Sea ice thickness derived from radar altimetry: achievements and future plans

NASA Astrophysics Data System (ADS)

Ricker, R.; Hendricks, S.; Paul, S.; Kaleschke, L.; Tian-Kunze, X.

2017-12-01

The retrieval of Arctic sea ice thickness is one of the major objectives of the European CryoSat-2 radar altimeter mission and the 7-year long period of operation has produced an unprecedented record of monthly sea ice thickness information. We present CryoSat-2 results that show changes and variability of Arctic sea ice from the winter season 2010/2011 until fall 2017. CryoSat-2, however, was designed to observe thick perennial sea ice, while an accurate retrieval of thin seasonal sea ice is more challenging. We have therefore developed a method of completing and improving Arctic sea ice thickness information within the ESA SMOS+ Sea Ice project by merging CryoSat-2 and SMOS sea ice thickness retrievals. Using these satellite missions together overcomes several issues of single-mission retrievals and provides a more accurate and comprehensive view on the state of Arctic sea-ice thickness at higher temporal resolution. However, stand-alone CryoSat-2 observations can be used as reference data for the exploitation of older pulse-limited radar altimetry data sets over sea ice. In order to observe trends in sea ice thickness, it is required to minimize inter-mission biases between subsequent satellite missions. Within the ESA Climate Change Initiative (CCI) on Sea Ice, a climate data record of sea ice thickness derived from satellite radar altimetry has been developed for both hemispheres, based on the 15-year (2002-2017) monthly retrievals from Envisat and CryoSat-2 and calibrated in the 2010-2012 overlap period. The next step in promoting the utilization of sea ice thickness information from radar altimetry is to provide products by a service that meets the requirements for climate applications and operational systems. This task will be pursued within a Copernicus Climate Change Service project (C3S). This framework also aims to include additional sensors such as onboard Sentinel-3 and we will show first results of Sentinel-3 Arctic sea-ice thickness. These developments are the base for preserving the continuity of the sea ice thickness data record and the transformation from research oriented products into an operational service.

Forecasting Future Sea Ice Conditions: A Lagrangian Approach

DTIC Science & Technology

2015-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Forecasting Future Sea Ice Conditions: A Lagrangian ...GCMs participating in IPCC AR5 agree with observed source region patterns from the satellite- derived dataset. 4- Compare Lagrangian ice... Lagrangian sea-ice back trajectories to estimate thermodynamic and dynamic (advection) ice loss. APPROACH We use a Lagrangian trajectory model to

Successes and Challenges in Linking Observations and Modeling of Marine and Terrestrial Cryospheric Processes

NASA Astrophysics Data System (ADS)

Herzfeld, U. C.; Hunke, E. C.; Trantow, T.; Greve, R.; McDonald, B.; Wallin, B.

2014-12-01

Understanding of the state of the cryosphere and its relationship to other components of the Earth system requires both models of geophysical processes and observations of geophysical properties and processes, however linking observations and models is far from trivial. This paper looks at examples from sea ice and land ice model-observation linkages to examine some approaches, challenges and solutions. In a sea-ice example, ice deformation is analyzed as a key process that indicates fundamental changes in the Arctic sea ice cover. Simulation results from the Los Alamos Sea-Ice Model CICE, which is also the sea-ice component of the Community Earth System Model (CESM), are compared to parameters indicative of deformation as derived from mathematical analysis of remote sensing data. Data include altimeter, micro-ASAR and image data from manned and unmanned aircraft campaigns (NASA OIB and Characterization of Arctic Sea Ice Experiment, CASIE). The key problem to linking data and model results is the derivation of matching parameters on both the model and observation side.For terrestrial glaciology, we include an example of a surge process in a glacier system and and example of a dynamic ice sheet model for Greenland. To investigate the surge of the Bering Bagley Glacier System, we use numerical forward modeling experiments and, on the data analysis side, a connectionist approach to analyze crevasse provinces. In the Greenland ice sheet example, we look at the influence of ice surface and bed topography, as derived from remote sensing data, on on results from a dynamic ice sheet model.

Seasonal sea surface and sea ice signal in the fjords of Eastern Greenland from CryoSat-2 SARin altimetry

NASA Astrophysics Data System (ADS)

Abulaitijiang, Adili; Baltazar Andersen, Ole; Stenseng, Lars

2014-05-01

Cryosat-2 offers the first ever possibility to perform coastal altimetric studies using SAR-Interferometry. This enabled qualified measurements of sea surface height (SST) in the fjords in Greenland. Scoresbysund fjord on the east coast of Greenland is the largest fjord in the world which is also covered by CryoSat-2 SAR-In mask making it a good test region. Also, the tide gauge operated by DTU Space is sitting in Scoresbysund bay, which provides solid ground-based sea level variation records throughout the year. We perform an investigation into sea surface height variation since the start of the Cryosat-2 mission using SAR-In L1B data processed with baseline B processing. We have employed a new develop method for projecting all SAR-In observations in the Fjord onto a centerline up the Fjord. Hereby we can make solid estimates of the annual and (semi-) annual signal in sea level/sea ice freeboard within the Fjord. These seasonal height variations enable us to derive sea ice freeboard changes in the fjord from satellite altimetry. Derived sea level and sea-ice freeboard can be validated by comparison with the tide gauge observations for sea level and output from the Microwave Radiometer derived observations of sea ice freeboard developed at the Danish Meteorological Institute.

Report of the first Nimbus-7 SMMR Experiment Team Workshop

NASA Technical Reports Server (NTRS)

Campbell, W. J.; Gloersen, P.

1983-01-01

Preliminary results of sea ice and techniques for calculating sea ice concentration and multiyear fraction from the microwave radiances obtained from the Nimbus-7 SMMR were presented. From these results, it is evident that these groups used different and independent approaches in deriving sea ice emissivities and algorithms. This precluded precise comparisons of their results. A common set of sea ice emissivities were defined for all groups to use for subsequent more careful comparison of the results from the various sea ice parameter algorithms. To this end, three different geographical areas in two different time intervals were defined as typifying SMMR beam-filling conditions for first year sea ice, multiyear sea ice, and open water and to be used for determining the required microwave emissivities.

Assessing concentration uncertainty estimates from passive microwave sea ice products

NASA Astrophysics Data System (ADS)

Meier, W.; Brucker, L.; Miller, J. A.

2017-12-01

Sea ice concentration is an essential climate variable and passive microwave derived estimates of concentration are one of the longest satellite-derived climate records. However, until recently uncertainty estimates were not provided. Numerous validation studies provided insight into general error characteristics, but the studies have found that concentration error varied greatly depending on sea ice conditions. Thus, an uncertainty estimate from each observation is desired, particularly for initialization, assimilation, and validation of models. Here we investigate three sea ice products that include an uncertainty for each concentration estimate: the NASA Team 2 algorithm product, the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI-SAF) product, and the NOAA/NSIDC Climate Data Record (CDR) product. Each product estimates uncertainty with a completely different approach. The NASA Team 2 product derives uncertainty internally from the algorithm method itself. The OSI-SAF uses atmospheric reanalysis fields and a radiative transfer model. The CDR uses spatial variability from two algorithms. Each approach has merits and limitations. Here we evaluate the uncertainty estimates by comparing the passive microwave concentration products with fields derived from the NOAA VIIRS sensor. The results show that the relationship between the product uncertainty estimates and the concentration error (relative to VIIRS) is complex. This may be due to the sea ice conditions, the uncertainty methods, as well as the spatial and temporal variability of the passive microwave and VIIRS products.

Polarimetric Signatures of Sea Ice. Part 1; Theoretical Model

NASA Technical Reports Server (NTRS)

Nghiem, S. V.; Kwok, R.; Yueh, S. H.; Drinkwater, M. R.

1995-01-01

Physical, structural, and electromagnetic properties and interrelating processes in sea ice are used to develop a composite model for polarimetric backscattering signatures of sea ice. Physical properties of sea ice constituents such as ice, brine, air, and salt are presented in terms of their effects on electromagnetic wave interactions. Sea ice structure and geometry of scatterers are related to wave propagation, attenuation, and scattering. Temperature and salinity, which are determining factors for the thermodynamic phase distribution in sea ice, are consistently used to derive both effective permittivities and polarimetric scattering coefficients. Polarimetric signatures of sea ice depend on crystal sizes and brine volumes, which are affected by ice growth rates. Desalination by brine expulsion, drainage, or other mechanisms modifies wave penetration and scattering. Sea ice signatures are further complicated by surface conditions such as rough interfaces, hummocks, snow cover, brine skim, or slush layer. Based on the same set of geophysical parameters characterizing sea ice, a composite model is developed to calculate effective permittivities and backscattering covariance matrices at microwave frequencies for interpretation of sea ice polarimetric signatures.

An Examination of the Sea Ice Rheology for Seasonal Ice Zones Based on Ice Drift and Thickness Observations

NASA Astrophysics Data System (ADS)

Toyota, Takenobu; Kimura, Noriaki

2018-02-01

The validity of the sea ice rheological model formulated by Hibler (1979), which is widely used in present numerical sea ice models, is examined for the Sea of Okhotsk as an example of the seasonal ice zone (SIZ), based on satellite-derived sea ice velocity, concentration and thickness. Our focus was the formulation of the yield curve, the shape of which can be estimated from ice drift pattern based on the energy equation of deformation, while the strength of the ice cover that determines its magnitude was evaluated using ice concentration and thickness data. Ice 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 ice thickness was obtained with a spatial resolution of 100 m from a regression of the PALSAR backscatter coefficients with ice thickness. To assess scale dependence, the ice 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 ice as a plastic material, with an elliptical shaped yield curve to some extent. However, it also highlights the difficulty in parameterizing sub-grid scale ridging in the model because grid scale ice velocities reduce the deformation magnitude by half due to the large variation of the deformation field in the SIZ.

Short-term sea ice forecasting: An assessment of ice concentration and ice drift forecasts using the U.S. Navy's Arctic Cap Nowcast/Forecast System

NASA Astrophysics Data System (ADS)

Hebert, David A.; Allard, Richard A.; Metzger, E. Joseph; Posey, Pamela G.; Preller, Ruth H.; Wallcraft, Alan J.; Phelps, Michael W.; Smedstad, Ole Martin

2015-12-01

In this study the forecast skill of the U.S. Navy operational Arctic sea ice forecast system, the Arctic Cap Nowcast/Forecast System (ACNFS), is presented for the period February 2014 to June 2015. ACNFS is designed to provide short term, 1-7 day forecasts of Arctic sea ice and ocean conditions. Many quantities are forecast by ACNFS; the most commonly used include ice concentration, ice thickness, ice velocity, sea surface temperature, sea surface salinity, and sea surface velocities. Ice concentration forecast skill is compared to a persistent ice state and historical sea ice climatology. Skill scores are focused on areas where ice concentration changes by ±5% or more, and are therefore limited to primarily the marginal ice zone. We demonstrate that ACNFS forecasts are skilful compared to assuming a persistent ice state, especially beyond 24 h. ACNFS is also shown to be particularly skilful compared to a climatologic state for forecasts up to 102 h. Modeled ice drift velocity is compared to observed buoy data from the International Arctic Buoy Programme. A seasonal bias is shown where ACNFS is slower than IABP velocity in the summer months and faster in the winter months. In February 2015, ACNFS began to assimilate a blended ice concentration derived from Advanced Microwave Scanning Radiometer 2 (AMSR2) and the Interactive Multisensor Snow and Ice Mapping System (IMS). Preliminary results show that assimilating AMSR2 blended with IMS improves the short-term forecast skill and ice edge location compared to the independently derived National Ice Center Ice Edge product.

A Microwave Technique for Mapping Ice Temperature in the Arctic Seasonal Sea Ice Zone

NASA Technical Reports Server (NTRS)

St.Germain, Karen M.; Cavalieri, Donald J.

1997-01-01

A technique for deriving ice temperature in the Arctic seasonal sea ice zone from passive microwave radiances has been developed. The algorithm operates on brightness temperatures derived from the Special Sensor Microwave/Imager (SSM/I) and uses ice concentration and type from a previously developed thin ice algorithm to estimate the surface emissivity. Comparisons of the microwave derived temperatures with estimates derived from infrared imagery of the Bering Strait yield a correlation coefficient of 0.93 and an RMS difference of 2.1 K when coastal and cloud contaminated pixels are removed. SSM/I temperatures were also compared with a time series of air temperature observations from Gambell on St. Lawrence Island and from Point Barrow, AK weather stations. These comparisons indicate that the relationship between the air temperature and the ice temperature depends on ice type.

Satellite altimetry in sea ice regions - detecting open water for estimating sea surface heights

NASA Astrophysics Data System (ADS)

Müller, Felix L.; Dettmering, Denise; Bosch, Wolfgang

2017-04-01

The Greenland Sea and the Farm Strait are transporting sea ice from the central Arctic ocean southwards. They are covered by a dynamic changing sea ice layer with significant influences on the Earth climate system. Between the sea ice there exist various sized open water areas known as leads, straight lined open water areas, and polynyas exhibiting a circular shape. Identifying these leads by satellite altimetry enables the extraction of sea surface height information. Analyzing the radar echoes, also called waveforms, provides information on the surface backscatter characteristics. For example waveforms reflected by calm water have a very narrow and single-peaked shape. Waveforms reflected by sea ice show more variability due to diffuse scattering. Here we analyze altimeter waveforms from different conventional pulse-limited satellite altimeters to separate open water and sea ice waveforms. An unsupervised classification approach employing partitional clustering algorithms such as K-medoids and memory-based classification methods such as K-nearest neighbor is used. The classification is based on six parameters derived from the waveform's shape, for example the maximum power or the peak's width. The open-water detection is quantitatively compared to SAR images processed while accounting for sea ice motion. The classification results are used to derive information about the temporal evolution of sea ice extent and sea surface heights. They allow to provide evidence on climate change relevant influences as for example Arctic sea level rise due to enhanced melting rates of Greenland's glaciers and an increasing fresh water influx into the Arctic ocean. Additionally, the sea ice cover extent analyzed over a long-time period provides an important indicator for a globally changing climate system.

Assessing deformation and morphology of Arctic landfast sea ice using InSAR to support use and management of coastal ice

NASA Astrophysics Data System (ADS)

Dammann, D. O.; Eicken, H.; Meyer, F. J.; Mahoney, A. R.

2016-12-01

Arctic landfast sea ice 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 ice by all stakeholders is increasingly limited by reduced stability of the ice cover, which results in more deformation and rougher ice conditions as well as reduced extent 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 ice use, in particular ice stability and morphology, which are difficult to assess using conventional SAR. InSAR has the capability to detect small-scale landfast ice displacements, which are linked to important coastal hazards, including the formation of cracks, ungrounding of ice pressure ridges, and catastrophic breakout events. While InSAR has previously been used to identify the extent of landfast ice and regions of deformation within, quantitative analysis of small-scale ice motion has yet to be thoroughly validated and its potential remains largely underutilized in sea ice science. Using TanDEM-X interferometry, we derive surface displacements of landfast ice 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 ice deformation in other regions of landfast ice 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 ice patterns and local in-situ observations. The utility of InSAR to quantify sea ice roughness has also been explored using TanDEM-X bistatic interferometry, which eliminates the effects of temporal changes in the ice cover. The InSAR-derived DEM shows good correlation with a high-resolution Structure from Motion DEM and laser surveys collected during a field campaign utilizing unmanned aircraft.

MMAB Operational Products

Science.gov Websites

Atlantic Real-Time Ocean Forecast System NOAA Wavewatch III® Ocean Wave Model Sea Ice Concentration Analysis Satellite Derived Ocean Surface Winds Daily Sea Surface Temperature Analysis Sea Ice Drift Model

Studies of Antarctic Sea Ice Concentrations from Satellite Data and Their Applications

NASA Technical Reports Server (NTRS)

Comiso, Josefino C.; Steffen, Konrad; Zukor, Dorothy J. (Technical Monitor)

2001-01-01

Large changes in the sea ice cover have been observed recently. Because of the relevance of such changes to climate change studies it is important that key ice concentration data sets used for evaluating such changes are interpreted properly. High and medium resolution visible and infrared satellite data are used in conjunction with passive microwave data to study the true characteristics of the Antarctic sea ice cover, assess errors in currently available ice concentration products, and evaluate the applications and limitations of the latter in polar process studies. Cloud-free high resolution data provide valuable information about the natural distribution, stage of formation, and composition of the ice cover that enables interpretation of the large spatial and temporal variability of the microwave emissivity of Antarctic sea ice. Comparative analyses of co-registered visible, infrared and microwave data were used to evaluate ice concentrations derived from standard ice algorithms (i.e., Bootstrap and Team) and investigate the 10 to 35% difference in derived values from large areas within the ice pack, especially in the Weddell Sea, Amundsen Sea, and Ross Sea regions. Landsat and OLS data show a predominance of thick consolidated ice in these areas and show good agreement with the Bootstrap Algorithm. While direct measurements were not possible, the lower values from the Team Algorithm results are likely due to layering within the ice and snow and/or surface flooding, which are known to affect the polarization ratio. In predominantly new ice regions, the derived ice concentration from passive microwave data is usually lower than the true percentage because the emissivity of new ice changes with age and thickness and is lower than that of thick ice. However, the product provides a more realistic characterization of the sea ice cover, and are more useful in polar process studies since it allows for the identification of areas of significant divergence and polynya activities. Also, heat and salinity fluxes are proportionately increased in these areas compared to those from the thicker ice areas. A slight positive trend in ice extent 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 ice edge is quite high.

Seasonal comparisons of sea ice concentration estimates derived from SSM/I, OKEAN, and RADARSAT data

USGS Publications Warehouse

Belchansky, Gennady I.; Douglas, David C.

2002-01-01

The Special Sensor Microwave Imager (SSM/I) microwave satellite radiometer and its predecessor SMMR are primary sources of information for global sea ice and climate studies. However, comparisons of SSM/I, Landsat, AVHRR, and ERS-1 synthetic aperture radar (SAR) have shown substantial seasonal and regional differences in their estimates of sea ice concentration. To evaluate these differences, we compared SSM/I estimates of sea ice coverage derived with the NASA Team and Bootstrap algorithms to estimates made using RADARSAT, and OKEAN-01 satellite sensor data. The study area included the Barents Sea, Kara Sea, Laptev Sea, and adjacent parts of the Arctic Ocean, during October 1995 through October 1999. Ice concentration estimates from spatially and temporally near-coincident imagery were calculated using independent algorithms for each sensor type. The OKEAN algorithm implemented the satellite's two-channel active (radar) and passive microwave data in a linear mixture model based on the measured values of brightness temperature and radar backscatter. The RADARSAT algorithm utilized a segmentation approach of the measured radar backscatter, and the SSM/I ice concentrations were derived at National Snow and Ice Data Center (NSIDC) using the NASA Team and Bootstrap algorithms. Seasonal and monthly differences between SSM/I, OKEAN, and RADARSAT ice concentrations were calculated and compared. Overall, total sea ice concentration estimates derived independently from near-coincident RADARSAT, OKEAN-01, and SSM/I satellite imagery demonstrated mean differences of less than 5.5% (S.D.<9.5%) during the winter period. Differences between the SSM/I NASA Team and the SSM/I Bootstrap concentrations were no more than 3.1% (S.D.<5.4%) during this period. RADARSAT and OKEAN-01 data both yielded higher total ice concentrations than the NASA Team and the Bootstrap algorithms. The Bootstrap algorithm yielded higher total ice concentrations than the NASA Team algorithm. Total ice concentrations derived from OKEAN-01 and SSM/I satellite imagery were highly correlated during winter, spring, and fall, with mean differences of less than 8.1% (S.D.<15%) for the NASA Team algorithm, and less than 2.8% (S.D.<13.8%) for the Bootstrap algorithm. Respective differences between SSM/I NASA Team and SSM/I Bootstrap total concentrations were less than 5.3% (S.D.<6.9%). Monthly mean differences between SSM/I and OKEAN differed annually by less than 6%, with smaller differences primarily in winter. The NASA Team and Bootstrap algorithms underestimated the total sea ice concentrations relative to the RADARSAT ScanSAR no more than 3.0% (S.D.<9%) and 1.2% (S.D.<7.5%) during cold months, and no more than 12% and 7% during summer, respectively. ScanSAR tended to estimate higher ice concentrations for ice concentrations greater than 50%, when compared to SSM/I during all months. ScanSAR underestimated total sea ice concentration by 2% compared to the OKEAN-01 algorithm during cold months, and gave an overestimation by 2% during spring and summer months. Total NASA Team and Bootstrap sea ice concentration estimates derived from coincident SSM/I and OKEAN-01 data demonstrated mean differences of no more than 5.3% (S.D.<7%), 3.1% (S.D.<5.5%), 2.0% (S.D.<5.5%), and 7.3% (S.D.<10%) for fall, winter, spring, and summer periods, respectively. Large disagreements were observed between the OKEAN and NASA Team results in spring and summer for estimates of the first-year (FY) and multiyear (MY) age classes. The OKEAN-01 algorithm and data tended to estimate, on average, lower concentrations of young or FY ice and higher concentrations of total and MY ice for all months and seasons. Our results contribute to the growing body of documentation about the levels of disparity obtained when seasonal sea ice concentrations are estimated using various types of satellite data and algorithms.

Atmospheric forcing of sea ice anomalies in the Ross Sea polynya region

NASA Astrophysics Data System (ADS)

Dale, Ethan R.; McDonald, Adrian J.; Coggins, Jack H. J.; Rack, Wolfgang

2017-01-01

We investigate the impacts of strong wind events on the sea ice concentration within the Ross Sea polynya (RSP), which may have consequences on sea ice formation. Bootstrap sea ice concentration (SIC) measurements derived from satellite SSM/I brightness temperatures are correlated with surface winds and temperatures from Ross Ice Shelf automatic weather stations (AWSs) and weather models (ERA-Interim). Daily data in the austral winter period were used to classify characteristic weather regimes based on the percentiles of wind speed. For each regime a composite of a SIC anomaly was formed for the entire Ross Sea region and we found that persistent weak winds near the edge of the Ross Ice Shelf are generally associated with positive SIC anomalies in the Ross Sea polynya and vice versa. By analyzing sea ice motion vectors derived from the SSM/I brightness temperatures we find significant sea ice motion anomalies throughout the Ross Sea during strong wind events, which persist for several days after a strong wind event has ended. Strong, negative correlations are found between SIC and AWS wind speed within the RSP indicating that strong winds cause significant advection of sea ice in the region. We were able to partially recreate these correlations using colocated, modeled ERA-Interim wind speeds. However, large AWS and model differences are observed in the vicinity of Ross Island, where ERA-Interim underestimates wind speeds by a factor of 1.7 resulting in a significant misrepresentation of RSP processes in this area based on model data. Thus, the cross-correlation functions produced by compositing based on ERA-Interim wind speeds differed significantly from those produced with AWS wind speeds. In general the rapid decrease in SIC during a strong wind event is followed by a more gradual recovery in SIC. The SIC recovery continues over a time period greater than the average persistence of strong wind events and sea ice motion anomalies. This suggests that sea ice recovery occurs through thermodynamic rather than dynamic processes.

Sea ice and oceanic processes on the Ross Sea continental shelf

NASA Technical Reports Server (NTRS)

Jacobs, S. S.; Comiso, J. C.

1989-01-01

The spatial and temporal variability of Antarctic sea ice concentrations on the Ross Sea continental shelf have been investigated in relation to oceanic and atmospheric forcing. Sea ice data were derived from Nimbus 7 scanning multichannel microwave radiometer (SMMR) brightness temperatures from 1979-1986. Ice cover over the shelf was persistently lower than above the adjacent deep ocean, averaging 86 percent during winter with little month-to-month of interannual variability. The large spring Ross Sea polynya on the western shelf results in a longer period of summer insolation, greater surface layer heat storage, and later ice formation in that region the following autumn.

Surface water mass composition changes captured by cores of Arctic land-fast sea ice

NASA Astrophysics Data System (ADS)

Smith, I. J.; Eicken, H.; Mahoney, A. R.; Van Hale, R.; Gough, A. J.; Fukamachi, Y.; Jones, J.

2016-04-01

In the Arctic, land-fast sea ice growth can be influenced by fresher water from rivers and residual summer melt. This paper examines a method to reconstruct changes in water masses using oxygen isotope measurements of sea ice cores. To determine changes in sea water isotope composition over the course of the ice growth period, the output of a sea ice thermodynamic model (driven with reanalysis data, observations of snow depth, and freeze-up dates) is used along with sea ice oxygen isotope measurements and an isotopic fractionation model. Direct measurements of sea ice growth rates are used to validate the output of the sea ice growth model. It is shown that for sea ice formed during the 2011/2012 ice growth season at Barrow, Alaska, large changes in isotopic composition of the ocean waters were captured by the sea ice isotopic composition. Salinity anomalies in the ocean were also tracked by moored instruments. These data indicate episodic advection of meteoric water, having both lower salinity and lower oxygen isotopic composition, during the winter sea ice growth season. Such advection of meteoric water during winter is surprising, as no surface meltwater and no local river discharge should be occurring at this time of year in that area. How accurately changes in water masses as indicated by oxygen isotope composition can be reconstructed using oxygen isotope analysis of sea ice cores is addressed, along with methods/strategies that could be used to further optimize the results. The method described will be useful for winter detection of meteoric water presence in Arctic fast ice regions, which is important for climate studies in a rapidly changing Arctic. Land-fast sea ice effective fractionation coefficients were derived, with a range of +1.82‰ to +2.52‰. Those derived effective fractionation coefficients will be useful for future water mass component proportion calculations. In particular, the equations given can be used to inform choices made when engaging in end member determination for working out the component proportions of water masses.

Classification methods for monitoring Arctic sea ice using OKEAN passive/active two-channel microwave data

USGS Publications Warehouse

Belchansky, Gennady I.; Douglas, David C.

2000-01-01

This paper presents methods for classifying Arctic sea ice using both passive and active (2-channel) microwave imagery acquired by the Russian OKEAN 01 polar-orbiting satellite series. Methods and results are compared to sea ice classifications derived from nearly coincident Special Sensor Microwave Imager (SSM/I) and Advanced Very High Resolution Radiometer (AVHRR) image data of the Barents, Kara, and Laptev Seas. The Russian OKEAN 01 satellite data were collected over weekly intervals during October 1995 through December 1997. Methods are presented for calibrating, georeferencing and classifying the raw active radar and passive microwave OKEAN 01 data, and for correcting the OKEAN 01 microwave radiometer calibration wedge based on concurrent 37 GHz horizontal polarization SSM/I brightness temperature data. Sea ice type and ice concentration algorithms utilized OKEAN's two-channel radar and passive microwave data in a linear mixture model based on the measured values of brightness temperature and radar backscatter, together with a priori knowledge about the scattering parameters and natural emissivities of basic sea ice types. OKEAN 01 data and algorithms tended to classify lower concentrations of young or first-year sea ice when concentrations were less than 60%, and to produce higher concentrations of multi-year sea ice when concentrations were greater than 40%, when compared to estimates produced from SSM/I data. Overall, total sea ice concentration maps derived independently from OKEAN 01, SSM/I, and AVHRR satellite imagery were all highly correlated, with uniform biases, and mean differences in total ice concentration of less than four percent (sd<15%).

Satellite-derived ice data sets no. 2: Arctic monthly average microwave brightness temperatures and sea ice concentrations, 1973-1976

NASA Technical Reports Server (NTRS)

Parkinson, C. L.; Comiso, J. C.; Zwally, H. J.

1987-01-01

A summary data set for four years (mid 70's) of Arctic sea ice conditions is available on magnetic tape. The data include monthly and yearly averaged Nimbus 5 electrically scanning microwave radiometer (ESMR) brightness temperatures, an ice concentration parameter derived from the brightness temperatures, monthly climatological surface air temperatures, and monthly climatological sea level pressures. All data matrices are applied to 293 by 293 grids that cover a polar stereographic map enclosing the 50 deg N latitude circle. The grid size varies from about 32 X 32 km at the poles to about 28 X 28 km at 50 deg N. The ice concentration parameter is calculated assuming that the field of view contains only open water and first-year ice with an ice emissivity of 0.92. To account for the presence of multiyear ice, a nomogram is provided relating the ice concentration parameter, the total ice concentration, and the fraction of the ice cover which is multiyear ice.

Statistical Analyses of High-Resolution Aircraft and Satellite Observations of Sea Ice: Applications for Improving Model Simulations

NASA Astrophysics Data System (ADS)

Farrell, S. L.; Kurtz, N. T.; Richter-Menge, J.; Harbeck, J. P.; Onana, V.

2012-12-01

Satellite-derived estimates of ice thickness and observations of ice extent over the last decade point to a downward trend in the basin-scale ice 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 ice pack and advance parameterizations in the next generation of numerical sea-ice models. High-resolution airborne and satellite observations of the sea ice are now available at meter-scale resolution or better that provide new details on the properties and morphology of the ice pack across basin scales. For example the NASA IceBridge airborne campaign routinely surveys the sea ice 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 ice freeboard, thickness, snow depth and lead distribution. Here we present statistical analyses of the ice pack primarily derived from the following IceBridge 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 ice. Together these instruments provide data from which a wide range of sea ice 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 ice regions, for example first-year/multi-year ice, diffuse ice edge/consolidated ice pack, and convergent/divergent ice zones, (ii) provide datasets that support enhanced parameterizations in numerical models as well as model initialization and validation, (iii) parameters of interest to Arctic stakeholders for marine navigation and ice engineering studies, and (iv) statistics that support algorithm development for the next-generation of airborne and satellite altimeters, including NASA's ICESat-2 mission. We describe the potential contribution our results can make towards the improvement of coupled ice-ocean numerical models, and discuss how data synthesis and integration with high-resolution models may improve our understanding of sea ice variability and our capabilities in predicting the future state of the ice pack.

Airborne gravity measurement over sea-ice: The western Weddel Sea

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brozena, J.; Peters, M.; LaBrecque, J.

1990-10-01

An airborne gravity study of the western Weddel Sea, east of the Antarctic Peninsula, has shown that floating pack-ice provides a useful radar altimetric reference surface for altitude and vertical acceleration corrections surface for alititude and vertical acceleration corrections to airborne gravimetry. Airborne gravimetry provides an important alternative to satellite altimetry for the sea-ice covered regions of the world since satellite alimeters are not designed or intended to provide accurate geoidal heights in areas where significant sea-ice is present within the radar footprint. Errors in radar corrected airborne gravimetry are primarily sensitive to the variations in the second derivative ofmore » the sea-ice reference surface in the frequency pass-band of interest. With the exception of imbedded icebergs the second derivative of the pack-ice surface closely approximates that of the mean sea-level surface at wavelengths > 10-20 km. With the airborne method the percentage of ice coverage, the mixture of first and multi-year ice and the existence of leads and pressure ridges prove to be unimportant in determining gravity anomalies at scales of geophysical and geodetic interest, provided that the ice is floating and not grounded. In the Weddell study an analysis of 85 crosstrack miss-ties distributed over 25 data tracks yields an rms error of 2.2 mGals. Significant structural anomalies including the continental shelf and offsets and lineations interpreted as fracture zones recording the early spreading directions within the Weddell Sea are observed in the gravity map.« less

Characterizing Arctic Sea Ice Topography Using High-Resolution IceBridge Data

NASA Technical Reports Server (NTRS)

Petty, Alek; Tsamados, Michel; Kurtz, Nathan; Farrell, Sinead; Newman, Thomas; Harbeck, Jeremy; Feltham, Daniel; Richter-Menge, Jackie

2016-01-01

We present an analysis of Arctic sea ice topography using high resolution, three-dimensional, surface elevation data from the Airborne Topographic Mapper, flown as part of NASA's Operation IceBridge mission. Surface features in the sea ice cover are detected using a newly developed surface feature picking algorithm. We derive information regarding the height, volume and geometry of surface features from 2009-2014 within the Beaufort/Chukchi and Central Arctic regions. The results are delineated by ice type to estimate the topographic variability across first-year and multi-year ice regimes.

Sea ice roughness: the key for predicting Arctic summer ice albedo

NASA Astrophysics Data System (ADS)

Landy, J.; Ehn, J. K.; Tsamados, M.; Stroeve, J.; Barber, D. G.

2017-12-01

Although melt ponds on Arctic sea ice evolve in stages, ice with smoother surface topography typically allows the pond water to spread over a wider area, reducing the ice-albedo and accelerating further melt. Building on this theory, we simulated the distribution of meltwater on a range of statistically-derived topographies to develop a quantitative relationship between premelt sea ice surface roughness and summer ice albedo. Our method, previously applied to ICESat observations of the end-of-winter sea ice roughness, could account for 85% of the variance in AVHRR observations of the summer ice-albedo [Landy et al., 2015]. Consequently, an Arctic-wide reduction in sea ice roughness over the ICESat operational period (from 2003 to 2008) explained a drop in ice-albedo that resulted in a 16% increase in solar heat input to the sea ice cover. Here we will review this work and present new research linking pre-melt sea ice surface roughness observations from Cryosat-2 to summer sea ice albedo over the past six years, examining the potential of winter roughness as a significant new source of sea ice predictability. We will further evaluate the possibility for high-resolution (kilometre-scale) forecasts of summer sea ice albedo from waveform-level Cryosat-2 roughness data in the landfast sea ice zone of the Canadian Arctic. Landy, J. C., J. K. Ehn, and D. G. Barber (2015), Albedo feedback enhanced by smoother Arctic sea ice, Geophys. Res. Lett., 42, 10,714-10,720, doi:10.1002/2015GL066712.

Indigenous Knowledge and Sea Ice Science: What Can We Learn from Indigenous Ice Users?

NASA Astrophysics Data System (ADS)

Eicken, H.

2010-12-01

Drawing on examples mostly from Iñupiaq and Yup’ik sea-ice expertise in coastal Alaska, this contribution examines how local, indigenous knowledge (LIK) can inform and guide geophysical and biological sea-ice research. Part of the relevance of LIK derives from its linkage to sea-ice use and the services coastal communities derive from the ice cover. As a result, indigenous experts keep track of a broad range of sea-ice variables at a particular location. These observations are embedded into a broader worldview that speaks to both long-term variability or change and to the system of values associated with ice use. The contribution examines eight different contexts in which LIK in study site selection and assessment of a sampling campaign in the context of inter annual variability, the identification of rare or inconspicuous phenomena or events, the contribution by indigenous experts to hazard assessment and emergency response, the record of past and present climate embedded in LIK, and the value of holistic sea-ice knowledge in detecting subtle, intertwined patterns of environmental change. The relevance of local, indigenous sea-ice expertise in helping advance adaptation and responses to climate change as well as its potential role in guiding research questions and hypotheses are also examined. The challenges that may have to be overcome in creating an interface for exchange between indigenous experts and seaice researchers are considered. Promising approaches to overcome these challenges include cross-cultural, interdisciplinary education, and the fostering of Communities of Practice.

Retrieval of sea ice thickness during Arctic summer using melt pond color

NASA Astrophysics Data System (ADS)

Istomina, L.; Nicolaus, M.; Heygster, G.

2016-12-01

The thickness of sea ice is an important climatic variable. Together with the ice concentration, it defines the total sea ice volume, is linked within the climatic feedback mechanisms and affects the Arctic energy balance greatly. During Arctic summer, the sea ice cover changes rapidly, which includes the presence of melt ponds, as well as reduction of ice albedo and ice thickness. Currently available remote sensing retrievals of sea ice thickness utilize data from altimeter, microwave, thermal infrared sensors and their combinations. All of these methods are compromised in summer in the presence of melt. This only leaves in situ and airborne sea ice thickness data available in summer. At the same time, data of greater coverage is needed for assimilation in global circulation models and correct estimation of ice mass balance.This study presents a new approach to estimate sea ice thickness in summer in the presence of melt ponds. Analysis of field data obtained during the RV "Polarstern" cruise ARK27/3 (August - October 2012) has shown a clear connection of ice thickness under melt ponds to their measured spectral albedo and to melt pond color in the hue-saturation-luminance color space from field photographs. An empirical function is derived from the HSL values and applied to aerial imagery obtained during various airborne campaigns. Comparison to in situ ice thickness shows a good correspondence to the ice thickness value retrieved in the melt ponds. A similar retrieval is developed for satellite spectral bands using the connection of the measured pond spectral albedo to the ice thickness within the melt ponds. Correction of the retrieved ice thickness in ponds to derive total thickness of sea ice is discussed. Case studies and application to very high resolution optical data are presented, as well as a concept to transfer the method to satellite data of lower spatial resolution where melt ponds become subpixel features.

A Parameter Tuning Scheme of Sea-ice Model Based on Automatic Differentiation Technique

NASA Astrophysics Data System (ADS)

Kim, J. G.; Hovland, P. D.

2001-05-01

Automatic diferentiation (AD) technique was used to illustrate a new approach for parameter tuning scheme of an uncoupled sea-ice model. Atmospheric forcing field of 1992 obtained from NCEP data was used as enforcing variables in the study. The simulation results were compared with the observed ice movement provided by the International Arctic Buoy Programme (IABP). All of the numerical experiments were based on a widely used dynamic and thermodynamic model for simulating the seasonal sea-ice chnage of the main Arctic ocean. We selected five dynamic and thermodynamic parameters for the tuning process in which the cost function defined by the norm of the difference between observed and simulated ice drift locations was minimized. The selected parameters are the air and ocean drag coefficients, the ice strength constant, the turning angle at ice-air/ocean interface, and the bulk sensible heat transfer coefficient. The drag coefficients were the major parameters to control sea-ice movement and extent. The result of the study shows that more realistic simulations of ice thickness distribution was produced by tuning the simulated ice drift trajectories. In the tuning process, the L-BFCGS-B minimization algorithm of a quasi-Newton method was used. The derivative information required in the minimization iterations was provided by the AD processed Fortran code. Compared with a conventional approach, AD generated derivative code provided fast and robust computations of derivative information.

Reconciliation of late Quaternary sea levels derived from coral terraces at Huon Peninsula with deep sea oxygen isotope records

NASA Astrophysics Data System (ADS)

Chappell, John; Omura, Akio; Esat, Tezer; McCulloch, Malcolm; Pandolfi, John; Ota, Yoko; Pillans, Brad

1996-06-01

A major discrepancy between the Late Quaternary sea level changes derived from raised coral reef terraces at the Huon Peninsula in Papua New Guinea and from oxygen isotopes in deep sea cores is resolved. The two methods agree closely from 120 ka to 80 ka and from 20 ka to 0 ka (ka = 1000 yr before present), but between 70 and 30 ka the isotopic sea levels are 20-40 m lower than the Huon Peninsula sea levels derived in earlier studies. New, high precision U-series age measurements and revised stratigraphic data for Huon Peninsula terraces aged between 30 and 70 ka now give similar sea levels to those based on deep sea oxygen isotope data planktonic and benthic δ 18O data. Using the sea level and deep sea isotopic data, oxygen isotope ratios are calculated for the northern continental ice sheets through the last glacial cycle and are consistent with results from Greenland ice cores. The record of ice volume changes through the last glacial cycle now appears to be reasonably complete.

Abnormal Winter Melting of the Arctic Sea Ice Cap Observed by the Spaceborne Passive Microwave Sensors

NASA Astrophysics Data System (ADS)

Lee, Seongsuk; Yi, Yu

2016-12-01

The spatial size and variation of Arctic sea ice play an important role in Earth’s climate system. These are affected by conditions in the polar atmosphere and Arctic sea temperatures. The Arctic sea ice concentration is calculated from brightness temperature data derived from the Defense Meteorological Satellite program (DMSP) F13 Special Sensor Microwave/Imagers (SSMI) and the DMSP F17 Special Sensor Microwave Imager/Sounder (SSMIS) sensors. Many previous studies point to significant reductions in sea ice and their causes. We investigated the variability of Arctic sea ice using the daily sea ice concentration data from passive microwave observations to identify the sea ice melting regions near the Arctic polar ice cap. We discovered the abnormal melting of the Arctic sea ice near the North Pole during the summer and the winter. This phenomenon is hard to explain only surface air temperature or solar heating as suggested by recent studies. We propose a hypothesis explaining this phenomenon. The heat from the deep sea in Arctic Ocean ridges and/ or the hydrothermal vents might be contributing to the melting of Arctic sea ice. This hypothesis could be verified by the observation of warm water column structure below the melting or thinning arctic sea ice through the project such as Coriolis dataset for reanalysis (CORA).

Observational Evidence of a Hemispheric-wide Ice-ocean Albedo Feedback Effect on Antarctic Sea-ice Decay

NASA Technical Reports Server (NTRS)

Nihashi, Sohey; Cavalieri, Donald J.

2007-01-01

The effect of ice-ocean albedo feedback (a kind of ice-albedo feedback) on sea-ice decay is demonstrated over the Antarctic sea-ice zone from an analysis of satellite-derived hemispheric sea ice concentration and European Centre for Medium-Range Weather Forecasts (ERA-40) atmospheric data for the period 1979-2001. Sea ice concentration in December (time of most active melt) correlates better with the meridional component of the wind-forced ice drift (MID) in November (beginning of the melt season) than the MID in December. This 1 month lagged correlation is observed in most of the Antarctic sea-ice covered ocean. Daily time series of ice , concentration show that the ice concentration anomaly increases toward the time of maximum sea-ice melt. These findings can be explained by the following positive feedback effect: once ice concentration decreases (increases) at the beginning of the melt season, solar heating of the upper ocean through the increased (decreased) open water fraction is enhanced (reduced), leading to (suppressing) a further decrease in ice concentration by the oceanic heat. Results obtained fi-om a simple ice-ocean coupled model also support our interpretation of the observational results. This positive feedback mechanism explains in part the large interannual variability of the sea-ice cover in summer.

The melting sea ice of Arctic polar cap in the summer solstice month and the role of ocean

NASA Astrophysics Data System (ADS)

Lee, S.; Yi, Y.

2014-12-01

The Arctic sea ice is becoming smaller and thinner than climatological standard normal and more fragmented in the early summer. We investigated the widely changing Arctic sea ice using the daily sea ice concentration data. Sea ice data is generated from brightness temperature data derived from the sensors: Defense Meteorological Satellite Program (DMSP)-F13 Special Sensor Microwave/Imagers (SSM/Is), the DMSP-F17 Special Sensor Microwave Imager/Sounder (SSMIS) and the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) instrument on the NASA Earth Observing System (EOS) Aqua satellite. We tried to figure out appearance of arctic sea ice melting region of polar cap from the data of passive microwave sensors. It is hard to explain polar sea ice melting only by atmosphere effects like surface air temperature or wind. Thus, our hypothesis explaining this phenomenon is that the heat from deep undersea in Arctic Ocean ridges and the hydrothermal vents might be contributing to the melting of Arctic sea ice.

Variational Ridging in Sea Ice Models

NASA Astrophysics Data System (ADS)

Roberts, A.; Hunke, E. C.; Lipscomb, W. H.; Maslowski, W.; Kamal, S.

2017-12-01

This work presents the results of a new development to make basin-scale sea ice models aware of the shape, porosity and extent of individual ridges within the pack. We have derived an analytic solution for the Euler-Lagrange equation of individual ridges that accounts for non-conservative forces, and therefore the compressive strength of individual ridges. Because a region of the pack is simply a collection of paths of individual ridges, we are able to solve the Euler-Lagrange equation for a large-scale sea ice field also, and therefore the compressive strength of a region of the pack that explicitly accounts for the macro-porosity of ridged debris. We make a number of assumptions that have simplified the problem, such as treating sea ice as a granular material in ridges, and assuming that bending moments associated with ridging are perturbations around an isostatic state. Regardless of these simplifications, the ridge model is remarkably predictive of macro-porosity and ridge shape, and, because our equations are analytic, they do not require costly computations to solve the Euler-Lagrange equation of ridges on the large scale. The new ridge model is therefore applicable to large-scale sea ice models. We present results from this theoretical development, as well as plans to apply it to the Regional Arctic System Model and a community sea ice code. Most importantly, the new ridging model is particularly useful for pinpointing gaps in our observational record of sea ice ridges, and points to the need for improved measurements of the evolution of porosity of deformed ice in the Arctic and Antarctic. Such knowledge is not only useful for improving models, but also for improving estimates of sea ice volume derived from altimetric measurements of sea ice freeboard.

Low-frequency passive-microwave observations of sea ice in the Weddell Sea

NASA Technical Reports Server (NTRS)

Menashi, James D.; St. Germain, Karen M.; Swift, Calvin T.; Comiso, Josefino C.; Lohanick, Alan W.

1993-01-01

The microwave emission properties of first-year sea ice were investigated from the R/V Polarstern during the Antarctic Winter Weddell Gyre Project in 1989. Radiometer measurements were made at 611 MHz and 10 GHz and were accompanied by video and visual observations. Using the theory of radiometric emission from a layered medium, a method for deriving sea ice thickness from radiometer data is developed and tested. The model is based on an incoherent reflection process and predicts that the emissivity of saline ice increases monotonically with increasing ice thickness until saturation occurs.

NASA, Navy, and AES/York sea ice concentration comparison of SSM/I algorithms with SAR derived values

NASA Technical Reports Server (NTRS)

Jentz, R. R.; Wackerman, C. C.; Shuchman, R. A.; Onstott, R. G.; Gloersen, Per; Cavalieri, Don; Ramseier, Rene; Rubinstein, Irene; Comiso, Joey; Hollinger, James

1991-01-01

Previous research studies have focused on producing algorithms for extracting geophysical information from passive microwave data regarding ice floe size, sea ice concentration, open water lead locations, and sea ice extent. These studies have resulted in four separate algorithms for extracting these geophysical parameters. Sea ice concentration estimates generated from each of these algorithms (i.e., NASA/Team, NASA/Comiso, AES/York, and Navy) are compared to ice concentration estimates produced from coincident high-resolution synthetic aperture radar (SAR) data. The SAR concentration estimates are produced from data collected in both the Beaufort Sea and the Greenland Sea in March 1988 and March 1989, respectively. The SAR data are coincident to the passive microwave data generated by the Special Sensor Microwave/Imager (SSM/I).

The interaction between sea ice and salinity-dominated ocean circulation: implications for halocline stability and rapid changes of sea-ice cover

NASA Astrophysics Data System (ADS)

Jensen, M. F.; Nilsson, J.; Nisancioglu, K. H.

2016-02-01

In this study, we develop a simple conceptual model to examine how interactions between sea ice and oceanic heat and freshwater transports affect the stability of an upper-ocean halocline in a semi-enclosed basin. The model represents a sea-ice covered and salinity stratified ocean, and consists of a sea-ice component and a two-layer ocean; a cold, fresh surface layer above a warmer, more saline layer. The sea-ice thickness depends on the atmospheric energy fluxes as well as the ocean heat flux. We introduce a thickness-dependent sea-ice export. Whether sea ice stabilizes or destabilizes against a freshwater perturbation is shown to depend on the representation of the vertical mixing. In a system where the vertical diffusivity is constant, the sea ice acts as a positive feedback on a freshwater perturbation. If the vertical diffusivity is derived from a constant mixing energy constraint, the sea ice acts as a negative feedback. However, both representations lead to a circulation that breaks down when the freshwater input at the surface is small. As a consequence, we get rapid changes in sea ice. In addition to low freshwater forcing, increasing deep-ocean temperatures promote instability and the disappearance of sea ice. Generally, the unstable state is reached before the vertical density difference disappears, and small changes in temperature and freshwater inputs can provoke abrupt changes in sea ice.

Contribution of sea ice microbial production to Antarctic benthic communities is driven by sea ice dynamics and composition of functional guilds.

PubMed

Wing, Stephen R; Leichter, James J; Wing, Lucy C; Stokes, Dale; Genovese, Sal J; McMullin, Rebecca M; Shatova, Olya A

2018-04-28

Organic matter produced by the sea ice microbial community (SIMCo) is an important link between sea ice dynamics and secondary production in near-shore food webs of Antarctica. Sea ice conditions in McMurdo Sound were quantified from time series of MODIS satellite images for Sept. 1 through Feb. 28 of 2007-2015. A predictable sea ice persistence gradient along the length of the Sound and evidence for a distinct change in sea ice dynamics in 2011 were observed. We used stable isotope analysis (δ 13 C and δ 15 N) of SIMCo, suspended particulate organic matter (SPOM) and shallow water (10-20 m) macroinvertebrates to reveal patterns in trophic structure of, and incorporation of organic matter from SIMCo into, benthic communities at eight sites distributed along the sea ice persistence gradient. Mass-balance analysis revealed distinct trophic architecture among communities and large fluxes of SIMCo into the near-shore food web, with the estimates ranging from 2 to 84% of organic matter derived from SIMCo for individual species. Analysis of patterns in density, and biomass of macroinvertebrate communities among sites allowed us to model net incorporation of organic matter from SIMCo, in terms of biomass per unit area (g/m 2 ), into benthic communities. Here, organic matter derived from SIMCo supported 39 to 71 per cent of total biomass. Furthermore, for six species, we observed declines in contribution of SIMCo between years with persistent sea ice (2008-2009) and years with extensive sea ice breakout (2012-2015). Our data demonstrate the vital role of SIMCo in ecosystem function in Antarctica and strong linkages between sea ice dynamics and near-shore secondary productivity. These results have important implications for our understanding of how benthic communities will respond to changes in sea ice dynamics associated with climate change and highlight the important role of shallow water macroinvertebrate communities as sentinels of change for the Antarctic marine ecosystem. © 2018 John Wiley & Sons Ltd.

Arctic and Antarctic Sea-Ice Freeboard and Thickness Retrievals from CryoSat-2 and EnviSat

NASA Astrophysics Data System (ADS)

Ricker, Robert; Hendricks, Stefan; Schwegmann, Sandra; Helm, Veit; Rinne, Eero

2016-04-01

The CryoSat-2 satellite is now in the 6th year of data acquisition. With its synthetic aperture radar altimeter, CryoSat-2 achieves great improvements in the along track resolution compared to previous radar altimeter missions like ERS or Envisat. The latitudinal coverage contains major parts of the Arctic marine ice fields where previous missions left a big data gap around the North Pole and especially over the multiyear ice zone north of Greenland. With this unique data set, changes in sea-ice thickness can be investigated in the context of the rapid reduction of the Arctic sea-ice cover which has been observed during the last decades. We present the current state of the CryoSat-2 Arctic sea-ice thickness retrieval that is processed at the Alfred Wegener Institute and available via seaiceportal.de (originally: meereisportal.de). Though biases in sea-ice thickness may occur due to the interpretation of waveforms, airborne and ground-based validation measurements give confidence that the retrieval algorithm enables us to capture the actual distributions of sea-ice regimes. Nevertheless, long time series of data retrievals are essential to estimate trends in sea-ice thickness and volume. Today, more than 20 years of radar altimeter data are potentially available and capable to derive sea ice thickness. However, data originate from satellites with different sensor characteristics. Therefore, it is crucial to study the consistency between single sensors to derive long and consistent time series. We present results from the tested consistency between Antarctic freeboard measurements of the radar altimeters on-board of Envisat and CryoSat-2 for their overlap period in 2011.

ICESat Observations of Arctic Sea Ice: A First Look

NASA Technical Reports Server (NTRS)

Kwok, Ron; Zwally, H. Jay; Yi, Dong-Hui

2004-01-01

Analysis of near-coincident ICESat and RADARSAT imagery shows that the retrieved elevations from the laser altimeter are sensitive to new openings (containing thin ice or open water) in the sea ice cover as well as to surface relief of old and first-year ice. The precision of the elevation estimates, measured over relatively flat sea ice, is approx. 2 cm Using the thickness of thin-ice in recent openings to estimate sea level references, we obtain the sea-ice free-board along the altimeter tracks. This step is necessitated by the large uncertainties in the time-varying sea surface topography compared to that required for accurate determination of free-board. Unknown snow depth introduces the largest uncertainty in the conversion of free-board to ice thickness. Surface roughness is also derived, for the first time, from the variability of successive elevation estimates along the altimeter track Overall, these ICESat measurements provide an unprecedented view of the Arctic Ocean ice cover at length scales at and above the spatial dimension of the altimeter footprint.

On the retrieval of sea ice thickness and snow depth using concurrent laser altimetry and L-band remote sensing data

NASA Astrophysics Data System (ADS)

Zhou, Lu; Xu, Shiming; Liu, Jiping; Wang, Bin

2018-03-01

The accurate knowledge of sea ice parameters, including sea ice thickness and snow depth over the sea ice cover, is key to both climate studies and data assimilation in operational forecasts. Large-scale active and passive remote sensing is the basis for the estimation of these parameters. In traditional altimetry or the retrieval of snow depth with passive microwave remote sensing, although the sea ice thickness and the snow depth are closely related, the retrieval of one parameter is usually carried out under assumptions over the other. For example, climatological snow depth data or as derived from reanalyses contain large or unconstrained uncertainty, which result in large uncertainty in the derived sea ice thickness and volume. In this study, we explore the potential of combined retrieval of both sea ice thickness and snow depth using the concurrent active altimetry and passive microwave remote sensing of the sea ice cover. Specifically, laser altimetry and L-band passive remote sensing data are combined using two forward models: the L-band radiation model and the isostatic relationship based on buoyancy model. Since the laser altimetry usually features much higher spatial resolution than L-band data from the Soil Moisture Ocean Salinity (SMOS) satellite, there is potentially covariability between the observed snow freeboard by altimetry and the retrieval target of snow depth on the spatial scale of altimetry samples. Statistically significant correlation is discovered based on high-resolution observations from Operation IceBridge (OIB), and with a nonlinear fitting the covariability is incorporated in the retrieval algorithm. By using fitting parameters derived from large-scale surveys, the retrievability is greatly improved compared with the retrieval that assumes flat snow cover (i.e., no covariability). Verifications with OIB data show good match between the observed and the retrieved parameters, including both sea ice thickness and snow depth. With detailed analysis, we show that the error of the retrieval mainly arises from the difference between the modeled and the observed (SMOS) L-band brightness temperature (TB). The narrow swath and the limited coverage of the sea ice cover by altimetry is the potential source of error associated with the modeling of L-band TB and retrieval. The proposed retrieval methodology can be applied to the basin-scale retrieval of sea ice thickness and snow depth, using concurrent passive remote sensing and active laser altimetry based on satellites such as ICESat-2 and WCOM.

Estimation of Melt Ponds over Arctic Sea Ice using MODIS Surface Reflectance Data

NASA Astrophysics Data System (ADS)

Ding, Y.; Cheng, X.; Liu, J.

2017-12-01

Melt ponds over Arctic sea ice is one of the main factors affecting variability of surface albedo, increasing absorption of solar radiation and further melting of snow and ice. 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 ice minimum. In the study, we extract the melt pond fraction over Arctic sea ice since 2000 using three bands MODIS weekly surface reflectance data by considering the difference of spectral reflectance in ponds, ice 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 trend 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 trend in the melt pond fraction is observed for the period of 2000-2017. The relationship between melt pond fraction and sea ice extent will be also discussed. Key Words: melt ponds, sea ice, Arctic

Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: Mean seasonal cycle

NASA Astrophysics Data System (ADS)

Li, Linghan; McClean, Julie L.; Miller, Arthur J.; Eisenman, Ian; Hendershott, Myrl C.; Papadopoulos, Caroline A.

2014-12-01

The seasonal cycle of sea ice variability in the Bering Sea, together with the thermodynamic and dynamic processes that control it, are examined in a fine resolution (1/10°) global coupled ocean/sea-ice model configured in the Community Earth System Model (CESM) framework. The ocean/sea-ice model consists of the Los Alamos National Laboratory Parallel Ocean Program (POP) and the Los Alamos Sea Ice Model (CICE). The model was forced with time-varying reanalysis atmospheric forcing for the time period 1970-1989. This study focuses on the time period 1980-1989. The simulated seasonal-mean fields of sea ice concentration strongly resemble satellite-derived observations, as quantified by root-mean-square errors and pattern correlation coefficients. The sea ice energy budget reveals that the seasonal thermodynamic ice volume changes are dominated by the surface energy flux between the atmosphere and the ice in the northern region and by heat flux from the ocean to the ice along the southern ice edge, especially on the western side. The sea ice force balance analysis shows that sea ice motion is largely associated with wind stress. The force due to divergence of the internal ice stress tensor is large near the land boundaries in the north, and it is small in the central and southern ice-covered region. During winter, which dominates the annual mean, it is found that the simulated sea ice was mainly formed in the northern Bering Sea, with the maximum ice growth rate occurring along the coast due to cold air from northerly winds and ice motion away from the coast. South of St Lawrence Island, winds drive the model sea ice southwestward from the north to the southwestern part of the ice-covered region. Along the ice edge in the western Bering Sea, model sea ice is melted by warm ocean water, which is carried by the simulated Bering Slope Current flowing to the northwest, resulting in the S-shaped asymmetric ice edge. In spring and fall, similar thermodynamic and dynamic patterns occur in the model, but with typically smaller magnitudes and with season-specific geographical and directional differences.

ICESat Observations of Seasonal and Interannual Variations of Sea-Ice Freeboard and Estimated Thickness in the Weddell Sea, Antarctica (2003-2009)

NASA Technical Reports Server (NTRS)

Yi, Donghui; Robbins, John W.

2010-01-01

Sea-ice 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 ice, to estimate sea-ice thickness. Sea-ice freeboard and thickness distributions show clear seasonal variations that reflect the yearly cycle of growth and decay of the Weddell Sea (Antarctica) pack ice. During October-November, sea ice 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 ice melts away and the sea-ice 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 trends in sea-ice extent 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 trends are not statistically significant.

Satellite Data Sets in the Polar Regions

NASA Technical Reports Server (NTRS)

Comiso, Josefino C.; Busalacchi, Antonio J. (Technical Monitor)

2000-01-01

We have generated about two decades of consistently derived geophysical parameters in the polar regions. The key parameters are sea ice concentration, surface temperature, albedo, and cloud cover statistics. Sea ice concentrations were derived from the Scanning Multichannel Microwave Radiometer (SMMR) data and the Special Scanning Cl Microwave Imager (SSM/I) data from several platforms using the enhanced Bootstrap Algorithm for the period 1978 through 1999. The new algorithm reduces the errors associated with spatial and temporal variations in the emissivity and surface temperatures of sea ice. Also, bad data at ocean/land interfaces are identified and deleted in an unsupervised manner. Surface ice temperature, albedo and cloud cover statistics are derived simultaneously from the Advanced Very High Resolution Radiometer (AVHRR) data from 1981 through 1999 and mapped at a higher resolution but the same format as the ice concentration data. The technique makes use these co-registered ice concentration maps to enable cloud masking to be done separately for open ocean, sea ice and land areas. The effect of inversion is minimized by taking into consideration the expected changes in the effect of inversion with altitude, especially in the Antarctic. A technique for ice type regional classification has also been developed using multichannel cluster analysis and a neural network. This provide a means to identify large areas of thin ice, first year ice, and older ice types. The data sets have been shown to be coherent with each other and provide a powerful tool for in depth studies of the currently changing Arctic and Antarctic environment.

Statistical Analysis of SSMIS Sea Ice Concentration Threshold at the Arctic Sea Ice Edge during Summer Based on MODIS and Ship-Based Observational Data.

PubMed

Ji, Qing; Li, Fei; Pang, Xiaoping; Luo, Cong

2018-04-05

The threshold of sea ice concentration (SIC) is the basis for accurately calculating sea ice extent based on passive microwave (PM) remote sensing data. However, the PM SIC threshold at the sea ice edge used in previous studies and released sea ice 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 ice edge during summer in recent years, we extracted sea ice edge boundaries from the Moderate-resolution Imaging Spectroradiometer (MODIS) sea ice product (MOD29 with a spatial resolution of 1 km), MODIS images (250 m), and sea ice 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 ice edge based on ice-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 ice edge based on ice-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 ice edge pixels for the same days. The average SIC of 31% at the sea ice edge points extracted from ship-based observations also confirmed that choosing around 30% as the SIC threshold during summer is recommended for sea ice extent calculations based on SSMIS PM data. These results can provide a reference for further studying the variation of sea ice under the rapidly changing Arctic.

MODIS Snow and Ice Production

NASA Technical Reports Server (NTRS)

Hall, Dorthoy K.; Hoser, Paul (Technical Monitor)

2002-01-01

Daily, global snow cover maps, and sea ice cover and sea ice surface temperature (IST) maps are derived from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS), are available at no cost through the National Snow and Ice Data Center (NSIDC). Included on this CD-ROM are samples of the MODIS snow and ice products. In addition, an animation, done by the Scientific Visualization studio at Goddard Space Flight Center, is also included.

Sea ice-induced cold air advection as a mechanism controlling tundra primary productivity

NASA Astrophysics Data System (ADS)

Macias-Fauria, M.; Karlsen, S. R.

2015-12-01

The recent sharp decline in Arctic sea ice extent, concentration, and volume leaves urgent questions regarding its effects on ecological processes. Changes in tundra productivity have been associated with sea ice dynamics on the basis that most tundra ecosystems lay close to the sea. Although some studies have addressed the potential effect of sea ice 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 ice 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 ice (indirect/climate effect). We present a test on the direct/weather effect hypothesis: that is, tundra productivity is coupled with sea ice when sea ice 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 ice data at a spatial resolution of 232m for the period 2000-2014 (included), covering the Svalbard Archipelago. Our results suggest that sea ice-induced cold air advection is a likely mechanism to explain patterns of NDVI trends and heterogeneous spatial dynamics in the Svalbard archipelago. The mechanism offers the potential to explain sea ice/tundra productivity dynamics in other Arctic areas.

Effects of Mackenzie River Discharge and Bathymetry on Sea Ice in the Beaufort Sea

NASA Technical Reports Server (NTRS)

Nghiem, S. V.; Hall, D. K.; Rigor, I. G; Li, P.; Neumann, G.

2014-01-01

Mackenzie River discharge and bathymetry effects on sea ice in the Beaufort Sea are examined in 2012 when Arctic sea ice extent hit a record low. Satellite-derived sea surface temperature revealed warmer waters closer to river mouths. By 5 July 2012, Mackenzie warm waters occupied most of an open water area about 316,000 sq km. Surface temperature in a common open water area increased by 6.5 C between 14 June and 5 July 2012, before and after the river waters broke through a recurrent landfast ice barrier formed over the shallow seafloor offshore the Mackenzie Delta. In 2012, melting by warm river waters was especially effective when the strong Beaufort Gyre fragmented sea ice into unconsolidated floes. The Mackenzie and other large rivers can transport an enormous amount of heat across immense continental watersheds into the Arctic Ocean, constituting a stark contrast to the Antarctic that has no such rivers to affect sea ice.

Gypsum and hydrohalite dynamics in sea ice brines

NASA Astrophysics Data System (ADS)

Butler, Benjamin M.; Papadimitriou, Stathys; Day, Sarah J.; Kennedy, Hilary

2017-09-01

Mineral authigenesis from their dissolved sea salt matrix is an emergent feature of sea ice brines, fuelled by dramatic equilibrium solubility changes in the large sub-zero temperature range of this cryospheric system on the surface of high latitude oceans. The multi-electrolyte composition of seawater results in the potential for several minerals to precipitate in sea ice, each affecting the in-situ geochemical properties of the sea ice brine system, the habitat of sympagic biota. The solubility of two of these minerals, gypsum (CaSO4 ·2H2O) and hydrohalite (NaCl · 2H2O), was investigated in high ionic strength multi-electrolyte solutions at below-zero temperatures to examine their dissolution-precipitation dynamics in the sea ice brine system. The gypsum dynamics in sea ice were found to be highly dependent on the solubilities of mirabilite and hydrohalite between 0.2 and - 25.0 ° C. The hydrohalite solubility between - 14.3 and - 25.0 ° C exhibits a sharp change between undersaturated and supersaturated conditions, and, thus, distinct temperature fields of precipitation and dissolution in sea ice, with saturation occurring at - 22.9 ° C. The sharp changes in hydrohalite solubility at temperatures ⩽-22.9 °C result from the formation of an ice-hydrohalite aggregate, which alters the structural properties of brine inclusions in cold sea ice. Favourable conditions for gypsum precipitation in sea ice were determined to occur in the region of hydrohalite precipitation below - 22.9 ° C and in conditions of metastable mirabilite supersaturation above - 22.9 ° C (investigated at - 7.1 and - 8.2 ° C here) but gypsum is unlikely to persist once mirabilite forms at these warmer (>-22.9 °C) temperatures. The dynamics of hydrohalite in sea ice brines based on its experimental solubility were consistent with that derived from thermodynamic modelling (FREZCHEM code) but the gypsum dynamics derived from the code were inconsistent with that indicated by its experimental solubility in this system. Incorporation of hydrohalite solubility into a 1D thermodynamic model of the growth of first-year Arctic sea ice showed its precipitation to initiate once the incoming shortwave radiation dropped to 0 W m-2, and that it can reach concentrations of 9.9 g kg-1 within the upper and coldest layers of the ice pack. This suggests a limited effect of hydrohalite on the albedo of sea ice. The insights provided by the solubility measurements into the behaviour of gypsum and hydrohalite in the ice-brine system cannot be gleaned from field investigations at present.

The Algorithm Theoretical Basis Document for the Derivation of Range and Range Distributions from Laser Pulse Waveform Analysis for Surface Elevations, Roughness, Slope, and Vegetation Heights

NASA Technical Reports Server (NTRS)

Brenner, Anita C.; Zwally, H. Jay; Bentley, Charles R.; Csatho, Bea M.; Harding, David J.; Hofton, Michelle A.; Minster, Jean-Bernard; Roberts, LeeAnne; Saba, Jack L.; Thomas, Robert H.;

Variations in the Arctic's multiyear sea ice cover: A neural network analysis of SMMR-SSM/I data, 1979-2004

USGS Publications Warehouse

Belchansky, G.I.; Douglas, David C.; Eremeev, V.A.; Platonov, Nikita G.

2005-01-01

A 26-year (1979-2004) observational record of January multiyear sea ice distributions, derived from neural network analysis of SMMR-SSM/I passive microwave satellite data, reveals dense and persistent cover in the central Arctic basin surrounded by expansive regions of highly fluctuating interannual cover. Following a decade of quasi equilibrium, precipitous declines in multiyear ice area commenced in 1989 when the Arctic Oscillation shifted to a pronounced positive phase. Although extensive survival of first-year ice during autumn 1996 fully replenished the area of multiyear ice, a subsequent and accelerated decline returned the depletion to record lows. The most dramatic multiyear sea ice declines occurred in the East Siberian, Chukchi, and Beaufort Seas.

Analysis of sea ice dynamics

NASA Technical Reports Server (NTRS)

Zwally, J.

1988-01-01

The ongoing work has established the basis for using multiyear sea ice concentrations from SMMR passive microwave for studies of largescale advection and convergence/divergence of the Arctic sea ice pack. Comparisons were made with numerical model simulations and buoy data showing qualitative agreement on daily to interannual time scales. Analysis of the 7-year SMMR data set shows significant interannual variations in the total area of multiyear ice. The scientific objective is to investigate the dynamics, mass balance, and interannual variability of the Arctic sea ice pack. The research emphasizes the direct application of sea ice parameters derived from passive microwave data (SMMR and SSMI) and collaborative studies using a sea ice dynamics model. The possible causes of observed interannual variations in the multiyear ice area are being examined. The relative effects of variations in the large scale advection and convergence/divergence within the ice pack on a regional and seasonal basis are investigated. The effects of anomolous atmospheric forcings are being examined, including the long-lived effects of synoptic events and monthly variations in the mean geostrophic winds. Estimates to be made will include the amount of new ice production within the ice pack during winter and the amount of ice exported from the pack.

Characterizing Arctic sea ice topography and atmospheric form drag using high-resolution IceBridge data

NASA Astrophysics Data System (ADS)

Petty, A.; Tsamados, M.; Kurtz, N. T.; Farrell, S. L.; Newman, T.; Harbeck, J.; Feltham, D. L.; Richter-Menge, J.

2015-12-01

Here we present a detailed analysis of Arctic sea ice topography using high resolution, three-dimensional surface elevation data from the NASA Operation IceBridge Airborne Topographic Mapper (ATM) laser altimeter. We derive novel ice topography statistics from 2009-2014 across both first-year and multiyear ice regimes - including the height, area coverage, orientation and spacing of distinct surface features. The sea ice topography exhibits strong spatial variability, including increased surface feature (e.g. pressure ridge) height and area coverage within the multi-year ice regions. The ice topography also shows a strong coastal dependency, with the feature height and area coverage increasing as a function of proximity to the nearest coastline, especially north of Greenland and the Canadian Archipelago. The ice topography data have also been used to explicitly calculate atmospheric drag coefficients over Arctic sea ice; utilizing existing relationships regarding ridge geometry and their impact on form drag. The results are being used to calibrate the recent drag parameterization scheme included in the sea ice model CICE.

Responses of Baltic Sea Ice and Open-Water Natural Bacterial Communities to Salinity Change

PubMed Central

Kaartokallio, Hermanni; Laamanen, Maria; Sivonen, Kaarina

2005-01-01

To investigate the responses of Baltic Sea wintertime bacterial communities to changing salinity (5 to 26 practical salinity units), an experimental study was conducted. Bacterial communities of Baltic seawater and sea ice from a coastal site in southwest Finland were used in two batch culture experiments run for 17 or 18 days at 0°C. Bacterial abundance, cell volume, and leucine and thymidine incorporation were measured during the experiments. The bacterial community structure was assessed using denaturing gradient gel electrophoresis (DGGE) of PCR-amplified partial 16S rRNA genes with sequencing of DGGE bands from initial communities and communities of day 10 or 13 of the experiment. The sea ice-derived bacterial community was metabolically more active than the open-water community at the start of the experiment. Ice-derived bacterial communities were able to adapt to salinity change with smaller effects on physiology and community structure, whereas in the open-water bacterial communities, the bacterial cell volume evolution, bacterial abundance, and community structure responses indicated the presence of salinity stress. The closest relatives for all eight partial 16S rRNA gene sequences obtained were either organisms found in polar sea ice and other cold habitats or those found in summertime Baltic seawater. All sequences except one were associated with the α- and γ-proteobacteria or the Cytophaga-Flavobacterium-Bacteroides group. The overall physiological and community structure responses were parallel in ice-derived and open-water bacterial assemblages, which points to a linkage between community structure and physiology. These results support previous assumptions of the role of salinity fluctuation as a major selective factor shaping the sea ice bacterial community structure. PMID:16085826

Sea Ice Concentration Estimation Using Active and Passive Remote Sensing Data Fusion

NASA Astrophysics Data System (ADS)

Zhang, Y.; Li, F.; Zhang, S.; Zhu, T.

2017-12-01

In this abstract, a decision-level fusion method by utilizing SAR and passive microwave remote sensing data for sea ice concentration estimation is investigated. Sea ice concentration product from passive microwave concentration retrieval methods has large uncertainty within thin ice zone. Passive microwave data including SSM/I, AMSR-E, and AMSR-2 provide daily and long time series observations covering whole polar sea ice scene, and SAR images provide rich sea ice details with high spatial resolution including deformation and polarimetric features. In the proposed method, the merits from passive microwave data and SAR data are considered. Sea ice concentration products from ASI and sea ice category label derived from CRF framework in SAR imagery are calibrated under least distance protocol. For SAR imagery, incident angle and azimuth angle were used to correct backscattering values from slant range to ground range in order to improve geocoding accuracy. The posterior probability distribution between category label from SAR imagery and passive microwave sea ice concentration product is modeled and integrated under Bayesian network, where Gaussian statistical distribution from ASI sea ice concentration products serves as the prior term, which represented as an uncertainty of sea ice concentration. Empirical model based likelihood term is constructed under Bernoulli theory, which meets the non-negative and monotonically increasing conditions. In the posterior probability estimation procedure, final sea ice concentration is obtained using MAP criterion, which equals to minimize the cost function and it can be calculated with nonlinear iteration method. The proposed algorithm is tested on multiple satellite SAR data sets including GF-3, Sentinel-1A, RADARSAT-2 and Envisat ASAR. Results show that the proposed algorithm can improve the accuracy of ASI sea ice concentration products and reduce the uncertainty along the ice edge.

Rate and state dependent processes in sea ice deformation

NASA Astrophysics Data System (ADS)

Sammonds, P. R.; Scourfield, S.; Lishman, B.

2014-12-01

Realistic models of sea ice processes and properties are needed to assess sea ice thickness, extent and concentration and, when run within GCMs, provide prediction of climate change. The deformation of sea ice is a key control on the Arctic Ocean dynamics. But the deformation of sea ice is dependent not only on the rate of the processes involved but also the state of the sea ice and particular in terms of its evolution with time and temperature. Shear deformation is a dominant mechanism from the scale of basin-scale shear lineaments, through floe-floe interaction to block sliding in ice ridges. The shear deformation will not only depend on the speed of movement of ice surfaces but also the degree that the surfaces have bonded during thermal consolidation and compaction. Frictional resistance to sliding can vary by more than two orders of magnitude depending on the state of the interface. But this in turn is dependent upon both imposed conditions and sea ice properties such as size distribution of interfacial broken ice, angularity, porosity, salinity, etc. We review experimental results in sea ice mechanics from mid-scale experiments, conducted in the Hamburg model ship ice tank, simulating sea ice floe motion and interaction and compare these with laboratory experiments on ice friction done in direct shear from which a rate and state constitutive relation for shear deformation is derived. Finally we apply this to field measurement of sea ice friction made during experiments in the Barents Sea to assess the other environmental factors, the state terms, that need to be modelled in order to up-scale to Arctic Ocean-scale dynamics.

Deglacial and Holocene sea-ice variability north of Iceland and response to ocean circulation changes

NASA Astrophysics Data System (ADS)

Xiao, Xiaotong; Zhao, Meixun; Knudsen, Karen Luise; Sha, Longbin; Eiríksson, Jón; Gudmundsdóttir, Esther; Jiang, Hui; Guo, Zhigang

2017-08-01

Sea-ice conditions on the North Icelandic shelf constitute a key component for the study of the climatic gradients between the Arctic and the North Atlantic Oceans at the Polar Front between the cold East Icelandic Current delivering Polar surface water and the relatively warm Irminger Current derived from the North Atlantic Current. The variability of sea ice contributes to heat reduction (albedo) and gas exchange between the ocean and the atmosphere, and further affects the deep-water formation. However, lack of long-term and high-resolution sea-ice records in the region hinders the understanding of palaeoceanographic change mechanisms during the last glacial-interglacial cycle. Here, we present a sea-ice record back to 15 ka (cal. ka BP) based on the sea-ice biomarker IP25, phytoplankton biomarker brassicasterol and terrestrial biomarker long-chain n-alkanols in piston core MD99-2272 from the North Icelandic shelf. During the Bølling/Allerød (14.7-12.9 ka), the North Icelandic shelf was characterized by extensive spring sea-ice cover linked to reduced flow of warm Atlantic Water and dominant Polar water influence, as well as strong meltwater input in the area. This pattern showed an anti-phase relationship with the ice-free/less ice conditions in marginal areas of the eastern Nordic Seas, where the Atlantic Water inflow was strong, and contributed to an enhanced deep-water formation. Prolonged sea-ice cover with occasional occurrence of seasonal sea ice prevailed during the Younger Dryas (12.9-11.7 ka) interrupted by a brief interval of enhanced Irminger Current and deposition of the Vedde Ash, as opposed to abruptly increased sea-ice conditions in the eastern Nordic Seas. The seasonal sea ice decreased gradually from the Younger Dryas to the onset of the Holocene corresponding to increasing insolation. Ice-free conditions and sea surface warming were observed for the Early Holocene, followed by expansion of sea ice during the Mid-Holocene.

Phytoplankton in the Beaufort and Chukchi Seas: Distributions, Dynamics and Environmental Forcing

NASA Technical Reports Server (NTRS)

Wang, Jian; Cota, Glenn F.; Comiso, Josefino C.

2005-01-01

Time-series of remotely sensed distributions of phytoplankton, sea ice, surface temperature, albedo, and clouds were examined to evaluate the impact of the variability of environmental conditions and physical forcing on the phytoplankton distribution in the Beaufort and Chukchi Seas. Large-scale distributions of these parameters were studied for the first time using weekly and monthly composites from April 1998 through September 2002. The basic data set used in this study are phytoplankton pigment concentration derived from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), ice concentration obtained from the Special Sensor Microwave Imager (SSM/I) and surface temperature, cloud cover, and albedo derived from the Advanced Very High Resolution Radiometer (AVHRR). Seasonal variations of the sea ice cover was observed to be the dominant environmental factor as the ice edge blooms followed the retreating marginal ice zones northward. Blooms were most prominent in the southwestern Chukchi Sea, and were especially persistent immediately north of the Bering Strait in nutrient- rich Anadyr water and in some fronts. Chlorophyll concentrations are shown to increase from a nominal value during onset of melt in April to a maximum value in mid-spring or summer depending on location. Large interannual variability of ice cover and phytoplankton distributions was observed with the year 1998 being uniquely associated with an early season occurrence of a massive bloom. This is postulated to be caused in part by a rapid response of phytoplankton to an early retreat of the sea ice cover in the Beaufort Sea region. Correlation analyses showed relatively high negative correlation between chlorophyll and ice concentration with the correlation being highest in May, the correlation coefficient being -0.45. 1998 was also the warmest among the five years globally and the sea ice cover was least extensive in the Beaufort-Khukchi Sea region, partly because of the 1997-98 El Nino. Strong correlations were noted between ice extent and surface temperature, the correlation coefficient being highest at - 0.79 in April, during the onset of the bloom period

High interannual variability of sea ice thickness in the Arctic region.

PubMed

Laxon, Seymour; Peacock, Neil; Smith, Doug

2003-10-30

Possible future changes in Arctic sea ice cover and thickness, and consequent changes in the ice-albedo feedback, represent one of the largest uncertainties in the prediction of future temperature rise. Knowledge of the natural variability of sea ice thickness is therefore critical for its representation in global climate models. Numerical simulations suggest that Arctic ice thickness varies primarily on decadal timescales owing to changes in wind and ocean stresses on the ice, but observations have been unable to provide a synoptic view of sea ice thickness, which is required to validate the model results. Here we use an eight-year time-series of Arctic ice thickness, derived from satellite altimeter measurements of ice freeboard, to determine the mean thickness field and its variability from 65 degrees N to 81.5 degrees N. Our data reveal a high-frequency interannual variability in mean Arctic ice thickness that is dominated by changes in the amount of summer melt, rather than by changes in circulation. Our results suggest that a continued increase in melt season length would lead to further thinning of Arctic sea ice.

Trends in Sea Ice Cover, Sea Surface Temperature, and Chlorophyll Biomass Across a Marine Distributed Biological Observatory in the Pacific Arctic Region

NASA Astrophysics Data System (ADS)

Frey, K. E.; Grebmeier, J. M.; Cooper, L. W.; Wood, C.; Panday, P. K.

2011-12-01

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 ice-associated phytoplankton blooms occur throughout the region. Recent dramatic shifts in seasonal sea ice 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 ice 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 trends in sea ice 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, trends in sea ice 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 ice cover in the Chukchi Sea and Bering Strait region are due to both earlier sea ice breakup and later sea ice formation. Sea surface temperatures have also shown warming, where sites show significant warming particularly during August, September, and October. Satellite-derived chlorophyll-a concentrations over the past decade have shown trends seemingly in direct response to changing sea ice conditions, with increasing trends in chlorophyll-a concentrations when sea ice declines (and vice versa). In some cases, however, satellite-derived chlorophyll-a concentrations do not show expected changes with sea ice variability, indicating that limitations on biological productivity in this region are complex and spatially heterogeneous. An understanding of these spatial and temporal complexities impacting biological productivity is needed for the accurate prediction of how overall ecosystems may be altered with further expected warming sea surface temperatures and declines in sea ice cover.

Assessment of a demonstration project to supply near real-time sea ice information to end users

NASA Astrophysics Data System (ADS)

Blackford, C.; Howes, Sally; Whitelaw, Alan S.; Laxon, S.; Mantripp, D.

1994-12-01

Sea ice maps are required by a diverse range of users for scientific research and operational activities. Satellite remote sensing provides opportunities for monitoring and producing sea ice maps at a range of scales, in near real time. During March 1994 ESYS Limited and the University College London Mullard Space Science Laboratory (MSSL) operated a sea ice demonstration project to supply near real time sea ice maps in the southern ocean. The sea ice information was derived from a number of data sources: DMSP SSM/I data; ERS-1 SAR and Radar Altimeter fast delivery data; NOAA AVHRR data; and PoSAT-1 imagery. The maps were supplied to three users, two involved in yacht races in the southern ocean and a ship on an oceanographic research cruise in the waters of the Princess Elizabeth Trough region of Antarctica. The demonstration was successful, supplying the users with sea ice information which they had previously not received and combining data from various sources to produce sea ice maps. The demonstration also developed operational skills within ESYS and enabled the transfer of knowledge from MSSL to ESYS.

Sea ice type dynamics in the Arctic based on Sentinel-1 Data

NASA Astrophysics Data System (ADS)

Babiker, Mohamed; Korosov, Anton; Park, Jeong-Won

2017-04-01

Sea ice observation from satellites has been carried out for more than four decades and is one of the most important applications of EO data in operational monitoring as well as in climate change studies. Several sensors and retrieval methods have been developed and successfully utilized to measure sea ice area, concentration, drift, type, thickness, etc [e.g. Breivik et al., 2009]. Today operational sea ice monitoring and analysis is fully dependent on use of satellite data. However, new and improved satellite systems, such as multi-polarisation Synthetic Apperture Radar (SAR), require further studies to develop more advanced and automated sea ice monitoring methods. In addition, the unprecedented volume of data available from recently launched Sentinel missions provides both challenges and opportunities for studying sea ice dynamics. In this study we investigate sea ice type dynamics in the Fram strait based on Sentinel-1 A, B SAR data. Series of images for the winter season are classified into 4 ice types (young ice, first year ice, multiyear ice and leads) using the new algorithm developed by us for sea ice classification, which is based on segmentation, GLCM calculation, Haralick texture feature extraction, unsupervised and supervised classifications and Support Vector Machine (SVM) [Zakhvatkina et al., 2016; Korosov et al., 2016]. This algorithm is further improved by applying thermal and scalloping noise removal [Park et al. 2016]. Sea ice drift is retrieved from the same series of Sentinel-1 images using the newly developed algorithm based on combination of feature tracking and pattern matching [Mukenhuber et al., 2016]. Time series of these two products (sea ice type and sea ice drift) are combined in order to study sea ice deformation processes at small scales. Zones of sea ice convergence and divergence identified from sea ice drift are compared with ridges and leads identified from texture features. That allows more specific interpretation of SAR imagery and more accurate automatic classification. In addition, the map of four ice types calculated using the texture features from one SAR image is propagated forward using the sea ice drift vectors. The propagated ice type is compared with ice type derived from the next image. The comparison identifies changes in ice type which occurred during drift and allows to reduce uncertainties in sea ice type calculation.

Microbial response to different phytoplankton-derived dissolved organic matter sources in the Ross Sea, Antarctica

NASA Astrophysics Data System (ADS)

Sipler, R. E.; Spackeen, J.; McQuaid, J.; Bertrand, E. M.; Roberts, Q. N.; Baer, S. E.; Hutchins, D. A.; Allen, A. E.; Bronk, D. A.

2016-02-01

Western Antarctic shelves are highly productive regions that play an important role in global carbon and nitrogen cycles, specifically serving as a critical sink for carbon dioxide. Fixed carbon is stored within the phytoplankton cell as particulate organic matter or released into the surrounding water as dissolved organic matter (DOM). These phytoplankton-derived sources of organic matter support higher trophic levels as well as heterotrophic bacterial growth and respiration. The composition of the phytoplankton-derived organic matter is a function of the taxa as well as the environmental conditions under which it is produced. Phytoplankton community composition within western Antarctic Seas changes throughout Austral spring and summer with early production dominated by ice algae, switching to pelagic diatoms and flagellates later in the season. The goal of this study was to compare the response of Ross Sea microbial communities to DOM produced by ice algae or late season diatoms, specifically recent isolates of Pseudo nitzschia obtained from the Ross Sea. During 5-day bioassay studies, exudates from a natural ice algal community and from Pseudo nitzschia sp. isolates were added to natural microbial communities collected from two different Ross Sea locations, an ice-edge and an ice-covered site. The bacterial response to the DOM additions was greatest in the ice-covered community with a 5 and 3-fold higher bacterial abundance in the ice algae DOM and Pseudo nitzschia DOM treatments, respectively, relative to the control. The ice edge bacterial community responded similarly to both sources with a 2-fold increase in bacterial abundance compared to the control. Unlike the bacterial response, there was little difference in chlorophyll a concentrations between treatments, indicating that phytoplankton growth was not stimulated or inhibited by our additions.

Snow depth on Arctic and Antarctic sea ice derived from autonomous (Snow Buoy) measurements

NASA Astrophysics Data System (ADS)

Nicolaus, Marcel; Arndt, Stefanie; Hendricks, Stefan; Heygster, Georg; Huntemann, Marcus; Katlein, Christian; Langevin, Danielle; Rossmann, Leonard; Schwegmann, Sandra

2016-04-01

The snow cover on sea ice received more and more attention in recent sea ice studies and model simulations, because its physical properties dominate many sea ice and upper ocean processes. In particular; the temporal and spatial distribution of snow depth is of crucial importance for the energy and mass budgets of sea ice, as well as for the interaction with the atmosphere and the oceanic freshwater budget. Snow depth is also a crucial parameter for sea ice thickness retrieval algorithms from satellite altimetry data. Recent time series of Arctic sea ice volume only use monthly snow depth climatology, which cannot take into account annual changes of the snow depth and its properties. For Antarctic sea ice, no such climatology is available. With a few exceptions, snow depth on sea ice is determined from manual in-situ measurements with very limited coverage of space and time. Hence the need for more consistent observational data sets of snow depth on sea ice is frequently highlighted. Here, we present time series measurements of snow depths on Antarctic and Arctic sea ice, recorded by an innovative and affordable platform. This Snow Buoy is optimized to autonomously monitor the evolution of snow depth on sea ice and will allow new insights into its seasonality. In addition, the instruments report air temperature and atmospheric pressure directly into different international networks, e.g. the Global Telecommunication System (GTS) and the International Arctic Buoy Programme (IABP). We introduce the Snow Buoy concept together with technical specifications and results on data quality, reliability, and performance of the units. We highlight the findings from four buoys, which simultaneously drifted through the Weddell Sea for more than 1.5 years, revealing unique information on characteristic regional and seasonal differences. Finally, results from seven snow buoys co-deployed on Arctic sea ice throughout the winter season 2015/16 suggest the great importance of local effects, weather events, and potential influences of dynamic sea ice processes on snow accumulation.

The effects of mineral aerosol deposits on the BRDF (bidirectional reflectance distribution function) of sea ice for the calibration of satellite remote sensing products: an experimental and modelling study.

NASA Astrophysics Data System (ADS)

Lamare, Maxim; Hedley, John; King, Martin

2016-04-01

Knowledge of the albedo in the cryosphere is essential to monitor a range of climatic processes that have an impact on a global scale. Optical Earth Observation satellites are ideal for the synoptic observation of expansive and inaccessible areas, providing large datasets used to derive essential products, such as albedo. The application of remote sensing to investigate climate processes requires the combination of data from different sensors. However, although there is significant value in the analysis of data from individual sensors, global observing systems require accurate knowledge of sensor-to-sensor biases. Therefore, the inter-calibration of sensors used for climate studies is essential to avoid inconsistencies, which may mask climate effects. CEOS (Committee on Earth Observing Satellites) has established a number of natural Earth targets to serve as international reference standards, amongst which sea ice has great potential. The reflectance of natural surfaces is not isotropic and reflectance varies with the illumination and viewing geometries, consequently impacting satellite observations. Furthermore, variations in the physical properties (sea ice type, thickness) and the light absorbing impurities deposited in the sea ice have a strong impact on reflectance. Thus, the characterisation of the bi-directional reflectance distribution function (BRDF) of sea ice is a fundamental step toward the inter-calibration of optical satellite sensors. This study provides a characterisation of the effects of mineral aerosol and black carbon deposits on the BRDF of three different sea ice types. BRDF measurements were performed on bare sea ice grown in an experimental ice tank, using a state-of-the-art laboratory goniometer. The sea ice was "poisoned" with concentrations of mineral dust and black carbon varying between 100 and 5 000 ng g-1 deposited uniformly in a 5 cm surface layer. Using measurements from the experimental facility, novel information about sea ice BRDF as a function of sea ice type, thickness and light-absorbing impurities was derived using a radiative-transfer model (PlanarRad). This extensive characterisation of the multi angular reflectance of sea ice reveals the importance of BRDF for the validation and calibration of Earth Observation satellite sensor data.

Routine Mapping of the Snow Depth Distribution on Sea Ice

NASA Astrophysics Data System (ADS)

Farrell, S. L.; Newman, T.; Richter-Menge, J.; Dattler, M.; Paden, J. D.; Yan, S.; Li, J.; Leuschen, C.

2016-12-01

The annual growth and retreat of the polar sea ice cover is influenced by the seasonal accumulation, redistribution and melt of snow on sea ice. Due to its high albedo and low thermal conductivity, snow is also a controlling parameter in the mass and energy budgets of the polar climate system. Under a changing climate scenario it is critical to obtain reliable and routine measurements of snow depth, across basin scales, and long time periods, so as to understand regional, seasonal and inter-annual variability, and the subsequent impacts on the sea ice cover itself. Moreover the snow depth distribution remains a significant source of uncertainty in the derivation of sea ice thickness from remote sensing measurements, as well as in numerical model predictions of future climate state. Radar altimeter systems flown onboard NASA's Operation IceBridge (OIB) mission now provide annual measurements of snow across both the Arctic and Southern Ocean ice packs. We describe recent advances in the processing techniques used to interpret airborne radar waveforms and produce accurate and robust snow depth results. As a consequence of instrument effects and data quality issues associated with the initial release of the OIB airborne radar data, the entire data set was reprocessed to remove coherent noise and sidelobes in the radar echograms. These reprocessed data were released to the community in early 2016, and are available for improved derivation of snow depth. Here, using the reprocessed data, we present the results of seven years of radar measurements collected over Arctic sea ice at the end of winter, just prior to melt. Our analysis provides the snow depth distribution on both seasonal and multi-year sea ice. We present the inter-annual variability in snow depth for both the Central Arctic and the Beaufort/Chukchi Seas. We validate our results via comparison with temporally and spatially coincident in situ measurements gathered during many of the OIB surveys. The results will influence future sensor suite development for sea ice studies, and they provide a new metric for comparison with other sea ice observations. Integrating these novel snow depth observations with modeling studies will help inform model development, and advance our predictive capabilities to help better understand how sea ice is responding to a changing climate.

Uncertainty Quantification for Ice Sheet Science and Sea Level Projections

NASA Astrophysics Data System (ADS)

Boening, C.; Schlegel, N.; Limonadi, D.; Schodlok, M.; Seroussi, H. L.; Larour, E. Y.; Watkins, M. M.

2017-12-01

In order to better quantify uncertainties in global mean sea level rise projections and in particular upper bounds, we aim at systematically evaluating the contributions from ice sheets and potential for extreme sea level rise due to sudden ice mass loss. Here, we take advantage of established uncertainty quantification tools embedded within the Ice Sheet System Model (ISSM) as well as sensitivities to ice/ocean interactions using melt rates and melt potential derived from MITgcm/ECCO2. With the use of these tools, we conduct Monte-Carlo style sampling experiments on forward simulations of the Antarctic ice sheet, by varying internal parameters and boundary conditions of the system over both extreme and credible worst-case ranges. Uncertainty bounds for climate forcing are informed by CMIP5 ensemble precipitation and ice melt estimates for year 2100, and uncertainty bounds for ocean melt rates are derived from a suite of regional sensitivity experiments using MITgcm. Resulting statistics allow us to assess how regional uncertainty in various parameters affect model estimates of century-scale sea level rise projections. The results inform efforts to a) isolate the processes and inputs that are most responsible for determining ice sheet contribution to sea level; b) redefine uncertainty brackets for century-scale projections; and c) provide a prioritized list of measurements, along with quantitative information on spatial and temporal resolution, required for reducing uncertainty in future sea level rise projections. Results indicate that ice sheet mass loss is dependent on the spatial resolution of key boundary conditions - such as bedrock topography and melt rates at the ice-ocean interface. This work is performed at and supported by the California Institute of Technology's Jet Propulsion Laboratory. Supercomputing time is also supported through a contract with the National Aeronautics and Space Administration's Cryosphere program.

Arctic Ocean sea ice drift origin derived from artificial radionuclides.

PubMed

Cámara-Mor, P; Masqué, P; Garcia-Orellana, J; Cochran, J K; Mas, J L; Chamizo, E; Hanfland, C

2010-07-15

Since the 1950s, nuclear weapon testing and releases from the nuclear industry have introduced anthropogenic radionuclides into the sea, and in many instances their ultimate fate are the bottom sediments. The Arctic Ocean is one of the most polluted in this respect, because, in addition to global fallout, it is impacted by regional fallout from nuclear weapon testing, and indirectly by releases from nuclear reprocessing facilities and nuclear accidents. Sea-ice formed in the shallow continental shelves incorporate sediments with variable concentrations of anthropogenic radionuclides that are transported through the Arctic Ocean and are finally released in the melting areas. In this work, we present the results of anthropogenic radionuclide analyses of sea-ice sediments (SIS) collected on five cruises from different Arctic regions and combine them with a database including prior measurements of these radionuclides in SIS. The distribution of (137)Cs and (239,240)Pu activities and the (240)Pu/(239)Pu atom ratio in SIS showed geographical differences, in agreement with the two main sea ice drift patterns derived from the mean field of sea-ice motion, the Transpolar Drift and Beaufort Gyre, with the Fram Strait as the main ablation area. A direct comparison of data measured in SIS samples against those reported for the potential source regions permits identification of the regions from which sea ice incorporates sediments. The (240)Pu/(239)Pu atom ratio in SIS may be used to discern the origin of sea ice from the Kara-Laptev Sea and the Alaskan shelf. However, if the (240)Pu/(239)Pu atom ratio is similar to global fallout, it does not provide a unique diagnostic indicator of the source area, and in such cases, the source of SIS can be constrained with a combination of the (137)Cs and (239,240)Pu activities. Therefore, these anthropogenic radionuclides can be used in many instances to determine the geographical source area of sea-ice. Copyright 2010 Elsevier B.V. All rights reserved.

A Decade of High-Resolution Arctic Sea Ice Measurements from Airborne Altimetry

NASA Astrophysics Data System (ADS)

Duncan, K.; Farrell, S. L.; Connor, L. N.; Jackson, C.; Richter-Menge, J.

2017-12-01

Satellite altimeters carried on board ERS-1,-2, EnviSat, ICESat, CryoSat-2, AltiKa and Sentinel-3 have transformed our ability to map the thickness and volume of the polar sea ice cover, on seasonal and decadal time-scales. The era of polar satellite altimetry has coincided with a rapid decline of the Arctic ice cover, which has thinned, and transitioned from a predominantly multi-year to first-year ice cover. In conjunction with basin-scale satellite altimeter observations, airborne surveys of the Arctic Ocean at the end of winter are now routine. These surveys have been targeted to monitor regions of rapid change, and are designed to obtain the full snow and ice thickness distribution, across a range of ice types. Sensors routinely deployed as part of NASA's Operation IceBridge (OIB) campaigns include the Airborne Topographic Mapper (ATM) laser altimeter, the frequency-modulated continuous-wave snow radar, and the Digital Mapping System (DMS). Airborne measurements yield high-resolution data products and thus present a unique opportunity to assess the quality and characteristics of the satellite observations. We present a suite of sea ice data products that describe the snow depth and thickness of the Arctic ice cover during the last decade. Fields were derived from OIB measurements collected between 2009-2017, and from reprocessed data collected during ad-hoc sea ice campaigns prior to OIB. Our bespoke algorithms are designed to accommodate the heterogeneous sea ice surface topography, that varies at short spatial scales. We assess regional and inter-annual variability in the sea ice thickness distribution. Results are compared to satellite-derived ice thickness fields to highlight the sensitivities of satellite footprints to the tails of the thickness distribution. We also show changes in the dynamic forcing shaping the ice pack over the last eight years through an analysis of pressure-ridge sail-height distributions and surface roughness conditions. Variability is linked to the geographic location and extent of multi-year sea ice. Finally, we describe accessing our high-resolution data products at the NOAA Laboratory for Satellite Altimetry.

Sea Ice Mass Reconciliation Exercise (SIMRE) for altimetry derived sea ice thickness data sets

NASA Astrophysics Data System (ADS)

Hendricks, S.; Haas, C.; Tsamados, M.; Kwok, R.; Kurtz, N. T.; Rinne, E. J.; Uotila, P.; Stroeve, J.

2017-12-01

Satellite altimetry is the primary remote sensing data source for retrieval of Arctic sea-ice thickness. Observational data sets are available from current and previous missions, namely ESA's Envisat and CryoSat as well as NASA ICESat. In addition, freeboard results have been published from the earlier ESA ERS missions and candidates for new data products are the Sentinel-3 constellation, the CNES AltiKa mission and NASA laser altimeter successor ICESat-2. With all the different aspects of sensor type and orbit configuration, all missions have unique properties. In addition, thickness retrieval algorithms have evolved over time and data centers have developed different strategies. These strategies may vary in choice of auxiliary data sets, algorithm parts and product resolution and masking. The Sea Ice Mass Reconciliation Exercise (SIMRE) is a project by the sea-ice radar altimetry community to bridge the challenges of comparing data sets across missions and algorithms. The ESA Arctic+ research program facilitates this project with the objective to collect existing data sets and to derive a reconciled estimate of Arctic sea ice mass balance. Starting with CryoSat-2 products, we compare results from different data centers (UCL, AWI, NASA JPL & NASA GSFC) at full resolution along selected orbits with independent ice thickness estimates. Three regions representative of first-year ice, multiyear ice and mixed ice conditions are used to compare the difference in thickness and thickness change between products over the seasonal cycle. We present first results and provide an outline for the further development of SIMRE activities. The methodology for comparing data sets is designed to be extendible and the project is open to contributions by interested groups. Model results of sea ice thickness will be added in a later phase of the project to extend the scope of SIMRE beyond EO products.

Arctic sea ice signatures: L-band brightness temperature sensitivity comparison using two radiation transfer models

NASA Astrophysics Data System (ADS)

Richter, Friedrich; Drusch, Matthias; Kaleschke, Lars; Maaß, Nina; Tian-Kunze, Xiangshan; Mecklenburg, Susanne

2018-03-01

Sea ice is a crucial component for short-, medium- and long-term numerical weather predictions. Most importantly, changes of sea ice coverage and areas covered by thin sea ice have a large impact on heat fluxes between the ocean and the atmosphere. L-band brightness temperatures from ESA's Earth Explorer SMOS (Soil Moisture and Ocean Salinity) have been proven to be a valuable tool to derive thin sea ice thickness. These retrieved estimates were already successfully assimilated in forecasting models to constrain the ice analysis, leading to more accurate initial conditions and subsequently more accurate forecasts. However, the brightness temperature measurements can potentially be assimilated directly in forecasting systems, reducing the data latency and providing a more consistent first guess. As a first step towards such a data assimilation system we studied the forward operator that translates geophysical parameters provided by a model into brightness temperatures. We use two different radiative transfer models to generate top of atmosphere brightness temperatures based on ORAP5 model output for the 2012/2013 winter season. The simulations are then compared against actual SMOS measurements. The results indicate that both models are able to capture the general variability of measured brightness temperatures over sea ice. The simulated brightness temperatures are dominated by sea ice coverage and thickness changes are most pronounced in the marginal ice zone where new sea ice is formed. There we observe the largest differences of more than 20 K over sea ice between simulated and observed brightness temperatures. We conclude that the assimilation of SMOS brightness temperatures yields high potential for forecasting models to correct for uncertainties in thin sea ice areas and suggest that information on sea ice fractional coverage from higher-frequency brightness temperatures should be used simultaneously.

Local Effects of Ice Floes on Skin Sea Surface Temperature in the Marginal Ice Zone from UAVs

NASA Astrophysics Data System (ADS)

Zappa, C. J.; Brown, S.; Emery, W. J.; Adler, J.; Wick, G. A.; Steele, M.; Palo, S. E.; Walker, G.; Maslanik, J. A.

2013-12-01

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 ice extent, and loss of ice in areas that had been ice-covered throughout human memory. Even the oldest and thickest ice 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 ice zones (MIZ), or areas where the "ice-albedo feedback" driven by solar warming is highest and ice melt is extensive, may provide insights into the extent of these changes. Airborne remote sensing, in particular InfraRed (IR), offers a unique opportunity to observe physical processes at sea-ice margins. It permits monitoring the ice extent and coverage, as well as the ice and ocean temperature variability. It can also be used for derivation of surface flow field allowing investigation of turbulence and mixing at the ice-ocean interface. Here, we present measurements of visible and IR imagery of melting ice floes in the marginal ice zone north of Oliktok Point AK in the Beaufort Sea made during the Marginal Ice Zone Ocean and Ice 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 ice 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 ice 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 ice floe shows the coldest skin SST, and downstream the skin SST is mixed within the turbulent wake over 10s of meters. We compare the structure of circulation and mixing of the influx of cold skin SST driven by surface currents and wind. In-situ temperature measurements provide the context for the vertical structure of the mixing and its impact on the skin SST. Furthermore, comparisons to satellite-derived sea surface temperature of the region are presented. The accuracy of satellite derived SST products and how well the observed skin SSTs represent ocean bulk temperatures in polar regions is not well understood, due in part to lack of observations. Estimated error in the polar seas is relatively high at up to 0.4 deg. C compared to less than 0.2 deg. C for other areas. The goal of these and future analyses of the MIZOPEX data set is to elucidate a basic question that is significant for the entire Earth system. Have these regions passed a tipping point, such that they are now essentially acting as sub-Arctic seas where ice disappears in summer, or instead whether the changes are transient, with the potential for the ice pack to recover?

Sea Ice Biogeochemistry: A Guide for Modellers

PubMed Central

Tedesco, Letizia; Vichi, Marcello

2014-01-01

Sea ice is a fundamental component of the climate system and plays a key role in polar trophic food webs. Nonetheless sea ice biogeochemical dynamics at large temporal and spatial scales are still rarely described. Numerical models may potentially contribute integrating among sparse observations, but available models of sea ice biogeochemistry are still scarce, whether their relevance for properly describing the current and future state of the polar oceans has been recently addressed. A general methodology to develop a sea ice biogeochemical model is presented, deriving it from an existing validated model application by extension of generic pelagic biogeochemistry model parameterizations. The described methodology is flexible and considers different levels of ecosystem complexity and vertical representation, while adopting a strategy of coupling that ensures mass conservation. We show how to apply this methodology step by step by building an intermediate complexity model from a published realistic application and applying it to analyze theoretically a typical season of first-year sea ice in the Arctic, the one currently needing the most urgent understanding. The aim is to (1) introduce sea ice biogeochemistry and address its relevance to ocean modelers of polar regions, supporting them in adding a new sea ice component to their modelling framework for a more adequate representation of the sea ice-covered ocean ecosystem as a whole, and (2) extend our knowledge on the relevant controlling factors of sea ice algal production, showing that beyond the light and nutrient availability, the duration of the sea ice season may play a key-role shaping the algal production during the on going and upcoming projected changes. PMID:24586604

A Decade of Arctic Sea Ice Thickness Change from Airborne and Satellite Altimetry (Invited)

NASA Astrophysics Data System (ADS)

Farrell, S. L.; Richter-Menge, J.; Kurtz, N. T.; McAdoo, D. C.; Newman, T.; Zwally, H.; Ruth, J.

2013-12-01

Altimeters on both airborne and satellite platforms provide direct measurements of sea ice freeboard from which sea ice thickness may be calculated. Satellite altimetry observations of Arctic sea ice from ICESat and CryoSat-2 indicate a significant decline in ice thickness, and volume, over the last decade. During this time the ice pack has experienced a rapid change in its composition, transitioning from predominantly thick, multi-year ice to thinner, increasingly seasonal ice. We will discuss the regional trends in ice thickness derived from ICESat and IceBridge altimetry between 2003 and 2013, contrasting observations of the multi-year ice pack with seasonal ice 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 IceBridge airborne mission, which commenced operations in 2009. We describe our current efforts to more accurately convert from freeboard to ice thickness, with a modified methodology that corrects for range errors, instrument biases, and includes an enhanced treatment of snow depth, with respect to ice type. With the planned launch by NASA of ICESat-2 in 2016 we can expect continuity of the sea ice 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 trends and inter-annual variability in the Arctic sea ice thickness record. We briefly present the status of planned ICESat-2 sea ice data products, and demonstrate the utility of micro-pulse, photon-counting laser altimetry over sea ice.

Active and Passive Microwave Determination of the Circulation and Characteristics of Weddell and Ross Sea Ice

NASA Technical Reports Server (NTRS)

Drinkwater, Mark R.; Liu, Xiang

2000-01-01

A combination of satellite microwave data sets are used in conjunction with ECMWF (Medium Range Weather Forecasts) and NCEP (National Center for Environment Prediction) meteorological analysis fields to investigate seasonal variability in the circulation and sea-ice dynamics of the Weddell and Ross Seas. Results of sea-ice tracking using SSM/I (Special Sensor Microwave Imager), Scatterometer and SAR images are combined with in-situ data derived from Argos buoys and GPS drifters to validate observed drift patterns. Seasonal 3-month climatologies of ice motion and drift speed variance illustrate the response of the sea-ice system to seasonal forcing. A melt-detection algorithm is used to track the onset of seasonal melt, and to determine the extent and duration of atmospherically-led surface melting during austral summer. Results show that wind-driven drift regulates the seasonal distribution and characteristics of sea-ice and the intensity of the cyclonic Gyre circulation in these two regions.

Evidence for a substantial West Antarctic ice sheet contribution to meltwater pulses and abrupt global sea level rise

NASA Astrophysics Data System (ADS)

Fogwill, C. J.; Turney, C. S.; Golledge, N. R.; Etheridge, D. M.; Rubino, M.; Thornton, D.; Woodward, J.; Winter, K.; van Ommen, T. D.; Moy, A. D.; Curran, M. A.; Rootes, C.; Rivera, A.; Millman, H.

2015-12-01

During the last deglaciation (21,000 to 7,000years ago) global sea level rise was punctuated by several abrupt meltwater spikes triggered by the retreat of ice sheets and glaciers world-wide. However, the debate regarding the relative timing, geographical source and the physical mechanisms driving these rapid increases in sea level has catalyzed debate critical to predicting future sea level rise and climate. Here we present a unique record of West Antarctic Ice Sheet elevation change derived from the Patriot Hills blue ice area, located close to the modern day grounding line of the Institute Ice Stream in the Weddell Sea Embayment. Combined isotopic signatures and gas volume analysis from the ice allows us to develop a record of local ice sheet palaeo-altitude that is assessed against independent regional high-resolution ice sheet modeling studies, allowing us to demonstrate that past ice sheet elevations across this sector of the WSE were considerably higher than those suggested by current terrestrial reconstructions. We argue that ice in the WSE had a significant influence on both pre and post LGM sea level rise including MWP-1A (~14.6 ka) and during MWP-1B (11.7-11.6 ka), reconciling past sea level rise and demonstrating for the first time that this sector of the WAIS made a significant and direct contribution to post LGM sea level rise.

Incorrect Match Detection Method for Arctic Sea-Ice Reconstruction Using Uav Images

NASA Astrophysics Data System (ADS)

Kim, J.-I.; Kim, H.-C.

2018-05-01

Shapes and surface roughness, which are considered as key indicators in understanding Arctic sea-ice, can be measured from the digital surface model (DSM) of the target area. Unmanned aerial vehicle (UAV) flying at low altitudes enables theoretically accurate DSM generation. However, the characteristics of sea-ice with textureless surface and incessant motion make image matching difficult for DSM generation. In this paper, we propose a method for effectively detecting incorrect matches before correcting a sea-ice DSM derived from UAV images. The proposed method variably adjusts the size of search window to analyze the matching results of DSM generated and distinguishes incorrect matches. Experimental results showed that the sea-ice DSM produced large errors along the textureless surfaces, and that the incorrect matches could be effectively detected by the proposed method.

Trends in Arctic Sea Ice Volume 2010-2013 from CryoSat-2

NASA Astrophysics Data System (ADS)

Tilling, R.; Ridout, A.; Wingham, D.; Shepherd, A.; Haas, C.; Farrell, S. L.; Schweiger, A. J.; Zhang, J.; Giles, K.; Laxon, S.

2013-12-01

Satellite records show a decline in Arctic sea ice extent over the past three decades with a record minimum in September 2012, and results from the Pan-Arctic Ice-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 trends in Arctic sea ice volume between 2010 and 2013. The CS-2 estimates of sea ice thickness agree with in situ estimates derived from upward looking sonar measurements of ice draught and airborne measurements of ice thickness and freeboard to within 0.1 metres. Prior to the record minimum in summer 2012, autumn and winter Arctic sea ice 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 ice volume has decreased by ~700 km3/yr since 2010, approximately twice the average rate since 1980 as predicted by the PIOMAS.

Advances in Airborne Altimetric Techniques for the Measurement of Snow on Arctic Sea Ice

NASA Astrophysics Data System (ADS)

Newman, T.; Farrell, S. L.; Richter-Menge, J.; Elder, B. C.; Ruth, J.; Connor, L. N.

2014-12-01

Current sea ice observations and models indicate a transition towards a more seasonal Arctic ice pack with a smaller, and geographically more variable, multiyear ice component. To gain a comprehensive understanding of the processes governing this transition it is important to include the impact of the snow cover, determining the mechanisms by which snow is both responding to and forcing changes to the sea ice pack. Data from NASA's Operation IceBridge (OIB) snow radar system, which has been making yearly surveys of the western Arctic since 2009, offers a key resource for investigating the snow cover. In this work, we characterize the OIB snow radar instrument response to ascertain the location of 'side-lobes', aiding the interpretation of snow radar data. We apply novel wavelet-based techniques to identify the primary reflecting interfaces within the snow pack from which snow depth estimates are derived. We apply these techniques to the range of available snow radar data collected over the last 6 years during the NASA OIB mission. Our results are validated through comparison with a range of in-situ data. We discuss the impact of sea ice surface morphology on snow radar returns (with respect to ice type) and the topographic conditions over which accurate snow-radar-derived snow depths may be obtained. Finally we present improvements to in situ survey design that will allow for both an improved sampling of the snow radar footprint and more accurate assessment of the uncertainties in radar-derived snow depths in the future.

Evaluation of Arctic Sea Ice Thickness Simulated by Arctic Ocean Model Intercomparison Project Models

NASA Technical Reports Server (NTRS)

Johnson, Mark; Proshuntinsky, Andrew; Aksenov, Yevgeny; Nguyen, An T.; Lindsay, Ron; Haas, Christian; Zhang, Jinlun; Diansky, Nikolay; Kwok, Ron; Maslowski, Wieslaw;

Complementary biomarker-based methods for characterising Arctic sea ice conditions: A case study comparison between multivariate analysis and the PIP25 index

NASA Astrophysics Data System (ADS)

Köseoğlu, Denizcan; Belt, Simon T.; Smik, Lukas; Yao, Haoyi; Panieri, Giuliana; Knies, Jochen

2018-02-01

The discovery of IP25 as a qualitative biomarker proxy for Arctic sea ice and subsequent introduction of the so-called PIP25 index for semi-quantitative descriptions of sea ice conditions has significantly advanced our understanding of long-term paleo Arctic sea ice conditions over the past decade. We investigated the potential for classification tree (CT) models to provide a further approach to paleo Arctic sea ice reconstruction through analysis of a suite of highly branched isoprenoid (HBI) biomarkers in ca. 200 surface sediments from the Barents Sea. Four CT models constructed using different HBI assemblages revealed IP25 and an HBI triene as the most appropriate classifiers of sea ice conditions, achieving a >90% cross-validated classification rate. Additionally, lower model performance for locations in the Marginal Ice Zone (MIZ) highlighted difficulties in characterisation of this climatically-sensitive region. CT model classification and semi-quantitative PIP25-derived estimates of spring sea ice concentration (SpSIC) for four downcore records from the region were consistent, although agreement between proxy and satellite/observational records was weaker for a core from the west Svalbard margin, likely due to the highly variable sea ice conditions. The automatic selection of appropriate biomarkers for description of sea ice conditions, quantitative model assessment, and insensitivity to the c-factor used in the calculation of the PIP25 index are key attributes of the CT approach, and we provide an initial comparative assessment between these potentially complementary methods. The CT model should be capable of generating longer-term temporal shifts in sea ice conditions for the climatically sensitive Barents Sea.

Variability and Trends in the Arctic Sea Ice Cover: Results from Different Techniques

NASA Technical Reports Server (NTRS)

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

2017-01-01

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 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. 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.

Temporal variatiions of Sea ice cover in the Baltic Sea derived from operational sea ice products used in NWP.

NASA Astrophysics Data System (ADS)

Lange, Martin; Paul, Gerhard; Potthast, Roland

2014-05-01

Sea ice cover is a crucial parameter for surface fluxes of heat and moisture over water areas. The isolating effect and the much higher albedo strongly reduces the turbulent exchange of heat and moisture from the surface to the atmosphere and allows for cold and dry air mass flow with strong impact on the stability of the whole boundary layer and consequently cloud formation as well as precipitation in the downstream regions. Numerical weather centers as, ECMWF, MetoFrance or DWD use external products to initialize SST and sea ice cover in their NWP models. To the knowledge of the author there are mainly two global sea ice products well established with operational availability, one from NOAA NCEP that combines measurements with satellite data, and the other from OSI-SAF derived from SSMI/S sensors. The latter one is used in the Ostia product. DWD additionally uses a regional product for the Baltic Sea provided by the national center for shipping and hydrografie which combines observations from ships (and icebreakers) for the German part of the Baltic Sea and model analysis from the hydrodynamic HIROMB model of the Swedish meteorological service for the rest of the domain. The temporal evolution of the three different products are compared for a cold period in Februar 2012. Goods and bads will be presented and suggestions for a harmonization of strong day to day jumps over large areas are suggested.

Critical Mechanisms for the Formation of Extreme Arctic Sea-Ice Extent in the Summers of 2007 and 1996

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, Xiquan; Zib, Benjamin J.; Xi, Baike

A warming Arctic climate is undergoing significant e 21 nvironmental change, most evidenced by the reduction of Arctic sea-ice extent during the summer. In this study, we examine two extreme anomalies of September sea-ice extent 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-ice variation in 2007 and 1996 using both satellite-derived sea-ice 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-ice extentmore » from year-to-year and defined here as the Area Of Focus (AOF). The record low September sea-ice extent 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-ice extent. Through this study, we hypothesize the following positive feedbacks of clouds, water vapor, radiation and atmospheric variables on the sea-ice retreat during the summer 2007. The record low sea-ice extent 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-ice melt across the AOF, but also increasing clouds. The positive cloud feedback results in higher SAT and more sea-ice 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-ice retreat during the summer 2007.« less

Sea Ice Kinematics and Thickness from RGPS: Observations and Theory

NASA Technical Reports Server (NTRS)

Stern, Harry; Lindsay, Ron; Yu, Yan-Ling; Moritz, Richard; Rothrock, Drew

2005-01-01

The RADARSAT Geophysical Processor System (RGPS) has produced a wealth of data on Arctic sea ice motion, deformation, and thickness with broad geographical coverage and good temporal resolution. These data provide unprecedented spatial detail of the structure and evolution of the sea ice cover. The broad purpose of this study was to take advantage of the strengths of the RGPS data set to investigate sea ice kinematics and thickness, which affect the climate through their influence on ice production, ridging, and transport (i.e. mass balance); heat flux to the atmosphere; and structure of the upper ocean mixed layer. The objectives of this study were to: (1) Explain the relationship between the discontinuous motion of the ice cover and the large-scale, smooth wind field that drives the ice; (2) Characterize the sea ice deformation in the Arctic at different temporal and spatial scales, and compare it with deformation predicted by a state-of-theart ice/ocean model; and (3) Compare RGPS-derived sea ice thickness with other data, and investigate the thinning of the Arctic sea ice cover as seen in ULS data obtained by U.S. Navy submarines. We briefly review the results of our work below, separated into the topics of sea ice deformation and sea ice thickness. This is followed by a list of publications, meetings and presentations, and other activities supported under this grant. We are attaching to this report copies of all the listed publications. Finally, we would like to point out our community service to NASA through our involvement with the ASF User Working Group and the RGPS Science Working Group, as evidenced in the list of meetings and presentations below.

Bacterial community dynamics and activity in relation to dissolved organic matter availability during sea-ice formation in a mesocosm experiment.

PubMed

Eronen-Rasimus, Eeva; Kaartokallio, Hermanni; Lyra, Christina; Autio, Riitta; Kuosa, Harri; Dieckmann, Gerhard S; Thomas, David N

2014-02-01

The structure of sea-ice bacterial communities is frequently different from that in seawater. Bacterial entrainment in sea ice has been studied with traditional microbiological, bacterial abundance, and bacterial production methods. However, the dynamics of the changes in bacterial communities during the transition from open water to frozen sea ice is largely unknown. Given previous evidence that the nutritional status of the parent water may affect bacterial communities during ice formation, bacterial succession was studied in under ice water and sea ice in two series of mesocosms: the first containing seawater from the North Sea and the second containing seawater enriched with algal-derived dissolved organic matter (DOM). The composition and dynamics of bacterial communities were investigated with terminal restriction fragment length polymorphism (T-RFLP), and cloning alongside bacterial production (thymidine and leucine uptake) and abundance measurements (measured by flow cytometry). Enriched and active sea-ice bacterial communities developed in ice formed in both unenriched and DOM-enriched seawater (0-6 days). γ-Proteobacteria dominated in the DOM-enriched samples, indicative of their capability for opportunistic growth in sea ice. The bacterial communities in the unenriched waters and ice consisted of the classes Flavobacteria, α- and γ-Proteobacteria, which are frequently found in natural sea ice in polar regions. Furthermore, the results indicate that seawater bacterial communities are able to adapt rapidly to sudden environmental changes when facing considerable physicochemical stress such as the changes in temperature, salinity, nutrient status, and organic matter supply during ice formation. © 2014 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Brine Convection, Temperature Fluctuations, and Permeability in Winter Antarctic Land-Fast Sea Ice

NASA Astrophysics Data System (ADS)

Wongpan, P.; Hughes, K. G.; Langhorne, P. J.; Smith, I. J.

2018-01-01

Vertical temperature strings are used in sea ice research to study heat flow, ice growth rate, and ocean-ice-atmosphere interaction. We demonstrate the feasibility of using temperature fluctuations as a proxy for fluid movement, a key process for supplying nutrients to Antarctic sea ice algal communities. Four strings were deployed in growing, land-fast sea ice in McMurdo Sound, Antarctica. By smoothing temperature data with the robust LOESS method, we obtain temperature fluctuations that cannot be explained by insolation or atmospheric heat loss. Statistical distributions of these temperature fluctuations are investigated with sensitivities to the distance from the ice-ocean interface, average ice temperature, and sea ice structure. Fluctuations are greatest close to the base (<50 mm) at temperatures >-3°C, and are discrete events with an average active period of 43% compared to 11% when the ice is colder (-3°C to -5°C). Assuming fluctuations occur when the Rayleigh number, derived from mushy layer theory, exceeds a critical value of 10 we approximate the harmonic mean permeability of this thick (>1 m) sea ice in terms of distance from the ice-ocean interface. Near the base, we obtain values in the same range as those measured by others in Arctic spring and summer. The permeability between the ice-ocean interface and 0.05 ± 0.04 m above it is of order 10-9 m2. Columnar and incorporated platelet ice permeability distributions in the bottom 0.1 m of winter Antarctic sea ice are statistically significantly different although their arithmetic means are indistinguishable.

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 record of temperature increases. Still, although the patterns of the temperature and ice changes match fairly well, there is a substantial ways to go before these patterns are understood (and can be modeled) in the full context of global change.

About uncertainties in sea ice thickness retrieval from satellite radar altimetry: results from the ESA-CCI Sea Ice ECV Project Round Robin Exercise

NASA Astrophysics Data System (ADS)

Kern, S.; Khvorostovsky, K.; Skourup, H.; Rinne, E.; Parsakhoo, Z. S.; Djepa, V.; Wadhams, P.; Sandven, S.

2014-03-01

One goal of the European Space Agency Climate Change Initiative sea ice Essential Climate Variable project is to provide a quality controlled 20 year long data set of Arctic Ocean winter-time sea ice thickness distribution. An important step to achieve this goal is to assess the accuracy of sea ice thickness retrieval based on satellite radar altimetry. For this purpose a data base is created comprising sea ice freeboard derived from satellite radar altimetry between 1993 and 2012 and collocated observations of snow and sea ice freeboard from Operation Ice Bridge (OIB) and CryoSat Validation Experiment (CryoVEx) air-borne campaigns, of sea ice draft from moored and submarine Upward Looking Sonar (ULS), and of snow depth from OIB campaigns, Advanced Microwave Scanning Radiometer aboard EOS (AMSR-E) and the Warren Climatology (Warren et al., 1999). An inter-comparison of the snow depth data sets stresses the limited usefulness of Warren climatology snow depth for freeboard-to-thickness conversion under current Arctic Ocean conditions reported in other studies. This is confirmed by a comparison of snow freeboard measured during OIB and CryoVEx and snow freeboard computed from radar altimetry. For first-year ice the agreement between OIB and AMSR-E snow depth within 0.02 m suggests AMSR-E snow depth as an appropriate alternative. Different freeboard-to-thickness and freeboard-to-draft conversion approaches are realized. The mean observed ULS sea ice draft agrees with the mean sea ice draft computed from radar altimetry within the uncertainty bounds of the data sets involved. However, none of the realized approaches is able to reproduce the seasonal cycle in sea ice draft observed by moored ULS satisfactorily. A sensitivity analysis of the freeboard-to-thickness conversion suggests: in order to obtain sea ice thickness as accurate as 0.5 m from radar altimetry, besides a freeboard estimate with centimetre accuracy, an ice-type dependent sea ice density is as mandatory as a snow depth with centimetre accuracy.

NASA Sea Ice and Snow Validation Program for the DMSP SSM/I: NASA DC-8 flight report

NASA Technical Reports Server (NTRS)

Cavalieri, D. J.

1988-01-01

In June 1987 a new microwave sensor called the Special Sensor Microwave Imager (SSM/I) was launched as part of the Defense Meteorological Satellite Program (DMSP). In recognition of the importance of this sensor to the polar research community, NASA developed a program to acquire the data, to convert the data into sea ice parameters, and finally to validate and archive both the SSM/I radiances and the derived sea ice parameters. Central to NASA's sea ice validation program was a series of SSM/I aircraft underflights with the NASA DC-8 airborne Laboratory. The mission (the Arctic '88 Sea Ice Mission) was completed in March 1988. This report summarizes the mission and includes a summary of aircraft instrumentation, coordination with participating Navy aircraft, flight objectives, flight plans, data collected, SSM/I orbits for each day during the mission, and lists several piggyback experiments supported during this mission.

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).

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)).

Estimation of Arctic Sea Ice Freeboard and Thickness Using CryoSat-2

NASA Astrophysics Data System (ADS)

Lee, Sanggyun; Im, Jungho; yoon, Hyeonjin; Shin, Minso; Kim, Miae

2014-05-01

Arctic sea ice 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 ice extent 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 ice thickness has also been diminishing along with the decreasing sea ice extent. Because extent and thickness, two main characteristics of sea ice, 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 ice 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 ice thickness. Ice 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 ice thickness. In this study, Arctic sea ice freeboard and thickness in 2012 and 2013 were estimated using CryoSat-2 SAR mode data that has sea ice surface height relative to the reference ellipsoid WGS84. In order to estimate sea ice thickness, freeboard height, elevation difference between the top of sea ice 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 ice. Several near-real time cloud-free MODIS images as CryoSat-2 data were used to identify leads. Rule-based machine learning approaches such as random forest and See5.0 and human-derived decision trees were used to produce rules to identify leads. With the freeboard height calculated from the lead analysis, sea ice thickness was finally estimated using the Archimedes' buoyancy principle with density of sea ice and sea water and the height of freeboard. The results were compared with Arctic sea ice thickness distribution retrieved from CryoSat-2 data by Alfred-Wegener-Institute.

Seasonal and interannual variability of the Arctic sea ice: A comparison between AO-FVCOM and observations

NASA Astrophysics Data System (ADS)

Zhang, Yu; Chen, Changsheng; Beardsley, Robert C.; Gao, Guoping; Qi, Jianhua; Lin, Huichan

2016-11-01

A high-resolution (up to 2 km), unstructured-grid, fully ice-sea coupled Arctic Ocean Finite-Volume Community Ocean Model (AO-FVCOM) was used to simulate the sea ice in the Arctic over the period 1978-2014. The spatial-varying horizontal model resolution was designed to better resolve both topographic and baroclinic dynamics scales over the Arctic slope and narrow straits. The model-simulated sea ice was in good agreement with available observed sea ice extent, concentration, drift velocity and thickness, not only in seasonal and interannual variability but also in spatial distribution. Compared with six other Arctic Ocean models (ECCO2, GSFC, INMOM, ORCA, NAME, and UW), the AO-FVCOM-simulated ice thickness showed a higher mean correlation coefficient of ˜0.63 and a smaller residual with observations. Model-produced ice drift speed and direction errors varied with wind speed: the speed and direction errors increased and decreased as the wind speed increased, respectively. Efforts were made to examine the influences of parameterizations of air-ice external and ice-water interfacial stresses on the model-produced bias. The ice drift direction was more sensitive to air-ice drag coefficients and turning angles than the ice drift speed. Increasing or decreasing either 10% in water-ice drag coefficient or 10° in water-ice turning angle did not show a significant influence on the ice drift velocity simulation results although the sea ice drift speed was more sensitive to these two parameters than the sea ice drift direction. Using the COARE 4.0-derived parameterization of air-water drag coefficient for wind stress did not significantly influence the ice drift velocity simulation.

EM Bias-Correction for Ice Thickness and Surface Roughness Retrievals over Rough Deformed Sea Ice

NASA Astrophysics Data System (ADS)

Li, L.; Gaiser, P. W.; Allard, R.; Posey, P. G.; Hebert, D. A.; Richter-Menge, J.; Polashenski, C. M.

2016-12-01

The very rough ridge sea ice accounts for significant percentage of total ice areas and even larger percentage of total volume. The commonly used Radar altimeter surface detection techniques are empirical in nature and work well only over level/smooth sea ice. Rough sea ice surfaces can modify the return waveforms, resulting in significant Electromagnetic (EM) bias in the estimated surface elevations, and thus large errors in the ice thickness retrievals. To understand and quantify such sea ice surface roughness effects, a combined EM rough surface and volume scattering model was developed to simulate radar returns from the rough sea ice `layer cake' structure. A waveform matching technique was also developed to fit observed waveforms to a physically-based waveform model and subsequently correct the roughness induced EM bias in the estimated freeboard. This new EM Bias Corrected (EMBC) algorithm was able to better retrieve surface elevations and estimate the surface roughness parameter simultaneously. In situ data from multi-instrument airborne and ground campaigns were used to validate the ice thickness and surface roughness retrievals. For the surface roughness retrievals, we applied this EMBC algorithm to co-incident LiDAR/Radar measurements collected during a Cryosat-2 under-flight by the NASA IceBridge missions. Results show that not only does the waveform model fit very well to the measured radar waveform, but also the roughness parameters derived independently from the LiDAR and radar data agree very well for both level and deformed sea ice. For sea ice thickness retrievals, validation based on in-situ data from the coordinated CRREL/NRL field campaign demonstrates that the physically-based EMBC algorithm performs fundamentally better than the empirical algorithm over very rough deformed sea ice, suggesting that sea ice surface roughness effects can be modeled and corrected based solely on the radar return waveforms.

30-Year Satellite Record Reveals Contrasting Arctic and Antarctic Decadal Sea Ice Variability

NASA Technical Reports Server (NTRS)

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

2003-01-01

A 30-year satellite record of sea ice extents derived mostly from satellite microwave radiometer observations reveals that the Arctic sea ice extent 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 ice extent decreased dramatically over the period 1973-1977, then gradually increased. Over the full 30-year period, the Antarctic ice extent decreased by 0.15 plus or minus 0.08 x 10(exp 6) square kilometers per 10 yr. The trend reversal is attributed to a large positive anomaly in Antarctic sea ice extent in the early 1970's, an anomaly that apparently began in the late 1960's, as observed in early visible and infrared satellite images.

Cloud and surface textural features in polar regions

NASA Technical Reports Server (NTRS)

Welch, Ronald M.; Kuo, Kwo-Sen; Sengupta, Sailes K.

1990-01-01

The study examines the textural signatures of clouds, ice-covered mountains, solid and broken sea ice and floes, and open water. The textural features are computed from sum and difference histogram and gray-level difference vector statistics defined at various pixel displacement distances derived from Landsat multispectral scanner data. Polar cloudiness, snow-covered mountainous regions, solid sea ice, glaciers, and open water have distinguishable texture features. This suggests that textural measures can be successfully applied to the detection of clouds over snow-covered mountains, an ability of considerable importance for the modeling of snow-melt runoff. However, broken stratocumulus cloud decks and thin cirrus over broken sea ice remain difficult to distinguish texturally. It is concluded that even with high spatial resolution imagery, it may not be possible to distinguish broken stratocumulus and thin clouds from sea ice in the marginal ice zone using the visible channel textural features alone.

Symmetry in polarimetric remote sensing

NASA Technical Reports Server (NTRS)

Nghiem, S. V.; Yueh, S. H.; Kwok, R.

1993-01-01

Relationships among polarimetric backscattering coefficients are derived from the viewpoint of symmetry groups. For both reciprocal and non-reciprocal media, symmetry encountered in remote sensing due to reflection, rotation, azimuthal, and centrical symmetry groups is considered. The derived properties are general and valid to all scattering mechanisms, including volume and surface scatterings and their interactions, in a given symmetrical configuration. The scattering coefficients calculated from theoretical models for layer random media and rough surfaces are shown to obey the symmetry relations. Use of symmetry properties in remote sensing of structural and environmental responses of scattering media is also discussed. Orientations of spheroidal scatterers described by spherical, uniform, planophile, plagiothile, erectophile, and extremophile distributions are considered to derive their polarimetric backscattering characteristics. These distributions can be identified from the observed scattering coefficients by comparison with theoretical symmetry calculations. A new parameter is then defined to study scattering structures in geophysical media. Observations from polarimetric data acquired by the Jet Propulsion Laboratory airborne synthetic aperture radar over forests, sea ice, and sea surface are presented. Experimental evidences of the symmetry relationships are shown and their use in polarimetric remote sensing is illustrated. For forests, the coniferous forest in Mt. Shasta area (California) and mixed forest near Presque Isle (Maine) exhibit characteristics of the centrical symmetry at C-band. For sea ice in the Beaufort Sea, multi-year sea ice has a cross-polarized ratio e close to e(sub 0), calculated from symmetry, due to the randomness in the scattering structure. First-year sea ice has e much smaller than e(sub 0) due to the preferential alignment of the columnar structure of the ice. From polarimetric data of a sea surface in the Bering Sea, it is observed that e and e(sub 0) are increasing with incident angle and e is greater than e(sub 0) at L-band because of the directional feature of sea surface waves. Symmetry properties of geophysical media can also be used to calibrate polarimetric radars.

Arctic multiyear ice classification and summer ice cover using passive microwave satellite data

NASA Technical Reports Server (NTRS)

Comiso, J. C.

1990-01-01

Passive microwave data collected by Nimbus 7 were used to classify and monitor the Arctic multilayer sea ice cover. Sea ice concentration maps during several summer minima are analyzed to obtain estimates of ice floes that survived summer, and the results are compared with multiyear-ice concentrations derived from these data by using an algorithm that assumes a certain emissivity for multiyear ice. The multiyear ice cover inferred from the winter data was found to be about 25 to 40 percent less than the summer ice-cover minimum, indicating that the multiyear ice cover in winter is inadequately represented by the passive microwave winter data and that a significant fraction of the Arctic multiyear ice floes exhibits a first-year ice signature.

Change and Variability in East Antarctic Sea Ice Seasonality, 1979/80–2009/10

PubMed Central

Massom, Robert; Reid, Philip; Stammerjohn, Sharon; Raymond, Ben; Fraser, Alexander; Ushio, Shuki

2013-01-01

Recent analyses have shown that significant changes have occurred in patterns of sea ice 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 ice advance, retreat and resultant ice season duration in East Antarctica. These were calculated from satellite-derived ice concentration data for the period 1979/80 to 2009/10. The pattern of change in sea ice seasonality off East Antarctica comprises mixed signals on regional to local scales, with pockets of strongly positive and negative trends 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 ice, polynyas and the marginal ice zone. A trend towards shorter sea-ice 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 Ice Shelves. These areas are largely associated with coastal polynyas that are important as sites of enhanced sea ice production/melt. Areas of positive trend in ice 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 trends in West Antarctica e.g., in the Antarctic Peninsula-Bellingshausen Sea and western Ross Sea sectors. PMID:23705008

Change and variability in East antarctic sea ice seasonality, 1979/80-2009/10.

PubMed

Massom, Robert; Reid, Philip; Stammerjohn, Sharon; Raymond, Ben; Fraser, Alexander; Ushio, Shuki

2013-01-01

Recent analyses have shown that significant changes have occurred in patterns of sea ice 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 ice advance, retreat and resultant ice season duration in East Antarctica. These were calculated from satellite-derived ice concentration data for the period 1979/80 to 2009/10. The pattern of change in sea ice seasonality off East Antarctica comprises mixed signals on regional to local scales, with pockets of strongly positive and negative trends 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 ice, polynyas and the marginal ice zone. A trend towards shorter sea-ice 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 Ice Shelves. These areas are largely associated with coastal polynyas that are important as sites of enhanced sea ice production/melt. Areas of positive trend in ice 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 trends in West Antarctica e.g., in the Antarctic Peninsula-Bellingshausen Sea and western Ross Sea sectors.

A Quantitative Proxy for Sea-Ice Based on Diatoms: A Cautionary Tale.

NASA Astrophysics Data System (ADS)

Nesterovich, A.; Caissie, B.

2016-12-01

Sea ice in the Polar Regions supports unique and productive ecosystems, but the current decline in the Arctic sea ice extent prompts questions about previous sea ice declines and the response of ice related ecosystems. Since satellite data only extend back to 1978, the study of sea ice 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 ice concentrations, the Bering and Chukchi seas are a perfect place to find a relationship between the presence of sea ice and diatom community composition. The aim of this work is to develop a diatom-based proxy for the sea ice extent. 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 ice 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 ice extent 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 ice-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 Random Forests. All models showed the same consistent pattern in the residuals. We conclude that ecosystems of the Bering and Chukchi seas respond differently to sea ice concentration and an integrated proxy must take it into account.

Snow and Ice Products from the Moderate Resolution Imaging Spectroradiometer

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Salomonson, Vincent V.; Riggs, George A.; Klein, Andrew G.

2003-01-01

Snow and sea ice products, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, flown on the Terra and Aqua satellites, are or will be available through the National Snow and Ice Data Center Distributed Active Archive Center (DAAC). The algorithms that produce the products are automated, thus providing a consistent global data set that is suitable for climate studies. The suite of MODIS snow products begins with a 500-m resolution, 2330-km swath snow-cover map that is then projected onto a sinusoidal grid to produce daily and 8-day composite tile products. The sequence proceeds to daily and 8-day composite climate-modeling grid (CMG) products at 0.05 resolution. A daily snow albedo product will be available in early 2003 as a beta test product. The sequence of sea ice products begins with a swath product at 1-km resolution that provides sea ice extent and ice-surface temperature (IST). The sea ice swath products are then mapped onto the Lambert azimuthal equal area or EASE-Grid projection to create a daily and 8-day composite sea ice tile product, also at 1 -km resolution. Climate-Modeling Grid (CMG) sea ice products in the EASE-Grid projection at 4-km resolution are planned for early 2003.

Diverse landscapes beneath Pine Island Glacier influence ice flow.

PubMed

Bingham, Robert G; Vaughan, David G; King, Edward C; Davies, Damon; Cornford, Stephen L; Smith, Andrew M; Arthern, Robert J; Brisbourne, Alex M; De Rydt, Jan; Graham, Alastair G C; Spagnolo, Matteo; Marsh, Oliver J; Shean, David E

2017-11-20

The retreating Pine Island Glacier (PIG), West Antarctica, presently contributes ~5-10% of global sea-level rise. PIG's retreat rate has increased in recent decades with associated thinning migrating upstream into tributaries feeding the main glacier trunk. To project future change requires modelling that includes robust parameterisation of basal traction, the resistance to ice flow at the bed. However, most ice-sheet models estimate basal traction from satellite-derived surface velocity, without a priori knowledge of the key processes from which it is derived, namely friction at the ice-bed interface and form drag, and the resistance to ice flow that arises as ice deforms to negotiate bed topography. Here, we present high-resolution maps, acquired using ice-penetrating radar, of the bed topography across parts of PIG. Contrary to lower-resolution data currently used for ice-sheet models, these data show a contrasting topography across the ice-bed interface. We show that these diverse subglacial landscapes have an impact on ice flow, and present a challenge for modelling ice-sheet evolution and projecting global sea-level rise from ice-sheet loss.

Sea ice and oceanic processes on the Ross Sea continental shelf

NASA Astrophysics Data System (ADS)

Jacobs, S. S.; Comiso, J. C.

1989-12-01

We have investigated the spatial and temporal variability of Antarctic sea ice concentrations on the Ross Sea continental shelf, in relation to oceanic and atmospheric forcing. Sea ice data were derived from Nimbus 7 scanning multichannel microwave radiometer (SMMR) brightness temperatures from 1979-1986. Ice cover over the shelf was persistently lower than above the adjacent deep ocean, averaging 86% during winter with little month-to-month or interannual variability. The large spring Ross Sea polynya on the western shelf results in a longer period of summer insolation, greater surface layer heat storage, and later ice formation in that region the following autumn. Newly identified Pennell and Ross Passage polynyas near the continental shelf break appear to be maintained in part by divergence above a submarine bank and by upwelling of warmer water near the slope front. Warmer subsurface water enters the shelf region year-round and will retard ice growth and enhance heat flux to the atmosphere when entrained in the strong winter vertical circulation. Temperatures at 125-m depth on a mooring near the Ross Ice Shelf during July 1984 averaged 0.15°C above freezing, sufficient to support a vertical heat flux above 100 W/m2. Monthly average subsurface ocean temperatures along the Ross Ice Shelf lag the air temperature cycle and begin to rise several weeks before spring ice breakout. The coarse SMMR resolution and dynamic ice shelf coastlines can compromise the use of microwave sea ice data near continental boundaries.

Derive Arctic Sea-ice Freeboard and Thickness from NASA's LVIS Observations

NASA Astrophysics Data System (ADS)

Yi, D.; Hofton, M. A.; Harbeck, J.; Cornejo, H.; Kurtz, N. T.

2015-12-01

The sea-ice freeboard and thickness are derived from the six sea-ice flights of NASA's IceBridge Land, Vegetation, and Ice Sensor (LVIS) over the Arctic from 2009 to 2013. The LVIS is an airborne scanning laser altimeter. It can operate at an altitude up to 10 km above the ground and produce a data swath up to 2 km wide with 20-m wide footprints. The laser output wavelength is 1064 nm and pulse repetition rate is 1000 Hz. The LVIS L2 geolocated surface elevation product and Level-1b waveform product (http://nsidc.org/data/ilvis2.html and http://nsidc.org/data/ilvis1b.html) at National Snow and Ice Data Center, USA (NSIDC) are used in this study. The elevations are referenced to a geoid with tides and dynamic atmospheric corrections applied. The LVIS waveforms were fitted with Gaussian curves to calculate pulse width, peak location, pulse amplitude, and signal baseline. For each waveform, the centroid, skewness, kurtosis, and pulse area were also calculated. The waveform parameters were calibrated based on laser off pointing angle and laser channels. Calibrated LVIS waveform parameters show a coherent response to variations in surface features along their ground tracks. These parameters, combined with elevation, can be used to identify leads, enabling the derivation of sea-ice freeboard and thickness without relying upon visual images. Preliminary results show that the elevations in some of the LVIS campaigns may vary with laser incident angle; this can introduce an elevation bias if not corrected. Further analysis of the LVIS data shown that the laser incident angle related elevation bias can be removed empirically. The sea-ice freeboard and thickness results from LVIS are compared with NASA's Airborne Topographic Mapper (ATM) for an April 20, 2010 flight, when both LVIS and ATM sensors were on the same aircraft and made coincidental measurements along repeat ground tracks.

Summer Sea Ice Motion from the 18 GHz Channel of AMSR-E and the Exchange of Sea Ice between the Pacific and Atlantic Sectors

NASA Technical Reports Server (NTRS)

Kwok, Ronald

2008-01-01

We demonstrate that sea ice motion in summer can be derived reliably from the 18GHz channel of the AMSR-E instrument on the EOS Aqua platform. The improved spatial resolution of this channel with its lower sensitivity to atmospheric moisture seems to have alleviated various issues that have plagued summer motion retrievals from shorter wavelength observations. Two spatial filters improve retrieval quality: one reduces some of the microwave signatures associated with synoptic-scale weather systems and the other removes outliers. Compared with daily buoy drifts, uncertainties in motion are approx.3-4 km/day. Using the daily motion fields, we examine five years of summer ice area exchange between the Pacific and Atlantic sectors of the Arctic Ocean. With the sea-level pressure patterns during the summer of 2006 and 2007 favoring the export of sea ice into the Atlantic Sector, the regional outflow is approx.21% and approx.15% of the total sea ice retreat in the Pacific sector.

Whither Arctic Sea Ice? - An Earth Exploration Toolbook chapter on the climate's canary in a coal mine

NASA Astrophysics Data System (ADS)

Meier, W. N.; Youngman, E.; Dahlman, L.

2007-12-01

Arctic sea ice is declining rapidly. Since 2002, summer Arctic sea ice extents have been at record or near-record lows; winter extents have also showed a marked decline. Even in comparison to the previous five extreme low years, the 2007 summer melt season has been stunning, with dramatically less ice than the previous record in 2005. This is further evidence that the Arctic sea ice may have already passed a tipping point toward a state without ice during the summer by 2050 or before. Such a change will have profound impacts on climate as well as human and wildlife activities in the region. The "Whither Arctic Sea Ice?" Earth Exploration Toolbook chapter (http://serc.carleton.edu/eet/seaice/index.html) exposes students to satellite-derived sea ice data and allows them to process and interpret the data to "discover" these sea ice changes for themselves. A sample case study in Hudson Bay has been developed that relates the physical changes occurring on the sea ice to peoples and wildlife that depend on the ice for their livelihood. This approach provides a personal connection for students and allows them to relate to the impacts of the changes. Suggestions are made for further case studies that can be developed using the same data relating to topical events in the Arctic. The EET chapter exposes students to climate change, scientific data, statistical concepts, and image processing software providing an avenue for the communication of IPY data and science to teachers and students.

Arctic Sea Ice Parameters from AMSR-E Data using Two Techniques, and Comparisons with Sea Ice from SSM

NASA Technical Reports Server (NTRS)

Comiso, Josefino C.; Parkinson, Claire L.

2007-01-01

We use two algorithms to process AMSR-E data in order to determine algorithm dependence, if any, on the estimates of sea ice concentration, ice extent and area, and trends and to evaluate how AMSR-E data compare with historical SSM/I data. The monthly ice 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 ice region being generally comparable for ABA and NT2 retrievals while data in the marginal ice zones and thin ice regions show higher values when the NT2 algorithm is used. The ice extents 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 ice extents and -6.6 x 10(exp 4) square kilometers for ice area which are small compared to mean seasonal values of 10.5 x 10(exp 6) and 9.8 x 10(exp 6) for ice extent and area: respectively. Likewise, extents 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 extents than area mainly because of differences in channel selection and sensor resolutions. Trends in extent during the AMSR-E era were also estimated and results from all three data sets are shown to be in good agreement (within errors).

NASA sea ice and snow validation plan for the Defense Meteorological Satellite Program special sensor microwave/imager

NASA Technical Reports Server (NTRS)

Cavalieri, Donald J. (Editor); Swift, Calvin T. (Editor)

1987-01-01

This document addresses the task of developing and executing a plan for validating the algorithm used for initial processing of sea ice data from the Special Sensor Microwave/Imager (SSMI). The document outlines a plan for monitoring the performance of the SSMI, for validating the derived sea ice parameters, and for providing quality data products before distribution to the research community. Because of recent advances in the application of passive microwave remote sensing to snow cover on land, the validation of snow algorithms is also addressed.

Toward Sub-seasonal to Seasonal Arctic Sea Ice Forecasting Using the Regional Arctic System Model (RASM)

NASA Astrophysics Data System (ADS)

Kamal, S.; Maslowski, W.; Roberts, A.; Osinski, R.; Cassano, J. J.; Seefeldt, M. W.

2017-12-01

The Regional Arctic system model has been developed and used to advance the current state of Arctic modeling and increase the skill of sea ice forecast. RASM is a fully coupled, limited-area model that includes the atmosphere, ocean, sea ice, land hydrology and runoff routing components and the flux coupler to exchange information among them. Boundary conditions are derived from NCEP Climate Forecasting System Reanalyses (CFSR) or Era Iterim (ERA-I) for hindcast simulations or from NCEP Coupled Forecast System Model version 2 (CFSv2) for seasonal forecasts. We have used RASM to produce sea ice forecasts for September 2016 and 2017, in contribution to the Sea Ice Outlook (SIO) of the Sea Ice Prediction Network (SIPN). Each year, we produced three SIOs for the September minimum, initialized on June 1, July 1 and August 1. In 2016, predictions used a simple linear regression model to correct for systematic biases and included the mean September sea ice extent, the daily minimum and the week of the minimum. In 2017, we produced a 12-member ensemble on June 1 and July 1, and 28-member ensemble August 1. The predictions of September 2017 included the pan-Arctic and regional Alaskan sea ice extent, daily and monthly mean pan-Arctic maps of sea ice probability, concentration and thickness. No bias correction was applied to the 2017 forecasts. Finally, we will also discuss future plans for RASM forecasts, which include increased resolution for model components, ecosystem predictions with marine biogeochemistry extensions (mBGC) to the ocean and sea ice components, and feasibility of optional boundary conditions using the Navy Global Environmental Model (NAVGEM).

Transient sensitivities of sea ice export through the Canadian Arctic Archipelago inferred from a coupled ocean/sea-ice adjoint model

NASA Astrophysics Data System (ADS)

Heimbach, P.; Losch, M.; Menemenlis, D.; Campin, J.; Hill, C.

2008-12-01

The sensitivity of sea-ice export through the Canadian Arctic Archipelago (CAA), measured in terms of its solid freshwater export through Lancaster Sound, to changes in various elements of the ocean and sea-ice state, and to elements of the atmospheric forcing fields through time and space is assessed by means of a coupled ocean/sea-ice adjoint model. The adjoint model furnishes full spatial sensitivity maps (also known as Lagrange multipliers) of the export metric to a variety of model variables at any chosen point in time, providing the unique capability to quantify major drivers of sea-ice export variability. The underlying model is the MIT ocean general circulation model (MITgcm), which is coupled to a Hibler-type dynamic/thermodynamic sea-ice model. The configuration is based on the Arctic face of the ECCO3 high-resolution cubed-sphere model, but coarsened to 36-km horizontal grid spacing. The adjoint of the coupled system has been derived by means of automatic differentiation using the software tool TAF. Finite perturbation simulations are performed to check the information provided by the adjoint. The sea-ice model's performance in the presence of narrow straits is assessed with different sea-ice lateral boundary conditions. The adjoint sensitivity clearly exposes the role of the model trajectory and the transient nature of the problem. The complex interplay between forcing, dynamics, and boundary condition is demonstrated in the comparison between the different calculations. The study is a step towards fully coupled adjoint-based ocean/sea-ice state estimation at basin to global scales as part of the ECCO efforts.

Sea ice variations in the central Okhotsk Sea during the last two glacial-interglacial cycles

NASA Astrophysics Data System (ADS)

Lo, L.; Cabedo-Sanz, P.; Lattaud, J.; Belt, S. T.; Schouten, S.; Huang, J. J.; Timmermann, A.; Zeeden, C.; Wei, K. Y.; Shen, C. C.; Hodell, D. A.; Elderfield, H.

2016-12-01

Sea ice system as one of the critical and sensitive climate components in the Earth's climate system has experienced dramatically declination for the past few decades. Little knowledge, however, about the sea ice variations in the past orbital timescales has been obtained by paleoclimatic studies due to the lack of reliable sea ice proxy and age model constrain in the high productivity subpolar to polar regions. Here we present continuous 180,000 years subarctic northwestern Pacific sea ice and surface temperature (SST) records in the center Okhotsk Sea, the southernmost of seasonal sea ice fomration region in the Northern Hemisphere by using by using novel organic and non-destructive geochemical proxies from Site MD01-2414 (53oN, 149oE, water depth 1123 m). High resolution X-ray fluoresces scanning biogenic/terrestrial (Ba/Ti) elemental ratio represent clear glacial-interglacial cycles. Organic geochemical proxies (IP25 and TEX86) derived sea ice and SST changes in the same time resolution reveal the seasonality in the center Okhotsk Sea. Sea ice shows strong 23-kyr precession cycle control with modulation of 100-kyr eccentricity cycle during the peak interglacial periods (Marine Isotope Stage 5e and Holocene). On the other hand, SST represent global background climate change of 100-kyr cycle with very strong obliquity changes. According to the timeseries analyses, we argue that the sea ice minimum in the center of Okhotsk Sea has mainly been controlled by the local autumn insolation. SST represent annual insolation increasing due to local summer insolation and the obliquity pacing. This study firstly demonstrated clear seasonality in the same site. Further study of the relationship between sea ice and seawater thermal hisotries on the orbital timescale in the subarctic Pacific is crucial in the understanding of past major climate event, e.g. Middle Pleistocene Transition and Middle Brunhes Event.

The Timing of Arctic Sea Ice Advance and Retreat as an Indicator of Ice-Dependent Marine Mammal Habitat

NASA Astrophysics Data System (ADS)

Stern, H. L.; Laidre, K. L.

2013-12-01

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-ice cover is shrinking and thinning, with total disappearance of summer sea ice 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-ice cover as an integral part of their existence. While the downward trend in sea-ice extent in a given month is an often-used metric for quantifying physical changes in the ice cover, it is not the most relevant measure for characterizing changes in the sea-ice habitat of marine mammals. Species that depend on sea ice are behaviorally tied to the annual retreat of sea ice 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-ice coverage in a particular month of the year. Many ecologically important regions of the Arctic are essentially ice-covered in winter and ice-free in summer, and will probably remain so for a long time into the future. But the dates of sea-ice retreat in spring and advance in fall are key indicators of climate change for ice-dependent marine mammals. We use daily sea-ice concentration data derived from satellite passive microwave sensors to calculate the dates of sea-ice 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 ice 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 days/decade, with steeper trends in the Barents Sea. Thus the season of sparse sea-ice coverage is lengthening by about 2 weeks/decade, or 6 weeks over the period of record. The trends in all 11 regions are statistically significant. The dates of sea-ice retreat in spring and advance in fall are negatively correlated: an early spring retreat tends to be followed by a late fall advance, and vice-versa. This is a manifestation of the ice-albedo feedback: with an early sea-ice retreat, the ocean has more time to absorb heat from the sun. The extra heat is stored in the upper ocean through the summer, and must be released to the atmosphere in the fall before sea ice can begin to form, thus delaying fall freeze-up. This relationship gives some predictive power to the date of fall sea-ice advance, given the date of spring retreat. Changes have been reported in the seasonal distribution of polar bears, walruses, seals, and whales in the Arctic. We are developing metrics for potential use by the U.S. National Climate Assessment based on the timing of sea-ice advance and retreat, to be used as indicators of ice-dependent marine mammal habitat. Future work will examine connections between the phenology of Arctic marine mammals and the sea-ice indicators.

Inter-comparison of isotropic and anisotropic sea ice rheology in a fully coupled model

NASA Astrophysics Data System (ADS)

Roberts, A.; Cassano, J. J.; Maslowski, W.; Osinski, R.; Seefeldt, M. W.; Hughes, M.; Duvivier, A.; Nijssen, B.; Hamman, J.; Hutchings, J. K.; Hunke, E. C.

2015-12-01

We present the sea ice climate of the Regional Arctic System Model (RASM), using a suite of new physics available in the Los Alamos Sea Ice Model (CICE5). RASM is a high-resolution fully coupled pan-Arctic model that also includes the Parallel Ocean Program (POP), the Weather Research and Forecasting Model (WRF) and Variable Infiltration Capacity (VIC) land model. The model domain extends from ~45˚N to the North Pole and is configured to run at ~9km resolution for the ice and ocean components, coupled to 50km resolution atmosphere and land models. The baseline sea ice model configuration includes mushy-layer sea ice thermodynamics and level-ice melt ponds. Using this configuration, we compare the use of isotropic and anisotropic sea ice mechanics, and evaluate model performance using these two variants against observations including Arctic buoy drift and deformation, satellite-derived drift and deformation, and sea ice volume estimates from ICESat. We find that the isotropic rheology better approximates spatial patterns of thickness observed across the Arctic, but that both rheologies closely approximate scaling laws observed in the pack using buoys and RGPS data. A fundamental component of both ice mechanics variants, the so called Elastic-Viscous-Plastic (EVP) and Anisotropic-Elastic-Plastic (EAP), is that they are highly sensitive to the timestep used for elastic sub-cycling in an inertial-resolving coupled framework, and this has a significant affect on surface fluxes in the fully coupled framework.

Sea-level Fingerprinting, Vertical Crustal Motion from GIA, and Projections of Relative Sea-level Change in the Canadian Arctic

NASA Astrophysics Data System (ADS)

James, Thomas; Simon, Karen; Forbes, Donald; Dyke, Arthur; Mazzotti, Stephane

2010-05-01

We present projections of relative sea-level rise in the 21st century for communities in the Canadian Arctic. First, for selected communities, we determine the sea-level fingerprinting response from Antarctica, Greenland, and mountain glaciers and ice caps. Then, for various published projections of global sea-level change in the 21st century, we determine the local amount of "absolute" sea-level change. We next determine the vertical land motion arising from glacial isostatic adjustment (GIA) and incorporate this into the estimates of absolute sea-level change to obtain projections of relative sea-level change. The sea-level fingerprinting effect is especially important in the Canadian Arctic owing to proximity to Arctic ice caps and especially to the Greenland ice sheet. Its effect is to reduce the range of projected relative sea-level change compared to the range of global sea-level projections. Vertical crustal motion is assessed through empirically derived regional isobases, the Earth's predicted response to ice-sheet loading and unloading by the ICE-5G ice sheet reconstruction, and Global Positioning System vertical velocities. Owing to the large rates of crustal uplift from glacial isostatic adjustment across a large region of central Arctic Canada, many communities are projected to experience relative sea-level fall despite projections of global sea-level rise. Where uplift rates are smaller, such as eastern Baffin Island and the western Canadian Arctic, sea-level is projected to rise.

Recent Trends in the Arctic Navigable Ice Season and Links to Atmospheric Circulation

NASA Astrophysics Data System (ADS)

Maslanik, J.; Drobot, S.

2002-12-01

One of the potential effects of Arctic climate warming is an increase in the navigable ice 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 ice 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 ice concentrations, trends and variability in the Arctic navigable ice season are examined from 1979 through 2001. Trend analyses suggest large increases in the length of the navigable ice season in the Kara and Barents seas, the Sea of Okhotsk, and the Beaufort Sea, with decreases in the length of the navigable ice season in the Bering Sea. Interannual variations in the navigable ice season largely are governed by fluctuations in low-frequency atmospheric circulation, although the specific annular modes affecting the length of the navigable ice season vary by region. In the Beaufort and East Siberian seas, variations in the North Atlantic Oscillation/Arctic Oscillation control the navigable ice season, while variations in the East Pacific anomaly play an important role in controlling the navigable ice season in the Kara and Barents seas. In Hudson Bay, the Canadian Arctic Archipelago, and Baffin Bay, interannual variations in the navigable ice season are strongly related to the Pacific Decadal Oscillation.

Some Results on Sea Ice Rheology for the Seasonal Ice Zone, Obtained from the Deformation Field of Sea Ice Drift Pattern

NASA Astrophysics Data System (ADS)

Toyota, T.; Kimura, N.

2017-12-01

Sea ice rheology which relates sea ice stress to the large-scale deformation of the ice cover has been a big issue to numerical sea ice modelling. At present the treatment of internal stress within sea ice area is based mostly on the rheology formulated by Hibler (1979), where the whole sea ice 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 ice area and horizontal resolution of the model. However, this formulation was initially developed to reproduce the seasonal variation of the perennial ice in the Arctic Ocean. As for its applicability to the seasonal ice zones (SIZ), where various types of sea ice are present, it still needs validation from observational data. In this study, the validity of this rheology was examined for the Sea of Okhotsk ice, typical of the SIZ, based on the AMSR-derived ice 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. Ice 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 ice areas. Since this result corresponds with the yield criterion by Tresca and Von Mises for a 2D plastic matter, it suggests the validity and applicability of this rheology to the SIZ to some extent. However, it was also noted that the variation of the deformation field in the Sea of Okhotsk is much larger than in the Beaufort Sea, which indicates the need for the careful treatment of grid size in the model.

Mass Balance of Multiyear Sea Ice in the Southern Beaufort Sea

DTIC Science & Technology

2014-09-30

Petty et al. We will extend these results by combining them with satelite -derived ice age data (Maslanik et al., 2007) to focus on the areal...from buoys and satelites with thickness data from AEM surveys, while for the repeat- Figure 1: “Pseudo-plumes” of icepass analysis we are also using

Arctic Sea Ice in Transformation: A Review of Recent Observed Changes and Impacts on Biology and Human Activity

NASA Technical Reports Server (NTRS)

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.;

Satellite radar altimetry over ice. Volume 1: Processing and corrections of Seasat data over Greenland

NASA Technical Reports Server (NTRS)

Zwally, H. Jay; Brenner, Anita C.; Major, Judith A.; Martin, Thomas V.; Bindschadler, Robert A.

1990-01-01

The data-processing methods and ice data products derived from Seasat radar altimeter measurements over the Greenland ice sheet and surrounding sea ice are documented. The corrections derived and applied to the Seasat radar altimeter data over ice are described in detail, including the editing and retracking algorithm to correct for height errors caused by lags in the automatic range tracking circuit. The methods for radial adjustment of the orbits and estimation of the slope-induced errors are given.

L-band radiometry for sea ice applications

NASA Astrophysics Data System (ADS)

Heygster, G.; Hedricks, S.; Mills, P.; Kaleschke, L.; Stammer, D.; Tonboe, R.

2009-04-01

Although sea ice remote sensing has reached the level of operational exploitation with well established retrieval methods, several important tasks are still unsolved. In particular during freezing and melting periods with mixed ice and water surfaces, estimates of ice concentration with passive and active microwave sensors remain challenging. Newly formed thin ice is also hard to distinguish from open water with radiometers for frequencies above 8 GHz. The SMOS configuration (planned launch 2009) with a radiometer at 1.4 GHz is a promising technique to complement observations at higher microwave frequencies. ESA has initiated a project to investigate the possibilities for an additional Level-2 sea ice data product based on SMOS. In detail, the project objectives are (1) to model the L band emission of sea ice, and to assess the potential (2) to retrieve sea ice parameters, especially concentration and thickness, and (3) to use cold water regions for an external calibration of SMOS. Modelling of L band emission: Several models have are investigated. All of them work on the same basic principles and have a vertically-layered, plane-parallel geometry. They are comprised of three basic components: (1) effective permittivities are calculated for each layer based on ice bulk and micro-structural properties; (2) these are integrated across the total depth to derive emitted brightness temperature; (3) scattering terms can also be added because of the granular structure of ice and snow. MEMLS (Microwave Emission Model of Layered Snowpacks (Wiesmann and Matzler 1999)) is one such model that contains all three elements in a single Matlab program. In the absence of knowledge about the internal structure of the sea ice, three-layer (air, ice and water) dielectric slab models which take as input a single effective permittivity for the ice layer are appropriate. By ignoring scattering effects one can derive a simple analytic expression for a dielectric slab as shown by Apinis and Peake (1976). This expression was used by Menashi et al. (1993) to derive the thickness of sea ice from UHF (0.6 GHz) radiometer. Second, retrieval algorithms for sea ice parameters with emphasis on ice-water discrimination from L-band observations considering the specific SMOS observations modes and geometries are investigated. A modified Menashi model with the permittivity depending on brine volume and temperature suggests a thickness sensitivity of up to 150 cm for low salinity (multi year or brackish) sea ice at low temperatures. At temperatures approaching the melting point the thickness sensitivity reduces to a few centimetres. For first year ice the modelled thickness sensitivity is roughly half a meter. Runs of the model MEMLS with input data generated from a 1-d thermodynamic sea ice model lead to similar conclusio. The results of the forward model may strongly vary with the input microphysical details. E.g. if the permittivity is modelled to depend in addition on the sea ice thickness as supported by several former field campaigns for thin ice, the model predictions change strongly. Prior to the launch of SMOS, an important source of observational data is the SMOS Sea-Ice campaign held near Kokkola, Finland, March 2007 conducted as an add-on of the POL-ICE campaign. Co-incident L-band observations taken with the EMIRAD instrument of the Technical University of Denmark, ice thickness values determined from the EM bird of AWI and in situ observations during the campaign are combined. Although the campaign data are to be use with care, for selected parts of the flights the sea ice thickness can be retrieved correctly. However, as the instrumental conditions and calibration were not optimal, more in situ data, preferably from the Arctic, will be needed before drawing clear conclusions about a future the sea ice thickness product based on SMOS data. Use of additional information from other microwave sensors like AMSR-E might be needed to constrain the conditions, e.g. on sea ice concentration and temperature. External calibration: to combine SMOS ice information with statistics on temperature and salinity variations derived from a suitable ocean model to identify ocean targets for a vicarious target calibration of the SMOS radiometer. Such a target can be identified most reliably in cold waters as suggested by Ruf (2000) before. At higher microwave frequencies the advantage of the Ruf method is that the absolute minimum of the observed brightness temperatures is a universal constant and can be used for external calibration. However, in the L band the salinity variations may shift the minimum to both directions so that suitable regions of low salinity variations need to be identified. For finding areas with fairly stable, at least known cold temperatures, one has to analyze existing prior (external) knowledge available from ocean observations (in situ and satellite) and from numerical models. From statistics based on daily AMSR SST fields and model simulations, the best area seems to be between Svalbard and Ocean Weather Ship Station (OWS) Mike, at 66N, 02E. However, variations in SST are still comparably large and the area can hardly be used for instrument calibration. It is suggested to deploy a number of drifters in a limited area representing a SMOS footprint to obtain accurate estimates of SSS and SST.

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.