformation modes and proxies for the associated relative internal elastic stress. The derived potential for fractures corresponds well with large-scale sea <span class="hlt">ice</span> patterns and local in-situ observations. The utility of InSAR to quantify sea <span class="hlt">ice</span> roughness has also been explored using TanDEM-X bistatic interferometry, which eliminates the effects of temporal changes in the <span class="hlt">ice</span> cover. The InSAR-derived DEM shows good correlation with a high</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21G1186T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21G1186T"><span>There goes the sea <span class="hlt">ice</span>: following Arctic sea <span class="hlt">ice</span> parcels and their properties.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tschudi, M. A.; Tooth, M.; Meier, W.; Stewart, S.</p> <p>2017-12-01</p> <p>Arctic sea <span class="hlt">ice</span> distribution has changed considerably over the last couple of decades. Sea <span class="hlt">ice</span> <span class="hlt">extent</span> record minimums have been observed in recent years, the distribution of <span class="hlt">ice</span> age now heavily favors younger <span class="hlt">ice</span>, and sea <span class="hlt">ice</span> is likely thinning. This new state of the Arctic sea <span class="hlt">ice</span> cover has several impacts, including effects on marine life, feedback on the warming of the ocean and atmosphere, and on the future evolution of the <span class="hlt">ice</span> pack. The shift in the state of the <span class="hlt">ice</span> cover, from a pack dominated by older <span class="hlt">ice</span>, to the current state of a pack with mostly young <span class="hlt">ice</span>, impacts specific properties of the <span class="hlt">ice</span> pack, and consequently the pack's response to the changing Arctic climate. For example, younger <span class="hlt">ice</span> typically contains more numerous melt ponds during the melt season, resulting in a lower albedo. First-year <span class="hlt">ice</span> is typically thinner and more fragile than multi-year <span class="hlt">ice</span>, making it more susceptible to dynamic and thermodynamic forcing. To investigate the response of the <span class="hlt">ice</span> pack to climate forcing during summertime melt, we have developed a database that tracks individual Arctic sea <span class="hlt">ice</span> parcels along with associated properties as these parcels advect during the summer. Our database tracks parcels in the Beaufort Sea, from 1985 - present, along with variables such as <span class="hlt">ice</span> surface temperature, albedo, <span class="hlt">ice</span> concentration, and convergence. We are using this database to deduce how these thousands of tracked parcels fare during summer melt, i.e. what fraction of the parcels advect through the Beaufort, and what fraction melts out? The tracked variables describe the thermodynamic and dynamic forcing on these parcels during their journey. This database will also be made available to all interested investigators, after it is published in the near future. The attached image shows the <span class="hlt">ice</span> surface temperature of all parcels (right) that advected through the Beaufort Sea region (left) in 2014.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21E1162L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21E1162L"><span>Exploring changes in vertical <span class="hlt">ice</span> <span class="hlt">extent</span> along the margin of the East Antarctic <span class="hlt">Ice</span> Sheet in western Dronning Maud Land - initial results of the MAGIC-DML collaboration</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lifton, N. A.; Newall, J. C.; Fredin, O.; Glasser, N. F.; Fabel, D.; Rogozhina, I.; Bernales, J.; Prange, M.; Sams, S.; Eisen, O.; Hättestrand, C.; Harbor, J.; Stroeven, A. P.</p> <p>2017-12-01</p> <p>Numerical <span class="hlt">ice</span> sheet models constrained by theory and refined by comparisons with observational data are a central component of work to address the interactions between the cryosphere and changing climate, at a wide range of scales. Such models are tested and refined by comparing model predictions of past <span class="hlt">ice</span> geometries with field-based reconstructions from geological, geomorphological, and <span class="hlt">ice</span> core data. However, on the East Antarctic <span class="hlt">Ice</span> sheet, there are few empirical data with which to reconstruct changes in <span class="hlt">ice</span> sheet geometry in the Dronning Maud Land (DML) region. In addition, there is poor control on the regional climate history of the <span class="hlt">ice</span> sheet margin, because <span class="hlt">ice</span> core locations, where detailed reconstructions of climate history exist, are located on high inland domes. This leaves numerical models of regional glaciation history in this near-coastal area largely unconstrained. MAGIC-DML is an ongoing Swedish-US-Norwegian-German-UK collaboration with a focus on improving <span class="hlt">ice</span> sheet models by combining advances in numerical modeling with filling critical data gaps that exist in our knowledge of the timing and pattern of <span class="hlt">ice</span> surface changes on the western Dronning Maud Land margin. A combination of geomorphological mapping using remote sensing data, field investigations, cosmogenic nuclide surface exposure dating, and numerical <span class="hlt">ice</span>-sheet modeling are being used in an iterative manner to produce a comprehensive reconstruction of the glacial history of western Dronning Maud Land. We will present an overview of the project, as well as field observations and preliminary in situ cosmogenic nuclide measurements from the 2016/17 expedition.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23705008','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23705008"><span>Change and variability in East antarctic sea <span class="hlt">ice</span> seasonality, 1979/80-2009/10.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Massom, Robert; Reid, Philip; Stammerjohn, Sharon; Raymond, Ben; Fraser, Alexander; Ushio, Shuki</p> <p>2013-01-01</p> <p>Recent analyses have shown that significant changes have occurred in patterns of sea <span class="hlt">ice</span> seasonality in West Antarctica since 1979, with wide-ranging climatic, biological and biogeochemical consequences. Here, we provide the first detailed report on long-term change and variability in annual timings of sea <span class="hlt">ice</span> advance, retreat and resultant <span class="hlt">ice</span> season duration in East Antarctica. These were calculated from satellite-derived <span class="hlt">ice</span> concentration data for the period 1979/80 to 2009/10. The pattern of change in sea <span class="hlt">ice</span> seasonality off East Antarctica comprises mixed signals on regional to local scales, with pockets of strongly positive and negative <span class="hlt">trends</span> occurring in near juxtaposition in certain regions e.g., Prydz Bay. This pattern strongly reflects change and variability in different elements of the marine "icescape", including fast <span class="hlt">ice</span>, polynyas and the marginal <span class="hlt">ice</span> zone. A <span class="hlt">trend</span> towards shorter sea-<span class="hlt">ice</span> duration (of 1 to 3 days per annum) occurs in fairly isolated pockets in the outer pack from∼95-110°E, and in various near-coastal areas that include an area of particularly strong and persistent change near Australia's Davis Station and between the Amery and West <span class="hlt">Ice</span> Shelves. These areas are largely associated with coastal polynyas that are important as sites of enhanced sea <span class="hlt">ice</span> production/melt. Areas of positive <span class="hlt">trend</span> in <span class="hlt">ice</span> season duration are more extensive, and include an extensive zone from 160-170°E (i.e., the western Ross Sea sector) and the near-coastal zone between 40-100°E. The East Antarctic pattern is considerably more complex than the well-documented <span class="hlt">trends</span> in West Antarctica e.g., in the Antarctic Peninsula-Bellingshausen Sea and western Ross Sea sectors.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.C22A..05T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.C22A..05T"><span>The ‘dark’ side of the Greenland <span class="hlt">Ice</span> Sheet: 2009 updated long term melting <span class="hlt">trends</span>, remotely controlled boats on supraglacial lakes and cryokonite holes. (Invited)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tedesco, M.</p> <p>2009-12-01</p> <p>In this talk I will report recent results from different projects concerning melting over the Greenland <span class="hlt">Ice</span> Sheet. In particular, I will focus on three aspects: first, I will show results updating the long-term melting <span class="hlt">trends</span> (1979 - 2009) derived with spaceborne satellite data will discuss the 2009 melting season. Second, I will present results of an experiment aiming at improving the monitoring of supraglacial lakes from visible and near-infrared satellite data and will present seasonal <span class="hlt">trends</span> of these surface features. At the beginning of July 2009, we collected lake depth data and satellites-like data to evaluate satellites products used to study supraglacial lakes and improve monitoring techniques. We used a remotely controlled boat equipped with a GPS, fishfinder, spectrometer and microcomputer to collect these data. Third, while on the <span class="hlt">ice</span> sheet, we also collected samples of cryoconite (that dark powdered material responsible for dark holes in the <span class="hlt">ice</span>). I will report the results of preliminary analysis of this material by using Scanning Electronic Microscopy (SEM, for analyzing the composition) and a spectrometer (to characterize the visible and near-infrared properties). The following people contributed to the results of the different projects here reported: Nick Steiner (CUNY), M. Jenkins (National Geographic), X. Fettweis (University of Liege), Adam Lewinter and James Balog (Extreme <span class="hlt">Ice</span> Survey), Gina Stovall and Gordon Green (CCNY). The World Wildlife Foundation (WWF) and Martin Sommerkorn are deeply acknowledged for the financial support provided for the experiment.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120013476','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120013476"><span><span class="hlt">Trends</span> in Surface Temperature at High Latitudes</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Josefino C.</p> <p>2012-01-01</p> <p> started. Also, the SST in the Arctic basin is observed to be anomalously high in 2007 when the perennial <span class="hlt">ice</span> cover declined dramatically to its lowest <span class="hlt">extent</span>. In the Antarctic, surface temperature <span class="hlt">trends</span> are much more moderate with the most positive <span class="hlt">trends</span> occurring in the Antarctic Peninsula and parts of Western Antarctica while some cooling are observed in the Antarctic Plateau and the Ross Sea. The <span class="hlt">trends</span> in SST in the region is similar to global averages but precipitation from more evaporation may have a key role in the spatial distribution of surface temperature in the <span class="hlt">ice</span> covered region</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1913097K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1913097K"><span>Improved method for sea <span class="hlt">ice</span> age computation based on combination of sea <span class="hlt">ice</span> drift and concentration</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Korosov, Anton; Rampal, Pierre; Lavergne, Thomas; Aaboe, Signe</p> <p>2017-04-01</p> <p>Sea <span class="hlt">Ice</span> Age is one of the components of the Sea <span class="hlt">Ice</span> ECV as defined by the Global Climate Observing System (GCOS) [WMO, 2015]. It is an important climate indicator describing the sea <span class="hlt">ice</span> state in addition to sea <span class="hlt">ice</span> concentration (SIC) and thickness (SIT). The amount of old/thick <span class="hlt">ice</span> in the Arctic Ocean has been decreasing dramatically [Perovich et al. 2015]. Kwok et al. [2009] reported significant decline in the MYI share and consequent loss of thickness and therefore volume. Today, there is only one acknowledged sea <span class="hlt">ice</span> age climate data record [Tschudi, et al. 2015], based on Maslanik et al. [2011] provided by National Snow and <span class="hlt">Ice</span> Data Center (NSIDC) [http://nsidc.org/data/docs/daac/nsidc0611-sea-<span class="hlt">ice</span>-age/]. The sea <span class="hlt">ice</span> age algorithm [Fowler et al., 2004] is using satellite-derived <span class="hlt">ice</span> drift for Lagrangian tracking of individual <span class="hlt">ice</span> parcels (12-km grid cells) defined by areas of sea <span class="hlt">ice</span> concentration > 15% [Maslanik et al., 2011], i.e. sea <span class="hlt">ice</span> <span class="hlt">extent</span>, according to the NASA Team algorithm [Cavalieri et al., 1984]. This approach has several drawbacks. (1) Using sea <span class="hlt">ice</span> <span class="hlt">extent</span> instead of sea <span class="hlt">ice</span> concentration leads to overestimation of the amount of older <span class="hlt">ice</span>. (2) The individual <span class="hlt">ice</span> parcels are not advected uniformly over (long) time. This leads to undersampling in areas of consistent <span class="hlt">ice</span> divergence. (3) The end product grid cells are assigned the age of the oldest <span class="hlt">ice</span> parcel within that cell, and the frequency distribution of the <span class="hlt">ice</span> age is not taken into account. In addition, the base sea <span class="hlt">ice</span> drift product (https://nsidc.org/data/docs/daac/nsidc0116_icemotion.gd.html) is known to exhibit greatly reduced accuracy during the summer season [Sumata et al 2014, Szanyi, 2016] as it only relies on a combination of sea <span class="hlt">ice</span> drifter trajectories and wind-driven "free-drift" motion during summer. This results in a significant overestimate of old-<span class="hlt">ice</span> content, incorrect shape of the old-<span class="hlt">ice</span> pack, and lack of information about the <span class="hlt">ice</span> age distribution within the grid cells. We</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AIPC.1839b0089X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AIPC.1839b0089X"><span>Road <span class="hlt">icing</span> forecasting and detecting system</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xu, Hongke; Zheng, Jinnan; Li, Peiqi; Wang, Qiucai</p> <p>2017-05-01</p> <p>Regard for the facts that the low accuracy and low real-time of the artificial observation to determine the road <span class="hlt">icing</span> condition, and it is difficult to forecast <span class="hlt">icing</span> situation, according to the main factors influencing the road-<span class="hlt">icing</span>, and the electrical characteristics reflected by the pavement <span class="hlt">ice</span> layer, this paper presents an innovative system, that is, <span class="hlt">ice</span>-forecasting of the highway's dangerous section. The system bases on road surface water salinity measurements and pavement temperature measurement to calculate the freezing point of water and temperature change <span class="hlt">trend</span>, and then predicts the occurrence time of road <span class="hlt">icing</span>; using capacitance measurements to verdict the road surface is frozen or not; This paper expounds the method of using single chip microcomputer as the core of the control system and described the business process of the system.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170007898','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170007898"><span>Evaluation of Alternative Altitude Scaling Methods for Thermal <span class="hlt">Ice</span> Protection System in NASA <span class="hlt">Icing</span> Research Tunnel</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lee, Sam; Addy, Harold E. Jr.; Broeren, Andy P.; Orchard, David M.</p> <p>2017-01-01</p> <p>A test was conducted at NASA <span class="hlt">Icing</span> Research Tunnel to evaluate altitude scaling methods for thermal <span class="hlt">ice</span> protection system. Two new scaling methods based on Weber number were compared against a method based on Reynolds number. The results generally agreed with the previous set of tests conducted in NRCC Altitude <span class="hlt">Icing</span> Wind Tunnel where the three methods of scaling were also tested and compared along with reference (altitude) <span class="hlt">icing</span> conditions. In those tests, the Weber number-based scaling methods yielded results much closer to those observed at the reference <span class="hlt">icing</span> conditions than the Reynolds number-based <span class="hlt">icing</span> conditions. The test in the NASA IRT used a much larger, asymmetric airfoil with an <span class="hlt">ice</span> protection system that more closely resembled designs used in commercial aircraft. Following the <span class="hlt">trends</span> observed during the AIWT tests, the Weber number based scaling methods resulted in smaller runback <span class="hlt">ice</span> than the Reynolds number based scaling, and the <span class="hlt">ice</span> formed farther upstream. The results show that the new Weber number based scaling methods, particularly the Weber number with water loading scaling, continue to show promise for <span class="hlt">ice</span> protection system development and evaluation in atmospheric <span class="hlt">icing</span> tunnels.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19910021293','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19910021293"><span>The influence of the hydrologic cycle on the <span class="hlt">extent</span> of sea <span class="hlt">ice</span> with climatic implications</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Dean, Ken; Gosink, Joan</p> <p>1991-01-01</p> <p>The role was analyzed of the hydrologic cycle on the distribution of sea <span class="hlt">ice</span>, and its influence on forcings and fluxes between the marine environment and the atmosphere. River discharge plays a significant role in degrading the sea <span class="hlt">ice</span> before any melting occurs elsewhere along the coast. The influence is considered of river discharge on the albedo, thermal balance, and distribution of sea <span class="hlt">ice</span>. Quantitative atmospheric-hydrologic models are being developed to describe these processes in the coastal zone. Input for the models will come from satellite images, hydrologic data, and field observations. The resulting analysis provides a basis for the study of the significance of the hydrologic cycle throughout the Arctic Basin and its influence on the regional climate as a result of possible climatic scenarios. The area offshore from the Mackenzie River delta was selected as the study area.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_17 --> <div id="page_18" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="341"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC23A1220I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC23A1220I"><span>Statistical prediction of September Arctic Sea <span class="hlt">Ice</span> minimum based on stable teleconnections with global climate and oceanic patterns</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ionita, M.; Grosfeld, K.; Scholz, P.; Lohmann, G.</p> <p>2016-12-01</p> <p>Sea <span class="hlt">ice</span> in both Polar Regions is an important indicator for the expression of global climate change and its polar amplification. Consequently, a broad information interest exists on sea <span class="hlt">ice</span>, its coverage, variability and long term change. Knowledge on sea <span class="hlt">ice</span> requires high quality data on <span class="hlt">ice</span> <span class="hlt">extent</span>, thickness and its dynamics. However, its predictability depends on various climate parameters and conditions. In order to provide insights into the potential development of a monthly/seasonal signal, we developed a robust statistical model based on ocean heat content, sea surface temperature and atmospheric variables to calculate an estimate of the September minimum sea <span class="hlt">ice</span> <span class="hlt">extent</span> for every year. Although previous statistical attempts at monthly/seasonal forecasts of September sea <span class="hlt">ice</span> minimum show a relatively reduced skill, here it is shown that more than 97% (r = 0.98) of the September sea <span class="hlt">ice</span> <span class="hlt">extent</span> can predicted three months in advance by using previous months conditions via a multiple linear regression model based on global sea surface temperature (SST), mean sea level pressure (SLP), air temperature at 850hPa (TT850), surface winds and sea <span class="hlt">ice</span> <span class="hlt">extent</span> persistence. The statistical model is based on the identification of regions with stable teleconnections between the predictors (climatological parameters) and the predictand (here sea <span class="hlt">ice</span> <span class="hlt">extent</span>). The results based on our statistical model contribute to the sea <span class="hlt">ice</span> prediction network for the sea <span class="hlt">ice</span> outlook report (https://www.arcus.org/sipn) and could provide a tool for identifying relevant regions and climate parameters that are important for the sea <span class="hlt">ice</span> development in the Arctic and for detecting sensitive and critical regions in global coupled climate models with focus on sea <span class="hlt">ice</span> formation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.nsf.gov/pubs/2005/nsf0539/nsf0539_5.pdf','USGSPUBS'); return false;" href="http://www.nsf.gov/pubs/2005/nsf0539/nsf0539_5.pdf"><span>Correlated declines in Pacific arctic snow and sea <span class="hlt">ice</span> cover</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Stone, Robert P.; Douglas, David C.; Belchansky, Gennady I.; Drobot, Sheldon</p> <p>2005-01-01</p> <p>Simulations of future climate suggest that global warming will reduce Arctic snow and <span class="hlt">ice</span> cover, resulting in decreased surface albedo (reflectivity). Lowering of the surface albedo leads to further warming by increasing solar absorption at the surface. This phenomenon is referred to as “temperature–albedo feedback.” Anticipation of such a feedback is one reason why scientists look to the Arctic for early indications of global warming. Much of the Arctic has warmed significantly. Northern Hemisphere snow cover has decreased, and sea <span class="hlt">ice</span> has diminished in area and thickness. As reported in the Arctic Climate Impact Assessment in 2004, the <span class="hlt">trends</span> are considered to be outside the range of natural variability, implicating global warming as an underlying cause. Changing climatic conditions in the high northern latitudes have influenced biogeochemical cycles on a broad scale. Warming has already affected the sea <span class="hlt">ice</span>, the tundra, the plants, the animals, and the indigenous populations that depend on them. Changing annual cycles of snow and sea <span class="hlt">ice</span> also affect sources and sinks of important greenhouse gases (such as carbon dioxide and methane), further complicating feedbacks involving the global budgets of these important constituents. For instance, thawing permafrost increases the <span class="hlt">extent</span> of tundra wetlands and lakes, releasing greater amounts of methane into the atmosphere. Variable sea <span class="hlt">ice</span> cover may affect the hemispheric carbon budget by altering the ocean–atmosphere exchange of carbon dioxide. There is growing concern that amplification of global warming in the Arctic will have far-reaching effects on lower latitude climate through these feedback mechanisms. Despite the diverse and convincing observational evidence that the Arctic environment is changing, it remains unclear whether these changes are anthropogenically forced or result from natural variations of the climate system. A better understanding of what controls the seasonal distributions of snow and <span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015436','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015436"><span>Intersensor Calibration Between F13 SSMI and F17 SSMIS for Global Sea <span class="hlt">Ice</span> Data Records</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cavalieri, Donald J.; Parkinson, Claire L.; DiGirolamo, Nicolo; Ivanoff, Alvaro</p> <p>2011-01-01</p> <p>An intercalibration between F13 Special Sensor Microwave Imager (SSMI) and F17 Special Sensor Microwave Imager Sounder (SSMIS) sea <span class="hlt">ice</span> <span class="hlt">extents</span> and areas for a full year of overlap was undertaken preparatory to extending the 1979-2007 NASA Goddard Space Flight Center (GSFC) NASA Team algorithm time series of global sea <span class="hlt">ice</span> <span class="hlt">extents</span> and areas. The 1979- 2007 time series was created from Scanning Multichannel Microwave Radiometer (SMMR) and SSMI data. After intercalibration, the yearly mean F17 and F13 difference in Northern Hemisphere sea <span class="hlt">ice</span> <span class="hlt">extents</span> is -0.0156%, with a standard deviation of the differences of 0.6204%, and the yearly mean difference in Northern Hemisphere sea <span class="hlt">ice</span> areas is 0.5433%, with a standard deviation of 0.3519%. For the Southern Hemisphere, the yearly mean difference in sea <span class="hlt">ice</span> <span class="hlt">extents</span> is 0.0304% +/- 0.4880%, and the mean difference in sea <span class="hlt">ice</span> areas is 0.1550% +/- 0.3753%. This F13/F17 intercalibration enables the extension of the 28-year 1979-2007 SMMR/SSMI sea <span class="hlt">ice</span> time series for as long as there are stable F17 SSMIS brightness temperatures available.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120009376','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120009376"><span>Intersensor Calibration Between F13 SSMI and F17 SSMIS for Global Sea <span class="hlt">Ice</span> Data Records</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Cavalieri, Donald J.; Parkinson, Claire L.; DiGirolamo, Nicolo; Ivanoff, Alvaro</p> <p>2012-01-01</p> <p>An intercalibration between F13 Special Sensor Microwave Imager (SSMI) and F17 Special Sensor Microwave Imager Sounder (SSMIS) sea <span class="hlt">ice</span> <span class="hlt">extents</span> and areas for a full year of overlap was undertaken preparatory to extending the 1979-2007 NASA Goddard Space Flight Center (GSFC) NASA Team algorithm time series of global sea <span class="hlt">ice</span> <span class="hlt">extents</span> and areas. The 1979- 2007 time series was created from Scanning Multichannel Microwave Radiometer (SMMR) and SSMI data. After intercalibration, the yearly mean F17 and F13 difference in Northern Hemisphere sea <span class="hlt">ice</span> <span class="hlt">extents</span> is -0.0156%, with a standard deviation of the differences of 0.6204%, and the yearly mean difference in Northern Hemisphere sea <span class="hlt">ice</span> areas is 0.5433%, with a standard deviation of 0.3519%. For the Southern Hemisphere, the yearly mean difference in sea <span class="hlt">ice</span> <span class="hlt">extents</span> is 0.0304% 0.4880%, and the mean difference in sea <span class="hlt">ice</span> areas is 0.1550% 0.3753%. This F13/F17 intercalibration enables the extension of the 28-year 1979-2007 SMMR/SSMI sea <span class="hlt">ice</span> time series for as long as there are stable F17 SSMIS brightness temperatures available.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC43J..05S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC43J..05S"><span>Integrating Observations and Models to Better Understand a Changing Arctic Sea <span class="hlt">Ice</span> Cover</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stroeve, J. C.</p> <p>2017-12-01</p> <p>TThe loss of the Arctic sea <span class="hlt">ice</span> cover has captured the world's attention. While much attention has been paid to the summer <span class="hlt">ice</span> loss, changes are not limited to summer. The last few winters have seen record low sea <span class="hlt">ice</span> <span class="hlt">extents</span>, with 2017 marking the 3rdyear in a row with a new record low for the winter maximum <span class="hlt">extent</span>. More surprising is the number of consecutive months between January 2016 through April 2017 with <span class="hlt">ice</span> <span class="hlt">extent</span> anomalies more than 2 standard deviations below the 1981-2010 mean. Additionally, October 2016 through April 2017 saw 7 consecutive months with record low <span class="hlt">extents</span>, something that had not happened before in the last 4 decades of satellite observations. As larger parts of the Arctic Ocean become <span class="hlt">ice</span>-free in summer, regional seas gradually transition from a perennial to a seasonal <span class="hlt">ice</span> cover. The Barents Sea is already only seasonally <span class="hlt">ice</span> covered, whereas the Kara Sea has recently lost most of its summer <span class="hlt">ice</span> and is thereby starting to become a seasonally <span class="hlt">ice</span> covered region. These changes serve as harbinger for what's to come for other Arctic seas. Given the rapid pace of change, there is an urgent need to improve our understanding of the drivers behind Arctic sea <span class="hlt">ice</span> loss, the implications of this <span class="hlt">ice</span> loss and to predict future changes to better inform policy makers. Climate models play a fundamental role in helping us synthesize the complex elements of the Arctic sea <span class="hlt">ice</span> system yet generally fail to simulate key features of the sea <span class="hlt">ice</span> system and the pace of sea <span class="hlt">ice</span> loss. Nevertheless, modeling advances continue to provide better means of diagnosing sea <span class="hlt">ice</span> change, and new insights are likely to be gained with model output from the 6th phase of the Coupled Model Intercomparison Project (CMIP6). The CMIP6 Sea-<span class="hlt">Ice</span> Model Intercomparison Project (SIMIP) aim is to better understand biases and errors in sea <span class="hlt">ice</span> simulations so that we can improve our understanding of the likely future evolution of the sea <span class="hlt">ice</span> cover and its impacts on global climate. To</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000613.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000613.html"><span>Approaching the 2015 Arctic Sea <span class="hlt">Ice</span> Minimum</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2017-12-08</p> <p>As the sun sets over the Arctic, the end of this year’s melt season is quickly approaching and the sea <span class="hlt">ice</span> cover has already shrunk to the fourth lowest in the satellite record. With possibly some days of melting left, the sea <span class="hlt">ice</span> <span class="hlt">extent</span> could still drop to the second or third lowest on record. Arctic sea <span class="hlt">ice</span>, which regulates the planet’s temperature by bouncing solar energy back to space, has been on a steep decline for the last two decades. This animation shows the evolution of Arctic sea <span class="hlt">ice</span> in 2015, from its annual maximum wintertime <span class="hlt">extent</span>, reached on February 25, to September 6. Credit: NASA Scientific Visualization Studio DOWNLOAD THIS VIDEO HERE: svs.gsfc.nasa.gov/cgi-bin/details.cgi?aid=11999 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016SPIE.9972E..13B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016SPIE.9972E..13B"><span>Integrated approach using multi-platform sensors for enhanced high-resolution daily <span class="hlt">ice</span> cover product</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bonev, George; Gladkova, Irina; Grossberg, Michael; Romanov, Peter; Helfrich, Sean</p> <p>2016-09-01</p> <p>The ultimate objective of this work is to improve characterization of the <span class="hlt">ice</span> cover distribution in the polar areas, to improve sea <span class="hlt">ice</span> mapping and to develop a new automated real-time high spatial resolution multi-sensor <span class="hlt">ice</span> <span class="hlt">extent</span> and <span class="hlt">ice</span> edge product for use in operational applications. Despite a large number of currently available automated satellite-based sea <span class="hlt">ice</span> <span class="hlt">extent</span> datasets, analysts at the National <span class="hlt">Ice</span> Center tend to rely on original satellite imagery (provided by satellite optical, passive microwave and active microwave sensors) mainly because the automated products derived from satellite optical data have gaps in the area coverage due to clouds and darkness, passive microwave products have poor spatial resolution, automated <span class="hlt">ice</span> identifications based on radar data are not quite reliable due to a considerable difficulty in discriminating between the <span class="hlt">ice</span> cover and rough <span class="hlt">ice</span>-free ocean surface due to winds. We have developed a multisensor algorithm that first extracts maximum information on the sea <span class="hlt">ice</span> cover from imaging instruments VIIRS and MODIS, including regions covered by thin, semitransparent clouds, then supplements the output by the microwave measurements and finally aggregates the results into a cloud gap free daily product. This ability to identify <span class="hlt">ice</span> cover underneath thin clouds, which is usually masked out by traditional cloud detection algorithms, allows for expansion of the effective coverage of the sea <span class="hlt">ice</span> maps and thus more accurate and detailed delineation of the <span class="hlt">ice</span> edge. We have also developed a web-based monitoring system that allows comparison of our daily <span class="hlt">ice</span> <span class="hlt">extent</span> product with the several other independent operational daily products.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19980021232','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19980021232"><span>Sea <span class="hlt">Ice</span> on the Southern Ocean</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Jacobs, Stanley S.</p> <p>1998-01-01</p> <p>Year-round satellite records of sea <span class="hlt">ice</span> distribution now extend over more than two decades, providing a valuable tool to investigate related characteristics and circulations in the Southern Ocean. We have studied a variety of features indicative of oceanic and atmospheric interactions with Antarctic sea <span class="hlt">ice</span>. In the Amundsen & Bellingshausen Seas, sea <span class="hlt">ice</span> <span class="hlt">extent</span> was found to have decreased by approximately 20% from 1973 through the early 1990's. This change coincided with and probably contributed to recently warmer surface conditions on the west side of the Antarctic Peninsula, where air temperatures have increased by approximately 0.5 C/decade since the mid-1940's. The sea <span class="hlt">ice</span> decline included multiyear cycles of several years in length superimposed on high interannual variability. The retreat was strongest in summer, and would have lowered the regional mean <span class="hlt">ice</span> thickness, with attendant impacts upon vertical heat flux and the formation of snow <span class="hlt">ice</span> and brine. The cause of the regional warming and loss of sea <span class="hlt">ice</span> is believed to be linked to large-scale circulation changes in the atmosphere and ocean. At the eastern end of the Weddell Gyre, the Cosmonaut Polyna revealed greater activity since 1986, a recurrence pattern during recent winters and two possible modes of formation. Persistence in polynya location was noted off Cape Ann, where the coastal current can interact more strongly with the Antarctic Circumpolar Current. As a result of vorticity conservation, locally enhanced upwelling brings warmer deep water into the mixed layer, causing divergence and melting. In the Ross Sea, <span class="hlt">ice</span> <span class="hlt">extent</span> fluctuates over periods of several years, with summer minima and winter maxima roughly in phase. This leads to large interannual cycles of sea <span class="hlt">ice</span> range, which correlate positively with meridinal winds, regional air temperatures and subsequent shelf water salinities. Deep shelf waters display considerable interannual variability, but have freshened by approximately 0.03/decade</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C33A0662C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C33A0662C"><span>Holocene history of North <span class="hlt">Ice</span> Cap, northwestern Greenland</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Corbett, L. B.; Kelly, M. A.; Osterberg, E. C.; Axford, Y.; Bigl, M.; Roy, E. P.; Thompson, J. T.</p> <p>2013-12-01</p> <p>Although much research has focused on the past <span class="hlt">extents</span> of the Greenland <span class="hlt">Ice</span> Sheet, less is known about the smaller <span class="hlt">ice</span> caps on Greenland and how they have evolved over time. These small <span class="hlt">ice</span> caps respond sensitively to summer temperatures and, to a lesser <span class="hlt">extent</span>, winter precipitation, and provide valuable information about climatic conditions along the Greenland <span class="hlt">Ice</span> Sheet margins. Here, we investigate the Holocene history of North <span class="hlt">Ice</span> Cap (76°55'N 68°00'W), located in the Nunatarssuaq region near Thule, northwest Greenland. Our results are based on glacial geomorphic mapping, 10Be dating, and analyses of sediment cores from a glacially fed lake. Fresh, unweathered and unvegetated boulders comprise moraines and drift that mark an <span class="hlt">extent</span> of North <span class="hlt">Ice</span> Cap ~25 m outboard of the present <span class="hlt">ice</span> margin. It is likely that these deposits were formed during late Holocene time and we are currently employing 10Be surface exposure dating to examine this hypothesis. Just outboard of the fresh moraines and drift, boulders and bedrock show significant weathering and are covered with lichen. Based on glacial geomorphic mapping and detailed site investigations, including stone counts, we suggest that the weathered boulders and bedrock were once covered by erosive Greenland <span class="hlt">Ice</span> Sheet flow from southeast to northwest over the Nunatarssuaq region. Five 10Be ages from the more weathered landscape only 100-200 m outboard of the modern North <span class="hlt">Ice</span> Cap margin are 52 and 53 ka (bedrock) and 16, 23, and 31 ka (boulders). These ages indicate that recent <span class="hlt">ice</span> cover has likely been cold-based and non-erosive, failing to remove inherited cosmogenic nuclides from previous periods of exposure, although the youngest boulder may provide a maximum limiting deglaciation age. Sediment cores collected from Delta Sø, a glacially-fed lake ~1.5 km outside of the modern North <span class="hlt">Ice</span> Cap margin, contain 130 cm of finely laminated sediments overlying coarse sands and glacial till. Radiocarbon ages from just above</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010027899','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010027899"><span>Studies of Antarctic Sea <span class="hlt">Ice</span> Concentrations from Satellite Data and Their Applications</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Josefino C.; Steffen, Konrad; Zukor, Dorothy J. (Technical Monitor)</p> <p>2001-01-01</p> <p> activities. Also, heat and salinity fluxes are proportionately increased in these areas compared to those from the thicker <span class="hlt">ice</span> areas. A slight positive <span class="hlt">trend</span> in <span class="hlt">ice</span> <span class="hlt">extent</span> and area from 1978 through 2000 is observed consistent with slight continental cooling during the period. However, the confidence in this result is only moderate because the overlap period for key instruments is just one month and the sensitivity to changes in sensor characteristics, calibration and threshold for the <span class="hlt">ice</span> edge is quite high.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1911853E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1911853E"><span>Tracking the seasonal cycle of coastal sea <span class="hlt">ice</span>: Community-based observations and satellite remote sensing in service of societal needs</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Eicken, Hajo; Lee, Olivia A.; Johnson, Mark A.; Pulsifer, Peter; Danielsen, Finn</p> <p>2017-04-01</p> <p>Break-up and freeze-up of coastal sea <span class="hlt">ice</span> determine the timing and <span class="hlt">extent</span> of a number of human activities, ranging from <span class="hlt">ice</span> use by Indigenous hunters to coastal shipping. Yet, while major reductions in the <span class="hlt">extent</span> of Arctic summer sea <span class="hlt">ice</span> have been well studied, changes in its seasonal cycle have received less attention. Here, we discuss decadal scale changes and interannual variability in the timing of spring break-up and fall freeze-up, with a focus on coastal communities in Arctic Alaska. Observations of <span class="hlt">ice</span> conditions by Indigenous sea-<span class="hlt">ice</span> experts since 2006 indicate significant interannual variability in both the character and timing of freeze-up and break-up in the region. To aid in the archival and sharing of such observations, we have developed a database for community <span class="hlt">ice</span> observations (eloka-arctic.org/sizonet). Development of this database addressed key questions ranging from community guidance on different levels of data sharing and access to the development of protocols that may lend themselves for implementation in the context of operational programs such as Global Cryosphere Watch. The lessons learned and tools developed through this effort may help foster the emergence of common observation protocols and sharing practices across the Arctic, as explored jointly with the Greenlandic PISUNA initiative and the European INTAROS project. For the Arctic Alaska region, we developed an algorithm to extract the timing of break-up and freeze-up from passive microwave satellite data, drawing on community-based observations. Data from 1979 to 2013 show break-up start arriving earlier by 5-9 days per decade and freeze-up start arriving later by 7-14 days per decade in the Chukchi and Beaufort Seas. The <span class="hlt">trends</span> towards a shorter <span class="hlt">ice</span> season observed over the past several decades point towards a substantial change in the winter <span class="hlt">ice</span> regime by mid-century with incipient overlap of the end of the freeze-up and start of the break-up season as defined by coastal <span class="hlt">ice</span> users.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ClDy...46.2391T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ClDy...46.2391T"><span>Antarctic sea <span class="hlt">ice</span> increase consistent with intrinsic variability of the Amundsen Sea Low</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Turner, John; Hosking, J. Scott; Marshall, Gareth J.; Phillips, Tony; Bracegirdle, Thomas J.</p> <p>2016-04-01</p> <p>We investigate the relationship between atmospheric circulation variability and the recent <span class="hlt">trends</span> in Antarctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> (SIE) using Coupled Model Intercomparison Project Phase 5 (CMIP5) atmospheric data, ECMWF Interim reanalysis fields and passive microwave satellite data processed with the Bootstrap version 2 algorithm. Over 1979-2013 the annual mean total Antarctic SIE increased at a rate of 195 × 103 km2 dec-1 (1.6 % dec-1), p < 0.01. The largest regional positive <span class="hlt">trend</span> of annual mean SIE of 119 × 103 km2 dec-1 (4.0 % dec-1) has been in the Ross Sea sector. Off West Antarctica there is a high correlation between <span class="hlt">trends</span> in SIE and <span class="hlt">trends</span> in the near-surface winds. The Ross Sea SIE seasonal <span class="hlt">trends</span> are positive throughout the year, but largest in spring. The stronger meridional flow over the Ross Sea has been driven by a deepening of the Amundsen Sea Low (ASL). Pre-industrial control and historical simulations from CMIP5 indicate that the observed deepening of the ASL and stronger southerly flow over the Ross Sea are within the bounds of modeled intrinsic variability. The spring <span class="hlt">trend</span> would need to continue for another 11 years for it to fall outside the 2 standard deviation range seen in 90 % of the simulations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140003875','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140003875"><span>Modeling Commercial Turbofan Engine <span class="hlt">Icing</span> Risk With <span class="hlt">Ice</span> Crystal Ingestion</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Jorgenson, Philip C. E.; Veres, Joseph P.</p> <p>2013-01-01</p> <p> flight. The computational tool was utilized to help guide a portion of the PSL testing, and was used to predict <span class="hlt">ice</span> accretion could also occur at significantly lower altitudes. The predictions were qualitatively verified by subsequent testing of the engine in the PSL. The PSL test has helped to calibrate the engine <span class="hlt">icing</span> computational tool to assess the risk of <span class="hlt">ice</span> accretion. The results from the computer simulation identified prevalent <span class="hlt">trends</span> in wet bulb temperature, <span class="hlt">ice</span> particle melt ratio, and engine inlet temperature as a function of altitude for predicting engine <span class="hlt">icing</span> risk due to <span class="hlt">ice</span> crystal ingestion.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20150023363&hterms=permafrost&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dpermafrost','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20150023363&hterms=permafrost&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dpermafrost"><span>Climate <span class="hlt">Trends</span> in the Arctic as Observed from Space</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Comiso, Josefino C.; Hall, Dorothy K.</p> <p>2014-01-01</p> <p>The Arctic is a region in transformation. Warming in the region has been amplified, as expected from <span class="hlt">ice</span>-albedo feedback effects, with the rate of warming observed to be approx. 0.60+/-0.07 C/decade in the Arctic (>64degN) compared to approx. 0.17 C/decade globally during the last three decades. This increase in surface temperature is manifested in all components of the cryosphere. In particular, the sea <span class="hlt">ice</span> <span class="hlt">extent</span> has been declining at the rate of approx. 3.8%/decade, whereas the perennial <span class="hlt">ice</span> (represented by summer <span class="hlt">ice</span> minimum) is declining at a much greater rate of approx.11.5%/decade. Spring snow cover has also been observed to be declining by -2.12%/decade for the period 1967-2012. The Greenland <span class="hlt">ice</span> sheet has been losing mass at the rate of approx. 34.0Gt/year (sea level equivalence of 0.09 mm/year) during the period from 1992 to 2011, but for the period 2002-2011, a higher rate of mass loss of approx. 215 Gt/year has been observed. Also, the mass of glaciers worldwide declined at the rate of 226 Gt/year from 1971 to 2009 and 275 Gt/year from 1993 to 2009. Increases in permafrost temperature have also been measured in many parts of the Northern Hemisphere while a thickening of the active layer that overlies permafrost and a thinning of seasonally frozen ground has also been reported. To gain insight into these changes, comparative analysis with <span class="hlt">trends</span> in clouds, albedo, and the Arctic Oscillation is also presented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015PrOce.139..122B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015PrOce.139..122B"><span>Selected physical, biological and biogeochemical implications of a rapidly changing Arctic Marginal <span class="hlt">Ice</span> Zone</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Barber, David G.; Hop, Haakon; Mundy, Christopher J.; Else, Brent; Dmitrenko, Igor A.; Tremblay, Jean-Eric; Ehn, Jens K.; Assmy, Philipp; Daase, Malin; Candlish, Lauren M.; Rysgaard, Søren</p> <p>2015-12-01</p> <p>The Marginal <span class="hlt">Ice</span> Zone (MIZ) of the Arctic Ocean is changing rapidly due to a warming Arctic climate with commensurate reductions in sea <span class="hlt">ice</span> <span class="hlt">extent</span> and thickness. This Pan-Arctic review summarizes the main changes in the Arctic ocean-sea <span class="hlt">ice</span>-atmosphere (OSA) interface, with implications for primary- and secondary producers in the <span class="hlt">ice</span> and the underlying water column. Changes in the Arctic MIZ were interpreted for the period 1979-2010, based on best-fit regressions for each month. <span class="hlt">Trends</span> of increasingly open water were statistically significant for each month, with quadratic fit for August-November, illustrating particularly strong seasonal feedbacks in sea-<span class="hlt">ice</span> formation and decay. Geographic interpretations of physical and biological changes were based on comparison of regions with significant changes in sea <span class="hlt">ice</span>: (1) The Pacific Sector of the Arctic Ocean including the Canada Basin and the Beaufort, Chukchi and East Siberian seas; (2) The Canadian Arctic Archipelago; (3) Baffin Bay and Hudson Bay; and (4) the Barents and Kara seas. Changes in <span class="hlt">ice</span> conditions in the Barents sea/Kara sea region appear to be primarily forced by ocean heat fluxes during winter, whereas changes in the other sectors appear to be more summer-autumn related and primarily atmospherically forced. Effects of seasonal and regional changes in OSA-system with regard to increased open water were summarized for photosynthetically available radiation, nutrient delivery to the euphotic zone, primary production of <span class="hlt">ice</span> algae and phytoplankton, <span class="hlt">ice</span>-associated fauna and zooplankton, and gas exchange of CO2. Changes in the physical factors varied amongst regions, and showed direct effects on organisms linked to sea <span class="hlt">ice</span>. Zooplankton species appear to be more flexible and likely able to adapt to variability in the onset of primary production. The major changes identified for the <span class="hlt">ice</span>-associated ecosystem are with regard to production timing and abundance or biomass of <span class="hlt">ice</span> flora and fauna, which are related to</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170003145','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170003145"><span>Antarctic Sea-<span class="hlt">Ice</span> Freeboard and Estimated Thickness from NASA's ICESat and <span class="hlt">Ice</span>Bridge Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Yi, Donghui; Kurtz, Nathan; Harbeck, Jeremy; Manizade, Serdar; Hofton, Michelle; Cornejo, Helen G.; Zwally, H. Jay; Robbins, John</p> <p>2016-01-01</p> <p>ICESat completed 18 observational campaigns during its lifetime from 2003 to 2009. Data from all of the 18 campaign periods are used in this study. Most of the operational periods were between 34 and 38 days long. Because of laser failure and orbit transition from 8-day to 91-day orbit, there were four periods lasting 57, 16, 23, and 12 days. <span class="hlt">Ice</span>Bridge data from 2009, 2010, and 2011 are used in this study. Since 2009, there are 19 Airborne Topographic Mapper (ATM) campaigns, and eight Land, Vegetation, and <span class="hlt">Ice</span> Sensor (LVIS) campaigns over the Antarctic sea <span class="hlt">ice</span>. Freeboard heights are derived from ICESat, ATM and LVIS elevation and waveform data. With nominal densities of snow, water, and sea <span class="hlt">ice</span>, combined with snow depth data from AMSR-E/AMSR2 passive microwave observation over the southern ocean, sea-<span class="hlt">ice</span> thickness is derived from the freeboard. Combined with AMSR-E/AMSR2 <span class="hlt">ice</span> concentration, sea-<span class="hlt">ice</span> area and volume are also calculated. During the 2003-2009 period, sea-<span class="hlt">ice</span> freeboard and thickness distributions show clear seasonal variations that reflect the yearly cycle of the growth and decay of the Antarctic pack <span class="hlt">ice</span>. We found no significant <span class="hlt">trend</span> of thickness or area for the Antarctic sea <span class="hlt">ice</span> during the ICESat period. <span class="hlt">Ice</span>Bridge sea <span class="hlt">ice</span> freeboard and thickness data from 2009 to 2011 over the Weddell Sea and Amundsen and Bellingshausen Seas are compared with the ICESat results.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/17781630','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/17781630"><span>The surface of the <span class="hlt">ice</span>-age Earth.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p></p> <p>1976-03-19</p> <p>In the Northern Hemisphere the 18,000 B.P. world differed strikingly from the present in the huge land-based <span class="hlt">ice</span> sheets, reaching approximately 3 km in thickness, and in a dramatic increase in the <span class="hlt">extent</span> of pack <span class="hlt">ice</span> and marine-based <span class="hlt">ice</span> sheets. In the Southern Hemisphere the most striking contrast was the greater <span class="hlt">extent</span> of sea <span class="hlt">ice</span>. On land, grasslands, steppes, and deserts spread at the expense of forests. This change in vegetation, together with extensive areas of permanent <span class="hlt">ice</span> and sandy outwash plains, caused an increase in global surface albedo over modern values. Sea level was lower by at least 85 m. The 18,000 B.P. oceans were characterized by: (i) marked steepening of thermal gradients along polar frontal systems, particularly in the North Atlantic and Antarctic; (ii) an equatorward displacement of polar frontal systems; (iii) general cooling of most surface waters, with a global average of -2.3 degrees C; (iv) increased cooling and up-welling along equatorial divergences in the Pacific and Atlantic; (v) low temperatures extending equatorward along the western coast of Africa, Australia, and South America, indicating increased upwelling and advection of cool waters; and (vi) nearly stable positions and temperatures of the central gyres in the subtropical Atlantic, Pacific, and Indian oceans.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/6085044-arctic-ice-shelves-ice-islands-origin-growth-disintegration-physical-characteristics-structural-stratigraphic-variability-dynamics','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/6085044-arctic-ice-shelves-ice-islands-origin-growth-disintegration-physical-characteristics-structural-stratigraphic-variability-dynamics"><span>Arctic <span class="hlt">ice</span> shelves and <span class="hlt">ice</span> islands: Origin, growth and disintegration, physical characteristics, structural-stratigraphic variability, and dynamics</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Jeffries, M.O.</p> <p>1992-08-01</p> <p><span class="hlt">Ice</span> shelves are thick, floating <span class="hlt">ice</span> masses most often associated with Antarctica where they are seaward extensions of the grounded Antarctic <span class="hlt">ice</span> sheet and sources of many icebergs. However, there are also <span class="hlt">ice</span> shelves in the Arctic, primarily located along the north coast of Ellesmere Island in the Canadian High Arctic. The only <span class="hlt">ice</span> shelves in North America and the most extensive in the north polar region, the Ellesmere <span class="hlt">ice</span> shelves originate from glaciers and from sea <span class="hlt">ice</span> and are the source of <span class="hlt">ice</span> islands, the tabular icebergs of the Arctic Ocean. The present state of knowledge and understanding ofmore » these <span class="hlt">ice</span> features is summarized in this paper. It includes historical background to the discovery and early study of <span class="hlt">ice</span> shelves and <span class="hlt">ice</span> islands, including the use of <span class="hlt">ice</span> islands as floating laboratories for polar geophysical research. Growth mechanisms and age, the former <span class="hlt">extent</span> and the twentieth century disintegration of the Ellesmere <span class="hlt">ice</span> shelves, and the processes and mechanisms of <span class="hlt">ice</span> island calving are summarized. Surface features, thickness, thermal regime, and the size, shape, and numbers of <span class="hlt">ice</span> islands are discussed. The structural-stratigraphic variability of <span class="hlt">ice</span> islands and <span class="hlt">ice</span> shelves and the complex nature of their growth and development are described. Large-scale and small-scale dynamics of <span class="hlt">ice</span> islands are described, and the results of modeling their drift and recurrence intervals are presented. The conclusion identifies some unanswered questions and future research opportunities and needs. 97 refs., 18 figs.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140017824','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140017824"><span>Changes in Arctic and Antarctic Sea <span class="hlt">Ice</span> as a Microcosm of Global Climate Change</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>2014-01-01</p> <p>Polar sea <span class="hlt">ice</span> is a key element of the climate system and has now been monitored through satellite observations for over three and a half decades. The satellite observations reveal considerable information about polar <span class="hlt">ice</span> and its changes since the late 1970s, including a prominent downward <span class="hlt">trend</span> in Arctic sea <span class="hlt">ice</span> coverage and a much lesser upward <span class="hlt">trend</span> in Antarctic sea <span class="hlt">ice</span> coverage, illustrative of the important fact that climate change entails spatial contrasts. The decreasing <span class="hlt">ice</span> coverage in the Arctic corresponds well with contemporaneous Arctic warming and exhibits particularly large decreases in the summers of 2007 and 2012, influenced by both preconditioning and atmospheric conditions. The increasing <span class="hlt">ice</span> coverage in the Antarctic is not as readily explained, but spatial differences in the Antarctic <span class="hlt">trends</span> suggest a possible connection with atmospheric circulation changes that have perhaps been influenced by the Antarctic ozone hole. The changes in the polar <span class="hlt">ice</span> covers and the issues surrounding those changes have many commonalities with broader climate changes and their surrounding issues, allowing the sea <span class="hlt">ice</span> changes to be viewed in some important ways as a microcosm of global climate change.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010037604','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010037604"><span>Satellite Remote Sensing: Passive-Microwave Measurements of Sea <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.; Zukor, Dorothy J. (Technical Monitor)</p> <p>2001-01-01</p> <p>Satellite passive-microwave measurements of sea <span class="hlt">ice</span> have provided global or near-global sea <span class="hlt">ice</span> data for most of the period since the launch of the Nimbus 5 satellite in December 1972, and have done so with horizontal resolutions on the order of 25-50 km and a frequency of every few days. These data have been used to calculate sea <span class="hlt">ice</span> concentrations (percent areal coverages), sea <span class="hlt">ice</span> <span class="hlt">extents</span>, the length of the sea <span class="hlt">ice</span> season, sea <span class="hlt">ice</span> temperatures, and sea <span class="hlt">ice</span> velocities, and to determine the timing of the seasonal onset of melt as well as aspects of the <span class="hlt">ice</span>-type composition of the sea <span class="hlt">ice</span> cover. In each case, the calculations are based on the microwave emission characteristics of sea <span class="hlt">ice</span> and the important contrasts between the microwave emissions of sea <span class="hlt">ice</span> and those of the surrounding liquid-water medium.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_18 --> <div id="page_19" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="361"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29621173','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29621173"><span>Statistical Analysis of SSMIS Sea <span class="hlt">Ice</span> Concentration Threshold at the Arctic Sea <span class="hlt">Ice</span> Edge during Summer Based on MODIS and Ship-Based Observational Data.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Ji, Qing; Li, Fei; Pang, Xiaoping; Luo, Cong</p> <p>2018-04-05</p> <p>The threshold of sea <span class="hlt">ice</span> concentration (SIC) is the basis for accurately calculating sea <span class="hlt">ice</span> <span class="hlt">extent</span> based on passive microwave (PM) remote sensing data. However, the PM SIC threshold at the sea <span class="hlt">ice</span> edge used in previous studies and released sea <span class="hlt">ice</span> products has not always been consistent. To explore the representable value of the PM SIC threshold corresponding on average to the position of the Arctic sea <span class="hlt">ice</span> edge during summer in recent years, we extracted sea <span class="hlt">ice</span> edge boundaries from the Moderate-resolution Imaging Spectroradiometer (MODIS) sea <span class="hlt">ice</span> product (MOD29 with a spatial resolution of 1 km), MODIS images (250 m), and sea <span class="hlt">ice</span> ship-based observation points (1 km) during the fifth (CHINARE-2012) and sixth (CHINARE-2014) Chinese National Arctic Research Expeditions, and made an overlay and comparison analysis with PM SIC derived from Special Sensor Microwave Imager Sounder (SSMIS, with a spatial resolution of 25 km) in the summer of 2012 and 2014. Results showed that the average SSMIS SIC threshold at the Arctic sea <span class="hlt">ice</span> edge based on <span class="hlt">ice</span>-water boundary lines extracted from MOD29 was 33%, which was higher than that of the commonly used 15% discriminant threshold. The average SIC threshold at sea <span class="hlt">ice</span> edge based on <span class="hlt">ice</span>-water boundary lines extracted by visual interpretation from four scenes of the MODIS image was 35% when compared to the average value of 36% from the MOD29 extracted <span class="hlt">ice</span> edge pixels for the same days. The average SIC of 31% at the sea <span class="hlt">ice</span> edge points extracted from ship-based observations also confirmed that choosing around 30% as the SIC threshold during summer is recommended for sea <span class="hlt">ice</span> <span class="hlt">extent</span> calculations based on SSMIS PM data. These results can provide a reference for further studying the variation of sea <span class="hlt">ice</span> under the rapidly changing Arctic.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020082883','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020082883"><span><span class="hlt">Ice</span> Shelves and Landfast <span class="hlt">Ice</span> on the Antarctic Perimeter: Revised Scope of Work</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Scambos, Ted</p> <p>2002-01-01</p> <p><span class="hlt">Ice</span> shelves respond quickly and profoundly to a warming climate. Within a decade after mean summertime temperature reaches approx. O C and persistent melt pending is observed, a rapid retreat and disintegration occurs. This link was documented for <span class="hlt">ice</span> shelves in the Antarctic Peninsula region (the Larsen 'A', 'B' and Wilkins <span class="hlt">Ice</span> shelves) by the results of a previous grant under ADRO-1. Modeling of <span class="hlt">ice</span> flow and the effects of meltwater indicated that melt pending accelerates shelf breakup by increasing fracture penetration. SAR data supplemented an AVHRR- and SSM/I-based image analysis of <span class="hlt">extent</span> and surface characteristic changes. This funded grant is a revised, scaled-down version of an earlier proposal under the ADRO-2 NRA. The overall objective remains the same: we propose to build on the previous study by examining other <span class="hlt">ice</span> shelves of the Antarctic and incorporate an examination of the climate-related characteristics of landfast <span class="hlt">ice</span>. The study now considers just a few shelf and fast <span class="hlt">ice</span> areas for study, and is funded for two years. The study regions are the northeastern Ross <span class="hlt">Ice</span> Shelf, the Larsen 'B' and 'C' shelves, fast <span class="hlt">ice</span> and floating shelf <span class="hlt">ice</span> in the Pine Island Glacier area, and fast <span class="hlt">ice</span> along the Wilkes Land coast. Further, rather than investigating a host of shelf and fast <span class="hlt">ice</span> processes, we will home in on developing a series of characteristics associated with climate change over shelf and fast <span class="hlt">ice</span> areas. Melt pending and break-up are the end stages of a response to a warming climate that may begin with increased melt event frequency (which changes both albedo and emissivity temporarily), changing firn backscatter (due to percolation features), and possibly increased rifting of the shelf surface. Fast <span class="hlt">ice</span> may show some of these same processes on a seasonal timescale, providing insight into shelf evolution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3629225','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3629225"><span><span class="hlt">Trends</span> in North American Newspaper Reporting of Brain Injury in <span class="hlt">Ice</span> Hockey</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Cusimano, Michael D.; Sharma, Bhanu; Lawrence, David W.; Ilie, Gabriela; Silverberg, Sarah; Jones, Rochelle</p> <p>2013-01-01</p> <p>The frequency and potential long-term effects of sport-related traumatic brain injuries (TBI) make it a major public health concern. The culture within contact sports, such as <span class="hlt">ice</span> hockey, encourages aggression that puts youth at risk of TBI such as concussion. Newspaper reports play an important role in conveying and shaping the culture around health-related behaviors. We qualitatively studied reports about sport-related TBI in four major North American newspapers over the last quarter-century. We used the grounded-theory approach to identify major themes and then did a content analysis to compare the frequency of key themes between 1998–2000 and 2009–2011. The major themes were: perceptions of brain injury, aggression, equipment, rules and regulations, and youth hockey. Across the full study period, newspaper articles from Canada and America portrayed violence and aggression that leads to TBI both as integral to hockey and as an unavoidable risk associated with playing the game. They also condemned violence in <span class="hlt">ice</span> hockey, criticized the administrative response to TBI, and recognized the significance of TBI. In Canada, aggression was reported more often recently and there was a distinctive shift in portraying protective equipment as a solution to TBI in earlier years to a potential contributing factor to TBI later in the study period. American newspapers gave a greater attention to ‘perception of risks’ and the role of protective equipment, and discussed TBI in a broader context in the recent time period. Newspapers from both countries showed similar recent <span class="hlt">trends</span> in regards to a need for rule changes to curb youth sport-related TBI. This study provides a rich description of the reporting around TBI in contact sport. Understanding this reporting is important for evaluating whether the dangers of sport-related TBI are being appropriately communicated by the media. PMID:23613957</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23613957','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23613957"><span><span class="hlt">Trends</span> in North American newspaper reporting of brain injury in <span class="hlt">ice</span> hockey.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Cusimano, Michael D; Sharma, Bhanu; Lawrence, David W; Ilie, Gabriela; Silverberg, Sarah; Jones, Rochelle</p> <p>2013-01-01</p> <p>The frequency and potential long-term effects of sport-related traumatic brain injuries (TBI) make it a major public health concern. The culture within contact sports, such as <span class="hlt">ice</span> hockey, encourages aggression that puts youth at risk of TBI such as concussion. Newspaper reports play an important role in conveying and shaping the culture around health-related behaviors. We qualitatively studied reports about sport-related TBI in four major North American newspapers over the last quarter-century. We used the grounded-theory approach to identify major themes and then did a content analysis to compare the frequency of key themes between 1998-2000 and 2009-2011. The major themes were: perceptions of brain injury, aggression, equipment, rules and regulations, and youth hockey. Across the full study period, newspaper articles from Canada and America portrayed violence and aggression that leads to TBI both as integral to hockey and as an unavoidable risk associated with playing the game. They also condemned violence in <span class="hlt">ice</span> hockey, criticized the administrative response to TBI, and recognized the significance of TBI. In Canada, aggression was reported more often recently and there was a distinctive shift in portraying protective equipment as a solution to TBI in earlier years to a potential contributing factor to TBI later in the study period. American newspapers gave a greater attention to 'perception of risks' and the role of protective equipment, and discussed TBI in a broader context in the recent time period. Newspapers from both countries showed similar recent <span class="hlt">trends</span> in regards to a need for rule changes to curb youth sport-related TBI. This study provides a rich description of the reporting around TBI in contact sport. Understanding this reporting is important for evaluating whether the dangers of sport-related TBI are being appropriately communicated by the media.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.C43A0585U','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.C43A0585U"><span>Changes and variations in the turning angle of Arctic sea <span class="hlt">ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ukita, J.; Honda, M.; Ishizuka, S.</p> <p>2012-12-01</p> <p>The motion of sea <span class="hlt">ice</span> is under influences of forcing from winds and currents and of sea <span class="hlt">ice</span> properties. In facing rapidly changing Arctic climate we are interested in whether we observe and quantify changes in sea <span class="hlt">ice</span> conditions reflected in its velocity field. Theoretical consideration on the freedrift model predicts a change in the sea <span class="hlt">ice</span> turning angle with respect to the direction of forcing wind in association with thinning sea <span class="hlt">ice</span> thickness. Possible changes in atmospheric and ocean boundary layer conditions may be reflected in the sea <span class="hlt">ice</span> turning angle through modification of both atmospheric and oceanic Ekman spirals. With these in mind this study examines statistical properties of the turning angle of the Arctic sea <span class="hlt">ice</span> and compares them with atmospheric/<span class="hlt">ice</span>/ocean conditions for the period of 1979-2010 on the basis of IABP buoy data. Preliminary results indicate that over this period the turning angle has varying <span class="hlt">trends</span> depending on different seasons. We found weakly significant (>90% level) changes in the turning angle from August to October with the maximum <span class="hlt">trend</span> in October. The direction of <span class="hlt">trends</span> is counter-clockwise with respect to the geostrophic wind direction, which is consistent with the thinning of sea <span class="hlt">ice</span>. The interannual variability of the turning angle for this peak season of the reduced sea <span class="hlt">ice</span> cover is not the same as that of the Arctic SIE. However, in recent years the turning angle appears to covary with the surface air temperature, providing supporting evidence for the relationship between the angle and sea <span class="hlt">ice</span> thickness. In the presentation we will provide results on the relationships between the turning angle and atmospheric and oceanic variables and further discuss their implications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA601281','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA601281"><span>Coupling of Waves, Turbulence and Thermodynamics Across the Marginal <span class="hlt">Ice</span> Zone</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2013-09-30</p> <p>under-predict the observed <span class="hlt">trend</span> of declining sea <span class="hlt">ice</span> area over the last decade. A potential explanation for this under-prediction is that models...are missing important feedbacks within the ocean- <span class="hlt">ice</span> system. Results from the proposed research will contribute to improving the upper ocean and sea ...and solar-radiation-driven thermodynamic forcing in the marginal <span class="hlt">ice</span> zone. Within the MIZ, the ocean- <span class="hlt">ice</span> - albedo feedback mechanism is coupled to <span class="hlt">ice</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160013301&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsea','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160013301&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsea"><span>Assessment of Arctic and Antarctic Sea <span class="hlt">Ice</span> Predictability in CMIP5 Decadal Hindcasts</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Yang, Chao-Yuan; Liu, Jiping (Inventor); Hu, Yongyun; Horton, Radley M.; Chen, Liqi; Cheng, Xiao</p> <p>2016-01-01</p> <p>This paper examines the ability of coupled global climate models to predict decadal variability of Arctic and Antarctic sea <span class="hlt">ice</span>. We analyze decadal hindcasts/predictions of 11 Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Decadal hindcasts exhibit a large multimodel spread in the simulated sea <span class="hlt">ice</span> <span class="hlt">extent</span>, with some models deviating significantly from the observations as the predicted <span class="hlt">ice</span> <span class="hlt">extent</span> quickly drifts away from the initial constraint. The anomaly correlation analysis between the decadal hindcast and observed sea <span class="hlt">ice</span> suggests that in the Arctic, for most models, the areas showing significant predictive skill become broader associated with increasing lead times. This area expansion is largely because nearly all the models are capable of predicting the observed decreasing Arctic sea <span class="hlt">ice</span> cover. Sea <span class="hlt">ice</span> <span class="hlt">extent</span> in the North Pacific has better predictive skill than that in the North Atlantic (particularly at a lead time of 3-7 years), but there is a reemerging predictive skill in the North Atlantic at a lead time of 6-8 years. In contrast to the Arctic, Antarctic sea <span class="hlt">ice</span> decadal hindcasts do not show broad predictive skill at any timescales, and there is no obvious improvement linking the areal <span class="hlt">extent</span> of significant predictive skill to lead time increase. This might be because nearly all the models predict a retreating Antarctic sea <span class="hlt">ice</span> cover, opposite to the observations. For the Arctic, the predictive skill of the multi-model ensemble mean outperforms most models and the persistence prediction at longer timescales, which is not the case for the Antarctic. Overall, for the Arctic, initialized decadal hindcasts show improved predictive skill compared to uninitialized simulations, although this improvement is not present in the Antarctic.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22232652','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22232652"><span>Structure of <span class="hlt">ice</span> crystallized from supercooled water.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Malkin, Tamsin L; Murray, Benjamin J; Brukhno, Andrey V; Anwar, Jamshed; Salzmann, Christoph G</p> <p>2012-01-24</p> <p>The freezing of water to <span class="hlt">ice</span> is fundamentally important to fields as diverse as cloud formation to cryopreservation. At ambient conditions, <span class="hlt">ice</span> is considered to exist in two crystalline forms: stable hexagonal <span class="hlt">ice</span> and metastable cubic <span class="hlt">ice</span>. Using X-ray diffraction data and Monte Carlo simulations, we show that <span class="hlt">ice</span> that crystallizes homogeneously from supercooled water is neither of these phases. The resulting <span class="hlt">ice</span> is disordered in one dimension and therefore possesses neither cubic nor hexagonal symmetry and is instead composed of randomly stacked layers of cubic and hexagonal sequences. We refer to this <span class="hlt">ice</span> as stacking-disordered <span class="hlt">ice</span> I. Stacking disorder and stacking faults have been reported earlier for metastable <span class="hlt">ice</span> I, but only for <span class="hlt">ice</span> crystallizing in mesopores and in samples recrystallized from high-pressure <span class="hlt">ice</span> phases rather than in water droplets. Review of the literature reveals that almost all <span class="hlt">ice</span> that has been identified as cubic <span class="hlt">ice</span> in previous diffraction studies and generated in a variety of ways was most likely stacking-disordered <span class="hlt">ice</span> I with varying degrees of stacking disorder. These findings highlight the need to reevaluate the physical and thermodynamic properties of this metastable <span class="hlt">ice</span> as a function of the nature and <span class="hlt">extent</span> of stacking disorder using well-characterized samples.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3268266','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3268266"><span>Structure of <span class="hlt">ice</span> crystallized from supercooled water</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Malkin, Tamsin L.; Murray, Benjamin J.; Brukhno, Andrey V.; Anwar, Jamshed; Salzmann, Christoph G.</p> <p>2012-01-01</p> <p>The freezing of water to <span class="hlt">ice</span> is fundamentally important to fields as diverse as cloud formation to cryopreservation. At ambient conditions, <span class="hlt">ice</span> is considered to exist in two crystalline forms: stable hexagonal <span class="hlt">ice</span> and metastable cubic <span class="hlt">ice</span>. Using X-ray diffraction data and Monte Carlo simulations, we show that <span class="hlt">ice</span> that crystallizes homogeneously from supercooled water is neither of these phases. The resulting <span class="hlt">ice</span> is disordered in one dimension and therefore possesses neither cubic nor hexagonal symmetry and is instead composed of randomly stacked layers of cubic and hexagonal sequences. We refer to this <span class="hlt">ice</span> as stacking-disordered <span class="hlt">ice</span> I. Stacking disorder and stacking faults have been reported earlier for metastable <span class="hlt">ice</span> I, but only for <span class="hlt">ice</span> crystallizing in mesopores and in samples recrystallized from high-pressure <span class="hlt">ice</span> phases rather than in water droplets. Review of the literature reveals that almost all <span class="hlt">ice</span> that has been identified as cubic <span class="hlt">ice</span> in previous diffraction studies and generated in a variety of ways was most likely stacking-disordered <span class="hlt">ice</span> I with varying degrees of stacking disorder. These findings highlight the need to reevaluate the physical and thermodynamic properties of this metastable <span class="hlt">ice</span> as a function of the nature and <span class="hlt">extent</span> of stacking disorder using well-characterized samples. PMID:22232652</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C43B0393W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C43B0393W"><span>Arctic Sea <span class="hlt">Ice</span> Predictability and the Sea <span class="hlt">Ice</span> Prediction Network</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wiggins, H. V.; Stroeve, J. C.</p> <p>2014-12-01</p> <p>Drastic reductions in Arctic sea <span class="hlt">ice</span> cover have increased the demand for Arctic sea <span class="hlt">ice</span> predictions by a range of stakeholders, including local communities, resource managers, industry and the public. The science of sea-<span class="hlt">ice</span> prediction has been challenged to keep up with these developments. Efforts such as the SEARCH Sea <span class="hlt">Ice</span> Outlook (SIO; http://www.arcus.org/sipn/sea-<span class="hlt">ice</span>-outlook) and the Sea <span class="hlt">Ice</span> for Walrus Outlook have provided a forum for the international sea-<span class="hlt">ice</span> prediction and observing community to explore and compare different approaches. The SIO, originally organized by the Study of Environmental Change (SEARCH), is now managed by the new Sea <span class="hlt">Ice</span> Prediction Network (SIPN), which is building a collaborative network of scientists and stakeholders to improve arctic sea <span class="hlt">ice</span> prediction. The SIO synthesizes predictions from a variety of methods, including heuristic and from a statistical and/or dynamical model. In a recent study, SIO data from 2008 to 2013 were analyzed. The analysis revealed that in some years the predictions were very successful, in other years they were not. Years that were anomalous compared to the long-term <span class="hlt">trend</span> have proven more difficult to predict, regardless of which method was employed. This year, in response to feedback from users and contributors to the SIO, several enhancements have been made to the SIO reports. One is to encourage contributors to provide spatial probability maps of sea <span class="hlt">ice</span> cover in September and the first day each location becomes <span class="hlt">ice</span>-free; these are an example of subseasonal to seasonal, local-scale predictions. Another enhancement is a separate analysis of the modeling contributions. In the June 2014 SIO report, 10 of 28 outlooks were produced from models that explicitly simulate sea <span class="hlt">ice</span> from dynamic-thermodynamic sea <span class="hlt">ice</span> models. Half of the models included fully-coupled (atmosphere, <span class="hlt">ice</span>, and ocean) models that additionally employ data assimilation. Both of these subsets (models and coupled models with data</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A13A2043L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A13A2043L"><span>The Characteristics of <span class="hlt">Ice</span> Cloud Properties in China Derived from DARDAR data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lin, T.; Zheng, Y.</p> <p>2017-12-01</p> <p><span class="hlt">Ice</span> clouds play an important role in modulating the Earth radiation budget and global hydrological cycle.Thus,study the properties of <span class="hlt">ice</span> clouds has the vital significance on the interaction between the atmospheric models,cloud,radiation and climate .The world has explore the combination of two or several kinds of sensor data to solve the complementary strengths and error reduction to improve accuracy of <span class="hlt">ice</span> cloud at the present , but for China ,has be lack of research on combination sensor data to analysis properties of <span class="hlt">ice</span> cloud.To reach a wider range of <span class="hlt">ice</span> cloud, a combination of the CloudSat radar and the CALIPSO lidar is used to derive <span class="hlt">ice</span> cloud properties. These products include the radar/lidar product (DARDAR) developed at the University of Reading.The China probability distribution of <span class="hlt">ice</span> cloud occurrence frequency, <span class="hlt">ice</span> water path, <span class="hlt">ice</span> water content and <span class="hlt">ice</span> cloud effective radius were presented based on DARDAR data from 2012 to 2016,the distribution and vertical sturctures was discussed.The results indicate that the <span class="hlt">ice</span> cloud occurrence frequency distribution takes on ascend <span class="hlt">trend</span> in the last 4 years and has obvious seasonal variation, the high concentration area in the northeastern part of the Tibetan Plateau,<span class="hlt">ice</span> cloud occurrence frequency is relatively high in northwest area.the increased of <span class="hlt">ice</span> cloud occurrence frequency play an integral role of the climate warming in these four years; the general <span class="hlt">trend</span> for the <span class="hlt">ice</span> water path is southeast area bigger than northwest area, in winter the IWP is the smallest, biggest in summer; the IWC is the biggest in summer, and the vertical height distribution higher than other seasons; <span class="hlt">ice</span> cloud effective radius and <span class="hlt">ice</span> water content had similar <span class="hlt">trend</span>..There were slight declines in <span class="hlt">ice</span> cloud effective radius with increase height of China,in the summer <span class="hlt">ice</span> effective radius is generally larger.The <span class="hlt">ice</span> cloud impact Earth radiation via their albedo an greenhouse effects, that is, cooling the Earth by reflecting solar</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20010090331&hterms=BALANCE+SHEET&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DBALANCE%2BSHEET','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20010090331&hterms=BALANCE+SHEET&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DBALANCE%2BSHEET"><span>Estimates of <span class="hlt">Ice</span> Sheet Mass Balance from Satellite Altimetry: Past and Future</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zwally, H. Jay; Zukor, Dorothy J. (Technical Monitor)</p> <p>2001-01-01</p> <p>A major uncertainty in predicting sea level rise is the sensitivity of <span class="hlt">ice</span> sheet mass balance to climate change, as well as the uncertainty in present mass balance. Since the annual water exchange is about 8 mm of global sea level equivalent, the 20% uncertainty in current mass balance corresponds to 1.6 mm/yr in sea level change. Furthermore, estimates of the sensitivity of the mass balance to temperature change range from perhaps as much as - 10% to + 10% per K. A principal purpose of obtaining <span class="hlt">ice</span> sheet elevation changes from satellite altimetry has been estimation of the current <span class="hlt">ice</span> sheet mass balance. Limited information on <span class="hlt">ice</span> sheet elevation change and their implications about mass balance have been reported by several investigators from radar altimetry (Seasat, Geosat, ERS-1&2). Analysis of ERS-1&2 data over Greenland for 7 years from 1992 to 1999 shows mixed patterns of <span class="hlt">ice</span> elevation increases and decreases that are significant in terms of regional-scale mass balances. Observed seasonal and interannual variations in <span class="hlt">ice</span> surface elevation are larger than previously expected because of seasonal and interannUal variations in precipitation, melting, and firn compaction. In the accumulation zone, the variations in firn compaction are modeled as a function of temperature leaving variations in precipitation and the mass balance <span class="hlt">trend</span>. Significant interannual variations in elevation in some locations, in particular the difference in <span class="hlt">trends</span> from 1992 to 1995 compared to 1995 to 1999, can be explained by changes in precipitation over Greenland. Over the 7 years, <span class="hlt">trends</span> in elevation are mostly positive at higher elevations and negative at lower elevations. In addition, <span class="hlt">trends</span> for the winter seasons (from a <span class="hlt">trend</span> analysis through the average winter elevations) are more positive than the corresponding <span class="hlt">trends</span> for the summer. At lower elevations, the 7-year <span class="hlt">trends</span> in some locations are strongly negative for summer and near zero or slightly positive for winter. These</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3660359','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3660359"><span>Change and Variability in East Antarctic Sea <span class="hlt">Ice</span> Seasonality, 1979/80–2009/10</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Massom, Robert; Reid, Philip; Stammerjohn, Sharon; Raymond, Ben; Fraser, Alexander; Ushio, Shuki</p> <p>2013-01-01</p> <p>Recent analyses have shown that significant changes have occurred in patterns of sea <span class="hlt">ice</span> seasonality in West Antarctica since 1979, with wide-ranging climatic, biological and biogeochemical consequences. Here, we provide the first detailed report on long-term change and variability in annual timings of sea <span class="hlt">ice</span> advance, retreat and resultant <span class="hlt">ice</span> season duration in East Antarctica. These were calculated from satellite-derived <span class="hlt">ice</span> concentration data for the period 1979/80 to 2009/10. The pattern of change in sea <span class="hlt">ice</span> seasonality off East Antarctica comprises mixed signals on regional to local scales, with pockets of strongly positive and negative <span class="hlt">trends</span> occurring in near juxtaposition in certain regions e.g., Prydz Bay. This pattern strongly reflects change and variability in different elements of the marine “icescape”, including fast <span class="hlt">ice</span>, polynyas and the marginal <span class="hlt">ice</span> zone. A <span class="hlt">trend</span> towards shorter sea-<span class="hlt">ice</span> duration (of 1 to 3 days per annum) occurs in fairly isolated pockets in the outer pack from∼95–110°E, and in various near-coastal areas that include an area of particularly strong and persistent change near Australia's Davis Station and between the Amery and West <span class="hlt">Ice</span> Shelves. These areas are largely associated with coastal polynyas that are important as sites of enhanced sea <span class="hlt">ice</span> production/melt. Areas of positive <span class="hlt">trend</span> in <span class="hlt">ice</span> season duration are more extensive, and include an extensive zone from 160–170°E (i.e., the western Ross Sea sector) and the near-coastal zone between 40–100°E. The East Antarctic pattern is considerably more complex than the well-documented <span class="hlt">trends</span> in West Antarctica e.g., in the Antarctic Peninsula-Bellingshausen Sea and western Ross Sea sectors. PMID:23705008</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1208882-development-global-sea-ice-cice-configuration-met-office-global-coupled-model','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1208882-development-global-sea-ice-cice-configuration-met-office-global-coupled-model"><span>Development of global sea <span class="hlt">ice</span> 6.0 CICE configuration for the Met Office global coupled model</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Rae, J. . G. L; Hewitt, H. T.; Keen, A. B.; ...</p> <p>2015-03-05</p> <p>The new sea <span class="hlt">ice</span> configuration GSI6.0, used in the Met Office global coupled configuration GC2.0, is described and the sea <span class="hlt">ice</span> <span class="hlt">extent</span>, thickness and volume are compared with the previous configuration and with observationally-based datasets. In the Arctic, the sea <span class="hlt">ice</span> is thicker in all seasons than in the previous configuration, and there is now better agreement of the modelled concentration and <span class="hlt">extent</span> with the HadISST dataset. In the Antarctic, a warm bias in the ocean model has been exacerbated at the higher resolution of GC2.0, leading to a large reduction in <span class="hlt">ice</span> <span class="hlt">extent</span> and volume; further work is requiredmore » to rectify this in future configurations.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014GeoRL..41.2026W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014GeoRL..41.2026W"><span>Reconstructing lake <span class="hlt">ice</span> cover in subarctic lakes using a diatom-based inference model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Weckström, Jan; Hanhijärvi, Sami; Forsström, Laura; Kuusisto, Esko; Korhola, Atte</p> <p>2014-03-01</p> <p>A new quantitative diatom-based lake <span class="hlt">ice</span> cover inference model was developed to reconstruct past <span class="hlt">ice</span> cover histories and applied to four subarctic lakes. The used <span class="hlt">ice</span> cover model is based on a calculated melting degree day value of +130 and a freezing degree day value of -30 for each lake. The reconstructed Holocene <span class="hlt">ice</span> cover duration histories show similar <span class="hlt">trends</span> to the independently reconstructed regional air temperature history. The <span class="hlt">ice</span> cover duration was around 7 days shorter than the average <span class="hlt">ice</span> cover duration during the warmer early Holocene (approximately 10 to 6.5 calibrated kyr B.P.) and around 3-5 days longer during the cool Little <span class="hlt">Ice</span> Age (approximately 500 to 100 calibrated yr B.P.). Although the recent climate warming is represented by only 2-3 samples in the sediment series, these show a rising <span class="hlt">trend</span> in the prolonged <span class="hlt">ice</span>-free periods of up to 2 days. Diatom-based <span class="hlt">ice</span> cover inference models can provide a powerful tool to reconstruct past <span class="hlt">ice</span> cover histories in remote and sensitive areas where no measured data are available.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.U24B..02O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.U24B..02O"><span>Summer 2007 and 2008 Arctic Sea <span class="hlt">Ice</span> Loss in Context: OUTLOOK 2008</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Overland, J. E.; Eicken, H.; Wiggins, H. V.</p> <p>2008-12-01</p> <p>The Arctic is changing faster than the publication cycle for new information. In response, the SEARCH and DAMOCLES Programs initiated an OUTLOOK 2008 to provide broad-based communication and assessment within the arctic science community on the causes of rapid summer sea <span class="hlt">ice</span> loss, synthesizing information from Arctic observing networks and model simulations. The question for summer 2008 was whether the previous loss of multi-year sea <span class="hlt">ice</span> and delay in sea <span class="hlt">ice</span> formation in autumn 2007 would still allow sufficient winter growth of sea <span class="hlt">ice</span> thickness to last through the summer 2008, potentially allowing for recovery from the 2007 minimum. The answer is no; summer 2008 was a second sequential year of extremely low minimum sea <span class="hlt">ice</span> <span class="hlt">extent</span>. To organize OUTLOOK 2008, respondents were asked in May, June and July to provide a rationale and semi-quantitative assessment of arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> anticipated for September 2008. OUTLOOK 2008 supplemented information maintained by <span class="hlt">ice</span> centers, universities and other data providers. Using a range of methods, all of the approximately 20 groups responded that summer sea <span class="hlt">ice</span> would not return to climatological mean conditions, with a median response near the 2007 <span class="hlt">extent</span>. The range of responses depended on the relative weight given to "initial conditions," e.g., age and thickness of sea <span class="hlt">ice</span> at the end of spring, versus whether summer winds in 2008 would be as supportive for <span class="hlt">ice</span> loss as in 2007. Initial conditions turned out to be a primary factor for summer 2008, with implications for continued sea <span class="hlt">ice</span> loss in future years. OUTLOOK 2008 highlighted aspects of the observation and modeling efforts that require further attention such as interpretation of summer microwave signatures, in situ buoy measurements, and data assimilation in models. We appreciate the contributions from respondents and reviewers who made OUTLOOK 2008 a success.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.A54A..03R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.A54A..03R"><span>The Aeronomy of <span class="hlt">Ice</span> in the Mesosphere Mission: Science Results After Three PMC Seasons</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Russell, J. M.; Bailey, S. M.; Rusch, D.; Thomas, G. E.; Gordley, L. L.; Hervig, M. E.; Horanyi, M.</p> <p>2008-12-01</p> <p>The Aeronomy of <span class="hlt">Ice</span> in the Mesosphere (AIM) satellite was launched from Vandenberg Air Force Base in California at 1:26:03 PDT on April 25, 2007 becoming the first satellite mission dedicated to the study of Polar Mesospheric Clouds (PMCs). A Pegasus XL rocket launched the satellite into a near perfect 600 km sun synchronous circular orbit. AIM carries three instruments - a nadir imager, a solar occultation sounder and an in-situ cosmic dust detector. Brief instrument descriptions, data quality and key science results will be presented. AIM has observed three PMC seasons at this point in time including two in the northern hemisphere (2007 and 2008) and one in the south (2007/2008). The observations are providing extraordinary detail on the horizontal and vertical <span class="hlt">extent</span> of PMCs and their variability. Results show that the mesospheric <span class="hlt">ice</span> layer extends up to the mesopause, there are voids in the PMC fields of both hemispheres and for the two northern seasons, temporal <span class="hlt">trends</span> are remarkably similar.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008E%26PSL.265..246N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008E%26PSL.265..246N"><span>Conditions for a steady <span class="hlt">ice</span> sheet <span class="hlt">ice</span> shelf junction</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nowicki, S. M. J.; Wingham, D. J.</p> <p>2008-01-01</p> <p>This paper investigates the conditions under which a marine <span class="hlt">ice</span> sheet may adopt a steady profile. The <span class="hlt">ice</span> is treated as a linear viscous fluid caused to flow from a rigid base to and over water, treated as a denser but inviscid fluid. The solutions in the region around the point of flotation, or 'transition' zone, are calculated numerically. In-flow and out-flow conditions appropriate to <span class="hlt">ice</span> sheet and <span class="hlt">ice</span> shelf flow are applied at the ends of the transition zone and the rigid base is specified; the flow and steady free surfaces are determined as part of the solutions. The basal stress upstream, and the basal deflection downstream, of the flotation point are examined to determine which of these steady solutions satisfy 'contact' conditions that would prevent (i) the steady downstream basal deflection contacting the downstream base, and (ii) the upstream <span class="hlt">ice</span> commencing to float in the event it was melted at the base. In the case that the upstream bed is allowed to slide, we find only one mass flux that satisfies the contact conditions. When no sliding is allowed at the bed, however, we find a range of mass fluxes satisfy the contact conditions. The effect of 'backpressure' on the solutions is investigated, and is found to have no affect on the qualitative behaviour of the junctions. To the <span class="hlt">extent</span> that the numerical, linearly viscous treatment may be applied to the case of <span class="hlt">ice</span> flowing out over the ocean, we conclude that when sliding is present, Weertman's 'instability' hypothesis holds.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC53A0867D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC53A0867D"><span>Impacts of 1, 1.5, and 2 Degree Warming on Arctic Terrestrial Snow and Sea <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Derksen, C.; Mudryk, L.; Howell, S.; Flato, G. M.; Fyfe, J. C.; Gillett, N. P.; Sigmond, M.; Kushner, P. J.; Dawson, J.; Zwiers, F. W.; Lemmen, D.; Duguay, C. R.; Zhang, X.; Fletcher, C. G.; Dery, S. J.</p> <p>2017-12-01</p> <p>The 2015 Paris Agreement of the United Nations Framework Convention on Climate Change (UNFCCC) established the global temperature goal of "holding the increase in the global average temperature to below 2°C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5°C above pre-industrial levels." In this study, we utilize multiple gridded snow and sea <span class="hlt">ice</span> products (satellite retrievals; assimilation systems; physical models driven by reanalyses) and ensembles of climate model simulations to determine the impacts of observed warming, and project the relative impacts of the UNFCC future warming targets on Arctic seasonal terrestrial snow and sea <span class="hlt">ice</span> cover. Observed changes during the satellite era represent the response to approximately 1°C of global warming. Consistent with other studies, analysis of the observational record (1970's to present) identifies changes including a shorter snow cover duration (due to later snow onset and earlier snow melt), significant reductions in spring snow cover and summer sea <span class="hlt">ice</span> <span class="hlt">extent</span>, and the loss of a large proportion of multi-year sea <span class="hlt">ice</span>. The spatial patterns of observed snow and sea <span class="hlt">ice</span> loss are coherent across adjacent terrestrial/marine regions. There are strong pattern correlations between snow and temperature <span class="hlt">trends</span>, with weaker association between sea <span class="hlt">ice</span> and temperature due to the additional influence of dynamical effects such wind-driven redistribution of sea <span class="hlt">ice</span>. Climate model simulations from the Coupled Model Inter-comparison Project Phase 5(CMIP-5) multi-model ensemble, large initial condition ensembles of the Community Earth System Model (CESM) and Canadian Earth System Model (CanESM2) , and warming stabilization simulations from CESM were used to identify changes in snow and <span class="hlt">ice</span> under further increases to 1.5°C and 2°C warming. The model projections indicate these levels of warming will be reached over the coming 2-4 decades. Warming to 1.5°C results in an increase in the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeoRL..4411482W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeoRL..4411482W"><span>Snow Accumulation Variability Over the West Antarctic <span class="hlt">Ice</span> Sheet Since 1900: A Comparison of <span class="hlt">Ice</span> Core Records With ERA-20C Reanalysis</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, Yetang; Thomas, Elizabeth R.; Hou, Shugui; Huai, Baojuan; Wu, Shuangye; Sun, Weijun; Qi, Shanzhong; Ding, Minghu; Zhang, Yulun</p> <p>2017-11-01</p> <p>This study uses a set of 37 firn core records over the West Antarctic <span class="hlt">Ice</span> Sheet (WAIS) to test the performance of the twentieth century from the European Centre for Medium-Range Weather Forecasts (ERA-20C) reanalysis for snow accumulation and quantify temporal variability in snow accumulation since 1900. The firn cores are allocated to four geographical areas demarcated by drainage divides (i.e., Antarctic Peninsula (AP), western WAIS, central WAIS, and eastern WAIS) to calculate stacked records of regional snow accumulation. Our results show that the interannual variability in ERA-20C precipitation minus evaporation (P - E) agrees well with the corresponding <span class="hlt">ice</span> core snow accumulation composites in each of the four geographical regions, suggesting its skill for simulating snow accumulation changes before the modern satellite era (pre-1979). Snow accumulation experiences significantly positive <span class="hlt">trends</span> for the AP and eastern WAIS, a negative <span class="hlt">trend</span> for the western WAIS, and no significant <span class="hlt">trend</span> for the central WAIS from 1900 to 2010. The contrasting <span class="hlt">trends</span> are associated with changes in the large-scale moisture transport driven by a deepening of the low-pressure systems and anomalies of sea <span class="hlt">ice</span> in the Amundsen Sea Low region.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_19 --> <div id="page_20" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="381"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013JGRC..118.5899R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013JGRC..118.5899R"><span>Airborne thickness and freeboard measurements over the McMurdo <span class="hlt">Ice</span> Shelf, Antarctica, and implications for <span class="hlt">ice</span> density</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rack, Wolfgang; Haas, Christian; Langhorne, Pat J.</p> <p>2013-11-01</p> <p>We present airborne measurements to investigate the thickness of the western McMurdo <span class="hlt">Ice</span> Shelf in the western Ross Sea, Antarctica. Because of basal accretion of marine <span class="hlt">ice</span> and brine intrusions conventional radar systems are limited in detecting the <span class="hlt">ice</span> thickness in this area. In November 2009, we used a helicopter-borne laser and electromagnetic induction sounder (EM bird) to measure several thickness and freeboard profiles across the <span class="hlt">ice</span> shelf. The maximum electromagnetically detectable <span class="hlt">ice</span> thickness was about 55 m. Assuming hydrostatic equilibrium, the simultaneous measurement of <span class="hlt">ice</span> freeboard and thickness was used to derive bulk <span class="hlt">ice</span> densities ranging from 800 to 975 kg m-3. Densities higher than those of pure <span class="hlt">ice</span> can be largely explained by the abundance of sediments accumulated at the surface and present within the <span class="hlt">ice</span> shelf, and are likely to a smaller <span class="hlt">extent</span> related to the overestimation of <span class="hlt">ice</span> thickness by the electromagnetic induction measurement related to the presence of a subice platelet layer. The equivalent thickness of debris at a density of 2800 kg m-3 is found to be up to about 2 m thick. A subice platelet layer below the <span class="hlt">ice</span> shelf, similar to what is observed in front of the <span class="hlt">ice</span> shelf below the sea <span class="hlt">ice</span>, is likely to exist in areas of highest thickness. The thickness and density distribution reflects a picture of areas of basal freezing and supercooled <span class="hlt">Ice</span> Shelf Water emerging from below the central <span class="hlt">ice</span> shelf cavity into McMurdo Sound.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C21B0343L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C21B0343L"><span>Estimation of Arctic Sea <span class="hlt">Ice</span> Freeboard and Thickness Using CryoSat-2</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lee, S.; Im, J.; Kim, J. W.; Kim, M.; Shin, M.</p> <p>2014-12-01</p> <p>Arctic sea <span class="hlt">ice</span> is one of the significant components of the global climate system as it plays a significant role in driving global ocean circulation. Sea <span class="hlt">ice</span> <span class="hlt">extent</span> has constantly declined since 1980s. Arctic sea <span class="hlt">ice</span> thickness has also been diminishing along with the decreasing sea <span class="hlt">ice</span> <span class="hlt">extent</span>. Because <span class="hlt">extent</span> and thickness, two main characteristics of sea <span class="hlt">ice</span>, are important indicators of the polar response to on-going climate change. Sea <span class="hlt">ice</span> thickness has been measured with numerous field techniques such as surface drilling and deploying buoys. These techniques provide sparse and discontinuous data in spatiotemporal domain. Spaceborne radar and laser altimeters can overcome these limitations and have been used to estimate sea <span class="hlt">ice</span> thickness. <span class="hlt">Ice</span> Cloud and land Elevation Satellite (ICEsat), a laser altimeter provided data to detect polar area elevation change between 2003 and 2009. CryoSat-2 launched with Synthetic Aperture Radar (SAR)/Interferometric Radar Altimeter (SIRAL) in April 2010 can provide data to estimate time-series of Arctic sea <span class="hlt">ice</span> thickness. In this study, Arctic sea <span class="hlt">ice</span> freeboard and thickness between 2011 and 2014 were estimated using CryoSat-2 SAR and SARIn mode data that have sea <span class="hlt">ice</span> surface height relative to the reference ellipsoid WGS84. In order to estimate sea <span class="hlt">ice</span> thickness, freeboard, i.e., elevation difference between the top of sea <span class="hlt">ice</span> surface should be calculated. Freeboard can be estimated through detecting leads. We proposed a novel lead detection approach. CryoSat-2 profiles such as pulse peakiness, backscatter sigma-0, stack standard deviation, skewness and kurtosis were examined to distinguish leads from sea <span class="hlt">ice</span>. Near-real time cloud-free MODIS images corresponding to CryoSat-2 data measured were used to visually identify leads. Rule-based machine learning approaches such as See5.0 and random forest were used to identify leads. The proposed lead detection approach better distinguished leads from sea <span class="hlt">ice</span> than the existing approaches</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C33A0669O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C33A0669O"><span>Recent Increases in Snow Accumulation and Decreases in Sea-<span class="hlt">Ice</span> Concentration Recorded in a Coastal NW Greenland <span class="hlt">Ice</span> Core</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Osterberg, E. C.; Thompson, J. T.; Wong, G. J.; Hawley, R. L.; Kelly, M. A.; Lutz, E.; Howley, J.; Ferris, D. G.</p> <p>2013-12-01</p> <p> correlation represents a significant Na contribution from frost flowers growing on fall frazil <span class="hlt">ice</span>. Ongoing analyses will evaluate the relationship between MSA concentrations and sea <span class="hlt">ice</span> <span class="hlt">extent</span>. Our results show that a deep <span class="hlt">ice</span> core collected from this dynamic and climate-sensitive region of NW Greenland would produce a valuable record of late Holocene climate and sea <span class="hlt">ice</span> <span class="hlt">extent</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1982Natur.298..830T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1982Natur.298..830T"><span>Space Shuttle <span class="hlt">ice</span> nuclei</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Turco, R. P.; Toon, O. B.; Whitten, R. C.; Cicerone, R. J.</p> <p>1982-08-01</p> <p>Estimates are made showing that, as a consequence of rocket activity in the earth's upper atmosphere in the Shuttle era, average <span class="hlt">ice</span> nuclei concentrations in the upper atmosphere could increase by a factor of two, and that an aluminum dust layer weighing up to 1000 tons might eventually form in the lower atmosphere. The concentrations of Space Shuttle <span class="hlt">ice</span> nuclei (SSIN) in the upper troposphere and lower stratosphere were estimated by taking into account the composition of the particles, the <span class="hlt">extent</span> of surface poisoning, and the size of the particles. Calculated stratospheric size distributions at 20 km with Space Shuttle particulate injection, calculated SSIN concentrations at 10 and 20 km altitude corresponding to different water vapor/<span class="hlt">ice</span> supersaturations, and predicted SSIN concentrations in the lower stratosphere and upper troposphere are shown.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/18720967','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/18720967"><span>Workman-Reynolds freezing potential measurements between <span class="hlt">ice</span> and dilute salt solutions for single <span class="hlt">ice</span> crystal faces.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wilson, P W; Haymet, A D J</p> <p>2008-09-18</p> <p>Workman-Reynolds freezing potentials have been measured for the first time across the interface between single crystals of <span class="hlt">ice</span> 1h and dilute electrolyte solutions. The measured electric potential is a strictly nonequilibrium phenomenon and a function of the concentration of salt, freezing rate, orientation of the <span class="hlt">ice</span> crystal, and time. When all these factors are controlled, the voltage is reproducible to the <span class="hlt">extent</span> expected with <span class="hlt">ice</span> growth experiments. Zero voltage is obtained with no growth or melting. For rapidly grown <span class="hlt">ice</span> 1h basal plane in contact with a solution of 10 (-4) M NaCl the maximum voltage exceeds 30 V and decreases to zero at both high and low salt concentrations. These single-crystal experiments explain much of the data captured on this remarkable phenomenon since 1948.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016NatCC...6..479F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016NatCC...6..479F"><span>The safety band of Antarctic <span class="hlt">ice</span> shelves</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fürst, Johannes Jakob; Durand, Gaël; Gillet-Chaulet, Fabien; Tavard, Laure; Rankl, Melanie; Braun, Matthias; Gagliardini, Olivier</p> <p>2016-05-01</p> <p>The floating <span class="hlt">ice</span> shelves along the seaboard of the Antarctic <span class="hlt">ice</span> sheet restrain the outflow of upstream grounded <span class="hlt">ice</span>. Removal of these <span class="hlt">ice</span> shelves, as shown by past <span class="hlt">ice</span>-shelf recession and break-up, accelerates the outflow, which adds to sea-level rise. A key question in predicting future outflow is to quantify the <span class="hlt">extent</span> of calving that might precondition other dynamic consequences and lead to loss of <span class="hlt">ice</span>-shelf restraint. Here we delineate frontal areas that we label as `passive shelf ice’ and that can be removed without major dynamic implications, with contrasting results across the continent. The <span class="hlt">ice</span> shelves in the Amundsen and Bellingshausen seas have limited or almost no `passive’ portion, which implies that further retreat of current <span class="hlt">ice</span>-shelf fronts will yield important dynamic consequences. This region is particularly vulnerable as <span class="hlt">ice</span> shelves have been thinning at high rates for two decades and as upstream grounded <span class="hlt">ice</span> rests on a backward sloping bed, a precondition to marine <span class="hlt">ice</span>-sheet instability. In contrast to these <span class="hlt">ice</span> shelves, Larsen C <span class="hlt">Ice</span> Shelf, in the Weddell Sea, exhibits a large `passive’ frontal area, suggesting that the imminent calving of a vast tabular iceberg will be unlikely to instantly produce much dynamic change.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1914576F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1914576F"><span>CALICE: Calibrating Plant Biodiversity in Glacier <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Festi, Daniela; Cristofori, Antonella; Vernesi, Cristiano; Zerbe, Stefan; Wellstein, Camilla; Maggi, Valter; Oeggl, Klaus</p> <p>2017-04-01</p> <p>The objective of the project is to reconstruct plant biodiversity and its <span class="hlt">trend</span> archived in Alpine glacier <span class="hlt">ice</span> by pollen and eDNA (environmental DNA) during the last five decades by analyzing a 40 m <span class="hlt">ice</span> core. For our study we chose the Adamello glacier (Trentino - Südtirol, Lombardia) because of i) the good preservation conditions for pollen and eDNA in <span class="hlt">ice</span>, ii) the thickness of the <span class="hlt">ice</span> cap (270m) and iii) the expected high time resolution. The biodiversity estimates gained by pollen analysis and eDNA will be validated by historical biodiversity assessments mainly based on vegetation maps, aerial photos and vegetation surveys in the catchment area of the Adamello glacier for the last five decades. This historical reconstruction of biodiversity <span class="hlt">trends</span> will be performed on a micro-, meso- and macro-scale (5, 20-50 and 50-100 Km radius, respectively). The results will serve as a calibration data set on biodiversity for future studies, such as the second step of the coring by the POLLiCE research consortium (pollice.fmach.it). In fact, arrangements are currently been made to drill the complete <span class="hlt">ice</span> cap and retrieve a 270 m thick core which has the potential to cover a time span of minimum 400 years up to several millennia. This second stage will extend the time scale and enable the evaluation of dissimilarity/similarity of modern biodiversity in relation to Late Holocene <span class="hlt">trends</span>. Finally, we believe this case study has the potential to be applied in other glaciated areas to evaluate biodiversity for large regions (e.g. central Asian mountain ranges, Tibet and Tian Shan or the Andes).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19910004108','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19910004108"><span>A review of <span class="hlt">ice</span> accretion data from a model rotor <span class="hlt">icing</span> test and comparison with theory</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Britton, Randall K.; Bond, Thomas H.</p> <p>1991-01-01</p> <p>An experiment was conducted by the Helicopter <span class="hlt">Icing</span> Consortium (HIC) in the NASA Lewis <span class="hlt">Icing</span> Research Tunnel (IRT) in which a 1/6 scale fuselage model of a UH-60A Black Hawk helicopter with a generic rotor was subjected to a wide range of <span class="hlt">icing</span> conditions. The HIC consists of members from NASA, Bell Helicopter, Boeing Helicopter, McDonnell Douglas Helicopters, Sikorsky Aircraft, and Texas A&M University. Data was taken in the form of rotor torque, internal force balance measurements, blade strain gage loading, and two dimensional <span class="hlt">ice</span> shape tracings. A review of the <span class="hlt">ice</span> shape data is performed with special attention given to repeatability and correctness of <span class="hlt">trends</span> in terms of radial variation, rotational speed, <span class="hlt">icing</span> time, temperature, liquid water content, and volumetric median droplet size. Moreover, an indepth comparison between the experimental data and the analysis of NASA's <span class="hlt">ice</span> accretion code LEWICE is given. Finally, conclusions are drawn as to the quality of the <span class="hlt">ice</span> accretion data and the predictability of the data base as a whole. Recommendations are also given for improving data taking technique as well as potential future work.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013JGRF..118.1533D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013JGRF..118.1533D"><span>The Greenland <span class="hlt">Ice</span> Sheet's surface mass balance in a seasonally sea <span class="hlt">ice</span>-free Arctic</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Day, J. J.; Bamber, J. L.; Valdes, P. J.</p> <p>2013-09-01</p> <p>General circulation models predict a rapid decrease in sea <span class="hlt">ice</span> <span class="hlt">extent</span> with concurrent increases in near-surface air temperature and precipitation in the Arctic over the 21st century. This has led to suggestions that some Arctic land <span class="hlt">ice</span> masses may experience an increase in accumulation due to enhanced evaporation from a seasonally sea <span class="hlt">ice</span>-free Arctic Ocean. To investigate the impact of this phenomenon on Greenland <span class="hlt">Ice</span> Sheet climate and surface mass balance (SMB), a regional climate model, HadRM3, was used to force an insolation-temperature melt SMB model. A set of experiments designed to investigate the role of sea <span class="hlt">ice</span> independently from sea surface temperature (SST) forcing are described. In the warmer and wetter SI + SST simulation, Greenland experiences a 23% increase in winter SMB but 65% reduced summer SMB, resulting in a net decrease in the annual value. This study shows that sea <span class="hlt">ice</span> decline contributes to the increased winter balance, causing 25% of the increase in winter accumulation; this is largest in eastern Greenland as the result of increased evaporation in the Greenland Sea. These results indicate that the seasonal cycle of Greenland's SMB will increase dramatically as global temperatures increase, with the largest changes in temperature and precipitation occurring in winter. This demonstrates that the accurate prediction of changes in sea <span class="hlt">ice</span> cover is important for predicting Greenland SMB and <span class="hlt">ice</span> sheet evolution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C43D..01R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C43D..01R"><span>NASA <span class="hlt">Ice</span>Bridge: Scientific Insights from Airborne Surveys of the Polar Sea <span class="hlt">Ice</span> Covers</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Richter-Menge, J.; Farrell, S. L.</p> <p>2015-12-01</p> <p>The NASA Operation <span class="hlt">Ice</span>Bridge (OIB) airborne sea <span class="hlt">ice</span> surveys are designed to continue a valuable series of sea <span class="hlt">ice</span> thickness measurements by bridging the gap between NASA's <span class="hlt">Ice</span>, Cloud and Land Elevation Satellite (ICESat), which operated from 2003 to 2009, and ICESat-2, which is scheduled for launch in 2017. Initiated in 2009, OIB has conducted campaigns over the western Arctic Ocean (March/April) and Southern Oceans (October/November) on an annual basis when the thickness of sea <span class="hlt">ice</span> cover is nearing its maximum. More recently, a series of Arctic surveys have also collected observations in the late summer, at the end of the melt season. The Airborne Topographic Mapper (ATM) laser altimeter is one of OIB's primary sensors, in combination with the Digital Mapping System digital camera, a Ku-band radar altimeter, a frequency-modulated continuous-wave (FMCW) snow radar, and a KT-19 infrared radiation pyrometer. Data from the campaigns are available to the research community at: http://nsidc.org/data/icebridge/. This presentation will summarize the spatial and temporal <span class="hlt">extent</span> of the OIB campaigns and their complementary role in linking in situ and satellite measurements, advancing observations of sea <span class="hlt">ice</span> processes across all length scales. Key scientific insights gained on the state of the sea <span class="hlt">ice</span> cover will be highlighted, including snow depth, <span class="hlt">ice</span> thickness, surface roughness and morphology, and melt pond evolution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1912967S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1912967S"><span>Sediment features at the grounding zone and beneath Ekström <span class="hlt">Ice</span> Shelf, East Antarctica, imaged using on-<span class="hlt">ice</span> vibroseis.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Smith, Emma C.; Eisen, Olaf; Hofstede, Coen; Lambrecht, Astrid; Mayer, Christoph</p> <p>2017-04-01</p> <p>The grounding zone, where an <span class="hlt">ice</span> sheet becomes a floating <span class="hlt">ice</span> shelf, is known to be a key threshold region for <span class="hlt">ice</span> flow and stability. A better understanding of <span class="hlt">ice</span> dynamics and sediment transport across such zones will improve knowledge about contemporary and palaeo <span class="hlt">ice</span> flow, as well as past <span class="hlt">ice</span> <span class="hlt">extent</span>. Here we present a set of seismic reflection profiles crossing the grounding zone and continuing to the shelf edge of Ekström <span class="hlt">Ice</span> Shelf, East Antarctica. Using an on-<span class="hlt">ice</span> vibroseis source combined with a snowstreamer we have imaged a range of sub-glacial and sub-shelf sedimentary and geomorphological features; from layered sediment deposits to elongated flow features. The acoustic properties of the features as well as their morphology allow us to draw conclusions as to their material properties and origin. These results will eventually be integrated with numerical models of <span class="hlt">ice</span> dynamics to quantify past and present interactions between <span class="hlt">ice</span> and the solid Earth in East Antarctica; leading to a better understanding of future contributions of this region to sea-level rise.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1817671S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1817671S"><span>Mapping and Assessing Variability in the Antarctic Marginal <span class="hlt">Ice</span> Zone, the Pack <span class="hlt">Ice</span> and Coastal Polynyas</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stroeve, Julienne; Jenouvrier, Stephanie</p> <p>2016-04-01</p> <p>Sea <span class="hlt">ice</span> variability within the marginal <span class="hlt">ice</span> zone (MIZ) and polynyas plays an important role for phytoplankton productivity and krill abundance. Therefore mapping their spatial <span class="hlt">extent</span>, seasonal and interannual variability is essential for understanding how current and future changes in these biological active regions may impact the Antarctic marine ecosystem. Knowledge of the distribution of different <span class="hlt">ice</span> types to the total Antarctic sea <span class="hlt">ice</span> cover may also help to shed light on the factors contributing towards recent expansion of the Antarctic <span class="hlt">ice</span> cover in some regions and contraction in others. The long-term passive microwave satellite data record provides the longest and most consistent data record for assessing different <span class="hlt">ice</span> types. However, estimates of the amount of MIZ, consolidated pack <span class="hlt">ice</span> and polynyas depends strongly on what sea <span class="hlt">ice</span> algorithm is used. This study uses two popular passive microwave sea <span class="hlt">ice</span> algorithms, the NASA Team and Bootstrap to evaluate the distribution and variability in the MIZ, the consolidated pack <span class="hlt">ice</span> and coastal polynyas. Results reveal the NASA Team algorithm has on average twice the MIZ and half the consolidated pack <span class="hlt">ice</span> area as the Bootstrap algorithm. Polynya area is also larger in the NASA Team algorithm, and the timing of maximum polynya area may differ by as much as 5 months between algorithms. These differences lead to different relationships between sea <span class="hlt">ice</span> characteristics and biological processes, as illustrated here with the breeding success of an Antarctic seabird.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015GeoRL..42.8481G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015GeoRL..42.8481G"><span>Impact of aerosol emission controls on future Arctic sea <span class="hlt">ice</span> cover</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gagné, M.-Ã..; Gillett, N. P.; Fyfe, J. C.</p> <p>2015-10-01</p> <p>We examine the response of Arctic sea <span class="hlt">ice</span> to projected aerosol and aerosol precursor emission changes under the Representative Concentration Pathway (RCP) scenarios in simulations of the Canadian Earth System Model. The overall decrease in aerosol loading causes a warming, largest over the Arctic, which leads to an annual mean reduction in sea <span class="hlt">ice</span> <span class="hlt">extent</span> of approximately 1 million km2 over the 21st century in all RCP scenarios. This accounts for approximately 25% of the simulated reduction in sea <span class="hlt">ice</span> <span class="hlt">extent</span> in RCP 4.5, and 40% of the reduction in RCP 2.5. In RCP 4.5, the Arctic ocean is projected to become <span class="hlt">ice</span>-free during summertime in 2045, but it does not become <span class="hlt">ice</span>-free until 2057 in simulations with aerosol precursor emissions held fixed at 2000 values. Thus, while reductions in aerosol emissions have significant health and environmental benefits, their substantial contribution to projected Arctic climate change should not be overlooked.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012JGRF..117.2037G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012JGRF..117.2037G"><span>Investigation of land <span class="hlt">ice</span>-ocean interaction with a fully coupled <span class="hlt">ice</span>-ocean model: 1. Model description and behavior</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Goldberg, D. N.; Little, C. M.; Sergienko, O. V.; Gnanadesikan, A.; Hallberg, R.; Oppenheimer, M.</p> <p>2012-06-01</p> <p>Antarctic <span class="hlt">ice</span> shelves interact closely with the ocean cavities beneath them, with <span class="hlt">ice</span> shelf geometry influencing ocean cavity circulation, and heat from the ocean driving changes in the <span class="hlt">ice</span> shelves, as well as the grounded <span class="hlt">ice</span> streams that feed them. We present a new coupled model of an <span class="hlt">ice</span> stream-<span class="hlt">ice</span> shelf-ocean system that is used to study this interaction. The model is capable of representing a moving grounding line and dynamically responding ocean circulation within the <span class="hlt">ice</span> shelf cavity. Idealized experiments designed to investigate the response of the coupled system to instantaneous increases in ocean temperature show <span class="hlt">ice</span>-ocean system responses on multiple timescales. Melt rates and <span class="hlt">ice</span> shelf basal slopes near the grounding line adjust in 1-2 years, and downstream advection of the resulting <span class="hlt">ice</span> shelf thinning takes place on decadal timescales. Retreat of the grounding line and adjustment of grounded <span class="hlt">ice</span> takes place on a much longer timescale, and the system takes several centuries to reach a new steady state. During this slow retreat, and in the absence of either an upward-or downward-sloping bed or long-term <span class="hlt">trends</span> in ocean heat content, the <span class="hlt">ice</span> shelf and melt rates maintain a characteristic pattern relative to the grounding line.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JGRC..119.2327A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JGRC..119.2327A"><span>Implications of fractured Arctic perennial <span class="hlt">ice</span> cover on thermodynamic and dynamic sea <span class="hlt">ice</span> processes</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Asplin, Matthew G.; Scharien, Randall; Else, Brent; Howell, Stephen; Barber, David G.; Papakyriakou, Tim; Prinsenberg, Simon</p> <p>2014-04-01</p> <p>Decline of the Arctic summer minimum sea <span class="hlt">ice</span> <span class="hlt">extent</span> is characterized by large expanses of open water in the Siberian, Laptev, Chukchi, and Beaufort Seas, and introduces large fetch distances in the Arctic Ocean. Long waves can propagate deep into the pack <span class="hlt">ice</span>, thereby causing flexural swell and failure of the sea <span class="hlt">ice</span>. This process shifts the floe size diameter distribution smaller, increases floe surface area, and thereby affects sea <span class="hlt">ice</span> dynamic and thermodynamic processes. The results of Radarsat-2 imagery analysis show that a flexural fracture event which occurred in the Beaufort Sea region on 6 September 2009 affected ˜40,000 km2. Open water fractional area in the area affected initially decreased from 3.7% to 2.7%, but later increased to ˜20% following wind-forced divergence of the <span class="hlt">ice</span> pack. Energy available for lateral melting was assessed by estimating the change in energy entrainment from longwave and shortwave radiation in the mixed-layer of the ocean following flexural fracture. 11.54 MJ m-2 of additional energy for lateral melting of <span class="hlt">ice</span> floes was identified in affected areas. The impact of this process in future Arctic sea <span class="hlt">ice</span> melt seasons was assessed using estimations of earlier occurrences of fracture during the melt season, and is discussed in context with ocean heat fluxes, atmospheric mixing of the ocean mixed layer, and declining sea <span class="hlt">ice</span> cover. We conclude that this process is an important positive feedback to Arctic sea <span class="hlt">ice</span> loss, and timing of initiation is critical in how it affects sea <span class="hlt">ice</span> thermodynamic and dynamic processes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70171003','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70171003"><span>Role of ground <span class="hlt">ice</span> dynamics and ecological feedbacks in recent <span class="hlt">ice</span> wedge degradation and stabilization</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Mark Torre Jorgenson,; Mikhail Kanevskiy,; Yuri Shur,; Natalia Moskalenko,; Dana Brown,; Wickland, Kimberly P.; Striegl, Robert G.; Koch, Joshua C.</p> <p>2015-01-01</p> <p>Ground <span class="hlt">ice</span> is abundant in the upper permafrost throughout the Arctic and fundamentally affects terrain responses to climate warming. <span class="hlt">Ice</span> wedges, which form near the surface and are the dominant type of massive <span class="hlt">ice</span> in the Arctic, are particularly vulnerable to warming. Yet processes controlling <span class="hlt">ice</span> wedge degradation and stabilization are poorly understood. Here we quantified <span class="hlt">ice</span> wedge volume and degradation rates, compared ground <span class="hlt">ice</span> characteristics and thermal regimes across a sequence of five degradation and stabilization stages and evaluated biophysical feedbacks controlling permafrost stability near Prudhoe Bay, Alaska. Mean <span class="hlt">ice</span> wedge volume in the top 3 m of permafrost was 21%. Imagery from 1949 to 2012 showed thermokarst <span class="hlt">extent</span> (area of water-filled troughs) was relatively small from 1949 (0.9%) to 1988 (1.5%), abruptly increased by 2004 (6.3%) and increased slightly by 2012 (7.5%). Mean annual surface temperatures varied by 4.9°C among degradation and stabilization stages and by 9.9°C from polygon center to deep lake bottom. Mean thicknesses of the active layer, <span class="hlt">ice</span>-poor transient layer, <span class="hlt">ice</span>-rich intermediate layer, thermokarst cave <span class="hlt">ice</span>, and wedge <span class="hlt">ice</span> varied substantially among stages. In early stages, thaw settlement caused water to impound in thermokarst troughs, creating positive feedbacks that increased net radiation, soil heat flux, and soil temperatures. Plant growth and organic matter accumulation in the degraded troughs provided negative feedbacks that allowed ground <span class="hlt">ice</span> to aggrade and heave the surface, thus reducing surface water depth and soil temperatures in later stages. The ground <span class="hlt">ice</span> dynamics and ecological feedbacks greatly complicate efforts to assess permafrost responses to climate change.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JGRF..120.2280J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JGRF..120.2280J"><span>Role of ground <span class="hlt">ice</span> dynamics and ecological feedbacks in recent <span class="hlt">ice</span> wedge degradation and stabilization</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jorgenson, M. T.; Kanevskiy, M.; Shur, Y.; Moskalenko, N.; Brown, D. R. N.; Wickland, K.; Striegl, R.; Koch, J.</p> <p>2015-11-01</p> <p>Ground <span class="hlt">ice</span> is abundant in the upper permafrost throughout the Arctic and fundamentally affects terrain responses to climate warming. <span class="hlt">Ice</span> wedges, which form near the surface and are the dominant type of massive <span class="hlt">ice</span> in the Arctic, are particularly vulnerable to warming. Yet processes controlling <span class="hlt">ice</span> wedge degradation and stabilization are poorly understood. Here we quantified <span class="hlt">ice</span> wedge volume and degradation rates, compared ground <span class="hlt">ice</span> characteristics and thermal regimes across a sequence of five degradation and stabilization stages and evaluated biophysical feedbacks controlling permafrost stability near Prudhoe Bay, Alaska. Mean <span class="hlt">ice</span> wedge volume in the top 3 m of permafrost was 21%. Imagery from 1949 to 2012 showed thermokarst <span class="hlt">extent</span> (area of water-filled troughs) was relatively small from 1949 (0.9%) to 1988 (1.5%), abruptly increased by 2004 (6.3%) and increased slightly by 2012 (7.5%). Mean annual surface temperatures varied by 4.9°C among degradation and stabilization stages and by 9.9°C from polygon center to deep lake bottom. Mean thicknesses of the active layer, <span class="hlt">ice</span>-poor transient layer, <span class="hlt">ice</span>-rich intermediate layer, thermokarst cave <span class="hlt">ice</span>, and wedge <span class="hlt">ice</span> varied substantially among stages. In early stages, thaw settlement caused water to impound in thermokarst troughs, creating positive feedbacks that increased net radiation, soil heat flux, and soil temperatures. Plant growth and organic matter accumulation in the degraded troughs provided negative feedbacks that allowed ground <span class="hlt">ice</span> to aggrade and heave the surface, thus reducing surface water depth and soil temperatures in later stages. The ground <span class="hlt">ice</span> dynamics and ecological feedbacks greatly complicate efforts to assess permafrost responses to climate change.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70186594','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70186594"><span>Diminishing sea <span class="hlt">ice</span> in the western Arctic Ocean</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Stone, R.S.; Belchansky, G.I.; Drobot, Sheldon; Douglas, David C.; Levinson, D.H.; Waple, A.M.</p> <p>2004-01-01</p> <p>Since the advent of satellite passive microwave radiometry (1978), variations in sea <span class="hlt">ice</span> <span class="hlt">extent</span> and concentration have been carefully monitored from space. An estimated 7.4% decrease in sea <span class="hlt">ice</span> <span class="hlt">extent</span> has occurred in the last 25 yr (Johannessen et al. 2004), with recent record minima (e.g., Maslanik et al. 1999; Serreze et al. 2003) accounting for much of the decline. Comparisons between the time series of Arctic sea <span class="hlt">ice</span> melt dynamics and snowmelt dates at the NOAA–CMDL Barrow Observatory (BRW) reveal intriguing correlations.Melt-onset dates over sea <span class="hlt">ice</span> (Drobot and Anderson 2001) were cross correlated with the melt-date time series from BRW, and a prominent region of high correlation between snowmelt onset over sea <span class="hlt">ice</span> and the BRW record of melt dates was approximately aligned with the climatological center of the Beaufort Sea Anticyclone (BSA). The BSA induces anticyclonic <span class="hlt">ice</span> motion in the region, effectively forcing the Beaufort gyre. A weak gyre caused by a breakdown of the BSA diminishes transport of multiyear <span class="hlt">ice</span> into this region (Drobot and Maslanik 2003). Similarly, the annual snow cycle at BRW varies with the position and intensity of the BSA (Stone et al. 2002, their Fig. 6). Thus, variations in the BSA appear to have far-reaching effects on the annual accumulation and subsequent melt of snow over a large region of the western Arctic.A dramatic increase in melt season duration (Belchansky et al. 2004) was also observed within the same region of high correlation between onset of melt over the <span class="hlt">ice</span> pack and snowmelt at BRW (Fig. 5.7). By inference, this suggests linkages between factors that modulate the annual cycle of snow on land and processes that influence melting of snow and <span class="hlt">ice</span> in the western Arctic Ocean.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013SolED...5.2345S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013SolED...5.2345S"><span>Comparing a thermo-mechanical Weichselian <span class="hlt">ice</span> sheet reconstruction to GIA driven reconstructions: aspects of earth response and <span class="hlt">ice</span> configuration</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schmidt, P.; Lund, B.; Näslund, J.-O.</p> <p>2013-12-01</p> <p>In this study we compare a recent reconstruction of the Weichselian <span class="hlt">ice</span>-sheet as simulated by the University of Main <span class="hlt">ice</span>-sheet model (UMISM) to two reconstructions commonly used in glacial isostatic adjustment (GIA) modeling: <span class="hlt">ICE</span>-5G and ANU (also known as RSES). The UMISM reconstruction is carried out on a regional scale based on thermo-mechanical modelling whereas ANU and <span class="hlt">ICE</span>-5G are global models based on the sea-level equation. The Weichselian <span class="hlt">ice</span>-sheet in the three models are compared directly in terms of <span class="hlt">ice</span> volume, <span class="hlt">extent</span> and thickness, as well as in terms of predicted glacial isostatic adjustment in Fennoscandia. The three reconstructions display significant differences. UMISM and ANU includes phases of pronounced advance and retreat prior to the last glacial maximum (LGM), whereas the thickness and areal <span class="hlt">extent</span> of the <span class="hlt">ICE</span>-5G <span class="hlt">ice</span>-sheet is more or less constant up until LGM. The final retreat of the <span class="hlt">ice</span>-sheet initiates at earliest time in <span class="hlt">ICE</span>-5G and latest in UMISM, while <span class="hlt">ice</span> free conditions are reached earliest in UMISM and latest in <span class="hlt">ICE</span>-5G. The post-LGM deglaciation style also differs notably between the <span class="hlt">ice</span> models. While the UMISM simulation includes two temporary halts in the deglaciation, the later during the Younger Dryas, ANU only includes a decreased deglaciation rate during Younger Dryas and <span class="hlt">ICE</span>-5G retreats at a relatively constant pace after an initial slow phase. Moreover, ANU and <span class="hlt">ICE</span>-5G melt relatively uniformly over the entire <span class="hlt">ice</span>-sheet in contrast to UMISM which melts preferentially from the edges. We find that all three reconstructions fit the present day uplift rates over Fennoscandia and the observed relative sea-level curve along the Ångerman river equally well, albeit with different optimal earth model parameters. Given identical earth models, <span class="hlt">ICE</span>-5G predicts the fastest present day uplift rates and ANU the slowest, ANU also prefers the thinnest lithosphere. Moreover, only for ANU can a unique best fit model be determined. For UMISM and <span class="hlt">ICE</span></p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA624416','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA624416"><span>Sea <span class="hlt">Ice</span> Sensitivities in the 0.72 deg and 0.08 deg Arctic Cap Coupled HYCOM/CICE Models</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2014-09-30</p> <p>1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Sea <span class="hlt">Ice</span> Sensitivities in the 0.72°and 0.08° Arctic Cap...Arctic <span class="hlt">ice</span> <span class="hlt">extent</span>, which corresponds to the sea <span class="hlt">ice</span> that remains during the summer minimum, has decreased over the years 1979–2007 by more than 10% per...Goosse et al. 2009) with the lowest observed sea <span class="hlt">ice</span> <span class="hlt">extent</span> in the satellite record (1979-present) occurring in September 2012 (Perovich et al. 2012</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_20 --> <div id="page_21" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="401"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1997Natur.387..897L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1997Natur.387..897L"><span>Effects of sea-<span class="hlt">ice</span> <span class="hlt">extent</span> and krill or salp dominance on the Antarctic food web</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Loeb, V.; Siegel, V.; Holm-Hansen, O.; Hewitt, R.; Fraser, W.; Trivelpiece, W.; Trivelpiece, S.</p> <p>1997-06-01</p> <p>Krill (Euphausia superba) provide a direct link between primary producers and higher trophic levels in the Antarctic marine food web. The pelagic tunicate Salpa thompsoni can also be important during spring and summer through the formation of extensive and dense blooms. Although salps are not a major dietary item for Antarctic vertebrate predators,, their blooms can affect adult krill reproduction and survival of krill larvae. Here we provide data from 1995 and 1996 that support hypothesized relationships between krill, salps and region-wide sea-<span class="hlt">ice</span> conditions,. We have assessed salp consumption as a proportion of net primary production, and found correlations between herbivore densities and integrated chlorophyll-a that indicate that there is a degree of competition between krill and salps. Our analysis of the relationship between annual sea-<span class="hlt">ice</span> cover and a longer time series of air temperature measurements, indicates a decreased frequency of winters with extensive sea-<span class="hlt">ice</span> development over the last five decades. Our data suggest that decreased krill availability may affect the levels of their vertebrate predators. Regional warming and reduced krill abundance therefore affect the marine food web and krill resource management.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3365033','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3365033"><span>Pre-Partum Diet of Adult Female Bearded Seals in Years of Contrasting <span class="hlt">Ice</span> Conditions</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Hindell, Mark A.; Lydersen, Christian; Hop, Haakon; Kovacs, Kit M.</p> <p>2012-01-01</p> <p>Changing patterns of sea-<span class="hlt">ice</span> distribution and <span class="hlt">extent</span> have measurable effects on polar marine systems. Beyond the obvious impacts of key-habitat loss, it is unclear how such changes will influence <span class="hlt">ice</span>-associated marine mammals in part because of the logistical difficulties of studying foraging behaviour or other aspects of the ecology of large, mobile animals at sea during the polar winter. This study investigated the diet of pregnant bearded seals (Erignathus barbatus) during three spring breeding periods (2005, 2006 and 2007) with markedly contrasting <span class="hlt">ice</span> conditions in Svalbard using stable isotopes (δ13C and δ15N) measured in whiskers collected from their newborn pups. The δ15N values in the whiskers of individual seals ranged from 11.95 to 17.45 ‰, spanning almost 2 full trophic levels. Some seals were clearly dietary specialists, despite the species being characterised overall as a generalist predator. This may buffer bearded seal populations from the changes in prey distributions lower in the marine food web which seems to accompany continued changes in temperature and <span class="hlt">ice</span> cover. Comparisons with isotopic signatures of known prey, suggested that benthic gastropods and decapods were the most common prey. Bayesian isotopic mixing models indicated that diet varied considerably among years. In the year with most fast-<span class="hlt">ice</span> (2005), the seals had the greatest proportion of pelagic fish and lowest benthic invertebrate content, and during the year with the least <span class="hlt">ice</span> (2006), the seals ate more benthic invertebrates and less pelagic fish. This suggests that the seals fed further offshore in years with greater <span class="hlt">ice</span> cover, but moved in to the fjords when <span class="hlt">ice</span>-cover was minimal, giving them access to different types of prey. Long-term <span class="hlt">trends</span> of sea <span class="hlt">ice</span> decline, earlier <span class="hlt">ice</span> melt, and increased water temperatures in the Arctic are likely to have ecosystem-wide effects, including impacts on the forage bases of pagophilic seals. PMID:22693616</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19295608','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19295608"><span>Modelling West Antarctic <span class="hlt">ice</span> sheet growth and collapse through the past five million years.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Pollard, David; DeConto, Robert M</p> <p>2009-03-19</p> <p>The West Antarctic <span class="hlt">ice</span> sheet (WAIS), with <span class="hlt">ice</span> volume equivalent to approximately 5 m of sea level, has long been considered capable of past and future catastrophic collapse. Today, the <span class="hlt">ice</span> sheet is fringed by vulnerable floating <span class="hlt">ice</span> shelves that buttress the fast flow of inland <span class="hlt">ice</span> streams. Grounding lines are several hundred metres below sea level and the bed deepens upstream, raising the prospect of runaway retreat. Projections of future WAIS behaviour have been hampered by limited understanding of past variations and their underlying forcing mechanisms. Its variation since the Last Glacial Maximum is best known, with grounding lines advancing to the continental-shelf edges around approximately 15 kyr ago before retreating to near-modern locations by approximately 3 kyr ago. Prior collapses during the warmth of the early Pliocene epoch and some Pleistocene interglacials have been suggested indirectly from records of sea level and deep-sea-core isotopes, and by the discovery of open-ocean diatoms in subglacial sediments. Until now, however, little direct evidence of such behaviour has been available. Here we use a combined <span class="hlt">ice</span> sheet/<span class="hlt">ice</span> shelf model capable of high-resolution nesting with a new treatment of grounding-line dynamics and <span class="hlt">ice</span>-shelf buttressing to simulate Antarctic <span class="hlt">ice</span> sheet variations over the past five million years. Modelled WAIS variations range from full glacial <span class="hlt">extents</span> with grounding lines near the continental shelf break, intermediate states similar to modern, and brief but dramatic retreats, leaving only small, isolated <span class="hlt">ice</span> caps on West Antarctic islands. Transitions between glacial, intermediate and collapsed states are relatively rapid, taking one to several thousand years. Our simulation is in good agreement with a new sediment record (ANDRILL AND-1B) recovered from the western Ross Sea, indicating a long-term <span class="hlt">trend</span> from more frequently collapsed to more glaciated states, dominant 40-kyr cyclicity in the Pliocene, and major retreats at</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22693616','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22693616"><span>Pre-partum diet of adult female bearded seals in years of contrasting <span class="hlt">ice</span> conditions.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Hindell, Mark A; Lydersen, Christian; Hop, Haakon; Kovacs, Kit M</p> <p>2012-01-01</p> <p>Changing patterns of sea-<span class="hlt">ice</span> distribution and <span class="hlt">extent</span> have measurable effects on polar marine systems. Beyond the obvious impacts of key-habitat loss, it is unclear how such changes will influence <span class="hlt">ice</span>-associated marine mammals in part because of the logistical difficulties of studying foraging behaviour or other aspects of the ecology of large, mobile animals at sea during the polar winter. This study investigated the diet of pregnant bearded seals (Erignathus barbatus) during three spring breeding periods (2005, 2006 and 2007) with markedly contrasting <span class="hlt">ice</span> conditions in Svalbard using stable isotopes (δ(13)C and δ(15)N) measured in whiskers collected from their newborn pups. The δ(15)N values in the whiskers of individual seals ranged from 11.95 to 17.45 ‰, spanning almost 2 full trophic levels. Some seals were clearly dietary specialists, despite the species being characterised overall as a generalist predator. This may buffer bearded seal populations from the changes in prey distributions lower in the marine food web which seems to accompany continued changes in temperature and <span class="hlt">ice</span> cover. Comparisons with isotopic signatures of known prey, suggested that benthic gastropods and decapods were the most common prey. Bayesian isotopic mixing models indicated that diet varied considerably among years. In the year with most fast-<span class="hlt">ice</span> (2005), the seals had the greatest proportion of pelagic fish and lowest benthic invertebrate content, and during the year with the least <span class="hlt">ice</span> (2006), the seals ate more benthic invertebrates and less pelagic fish. This suggests that the seals fed further offshore in years with greater <span class="hlt">ice</span> cover, but moved in to the fjords when <span class="hlt">ice</span>-cover was minimal, giving them access to different types of prey. Long-term <span class="hlt">trends</span> of sea <span class="hlt">ice</span> decline, earlier <span class="hlt">ice</span> melt, and increased water temperatures in the Arctic are likely to have ecosystem-wide effects, including impacts on the forage bases of pagophilic seals.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010EGUGA..12.2865L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010EGUGA..12.2865L"><span>Solar cycle and long term variations of mesospheric <span class="hlt">ice</span> layers</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lübken, Franz-Josef; Berger, Uwe; Kiliani, Johannes; Baumgarten, Gerd; Fiedler, Jens; Gerding, Michael</p> <p>2010-05-01</p> <p><span class="hlt">Ice</span> layers in the summer mesosphere at middle and polar latitudes, frequently called `noctilucent clouds' (NLC) or `polar mesosphere clouds'(PMC), are considered to be sensitive indicators of long term changes in the middle atmosphere. We present a summary of long term observations from the ground and from satellites and compare with results from the LIMA model (Leibniz Institute Middle Atmosphere Model). LIMA nicely reproduces mean conditions of the summer mesopause region and also mean characteristics of <span class="hlt">ice</span> layers. LIMA nudges to ECMWF data in the troposphere and lower stratosphere which influences the background conditions in the mesosphere and thereby the morphology of <span class="hlt">ice</span> clouds. A strong correlation between temperatures and PMC altitudes is observed. Applied to historical measurements this give s negligible temperature <span class="hlt">trends</span> at PMC altitudes (approximately 0.01-0.02 K/y). Trace gas concentrations are kept constant in LIMA except for water vapor which is modified by variable solar radiation. Still, long term <span class="hlt">trends</span> in temperatures and <span class="hlt">ice</span> layer parameters are observed, consistent with observations. As will be shown, these <span class="hlt">trends</span> originate in the stratosphere. Solar cycle effects are expected in <span class="hlt">ice</span> layers due to variations in background temperatures and water paper. We will present results from LIMA regarding solar cycle variations and compare with NLC observations at our lidar stations in Kühlungsborn (54°N) and ALOMAR (69°N), and also with satellite measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.5267S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.5267S"><span>Formation of melt channels on <span class="hlt">ice</span> shelves</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sergienko, Olga</p> <p>2013-04-01</p> <p>Melt channels have been observed on <span class="hlt">ice</span> shelves experiencing strong melting in both Greenland (Petermann Glacier) and Antarctica (Pine Island Glacier). Using a fully-couple <span class="hlt">ice-shelf/sub-ice</span>-shelf-ocean flow model, it is demonstrated that these channels can form spontaneously in laterally confined <span class="hlt">ice</span> shelves. These channels have transverse <span class="hlt">extent</span> of a few kilometers and a vertical relief of about a few hundred meters. Meltrates and sea-water transport in the channels are significantly higher than in between the channels on the smooth flat <span class="hlt">ice</span> bottom. In circumstances where an <span class="hlt">ice</span> shelf has no-slip conditions at its lateral boundaries, the <span class="hlt">ice-shelf/sub-ice</span>-shelf-cavity system exhibits equilibrium periodic states, where the same configurations repetitively appear with a periodicity of about 30-35 years. This peculiar dynamics of the system has strong implications on the interpretation of the remote and in-situ observations and inferences of the system parameters (e.g., melt rates) based on these observations. For instance, the persistent temporal changes in the <span class="hlt">ice</span>-shelf thickness are caused by internal dynamics of the melt channels, and, in contrast to traditional interpretation, can be independent of the oceanic forcings.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA257132','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA257132"><span>Investigation of Antarctic Sea <span class="hlt">Ice</span> Concentration by Means of Selected Algorithms</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>1992-05-08</p> <p>Changes in areal <span class="hlt">extent</span> and concentration of sea <span class="hlt">ice</span> around Antarctica may serve as sensitive indicators of global warming . A comparison study was...occurred from July, 1987 through June, 1990. Antarctic Ocean, Antarctic regions, Global warming , Sea <span class="hlt">ice</span>-Antarctic regions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.C43D0577F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.C43D0577F"><span>Sea <span class="hlt">Ice</span> and Hydrographic Variability in the Northwest North Atlantic</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fenty, I. G.; Heimbach, P.; Wunsch, C. I.</p> <p>2010-12-01</p> <p> marginal <span class="hlt">ice</span> zone is mainly ablated via large sustained turbulent ocean enthalpy fluxes. The sensible heat required for these sustained fluxes is drawn from a reservoir of warm subsurface waters of subtropical origin entrained into the mixed layer via convective mixing. Analysis of ocean surface buoyancy fluxes during the period preceding quasi-equilibrium reveals that low-salinity upper ocean anomalies are required for <span class="hlt">ice</span> to advance seaward of the Arctic Water/Irminger Water thermohaline front in the northern Labrador Sea. Anomalous low-salinity waters inhibit mixed layer deepening, shielding the advancing <span class="hlt">ice</span> pack from the subsurface heat reservoir, and are conducive to a positive surface stratification enhancement feedback from <span class="hlt">ice</span> meltwater release. Interestingly, the climatological location of the front coincides with the minimum observed wintertime <span class="hlt">ice</span> <span class="hlt">extent</span>; positive <span class="hlt">ice</span> <span class="hlt">extent</span> anomalies may require hydrographic preconditioning. If true, the export of low-salinity anomalies from melting Arctic <span class="hlt">ice</span> associated with future warming may be predicted to lead positive <span class="hlt">ice</span> <span class="hlt">extent</span> anomalies in Labrador Sea via the positive surface stratification enhancement mechanism feedback outlined above.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1919277B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1919277B"><span>Quantifying model uncertainty in seasonal Arctic sea-<span class="hlt">ice</span> forecasts</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Blanchard-Wrigglesworth, Edward; Barthélemy, Antoine; Chevallier, Matthieu; Cullather, Richard; Fučkar, Neven; Massonnet, François; Posey, Pamela; Wang, Wanqiu; Zhang, Jinlun; Ardilouze, Constantin; Bitz, Cecilia; Vernieres, Guillaume; Wallcraft, Alan; Wang, Muyin</p> <p>2017-04-01</p> <p>Dynamical model forecasts in the Sea <span class="hlt">Ice</span> Outlook (SIO) of September Arctic sea-<span class="hlt">ice</span> <span class="hlt">extent</span> over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or post-processing techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer sea <span class="hlt">ice</span> using SIO dynamical models initialized with identical sea-<span class="hlt">ice</span> thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September sea-<span class="hlt">ice</span> volume and <span class="hlt">extent</span>, this is not the case for sea-<span class="hlt">ice</span> concentration. Additionally, forecast uncertainty of sea-<span class="hlt">ice</span> thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GeoRL..45.3255O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GeoRL..45.3255O"><span>Evaluating Impacts of Recent Arctic Sea <span class="hlt">Ice</span> Loss on the Northern Hemisphere Winter Climate Change</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ogawa, Fumiaki; Keenlyside, Noel; Gao, Yongqi; Koenigk, Torben; Yang, Shuting; Suo, Lingling; Wang, Tao; Gastineau, Guillaume; Nakamura, Tetsu; Cheung, Ho Nam; Omrani, Nour-Eddine; Ukita, Jinro; Semenov, Vladimir</p> <p>2018-04-01</p> <p>Wide disagreement among individual modeling studies has contributed to a debate on the role of recent sea <span class="hlt">ice</span> loss in the Arctic amplification of global warming and the Siberian wintertime cooling <span class="hlt">trend</span>. We perform coordinated experiments with six atmospheric general circulation models forced by the observed and climatological daily sea <span class="hlt">ice</span> concentration and sea surface temperature. The results indicate that the impact of the recent sea <span class="hlt">ice</span> decline is rather limited to the high-latitude lower troposphere in winter, and the sea <span class="hlt">ice</span> changes do not significantly lead to colder winters over Siberia. The observed wintertime Siberian temperature and corresponding circulation <span class="hlt">trends</span> are reproduced in a small number of ensemble members but not by the multimodel ensemble mean, suggesting that atmospheric internal dynamics could have played a major role in the observed <span class="hlt">trends</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.5885L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.5885L"><span>Estimation of Arctic Sea <span class="hlt">Ice</span> Freeboard and Thickness Using CryoSat-2</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lee, Sanggyun; Im, Jungho; yoon, Hyeonjin; Shin, Minso; Kim, Miae</p> <p>2014-05-01</p> <p>Arctic sea <span class="hlt">ice</span> is one of the significant components of the global climate system as it plays a significant role in driving global ocean circulation, provides a continuous insulating layer at air-sea interface, and reflects a large portion of the incoming solar radiation in Polar Regions. Sea <span class="hlt">ice</span> <span class="hlt">extent</span> has constantly declined since 1980s. Its area was the lowest ever recorded on 16 September 2012 since the satellite record began in 1979. Arctic sea <span class="hlt">ice</span> thickness has also been diminishing along with the decreasing sea <span class="hlt">ice</span> <span class="hlt">extent</span>. Because <span class="hlt">extent</span> and thickness, two main characteristics of sea <span class="hlt">ice</span>, are important indicators of the polar response to on-going climate change, there has been a great effort to quantify them using various approaches. Sea <span class="hlt">ice</span> thickness has been measured with numerous field techniques such as surface drilling and deploying buoys. These techniques provide sparse and discontinuous data in spatiotemporal domain. Spaceborne radar and laser altimeters can overcome these limitations and have been used to estimate sea <span class="hlt">ice</span> thickness. <span class="hlt">Ice</span> Cloud and land Elevation Satellite (ICEsat), a laser altimeter from National Aeronautics and Space Administration (NASA), provided data to detect polar area elevation change between 2003 and 2009. CryoSat-2 launched with Synthetic Aperture Radar (SAR)/Interferometric Radar Altimeter (SIRAL) on April 2010 can provide data to estimate time-series of Arctic sea <span class="hlt">ice</span> thickness. In this study, Arctic sea <span class="hlt">ice</span> freeboard and thickness in 2012 and 2013 were estimated using CryoSat-2 SAR mode data that has sea <span class="hlt">ice</span> surface height relative to the reference ellipsoid WGS84. In order to estimate sea <span class="hlt">ice</span> thickness, freeboard height, elevation difference between the top of sea <span class="hlt">ice</span> surface and leads should be calculated. CryoSat-2 profiles such as pulse peakiness, backscatter sigma-0, number of echoes, and significant wave height were examined to distinguish leads from sea <span class="hlt">ice</span>. Several near-real time cloud-free MODIS images as CryoSat-2</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JMS...166....4S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JMS...166....4S"><span>Modelling sea <span class="hlt">ice</span> formation in the Terra Nova Bay polynya</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sansiviero, M.; Morales Maqueda, M. Á.; Fusco, G.; Aulicino, G.; Flocco, D.; Budillon, G.</p> <p>2017-02-01</p> <p> realistic polynya <span class="hlt">extent</span> estimates. The model-derived polynya <span class="hlt">extent</span> has been validated by comparing the modelled sea <span class="hlt">ice</span> concentration against MODIS high resolution satellite images, confirming that the model is able to reproduce reasonably well the TNB polynya evolution in terms of both shape and <span class="hlt">extent</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016DSRII.131....7H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016DSRII.131....7H"><span>SIPEX 2012: Extreme sea-<span class="hlt">ice</span> and atmospheric conditions off East Antarctica</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Heil, P.; Stammerjohn, S.; Reid, P.; Massom, R. A.; Hutchings, J. K.</p> <p>2016-09-01</p> <p>In 2012, Antarctic sea-<span class="hlt">ice</span> coverage was marked by weak annual-mean climate anomalies that consisted of opposing anomalies early and late in the year (some setting new records) which were interspersed by near-average conditions for most of the austral autumn and winter. Here, we investigate the ocean-<span class="hlt">ice</span>-atmosphere system off East Antarctica, prior to and during the Sea <span class="hlt">Ice</span> Physics and Ecosystems eXperiment [SIPEX] 2012, by exploring relationships between atmospheric and oceanic forcing together with the sea-<span class="hlt">ice</span> and snow characteristics. During August and September 2012, just prior to SIPEX 2012, atmospheric circulation over the Southern Ocean was near-average, setting up the ocean-<span class="hlt">ice</span>-atmosphere system for near-average conditions. However, below-average surface pressure and temperature as well as strengthened circumpolar winds prevailed during June and July 2012. This led to a new record (19.48×106 km2) in maximum Antarctic sea-<span class="hlt">ice</span> <span class="hlt">extent</span> recorded in late September. In contrast to the weak circum-Antarctic conditions, the East Antarctic sector (including the SIPEX 2012 region) experienced positive sea-<span class="hlt">ice</span> <span class="hlt">extent</span> and concentration anomalies during most of 2012, coincident with negative atmospheric pressure and sea-surface temperature anomalies. Heavily deformed sea <span class="hlt">ice</span> appeared to be associated with intensified wind stress due to increased cyclonicity as well as an increased influx of sea <span class="hlt">ice</span> from the east. This increased westward <span class="hlt">ice</span> flux is likely linked to the break-up of nearly 80% of the Mertz Glacier Tongue in 2010, which strongly modified the coastal configuration and hence the width of the westward coastal current. Combined with favourable atmospheric conditions the associated changed coastal configuration allowed more sea <span class="hlt">ice</span> to remain within the coastal current at the expense of a reduced northward flow in the region around 141°-145°E. In addition a westward propagating positive anomaly of sea-<span class="hlt">ice</span> <span class="hlt">extent</span> from the western Ross Sea during austral winter</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.1399D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.1399D"><span>Nudging the Arctic Ocean to quantify Arctic sea <span class="hlt">ice</span> feedbacks</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dekker, Evelien; Severijns, Camiel; Bintanja, Richard</p> <p>2017-04-01</p> <p>It is well-established that the Arctic is warming 2 to 3 time faster than rest of the planet. One of the great uncertainties in climate research is related to what <span class="hlt">extent</span> sea <span class="hlt">ice</span> feedbacks amplify this (seasonally varying) Arctic warming. Earlier studies have analyzed existing climate model output using correlations and energy budget considerations in order to quantify sea <span class="hlt">ice</span> feedbacks through indirect methods. From these analyses it is regularly inferred that sea <span class="hlt">ice</span> likely plays an important role, but details remain obscure. Here we will take a different and a more direct approach: we will keep the sea <span class="hlt">ice</span> constant in a sensitivity simulation, using a state-of -the-art climate model (EC-Earth), applying a technique that has never been attempted before. This experimental technique involves nudging the temperature and salinity of the ocean surface (and possibly some layers below to maintain the vertical structure and mixing) to a predefined prescribed state. When strongly nudged to existing (seasonally-varying) sea surface temperatures, ocean salinity and temperature, we force the sea <span class="hlt">ice</span> to remain in regions/seasons where it is located in the prescribed state, despite the changing climate. Once we obtain fixed' sea <span class="hlt">ice</span>, we will run a future scenario, for instance 2 x CO2 with and without prescribed sea <span class="hlt">ice</span>, with the difference between these runs providing a measure as to what <span class="hlt">extent</span> sea <span class="hlt">ice</span> contributes to Arctic warming, including the seasonal and geographical imprint of the effects.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018QSRv..180..240L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018QSRv..180..240L"><span>New age constraints for the Saalian glaciation in northern central Europe: Implications for the <span class="hlt">extent</span> of <span class="hlt">ice</span> sheets and related proglacial lake systems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lang, Jörg; Lauer, Tobias; Winsemann, Jutta</p> <p>2018-01-01</p> <p>A comprehensive palaeogeographic reconstruction of <span class="hlt">ice</span> sheets and related proglacial lake systems for the older Saalian glaciation in northern central Europe is presented, which is based on the integration of palaeo-<span class="hlt">ice</span> flow data, till provenance, facies analysis, geomorphology and new luminescence ages of <span class="hlt">ice</span>-marginal deposits. Three major <span class="hlt">ice</span> advances with different <span class="hlt">ice</span>-advance directions and source areas are indicated by palaeo-<span class="hlt">ice</span> flow directions and till provenance. The first <span class="hlt">ice</span> advance was characterised by a southwards directed <span class="hlt">ice</span> flow and a dominance of clasts derived from southern Sweden. The second <span class="hlt">ice</span> advance was initially characterised by an <span class="hlt">ice</span> flow towards the southwest. Clasts are mainly derived from southern and central Sweden. The latest stage in the study area (third <span class="hlt">ice</span> advance) was characterised by <span class="hlt">ice</span> streaming (Hondsrug <span class="hlt">ice</span> stream) in the west and a re-advance in the east. Clasts of this stage are mainly derived from eastern Fennoscandia. Numerical ages for the first <span class="hlt">ice</span> advance are sparse, but may indicate a correlation with MIS 8 or early MIS 6. New pIRIR290 luminescence ages of <span class="hlt">ice</span>-marginal deposits attributed to the second <span class="hlt">ice</span> advance range from 175 ± 10 to 156 ± 24 ka and correlate with MIS 6. The <span class="hlt">ice</span> sheets repeatedly blocked the main river-drainage pathways and led to the formation of extensive <span class="hlt">ice</span>-dammed lakes. The formation of proglacial lakes was mainly controlled by <span class="hlt">ice</span>-damming of river valleys and major bedrock spillways; therefore the lake levels and extends were very similar throughout the repeated <span class="hlt">ice</span> advances. During deglaciation the lakes commonly increased in size and eventually drained successively towards the west and northwest into the Lower Rhine Embayment and the North Sea. Catastrophic lake-drainage events occurred when large overspill channels were suddenly opened. <span class="hlt">Ice</span>-streaming at the end of the older Saalian glaciation was probably triggered by major lake-drainage events.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018QSRv..179...87E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018QSRv..179...87E"><span><span class="hlt">Ice</span> streams of the Late Wisconsin Cordilleran <span class="hlt">Ice</span> Sheet in western North America</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Eyles, Nick; Arbelaez Moreno, Lina; Sookhan, Shane</p> <p>2018-01-01</p> <p>The Late Wisconsin Cordilleran <span class="hlt">Ice</span> Sheet (CIS) of western North America is thought to have reached its maximum <span class="hlt">extent</span> (∼2.5 × 106 km2) as late at c. 14.5 ka. Most (80%) of the <span class="hlt">ice</span> sheet's bed consists of high mountains but its 'core zone' sited on plateaux of the Intermontane Belt of British Columbia and coterminous parts of the USA, shows broad swaths of subglacially-streamlined rock and sediment. Broad scale mapping from new digital imagery data identifies three subglacial bed types: 1) 'hard beds' of variably streamlined bedrock; 2) drumlinized 'soft beds' of deformation till reworked from antecedent sediment, and 3) 'mixed beds' of variably-streamlined bedrock protruding through drumlinized sediment. Drumlins on soft beds appear to be erosional features cut into till and antecedent sediments, and identify the catchment areas of paleo <span class="hlt">ice</span> streams expressed downglacier as flow sets of megascale glacial lineations (MSGLs). 'Grooved' and 'cloned' drumlins appear to record the transition from drumlins to MSGLs. The location of paleo <span class="hlt">ice</span> streams reflects topographic funneling of <span class="hlt">ice</span> from plateau surfaces through outlet valleys and a soft bed that sustained fast flow; rock-cut MSGLs are also present locally on the floors of outlet valleys. CIS disintegrated in <1000 years shortly after c. 13.0 ka releasing very large volumes of meltwater and sediment to the Pacific coast. Abrupt deglaciation may reflect unsustainable calving of marine-based <span class="hlt">ice</span> streams along the glacio-isostatically depressed coast; large deep 'fiord lakes' in the <span class="hlt">ice</span> sheet's interior may have played an analogous role. Mapping of the broad scale distribution of bed types across the Cordilleran <span class="hlt">Ice</span> Sheet provides key information for paleoglaciological modelling and also for understanding the beds of modern <span class="hlt">ice</span> masses such as the Greenland <span class="hlt">Ice</span> Sheet which is of a comparable topographic setting.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017QSRv..169..330G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017QSRv..169..330G"><span>Younger-Dryas cooling and sea-<span class="hlt">ice</span> feedbacks were prominent features of the Pleistocene-Holocene transition in Arctic Alaska</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gaglioti, Benjamin V.; Mann, Daniel H.; Wooller, Matthew J.; Jones, Benjamin M.; Wiles, Gregory C.; Groves, Pamela; Kunz, Michael L.; Baughman, Carson A.; Reanier, Richard E.</p> <p>2017-08-01</p> <p>Declining sea-<span class="hlt">ice</span> <span class="hlt">extent</span> is currently amplifying climate warming in the Arctic. Instrumental records at high latitudes are too short-term to provide sufficient historical context for these <span class="hlt">trends</span>, so paleoclimate archives are needed to better understand the functioning of the sea <span class="hlt">ice</span>-albedo feedback. Here we use the oxygen isotope values of wood cellulose in living and sub-fossil willow shrubs (δ18Owc) (Salix spp.) that have been radiocarbon-dated (14C) to produce a multi-millennial record of climatic change on Alaska's North Slope during the Pleistocene-Holocene transition (13,500-7500 calibrated 14C years before present; 13.5-7.5 ka). We first analyzed the spatial and temporal patterns of δ18Owc in living willows growing at upland sites and found that over the last 30 years δ18Owc values in individual growth rings correlate with local summer temperature and inter-annual variations in summer sea-<span class="hlt">ice</span> <span class="hlt">extent</span>. Deglacial δ18Owc values from 145 samples of subfossil willows clearly record the Allerød warm period (∼13.2 ka), the Younger Dryas cold period (12.9-11.7 ka), and the Holocene Thermal Maximum (11.7-9.0 ka). The magnitudes of isotopic changes over these rapid climate oscillations were ∼4.5‰, which is about 60% of the differences in δ18Owc between those willows growing during the last glacial period and today. Modeling of isotope-precipitation relationships based on Rayleigh distillation processes suggests that during the Younger Dryas these large shifts in δ18Owc values were caused by interactions between local temperature and changes in evaporative moisture sources, the latter controlled by sea <span class="hlt">ice</span> <span class="hlt">extent</span> in the Arctic Ocean and Bering Sea. Based on these results and on the effects that sea-<span class="hlt">ice</span> have on climate today, we infer that ocean-derived feedbacks amplified temperature changes and enhanced precipitation in coastal regions of Arctic Alaska during warm times in the past. Today, isotope values in willows on the North Slope of Alaska are similar</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMPP41C2260G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMPP41C2260G"><span>The Role of Arctic Sea <span class="hlt">Ice</span> in Last Millennium Climate Variability: Model-Proxy Comparisons Using Ensemble Members and Novel Model Experiments.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gertler, C. G.; Monier, E.; Prinn, R. G.</p> <p>2016-12-01</p> <p>Variability in sea <span class="hlt">ice</span> <span class="hlt">extent</span> is a prominent feature of forced simulations of the last millennium and reconstructions of paleoclimate using proxy records. The rapid 20th century decline in sea <span class="hlt">ice</span> <span class="hlt">extent</span> is most likely due to greenhouse gas forcing, but the accuracy of future projections depend on the characterization of natural variability. Declining sea <span class="hlt">ice</span> <span class="hlt">extent</span> affects regional climate and society, but also plays a large role in Arctic amplification, with implications for mid-latitude circulation and even large-scale climate oscillations. To characterize the effects of natural and anthropogenic climate forcing on sea <span class="hlt">ice</span> and the related changes in large-scale atmospheric circulation, a combination of instrumental record, paleoclimate reconstructions, and general circulation models can be employed to recreate sea <span class="hlt">ice</span> <span class="hlt">extents</span> and the corresponding atmosphere-ocean states. Model output from the last millennium ensemble (LME) is compared to a proxy-based sea <span class="hlt">ice</span> reconstruction and a global proxy network using a variety of statistical and data assimilation techniques. Further model runs using the Community Earth Systems Model (CESM) are performed with the same inputs as LME but forced with experimental sea <span class="hlt">ice</span> <span class="hlt">extents</span>, and results are contextualized within the larger ensemble by a variety of metrics.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C31B0741W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C31B0741W"><span>Sea <span class="hlt">Ice</span> Evolution in the Pacific Arctic by Selected CMIP5 Models: the Present and the Future</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, M.; Yang, Q.; Overland, J. E.; Stabeno, P. J.</p> <p>2016-12-01</p> <p>With fast declining of sea <span class="hlt">ice</span> cover in the Arctic, the timing of sea <span class="hlt">ice</span> break-up and freeze-up is an urgent economic, social and scientific issue. Based on daily sea <span class="hlt">ice</span> concentration data we assess three parameters: the dates of sea <span class="hlt">ice</span> break-up and freeze-up and the annual sea <span class="hlt">ice</span> duration in the Pacific Arctic. The sea <span class="hlt">ice</span> duration is shrinking, with the largest <span class="hlt">trend</span> during the past decade (1990-2015); this declining <span class="hlt">trend</span> will continue based on CMIP5 model projections. The seven CMIP5 models used in current study are able to simulate all three parameters well when compared with observations. Comparisons made at eight Chukchi Sea mooring sites and the eight Distributed Biological Observatory (DBO) boxes show consistent results as well. The 30-year averaged <span class="hlt">trend</span> for annual sea <span class="hlt">ice</span> duration is projected to be -0.68 days/year to -1.2 days/year for 2015-2044. This is equivalent 20 to 36 days reduction in the annual sea <span class="hlt">ice</span> duration. A similar magnitude of the negative <span class="hlt">trend</span> is also found at all eight DBO boxes. The reduction in annual sea <span class="hlt">ice</span> duration will include both earlier break-up dates and later freeze-up date. However, models project that a later freeze-up contributes more than early break-up to the overall shortening of annual sea <span class="hlt">ice</span> duration. Around the Bering Strait future changes are the smallest, with less than 20-days change in duration during next 30 years. Upto 60 days reduction of the sea <span class="hlt">ice</span> duration is projected for the decade of 2030-2044 in the East Siberia, the Chukchi and the Beaufort Seas.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140016849','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140016849"><span>Reducing Spread in Climate Model Projections of a September <span class="hlt">Ice</span>-Free Arctic</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Liu, Jiping; Song, Mirong; Horton, Radley M.; Hu, Yongyun</p> <p>2013-01-01</p> <p>This paper addresses the specter of a September <span class="hlt">ice</span>-free Arctic in the 21st century using newly available simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). We find that large spread in the projected timing of the September <span class="hlt">ice</span>-free Arctic in 30 CMIP5 models is associated at least as much with different atmospheric model components as with initial conditions. Here we reduce the spread in the timing of an <span class="hlt">ice</span>-free state using two different approaches for the 30 CMIP5 models: (i) model selection based on the ability to reproduce the observed sea <span class="hlt">ice</span> climatology and variability since 1979 and (ii) constrained estimation based on the strong and persistent relationship between present and future sea <span class="hlt">ice</span> conditions. Results from the two approaches show good agreement. Under a high-emission scenario both approaches project that September <span class="hlt">ice</span> <span class="hlt">extent</span> will drop to approx. 1.7 million sq km in the mid 2040s and reach the <span class="hlt">ice</span>-free state (defined as 1 million sq km) in 2054-2058. Under a medium-mitigation scenario, both approaches project a decrease to approx.1.7 million sq km in the early 2060s, followed by a leveling off in the <span class="hlt">ice</span> <span class="hlt">extent</span>.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_21 --> <div id="page_22" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="421"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28753208','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28753208"><span><span class="hlt">Ice</span> nucleation active bacteria in precipitation are genetically diverse and nucleate <span class="hlt">ice</span> by employing different mechanisms.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Failor, K C; Schmale, D G; Vinatzer, B A; Monteil, C L</p> <p>2017-12-01</p> <p>A growing body of circumstantial evidence suggests that <span class="hlt">ice</span> nucleation active (<span class="hlt">Ice</span> + ) bacteria contribute to the initiation of precipitation by heterologous freezing of super-cooled water in clouds. However, little is known about the concentration of <span class="hlt">Ice</span> + bacteria in precipitation, their genetic and phenotypic diversity, and their relationship to air mass trajectories and precipitation chemistry. In this study, 23 precipitation events were collected over 15 months in Virginia, USA. Air mass trajectories and water chemistry were determined and 33 134 isolates were screened for <span class="hlt">ice</span> nucleation activity (INA) at -8 °C. Of 1144 isolates that tested positive during initial screening, 593 had confirmed INA at -8 °C in repeated tests. Concentrations of <span class="hlt">Ice</span> + strains in precipitation were found to range from 0 to 13 219 colony forming units per liter, with a mean of 384±147. Most <span class="hlt">Ice</span> + bacteria were identified as members of known and unknown <span class="hlt">Ice</span> + species in the Pseudomonadaceae, Enterobacteriaceae and Xanthomonadaceae families, which nucleate <span class="hlt">ice</span> employing the well-characterized membrane-bound INA protein. Two <span class="hlt">Ice</span> + strains, however, were identified as Lysinibacillus, a Gram-positive genus not previously known to include <span class="hlt">Ice</span> + bacteria. INA of the Lysinibacillus strains is due to a nanometer-sized molecule that is heat resistant, lysozyme and proteinase resistant, and secreted. <span class="hlt">Ice</span> + bacteria and the INA mechanisms they employ are thus more diverse than expected. We discuss to what <span class="hlt">extent</span> the concentration of culturable <span class="hlt">Ice</span> + bacteria in precipitation and the identification of a new heat-resistant biological INA mechanism support a role for <span class="hlt">Ice</span> + bacteria in the initiation of precipitation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.C21A0462V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.C21A0462V"><span>Measurements of ethane in Antarctic <span class="hlt">ice</span> cores</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Verhulst, K. R.; Fosse, E. K.; Aydin, K. M.; Saltzman, E. S.</p> <p>2011-12-01</p> <p>Ethane is one of the most abundant hydrocarbons in the atmosphere. The major ethane sources are fossil fuel production and use, biofuel combustion, and biomass-burning emissions and the primary loss pathway is via reaction with OH. A paleoatmospheric ethane record would be useful as a tracer of biomass-burning emissions, providing a constraint on past changes in atmospheric methane and methane isotopes. An independent biomass-burning tracer would improve our understanding of the relationship between biomass burning and climate. The mean annual atmospheric ethane level at high southern latitudes is about 230 parts per trillion (ppt), and Antarctic firn air measurements suggest that atmospheric ethane levels in the early 20th century were considerably lower (Aydin et al., 2011). In this study, we present preliminary measurements of ethane (C2H6) in Antarctic <span class="hlt">ice</span> core samples with gas ages ranging from 0-1900 C.E. Samples were obtained from dry-drilled <span class="hlt">ice</span> cores from South Pole and Vostok in East Antarctica, and from the West Antarctic <span class="hlt">Ice</span> Sheet Divide (WAIS-D). Gases were extracted from the <span class="hlt">ice</span> by melting under vacuum in a glass vessel sealed by indium wire and were analyzed using high resolution GC/MS with isotope dilution. Ethane levels measured in <span class="hlt">ice</span> core samples were in the range 100-220 ppt, with a mean of 157 ± 45 ppt (n=12). System blanks contribute roughly half the amount of ethane extracted from a 300 g <span class="hlt">ice</span> core sample. These preliminary data exhibit a temporal <span class="hlt">trend</span>, with higher ethane levels from 0-900 C.E., followed by a decline, reaching a minimum between 1600-1700 C.E. These <span class="hlt">trends</span> are consistent with variations in <span class="hlt">ice</span> core methane isotopes and carbon monoxide isotopes (Ferretti et al., 2005, Wang et al., 2010), which indicate changes in biomass burning emissions over this time period. These preliminary data suggest that Antarctic <span class="hlt">ice</span> core bubbles contain paleoatmospheric ethane levels. With further improvement of laboratory techniques it appears</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C21A0658Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C21A0658Z"><span>Changes in Arctic Sea <span class="hlt">Ice</span> Thickness and Floe Size</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, J.; Schweiger, A. J. B.; Stern, H. L., III; Steele, M.</p> <p>2016-12-01</p> <p>A thickness, floe size, and enthalpy distribution sea <span class="hlt">ice</span> model was implemented into the Pan-arctic <span class="hlt">Ice</span>-Ocean Modeling and Assimilation System (PIOMAS) by coupling the Zhang et al. [2015] sea <span class="hlt">ice</span> floe size distribution (FSD) theory with the Thorndike et al. [1975] <span class="hlt">ice</span> thickness distribution (ITD) theory in order to explicitly simulate multicategory FSD and ITD simultaneously. A range of <span class="hlt">ice</span> thickness and floe size observations were used for model calibration and validation. The expanded, validated PIOMAS was used to study sea <span class="hlt">ice</span> response to atmospheric and oceanic changes in the Arctic, focusing on the interannual variability and <span class="hlt">trends</span> of <span class="hlt">ice</span> thickness and floe size over the period 1979-2015. It is found that over the study period both <span class="hlt">ice</span> thickness and floe size have been decreasing steadily in the Arctic. The simulated <span class="hlt">ice</span> thickness shows considerable spatiotemporal variability in recent years. As the <span class="hlt">ice</span> cover becomes thinner and weaker, the model simulates an increasing number of small floes (at the low end of the FSD), which affects sea <span class="hlt">ice</span> properties, particularly in the marginal <span class="hlt">ice</span> zone.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19910047694&hterms=lead+history&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dlead%2Bhistory','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19910047694&hterms=lead+history&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dlead%2Bhistory"><span>Texture analysis of radiometric signatures of new sea <span class="hlt">ice</span> forming in Arctic leads</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Eppler, Duane T.; Farmer, L. Dennis</p> <p>1991-01-01</p> <p>Analysis of 33.6-GHz, high-resolution, passive microwave images suggests that new sea <span class="hlt">ice</span> accumulating in open leads is characterized by a unique textural signature which can be used to discriminate new <span class="hlt">ice</span> forming in this environment from adjacent surfaces of similar radiometric temperature. Ten training areas were selected from the data set, three of which consisted entirely of first-year <span class="hlt">ice</span>, four entirely of multilayer <span class="hlt">ice</span>, and three of new <span class="hlt">ice</span> in open leads in the process of freezing. A simple gradient operator was used to characterize the radiometric texture in each training region in terms of the degree to which radiometric gradients are oriented. New <span class="hlt">ice</span> in leads has a sufficiently high proportion of well-oriented features to distinguish it uniquely from first-year <span class="hlt">ice</span> and multiyear <span class="hlt">ice</span>. The predominance of well-oriented features probably reflects physical processes by which new <span class="hlt">ice</span> accumulates in open leads. Banded structures, which are evident in aerial photographs of new <span class="hlt">ice</span>, apparently give rise to the radiometric signature observed, in which the <span class="hlt">trend</span> of brightness temperature gradients is aligned parallel to lead <span class="hlt">trends</span>. First-year <span class="hlt">ice</span> and multiyear <span class="hlt">ice</span>, which have been subjected to a more random growth and process history, lack this banded structure and therefore are characterized by signatures in which well-aligned elements are less dominant.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040070783','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040070783"><span>Representation of <span class="hlt">Ice</span> Geometry by Parametric Functions: Construction of Approximating NURBS Curves and Quantification of <span class="hlt">Ice</span> Roughness--Year 1: Approximating NURBS Curves</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Dill, Loren H.; Choo, Yung K. (Technical Monitor)</p> <p>2004-01-01</p> <p>Software was developed to construct approximating NURBS curves for <span class="hlt">iced</span> airfoil geometries. Users specify a tolerance that determines the <span class="hlt">extent</span> to which the approximating curve follows the rough <span class="hlt">ice</span>. The user can therefore smooth the <span class="hlt">ice</span> geometry in a controlled manner, thereby enabling the generation of grids suitable for numerical aerodynamic simulations. Ultimately, this ability to smooth the <span class="hlt">ice</span> geometry will permit studies of the effects of smoothing upon the aerodynamics of <span class="hlt">iced</span> airfoils. The software was applied to several different types of <span class="hlt">iced</span> airfoil data collected in the <span class="hlt">Icing</span> Research Tunnel at NASA Glenn Research Center, and in all cases was found to efficiently generate suitable approximating NURBS curves. This method is an improvement over the current "control point formulation" of Smaggice (v.1.2). In this report, we present the relevant theory of approximating NURBS curves and discuss typical results of the software.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.sciencedirect.com/science/article/pii/S0165232X13001730','USGSPUBS'); return false;" href="http://www.sciencedirect.com/science/article/pii/S0165232X13001730"><span>Reconstruction of historic sea <span class="hlt">ice</span> conditions in a sub-Arctic lagoon</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Petrich, Chris; Tivy, Adrienne C.; Ward, David H.</p> <p>2014-01-01</p> <p>Historical sea <span class="hlt">ice</span> conditions were reconstructed for Izembek Lagoon, Bering Sea, Alaska. This lagoon is a crucial staging area during migration for numerous species of avian migrants and a major eelgrass (Zostera marina) area important to a variety of marine and terrestrial organisms, especially Pacific Flyway black brant geese (Branta bernicla nigricans). <span class="hlt">Ice</span> cover is a common feature of the lagoon in winter, but appears to be declining, which has implications for eelgrass distribution and abundance, and its use by wildlife. We evaluated <span class="hlt">ice</span> conditions from a model based on degree days, calibrated to satellite observations, to estimate distribution and long-term <span class="hlt">trends</span> in <span class="hlt">ice</span> conditions in Izembek Lagoon. Model results compared favorably with ground observations and 26 years of satellite data, allowing <span class="hlt">ice</span> conditions to be reconstructed back to 1943. Specifically, periods of significant (limited access to eelgrass areas) and severe (almost complete <span class="hlt">ice</span> coverage of the lagoon) <span class="hlt">ice</span> conditions could be identified. The number of days of severe <span class="hlt">ice</span> within a single season ranged from 0 (e.g., 2001) to ≥ 67 (e.g., 2000). We detected a slight long-term negative <span class="hlt">trend</span> in <span class="hlt">ice</span> conditions, superimposed on high inter-annual variability in seasonal aggregate <span class="hlt">ice</span> conditions. Based on reconstructed <span class="hlt">ice</span> conditions, the seasonally cumulative number of significant or severe <span class="hlt">ice</span> days correlated linearly with mean air temperature from January until March. Further, air temperature at Izembek Lagoon was correlated with wind direction, suggesting that <span class="hlt">ice</span> conditions in Izembek Lagoon were associated with synoptic-scale weather patterns. Methods employed in this analysis may be transferable to other coastal locations in the Arctic.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC44B..02K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC44B..02K"><span>Quantifying the <span class="hlt">ice</span>-albedo feedback through decoupling</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kravitz, B.; Rasch, P. J.</p> <p>2017-12-01</p> <p>The <span class="hlt">ice</span>-albedo feedback involves numerous individual components, whereby warming induces sea <span class="hlt">ice</span> melt, inducing reduced surface albedo, inducing increased surface shortwave absorption, causing further warming. Here we attempt to quantify the sea <span class="hlt">ice</span> albedo feedback using an analogue of the "partial radiative perturbation" method, but where the governing mechanisms are directly decoupled in a climate model. As an example, we can isolate the insulating effects of sea <span class="hlt">ice</span> on surface energy and moisture fluxes by allowing sea <span class="hlt">ice</span> thickness to change but fixing Arctic surface albedo, or vice versa. Here we present results from such idealized simulations using the Community Earth System Model in which individual components are successively fixed, effectively decoupling the <span class="hlt">ice</span>-albedo feedback loop. We isolate the different components of this feedback, including temperature change, sea <span class="hlt">ice</span> <span class="hlt">extent</span>/thickness, and air-sea exchange of heat and moisture. We explore the interactions between these different components, as well as the strengths of the total feedback in the decoupled feedback loop, to quantify contributions from individual pieces. We also quantify the non-additivity of the effects of the components as a means of investigating the dominant sources of nonlinearity in the <span class="hlt">ice</span>-albedo feedback.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19730015654','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19730015654"><span>Sea <span class="hlt">ice</span> and surface water circulation, Alaskan Continental Shelf</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wright, F. F. (Principal Investigator); Sharma, G. D.; Burn, J. J.</p> <p>1973-01-01</p> <p>The author has identified the following significant results. The boundaries of land-fast <span class="hlt">ice</span>, distribution of pack <span class="hlt">ice</span>, and major polynya were studied in the vicinity of the Bering Strait. Movement of pack <span class="hlt">ice</span> during 24 hours was determined by plotting the distinctly identifiable <span class="hlt">ice</span> floes on ERTS-1 imagery obtained from two consecutive passes. Considerably large shallow area along the western Seward Peninsula just north of the Bering Strait is covered by land fast <span class="hlt">ice</span>. This <span class="hlt">ice</span> hinders the movement of <span class="hlt">ice</span> formed in eastern Chukchi Sea southward through the Bering Strait. The movement of <span class="hlt">ice</span> along the Russian coast is relatively faster. Plotting of some of the <span class="hlt">ice</span> floes indicated movement of <span class="hlt">ice</span> in excess of 30 km in and south of the Bering Strait between 6 and 7 March, 1973. North of the Bering Strait the movement approached 18 km. The movement of <span class="hlt">ice</span> observed during March 6 and 7 considerably altered the distribution and <span class="hlt">extent</span> of polynya. These features when continually plotted should be of considerable aid in navigation of <span class="hlt">ice</span> breakers. The movement of <span class="hlt">ice</span> will also help delineate the migration and distribution of sea mammals.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27812435','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27812435"><span>Loitering of the retreating sea <span class="hlt">ice</span> edge in the Arctic Seas.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Steele, Michael; Ermold, Wendy</p> <p>2015-12-01</p> <p>Each year, the arctic sea <span class="hlt">ice</span> edge retreats from its winter maximum <span class="hlt">extent</span> through the Seasonal <span class="hlt">Ice</span> Zone (SIZ) to its summer minimum <span class="hlt">extent</span>. On some days, this retreat happens at a rapid pace, while on other days, parts of the pan-arctic <span class="hlt">ice</span> edge hardly move for periods of days up to 1.5 weeks. We term this stationary behavior "<span class="hlt">ice</span> edge loitering," and identify areas that are more prone to loitering than others. Generally, about 20-25% of the SIZ area experiences loitering, most often only one time at any one location during the retreat season, but sometimes two or more times. The main mechanism controlling loitering is an interaction between surface winds and warm sea surface temperatures in areas from which the <span class="hlt">ice</span> has already retreated. When retreat happens early enough to allow atmospheric warming of this open water, winds that force <span class="hlt">ice</span> floes into this water cause melting. Thus, while individual <span class="hlt">ice</span> floes are moving, the <span class="hlt">ice</span> edge as a whole appears to loiter. The time scale of loitering is then naturally tied to the synoptic time scale of wind forcing. Perhaps surprisingly, the area of loitering in the arctic seas has not changed over the past 25 years, even as the SIZ area has grown. This is because rapid <span class="hlt">ice</span> retreat happens most commonly late in the summer, when atmospheric warming of open water is weak. We speculate that loitering may have profound effects on both physical and biological conditions at the <span class="hlt">ice</span> edge during the retreat season.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1513402T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1513402T"><span>Export of <span class="hlt">Ice</span>-Cavity Water from Pine Island <span class="hlt">Ice</span> Shelf, West Antarctica</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Thurnherr, Andreas; Jacobs, Stanley; Dutrieux, Pierre</p> <p>2013-04-01</p> <p>Stability of the West Antarctic <span class="hlt">Ice</span> Sheet is sensitive to changes in melting at the bottom of floating <span class="hlt">ice</span> shelves that form the seaward extensions of Antarctic glaciers flowing into the ocean. Not least because observations in the cavities beneath <span class="hlt">ice</span> shelves are difficult, heat fluxes and melt rates have been inferred from oceanographic measurements obtained near the <span class="hlt">ice</span> edge (calving fronts). Here, we report on a set of hydrographic and velocity data collected in early 2009 near the calving front of the Amundsen Sea's fast-moving and (until recently) accelerating Pine Island Glacier and its associated <span class="hlt">ice</span> shelf. CTD profiles collected along the southern half of the meridionally-<span class="hlt">trending</span> <span class="hlt">ice</span> front show clear evidence for export of <span class="hlt">ice</span>-cavity water. That water was carried in the upper ocean along the <span class="hlt">ice</span> front by a southward current that is possibly related to a striking clockwise gyre that dominated the (summertime) upper-ocean circulation in Pine Island Bay. Signatures of <span class="hlt">ice</span>-cavity water appear unrelated to current direction along most of the <span class="hlt">ice</span> front, suggesting that cross-frontal exchange is dominated by temporal variability. However, repeated hydrographic and velocity measurements in a small "<span class="hlt">ice</span> cove" at the southern end of the calving front show a persistent strong (mean velocity peaking near 0.5 ms-1) outflow of <span class="hlt">ice</span>-cavity water in the upper 500 m. While surface features (boils) suggested upwelling from deep below the <span class="hlt">ice</span> shelf, vertical velocity measurements reveal 1) that the mean upwelling within the confines of the cove was too weak to feed the observed outflow, and 2) that large high-frequency internal waves dominated the vertical motion of water inside the cove. These observations indicate that water exchange between the Pine Island <span class="hlt">Ice</span> Shelf cavity and the Amundsen sea is strongly asymmetric with weak broad inflow at depth and concentrated surface-intensified outflow of melt-laden deep water at the southern edge of the calving front. The lack of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.6665W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.6665W"><span>Recent sea <span class="hlt">ice</span> thickness <span class="hlt">trends</span> in the Arctic Basin from submarine data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wadhams, P.; Rodriguez, J. M.; Toberg, N.</p> <p>2009-04-01</p> <p>Detailed mapping of the underside of Arctic sea <span class="hlt">ice</span> in the 21st Century is largely the result of two UK submarine cruises by HMS "Tireless", in April of 2004 and 2007, since the annual US cruises of the SCICEX program ended in 2000. The 2007 cruise reproduced part of the 2004 track, across the north of Greenland and Ellesmere Island, and went on to cover the Beaufort Sea, including a gridded survey of the region of the APLIS-2007 <span class="hlt">ice</span> camp. Where the 2004 and 2007 tracks matched, the mean thicknesses of the <span class="hlt">ice</span> cover were essentially identical, with no evidence of significant further thinning between 2004 and 2007. In the Beaufort Sea, there is a direct comparison possible with a cruise covering the same region in the same season (April) of 1976. Here a very significant thinning can be seen, with a much lower mean draft, less multi-year <span class="hlt">ice</span> and less ridging. In all cases the ridge draft distribution falls away quickly in probability with increasing depth, with no ridges deeper than 30 m anywhere in the submarine profiles, whereas in earlier cruises such ridges were numerous in the multi-year <span class="hlt">ice</span> zone with some ridges exceeding 40 m. The 2007 cruise had the added advantage of a multibeam sonar fitted to the submarine to give a 3-D view of the underside; the data reinforce the view that active melt and decay of pressure ridges is taking place.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ISPAr42.3..485H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ISPAr42.3..485H"><span>Thin <span class="hlt">Ice</span> Area Extraction in the Seasonal Sea <span class="hlt">Ice</span> Zones of the Northern Hemisphere Using Modis Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hayashi, K.; Naoki, K.; Cho, K.</p> <p>2018-04-01</p> <p>Sea <span class="hlt">ice</span> has an important role of reflecting the solar radiation back into space. However, once the sea <span class="hlt">ice</span> area melts, the area starts to absorb the solar radiation which accelerates the global warming. This means that the <span class="hlt">trend</span> of global warming is likely to be enhanced in sea <span class="hlt">ice</span> areas. In this study, the authors have developed a method to extract thin <span class="hlt">ice</span> area using reflectance data of MODIS onboard Terra and Aqua satellites of NASA. The reflectance of thin sea <span class="hlt">ice</span> in the visible region is rather low. Moreover, since the surface of thin sea <span class="hlt">ice</span> is likely to be wet, the reflectance of thin sea <span class="hlt">ice</span> in the near infrared region is much lower than that of visible region. Considering these characteristics, the authors have developed a method to extract thin sea <span class="hlt">ice</span> areas by using the reflectance data of MODIS (NASA MYD09 product, 2017) derived from MODIS L1B. By using the scatter plots of the reflectance of Band 1 (620 nm-670 nm) and Band 2 (841 nm-876 nm)) of MODIS, equations for extracting thin <span class="hlt">ice</span> area were derived. By using those equations, most of the thin <span class="hlt">ice</span> areas which could be recognized from MODIS images were well extracted in the seasonal sea <span class="hlt">ice</span> zones in the Northern Hemisphere, namely the Sea of Okhotsk, the Bering Sea and the Gulf of Saint Lawrence. For some limited areas, Landsat-8 OLI images were also used for validation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4368101','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4368101"><span>Climate <span class="hlt">trends</span> in the Arctic as observed from space</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Comiso, Josefino C; Hall, Dorothy K</p> <p>2014-01-01</p> <p>The Arctic is a region in transformation. Warming in the region has been amplified, as expected from <span class="hlt">ice</span>-albedo feedback effects, with the rate of warming observed to be ∼0.60 ± 0.07°C/decade in the Arctic (>64°N) compared to ∼0.17°C/decade globally during the last three decades. This increase in surface temperature is manifested in all components of the cryosphere. In particular, the sea <span class="hlt">ice</span> <span class="hlt">extent</span> has been declining at the rate of ∼3.8%/decade, whereas the perennial <span class="hlt">ice</span> (represented by summer <span class="hlt">ice</span> minimum) is declining at a much greater rate of ∼11.5%/decade. Spring snow cover has also been observed to be declining by −2.12%/decade for the period 1967–2012. The Greenland <span class="hlt">ice</span> sheet has been losing mass at the rate of ∼34.0 Gt/year (sea level equivalence of 0.09 mm/year) during the period from 1992 to 2011, but for the period 2002–2011, a higher rate of mass loss of ∼215 Gt/year has been observed. Also, the mass of glaciers worldwide declined at the rate of 226 Gt/year from 1971 to 2009 and 275 Gt/year from 1993 to 2009. Increases in permafrost temperature have also been measured in many parts of the Northern Hemisphere while a thickening of the active layer that overlies permafrost and a thinning of seasonally frozen ground has also been reported. To gain insight into these changes, comparative analysis with <span class="hlt">trends</span> in clouds, albedo, and the Arctic Oscillation is also presented. How to cite this article:WIREs Clim Change 2014, 5:389�409. doi: 10.1002/wcc.277 PMID:25810765</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25810765','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25810765"><span>Climate <span class="hlt">trends</span> in the Arctic as observed from space.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Comiso, Josefino C; Hall, Dorothy K</p> <p>2014-05-01</p> <p>The Arctic is a region in transformation. Warming in the region has been amplified, as expected from <span class="hlt">ice</span>-albedo feedback effects, with the rate of warming observed to be ∼0.60 ± 0.07°C/decade in the Arctic (>64°N) compared to ∼0.17°C/decade globally during the last three decades. This increase in surface temperature is manifested in all components of the cryosphere. In particular, the sea <span class="hlt">ice</span> <span class="hlt">extent</span> has been declining at the rate of ∼3.8%/decade, whereas the perennial <span class="hlt">ice</span> (represented by summer <span class="hlt">ice</span> minimum) is declining at a much greater rate of ∼11.5%/decade. Spring snow cover has also been observed to be declining by -2.12%/decade for the period 1967-2012. The Greenland <span class="hlt">ice</span> sheet has been losing mass at the rate of ∼34.0 Gt/year (sea level equivalence of 0.09 mm/year) during the period from 1992 to 2011, but for the period 2002-2011, a higher rate of mass loss of ∼215 Gt/year has been observed. Also, the mass of glaciers worldwide declined at the rate of 226 Gt/year from 1971 to 2009 and 275 Gt/year from 1993 to 2009. Increases in permafrost temperature have also been measured in many parts of the Northern Hemisphere while a thickening of the active layer that overlies permafrost and a thinning of seasonally frozen ground has also been reported. To gain insight into these changes, comparative analysis with <span class="hlt">trends</span> in clouds, albedo, and the Arctic Oscillation is also presented. How to cite this article: WIREs Clim Change 2014, 5:389�409. doi: 10.1002/wcc.277.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19990109666','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19990109666"><span>The Formation each Winter of the Circumpolar Wave in the Sea <span class="hlt">Ice</span> around Antarctica</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Gloersen, Per; White, Warren B.</p> <p>1999-01-01</p> <p>Seeking to improve upon the visualization of the Antarctic Circumpolar Wave (ACW) , we compare a 16-year sequence of 6-month winter averages of Antarctic sea <span class="hlt">ice</span> <span class="hlt">extents</span> and concentrations with those of adjacent sea surface temperatures (SSTs). Here we follow SSTs around the globe along the maximum sea <span class="hlt">ice</span> edge rather than in a zonal band equatorward of it. The results are similar to the earlier ones, but the ACWs do not propagate with equal amplitude or speed. Additionally in a sequence of 4 polar stereographic plots of these SSTs and sea <span class="hlt">ice</span> concentrations, we find a remarkable correlation between SST minima and sea <span class="hlt">ice</span> concentration maxima, even to the <span class="hlt">extent</span> of matching contours across the <span class="hlt">ice</span>-sea boundary, in the sector between 900E and the Palmer Peninsula. Based on these observations, we suggest that the memory of the ACW in the sea <span class="hlt">ice</span> is carried from one Austral winter to the next by the neighboring SSTS, since the sea <span class="hlt">ice</span> is nearly absent in the Austral summer.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5885011','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5885011"><span>The diversity of <span class="hlt">ice</span> algal communities on the Greenland <span class="hlt">Ice</span> Sheet as revealed by oligotyping</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Lutz, Stefanie; McCutcheon, Jenine; McQuaid, James B.; Benning, Liane G.</p> <p>2018-01-01</p> <p>The Arctic is being disproportionally affected by climate change compared with other geographic locations, and is currently experiencing unprecedented melt rates. The Greenland <span class="hlt">Ice</span> Sheet (GrIS) can be regarded as the largest supraglacial ecosystem on Earth, and <span class="hlt">ice</span> algae are the dominant primary producers on bare <span class="hlt">ice</span> surfaces throughout the course of a melt season. <span class="hlt">Ice</span>-algal-derived pigments cause a darkening of the <span class="hlt">ice</span> surface, which in turn decreases albedo and increases melt rates. The important role of <span class="hlt">ice</span> algae in changing melt rates has only recently been recognized, and we currently know little about their community compositions and functions. Here, we present the first analysis of <span class="hlt">ice</span> algal communities across a 100 km transect on the GrIS by high-throughput sequencing and subsequent oligotyping of the most abundant taxa. Our data reveal an extremely low algal diversity with Ancylonema nordenskiöldii and a Mesotaenium species being by far the dominant taxa at all sites. We employed an oligotyping approach and revealed a hidden diversity not detectable by conventional clustering of operational taxonomic units and taxonomic classification. Oligotypes of the dominant taxa exhibit a site-specific distribution, which may be linked to differences in temperatures and subsequently the <span class="hlt">extent</span> of the melting. Our results help to better understand the distribution patterns of <span class="hlt">ice</span> algal communities that play a crucial role in the GrIS ecosystem. PMID:29547098</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C51A0947C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C51A0947C"><span><span class="hlt">Ice</span>-sheet thinning and acceleration at Camp Century, Greenlan</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Colgan, W. T.</p> <p>2017-12-01</p> <p>Camp Century, Greenland (77.18 °N, 61.12 °W, 1900 m), is located approximately 150 km inland from the <span class="hlt">ice</span>-sheet margin in Northwest Greenland. In-situ and remotely-sensed measurements of <span class="hlt">ice</span>-sheet elevation at Camp Century exhibit a thinning <span class="hlt">trend</span> between 1964 and the present. A comparison of 1966 and 2017 firn density profiles indicates that a portion of this <span class="hlt">ice</span>-sheet thinning is attributable to increased firn compaction rate. In-situ measurements of increasing <span class="hlt">ice</span> surface velocity over the 1977-2017 period indicate that enhanced horizontal divergence of <span class="hlt">ice</span> flux is also contributing to <span class="hlt">ice</span> dynamic thinning at Camp Century. This apparent <span class="hlt">ice</span> dynamic thinning could potentially result from a migrating local flow divide or decreasing effective <span class="hlt">ice</span> viscosity. In a shorter-term context, observations of decadal-scale <span class="hlt">ice</span>-sheet thinning and acceleration at Camp Century highlights underappreciated transience in inland <span class="hlt">ice</span> form and flow during the satellite era. In a longer-term context, these multi-decadal observations contrast with inferences of millennial-scale <span class="hlt">ice</span>-sheet thickening and deceleration at Camp Century.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1810892P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1810892P"><span>"<span class="hlt">Ice</span> out": the contribution of citizen scientists to our understanding of climate change</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Patterson, R. Timothy; Swindles, Graeme T.</p> <p>2016-04-01</p> <p>Long-term <span class="hlt">trends</span> in spring '<span class="hlt">ice</span> out' dates (1836-2013) for twelve lakes in Maine, New Brunswick and New Hampshire, in eastern North America reveal a remarkable coherency across the region (rs=0.462-0.933, p<0.01). These data have been compiled since the early 19th century, primarily by amateur citizen scientists, for a variety of purposes, including determining fishing seasons, estimating the spring opening of ferry boat routes, community contests, and general curiosity. <span class="hlt">Ice</span> out dates correlate closely with late-winter/early-spring, March-April (MA), instrumental temperature records from across the region (rs=0.488-0.816, p<0.01). This correlation permits use of <span class="hlt">ice</span> out dates as a proxy to extend the shorter MA instrumental record (1876-2013). Mean <span class="hlt">ice</span> out dates <span class="hlt">trended</span> progressively earlier during the recovery from the Little <span class="hlt">Ice</span> Age through to the 1940s, and gradually became later again through to the late 1970s, when <span class="hlt">ice</span> out dates had returned to values more typical of the late nineteenth century. Post-1970's <span class="hlt">ice</span> out dates resumed <span class="hlt">trending</span> toward earlier dates, with the twenty-first century being characterized by the earliest <span class="hlt">ice</span> out dates on record. Spectral and wavelet time series analysis indicate that <span class="hlt">ice</span> out is influenced by several teleconnections including the Quasi-biennial Oscillation, El Niño-Southern Oscillation, North Atlantic Oscillation, Atlantic Multidecadal Oscillation as well as a significant correlation between inland lake records and the Arctic Oscillation. The relative influence of these teleconnections is variable with notable shifts occurring after ~1870, ~1925, and ~1980-2000. The intermittent expression of these cycles in the <span class="hlt">ice</span> out and MA instrumental record is not only influenced by absolute changes in the intensity of the various teleconnections and other climate drivers, but by phase interference between teleconnections, which periodically damps the various signals.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C31B0742N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C31B0742N"><span>A Quantitative Proxy for Sea-<span class="hlt">Ice</span> Based on Diatoms: A Cautionary Tale.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nesterovich, A.; Caissie, B.</p> <p>2016-12-01</p> <p>Sea <span class="hlt">ice</span> in the Polar Regions supports unique and productive ecosystems, but the current decline in the Arctic sea <span class="hlt">ice</span> <span class="hlt">extent</span> prompts questions about previous sea <span class="hlt">ice</span> declines and the response of <span class="hlt">ice</span> related ecosystems. Since satellite data only extend back to 1978, the study of sea <span class="hlt">ice</span> before this time requires a proxy. Being one of the most productive, diatom-dominated regions in the world and having a wide range of sea <span class="hlt">ice</span> concentrations, the Bering and Chukchi seas are a perfect place to find a relationship between the presence of sea <span class="hlt">ice</span> and diatom community composition. The aim of this work is to develop a diatom-based proxy for the sea <span class="hlt">ice</span> <span class="hlt">extent</span>. A total of 473 species have been identified in 104 sediment samples, most of which were collected on board the US Coast Guard Cutter Healy <span class="hlt">ice</span> breaker (2006, 2007) and the Norseman II (2008). The study also included some of the archived diatom smear slides made from sediments collected in 1969. The assemblages were compared to satellite-derived sea <span class="hlt">ice</span> <span class="hlt">extent</span> data averaged over the 10 years preceding the sampling. Previous studies in the Arctic and Antarctic regions demonstrated that the Generalized Additive Model (GAM) is one of the best choices for proxy construction. It has the advantage of using only several species instead of the whole assemblage, thus including only sea <span class="hlt">ice</span>-associated species and minimizing the noise created by species responding to other environmental factors. Our GAM on three species (Connia compita, Fragilariopsis reginae-jahniae, and Neodenticula seminae) has low standard deviation, high level of explained variation, and holds under the ten-fold cross-validation; the standard residual analysis is acceptable. However, a spatial residual analysis revealed that the model consistently over predicts in the Chukchi Sea and under predicts in the Bering Sea. Including a spatial model into the GAM didn't improve the situation. This has led us to test other methods, including a non-parametric model</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C43B0754M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C43B0754M"><span>Coordinated Mapping of Sea <span class="hlt">Ice</span> Deformation Features with Autonomous Vehicles</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Maksym, T.; Williams, G. D.; Singh, H.; Weissling, B.; Anderson, J.; Maki, T.; Ackley, S. F.</p> <p>2016-12-01</p> <p>Decreases in summer sea <span class="hlt">ice</span> <span class="hlt">extent</span> in the Beaufort and Chukchi Seas has lead to a transition from a largely perennial <span class="hlt">ice</span> cover, to a seasonal <span class="hlt">ice</span> cover. This drives shifts in sea <span class="hlt">ice</span> production, dynamics, <span class="hlt">ice</span> types, and thickness distribution. To examine how the processes driving <span class="hlt">ice</span> advance might also impact the morphology of the <span class="hlt">ice</span> cover, a coordinated <span class="hlt">ice</span> mapping effort was undertaken during a field campaign in the Beaufort Sea in October, 2015. Here, we present observations of sea <span class="hlt">ice</span> draft topography from six missions of an Autonomous Underwater Vehicle run under different <span class="hlt">ice</span> types and deformation features observed during autumn freeze-up. <span class="hlt">Ice</span> surface features were also mapped during coordinated drone photogrammetric missions over each site. We present preliminary results of a comparison between sea <span class="hlt">ice</span> surface topography and <span class="hlt">ice</span> underside morphology for a range of sample <span class="hlt">ice</span> types, including hummocked multiyear <span class="hlt">ice</span>, rubble fields, young <span class="hlt">ice</span> ridges and rafts, and consolidated pancake <span class="hlt">ice</span>. These data are compared to prior observations of <span class="hlt">ice</span> morphological features from deformed Antarctic sea <span class="hlt">ice</span>. Such data will be useful for improving parameterizations of sea <span class="hlt">ice</span> redistribution during deformation, and for better constraining estimates of airborne or satellite sea <span class="hlt">ice</span> thickness.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_22 --> <div id="page_23" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="441"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EOSTr..90R.169P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EOSTr..90R.169P"><span>Developing and Implementing Protocols for Arctic Sea <span class="hlt">Ice</span> Observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Perovich, Donald K.; Gerland, Sebastian</p> <p>2009-05-01</p> <p>Arctic Surface-Based Sea <span class="hlt">Ice</span> Observations: Integrated Protocols and Coordinated Data Acquisition; Tromsø, Norway, 26-27 January 2009; The Arctic sea <span class="hlt">ice</span> cover is diminishing. Over the past several years, not only has <span class="hlt">ice</span> thinned but the <span class="hlt">extent</span> of <span class="hlt">ice</span> at the end of summer, and hence perennial <span class="hlt">ice</span>, has declined markedly. These changes affect a wide range of issues and are important for a varied group of stakeholders, including Arctic coastal communities, policy makers, industry, the scientific community, and the public. Concerns range from the role of sea <span class="hlt">ice</span> cover as an indicator and amplifier of climate change to marine transportation, resource extraction, and coastal erosion. To understand and respond to these ongoing changes, it is imperative to develop and implement consistent and robust observational protocols that can be used to describe the current state of the <span class="hlt">ice</span> cover as well as future changes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20150021896&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dsea','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20150021896&hterms=sea&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dsea"><span>Is <span class="hlt">Ice</span>-Rafted Sediment in a North Pole Marine Record Evidence for Perennial Sea-<span class="hlt">ice</span> Cover?</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tremblay, L.B.; Schmidt, G.A.; Pfirman, S.; Newton, R.; DeRepentigny, P.</p> <p>2015-01-01</p> <p><span class="hlt">Ice</span>-rafted sediments of Eurasian and North American origin are found consistently in the upper part (13 Ma BP to present) of the Arctic Coring Expedition (ACEX) ocean core from the Lomonosov Ridge, near the North Pole (approximately 88 degrees N). Based on modern sea-<span class="hlt">ice</span> drift trajectories and speeds, this has been taken as evidence of the presence of a perennial sea-<span class="hlt">ice</span> cover in the Arctic Ocean from the middle Miocene onwards. However, other high latitude land and marine records indicate a long-term <span class="hlt">trend</span> towards cooling broken by periods of extensive warming suggestive of a seasonally <span class="hlt">ice</span>-free Arctic between the Miocene and the present. We use a coupled sea-<span class="hlt">ice</span> slab-ocean model including sediment transport tracers to map the spatial distribution of <span class="hlt">ice</span>-rafted deposits in the Arctic Ocean. We use 6 hourly wind forcing and surface heat fluxes for two different climates: one with a perennial sea-<span class="hlt">ice</span> cover similar to that of the present day and one with seasonally <span class="hlt">ice</span>-free conditions, similar to that simulated in future projections. Model results confirm that in the present-day climate, sea <span class="hlt">ice</span> takes more than 1 year to transport sediment from all its peripheral seas to the North Pole. However, in a warmer climate, sea-<span class="hlt">ice</span> speeds are significantly faster (for the same wind forcing) and can deposit sediments of Laptev, East Siberian and perhaps also Beaufort Sea origin at the North Pole. This is primarily because of the fact that sea-<span class="hlt">ice</span> interactions are much weaker with a thinner <span class="hlt">ice</span> cover and there is less resistance to drift. We conclude that the presence of <span class="hlt">ice</span>-rafted sediment of Eurasian and North American origin at the North Pole does not imply a perennial sea-<span class="hlt">ice</span> cover in the Arctic Ocean, reconciling the ACEX ocean core data with other land and marine records.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A44B..06R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A44B..06R"><span>Extreme cyclone events in the Arctic: Wintertime variability and <span class="hlt">trends</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rinke, A.; Maturilli, M.; Graham, R. M.; Matthes, H.; Handorf, D.; Cohen, L.; Hudson, S. R.; Moore, J. C.</p> <p>2017-12-01</p> <p>Extreme cyclone events often occur during Arctic winters, and are of concern as they transport heat and moisture into the Arctic, which is associated with mixed-phase clouds and increased longwave downward radiation, and can cause temperatures to rise above freezing resulting in wintertime sea-<span class="hlt">ice</span> melting or retarded sea-<span class="hlt">ice</span> growth. With Arctic amplification and associated reduced sea-<span class="hlt">ice</span> cover and warmer sea surface temperatures, the occurrence of extreme cyclones events could be a plausible scenario. We calculate the spatial patterns, and changes and <span class="hlt">trends</span> of the number of extreme cyclone events in the Arctic based on ERA-Interim six-hourly sea level pressure (SLP) data for winter (November-February) 1979-2015. Further, we analyze the SLP data from the Ny-Ålesund station for the same 37 year period. We define an extreme cyclone event by an extreme low central pressure (SLP below 985 hPa, which is the 5th percentile of the Ny-Ålesund/N-<span class="hlt">ICE</span>2015 SLP data). Typically 20-40 extreme cyclone events (sometimes called `weather bombs') occur in the Arctic North Atlantic per winter season, with an increasing <span class="hlt">trend</span> of 6 events/decade, according to the Ny-Ålesund data. This increased frequency of extreme cyclones drive considerable warming in that region, consistent with the observed significant winter warming of 3 K/decade. The positive winter <span class="hlt">trend</span> in extreme cyclones is dominated by a positive monthly <span class="hlt">trend</span> of about 3-4 events/decade in November-December, due mainly to an increasing persistence of extreme cyclone events. A negative <span class="hlt">trend</span> in January opposes this, while there is no significant <span class="hlt">trend</span> in February. We relate the regional patterns of the <span class="hlt">trend</span> in extreme cyclones to anomalously low sea-<span class="hlt">ice</span> conditions in recent years, together with associated large-scale atmospheric circulation changes such as "blocking-like" circulation patterns (e.g. Scandinavian blocking in December and Ural blocking during January-February).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.C41B0701R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.C41B0701R"><span>The Relationship Between Arctic Sea <span class="hlt">Ice</span> Albedo and the Geophysical Parameters of the <span class="hlt">Ice</span> Cover</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Riihelä, A.</p> <p>2015-12-01</p> <p> <span class="hlt">ice</span> in the central parts of the Arctic Ocean is resistant to the decreasing overall <span class="hlt">trend</span>.A similar analysis is also extended to <span class="hlt">ice</span> concentration, melt season length and other appropriate parameters describing the surface conditions. The results of the analyses are summed up to provide an assessment of the relative impact strengths of the <span class="hlt">ice</span> field parameters on the albedo.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C41A0639L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C41A0639L"><span>Upper Ocean Evolution Across the Beaufort Sea Marginal <span class="hlt">Ice</span> Zone</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lee, C.; Rainville, L.; Gobat, J. I.; Perry, M. J.; Freitag, L. E.; Webster, S.</p> <p>2016-12-01</p> <p>The observed reduction of Arctic summertime sea <span class="hlt">ice</span> <span class="hlt">extent</span> and expansion of the marginal <span class="hlt">ice</span> zone (MIZ) have profound impacts on the balance of processes controlling sea <span class="hlt">ice</span> evolution, including the introduction of several positive feedback mechanisms that may act to accelerate melting. Examples of such feedbacks include increased upper ocean warming though absorption of solar radiation, elevated internal wave energy and mixing that may entrain heat stored in subsurface watermasses (e.g., the relatively warm Pacific Summer and Atlantic waters), and elevated surface wave energy that acts to deform and fracture sea <span class="hlt">ice</span>. Spatial and temporal variability in <span class="hlt">ice</span> properties and open water fraction impact these processes. To investigate how upper ocean structure varies with changing <span class="hlt">ice</span> cover, how the balance of processes shift as a function of <span class="hlt">ice</span> fraction and distance from open water, and how these processes impact sea <span class="hlt">ice</span> evolution, a network of autonomous platforms sampled the atmosphere-<span class="hlt">ice</span>-ocean system in the Beaufort, beginning in spring, well before the start of melt, and ending with the autumn freeze-up. Four long-endurance autonomous Seagliders occupied sections that extended from open water, through the marginal <span class="hlt">ice</span> zone, deep into the pack during summer 2014 in the Beaufort Sea. Gliders penetrated up to 200 km into the <span class="hlt">ice</span> pack, under complete <span class="hlt">ice</span> cover for up to 10 consecutive days. Sections reveal strong fronts where cold, <span class="hlt">ice</span>-covered waters meet waters that have been exposed to solar warming, and O(10 km) scale eddies near the <span class="hlt">ice</span> edge. In the pack, Pacific Summer Water and a deep chlorophyll maximum form distinct layers at roughly 60 m and 80 m, respectively, which become increasingly diffuse late in the season as they progress through the MIZ and into open water. Stratification just above the Pacific Summer Water rapidly weakens near the <span class="hlt">ice</span> edge and temperature variance increases, likely due to mixing or energetic vertical exchange associated with strong</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000037971&hterms=round&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dround','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000037971&hterms=round&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dround"><span>Year-Round Pack <span class="hlt">Ice</span> in the Weddell Sea, Antarctica: Response and Sensitivity to Atmospheric and Oceanic Forcing</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Geiger, Cathleen A.; Ackley, Stephen F.; Hibler, William D., III</p> <p>1997-01-01</p> <p>Using a dynamic-thermodynamic numerical sea-<span class="hlt">ice</span> model, external oceanic and atmospheric forcings on sea <span class="hlt">ice</span> in the Weddell Sea are examined to identify physical processes associated with the seasonal cycle of pack <span class="hlt">ice</span>, and to identify further the parameters that coupled models need to consider in predicting the response of the pack <span class="hlt">ice</span> to climate and ocean-circulation changes. In agreement with earlier studies, the primary influence on the winter <span class="hlt">ice</span>-edge maximum <span class="hlt">extent</span> is air temperature. Ocean heat flux has more impact on the minimum-<span class="hlt">ice</span>-edge <span class="hlt">extent</span> and in reducing pack-<span class="hlt">ice</span> thickness, especially in the eastern-Weddell Sea. Low relative humidity enhances <span class="hlt">ice</span> growth in thin <span class="hlt">ice</span> and open-water regions, producing a more realistic <span class="hlt">ice</span> edge along the coastal areas of the western-Weddell Sea where dry continental air has an impact. The modeled <span class="hlt">extent</span> of the Weddell summer pack is equally sensitive to ocean heat flux and atmospheric relative humidity variations with the more dynamic responses being from the atmosphere. Since the atmospheric regime in the eastern Weddell is dominated by marine intrusions from lower latitudes, with high humidity already, it is unlikely that either the moisture trans- port could be further raised or that it could be significantly lowered because of its distance from the continent (the lower humidity source). Ocean heat-transport variability is shown to lead to overall <span class="hlt">ice</span> thinning in the model response and is a known feature of the actual system, as evidenced by the occurrence of the Weddell Polynya in the mid 1970s.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.C33B0782T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.C33B0782T"><span>Radiative transfer model of snow for bare <span class="hlt">ice</span> regions</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tanikawa, T.; Aoki, T.; Niwano, M.; Hosaka, M.; Shimada, R.; Hori, M.; Yamaguchi, S.</p> <p>2016-12-01</p> <p>Modeling a radiative transfer (RT) for coupled atmosphere-snow-bare <span class="hlt">ice</span> systems is of fundamental importance for remote sensing applications to monitor snow and bare <span class="hlt">ice</span> regions in the Greenland <span class="hlt">ice</span> sheet and for accurate climate change predictions by regional and global climate models. Recently, the RT model for atmosphere-snow system was implemented for our regional and global climate models. However, the bare <span class="hlt">ice</span> region where recently it has been expanded on the Greenland <span class="hlt">ice</span> sheet due to the global warming, has not been implemented for these models, implying that this region leads miscalculations in these climate models. Thus, the RT model of snow for bare <span class="hlt">ice</span> regions is needed for accurate climate change predictions. We developed the RT model for coupled atmosphere-snow-bare <span class="hlt">ice</span> systems, and conducted a sensitivity analysis of the RT model to know the effect of snow, bare <span class="hlt">ice</span> and geometry parameters on the spectral radiant quantities. The RT model considers snow and bare-<span class="hlt">ice</span> inherent optical properties (IOPs), including snow grain size, air bubble size and its concentration and bare <span class="hlt">ice</span> thickness. The conventional light scattering theory, Mie theory, was used for IOP calculations. Monte Carlo method was used for the multiple scattering. The sensitivity analyses showed that spectral albedo for the bare <span class="hlt">ice</span> increased with increasing the concentration of the air bubble in the bare <span class="hlt">ice</span> for visible wavelengths because the air bubble is scatterer with no absorption. For near infrared wavelengths, spectral albedo has no dependence on the air bubble due to the strong light absorption by <span class="hlt">ice</span>. When increasing solar zenith angle, the spectral albedo were increased for all wavelengths. This is the similar <span class="hlt">trend</span> with spectral snow albedo. Cloud cover influenced the bare <span class="hlt">ice</span> spectral albedo by covering direct radiation into diffuse radiation. The purely diffuse radiation has an effective solar zenith angle near 50°. Converting direct into diffuse radiation reduces the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014PhDT........38L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014PhDT........38L"><span>A model of the Greenland <span class="hlt">ice</span> sheet deglaciation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lecavalier, Benoit</p> <p></p> <p>The goal of this thesis is to improve our understanding of the Greenland <span class="hlt">ice</span> sheet (GrIS) and how it responds to climate change. This was achieved using <span class="hlt">ice</span> core records to infer elevation changes of the GrIS during the Holocene (11.7 ka BP to Present). The inferred elevation changes show the response of the <span class="hlt">ice</span> sheet interior to the Holocene Thermal Maximum (HTM; 9-5 ka BP) when temperatures across Greenland were warmer than present. These <span class="hlt">ice</span>-core derived thinning curves act as a new set of key constraints on the deglacial history of the GrIS. Furthermore, a calibration was conducted on a three-dimensional thermomechanical <span class="hlt">ice</span> sheet, glacial isostatic adjustment, and relative sea-level model of GrIS evolution during the most recent deglaciation (21 ka BP to present). The model was data-constrained to a variety of proxy records from paleoclimate archives and present-day observations of <span class="hlt">ice</span> thickness and <span class="hlt">extent</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170003226','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170003226"><span>Does a Relationship Between Arctic Low Clouds and Sea <span class="hlt">Ice</span> Matter?</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Taylor, Patrick C.</p> <p>2016-01-01</p> <p>Arctic low clouds strongly affect the Arctic surface energy budget. Through this impact Arctic low clouds influence important aspects of the Arctic climate system, namely surface and atmospheric temperature, sea <span class="hlt">ice</span> <span class="hlt">extent</span> and thickness, and atmospheric circulation. Arctic clouds are in turn influenced by these elements of the Arctic climate system, and these interactions create the potential for Arctic cloud-climate feedbacks. To further our understanding of potential Arctic cloudclimate feedbacks, the goal of this paper is to quantify the influence of atmospheric state on the surface cloud radiative effect (CRE) and its covariation with sea <span class="hlt">ice</span> concentration (SIC). We build on previous research using instantaneous, active remote sensing satellite footprint data from the NASA A-Train. First, the results indicate significant differences in the surface CRE when stratified by atmospheric state. Second, there is a weak covariation between CRE and SIC for most atmospheric conditions. Third, the results show statistically significant differences in the average surface CRE under different SIC values in fall indicating a 3-5 W m(exp -2) larger LW CRE in 0% versus 100% SIC footprints. Because systematic changes on the order of 1 W m(exp -2) are sufficient to explain the observed long-term reductions in sea <span class="hlt">ice</span> <span class="hlt">extent</span>, our results indicate a potentially significant amplifying sea <span class="hlt">ice</span>-cloud feedback, under certain meteorological conditions, that could delay the fall freeze-up and influence the variability in sea <span class="hlt">ice</span> <span class="hlt">extent</span> and volume. Lastly, a small change in the frequency of occurrence of atmosphere states may yield a larger Arctic cloud feedback than any cloud response to sea <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://rosap.ntl.bts.gov/view/dot/26834','DOTNTL'); return false;" href="https://rosap.ntl.bts.gov/view/dot/26834"><span>Anti-<span class="hlt">icing</span> and de-<span class="hlt">icing</span> superhydrophobic concrete to improve the safety on critical elements on roadway pavements.</span></a></p> <p><a target="_blank" href="http://ntlsearch.bts.gov/tris/index.do">DOT National Transportation Integrated Search</a></p> <p></p> <p>2013-09-01</p> <p>Icy roads lead to treacherous driving conditions in regions of the U.S. resulting in over 450 fatalities per year. Deicing chemicals, such as rock salt help to reduce <span class="hlt">ice</span> formation on roadways to an <span class="hlt">extent</span>, however also result in detrimental effects ...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMPP21A1252A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMPP21A1252A"><span>Modelling the effects of <span class="hlt">ice</span>-sheet activity on CO2 outgassing by Icelandic volcanoes</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Armitage, J. J.; Ferguson, D.; Petersen, K. D.; Creyts, T. T.</p> <p>2017-12-01</p> <p>Glacial cycles may play a significant role in mediating the flux of magmatic CO2 between the Earth's mantle and atmosphere. In Iceland, it is thought that late-Pleistocene deglaciation led to a significant volcanic pulse, evidenced by increased post-glacial lava volumes and changes in melt chemistry consistent with depressurization. Investigating the <span class="hlt">extent</span> to which glacial activity may have affected volcanic CO2 emissions from Iceland, and crucially over what timescale, requires detailed knowledge of how the magma system responded to the growth and collapse of the <span class="hlt">ice</span>-sheet before and after the LGM. To investigate this, we coupled a model of magma generation and transport with a history of <span class="hlt">ice</span>-sheet activity. Our results show that the emplacement and removal of the LGM <span class="hlt">ice</span>-sheet likely led to two significant pulses of magmatic CO2. The first, and most significant of these, is associated with <span class="hlt">ice</span>-sheet growth and occurs as the magma system recovers from glacial loading. This recovery happens from the base of the melting region upwards, producing a pulse of CO2 rich magma that is predicted to reach the surface around 20 ka after the loading event, close in time to the LGM. The second peak in CO2 output occurs abruptly following deglaciation as a consequence of increased rates of melt generation and transport in the shallow mantle. Although these post-glacial melts are relatively depleted in CO2, the increase in magma flux leads to a short-lived period of elevated CO2 emissions. Our results therefore suggest a negative feedback, whereby <span class="hlt">ice</span>-sheet growth produces a delayed pulse of magmatic CO2, which, in addition to increased geothermal heat flux, may contribute towards driving deglaciation, which itself then causes further magmatism and CO2 outgassing. This model is consistent with the seismic structure of the asthenosphere below Iceland, and the established compositional and volumetric <span class="hlt">trends</span> for sub- and post-glacial volcanism in Iceland. These <span class="hlt">trends</span> show that</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eric.ed.gov/?q=arctic&pg=3&id=EJ727887','ERIC'); return false;" href="https://eric.ed.gov/?q=arctic&pg=3&id=EJ727887"><span><span class="hlt">Ice</span>-Free Arctic Ocean?</span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Science Teacher, 2005</p> <p>2005-01-01</p> <p>The current warming <span class="hlt">trends</span> in the Arctic may shove the Arctic system into a seasonally <span class="hlt">ice</span>-free state not seen for more than one million years, according to a new report. The melting is accelerating, and researchers were unable to identify any natural processes that might slow the deicing of the Arctic. "What really makes the Arctic different…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014SolE....5..371S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014SolE....5..371S"><span>Comparing a thermo-mechanical Weichselian <span class="hlt">Ice</span> Sheet reconstruction to reconstructions based on the sea level equation: aspects of <span class="hlt">ice</span> configurations and glacial isostatic adjustment</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schmidt, P.; Lund, B.; Näslund, J.-O.; Fastook, J.</p> <p>2014-05-01</p> <p>In this study we compare a recent reconstruction of the Weichselian <span class="hlt">Ice</span> Sheet as simulated by the University of Maine <span class="hlt">ice</span> sheet model (UMISM) to two reconstructions commonly used in glacial isostatic adjustment (GIA) modelling: <span class="hlt">ICE</span>-5G and ANU (Australian National University, also known as RSES). The UMISM reconstruction is carried out on a regional scale based on thermo-mechanical modelling, whereas ANU and <span class="hlt">ICE</span>-5G are global models based on the sea level equation. The three models of the Weichselian <span class="hlt">Ice</span> Sheet are compared directly in terms of <span class="hlt">ice</span> volume, <span class="hlt">extent</span> and thickness, as well as in terms of predicted glacial isostatic adjustment in Fennoscandia. The three reconstructions display significant differences. Whereas UMISM and ANU includes phases of pronounced advance and retreat prior to the last glacial maximum (LGM), the thickness and areal <span class="hlt">extent</span> of the <span class="hlt">ICE</span>-5G <span class="hlt">ice</span> sheet is more or less constant up until the LGM. During the post-LGM deglaciation phase ANU and <span class="hlt">ICE</span>-5G melt relatively uniformly over the entire <span class="hlt">ice</span> sheet in contrast to UMISM, which melts preferentially from the edges, thus reflecting the fundamental difference in the reconstruction scheme. We find that all three reconstructions fit the present-day uplift rates over Fennoscandia equally well, albeit with different optimal earth model parameters. Given identical earth models, <span class="hlt">ICE</span>-5G predicts the fastest present-day uplift rates, and ANU the slowest. Moreover, only for ANU can a unique best-fit model be determined. For UMISM and <span class="hlt">ICE</span>-5G there is a range of earth models that can reproduce the present-day uplift rates equally well. This is understood from the higher present-day uplift rates predicted by <span class="hlt">ICE</span>-5G and UMISM, which result in bifurcations in the best-fit upper- and lower-mantle viscosities. We study the areal distributions of present-day residual surface velocities in Fennoscandia and show that all three reconstructions generally over-predict velocities in southwestern Fennoscandia and that</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70190395','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70190395"><span>Polar bears and sea <span class="hlt">ice</span> habitat change</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Durner, George M.; Atwood, Todd C.; Butterworth, Andy</p> <p>2017-01-01</p> <p>The polar bear (Ursus maritimus) is an obligate apex predator of Arctic sea <span class="hlt">ice</span> and as such can be affected by climate warming-induced changes in the <span class="hlt">extent</span> and composition of pack <span class="hlt">ice</span> and its impacts on their seal prey. Sea <span class="hlt">ice</span> declines have negatively impacted some polar bear subpopulations through reduced energy input because of loss of hunting habitats, higher energy costs due to greater <span class="hlt">ice</span> drift, <span class="hlt">ice</span> fracturing and open water, and ultimately greater challenges to recruit young. Projections made from the output of global climate models suggest that polar bears in peripheral Arctic and sub-Arctic seas will be reduced in numbers or become extirpated by the end of the twenty-first century if the rate of climate warming continues on its present trajectory. The same projections also suggest that polar bears may persist in the high-latitude Arctic where heavy multiyear sea <span class="hlt">ice</span> that has been typical in that region is being replaced by thinner annual <span class="hlt">ice</span>. Underlying physical and biological oceanography provides clues as to why polar bear in some regions are negatively impacted, while bears in other regions have shown no apparent changes. However, continued declines in sea <span class="hlt">ice</span> will eventually challenge the survival of polar bears and efforts to conserve them in all regions of the Arctic.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1986JGR....9110661E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1986JGR....9110661E"><span>Classification of sea <span class="hlt">ice</span> types with single-band (33.6 GHz) airborne passive microwave imagery</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Eppler, Duane T.; Farmer, L. Dennis; Lohanick, Alan W.; Hoover, Mervyn</p> <p>1986-09-01</p> <p>During March 1983 extensive high-quality airborne passive Ka band (33.6 GHz) microwave imagery and coincident high-resolution aerial photography were obtained of <span class="hlt">ice</span> along a 378-km flight line in the Beaufort Sea. Analysis of these data suggests that four classes of winter surfaces can be distinguished solely on the basis of 33.6-GHz brightness temperature: open water, frazil, old <span class="hlt">ice</span>, and young/first-year <span class="hlt">ice</span>. New <span class="hlt">ice</span> (excluding frazil) and nilas display brightness temperatures that overlap the range of temperatures characteristic of old <span class="hlt">ice</span> and, to a lesser <span class="hlt">extent</span>, young/first-year <span class="hlt">ice</span>. Scenes in which a new <span class="hlt">ice</span> or nilas are present in appreciable amounts are subject to substantial errors in classification if static measures of Ka band radiometric brightness temperature alone are considered. Textural characteristics of nilas and new <span class="hlt">ice</span>, however, differ significantly from textural features characteristic of other <span class="hlt">ice</span> types and probably can be used with brightness temperature data to classify <span class="hlt">ice</span> type in high-resolution single-band microwave images. In any case, open water is radiometrically the coldest surface observed in any scene. Lack of overlap between brightness temperatures characteristic of other surfaces indicates that estimates of the areal <span class="hlt">extent</span> of open water based on only 33.6-GHz brightness temperatures are accurate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1612776S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1612776S"><span>Reconstructions of the Weichselian <span class="hlt">ice</span> sheet, a comparative study of a thermo-mechanical approach to GIA driven models.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schmidt, Peter; Lund, Björn; Näslund, Jens-Ove; Fastook, James</p> <p>2014-05-01</p> <p>Observations of glacial isostatic adjustment (GIA) have been used both to study the mechanical properties of the Earth and to invert for Northern Hemisphere palaeo-<span class="hlt">ice</span>-sheets. This is typically done by solving the sea-level equation using simplified scaling laws to control <span class="hlt">ice</span>-sheet thickness. However, past <span class="hlt">ice</span>-sheets can also be reconstructed based on thermo-mechanical modelling driven by palaeo-climate data, invoking simple analytical models to account for the Earth's response. Commonly, both approaches use dated geological markers to constrain the <span class="hlt">ice</span>-sheet margin location. Irrespective of the approach, the resulting <span class="hlt">ice</span>-sheet reconstruction depends on the earth response, although the interdependence between the <span class="hlt">ice</span> model and the earth model differs and therefore the two types of reconstructions could provide complementary information on Earth properties. We compare a thermo-mechanical reconstruction of the Weichselian <span class="hlt">ice</span>-sheet using the UMISM model (Näslund, 2010) to two GIA driven reconstructions, ANU (Lambeck et al., 2010) and <span class="hlt">ICE</span>-5G (Peltier & Fairbanks, 2006), commonly used in GIA modelling. We evaluate the three reconstructions both in terms of <span class="hlt">ice</span>-sheet configurations and predicted Fennoscandian surface deformation <span class="hlt">ICE</span>-5G comprise the largest reconstructed <span class="hlt">ice</span>-sheet whereas ANU and UMISM are more similar in volume and areal <span class="hlt">extent</span>. Significant differences still exists between ANU and UMISM, especially during the final deglaciation phase. Prior to the final retreat of the <span class="hlt">ice</span>-sheet, <span class="hlt">ICE</span>-5G is displays a massive and more or less constant <span class="hlt">ice</span>-sheet configuration, while both ANU and UMISM fluctuates with at times almost <span class="hlt">ice</span>-free conditions, such as during MIS3. This results in <span class="hlt">ICE</span>-5G being close to isostatic equilibrium at LGM, whereas ANU and UMISM are not. Hence, the pre-LGM evolution of the Weichselian <span class="hlt">ice</span>-sheet needs to be considered in GIA studies. For example, perturbing the ANU or UMISM reconstructions we find that changes more recent than 36 kyr BP</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C14B..07T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C14B..07T"><span>Spaceborne estimated long-term <span class="hlt">trends</span> (1980s - 2013) of albedo and melting season length over the Greenland <span class="hlt">ice</span> sheet and linkages to climate drivers</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tedesco, M.; Stroeve, J. C.</p> <p>2014-12-01</p> <p>The length of the melting season and surface albedo modulate the amount of meltwater produced over the Greenland <span class="hlt">ice</span> sheet. The two quantities are intimately connected through a suite of non-linear processes: for example, early melting can reduce the surface albedo (through constructive grain size metamorphism), hence affecting the surface energy balance and further increasing melting. Over the past years, several studies have highlighted increased melting concurring, with a decrease of mean surface albedo over Greenland. However, few studies have examined the duration of the melting season, its implication for surface processes and linkages to climate drivers. Moreover, the majority (if not all) of the studies assessing albedo <span class="hlt">trends</span> from spaceborne data over Greenland have focused on the last decade or so (2000 - 2013) because they use data collected over the same period by the Moderate Resolution Imaging Spectroradiometer (MODIS). Here, we evaluate and synthesize long-term <span class="hlt">trends</span> in the length of the melting season (1979 - 2013) derived from spaceborne microwave observations together with surface albedo <span class="hlt">trends</span> for the period 1982 - 2013 using data from the Advanced Very High Resolution Radiometer (AVHRR). To our knowledge, this is the first time that <span class="hlt">trends</span> in Greenland albedo and melt season length are discussed for the periods considered in this study. Our results point to a lengthening of the melting season as a consequence of earlier melt onset and later refreeze and to a decrease of mean albedo (1982 - 2013) over the Greenland <span class="hlt">ice</span> sheet, with <span class="hlt">trends</span> being spatially variable. To account for this spatial variability, the results of an analysis at regional scales over 12 different regions (defined by elevation and drainage systems) are also reported. The robustness of the results is evaluated by means of a comparative analysis of the results obtained from both AVHRR and MODIS when overlapping data are available (2000 - 2013). Lastly, because large</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRD..12210855K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..12210855K"><span>Vertical thermodynamic structure of the troposphere during the Norwegian young sea <span class="hlt">ICE</span> expedition (N-<span class="hlt">ICE</span>2015)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kayser, Markus; Maturilli, Marion; Graham, Robert M.; Hudson, Stephen R.; Rinke, Annette; Cohen, Lana; Kim, Joo-Hong; Park, Sang-Jong; Moon, Woosok; Granskog, Mats A.</p> <p>2017-10-01</p> <p>The Norwegian young sea <span class="hlt">ICE</span> (N-<span class="hlt">ICE</span>2015) expedition was designed to investigate the atmosphere-snow-<span class="hlt">ice</span>-ocean interactions in the young and thin sea <span class="hlt">ice</span> regime north of Svalbard. Radiosondes were launched twice daily during the expedition from January to June 2015. Here we use these upper air measurements to study the multiple cyclonic events observed during N-<span class="hlt">ICE</span>2015 with respect to changes in the vertical thermodynamic structure, moisture content, and boundary layer characteristics. We provide statistics of temperature inversion characteristics, static stability, and boundary layer <span class="hlt">extent</span>. During winter, when radiative cooling is most effective, we find the strongest impact of synoptic cyclones. Changes to thermodynamic characteristics of the boundary layer are associated with transitions between the radiatively "clear" and "opaque" atmospheric states. In spring, radiative fluxes warm the surface leading to lifted temperature inversions and a statically unstable boundary layer. Further, we compare the N-<span class="hlt">ICE</span>2015 static stability distributions to corresponding profiles from ERA-Interim reanalysis, from the closest land station in the Arctic North Atlantic sector, Ny-Ålesund, and to soundings from the SHEBA expedition (1997/1998). We find similar stability characteristics for N-<span class="hlt">ICE</span>2015 and SHEBA throughout the troposphere, despite differences in location, sea <span class="hlt">ice</span> thickness, and snow cover. For Ny-Ålesund, we observe similar characteristics above 1000 m, while the topography and <span class="hlt">ice</span>-free fjord surrounding Ny-Ålesund generate great differences below. The long-term radiosonde record (1993-2014) from Ny-Ålesund indicates that during the N-<span class="hlt">ICE</span>2015 spring period, temperatures were close to the climatological mean, while the lowest 3000 m were 1-3°C warmer than the climatology during winter.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70025908','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70025908"><span>Exposed water <span class="hlt">ice</span> discovered near the south pole of Mars</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Titus, T.N.; Kieffer, H.H.; Christensen, P.R.</p> <p>2003-01-01</p> <p>The Mars Odyssey Thermal Emission Imaging System (THEMIS) has discovered water <span class="hlt">ice</span> exposed near the edge of Mars' southern perennial polar cap. The surface H2O <span class="hlt">ice</span> was first observed by THEMIS as a region that was cooler than expected for dry soil at that latitude during the summer season. Diurnal and seasonal temperature <span class="hlt">trends</span> derived from Mars Global Surveyor Thermal Emission Spectrometer observations indicate that there is H2O <span class="hlt">ice</span> at the surface. Viking observations, and the few other relevant THEMIS observations, indicate that surface H2O <span class="hlt">ice</span> may be widespread around and under the perennial CO2 cap.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19920051541&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3DParkinsons','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19920051541&hterms=Parkinsons&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3DParkinsons"><span>Interannual variability of monthly Southern Ocean sea <span class="hlt">ice</span> distributions</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parkinson, Claire L.</p> <p>1992-01-01</p> <p>The interannual variability of the Southern-Ocean sea-<span class="hlt">ice</span> distributions was mapped and analyzed using data from Nimbus-5 ESMR and Nimbus-7 SMMR, collected from 1973 to 1987. The set of 12 monthly maps obtained reveals many details on spatial variability that are unobtainable from time series of <span class="hlt">ice</span> <span class="hlt">extents</span>. These maps can be used as baseline maps for comparisons against future Southern Ocean sea <span class="hlt">ice</span> distributions. The maps are supplemented by more detailed maps of the frequency of <span class="hlt">ice</span> coverage, presented in this paper for one month within each of the four seasons, and by the breakdown of these results to the periods covered individually by each of the two passive-microwave imagers.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_23 --> <div id="page_24" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="461"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.C11C..05F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.C11C..05F"><span>A Decade of Arctic Sea <span class="hlt">Ice</span> Thickness Change from Airborne and Satellite Altimetry (Invited)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Farrell, S. L.; Richter-Menge, J.; Kurtz, N. T.; McAdoo, D. C.; Newman, T.; Zwally, H.; Ruth, J.</p> <p>2013-12-01</p> <p>Altimeters on both airborne and satellite platforms provide direct measurements of sea <span class="hlt">ice</span> freeboard from which sea <span class="hlt">ice</span> thickness may be calculated. Satellite altimetry observations of Arctic sea <span class="hlt">ice</span> from ICESat and CryoSat-2 indicate a significant decline in <span class="hlt">ice</span> thickness, and volume, over the last decade. During this time the <span class="hlt">ice</span> pack has experienced a rapid change in its composition, transitioning from predominantly thick, multi-year <span class="hlt">ice</span> to thinner, increasingly seasonal <span class="hlt">ice</span>. We will discuss the regional <span class="hlt">trends</span> in <span class="hlt">ice</span> thickness derived from ICESat and <span class="hlt">Ice</span>Bridge altimetry between 2003 and 2013, contrasting observations of the multi-year <span class="hlt">ice</span> pack with seasonal <span class="hlt">ice</span> zones. ICESat ceased operation in 2009, and the final, reprocessed data set became available recently. We extend our analysis to April 2013 using data from the <span class="hlt">Ice</span>Bridge airborne mission, which commenced operations in 2009. We describe our current efforts to more accurately convert from freeboard to <span class="hlt">ice</span> thickness, with a modified methodology that corrects for range errors, instrument biases, and includes an enhanced treatment of snow depth, with respect to <span class="hlt">ice</span> type. With the planned launch by NASA of ICESat-2 in 2016 we can expect continuity of the sea <span class="hlt">ice</span> thickness time series through the end of this decade. Data from the ICESat-2 mission, together with ongoing observations from CryoSat-2, will allow us to understand both the decadal <span class="hlt">trends</span> and inter-annual variability in the Arctic sea <span class="hlt">ice</span> thickness record. We briefly present the status of planned ICESat-2 sea <span class="hlt">ice</span> data products, and demonstrate the utility of micro-pulse, photon-counting laser altimetry over sea <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20060017828','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20060017828"><span>Evaluation of the Simulation of Arctic and Antarctic Sea <span class="hlt">Ice</span> Coverages by Eleven Major Global Climate Models</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Parksinson, Claire; Vinnikov, Konstantin Y.; Cavalieri, Donald J.</p> <p>2005-01-01</p> <p>Comparison of polar sea <span class="hlt">ice</span> results from 11 major global climate models and satellite-derived observations for 1979-2004 reveals that each of the models is simulating seasonal cycles that are phased at least approximately correctly in both hemispheres. Each is also simulating various key aspects of the observed <span class="hlt">ice</span> cover distributions, such as winter <span class="hlt">ice</span> not only throughout the central Arctic basin but also throughout Hudson Bay, despite its relatively low latitudes. However, some of the models simulate too much <span class="hlt">ice</span>, others too little <span class="hlt">ice</span> (in some cases varying depending on hemisphere and/or season), and some match the observations better in one season versus another. Several models do noticeably better in the Northern Hemisphere than in the Southern Hemisphere, and one does noticeably better in the Southern Hemisphere. In the Northern Hemisphere all simulate monthly average <span class="hlt">ice</span> <span class="hlt">extents</span> to within +/-5.1 x 10(exp 6)sq km of the observed <span class="hlt">ice</span> <span class="hlt">extent</span> throughout the year; and in the Southern Hemisphere all except one simulate the monthly averages to within +/-6.3 x 10(exp 6) sq km of the observed values. All the models properly simulate a lack of winter <span class="hlt">ice</span> to the west of Norway; however, most do not obtain as much absence of <span class="hlt">ice</span> immediately north of Norway as the observations show, suggesting an under simulation of the North Atlantic Current. The spread in monthly averaged <span class="hlt">ice</span> <span class="hlt">extents</span> amongst the 11 model simulations is greater in the Southern Hemisphere than in the Northern Hemisphere and greatest in the Southern Hemisphere winter and spring.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000945.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000945.html"><span>Operation <span class="hlt">Ice</span>Bridge Turns Five</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2017-12-08</p> <p>In May 2014, two new studies concluded that a section of the land-based West Antarctic <span class="hlt">ice</span> sheet had reached a point of inevitable collapse. Meanwhile, fresh observations from September 2014 showed sea <span class="hlt">ice</span> around Antarctica had reached its greatest <span class="hlt">extent</span> since the late 1970s. To better understand such dynamic and dramatic differences in the region's land and sea <span class="hlt">ice</span>, researchers are travelling south to Antarctica this month for the sixth campaign of NASA’s Operation <span class="hlt">Ice</span>Bridge. The airborne campaign, which also flies each year over Greenland, makes annual surveys of the <span class="hlt">ice</span> with instrumented research aircraft. Instruments range from lasers that map the elevation of the <span class="hlt">ice</span> surface, radars that "see" below it, and downward looking cameras to provide a natural-color perspective. The Digital Mapping System (DMS) camera acquired the above photo during the mission’s first science flight on October 16, 2009. At the time of the image, the DC-8 aircraft was flying at an altitude of 515 meters (1,700 feet) over heavily compacted first-year sea <span class="hlt">ice</span> along the edge of the Amundsen Sea. Since that first flight, much has been gleaned from <span class="hlt">Ice</span>Bridge data. For example, images from an <span class="hlt">Ice</span>Bridge flight in October 2011 revealed a massive crack running about 29 kilometers (18 miles) across the floating tongue of Antarctica's Pine Island Glacier. The crack ultimately led to a 725-square-kilometer (280-square-mile) iceberg. In 2012, <span class="hlt">Ice</span>Bridge data was a key part of a new map of Antarctica called Bedmap2. By combining surface elevation, <span class="hlt">ice</span> thickness, and bedrock topography, Bedmap2 gives a clearer picture of Antarctica from the <span class="hlt">ice</span> surface down to the land surface. Discoveries have been made in Greenland, too, including the identification of a 740-kilometer-long (460-mile-long) mega canyon below the <span class="hlt">ice</span> sheet. Repeated measurements of land and sea <span class="hlt">ice</span> from aircraft extend the record of observations once made by NASA’s <span class="hlt">Ice</span>, Cloud, and Land Elevation Satellite, or ICESat, which</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.1023C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.1023C"><span>A New Attempt of 2-D Numerical <span class="hlt">Ice</span> Flow Model to Reconstruct Paleoclimate from Mountain Glaciers</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Candaş, Adem; Akif Sarıkaya, Mehmet</p> <p>2017-04-01</p> <p>A new two dimensional (2D) numerical <span class="hlt">ice</span> flow model is generated to simulate the steady-state glacier <span class="hlt">extent</span> for a wide range of climate conditions. The simulation includes the flow of <span class="hlt">ice</span> enforced by the annual mass balance gradient of a valley glacier. The annual mass balance is calculated by the difference of the net accumulation and ablation of snow and (or) <span class="hlt">ice</span>. The generated model lets users to compare the simulated and field observed <span class="hlt">ice</span> <span class="hlt">extent</span> of paleoglaciers. As a result, model results provide the conditions about the past climates since simulated <span class="hlt">ice</span> <span class="hlt">extent</span> is a function of predefined climatic conditions. To predict the glacier shape and distribution in two dimension, time dependent partial differential equation (PDE) is solved. Thus, a 2D glacier flow model code is constructed in MATLAB and a finite difference method is used to solve this equation. On the other hand, Parallel <span class="hlt">Ice</span> Sheet Model (PISM) is used to regenerate paleoglaciers in the same area where the MATLAB code is applied. We chose the Mount Dedegöl, an extensively glaciated mountain in SW Turkey, to apply both models. Model results will be presented and discussed in this presentation. This study was supported by TÜBİTAK 114Y548 project.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19840002650','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19840002650"><span>Antartic sea <span class="hlt">ice</span>, 1973 - 1976: Satellite passive-microwave observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zwally, H. J.; Comiso, J. C.; Parkinson, C. L.; Campbell, W. J.; Carsey, F. D.; Gloersen, P.</p> <p>1983-01-01</p> <p>Data from the Electrically Scanning Microwave Radiometer (ESMR) on the Nimbus 5 satellite are used to determine the <span class="hlt">extent</span> and distribution of Antarctic sea <span class="hlt">ice</span>. The characteristics of the southern ocean, the mathematical formulas used to obtain quantitative sea <span class="hlt">ice</span> concentrations, the general characteristics of the seasonal sea <span class="hlt">ice</span> growth/decay cycle and regional differences, and the observed seasonal growth/decay cycle for individual years and interannual variations of the <span class="hlt">ice</span> cover are discussed. The sea <span class="hlt">ice</span> data from the ESMR are presented in the form of color-coded maps of the Antarctic and the southern oceans. The maps show brightness temperatures and concentrations of pack <span class="hlt">ice</span> averaged for each month, 4-year monthly averages, and month-to-month changes. Graphs summarizing the results, such as areas of sea <span class="hlt">ice</span> as a function of time in the various sectors of the southern ocean are included. The images demonstrate that satellite microwave data provide unique information on large-scale sea <span class="hlt">ice</span> conditions for determining climatic conditions in polar regions and possible global climatic changes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ISPAn.IV2..311X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ISPAn.IV2..311X"><span>Lake <span class="hlt">Ice</span> Monitoring with Webcams</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiao, M.; Rothermel, M.; Tom, M.; Galliani, S.; Baltsavias, E.; Schindler, K.</p> <p>2018-05-01</p> <p>Continuous monitoring of climate indicators is important for understanding the dynamics and <span class="hlt">trends</span> of the climate system. Lake <span class="hlt">ice</span> has been identified as one such indicator, and has been included in the list of Essential Climate Variables (ECVs). Currently there are two main ways to survey lake <span class="hlt">ice</span> cover and its change over time, in-situ measurements and satellite remote sensing. The challenge with both of them is to ensure sufficient spatial and temporal resolution. Here, we investigate the possibility to monitor lake <span class="hlt">ice</span> with video streams acquired by publicly available webcams. Main advantages of webcams are their high temporal frequency and dense spatial sampling. By contrast, they have low spectral resolution and limited image quality. Moreover, the uncontrolled radiometry and low, oblique viewpoints result in heavily varying appearance of water, <span class="hlt">ice</span> and snow. We present a workflow for pixel-wise semantic segmentation of images into these classes, based on state-of-the-art encoder-decoder Convolutional Neural Networks (CNNs). The proposed segmentation pipeline is evaluated on two sequences featuring different ground sampling distances. The experiment suggests that (networks of) webcams have great potential for lake <span class="hlt">ice</span> monitoring. The overall per-pixel accuracies for both tested data sets exceed 95 %. Furthermore, per-image discrimination between <span class="hlt">ice</span>-on and <span class="hlt">ice</span>-off conditions, derived by accumulating per-pixel results, is 100 % correct for our test data, making it possible to precisely recover freezing and thawing dates.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170008477','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170008477"><span>Improving Our Understanding of Antarctic Sea <span class="hlt">Ice</span> with NASA's Operation <span class="hlt">Ice</span>Bridge and the Upcoming ICESat-2 Mission</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Petty, Alek A.; Markus, Thorsten; Kurtz, Nathan T.</p> <p>2017-01-01</p> <p>Antarctic sea <span class="hlt">ice</span> is a crucial component of the global climate system. Rapid sea <span class="hlt">ice</span> production regimes around Antarctica feed the lower branch of the Southern Ocean overturning circulation through intense brine rejection and the formation of Antarctic Bottom Water (e.g., Orsi et al. 1999; Jacobs 2004), while the northward transport and subsequent melt of Antarctic sea <span class="hlt">ice</span> drives the upper branch of the overturning circulation through freshwater input (Abernathy et al. 2016). Wind-driven <span class="hlt">trends</span> in Antarctic sea <span class="hlt">ice</span> (Holland Kwok 2012) have likely increased the transport of freshwater away from the Antarctic coastline, significantly altering the salinity distribution of the Southern Ocean (Haumann et al. 2016). Conversely, weaker sea <span class="hlt">ice</span> production and the lack of shelf water formation over the Amundsen and Bellingshausen shelf seas promote intrusion of warm Circumpolar Deep Water onto the continental shelf and the ocean-driven melting of several <span class="hlt">ice</span> shelves fringing the West Antarctic <span class="hlt">Ice</span> Sheet (e.g., Jacobs et al. 2011; Pritchard et al. 2012; Dutrieux et al. 2014). Sea <span class="hlt">ice</span> conditions around Antarctica are also increasingly considered an important factor impacting local atmospheric conditions and the surface melting of Antarctic <span class="hlt">ice</span> shelves (e.g., Scambos et al. 2017). Sea <span class="hlt">ice</span> formation around Antarctica is responsive to the strong regional variability in atmospheric forcing present around Antarctica, driving this bimodal variability in the behavior and properties of the underlying shelf seas (e.g., Petty et al. 2012; Petty et al. 2014).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017CliPa..13..533D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017CliPa..13..533D"><span>A 21 000-year record of fluorescent organic matter markers in the WAIS Divide <span class="hlt">ice</span> core</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>D'Andrilli, Juliana; Foreman, Christine M.; Sigl, Michael; Priscu, John C.; McConnell, Joseph R.</p> <p>2017-05-01</p> <p>Englacial <span class="hlt">ice</span> contains a significant reservoir of organic material (OM), preserving a chronological record of materials from Earth's past. Here, we investigate if OM composition surveys in <span class="hlt">ice</span> core research can provide paleoecological information on the dynamic nature of our Earth through time. Temporal <span class="hlt">trends</span> in OM composition from the early Holocene extending back to the Last Glacial Maximum (LGM) of the West Antarctic <span class="hlt">Ice</span> Sheet Divide (WD) <span class="hlt">ice</span> core were measured by fluorescence spectroscopy. Multivariate parallel factor (PARAFAC) analysis is widely used to isolate the chemical components that best describe the observed variation across three-dimensional fluorescence spectroscopy (excitation-emission matrices; EEMs) assays. Fluorescent OM markers identified by PARAFAC modeling of the EEMs from the LGM (27.0-18.0 kyr BP; before present 1950) through the last deglaciation (LD; 18.0-11.5 kyr BP), to the mid-Holocene (11.5-6.0 kyr BP) provided evidence of different types of fluorescent OM composition and origin in the WD <span class="hlt">ice</span> core over 21.0 kyr. Low excitation-emission wavelength fluorescent PARAFAC component one (C1), associated with chemical species similar to simple lignin phenols was the greatest contributor throughout the <span class="hlt">ice</span> core, suggesting a strong signature of terrestrial OM in all climate periods. The component two (C2) OM marker, encompassed distinct variability in the <span class="hlt">ice</span> core describing chemical species similar to tannin- and phenylalanine-like material. Component three (C3), associated with humic-like terrestrial material further resistant to biodegradation, was only characteristic of the Holocene, suggesting that more complex organic polymers such as lignins or tannins may be an ecological marker of warmer climates. We suggest that fluorescent OM markers observed during the LGM were the result of greater continental dust loading of lignin precursor (monolignol) material in a drier climate, with lower marine influences when sea <span class="hlt">ice</span> <span class="hlt">extent</span> was higher and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1814695S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1814695S"><span>N-<span class="hlt">ICE</span>2015: Multi-disciplinary study of the young sea <span class="hlt">ice</span> system north of Svalbard from winter to summer.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Steen, Harald; Granskog, Mats; Assmy, Philipp; Duarte, Pedro; Hudson, Stephen; Gerland, Sebastian; Spreen, Gunnar; Smedsrud, Lars H.</p> <p>2016-04-01</p> <p>The Arctic Ocean is shifting to a new regime with a thinner and smaller sea-<span class="hlt">ice</span> area cover. Until now, winter sea <span class="hlt">ice</span> <span class="hlt">extent</span> has changed less than during summer, as the heat loss to the atmosphere during autumn and winter is large enough form an <span class="hlt">ice</span> cover in most regions. The insulating snow cover also heavily influences the winter <span class="hlt">ice</span> growth. Consequently, the older, thicker multi-year sea <span class="hlt">ice</span> has been replace by a younger and thinner sea. These large changes in the sea <span class="hlt">ice</span> cover may have dramatic consequences for ecosystems, energy fluxes and ultimately atmospheric circulation and the Northern Hemisphere climate. To study the effects of the changing Arctic the Norwegian Polar Institute, together with national and international partners, launched from January 11 to June 24, 2015 the Norwegian Young Sea <span class="hlt">ICE</span> cruise 2015 (N-<span class="hlt">ICE</span>2015). N-<span class="hlt">ICE</span>2015 was a multi-disciplinary cruise aimed at simultaneously studying the effect of the Arctic Ocean changes in the sea <span class="hlt">ice</span>, the atmosphere, in radiation, in ecosystems. as well as water chemistry. R/V Lance was frozen into the drift <span class="hlt">ice</span> north of Svalbard at about N83 E25 and drifted passively southwards with the <span class="hlt">ice</span> until she was broken loose. When she was loose, R/V Lance was brought back north to a similar starting position. While fast in the <span class="hlt">ice</span>, she served as a living and working platform for 100 scientist and engineers from 11 countries. One aim of N-<span class="hlt">ICE</span>2015 is to present a comprehensive data-set on the first year <span class="hlt">ice</span> dominated system available for the scientific community describing the state and changes of the Arctic sea <span class="hlt">ice</span> system from freezing to melt. Analyzing the data is progressing and some first results will be presented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.C23B0610L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.C23B0610L"><span>Late glacial and Early Holocene climatic conditions along the margin of the Greenland <span class="hlt">Ice</span> Sheet, registered by glacial <span class="hlt">extents</span> in Milne Land, east Greenland</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Levy, L.; Kelly, M. A.; Lowell, T. V.</p> <p>2010-12-01</p> <p>Determining the mechanisms that caused past abrupt climate changes is important for understanding today’s rapidly warming climate and, in particular, whether we may be faced with abrupt climate change in the future. Scientists, policy makers and the public are concerned about ongoing warming because it is sending our climate into unprecedented territory at a rapid pace. The Younger Dryas cold event (~12,850-11,650 cal yr B.P.) was an abrupt climate event that occurred during the last transition from glacial to interglacial conditions. Due to its abrupt nature and the magnitude of temperature change that occurred, the Younger Dryas has been the focus of extensive research, however, the mechanisms that caused this cold event are still not well understood. Wide belts (up to 5 km) of moraines, known as the Milne Land stade moraines, are present in the Scoresby Sund region of central east Greenland. Previous work in the region using a combination of equilibrium line altitudes, surface exposure dating of moraines, and relative sea level changes indicates that mountain glacier advances during Younger Dryas time represent only moderate summer temperature cooling (~3-4C colder than at present). In contrast, Greenland <span class="hlt">ice</span> cores, which register mean annual temperatures, indicate that Younger Dryas temperatures over the <span class="hlt">ice</span> sheet were ~15C colder than at present. This mismatch between the two nearby paleoclimate records is interpreted to result from strong seasonality (very cold winters and only moderately cold summers) during Younger Dryas time. We are examining seasonality during Younger Dryas time by developing records of summer temperatures from local glaciers in Milne Land (71.0°N, 25.6°W). These mountain glaciers are located adjacent to the Greenland <span class="hlt">Ice</span> Sheet, less than 50 km from the location of Renland <span class="hlt">Ice</span> core and only ~250 km from the locations of the GISP2 and GRIP cores. We present new 10Be ages of local glacial <span class="hlt">extents</span> in Milne Land. Ages range from 11,880 yr</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017PhDT.......131M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017PhDT.......131M"><span>Investigating the Effects of Environmental Solutes on the Reaction Environment in <span class="hlt">Ice</span> and at <span class="hlt">Ice</span> Surfaces</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Malley, Philip Patrick Anthony</p> <p></p> <p>The reaction environments present in water, <span class="hlt">ice</span>, and at <span class="hlt">ice</span> surfaces are physically distinct from one another and studies have shown that photolytic reactions can take place at different rates in the different media. Kinetics of reactions in frozen media are measured in snow and <span class="hlt">ice</span> prepared from deionized water. This reduces experimental artifacts, but is not relevant to snow in the environment, which contains solutes. We have monitored the effect of nonchromophoric (will not absorb sunlight) organic matter on the photolytic fate of the polycyclic aromatic hydrocarbons (PAHs) phenanthrene, pyrene, and anthracene in <span class="hlt">ice</span> and at <span class="hlt">ice</span> surfaces. Nonchromophoric organic matter reduced photolysis rates to below our detection limit in bulk <span class="hlt">ice</span>, and reduced rates at <span class="hlt">ice</span> surfaces to a lesser <span class="hlt">extent</span> due to the PAHs partially partitioning to the organics present. In addition, we have monitored the effect of chromophoric (will absorb sunlight) dissolved organic matter (cDOM) on the fate of anthracene in water, <span class="hlt">ice</span>, and <span class="hlt">ice</span> surfaces. cDOM reduced rates in all three media. Suppression in liquid water was due to physical interactions between anthracene and the cDOM, rather than to competitive photon absorbance. More suppression was observed in <span class="hlt">ice</span> cubes and <span class="hlt">ice</span> granules than in liquid water due to a freeze concentrating effect. Sodium Chloride (NaCl) is another ubiquitous environmental solute that can influence reaction kinetics in water, <span class="hlt">ice</span>, and at <span class="hlt">ice</span> surfaces. Using Raman microscopy, we have mapped the surface of <span class="hlt">ice</span> of frozen NaCl solutions at 0.02M and 0.6M, as well as the surface of frozen samples of Sargasso Sea Water. At temperatures above and below the eutectic temperature (-21.1°C). Above the eutectic, regions of <span class="hlt">ice</span> and liquid water were observed in all samples. Liquid regions generally took the form of channels. Channel widths and fractional liquid surface coverage increased with NaCl concentration and temperature. Volume maps of the three samples at temperatures</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.7692A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.7692A"><span>Timing and regional patterns of snowmelt on Antarctic sea <span class="hlt">ice</span> from passive microwave satellite observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Arndt, Stefanie; Willmes, Sascha; Dierking, Wolfgang; Nicolaus, Marcel</p> <p>2016-04-01</p> <p>The better understanding of temporal variability and regional distribution of surface melt on Antarctic sea <span class="hlt">ice</span> is crucial for the understanding of atmosphere-ocean interactions and the determination of mass and energy budgets of sea <span class="hlt">ice</span>. Since large regions of Antarctic sea <span class="hlt">ice</span> are covered with snow during most of the year, observed inter-annual and regional variations of surface melt mainly represents melt processes in the snow. It is therefore important to understand the mechanisms that drive snowmelt, both at different times of the year and in different regions around Antarctica. In this study we combine two approaches for observing both surface and volume snowmelt by means of passive microwave satellite data. The former is achieved by measuring diurnal differences of the brightness temperature TB at 37 GHz, the latter by analyzing the ratio TB(19GHz)/TB(37GHz). Moreover, we use both melt onset proxies to divide the Antarctic sea <span class="hlt">ice</span> cover into characteristic surface melt patterns from 1988/89 to 2014/15. Our results indicate four characteristic melt types. On average, 43% of the <span class="hlt">ice</span>-covered ocean shows diurnal freeze-thaw cycles in the surface snow layer, resulting in temporary melt (Type A), less than 1% shows continuous snowmelt throughout the snowpack, resulting in strong melt over a period of several days (Type B), 19% shows Type A and B taking place consecutively (Type C), and for 37% no melt is observed at all (Type D). Continuous melt is primarily observed in the outflow of the Weddell Gyre and in the northern Ross Sea, usually 20 days after the onset of temporary melt. Considering the entire data set, snowmelt processes and onset do not show significant temporal <span class="hlt">trends</span>. Instead, areas of increasing (decreasing) sea-<span class="hlt">ice</span> <span class="hlt">extent</span> have longer (shorter) periods of continuous snowmelt.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ESD.....6..583G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ESD.....6..583G"><span>Atmospheric moisture transport: the bridge between ocean evaporation and Arctic <span class="hlt">ice</span> melting</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gimeno, L.; Vázquez, M.; Nieto, R.; Trigo, R. M.</p> <p>2015-09-01</p> <p>Changes in the atmospheric moisture transport have been proposed as a vehicle for interpreting some of the most significant changes in the Arctic region. The increasing moisture over the Arctic during the last decades is not strongly associated with the evaporation that takes place within the Arctic area itself, despite the fact that the sea <span class="hlt">ice</span> cover is decreasing. Such an increment is consistent and is more dependent on the transport of moisture from the extratropical regions to the Arctic that has increased in recent decades and is expected to increase within a warming climate. This increase could be due either to changes in circulation patterns which have altered the moisture sources, or to changes in the intensity of the moisture sources because of enhanced evaporation, or a combination of these two mechanisms. In this short communication we focus on the more objective assessment of the strong link between ocean evaporation <span class="hlt">trends</span> and Arctic Sea <span class="hlt">ice</span> melting. We will critically analyse several recent results suggesting links between moisture transport and the <span class="hlt">extent</span> of sea <span class="hlt">ice</span> in the Arctic, this being one of the most distinct indicators of continuous climate change both in the Arctic and on a global scale. To do this we will use a sophisticated Lagrangian approach to develop a more robust framework on some of these previous disconnecting results, using new information and insights. Results reached in this study stress the connection between two climate change indicators, namely an increase in evaporation over source regions (mainly the Mediterranean Sea, the North Atlantic Ocean and the North Pacific Ocean in the paths of the global western boundary currents and their extensions) and Arctic <span class="hlt">ice</span> melting precursors.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMIN53B1627C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMIN53B1627C"><span>Nimbus Satellite Data Rescue Project for Sea <span class="hlt">Ice</span> <span class="hlt">Extent</span>: Data Processing</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Campbell, G. G.; Sandler, M.; Moses, J. F.; Gallaher, D. W.</p> <p>2011-12-01</p> <p> scanning and simple quality control of more than 200,000 pictures. Preliminary results from September 1964, 1966 and 1969 data analysis will be discussed in this presentation. Our scientific use of the data will focus on recovering the sea <span class="hlt">ice</span> <span class="hlt">extent</span> around the poles. We especially welcome new users interested in the meteorology from 50N to 50S in the 1960's. Lessons and examples of the scanning and quality control procedures will be highlighted in the presentation. Illustrations will include mapped and reformatted data. When the project is finished a public archive from September 1964, April to November 1966 and May to December 1969 will be available for general use.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28835469','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28835469"><span>Sea-<span class="hlt">ice</span> induced growth decline in Arctic shrubs.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Forchhammer, Mads</p> <p>2017-08-01</p> <p>Measures of increased tundra plant productivity have been associated with the accelerating retreat of the Arctic sea-<span class="hlt">ice</span>. Emerging studies document opposite effects, advocating for a more complex relationship between the shrinking sea-<span class="hlt">ice</span> and terrestrial plant productivity. I introduce an autoregressive plant growth model integrating effects of biological and climatic conditions for analysing individual ring-width growth time series. Using 128 specimens of Salix arctica , S. glauca and Betula nana sampled across Greenland to Svalbard, an overall negative effect of the retreating June sea-<span class="hlt">ice</span> <span class="hlt">extent</span> was found on the annual growth. The negative effect of the retreating June sea-<span class="hlt">ice</span> was observed for younger individuals with large annual growth allocations and with little or no trade-off between previous and current year's growth. © 2017 The Author(s).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000757.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000757.html"><span>Arctic Sea <span class="hlt">Ice</span> Sets New Record Winter Low</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2015-03-19</p> <p>The sea <span class="hlt">ice</span> cap of the Arctic appeared to reach its annual maximum winter <span class="hlt">extent</span> on February 25, according to data from the NASA-supported National Snow and <span class="hlt">Ice</span> Data Center (NSIDC) at the University of Colorado, Boulder. At 5.61 million square miles (14.54 million square kilometers), this year’s maximum <span class="hlt">extent</span> was the smallest on the satellite record and also one of the earliest. Credit: NASA Goddard Space Flight Center NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1997JCli...10..593W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1997JCli...10..593W"><span>Modeling of Antarctic Sea <span class="hlt">Ice</span> in a General Circulation Model.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wu, Xingren; Simmonds, Ian; Budd, W. F.</p> <p>1997-04-01</p> <p>A dynamic-thermodynamic sea <span class="hlt">ice</span> model is developed and coupled with the Melbourne University general circulation model to simulate the seasonal cycle of the Antarctic sea <span class="hlt">ice</span> distribution. The model is efficient, rapid to compute, and useful for a range of climate studies. The thermodynamic part of the sea <span class="hlt">ice</span> model is similar to that developed by Parkinson and Washington, the dynamics contain a simplified <span class="hlt">ice</span> rheology that resists compression. The thermodynamics is based on energy conservation at the top surface of the <span class="hlt">ice</span>/snow, the <span class="hlt">ice</span>/water interface, and the open water area to determine the <span class="hlt">ice</span> formation, accretion, and ablation. A lead parameterization is introduced with an effective partitioning scheme for freezing between and under the <span class="hlt">ice</span> floes. The dynamic calculation determines the motion of <span class="hlt">ice</span>, which is forced with the atmospheric wind, taking account of <span class="hlt">ice</span> resistance and rafting. The simulated sea <span class="hlt">ice</span> distribution compares reasonably well with observations. The seasonal cycle of <span class="hlt">ice</span> <span class="hlt">extent</span> is well simulated in phase as well as in magnitude. Simulated sea <span class="hlt">ice</span> thickness and concentration are also in good agreement with observations over most regions and serve to indicate the importance of advection and ocean drift in the determination of the sea <span class="hlt">ice</span> distribution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/484365-modeling-antarctic-sea-ice-general-circulation-model','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/484365-modeling-antarctic-sea-ice-general-circulation-model"><span>Modeling of Antarctic sea <span class="hlt">ice</span> in a general circulation model</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Wu, Xingren; Budd, W.F.; Simmonds, I.</p> <p>1997-04-01</p> <p>A dynamic-thermodynamic sea <span class="hlt">ice</span> model is developed and coupled with the Melbourne University general circulation model to simulate the seasonal cycle of the Antarctic sea <span class="hlt">ice</span> distributions The model is efficient, rapid to compute, and useful for a range of climate studies. The thermodynamic part of the sea <span class="hlt">ice</span> model is similar to that developed by Parkinson and Washington, the dynamics contain a simplified <span class="hlt">ice</span> rheology that resists compression. The thermodynamics is based on energy conservation at the top surface of the <span class="hlt">ice</span>/snow, the <span class="hlt">ice</span>/water interface, and the open water area to determine the <span class="hlt">ice</span> formation, accretion, and ablation. Amore » lead parameterization is introduced with an effective partitioning scheme for freezing between and under the <span class="hlt">ice</span> floes. The dynamic calculation determines the motion of <span class="hlt">ice</span>, which is forced with the atmospheric wind, taking account of <span class="hlt">ice</span> resistance and rafting. The simulated sea <span class="hlt">ice</span> distribution compares reasonably well with observations. The seasonal cycle of <span class="hlt">ice</span> <span class="hlt">extent</span> is well simulated in phase as well as in magnitude. Simulated sea <span class="hlt">ice</span> thickness and concentration are also in good agreement with observations over most regions and serve to indicate the importance of advection and ocean drift in the determination of the sea <span class="hlt">ice</span> distribution. 64 refs., 15 figs., 2 tabs.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1222091-marine-biogenic-source-atmospheric-ice-nucleating-particles','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1222091-marine-biogenic-source-atmospheric-ice-nucleating-particles"><span>A marine biogenic source of atmospheric <span class="hlt">ice</span>-nucleating particles</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Wilson, T. W.; Ladino, L. A.; Alpert, Peter A.</p> <p>2015-09-09</p> <p>The formation of <span class="hlt">ice</span> in clouds is facilitated by the presence of airborne <span class="hlt">ice</span> nucleating particles1,2. Sea spray is one of the major global sources of atmospheric particles, but it is unclear to what <span class="hlt">extent</span> these particles are capable of nucleating <span class="hlt">ice</span>3–11. Here we show that material in the sea surface microlayer, which is enriched in surface active organic material representative of that found in sub-micron sea- spray aerosol12–21, nucleates <span class="hlt">ice</span> under conditions that occur in mixed-phase clouds and high-altitude <span class="hlt">ice</span> clouds. The <span class="hlt">ice</span> active material is likely biogenic and is less than ~0.2 ?m in size. We also showmore » that organic material (exudate) released by a common marine diatom nucleates <span class="hlt">ice</span> when separated from cells and propose that organic material associated with phytoplankton cell exudates are a candidate for the observed <span class="hlt">ice</span> nucleating ability of the microlayer samples. By combining our measurements with global model simulations of marine organic aerosol, we show that <span class="hlt">ice</span> nucleating particles of marine origin are dominant in remote marine environments, such as the Southern Ocean, the North Pacific and the North Atlantic.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRD..122.4312M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..122.4312M"><span>Sunshine duration and global radiation <span class="hlt">trends</span> in Italy (1959-2013): To what <span class="hlt">extent</span> do they agree?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Manara, V.; Brunetti, M.; Maugeri, M.; Sanchez-Lorenzo, A.; Wild, M.</p> <p>2017-04-01</p> <p>Two Italian homogenized data sets of sunshine duration (SD) and global radiation (Eg↓) relative anomalies are used to investigate to what <span class="hlt">extent</span> these two variables agree with respect to their temporal evolution. They are compared for northern and southern Italy over the period 1959-2013. Both under all-sky and clear-sky conditions, the SD records tend to show a shorter and less intense decrease until the 1980s ("global dimming") with respect to the Eg↓ ones, while there is a better agreement in the subsequent period when both variables increase ("brightening period"). To investigate whether such behavior can be explained by a different sensitivity of SD and Eg↓ to atmospheric turbidity variations, the observed clear-sky <span class="hlt">trends</span> are compared to those estimated by a model based both on Lambert-Beer's law and on a simple estimation of diffuse radiation. Results show that most of the differences observed in the <span class="hlt">trends</span> of the clear-sky SD and Eg↓ records can be explained considering a realistic pattern of atmospheric turbidity in the 1959-2013 period. The only exception concerns winter and autumn in northern Italy where clear-sky SD does not decrease in the dimming period as much as it would be expected on the basis of the corresponding increase in atmospheric turbidity. One reason for this discrepancy could be the influence of other variables like relative humidity. This case study highlights that changes in atmospheric turbidity have to be kept in mind when SD is used to investigate the multidecadal evolution of Eg↓.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_24 --> <div id="page_25" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active"><span>25</span></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="481"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25978903','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25978903"><span>Molecular simulations of heterogeneous <span class="hlt">ice</span> nucleation. II. Peeling back the layers.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Cox, Stephen J; Kathmann, Shawn M; Slater, Ben; Michaelides, Angelos</p> <p>2015-05-14</p> <p>Coarse grained molecular dynamics simulations are presented in which the sensitivity of the <span class="hlt">ice</span> nucleation rate to the hydrophilicity of a graphene nanoflake is investigated. We find that an optimal interaction strength for promoting <span class="hlt">ice</span> nucleation exists, which coincides with that found previously for a face centered cubic (111) surface. We further investigate the role that the layering of interfacial water plays in heterogeneous <span class="hlt">ice</span> nucleation and demonstrate that the <span class="hlt">extent</span> of layering is not a good indicator of <span class="hlt">ice</span> nucleating ability for all surfaces. Our results suggest that to be an efficient <span class="hlt">ice</span> nucleating agent, a surface should not bind water too strongly if it is able to accommodate high coverages of water.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/17733504','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/17733504"><span>Devon island <span class="hlt">ice</span> cap: core stratigraphy and paleoclimate.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Koerner, R M</p> <p>1977-04-01</p> <p>Valuable paleoclimatic information can be gained by studying the distribution of melt layers in deep <span class="hlt">ice</span> cores. A profile representing the percentage of <span class="hlt">ice</span> in melt layers in a core drilled from the Devon Island <span class="hlt">ice</span> cap plotted against both time and depth shows that the <span class="hlt">ice</span> cap has experienced a period of very warm summers since 1925, following a period of colder summers between about 1600 and 1925. The earlier period was coldest between 1680 and 1730. There is a high correlation between the melt-layer <span class="hlt">ice</span> percentage and the mass balance of the <span class="hlt">ice</span> cap. The relation between them suggests that the <span class="hlt">ice</span> cap mass balance was zero (accumulation equaled ablation) during the colder period but is negative in the present warmer one. There is no firm evidence of a present cooling <span class="hlt">trend</span> in the summer conditions on the <span class="hlt">ice</span> cap. A comparison with the melt-layer <span class="hlt">ice</span> percentage in cores from the other major Canadian Arctic <span class="hlt">ice</span> caps shows that the variation of summer conditions found for the Devon Island <span class="hlt">ice</span> cap is representative for all the large <span class="hlt">ice</span> caps for about 90 percent of the time. There is also a good correlation between melt-layer percentage and summer sea-<span class="hlt">ice</span> conditions in the archipelago. This suggests that the search for the northwest passage was influenced by changing climate, with the 19th-century peak of the often tragic exploration coinciding with a period of very cold summers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.1971Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.1971Z"><span>Impact of the initialisation on the predictability of the Southern Ocean sea <span class="hlt">ice</span> at interannual to multi-decadal timescales</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zunz, Violette; Goosse, Hugues; Dubinkina, Svetlana</p> <p>2014-05-01</p> <p>In this study, we assess systematically the impact of different initialisation procedures on the predictability of the sea <span class="hlt">ice</span> in the Southern Ocean. These initialisation strategies are based on three data assimilation methods: the nudging, the particle filter with sequential resampling and the nudging proposal particle filter. An Earth-system model of intermediate complexity has been used to perform hindcast simulations in a perfect model approach. The predictability of the Southern Ocean sea <span class="hlt">ice</span> is estimated through two aspects: the spread of the hindcast ensemble, indicating the uncertainty on the ensemble, and the correlation between the ensemble mean and the pseudo-observations, used to assess the accuracy of the prediction. Our results show that, at decadal timescales, more sophisticated data assimilation methods as well as denser pseudo-observations used to initialise the hindcasts decrease the spread of the ensemble but improve only slightly the accuracy of the prediction of the sea <span class="hlt">ice</span> in the Southern Ocean. Overall, the predictability at interannual timescales is limited, at most, to three years ahead. At multi-decadal timescales, there is a clear improvement of the correlation of the <span class="hlt">trend</span> in sea <span class="hlt">ice</span> <span class="hlt">extent</span> between the hindcasts and the pseudo-observations if the initialisation takes into account the pseudo-observations. The correlation reaches values larger than 0.5 and is due to the inertia of the ocean, showing the importance of the quality of the initialisation below the sea <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy...50..655S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy...50..655S"><span>Multiple climate regimes in an idealized lake-<span class="hlt">ice</span>-atmosphere model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sugiyama, Noriyuki; Kravtsov, Sergey; Roebber, Paul</p> <p>2018-01-01</p> <p>In recent decades, the Laurentian Great Lakes have undergone rapid surface warming with the summertime <span class="hlt">trends</span> substantially exceeding the warming rates of surrounding land. Warming of the deepest (Lake Superior) was the strongest, and that of the shallowest (Lake Erie)—the weakest of all lakes. To investigate the dynamics of accelerated lake warming, we considered single-column and multi-column thermodynamic lake-<span class="hlt">ice</span> models coupled to an idealized two-layer atmosphere. The variable temperature of the upper atmospheric layer—a proxy for the large-scale atmospheric forcing—consisted, in the most general case, of a linear <span class="hlt">trend</span> mimicking the global warming and atmospheric interannual variability, both on top of the prescribed seasonal cycle of the upper-air temperature. The atmospheric boundary layer of the coupled model exchanged heat with the lake and exhibited lateral diffusive heat transports between the adjacent atmospheric columns. In simpler single-column models, we find that, for a certain range of periodic atmospheric forcing, each lake possesses two stable equilibrium seasonal cycles, which we call "regimes"—with and without lake-<span class="hlt">ice</span> occurrence in winter and with corresponding cold and warm temperatures in the following summer, respectively, all under an identical seasonally varying external forcing. Deeper lakes exhibit larger differences in their summertime surface water temperature between the warm and cold regimes, due to their larger thermal and dynamical inertia. The regime behavior of multi-column coupled models is similar but more complex, and in some cases, they admit more than two stable equilibrium seasonal cycles, with varying degrees of wintertime <span class="hlt">ice</span>-cover. The simulated lake response to climate change in the presence of the atmospheric noise rationalizes the observed accelerated warming of the lakes, the correlation between wintertime <span class="hlt">ice</span> cover and next summer's lake-surface temperature, as well as higher warming <span class="hlt">trends</span> of the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRC..121.5470L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRC..121.5470L"><span>Changes in summer sea <span class="hlt">ice</span>, albedo, and portioning of surface solar radiation in the Pacific sector of Arctic Ocean during 1982-2009</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lei, Ruibo; Tian-Kunze, Xiangshan; Leppäranta, Matti; Wang, Jia; Kaleschke, Lars; Zhang, Zhanhai</p> <p>2016-08-01</p> <p>SSM/I sea <span class="hlt">ice</span> concentration and CLARA black-sky composite albedo were used to estimate sea <span class="hlt">ice</span> albedo in the region 70°N-82°N, 130°W-180°W. The long-term <span class="hlt">trends</span> and seasonal evolutions of <span class="hlt">ice</span> concentration, composite albedo, and <span class="hlt">ice</span> albedo were then obtained. In July-August 1982-2009, the linear <span class="hlt">trend</span> of the composite albedo and the <span class="hlt">ice</span> albedo was -0.069 and -0.046 units per decade, respectively. During 1 June to 19 August, melting of sea <span class="hlt">ice</span> resulted in an increase of solar heat input to the <span class="hlt">ice</span>-ocean system by 282 MJ·m-2 from 1982 to 2009. However, because of the counter-balancing effects of the loss of sea <span class="hlt">ice</span> area and the enhanced <span class="hlt">ice</span> surface melting, the <span class="hlt">trend</span> of solar heat input to the <span class="hlt">ice</span> was insignificant. The summer evolution of <span class="hlt">ice</span> albedo matched the <span class="hlt">ice</span> surface melting and ponding well at basin scale. The <span class="hlt">ice</span> albedo showed a large difference between the multiyear and first-year <span class="hlt">ice</span> because the latter melted completely by the end of a melt season. At the SHEBA geolocations, a distinct change in the <span class="hlt">ice</span> albedo has occurred since 2007, because most of the multiyear <span class="hlt">ice</span> has been replaced by first-year <span class="hlt">ice</span>. A positive polarity in the Arctic Dipole Anomaly could be partly responsible for the rapid loss of summer <span class="hlt">ice</span> within the study region in the recent years by bringing warmer air masses from the south and advecting more <span class="hlt">ice</span> toward the north. Both these effects would enhance <span class="hlt">ice</span>-albedo feedback.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AAS...23211302G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AAS...23211302G"><span>What Governs <span class="hlt">Ice</span>-Sticking in Planetary Science Experiments?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gaertner, Sabrina; Gundlach, B.; Blum, J.; Fraser, H. J.</p> <p>2018-06-01</p> <p>Water <span class="hlt">ice</span> plays an important role, alongside dust, in current theories of planet formation. Decades of laboratory experiments have proven that water <span class="hlt">ice</span> is far stickier in particle collisions than dust. However, water <span class="hlt">ice</span> is known to be a metastable material. Its physical properties strongly depend on its environmental parameters, the foremost being temperature and pressure. As a result, the properties of <span class="hlt">ice</span> change not only with the environment it is observed in, but also with its thermal history.The abundance of <span class="hlt">ice</span> structures that can be created by different environments likely explains the discrepancies observed across the multitude of collisional laboratory studies in the past [1-16]; unless the <span class="hlt">ices</span> for such experiments have been prepared in the same way and are collided under the same environmental conditions, these experiments simply do not collide the same <span class="hlt">ices</span>.This raises several questions:1. Which conditions and <span class="hlt">ice</span> properties are most favourable for <span class="hlt">ice</span> sticking?2. Which conditions and <span class="hlt">ice</span> properties are closest to the ones observed in protoplanetary disks?3. To what <span class="hlt">extent</span> do these two regimes overlap?4. Consequently, which collisional studies are most relevant to planetary science and therefore best suited to inform models of planet formation?In this presentation, I will give a non-exhaustive overview of what we already know about the properties of <span class="hlt">ice</span> particles, covering those used in planetary science experiments and those observed in planet forming regions. I will discuss to what <span class="hlt">extent</span> we can already answer questions 1-3, and what information we still need to obtain from observations, laboratory experiments, and modelling to be able to answer question 4.References:1. Bridges et al. 1984 Natur 309.2. Bridges et al. 1996 Icar 123.3. Deckers & Teiser 2016 MNRAS 456.4. Dilley & Crawford 1996 JGRE 101.5. Gundlach & Blum 2015 ApJ 798.6. Hatzes et al. 1991 Icar 89.7. Hatzes et al. 1988 MNRAS 231.8. Heißelmann et al. 2010 Icar 206.9. Higa et al. 1996 P</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ESASP.740E.346P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ESASP.740E.346P"><span>Remote Oil Spill Detection and Monitoring Beneath Sea <span class="hlt">Ice</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Polak, Adam; Marshall, Stephen; Ren, Jinchang; Hwang, Byongjun (Phil); Hagan, Bernard; Stothard, David J. M.</p> <p>2016-08-01</p> <p>The spillage of oil in Polar Regions is particularly serious due to the threat to the environment and the difficulties in detecting and tracking the full <span class="hlt">extent</span> of the oil seepage beneath the sea <span class="hlt">ice</span>. Development of fast and reliable sensing techniques is highly desirable. In this paper hyperspectral imaging combined with signal processing and classification techniques are proposed as a potential tool to detect the presence of oil beneath the sea <span class="hlt">ice</span>. A small sample, lab based experiment, serving as a proof of concept, resulted in the successful identification of oil presence beneath the thin <span class="hlt">ice</span> layer as opposed to the other sample with <span class="hlt">ice</span> only. The paper demonstrates the results of this experiment that granted a financial support to execute full feasibility study of this technology for oil spill detection beneath the sea <span class="hlt">ice</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMPA31A2196M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMPA31A2196M"><span>Climate Change and the Long-term Viability of the World's Busiest Heavy Haul <span class="hlt">Ice</span> Road</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mullan, D.</p> <p>2016-12-01</p> <p>Climate models project that the northern high latitudes will warm at a rate in excess of the global mean. This will pose severe problems for Arctic and sub-Arctic infrastructure dependent on maintaining low temperatures for structural integrity. This is the case for the economically important Tibbitt to Contwoyto Winter Road (TCWR)—the world's busiest heavy haul <span class="hlt">ice</span> road, spanning 400 km across mostly frozen lakes within the Northwest Territories of Canada. In this study, future climate scenarios are developed for the region using statistical downscaling methods. In addition, changes in lake <span class="hlt">ice</span> thickness are projected based on historical relationships between measured <span class="hlt">ice</span> thickness and air temperatures. These projections are used to infer the theoretical operational dates of the TCWR based on weight limits for trucks on the <span class="hlt">ice</span>. Results across three climate models driven by four RCPs reveal a considerable warming <span class="hlt">trend</span> over the coming decades. Projected changes in <span class="hlt">ice</span> thickness reveal a <span class="hlt">trend</span> towards thinner lake <span class="hlt">ice</span> and a reduced time window when lake <span class="hlt">ice</span> is at sufficient thickness to support trucks on the <span class="hlt">ice</span> road, driven by increasing future temperatures. Given the uncertainties inherent in climate modelling and the resultant projections, caution should be exercised in interpreting the magnitude of these scenarios. More certain is the direction of change, with a clear <span class="hlt">trend</span> towards winter warming that will reduce the operation time window of the TCWR. This illustrates the need for planners and policymakers to consider future changes in climate when planning annual haulage along the TCWR.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ThApC.129.1089M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ThApC.129.1089M"><span>Climate change and the long-term viability of the World's busiest heavy haul <span class="hlt">ice</span> road</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mullan, Donal; Swindles, Graeme; Patterson, Tim; Galloway, Jennifer; Macumber, Andrew; Falck, Hendrik; Crossley, Laura; Chen, Jie; Pisaric, Michael</p> <p>2017-08-01</p> <p>Climate models project that the northern high latitudes will warm at a rate in excess of the global mean. This will pose severe problems for Arctic and sub-Arctic infrastructure dependent on maintaining low temperatures for structural integrity. This is the case for the economically important Tibbitt to Contwoyto Winter Road (TCWR)—the world's busiest heavy haul <span class="hlt">ice</span> road, spanning 400 km across mostly frozen lakes within the Northwest Territories of Canada. In this study, future climate scenarios are developed for the region using statistical downscaling methods. In addition, changes in lake <span class="hlt">ice</span> thickness are projected based on historical relationships between measured <span class="hlt">ice</span> thickness and air temperatures. These projections are used to infer the theoretical operational dates of the TCWR based on weight limits for trucks on the <span class="hlt">ice</span>. Results across three climate models driven by four RCPs reveal a considerable warming <span class="hlt">trend</span> over the coming decades. Projected changes in <span class="hlt">ice</span> thickness reveal a <span class="hlt">trend</span> towards thinner lake <span class="hlt">ice</span> and a reduced time window when lake <span class="hlt">ice</span> is at sufficient thickness to support trucks on the <span class="hlt">ice</span> road, driven by increasing future temperatures. Given the uncertainties inherent in climate modelling and the resultant projections, caution should be exercised in interpreting the magnitude of these scenarios. More certain is the direction of change, with a clear <span class="hlt">trend</span> towards winter warming that will reduce the operation time window of the TCWR. This illustrates the need for planners and policymakers to consider future changes in climate when planning annual haulage along the TCWR.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C32B..01T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C32B..01T"><span>Some Results on Sea <span class="hlt">Ice</span> Rheology for the Seasonal <span class="hlt">Ice</span> Zone, Obtained from the Deformation Field of Sea <span class="hlt">Ice</span> Drift Pattern</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Toyota, T.; Kimura, N.</p> <p>2017-12-01</p> <p>Sea <span class="hlt">ice</span> rheology which relates sea <span class="hlt">ice</span> stress to the large-scale deformation of the <span class="hlt">ice</span> cover has been a big issue to numerical sea <span class="hlt">ice</span> modelling. At present the treatment of internal stress within sea <span class="hlt">ice</span> area is based mostly on the rheology formulated by Hibler (1979), where the whole sea <span class="hlt">ice</span> area behaves like an isotropic and plastic matter under the ordinary stress with the yield curve given by an ellipse with an aspect ratio (e) of 2, irrespective of sea <span class="hlt">ice</span> area and horizontal resolution of the model. However, this formulation was initially developed to reproduce the seasonal variation of the perennial <span class="hlt">ice</span> in the Arctic Ocean. As for its applicability to the seasonal <span class="hlt">ice</span> zones (SIZ), where various types of sea <span class="hlt">ice</span> are present, it still needs validation from observational data. In this study, the validity of this rheology was examined for the Sea of Okhotsk <span class="hlt">ice</span>, typical of the SIZ, based on the AMSR-derived <span class="hlt">ice</span> drift pattern in comparison with the result obtained for the Beaufort Sea. To examine the dependence on a horizontal scale, the coastal radar data operated near the Hokkaido coast, Japan, were also used. <span class="hlt">Ice</span> drift pattern was obtained by a maximum cross-correlation method with grid spacings of 37.5 km from the 89 GHz brightness temperature of AMSR-E for the entire Sea of Okhotsk and the Beaufort Sea and 1.3 km from the coastal radar for the near-shore Sea of Okhotsk. The validity of this rheology was investigated from a standpoint of work rate done by deformation field, following the theory of Rothrock (1975). In analysis, the relative rates of convergence were compared between theory and observation to check the shape of yield curve, and the strain ellipse at each grid cell was estimated to see the horizontal variation of deformation field. The result shows that the ellipse of e=1.7-2.0 as the yield curve represents the observed relative conversion rates well for all the <span class="hlt">ice</span> areas. Since this result corresponds with the yield criterion by Tresca and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.C21C0622M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.C21C0622M"><span>Meteorological conditions influencing the formation of level <span class="hlt">ice</span> within the Baltic Sea</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mazur, A. K.; Krezel, A.</p> <p>2012-12-01</p> <p>The Baltic Sea is covered by <span class="hlt">ice</span> every winter and on average, the <span class="hlt">ice</span>-covered area is 45% of the total area of the Baltic Sea. The beginning of <span class="hlt">ice</span> season usually starts in the end of November, <span class="hlt">ice</span> <span class="hlt">extent</span> is the largest between mid-February and mid-March and sea <span class="hlt">ice</span> disappears completely in May. The <span class="hlt">ice</span> covered areas during a typical winter are the Gulf of Bothnia, the Gulf of Finland and the Gulf of Riga. The studies of sea <span class="hlt">ice</span> in the Baltic Sea are related to two aspects: climate and marine transport. Depending on the local weather conditions during the winter different types of sea <span class="hlt">ice</span> can be formed. From the point of winter shipping it is important to locate level and deformed <span class="hlt">ice</span> areas (rafted <span class="hlt">ice</span>, ridged <span class="hlt">ice</span>, and hummocked <span class="hlt">ice</span>). Because of cloud and daylight independency as well as good spatial resolution, SAR data seems to be the most suitable source of data for sea <span class="hlt">ice</span> observation in the comparatively small area of the Baltic Sea. We used ASAR Wide Swath Mode data with spatial resolution 150 m. We analyzed data from the three winter seasons which were examples of severe, typical and mild winters. To remove the speckle effect the data were resampled to 250 m pixel size and filtred using Frost filter 5x5. To detect edges we used Sobel filter. The data were also converted into grayscale. Sea <span class="hlt">ice</span> classification was based on Object-Based Image Analysis (OBIA). Object-based methods are not a common tool in sea <span class="hlt">ice</span> studies but they seem to accurately separate level <span class="hlt">ice</span> within the <span class="hlt">ice</span> pack. The data were segmented and classified using eCognition Developer software. Level <span class="hlt">ice</span> were classified based on texture features defined by Haralick (Grey Level Co-Occurrence Matrix homogeneity, GLCM contrast, GLCM entropy and GLCM correlation). The long-term changes of the Baltic Sea <span class="hlt">ice</span> conditions have been already studied. They include date of freezing, date of break-up, sea <span class="hlt">ice</span> <span class="hlt">extent</span> and some of work also <span class="hlt">ice</span> thickness. There is a little knowledge about the relationship of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1817638P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1817638P"><span>RADARSAT-2 Polarimetry for Lake <span class="hlt">Ice</span> Mapping</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pan, Feng; Kang, Kyung-Kuk; Duguay, Claude</p> <p>2016-04-01</p> <p>Changes in the <span class="hlt">ice</span> regime of lakes can be employed to assess long-term climate <span class="hlt">trends</span> and variability in high latitude regions. Lake <span class="hlt">ice</span> cover observations are not only useful for climate monitoring, but also for improving <span class="hlt">ice</span> and weather forecasts using numerical prediction models. In recent years, satellite remote sensing has assumed a greater role in observing lake <span class="hlt">ice</span> cover for both purposes. Radar remote sensing has become an essential tool for mapping lake <span class="hlt">ice</span> at high latitudes where cloud cover and polar darkness severely limits <span class="hlt">ice</span> observations from optical systems. In Canada, there is an emerging interest by government agencies to evaluate the potential of fully polarimetric synthetic aperture radar (SAR) data from RADARSAT-2 (C-band) for lake <span class="hlt">ice</span> monitoring. In this study, we processed and analyzed the polarization states and scattering mechanisms of fully polarimetric RADARSAT-2 data obtained over Great Bear Lake, Canada, to identify open water and different <span class="hlt">ice</span> types during the freeze-up and break-up periods. Polarimetric decompositions were employed to separate polarimetric measurements into basic scattering mechanisms. Entropy, anisotropy, and alpha angle were derived to characterize the scattering heterogeneity and mechanisms. <span class="hlt">Ice</span> classes were then determined based on entropy and alpha angle using the unsupervised Wishart classifier and results evaluated against Landsat 8 imagery. Preliminary results suggest that the RADARSAT-2 polarimetric data offer a strong capability for identifying open water and different lake <span class="hlt">ice</span> types.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e002001.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e002001.html"><span>Sea <span class="hlt">Ice</span> in McClure Strait</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2017-12-08</p> <p>NASA image acquired August 17, 2010 In mid-August 2010, the Northwest Passage was almost—but not quite—free of <span class="hlt">ice</span>. The <span class="hlt">ice</span> content in the northern route through the passage (through the Western Parry Channel) was very light, but <span class="hlt">ice</span> remained in McClure (or M’Clure) Strait. The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite captured this natural-color image on August 17, 2010. Although most of McClure Strait looks perfectly <span class="hlt">ice</span>-free, immediately west of Prince Patrick Island, a band of sea <span class="hlt">ice</span> stretches southward across the strait (left edge of the image). The National Snow and <span class="hlt">Ice</span> Data Center Sea <span class="hlt">Ice</span> News and Analysis blog reported that even more <span class="hlt">ice</span> remained in the southern route (through Amundsen’s Passage) of the Northwest Passage in mid-August 2010. Nevertheless, the <span class="hlt">ice</span> content in the northern route was not only well below the 1968–2000 average, but also nearly a month ahead of the clearing observed in 2007, when Arctic sea <span class="hlt">ice</span> set a record low. As of mid-August 2010, however, overall sea <span class="hlt">ice</span> <span class="hlt">extent</span> was higher than it had been at the same time of year in 2007. Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team Caption by Michon Scott. To learn more go to: earthobservatory.nasa.gov/NaturalHazards/view.php?id=45333 Instrument: Terra - MODIS NASA Goddard Space Flight Center is home to the nation's largest organization of combined scientists, engineers and technologists that build spacecraft, instruments and new technology to study the Earth, the sun, our solar system, and the universe. Follow us on Twitter Join us on Facebook Click here to see more images from NASA Goddard’s Earth Observatory</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017Natur.547...49L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017Natur.547...49L"><span>Climate change drives expansion of Antarctic <span class="hlt">ice</span>-free habitat</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lee, Jasmine R.; Raymond, Ben; Bracegirdle, Thomas J.; Chadès, Iadine; Fuller, Richard A.; Shaw, Justine D.; Terauds, Aleks</p> <p>2017-07-01</p> <p>Antarctic terrestrial biodiversity occurs almost exclusively in <span class="hlt">ice</span>-free areas that cover less than 1% of the continent. Climate change will alter the <span class="hlt">extent</span> and configuration of <span class="hlt">ice</span>-free areas, yet the distribution and severity of these effects remain unclear. Here we quantify the impact of twenty-first century climate change on <span class="hlt">ice</span>-free areas under two Intergovernmental Panel on Climate Change (IPCC) climate forcing scenarios using temperature-index melt modelling. Under the strongest forcing scenario, <span class="hlt">ice</span>-free areas could expand by over 17,000 km2 by the end of the century, close to a 25% increase. Most of this expansion will occur in the Antarctic Peninsula, where a threefold increase in <span class="hlt">ice</span>-free area could drastically change the availability and connectivity of biodiversity habitat. Isolated <span class="hlt">ice</span>-free areas will coalesce, and while the effects on biodiversity are uncertain, we hypothesize that they could eventually lead to increasing regional-scale biotic homogenization, the extinction of less-competitive species and the spread of invasive species.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28658207','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28658207"><span>Climate change drives expansion of Antarctic <span class="hlt">ice</span>-free habitat.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Lee, Jasmine R; Raymond, Ben; Bracegirdle, Thomas J; Chadès, Iadine; Fuller, Richard A; Shaw, Justine D; Terauds, Aleks</p> <p>2017-07-06</p> <p>Antarctic terrestrial biodiversity occurs almost exclusively in <span class="hlt">ice</span>-free areas that cover less than 1% of the continent. Climate change will alter the <span class="hlt">extent</span> and configuration of <span class="hlt">ice</span>-free areas, yet the distribution and severity of these effects remain unclear. Here we quantify the impact of twenty-first century climate change on <span class="hlt">ice</span>-free areas under two Intergovernmental Panel on Climate Change (IPCC) climate forcing scenarios using temperature-index melt modelling. Under the strongest forcing scenario, <span class="hlt">ice</span>-free areas could expand by over 17,000 km 2 by the end of the century, close to a 25% increase. Most of this expansion will occur in the Antarctic Peninsula, where a threefold increase in <span class="hlt">ice</span>-free area could drastically change the availability and connectivity of biodiversity habitat. Isolated <span class="hlt">ice</span>-free areas will coalesce, and while the effects on biodiversity are uncertain, we hypothesize that they could eventually lead to increasing regional-scale biotic homogenization, the extinction of less-competitive species and the spread of invasive species.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMPP11B1783E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMPP11B1783E"><span>An unusual early Holocene diatom event north of the Getz <span class="hlt">Ice</span> Shelf (Amundsen Sea): Implications for West Antarctic <span class="hlt">Ice</span> Sheet development</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Esper, O.; Gersonde, R.; Hillenbrand, C.; Kuhn, G.; Smith, J.</p> <p>2011-12-01</p> <p>Modern global change affects not only the polar north but also, and to increasing <span class="hlt">extent</span>, the southern high latitudes, especially the Antarctic regions covered by the West Antarctic <span class="hlt">Ice</span> Sheet (WAIS). Consequently, knowledge of the mechanisms controlling past WAIS dynamics and WAIS behaviour at the last deglaciation is critical to predict its development in a future warming world. Geological and palaeobiological information from major drainage areas of the WAIS, like the Amundsen Sea Embayment, shed light on the history of the WAIS glaciers. Sediment records obtained from a deep inner shelf basin north of Getz <span class="hlt">Ice</span> Shelf document a deglacial warming in three phases. Above a glacial diamicton and a sediment package barren of microfossils that document sediment deposition by grounded <span class="hlt">ice</span> and below an <span class="hlt">ice</span> shelf or perennial sea <span class="hlt">ice</span> cover (possibly fast <span class="hlt">ice</span>), respectively, a sediment section with diatom assemblages dominated by sea <span class="hlt">ice</span> taxa indicates <span class="hlt">ice</span> shelf retreat and seasonal <span class="hlt">ice</span>-free conditions. This conclusion is supported by diatom-based summer temperature reconstructions. The early retreat was followed by a phase, when exceptional diatom ooze was deposited around 12,500 cal. years B.P. [1]. Microscopical inspection of this ooze revealed excellent preservation of diatom frustules of the species Corethron pennatum together with vegetative Chaetoceros, thus an assemblage usually not preserved in the sedimentary record. Sediments succeeding this section contain diatom assemblages indicating rather constant Holocene cold water conditions with seasonal sea <span class="hlt">ice</span>. The deposition of the diatom ooze can be related to changes in hydrographic conditions including strong advection of nutrients. However, sediment focussing in the partly steep inner shelf basins cannot be excluded as a factor enhancing the thickness of the ooze deposits. It is not only the presence of the diatom ooze but also the exceptional preservation and the species composition of the diatom assemblage</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.C43A0590F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.C43A0590F"><span>Statistical Analyses of High-Resolution Aircraft and Satellite Observations of Sea <span class="hlt">Ice</span>: Applications for Improving Model Simulations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Farrell, S. L.; Kurtz, N. T.; Richter-Menge, J.; Harbeck, J. P.; Onana, V.</p> <p>2012-12-01</p> <p>Satellite-derived estimates of <span class="hlt">ice</span> thickness and observations of <span class="hlt">ice</span> <span class="hlt">extent</span> over the last decade point to a downward <span class="hlt">trend</span> in the basin-scale <span class="hlt">ice</span> volume of the Arctic Ocean. This loss has broad-ranging impacts on the regional climate and ecosystems, as well as implications for regional infrastructure, marine navigation, national security, and resource exploration. New observational datasets at small spatial and temporal scales are now required to improve our understanding of physical processes occurring within the <span class="hlt">ice</span> pack and advance parameterizations in the next generation of numerical sea-<span class="hlt">ice</span> models. High-resolution airborne and satellite observations of the sea <span class="hlt">ice</span> are now available at meter-scale resolution or better that provide new details on the properties and morphology of the <span class="hlt">ice</span> pack across basin scales. For example the NASA <span class="hlt">Ice</span>Bridge airborne campaign routinely surveys the sea <span class="hlt">ice</span> of the Arctic and Southern Oceans with an advanced sensor suite including laser and radar altimeters and digital cameras that together provide high-resolution measurements of sea <span class="hlt">ice</span> freeboard, thickness, snow depth and lead distribution. Here we present statistical analyses of the <span class="hlt">ice</span> pack primarily derived from the following <span class="hlt">Ice</span>Bridge instruments: the Digital Mapping System (DMS), a nadir-looking, high-resolution digital camera; the Airborne Topographic Mapper, a scanning lidar; and the University of Kansas snow radar, a novel instrument designed to estimate snow depth on sea <span class="hlt">ice</span>. Together these instruments provide data from which a wide range of sea <span class="hlt">ice</span> properties may be derived. We provide statistics on lead distribution and spacing, lead width and area, floe size and distance between floes, as well as ridge height, frequency and distribution. The goals of this study are to (i) identify unique statistics that can be used to describe the characteristics of specific <span class="hlt">ice</span> regions, for example first-year/multi-year <span class="hlt">ice</span>, diffuse <span class="hlt">ice</span> edge/consolidated <span class="hlt">ice</span> pack, and convergent</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.H13N..09G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.H13N..09G"><span>Heating the <span class="hlt">Ice</span>-Covered Lakes of the McMurdo Dry Valleys, Antarctica - Decadal <span class="hlt">Trends</span> in Heat Content, <span class="hlt">Ice</span> Thickness, and Heat Exchange</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gooseff, M. N.; Priscu, J. C.; Doran, P. T.; Chiuchiolo, A.; Obryk, M.</p> <p>2014-12-01</p> <p>Lakes integrate landscape processes and climate conditions. Most of the permanently <span class="hlt">ice</span>-covered lakes in the McMurdo Dry Valleys, Antarctica are closed basin, receiving glacial melt water from streams for 10-12 weeks per year. Lake levels rise during the austral summer are balanced by sublimation of <span class="hlt">ice</span> covers (year-round) and evaporation of open water moats (summer only). Vertical profiles of water temperature have been measured in three lakes in Taylor Valley since 1988. Up to 2002, lake levels were dropping, <span class="hlt">ice</span> covers were thickening, and total heat contents were decreasing. These lakes have been gaining heat since the mid-2000s, at rates as high as 19.5x1014 cal/decade). Since 2002, lake levels have risen substantially (as much as 2.5 m), and <span class="hlt">ice</span> covers have thinned (1.5 m on average). Analyses of lake <span class="hlt">ice</span> thickness, meteorological conditions, and stream water heat loads indicate that the main source of heat to these lakes is from latent heat released when <span class="hlt">ice</span>-covers form during the winter. An aditional source of heat to the lakes is water inflows from streams and direct glacieal melt. Mean lake temperatures in the past few years have stabilized or cooled, despite increases in lake level and total heat content, suggesting increased direct inflow of meltwater from glaciers. These results indicate that McMurdo Dry Valley lakes are sensitive indicators of climate processes in this polar desert landscape and demonstrate the importance of long-term data sets when addressing the effects of climate on ecosystem processes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMSA21A2100S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMSA21A2100S"><span>PMC Formation From Space Shuttle Exhaust and Implications to <span class="hlt">Trend</span> Studies</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stevens, M. H.</p> <p>2012-12-01</p> <p>Main engine exhaust from the space shuttle is nearly entirely water vapor and about 350 tons were injected between 100-115 km during each launch. Many observational studies showed that the meridional transport of these exhaust plumes can be much faster than either general circulation models or satellite wind climatologies predicted. The fast meridional transport is global-scale and can furthermore lead to bursts of polar mesospheric clouds (PMCs) that constitute 10-20% of the PMC <span class="hlt">ice</span> mass during a summer season. This contribution is significant because reported PMC frequency and albedo <span class="hlt">trends</span> since the late 20th century are typically less than 1%/year. Although the shuttle program has ended, space traffic continues virtually every week worldwide and the potential effect to the annual PMC <span class="hlt">ice</span> budget from these smaller launch vehicles remains unquantified. Here we calculate the PMC <span class="hlt">ice</span> mass for each northern season since 1979 from the suite of Solar Backscatter UltraViolet (SBUV) instruments and compare that to the inventory of water vapor injected concurrently by space traffic worldwide. Care is taken to only consider PMC observations from one part of the diurnal cycle (11.6±1.1 local time) and one latitude (70±2.5° N) so as not to contaminate long-term <span class="hlt">trend</span> estimates with the well-known tidally induced variations of the PMC <span class="hlt">ice</span> mass. We infer the long term PMC <span class="hlt">trend</span> from the SBUV observations and compare that to the water vapor available from space traffic to assess the potential contribution of space traffic to the PMC <span class="hlt">trend</span>. We find that the total amount of water vapor exhaust injected worldwide into the upper atmosphere (90-140 km) each year between 1979-2011 is on average about three times larger than the PMC <span class="hlt">ice</span> mass observed. We also find that the PMC <span class="hlt">ice</span> mass <span class="hlt">trend</span> is less than 1%/year. Even after consideration of photodissociation, the water vapor exhaust available from space traffic far exceeds the PMC <span class="hlt">trend</span> estimate and can therefore contribute</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70188658','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70188658"><span>Younger-Dryas cooling and sea-<span class="hlt">ice</span> feedbacks were prominent features of the Pleistocene-Holocene transition in Arctic Alaska</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Gaglioti, Benjamin V.; Mann, Daniel H.; Wooller, Matthew J.; Jones, Benjamin M.; Wiles, Gregory C.; Groves, Pamela; Kunz, Michael L.; Baughman, Carson; Reanier, Richard E.</p> <p>2017-01-01</p> <p>Declining sea-<span class="hlt">ice</span> <span class="hlt">extent</span> is currently amplifying climate warming in the Arctic. Instrumental records at high latitudes are too short-term to provide sufficient historical context for these <span class="hlt">trends</span>, so paleoclimate archives are needed to better understand the functioning of the sea <span class="hlt">ice</span>-albedo feedback. Here we use the oxygen isotope values of wood cellulose in living and sub-fossil willow shrubs (δ18Owc) (Salix spp.) that have been radiocarbon-dated (14C) to produce a multi-millennial record of climatic change on Alaska's North Slope during the Pleistocene-Holocene transition (13,500–7500 calibrated 14C years before present; 13.5–7.5 ka). We first analyzed the spatial and temporal patterns of δ18Owc in living willows growing at upland sites and found that over the last 30 years δ18Owc values in individual growth rings correlate with local summer temperature and inter-annual variations in summer sea-<span class="hlt">ice</span> <span class="hlt">extent</span>. Deglacial δ18Owcvalues from 145 samples of subfossil willows clearly record the Allerød warm period (∼13.2 ka), the Younger Dryas cold period (12.9–11.7 ka), and the Holocene Thermal Maximum (11.7–9.0 ka). The magnitudes of isotopic changes over these rapid climate oscillations were ∼4.5‰, which is about 60% of the differences in δ18Owc between those willows growing during the last glacial period and today. Modeling of isotope-precipitation relationships based on Rayleigh distillation processes suggests that during the Younger Dryas these large shifts in δ18Owc values were caused by interactions between local temperature and changes in evaporative moisture sources, the latter controlled by seaice <span class="hlt">extent</span> in the Arctic Ocean and Bering Sea. Based on these results and on the effects that sea-<span class="hlt">ice</span> have on climate today, we infer that ocean-derived feedbacks amplified temperature changes and enhanced precipitation in coastal regions of Arctic Alaska during warm times in the past. Today, isotope values in willows on the North Slope of Alaska are</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active"><span>25</span></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_25 --> <div class="footer-extlink text-muted" style="margin-bottom:1rem; text-align:center;">Some links on this page may take you to non-federal websites. 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