Local short-term variability in solar irradiance

NASA Astrophysics Data System (ADS)

Lohmann, Gerald M.; Monahan, Adam H.; Heinemann, Detlev

2016-05-01

Characterizing spatiotemporal irradiance variability is important for the successful grid integration of increasing numbers of photovoltaic (PV) power systems. Using 1 Hz data recorded by as many as 99 pyranometers during the HD(CP)2 Observational Prototype Experiment (HOPE), we analyze field variability of clear-sky index k* (i.e., irradiance normalized to clear-sky conditions) and sub-minute k* increments (i.e., changes over specified intervals of time) for distances between tens of meters and about 10 km. By means of a simple classification scheme based on k* statistics, we identify overcast, clear, and mixed sky conditions, and demonstrate that the last of these is the most potentially problematic in terms of short-term PV power fluctuations. Under mixed conditions, the probability of relatively strong k* increments of ±0.5 is approximately twice as high compared to increment statistics computed without conditioning by sky type. Additionally, spatial autocorrelation structures of k* increment fields differ considerably between sky types. While the profiles for overcast and clear skies mostly resemble the predictions of a simple model published by , this is not the case for mixed conditions. As a proxy for the smoothing effects of distributed PV, we finally show that spatial averaging mitigates variability in k* less effectively than variability in k* increments, for a spatial sensor density of 2 km-2.

Long and Short Term Variability of the Main Physical Parameters in the Coastal Area of the SE Baltic Proper

NASA Astrophysics Data System (ADS)

Mingelaite, Toma; Rukseniene, Viktorija; Dailidiene, Inga

2015-04-01

Keywords: SE Baltic Sea, coastal upwelling, IR Remote Sensing The memory of the ocean and seas of atmospheric forcing events contributes to the long-term climate change. Intensifying climate change processes in the North Atlantic region including Baltic Sea has drawn widespread interest, as a changing water temperature has ecological, economic and social impact in coastal areas of the Europe seas. In this work we analyse long and short term variability of the main physical parameters in the coastal area of the South Eastern Baltic Sea Proper. The analysis of long term variability is based on monitoring data measured in the South Eastern Baltic Sea for the last 50 years. The main focus of the long term variability is changes of hydro meteorological parameters relevant to the observed changes in the climate.The water salinity variations in the Baltic Sea near the Lithuanian coast and in the Curonian Lagoon, a shallow and enclosed sub-basin of the Baltic Sea, were analysed along with the time series of some related hydroclimatic factors. The short term water temperature and salinity variations were analysed with a strong focus on coastal upwelling events. Combining both remote sensing and in situ monitoring data physical parameters such as vertical salinity variations during upwelling events was analysed. The coastal upwelling in the SE Baltic Sea coast, depending on its scale and intensity, may lead to an intrusion of colder and saltier marine waters to the Curonian Lagoon resulting in hydrodynamic changes and pronounced temperature drop extending for 30-40 km further down the Lagoon. The study results show that increasing trends of water level, air and water temperature, and decreasing ice cover duration are related to the changes in meso-scale atmospheric circulation, and more specifically, to the changes in regional and local wind regime climate. That is in a good agreement with the increasing trends in local higher intensity of westerly winds, and with the winter

Southern Hemisphere climate variability forced by Northern Hemisphere ice-sheet topography

NASA Astrophysics Data System (ADS)

Jones, T. R.; Roberts, W. H. G.; Steig, E. J.; Cuffey, K. M.; Markle, B. R.; White, J. W. C.

2018-02-01

The presence of large Northern Hemisphere ice sheets and reduced greenhouse gas concentrations during the Last Glacial Maximum fundamentally altered global ocean-atmosphere climate dynamics. Model simulations and palaeoclimate records suggest that glacial boundary conditions affected the El Niño-Southern Oscillation, a dominant source of short-term global climate variability. Yet little is known about changes in short-term climate variability at mid- to high latitudes. Here we use a high-resolution water isotope record from West Antarctica to demonstrate that interannual to decadal climate variability at high southern latitudes was almost twice as large at the Last Glacial Maximum as during the ensuing Holocene epoch (the past 11,700 years). Climate model simulations indicate that this increased variability reflects an increase in the teleconnection strength between the tropical Pacific and West Antarctica, owing to a shift in the mean location of tropical convection. This shift, in turn, can be attributed to the influence of topography and albedo of the North American ice sheets on atmospheric circulation. As the planet deglaciated, the largest and most abrupt decline in teleconnection strength occurred between approximately 16,000 years and 15,000 years ago, followed by a slower decline into the early Holocene.

Incidence of climate on common frog breeding: Long-term and short-term changes

NASA Astrophysics Data System (ADS)

Neveu, André

2009-09-01

In Brittany (northwest France), the climate is showing a trend toward warming. This change is increasingly suspected to have a role in driving amphibian decline, but it is very difficult to determine at what level the climate affects the future of species. Recently, some studies have detected some direct effects on breeding phenology and indirect effects on energy allocation. The present study explores some of these effects on the common frog ( Rana temporaria) from 1984 to 2007. The results show two trends: a long-term change in breeding activities and a short-term influence due to the 2003 climatic anomaly. For the period of study, the start of egg-laying shows a precocity that was correlated with thermal conditions during the preceding 40 days as well as milder springs during the previous year. This degree of precocity is currently the highest found in Europe (+26.6 days). As a result of the 2003 heat wave, the clutch mean fecundity in 2004 was smaller than for other years, the fecundity rates were reduced and abortions were numerous (unlike other years). Moreover, young females were the smallest observed in recent years and some females seemed to exhibit a trade-off between fecundity and growth. Before or after egg-laying, female body condition and mean weight of mature ovules were both lower. The year 2005 appears as a transition period before the recovery in 2006-2007. The results show that climate warming endangers the vital rates of the common frog, while the 2003 climatic events seem more detrimental than the long-term warming trend.

Assessment of short- and long-term memory in trends of major climatic variables over Iran: 1966-2015

NASA Astrophysics Data System (ADS)

Mianabadi, Ameneh; Shirazi, Pooya; Ghahraman, Bijan; Coenders-Gerrits, A. M. J.; Alizadeh, Amin; Davary, Kamran

2018-02-01

In arid and semi-arid regions, water scarcity is the crucial issue for crop production. Identifying the spatial and temporal trends in aridity, especially during the crop-growing season, is important for farmers to manage their agricultural practices. This will become especially relevant when considering climate change projections. To reliably determine the actual trends, the influence of short- and long-term memory should be removed from the trend analysis. The objective of this study is to investigate the effect of short- and long-term memory on estimates of trends in two aridity indicators—the inverted De Martonne (ϕ IDM ) and Budyko (ϕ B ) indices. The analysis is done using precipitation and temperature data over Iran for a 50-year period (1966-2015) at three temporal scales: annual, wheat-growing season (October-June), and maize-growing season (May-November). For this purpose, the original and the modified Mann-Kendall tests (i.e., modified by three methods of trend free pre-whitening (TFPT), effective sample size (ESS), and long-term persistence (LTP)) are used to investigate the temporal trends in aridity indices, precipitation, and temperature by taking into account the effect of short- and long-term memory. Precipitation and temperature data were provided by the Islamic Republic of Iran Meteorological Organization (IRIMO). The temporal trend analysis showed that aridity increased from 1966 to 2015 at the annual and wheat-growing season scales, which is due to a decreasing trend in precipitation and an increasing trend in mean temperature at these two timescales. The trend in aridity indices was decreasing in the maize-growing season, since precipitation has an increasing trend for most parts of Iran in that season. The increasing trend in aridity indices is significant in Western Iran, which can be related to the significantly more negative trend in precipitation in the West. This increasing trend in aridity could result in an increasing crop water

Intraseasonal Variability in the Atmosphere-Ocean Climate System. Second Edition

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Waliser, Duane E.

2011-01-01

Understanding and predicting the intraseasonal variability (ISV) of the ocean and atmosphere is crucial to improving long-range environmental forecasts and the reliability of climate change projections through climate models. This updated, comprehensive and authoritative second edition has a balance of observation, theory and modeling and provides a single source of reference for all those interested in this important multi-faceted natural phenomenon and its relation to major short-term climatic variations.

Short-term climate change impacts on Mara basin hydrology

NASA Astrophysics Data System (ADS)

Demaria, E. M.; Roy, T.; Valdés, J. B.; Lyon, B.; Valdés-Pineda, R.; Serrat-Capdevila, A.; Durcik, M.; Gupta, H.

2017-12-01

The predictability of climate diminishes significantly at shorter time scales (e.g. decadal). Both natural variability as well as sampling variability of climate can obscure or enhance climate change signals in these shorter scales. Therefore, in order to assess the impacts of climate change on basin hydrology, it is important to design climate projections with exhaustive climate scenarios. In this study, we first create seasonal climate scenarios by combining (1) synthetic precipitation projections generated from a Vector Auto-Regressive (VAR) model using the University of East Anglia Climate Research Unit (UEA-CRU) data with (2) seasonal trends calculated from 31 models in the Coupled Model Intercomparison Project Phase 5 (CMIP). The seasonal climate projections are then disaggregated to daily level using the Agricultural Modern-Era Retrospective Analysis for Research and Applications (AgMERRA) data. The daily climate data are then bias-corrected and used as forcings to the land-surface model, Variable Infiltration Capacity (VIC), to generate different hydrological projections for the Mara River basin in East Africa, which are then evaluated to study the hydrologic changes in the basin in the next three decades (2020-2050).

Constraining the long-term climate reponse to stratospheric sulfate aerosols injection by the short-term volcanic climate response

NASA Astrophysics Data System (ADS)

Plazzotta, M.; Seferian, R.; Douville, H.; Kravitz, B.; Tilmes, S.; Tjiputra, J.

2016-12-01

Rising greenhouse gas emissions are leading to global warming and climate change, which will have multiple impacts on human society. Geoengineering methods like solar radiation management by stratospheric sulfate aerosols injection (SSA-SRM) aim at treating the symptoms of climate change by reducing the global temperature. Since a real-world testing cannot be implemented, Earth System Models (ESMs) are useful tools to assess the climate impacts of such geoengineering methods. However, coordinated simulations performed with the Geoengineering Model Intercomparison Project (GeoMIP) have shown that climate cooling in response to a continuous injection of 5Tg of SO2 per year under RCP45 future projection (the so-called G4 experiment) differs substantially between ESMs. Here, we employ a volcano analog approach to constrain the climate response in SSA-SRM geoengineering simulations across an ensemble of 10 ESMs. We identify an emergent relationship between the long-term cooling in responses to the mitigation of the clear-sky surface downwelling shortwave radiation (RSDSCS), and the short-term cooling related to the change in RSDSCS during the major tropical volcanic eruptions observed over the historical period (1850-2005). This relationship explains almost 80% of the multi-model spread. Combined with contemporary observations of the latest volcanic eruptions (satellite observations and model reanalyzes), this relationship provides a tight constraint on the climate impacts of SSA-SRM. We estimate that a continuous injection of SO2 aerosols into the stratosphere will reduce the global average temperature of continental land surface by 0.47 K per W m-2, impacting both hydrological and carbon cycles. Compared with the unconstrained ESMs ensemble (range from 0.32 to 0.92 K per W m-2 ), our estimate represents much higher confidence ways to assess the impacts of SSA-SRM on the climate while ruling the most extreme projections of the unconstrained ensemble extremely unlikely.

Using Time Series of Landsat Data to Improve Understanding of Short- and Long-Term Changes to Vegetation Phenology in Response to Climate Change

NASA Astrophysics Data System (ADS)

Friedl, M. A.; Melaas, E. K.; Sulla-menashe, D. J.; Gray, J. M.

2014-12-01

Phenology, the seasonal progression of organisms through stages of dormancy, active growth, and senescence is a key regulator of ecosystem processes and is widely used as an indicator of vegetation responses to climate change. This is especially true in temperate forests, where seasonal dynamics in canopy development and senescence are tightly coupled to the climate system. Despite this, understanding of climate-phenology interactions is incomplete. A key impediment to improving this understanding is that available datasets are geographically sparse, and in most cases include relatively short time series. Remote sensing has been widely promoted as a useful tool for studies of large-scale phenology, but long-term studies from remote sensing have been limited to AVHRR data, which suffers from limitations related to its coarse spatial resolution and uncertainties in atmospheric corrections and radiometric adjustments that are used to create AVHRR time series. In this study, we used 30 years of Landsat data to quantify the nature and magnitude of long-term trends and short-term variability in the timing of spring leaf emergence and fall senescence. Our analysis focuses on temperate forest locations in the Northeastern United States that are co-located with surface meteorological observations, where we have estimated the timing of leaf emergence and leaf senescence at annual time steps using atmospherically corrected surface reflectances from Landsat TM and ETM+ imagery. Comparison of results from Landsat against ground observations demonstrates that phenological events can be reliably estimated from Landsat time series. More importantly, results from this analysis suggest two main conclusions related to the nature of climate change impacts on temperate forest phenology. First, there is clear evidence of trends towards longer growing seasons in the Landsat record. Second, interannual variability is large, with average year-to-year variability exceeding the magnitude of

Changes in heart rate variability are associated with expression of short-term and long-term contextual and cued fear memories.

PubMed

Liu, Jun; Wei, Wei; Kuang, Hui; Zhao, Fang; Tsien, Joe Z

2013-01-01

Heart physiology is a highly useful indicator for measuring not only physical states, but also emotional changes in animals. Yet changes of heart rate variability during fear conditioning have not been systematically studied in mice. Here, we investigated changes in heart rate and heart rate variability in both short-term and long-term contextual and cued fear conditioning. We found that while fear conditioning could increase heart rate, the most significant change was the reduction in heart rate variability which could be further divided into two distinct stages: a highly rhythmic phase (stage-I) and a more variable phase (stage-II). We showed that the time duration of the stage-I rhythmic phase were sensitive enough to reflect the transition from short-term to long-term fear memories. Moreover, it could also detect fear extinction effect during the repeated tone recall. These results suggest that heart rate variability is a valuable physiological indicator for sensitively measuring the consolidation and expression of fear memories in mice.

Short-term increase of body weight triggers immunological variables in dogs.

PubMed

Van de Velde, H; Janssens, G P J; Stuyven, E; Cox, E; Buyse, J; Hesta, M

2012-01-15

Overweight in dogs is, as in other companion animals, a major risk factor for several metabolic disorders. However, it is not yet known whether immunity is challenged by increased body weight in dogs. The aim of this study was to investigate the effect of a short-term increase in body weight on immunological variables in adult healthy beagle dogs. Sixteen dogs, divided into a control group (CG) and weight gain group (WGG), were included. During a period of 13 weeks, the CG was fed at maintenance energy requirement (MER), whereas the WGG received a double amount of food. After 13 weeks, blood samples were taken for immunological and biochemical analyses. Weight gain and increased body condition score in the WGG were accompanied by a significant higher leptin concentration. Weight gain increased the number of lymphocytes and immunoglobulins A and M and was responsible for a higher proliferation of peripheral blood mononuclear cells (PBMC). Short-term increase of body weight thus seems to trigger immunological variables in dogs. Copyright © 2011 Elsevier B.V. All rights reserved.

Broadband short term X-ray variability of the quasar PDS 456

NASA Astrophysics Data System (ADS)

Matzeu, G. A.; Reeves, J. N.; Nardini, E.; Braito, V.; Costa, M. T.; Tombesi, F.; Gofford, J.

2016-05-01

We present a detailed analysis of a recent 500 ks net exposure Suzaku observation, carried out in 2013, of the nearby (z=0.184) luminous (L_bol˜1047 erg s-1) quasar PDS 456 in which the X-ray flux was unusually low. The short term X-ray spectral variability has been interpreted in terms of variable absorption and/or intrinsic continuum changes. In the former scenario, the spectral variability is due to variable covering factors of two regions of partially covering absorbers. We find that these absorbers are characterised by an outflow velocity comparable to that of the highly ionised wind, i.e. ˜ 0.25 c, at the 99.9% (3.26σ) confidence level. This suggests that the partially absorbing clouds may be the denser clumpy part of the inhomogeneous wind. Following an obscuration event we obtained a direct estimate of the size of the X-ray emitting region, to be not larger than 20 R_g in PDS 456.

[Short-term and long-term fetal heart rate variability after amnioinfusion treatment of oligohydramnios complicated pregnancy].

PubMed

Machalski, T; Sikora, J; Bakon, I; Magnucki, J; Grzesiak-Kubica, E; Szkodny, E

2001-12-01

Results of computerised analysis of cardiotocograms obtained in the group of 21 pregnancies complicated by idiopathic oligohydramnios are presented in the study. Amnioinfusion procedures were administered serially in local anesthesia with ultrasound and colour Doppler control on the base of oligohydramnios criteria by Phelan. The analysis was based on KOMPOR software created by ITAM Zabrze based on PC computer connected to Hewlett-Packard Series 50A cardiotocograph. Significant short-term variability increase just after amnioinfusion procedure from 5.55 ms to 8.24 ms and after 24 hours up to 7.25 ms was found, while significant long-term variability values changes were not observed.

Effect of losartan on ambulatory short-term blood pressure variability and cardiovascular remodeling in hypertensive patients on hemodialysis.

PubMed

Mitsuhashi, Hiroshi; Tamura, Kouichi; Yamauchi, Junji; Ozawa, Motoko; Yanagi, Mai; Dejima, Toru; Wakui, Hiromichi; Masuda, Shin-ichiro; Azuma, Koichi; Kanaoka, Tomohiko; Ohsawa, Masato; Maeda, Akinobu; Tsurumi-Ikeya, Yuko; Okano, Yasuko; Ishigami, Tomoaki; Toya, Yoshiyuki; Tokita, Yasuo; Ohnishi, Toshimasa; Umemura, Satoshi

2009-11-01

Previous studies have shown increases in ambulatory short-term blood pressure (BP) variability to be related to cardiovascular disease. In this study, we examined whether an angiotensin II type 1 receptor blocker losartan would improve ambulatory short-term BP variability in hypertensive patients on hemodialysis. Forty hypertensive patients on hemodialysis therapy were randomly assigned to the losartan treatment group (n=20) or the control treatment group (n=20). At baseline and 6 and 12 months after the treatment, 24-h ambulatory BP monitoring was performed. Echocardiography and measurements of brachial-ankle pulse wave velocity (baPWV) and biochemical parameters were also performed before and after therapy. After 6- and 12-months of treatment, nighttime short-term BP variability, assessed on the basis of the coefficient of variation of ambulatory BP, was significantly decreased in the losartan group, but remained unchanged in the control group. Compared with the control group, losartan significantly decreased left ventricular mass index (LVMI), baPWV, and the plasma levels of brain natriuretic peptide and advanced glycation end products (AGE). Furthermore, multiple regression analysis showed significant correlations between changes in LVMI and changes in nighttime short-term BP variability, as well as between changes in LVMI and changes in the plasma levels of AGE. These results suggest that losartan is beneficial for the suppression of pathological cardiovascular remodeling though its inhibitory effect on ambulatory short-term BP variability during nighttime.

Application of Remote Sensing to Assess the Impact of Short Term Climate Variability on Coastal Sedimentation

NASA Technical Reports Server (NTRS)

Moeller, Christopher C.; Gunshor, Mathew M.; Menzel, W. Paul; Huh, Oscar K.; Walker, Nan D.; Rouse, Lawrence J.; Frey, Herbert V. (Technical Monitor)

2001-01-01

The University of Wisconsin and Louisiana State University have teamed to study the forcing of winter season cold frontal wind systems on sediment distribution patterns and geomorphology in the Louisiana coastal zone. Wind systems associated with cold fronts have been shown to modify coastal circulation and resuspend sediments along the microtidal Louisiana coast. The assessment includes quantifying the influence of cumulative winter season atmospheric forcing (through surface wind observations) from year to year in response to short term climate variability, such as El Nino events. A correlation between winter cyclone frequency and the strength of El Nino events has been suggested. The atmospheric forcing data are being correlated to geomorphic measurements along western Louisiana's prograding muddy coast. Remote sensing data is being used to map and track sediment distribution patterns for various wind conditions. Transferring a suspended sediment concentration (SSC) algorithm to EOS MODIS observations will enable estimates of SSC in case 2 waters over the global domain. Progress in Year 1 of this study has included data collection and analysis of wind observations for atmospheric forcing characterization, a field activity (TX-2001) to collect in situ water samples with co-incident remote sensing measurements from the NASA ER-2 based MODIS Airborne Simulator (MAS) and the EOS Terra based MODerate resolution Imaging Spectroradiometer (MODIS) instruments, aerial photography and of sediment burial pipe field measurements along the prograding muddy Chenier Plain coast of western Louisiana for documenting coastal change in that dynamic region, and routine collection of MODIS 250 in resolution data for monitoring coastal sediment patterns. The data sets are being used in a process to transfer an SSC estimation algorithm to the MODIS platform. Work is underway on assessing coastal transport for the winter 2000-01 season. Water level data for use in a Geomorphic Impact

Short-term variability in particle flux: Storms, blooms and river discharge in a coastal sea

NASA Astrophysics Data System (ADS)

Johannessen, Sophia C.; Macdonald, Robie W.; Wright, Cynthia A.; Spear, David J.

2017-07-01

's organic carbon during a single collection interval (12 days). As short-term climate variability increases in a warming climate , the importance of these sorts of events is likely to increase in the future, particularly in coastal waters that are strongly influenced by river discharge.

Short-term climate changes in the Holsteinian Interglacial - EGU2012-132

NASA Astrophysics Data System (ADS)

Nitychoruk, J.; Bińka, K.; Ruppert, H.; Tudryn, A.

2012-04-01

Oxygen and carbon stable isotopes from fossil lake sediments of the Holsteinian age (eastern Poland) give evidence for the abrupt climate shifts in this interglacial that coincide with the changes in vegetation inferred from palaeobotanical data. Especially changes of the stable isotope ratios as well as decrease in the carbonate content in the deposits and increase in silicate redeposited from the area around the lake are synchronous with the short-term climatic deteriorations within the interglacial pollen flora. Two distinct climate shifts are recorded in the Holsteinian. The first one is marked by the very characteristic pine-birch cold phase after the yew (Taxus) domination that is reported from numerous pollen diagrams from Central Europe. This distinct cooling resembles a phenomenon known as 8.2 ka event in the Holocene, when waters of the Agassiz Lake in North America drained into the Atlantic Ocean (Koutsodendris et al. 2010). Enormous volumes of freshwater from melting of the Laurentian ice-sheet caused disturbances in the Gulf Stream and as a result some decrease in regional temperatures. The second distinct cooling of a lower rank took place within the younger part of the climatic optimum of the Holsteinian. It is relatively less known, because most often pollen records lack sufficient temporal resolution needed to identify this event. A well documented cooling in the Holsteinian deposits from Dethlingen, northern Germany (Koutsodendris et al. 2010) and from the Ossówka, eastern Poland (Nitychoruk et al. 2005) are exceptional. In the sequence from Dethlingen, a distinct increase in the percentage of pioneer trees is accompanied by a lower content of temperate taxa. At Ossówka, the shift of climate is noted as the rise of ratio of oxygen and carbon isotopes. According to Nitychoruk (2000) the cold event is coincident with volcanic eruptions evidenced by volcanic ash found in the lake deposits at that time. Literature Koutsodendris, A., Müller, U

Association between climate variability and malaria epidemics in the East African highlands.

PubMed

Zhou, Guofa; Minakawa, Noboru; Githeko, Andrew K; Yan, Guiyun

2004-02-24

The causes of the recent reemergence of Plasmodium falciparum epidemic malaria in the East African highlands are controversial. Regional climate changes have been invoked as a major factor; however, assessing the impact of climate in malaria resurgence is difficult due to high spatial and temporal climate variability and the lack of long-term data series on malaria cases from different sites. Climate variability, defined as short-term fluctuations around the mean climate state, may be epidemiologically more relevant than mean temperature change, but its effects on malaria epidemics have not been rigorously examined. Here we used nonlinear mixed-regression model to investigate the association between autoregression (number of malaria outpatients during the previous time period), seasonality and climate variability, and the number of monthly malaria outpatients of the past 10-20 years in seven highland sites in East Africa. The model explained 65-81% of the variance in the number of monthly malaria outpatients. Nonlinear and synergistic effects of temperature and rainfall on the number of malaria outpatients were found in all seven sites. The net variance in the number of monthly malaria outpatients caused by autoregression and seasonality varied among sites and ranged from 18 to 63% (mean=38.6%), whereas 12-63% (mean=36.1%) of variance is attributed to climate variability. Our results suggest that there was a high spatial variation in the sensitivity of malaria outpatient number to climate fluctuations in the highlands, and that climate variability played an important role in initiating malaria epidemics in the East African highlands.

Thermal barriers constrain microbial elevational range size via climate variability.

PubMed

Wang, Jianjun; Soininen, Janne

2017-08-01

Range size is invariably limited and understanding range size variation is an important objective in ecology. However, microbial range size across geographical gradients remains understudied, especially on mountainsides. Here, the patterns of range size of stream microbes (i.e., bacteria and diatoms) and macroorganisms (i.e., macroinvertebrates) along elevational gradients in Asia and Europe were examined. In bacteria, elevational range size showed non-significant phylogenetic signals. In all taxa, there was a positive relationship between niche breadth and species elevational range size, driven by local environmental and climatic variables. No taxa followed the elevational Rapoport's rule. Climate variability explained the most variation in microbial mean elevational range size, whereas local environmental variables were more important for macroinvertebrates. Seasonal and annual climate variation showed negative effects, while daily climate variation had positive effects on community mean elevational range size for all taxa. The negative correlation between range size and species richness suggests that understanding the drivers of range is key for revealing the processes underlying diversity. The results advance the understanding of microbial species thermal barriers by revealing the importance of seasonal and diurnal climate variation, and highlight that aquatic and terrestrial biota may differ in their response to short- and long-term climate variability. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

Statistical downscaling of precipitation using long short-term memory recurrent neural networks

NASA Astrophysics Data System (ADS)

Misra, Saptarshi; Sarkar, Sudeshna; Mitra, Pabitra

2017-11-01

Hydrological impacts of global climate change on regional scale are generally assessed by downscaling large-scale climatic variables, simulated by General Circulation Models (GCMs), to regional, small-scale hydrometeorological variables like precipitation, temperature, etc. In this study, we propose a new statistical downscaling model based on Recurrent Neural Network with Long Short-Term Memory which captures the spatio-temporal dependencies in local rainfall. The previous studies have used several other methods such as linear regression, quantile regression, kernel regression, beta regression, and artificial neural networks. Deep neural networks and recurrent neural networks have been shown to be highly promising in modeling complex and highly non-linear relationships between input and output variables in different domains and hence we investigated their performance in the task of statistical downscaling. We have tested this model on two datasets—one on precipitation in Mahanadi basin in India and the second on precipitation in Campbell River basin in Canada. Our autoencoder coupled long short-term memory recurrent neural network model performs the best compared to other existing methods on both the datasets with respect to temporal cross-correlation, mean squared error, and capturing the extremes.

Glacier foreland colonisation: distinguishing between short-term and long-term effects of climate change.

PubMed

Kaufmann, Rüdiger

2002-02-01

By comparing short-term (6 years) observations with long-term (>100 years) community changes reconstructed from the chronosequence along a glacier foreland, I show that the colonisation of recently deglaciated terrain by invertebrates may constitute a process reacting sensitively to temperature fluctuations. Early colonising stages (<30 years old) currently develop faster, and intermediate successional stages (30-50 years old) slower, than would be indicated by the long-term chronosequence pattern. These differences between the chronosequence approach and direct observation can be explained by a simple model relating the rate of community evolution to the temperature record. It would mean that an increase of 0.6°C in summer temperatures approximately doubled the speed of initial colonisation, whereas later successional stages were less sensitive to climate change. The present situation appears to result from unusually warm summers around 1950 and a warm period accelerating glacier retreat since 1980. In contrast to the long-term trend, all except the youngest communities have suffered a loss in diversity in recent years.

Ambulatory blood pressure monitoring-derived short-term blood pressure variability is increased in Cushing's syndrome.

PubMed

Rebellato, Andrea; Grillo, Andrea; Dassie, Francesca; Sonino, Nicoletta; Maffei, Pietro; Martini, Chiara; Paoletta, Agostino; Fabris, Bruno; Carretta, Renzo; Fallo, Francesco

2014-11-01

Cushing's syndrome is associated with high cardiovascular morbility and mortality. Blood pressure (BP) variability within a 24-h period is increasingly recognized as an independent predictor of cardiovascular risk. The aim of our study was to investigate the short-term BP variability indices in Cushing's syndrome. Twenty-five patients with Cushing's syndrome (mean age 49 ± 13 years, 4 males; 21 Cushing's disease and 4 adrenal adenoma patients) underwent 24-h ambulatory BP monitoring (ABPM) and evaluation of cardiovascular risk factors. Cushing patients were divided into 8 normotensive (NOR-CUSH) and 17 hypertensive (HYP-CUSH) patients and were compared with 20 normotensive (NOR-CTR) and 20 hypertensive (HYP-CTR) age-, sex-, and BMI-matched control subjects. Short-term BP variability was derived from ABPM and calculated as the following: (1) standard deviation (SD) of 24-h, daytime, and nighttime BP; (2) 24-h weighted SD of BP; and (3) average real variability (ARV), i.e., the average of the absolute differences between consecutive BP measurements over 24 h. In comparison with controls, patients with Cushing's syndrome, either normotensive or hypertensive, had higher 24-h and daytime SD of BP, as well as higher 24-h weighted SD and ARV of BP (P = 0.03 to P < 0.0001). No difference in metabolic parameters was observed between NOR-CTR and NOR-CUSH or between HYP-CTR and HYP-CUSH subgroups. ABPM-derived short-term BP variability is increased in Cushing's syndrome, independent of BP elevation. It may represent an additional cardiovascular risk factor in this disease. The role of excess cortisol in BP variability has to be further clarified.

Metabolic Syndrome and Short-Term Heart Rate Variability in Adults with Intellectual Disabilities

ERIC Educational Resources Information Center

Chang, Yaw-Wen; Lin, Jin-Ding; Chen, Wei-Liang; Yen, Chia-Feng; Loh, Ching-Hui; Fang, Wen-Hui; Wu, Li-Wei

2012-01-01

Metabolic syndrome (MetS) increases the risk of cardiovascular events. Heart rate variability (HRV) represents autonomic functioning, and reduced HRV significantly increases cardiovascular mortality. The aims of the present paper are to assess the prevalence of MetS in adults with intellectual disabilities (ID), the difference in short-term HRV…

Climate Variability and Ecosystem Response

Treesearch

David Greenland; Lloyd W. Swift; [Editors

1990-01-01

Nine papers describe studies of climate variability and ecosystem response. The studies were conducted at LTER (Long-Term Ecological Research) sites representing forest, agricultural, and aquatic ecosystems and systems in which extreme climates limit vegetational cover. An overview paper prepared by the LTER Climate Committee stresses the importance of (1) clear...

Major modes of short-term climate variability in the newly developed NUIST Earth System Model (NESM)

NASA Astrophysics Data System (ADS)

Cao, Jian; Wang, Bin; Xiang, Baoqiang; Li, Juan; Wu, Tianjie; Fu, Xiouhua; Wu, Liguang; Min, Jinzhong

2015-05-01

A coupled earth system model (ESM) has been developed at the Nanjing University of Information Science and Technology (NUIST) by using version 5.3 of the European Centre Hamburg Model (ECHAM), version 3.4 of the Nucleus for European Modelling of the Ocean (NEMO), and version 4.1 of the Los Alamos sea ice model (CICE). The model is referred to as NUIST ESM1 (NESM1). Comprehensive and quantitative metrics are used to assess the model's major modes of climate variability most relevant to subseasonal-to-interannual climate prediction. The model's assessment is placed in a multi-model framework. The model yields a realistic annual mean and annual cycle of equatorial SST, and a reasonably realistic precipitation climatology, but has difficulty in capturing the spring-fall asymmetry and monsoon precipitation domains. The ENSO mode is reproduced well with respect to its spatial structure, power spectrum, phase locking to the annual cycle, and spatial structures of the central Pacific (CP)-ENSO and eastern Pacific (EP)-ENSO; however, the equatorial SST variability, biennial component of ENSO, and the amplitude of CP-ENSO are overestimated. The model captures realistic intraseasonal variability patterns, the vertical-zonal structures of the first two leading predictable modes of Madden-Julian Oscillation (MJO), and its eastward propagation; but the simulated MJO speed is significantly slower than observed. Compared with the T42 version, the high resolution version (T159) demonstrates improved simulation with respect to the climatology, interannual variance, monsoon-ENSO lead-lag correlation, spatial structures of the leading mode of the Asian-Australian monsoon rainfall variability, and the eastward propagation of the MJO.

Does climate variability influence the demography of wild primates? Evidence from long-term life-history data in seven species.

PubMed

Campos, Fernando A; Morris, William F; Alberts, Susan C; Altmann, Jeanne; Brockman, Diane K; Cords, Marina; Pusey, Anne; Stoinski, Tara S; Strier, Karen B; Fedigan, Linda M

2017-11-01

Earth's rapidly changing climate creates a growing need to understand how demographic processes in natural populations are affected by climate variability, particularly among organisms threatened by extinction. Long-term, large-scale, and cross-taxon studies of vital rate variation in relation to climate variability can be particularly valuable because they can reveal environmental drivers that affect multiple species over extensive regions. Few such data exist for animals with slow life histories, particularly in the tropics, where climate variation over large-scale space is asynchronous. As our closest relatives, nonhuman primates are especially valuable as a resource to understand the roles of climate variability and climate change in human evolutionary history. Here, we provide the first comprehensive investigation of vital rate variation in relation to climate variability among wild primates. We ask whether primates are sensitive to global changes that are universal (e.g., higher temperature, large-scale climate oscillations) or whether they are more sensitive to global change effects that are local (e.g., more rain in some places), which would complicate predictions of how primates in general will respond to climate change. To address these questions, we use a database of long-term life-history data for natural populations of seven primate species that have been studied for 29-52 years to investigate associations between vital rate variation, local climate variability, and global climate oscillations. Associations between vital rates and climate variability varied among species and depended on the time windows considered, highlighting the importance of temporal scale in detection of such effects. We found strong climate signals in the fertility rates of three species. However, survival, which has a greater impact on population growth, was little affected by climate variability. Thus, we found evidence for demographic buffering of life histories, but also

Short-term vs. long-term heart rate variability in ischemic cardiomyopathy risk stratification.

PubMed

Voss, Andreas; Schroeder, Rico; Vallverdú, Montserrat; Schulz, Steffen; Cygankiewicz, Iwona; Vázquez, Rafael; Bayés de Luna, Antoni; Caminal, Pere

2013-01-01

In industrialized countries with aging populations, heart failure affects 0.3-2% of the general population. The investigation of 24 h-ECG recordings revealed the potential of nonlinear indices of heart rate variability (HRV) for enhanced risk stratification in patients with ischemic heart failure (IHF). However, long-term analyses are time-consuming, expensive, and delay the initial diagnosis. The objective of this study was to investigate whether 30 min short-term HRV analysis is sufficient for comparable risk stratification in IHF in comparison to 24 h-HRV analysis. From 256 IHF patients [221 at low risk (IHFLR) and 35 at high risk (IHFHR)] (a) 24 h beat-to-beat time series (b) the first 30 min segment (c) the 30 min most stationary day segment and (d) the 30 min most stationary night segment were investigated. We calculated linear (time and frequency domain) and nonlinear HRV analysis indices. Optimal parameter sets for risk stratification in IHF were determined for 24 h and for each 30 min segment by applying discriminant analysis on significant clinical and non-clinical indices. Long- and short-term HRV indices from frequency domain and particularly from nonlinear dynamics revealed high univariate significances (p < 0.01) discriminating between IHFLR and IHFHR. For multivariate risk stratification, optimal mixed parameter sets consisting of 5 indices (clinical and nonlinear) achieved 80.4% AUC (area under the curve of receiver operating characteristics) from 24 h HRV analysis, 84.3% AUC from first 30 min, 82.2 % AUC from daytime 30 min and 81.7% AUC from nighttime 30 min. The optimal parameter set obtained from the first 30 min showed nearly the same classification power when compared to the optimal 24 h-parameter set. As results from stationary daytime and nighttime, 30 min segments indicate that short-term analyses of 30 min may provide at least a comparable risk stratification power in IHF in comparison to a 24 h analysis period.

Short-Term Effects of Climatic Variables on Hand, Foot, and Mouth Disease in Mainland China, 2008-2013: A Multilevel Spatial Poisson Regression Model Accounting for Overdispersion.

PubMed

Liao, Jiaqiang; Yu, Shicheng; Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying

2016-01-01

Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008-2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse "V" shape and "V" shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic variables spatial heterogeneity distributed across

Short-Term Variability on the Scotian Shelf

NASA Astrophysics Data System (ADS)

Greenan, B.; Petrie, B.; Harrison, G.; Oakey, N.; Strain, P.

2002-12-01

The traditional view of the production cycle on the continental shelf of Nova Scotia features a spring bloom followed by a period of low production and a less intense fall bloom. The annual cycle of primary productivity thus has a large, low frequency component. However, there is increasing evidence that the production cycle has significant variability on shorter time scales. Physical, chemical and biological variability on the Scotian Shelf is examined on a daily to weekly timescale. This is accomplished through the use of a newly developed mooring platform (SeaHorse) that uses surface wave energy to enable the instrument to climb down the mooring wire and then float upwards while sampling the water column. This provides bi-hourly profiles of temperature, salinity, pressure and chlorophyll at one location over month-long periods. Results from the three-week deployment in October 2000 indicate a subsurface chlorophyll maximum below the pycnocline during the first part of the time series. An event occurred in mid-October during which the temperature, salinity and density iso-surfaces rose approximately 25 m. During this event, a small bloom, with peak chlorophyll concentrations of about 2 mg m-3 and duration of several days, began as nutrients were brought into the upper part of the water column by upwelling-favorable winds. SeaWiFS ocean color satellite images were valuable in providing a spatial context for chlorophyll concentrations, however, the lack of temporal resolution due to poor quality images means that this data set provided limited information for short-term chlorophyll variability. Gradient Richardson Numbers were estimated for 2 m vertical bins using SeaHorse CTD data and nearby ADCP current measurements. A trend of decreasing Ri in the ocean mixed layer with increasing surface wind stress is suggested.

Variability of Short-term Precipitation and Runoff in Small Czech Drainage Basins

NASA Astrophysics Data System (ADS)

Kavka, Petr; Strouhal, Luděk; Landa, Martin; Neuman, Martin; Kožant, Petr; Muller, Miloslav

2016-04-01

The aim of this contribution is to introduce the recently started three year's project named "Variability of Short-term Precipitation and Runoff in Small Czech Drainage Basins and its Influence on Water Resources Management". Its main goal is to elaborate a methodology and online utility for deriving short-term design precipitation series, which could be utilized by a broad community of scientists, state administration as well as design planners. The outcomes of the project will especially be helpful in modelling hydrological or soil erosion problems when designing common measures for promoting water retention or landscape drainage systems in or out of the scope of Landscape consolidation projects. The precipitation scenarios will be derived from 10 years of observed data from point gauging stations and radar data. The analysis is focused on events' return period, rainfall total amount, internal intensity distribution and spatial distribution over the area of Czech Republic. The methodology will account for the choice of the simulation model. Several representatives of practically oriented models will be tested for the output sensitivity to selected precipitation scenario comparing to variability connected with other inputs uncertainty. The variability of the outputs will also be assessed in the context of economic impacts in design of landscape water structures or mitigation measures. The research was supported by the grant QJ1520265 of the Czech Ministry of Agriculture, using data provided by the Czech Hydrometeorological Institute.

Short-term variability and mass loss in Be stars. II. Physical taxonomy of photometric variability observed by the Kepler spacecraft

NASA Astrophysics Data System (ADS)

Rivinius, Th.; Baade, D.; Carciofi, A. C.

2016-09-01

Context. Classical Be stars have been established as pulsating stars. Space-based photometric monitoring missions contributed significantly to that result. However, whether Be stars are just rapidly rotating SPB or β Cep stars, or whether they have to be understood differently, remains debated in the view of their highly complex power spectra. Aims: Kepler data of three known Be stars are re-visited to establish their pulsational nature and assess the properties of additional, non-pulsational variations. The three program stars turned out to be one inactive Be star, one active, continuously outbursting Be star, and one Be star transiting from a non-outbursting into an outbursting phase, thus forming an excellent sample to distill properties of Be stars in the various phases of their life-cycle. Methods: The Kepler data was first cleaned from any long-term variability with Lomb-Scargle based pre-whitening. Then a Lomb-Scargle analysis of the remaining short-term variations was compared to a wavelet analysis of the cleaned data. This offers a new view on the variability, as it enables us to see the temporal evolution of the variability and phase relations between supposed beating phenomena, which are typically not visualized in a Lomb-Scargle analysis. Results: The short-term photometric variability of Be stars must be disentangled into a stellar and a circumstellar part. The stellar part is on the whole not different from what is seen in non-Be stars. However, some of the observed phenomena might be to be due to resonant mode coupling, a mechanism not typically considered for B-type stars. Short-term circumstellar variability comes in the form of either a group of relatively well-defined, short-lived frequencies during outbursts, which are called Štefl frequencies, and broad bumps in the power spectra, indicating aperiodic variability on a time scale similar to typical low-order g-mode pulsation frequencies, rather than true periodicity. Conclusions: From a

Climate Variability and Yields of Major Staple Food Crops in Northern Ghana

NASA Astrophysics Data System (ADS)

Amikuzuno, J.

2012-12-01

Climate variability, the short-term fluctuations in average weather conditions, and agriculture affect each other. Climate variability affects the agroecological and growing conditions of crops and livestock, and is recently believed to be the greatest impediment to the realisation of the first Millennium Development Goal of reducing poverty and food insecurity in arid and semi-arid regions of developing countries. Conversely, agriculture is a major contributor to climate variability and change by emitting greenhouse gases and reducing the agroecology's potential for carbon sequestration. What however, is the empirical evidence of this inter-dependence of climate variability and agriculture in Sub-Sahara Africa? In this paper, we provide some insight into the long run relationship between inter-annual variations in temperature and rainfall, and annual yields of the most important staple food crops in Northern Ghana. Applying pooled panel data of rainfall, temperature and yields of the selected crops from 1976 to 2010 to cointegration and Granger causality models, there is cogent evidence of cointegration between seasonal, total rainfall and crop yields; and causality from rainfall to crop yields in the Sudano-Guinea Savannah and Guinea Savannah zones of Northern Ghana. This suggests that inter-annual yields of the crops have been influenced by the total mounts of rainfall in the planting season. Temperature variability over the study period is however stationary, and is suspected to have minimal effect if any on crop yields. Overall, the results confirm the appropriateness of our attempt in modelling long-term relationships between the climate and crop yield variables.

Evolution of extreme temperature events in short term climate projection for Iberian Peninsula.

NASA Astrophysics Data System (ADS)

Rodriguez, Alfredo; Tarquis, Ana M.; Sanchez, Enrique; Dosio, Alessandro; Ruiz-Ramos, Margarita

2014-05-01

Extreme events of maximum and minimum temperatures are a main hazard for agricultural production in Iberian Peninsula. For this purpose, in this study we analyze projections of their evolution that could be valid for the next decade, represented in this study by the 30-year period 2004-2034 (target period). For this purpose two kinds of data were used in this study: 1) observations from the station network of AEMET (Spanish National Meteorological Agency) for five Spanish locations, and 2) simulated data at a resolution of 50 ×50 km horizontal grid derived from the outputs of twelve Regional Climate Models (RCMs) taken from project ENSEMBLES (van der Linden and Mitchell, 2009), with a bias correction (Dosio and Paruolo, 2011; Dosio et al., 2012) regarding the observational dataset Spain02 (Herrera et al., 2012). To validate the simulated climate, the available period of observations was compared to a baseline period (1964-1994) of simulated climate for all locations. Then, to analyze the changes for the present/very next future, probability of extreme temperature events for 2004-2034 were compared to that of the baseline period. Although only minor changes are expected, small variations in variability may have a significant impact in crop performance. The objective of the work is to evaluate the utility of these short term projections for potential users, as for instance insurance companies. References Dosio A. and Paruolo P., 2011. Bias correction of the ENSEMBLES high-resolution climate change projections for use by impact models: Evaluation on the present climate. Journal of Geophysical Research, VOL. 116,D16106, doi:10.1029/2011JD015934 Dosio A., Paruolo P. and Rojas R., 2012. Bias correction of the ENSEMBLES high resolution climate change projections for use by impact models: Analysis of the climate change signal. Journal of Geophysical Research,Volume 117, D17, doi: 0.1029/2012JD017968 Herrera et. al. (2012) Development and Analysis of a 50 year high

Short-term spatial and temporal variability in greenhouse gas fluxes in riparian zones.

PubMed

Vidon, P; Marchese, S; Welsh, M; McMillan, S

2015-08-01

Recent research indicates that riparian zones have the potential to contribute significant amounts of greenhouse gases (GHG: N2O, CO2, CH4) to the atmosphere. Yet, the short-term spatial and temporal variability in GHG emission in these systems is poorly understood. Using two transects of three static chambers at two North Carolina agricultural riparian zones (one restored, one unrestored), we show that estimates of the average GHG flux at the site scale can vary by one order of magnitude depending on whether the mean or the median is used as a measure of central tendency. Because the median tends to mute the effect of outlier points (hot spots and hot moments), we propose that both must be reported or that other more advanced spatial averaging techniques (e.g., kriging, area-weighted average) should be used to estimate GHG fluxes at the site scale. Results also indicate that short-term temporal variability in GHG fluxes (a few days) under seemingly constant temperature and hydrological conditions can be as large as spatial variability at the site scale, suggesting that the scientific community should rethink sampling protocols for GHG at the soil-atmosphere interface to include repeated measures over short periods of time at select chambers to estimate GHG emissions in the field. Although recent advances in technology provide tools to address these challenges, their cost is often too high for widespread implementation. Until technology improves, sampling design strategies will need to be carefully considered to balance cost, time, and spatial and temporal representativeness of measurements.

The impact of short term synaptic depression and stochastic vesicle dynamics on neuronal variability

PubMed Central

Reich, Steven

2014-01-01

Neuronal variability plays a central role in neural coding and impacts the dynamics of neuronal networks. Unreliability of synaptic transmission is a major source of neural variability: synaptic neurotransmitter vesicles are released probabilistically in response to presynaptic action potentials and are recovered stochastically in time. The dynamics of this process of vesicle release and recovery interacts with variability in the arrival times of presynaptic spikes to shape the variability of the postsynaptic response. We use continuous time Markov chain methods to analyze a model of short term synaptic depression with stochastic vesicle dynamics coupled with three different models of presynaptic spiking: one model in which the timing of presynaptic action potentials are modeled as a Poisson process, one in which action potentials occur more regularly than a Poisson process (sub-Poisson) and one in which action potentials occur more irregularly (super-Poisson). We use this analysis to investigate how variability in a presynaptic spike train is transformed by short term depression and stochastic vesicle dynamics to determine the variability of the postsynaptic response. We find that sub-Poisson presynaptic spiking increases the average rate at which vesicles are released, that the number of vesicles released over a time window is more variable for smaller time windows than larger time windows and that fast presynaptic spiking gives rise to Poisson-like variability of the postsynaptic response even when presynaptic spike times are non-Poisson. Our results complement and extend previously reported theoretical results and provide possible explanations for some trends observed in recorded data. PMID:23354693

The potential influence of short-term environmental variability on the composition of testate amoeba communities in Sphagnum peatlands.

PubMed

Sullivan, Maura E; Booth, Robert K

2011-07-01

Testate amoebae are a group of moisture-sensitive, shell-producing protozoa that have been widely used as indicators of changes in mean water-table depth within oligotrophic peatlands. However, short-term environmental variability (i.e., sub-annual) also probably influences community composition. The objective of this study was to assess the potential influence of short-term environmental variability on the composition of testate amoeba communities in Sphagnum-dominated peatlands. Testate amoebae and environmental conditions, including hourly measurements of relative humidity within the upper centimeter of the peatland surface, were examined throughout the 2008 growing season at 72 microsites within 11 peatlands of Pennsylvania and Wisconsin, USA. Relationships among testate amoeba communities, vegetation, depth to water table, pH, and an index of short-term environmental variability (EVI), were examined using nonmetric multidimensional scaling and correlation analysis. Results suggest that EVI influences testate amoeba communities, with some taxa more abundant under highly variable conditions (e.g., Arcella discoides, Difflugia pulex, and Hyalosphenia subflava) and others more abundant when environmental conditions at the peatland surface were relatively stable (e.g., Archerella flavum and Bullinularia indica). The magnitude of environmental variability experienced at the peatland surface appears to be primarily controlled by vegetation composition and density. In particular, sites with dense Sphagnum cover had lower EVI values than sites with loose-growing Sphagnum or vegetation dominated by vascular plants and/or non-Sphagnum bryophytes. Our results suggest that more environmental information may be inferred from testate amoebae than previously recognized. Knowledge of relationships between testate amoebae and short-term environmental variability should lead to more detailed and refined environmental inferences.

Climate variability and vulnerability to climate change: a review

PubMed Central

Thornton, Philip K; Ericksen, Polly J; Herrero, Mario; Challinor, Andrew J

2014-01-01

The focus of the great majority of climate change impact studies is on changes in mean climate. In terms of climate model output, these changes are more robust than changes in climate variability. By concentrating on changes in climate means, the full impacts of climate change on biological and human systems are probably being seriously underestimated. Here, we briefly review the possible impacts of changes in climate variability and the frequency of extreme events on biological and food systems, with a focus on the developing world. We present new analysis that tentatively links increases in climate variability with increasing food insecurity in the future. We consider the ways in which people deal with climate variability and extremes and how they may adapt in the future. Key knowledge and data gaps are highlighted. These include the timing and interactions of different climatic stresses on plant growth and development, particularly at higher temperatures, and the impacts on crops, livestock and farming systems of changes in climate variability and extreme events on pest-weed-disease complexes. We highlight the need to reframe research questions in such a way that they can provide decision makers throughout the food system with actionable answers, and the need for investment in climate and environmental monitoring. Improved understanding of the full range of impacts of climate change on biological and food systems is a critical step in being able to address effectively the effects of climate variability and extreme events on human vulnerability and food security, particularly in agriculturally based developing countries facing the challenge of having to feed rapidly growing populations in the coming decades. PMID:24668802

Country-Specific Effects of Climate Variability on Human Migration

PubMed Central

Gray, Clark; Wise, Erika

2016-01-01

Involuntary human migration is among the social outcomes of greatest concern in the current era of global climate change. Responding to this concern, a growing number of studies have investigated the consequences of short to medium-term climate variability for human migration using demographic and econometric approaches. These studies have provided important insights, but at the same time have been significantly limited by lack of expertise in the use of climate data, access to cross-national data on migration, and attention to model specification. To address these limitations, we link data on internal and international migration over a 6-year period from 9,812 origin households in Kenya, Uganda, Nigeria, Burkina Faso and Senegal to high-resolution gridded climate data from both station and satellite sources. Analyses of these data using several plausible specifications reveal that climate variability has country-specific effects on migration: Migration tends to increase with temperature anomalies in Uganda, tends to decrease with temperature anomalies in Kenya and Burkina Faso, and shows no consistent relationship with temperature in Nigeria and Senegal. Consistent with previous studies, precipitation shows weak and inconsistent relationships with migration across countries. These results challenge generalizing narratives that foresee a consistent migratory response to climate change across the globe. PMID:27092012

Country-Specific Effects of Climate Variability on Human Migration.

PubMed

Gray, Clark; Wise, Erika

2016-04-01

Involuntary human migration is among the social outcomes of greatest concern in the current era of global climate change. Responding to this concern, a growing number of studies have investigated the consequences of short to medium-term climate variability for human migration using demographic and econometric approaches. These studies have provided important insights, but at the same time have been significantly limited by lack of expertise in the use of climate data, access to cross-national data on migration, and attention to model specification. To address these limitations, we link data on internal and international migration over a 6-year period from 9,812 origin households in Kenya, Uganda, Nigeria, Burkina Faso and Senegal to high-resolution gridded climate data from both station and satellite sources. Analyses of these data using several plausible specifications reveal that climate variability has country-specific effects on migration: Migration tends to increase with temperature anomalies in Uganda, tends to decrease with temperature anomalies in Kenya and Burkina Faso, and shows no consistent relationship with temperature in Nigeria and Senegal. Consistent with previous studies, precipitation shows weak and inconsistent relationships with migration across countries. These results challenge generalizing narratives that foresee a consistent migratory response to climate change across the globe.

Ambulatory blood pressure monitoring-derived short-term blood pressure variability in primary hyperparathyroidism.

PubMed

Concistrè, A; Grillo, A; La Torre, G; Carretta, R; Fabris, B; Petramala, L; Marinelli, C; Rebellato, A; Fallo, F; Letizia, C

2018-04-01

Primary hyperparathyroidism is associated with a cluster of cardiovascular manifestations, including hypertension, leading to increased cardiovascular risk. The aim of our study was to investigate the ambulatory blood pressure monitoring-derived short-term blood pressure variability in patients with primary hyperparathyroidism, in comparison with patients with essential hypertension and normotensive controls. Twenty-five patients with primary hyperparathyroidism (7 normotensive,18 hypertensive) underwent ambulatory blood pressure monitoring at diagnosis, and fifteen out of them were re-evaluated after parathyroidectomy. Short-term-blood pressure variability was derived from ambulatory blood pressure monitoring and calculated as the following: 1) Standard Deviation of 24-h, day-time and night-time-BP; 2) the average of day-time and night-time-Standard Deviation, weighted for the duration of the day and night periods (24-h "weighted" Standard Deviation of BP); 3) average real variability, i.e., the average of the absolute differences between all consecutive BP measurements. Baseline data of normotensive and essential hypertension patients were matched for age, sex, BMI and 24-h ambulatory blood pressure monitoring values with normotensive and hypertensive-primary hyperparathyroidism patients, respectively. Normotensive-primary hyperparathyroidism patients showed a 24-h weighted Standard Deviation (P < 0.01) and average real variability (P < 0.05) of systolic blood pressure higher than that of 12 normotensive controls. 24-h average real variability of systolic BP, as well as serum calcium and parathyroid hormone levels, were reduced in operated patients (P < 0.001). A positive correlation of serum calcium and parathyroid hormone with 24-h-average real variability of systolic BP was observed in the entire primary hyperparathyroidism patients group (P = 0.04, P  = 0.02; respectively). Systolic blood pressure variability is increased in normotensive

[Glycemic variability and short-term outcome in critically ill].

PubMed

Zhang, L P; Guo, Y B; Zhou, L H

2016-06-07

To analyze the association of blood glucose variability and short-term outcome in critically ill. The retrospective study including 552 patients admitted to the Affiliated Hospital of Inner Mongolia Medical University from January 2013 to March 2015. The initial blood glucose (GluAdm), the first 24 hours average blood glucose(GluMV1d) and glycemic lability index(GLI1d), 72-hour average blood glucose (GluMV3d) and glycemic lability index(GLI3d) were recorded. The receiver operating characteristic curve (ROC curve) was applied to evaluate the association between GluAdm, GLI1d, GLI3d and APACHE Ⅱ score and prognosis. The levels of APACHE Ⅱ, GluAdm, GLI 1d, GLI 3d of nonsurvivors were higher than those of survivors[(23.2±5.2) vs (16.7±4.4), (12.3±5.2)mmol/L vs(9.2±2.2)mmol/L, (23.3±12.2)vs(12.3±11.1), (21.6±19.3)vs(13.2±9.9), P<0.05]; there was no statistically significant difference between GluMV1d and GluMV3d; when ROC was applied, and the area under the curve (AUC) of APACHEⅡ, GLI1d and GLI3d were 0.826±0.035, 0.726±0.052 and 0.786±0.046, which were significantly higher than the GluMV1d and GluMV3d (0.412±0.031, 0.425±0.026, P<0.05) .It is correlated between GluAdm, GLI1d, GLI3d and the 28-day mortality, ICU days and total time of hospitalization. Blood glucose variability is closely related with the mortality in critical ill patients, GLI1d, GLI3d and APACHEⅡ score of critically ill patients have a similar predictive value in the short-term prognosis.

Short-term blood pressure variability over 24 h and target organ damage in middle-aged men and women.

PubMed

Madden, J M; O'Flynn, A M; Dolan, E; Fitzgerald, A P; Kearney, P M

2015-12-01

Blood pressure variability (BPV) has been associated with cardiovascular events; however, the prognostic significance of short-term BPV remains uncertain. As uncertainty also remains as to which measure of variability most accurately describes short-term BPV, this study explores different indices and investigates their relationship with subclinical target organ damage (TOD). We used data from the Mitchelstown Study, a cross-sectional study of Irish adults aged 47-73 years (n=2047). A subsample (1207) underwent 24-h ambulatory BP monitoring (ABPM). As measures of short-term BPV, we estimated the s.d., weighted s.d. (wSD), coefficient of variation (CV) and average real variability (ARV). TOD was documented by microalbuminuria and electrocardiogram (ECG) left ventricular hypertrophy (LVH). There was no association found between any measure of BPV and LVH in both unadjusted and fully adjusted logistic regression models. Similar analysis found that ARV (24 h, day and night), s.d. (day and night) and wSD were all univariately associated with microalbuminuria and remained associated after adjustment for age, gender, smoking, body mass index (BMI), diabetes and antihypertensive treatment. However, when the models were further adjusted for the mean BP the association did not persist for all indices. Our findings illustrate choosing the appropriate summary measure, which accurately captures that short-term BPV is difficult. Despite discrepancies in values between the different measures, there was no association between any indexes of variability with TOD measures after adjustment for the mean BP.

Modeling Long-Term Fluvial Incision : Shall we Care for the Details of Short-Term Fluvial Dynamics?

NASA Astrophysics Data System (ADS)

Lague, D.; Davy, P.

2008-12-01

Fluvial incision laws used in numerical models of coupled climate, erosion and tectonics systems are mainly based on the family of stream power laws for which the rate of local erosion E is a power function of the topographic slope S and the local mean discharge Q : E = K Qm Sn. The exponents m and n are generally taken as (0.35, 0.7) or (0.5, 1), and K is chosen such that the predicted topographic elevation given the prevailing rates of precipitation and tectonics stay within realistic values. The resulting topographies are reasonably realistic, and the coupled system dynamics behaves somehow as expected : more precipitation induces increased erosion and localization of the deformation. Yet, if we now focus on smaller scale fluvial dynamics (the reach scale), recent advances have suggested that discharge variability, channel width dynamics or sediment flux effects may play a significant role in controlling incision rates. These are not factored in the simple stream power law model. In this work, we study how these short- term details propagate into long-term incision dynamics within the framework of surface/tectonics coupled numerical models. To upscale the short term dynamics to geological timescales, we use a numerical model of a trapezoidal river in which vertical and lateral incision processes are computed from fluid shear stress at a daily timescale, sediment transport and protection effects are factored in, as well as a variable discharge. We show that the stream power law model might still be a valid model but that as soon as realistic effects are included such as a threshold for sediment transport, variable discharge and dynamic width the resulting exponents m and n can be as high as 2 and 4. This high non-linearity has a profound consequence on the sensitivity of fluvial relief to incision rate. We also show that additional complexity does not systematically translates into more non-linear behaviour. For instance, considering only a dynamical width

Short-Term Behavior of Slag Concretes Exposed to a Real In Situ Mediterranean Climate Environment.

PubMed

Ortega, José Marcos; Sánchez, Isidro; Cabeza, Marta; Climent, Miguel Ángel

2017-08-08

At present, one of the most suitable ways to get a more sustainable cement industry is to reduce the CO₂ emissions generated during cement production. In order to reach that goal, the use of ground granulated blast-furnace slag as clinker replacement is becoming increasingly popular. Although the effects of this addition in the properties of cementitious materials are influenced by their hardening conditions, there are not too many experimental studies in which slag concretes have been exposed to real in situ environments. Then, the main objective of this research is to study the short-term effects of exposure to real Mediterranean climate environment of an urban site, where the action of airborne chlorides from sea water and the presence of CO₂ are combined, in the microstructure and service properties of a commercial slag cement concrete, compared to ordinary Portland cement (OPC). The microstructure was studied with mercury intrusion porosimetry. The effective porosity, capillary suction coefficient, chloride migration coefficient, carbonation front depth, and compressive strength were also analyzed. Considering the results obtained, slag concretes exposed to a real in situ Mediterranean climate environment show good service properties in the short-term (180 days), in comparison with OPC.

Mediterranean dunes on the go: Evidence from a short term study on coastal herbaceous vegetation

NASA Astrophysics Data System (ADS)

Prisco, Irene; Stanisci, Angela; Acosta, Alicia T. R.

2016-12-01

Detailed monitoring studies on permanent sites are a promising tool for an accurate evaluation of short, medium or long term vegetation dynamics. This work aims to evaluate short-term changes in coastal dune herbaceous plant species and EU Habitats through a multi-temporal analysis using permanent vegetation transects. In particular, (I) we analyze changes in species richness of coastal habitats; (II) we identify changes in plant cover of selected focal plants; and (III) we relate the changes to selected climatic variables and erosion/accretion processes. We selected one of the Italian's peninsula best preserved coastal dune areas (ca. 50 km along the Adriatic sea) with a relatively homogeneous coastal zonation and low anthropic pressure but with different erosion/accretion processes. We explored changes in richness over time using generalized linear models (GLMs). We identified different ecological guilds: focal, ruderal and alien plant species and investigated temporal trends in these guilds' species richness. We also applied GLMs to determine how plant cover of the most important focal species have changed over time. Overall, in this study we observed that the influence of climatic variables was relatively small. However, we found remarkable different trends in response to erosion/accretion processes both at community and at species level. Thus, our results highlight the importance of coastal dynamics in preserving not only coastal vegetation zonation, but also species richness and focal species cover. Moreover, we identified the dune grasslands as the most sensitive habitat for detecting the influence of climatic variables throughout a short term monitoring survey. Information from this study provides useful insights for detecting changes in vegetation, for establishing habitat protection priorities and for improving conservation efforts for these fragile ecosystems.

Social Memory of Short-term and Long-term Variability in the Sahelian Climate

Treesearch

Roderick J. McIntosh

2006-01-01

The 170,000 km2 interior floodplain of the Middle Niger (Mali) is a tight mosaic of alluvial and desert microenvironments. The interannual to intermillennial climate change profiles of this fluvial anomaly thrust deep into the Sahel and southern Sahara are masterpieces of abrupt phase shifts and unpredictability. Response has been of two kinds. The Office du Niger was...

Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment?

NASA Astrophysics Data System (ADS)

Quesada-Montano, Beatriz; Westerberg, Ida K.; Fuentes-Andino, Diana; Hidalgo-Leon, Hugo; Halldin, Sven

2017-04-01

Long-term hydrological data are key to understanding catchment behaviour and for decision making within water management and planning. Given the lack of observed data in many regions worldwide, hydrological models are an alternative for reproducing historical streamflow series. Additional types of information - to locally observed discharge - can be used to constrain model parameter uncertainty for ungauged catchments. Climate variability exerts a strong influence on streamflow variability on long and short time scales, in particular in the Central-American region. We therefore explored the use of climate variability knowledge to constrain the simulated discharge uncertainty of a conceptual hydrological model applied to a Costa Rican catchment, assumed to be ungauged. To reduce model uncertainty we first rejected parameter relationships that disagreed with our understanding of the system. We then assessed how well climate-based constraints applied at long-term, inter-annual and intra-annual time scales could constrain model uncertainty. Finally, we compared the climate-based constraints to a constraint on low-flow statistics based on information obtained from global maps. We evaluated our method in terms of the ability of the model to reproduce the observed hydrograph and the active catchment processes in terms of two efficiency measures, a statistical consistency measure, a spread measure and 17 hydrological signatures. We found that climate variability knowledge was useful for reducing model uncertainty, in particular, unrealistic representation of deep groundwater processes. The constraints based on global maps of low-flow statistics provided more constraining information than those based on climate variability, but the latter rejected slow rainfall-runoff representations that the low flow statistics did not reject. The use of such knowledge, together with information on low-flow statistics and constraints on parameter relationships showed to be useful to

Correlation structures in short-term variabilities of stock indices and exchange rates

NASA Astrophysics Data System (ADS)

Nakamura, Tomomichi; Small, Michael

2007-09-01

Financial data usually show irregular fluctuations and some trends. We investigate whether there are correlation structures in short-term variabilities (irregular fluctuations) among financial data from the viewpoint of deterministic dynamical systems. Our method is based on the small-shuffle surrogate method. The data we use are daily closing price of Standard & Poor's 500 and the volume, and daily foreign exchange rates, Euro/US Dollar (USD), British Pound/USD and Japanese Yen/USD. We found that these data are not independent.

Short-term to seasonal variability in factors driving primary productivity in a shallow estuary: Implications for modeling production

NASA Astrophysics Data System (ADS)

Canion, Andy; MacIntyre, Hugh L.; Phipps, Scott

2013-10-01

The inputs of primary productivity models may be highly variable on short timescales (hourly to daily) in turbid estuaries, but modeling of productivity in these environments is often implemented with data collected over longer timescales. Daily, seasonal, and spatial variability in primary productivity model parameters: chlorophyll a concentration (Chla), the downwelling light attenuation coefficient (kd), and photosynthesis-irradiance response parameters (Pmchl, αChl) were characterized in Weeks Bay, a nitrogen-impacted shallow estuary in the northern Gulf of Mexico. Variability in primary productivity model parameters in response to environmental forcing, nutrients, and microalgal taxonomic marker pigments were analysed in monthly and short-term datasets. Microalgal biomass (as Chla) was strongly related to total phosphorus concentration on seasonal scales. Hourly data support wind-driven resuspension as a major source of short-term variability in Chla and light attenuation (kd). The empirical relationship between areal primary productivity and a combined variable of biomass and light attenuation showed that variability in the photosynthesis-irradiance response contributed little to the overall variability in primary productivity, and Chla alone could account for 53-86% of the variability in primary productivity. Efforts to model productivity in similar shallow systems with highly variable microalgal biomass may benefit the most by investing resources in improving spatial and temporal resolution of chlorophyll a measurements before increasing the complexity of models used in productivity modeling.

Coping with climate variability and long-term climate trends for Nicaraguan maize-bean farmers (Invited)

NASA Astrophysics Data System (ADS)

Gourdji, S.; Zelaya Martinez, C.; Martinez Valle, A.; Mejia, O.; Laderach, P.; Lobell, D. B.

2013-12-01

Climate variability and change impact farmers at different timescales, but both are of concern for livelihoods and long-term viability of small farms in tropical, rain-fed agricultural systems. This study uses a historical dataset to analyze the impact of 40-year climate trends in Nicaragua on bean production, a staple crop that is an important source of calories and protein in the local diet, particularly in rural areas and in lower income classes. Bean yields are sensitive to rising temperatures, but also frequently limited by seasonal drought and low soil fertility. We use an empirical model to relate department-level yields to spatial variation and inter-annual fluctuations in historical precipitation, temperature and extreme rain events. We then use this model to quantify the impact on yields of long-term observed warming in day and night temperatures, increases in rainfall intensity, longer gaps between rain events, a shorter rainy season and overall drying in certain regions of the country. Preliminary results confirm the negative impacts of warming night temperatures, higher vapor pressure deficits, and longer gaps between rain events on bean yields, although some drying at harvest time has helped to reduce rotting. Across all bean-growing areas, these climate trends have led to a ~10% yield decline per decade relative to a stationary climate and production system, with this decline reaching up to ~20% in the dry northern highlands. In regions that have been particularly impacted by these trends, we look for evidence of farm abandonment, increases in off-farm employment, or on-farm adaptation solutions through crop diversification, use of drought or heat-tolerant seed, and adoption of rainwater harvesting. We will also repeat the modeling exercise for maize, another staple crop providing ~25% of daily calories at the national scale, but which is projected to be more resilient to climate trends.

Effects of temporal averaging on short-term irradiance variability under mixed sky conditions

NASA Astrophysics Data System (ADS)

Lohmann, Gerald M.; Monahan, Adam H.

2018-05-01

Characterizations of short-term variability in solar radiation are required to successfully integrate large numbers of photovoltaic power systems into the electrical grid. Previous studies have used ground-based irradiance observations with a range of different temporal resolutions and a systematic analysis of the effects of temporal averaging on the representation of variability is lacking. Using high-resolution surface irradiance data with original temporal resolutions between 0.01 and 1 s from six different locations in the Northern Hemisphere, we characterize the changes in representation of temporal variability resulting from time averaging. In this analysis, we condition all data to states of mixed skies, which are the most potentially problematic in terms of local PV power volatility. Statistics of clear-sky index k* and its increments Δk*τ (i.e., normalized surface irradiance and changes therein over specified intervals of time) are considered separately. Our results indicate that a temporal averaging time scale of around 1 s marks a transition in representing single-point irradiance variability, such that longer averages result in substantial underestimates of variability. Higher-resolution data increase the complexity of data management and quality control without appreciably improving the representation of variability. The results do not show any substantial discrepancies between locations or seasons.

Impact of short-term temperature variability on emergency hospital admissions for schizophrenia stratified by season of birth

NASA Astrophysics Data System (ADS)

Zhao, Desheng; Zhang, Xulai; Xu, Zhiwei; Cheng, Jian; Xie, Mingyu; Zhang, Heng; Wang, Shusi; Li, Kesheng; Yang, Huihui; Wen, Liying; Wang, Xu; Su, Hong

2017-04-01

Diurnal temperature range (DTR) and temperature change between neighboring days (TCN) are important meteorological indicators closely associated with global climate change. However, up to date, there have been no studies addressing the impacts of both DTR and TCN on emergency hospital admissions for schizophrenia. We conducted a time-series analysis to assess the relationship between temperature variability and daily schizophrenia onset in Hefei, an inland city in southeast China. Daily meteorological data and emergency hospital admissions for schizophrenia from 2005 to 2014 in Hefei were collected. After stratifying by season of birth, Poisson generalized linear regression combined with distributed lag nonlinear model (DLNM) was used to examine the relationship between temperature variability and schizophrenia, adjusting for long-term trend and seasonality, mean temperature, and relative humidity. Our analysis revealed that extreme temperature variability may increase the risk for schizophrenia onset among patients born in spring, while no such association was found in patients born in summer and autumn. In patients born in spring, the relative risks of extremely high DTR comparing the 95th and 99th percentiles with the reference (50th, 10 °C) at 3-day lag were 1.078 (95 % confidence interval (CI) 1.025-1.135) and 1.159 (95 % CI 1.050-1.279), respectively. For TCN effects, only comparing 99th percentile with reference (50th, 0.7 °C) was significantly associated with emergency hospital admissions for schizophrenia (relative risk (RR) 1.111, 95 % CI 1.002-1.231). This study suggested that exposure to extreme temperature variability in short-term may trigger later days of schizophrenia onset for patients born in spring, which may have important implications for developing intervention strategies to prevent large temperature variability exposure.

Impact of short-term temperature variability on emergency hospital admissions for schizophrenia stratified by season of birth.

PubMed

Zhao, Desheng; Zhang, Xulai; Xu, Zhiwei; Cheng, Jian; Xie, Mingyu; Zhang, Heng; Wang, Shusi; Li, Kesheng; Yang, Huihui; Wen, Liying; Wang, Xu; Su, Hong

2017-04-01

Diurnal temperature range (DTR) and temperature change between neighboring days (TCN) are important meteorological indicators closely associated with global climate change. However, up to date, there have been no studies addressing the impacts of both DTR and TCN on emergency hospital admissions for schizophrenia. We conducted a time-series analysis to assess the relationship between temperature variability and daily schizophrenia onset in Hefei, an inland city in southeast China. Daily meteorological data and emergency hospital admissions for schizophrenia from 2005 to 2014 in Hefei were collected. After stratifying by season of birth, Poisson generalized linear regression combined with distributed lag nonlinear model (DLNM) was used to examine the relationship between temperature variability and schizophrenia, adjusting for long-term trend and seasonality, mean temperature, and relative humidity. Our analysis revealed that extreme temperature variability may increase the risk for schizophrenia onset among patients born in spring, while no such association was found in patients born in summer and autumn. In patients born in spring, the relative risks of extremely high DTR comparing the 95th and 99th percentiles with the reference (50th, 10 °C) at 3-day lag were 1.078 (95 % confidence interval (CI) 1.025-1.135) and 1.159 (95 % CI 1.050-1.279), respectively. For TCN effects, only comparing 99th percentile with reference (50th, 0.7 °C) was significantly associated with emergency hospital admissions for schizophrenia (relative risk (RR) 1.111, 95 % CI 1.002-1.231). This study suggested that exposure to extreme temperature variability in short-term may trigger later days of schizophrenia onset for patients born in spring, which may have important implications for developing intervention strategies to prevent large temperature variability exposure.

Climate variability and extremes, interacting with nitrogen storage, amplify eutrophication risk

USGS Publications Warehouse

Lee, Minjin; Shevliakova, Elena; Malyshev, Sergey; Milly, P.C.D.; Jaffe, Peter R.

2016-01-01

Despite 30 years of basin-wide nutrient-reduction efforts, severe hypoxia continues to be observed in the Chesapeake Bay. Here we demonstrate the critical influence of climate variability, interacting with accumulated nitrogen (N) over multidecades, on Susquehanna River dissolved nitrogen (DN) loads, known precursors of the hypoxia in the Bay. We used the process model LM3-TAN (Terrestrial and Aquatic Nitrogen), which is capable of capturing both seasonal and decadal-to-century changes in vegetation-soil-river N storage, and produced nine scenarios of DN-load distributions under different short-term scenarios of climate variability and extremes. We illustrate that after 1 to 3 yearlong dry spells, the likelihood of exceeding a threshold DN load (56 kt yr−1) increases by 40 to 65% due to flushing of N accumulated throughout the dry spells and altered microbial processes. Our analyses suggest that possible future increases in climate variability/extremes—specifically, high precipitation occurring after multiyear dry spells—could likely lead to high DN-load anomalies and hypoxia.

Local-scale spatial modelling for interpolating climatic temperature variables to predict agricultural plant suitability

NASA Astrophysics Data System (ADS)

Webb, Mathew A.; Hall, Andrew; Kidd, Darren; Minansy, Budiman

2016-05-01

Assessment of local spatial climatic variability is important in the planning of planting locations for horticultural crops. This study investigated three regression-based calibration methods (i.e. traditional versus two optimized methods) to relate short-term 12-month data series from 170 temperature loggers and 4 weather station sites with data series from nearby long-term Australian Bureau of Meteorology climate stations. The techniques trialled to interpolate climatic temperature variables, such as frost risk, growing degree days (GDDs) and chill hours, were regression kriging (RK), regression trees (RTs) and random forests (RFs). All three calibration methods produced accurate results, with the RK-based calibration method delivering the most accurate validation measures: coefficients of determination ( R 2) of 0.92, 0.97 and 0.95 and root-mean-square errors of 1.30, 0.80 and 1.31 °C, for daily minimum, daily maximum and hourly temperatures, respectively. Compared with the traditional method of calibration using direct linear regression between short-term and long-term stations, the RK-based calibration method improved R 2 and reduced root-mean-square error (RMSE) by at least 5 % and 0.47 °C for daily minimum temperature, 1 % and 0.23 °C for daily maximum temperature and 3 % and 0.33 °C for hourly temperature. Spatial modelling indicated insignificant differences between the interpolation methods, with the RK technique tending to be the slightly better method due to the high degree of spatial autocorrelation between logger sites.

Ultra-Short-Term Heart Rate Variability is Sensitive to Training Effects in Team Sports Players.

PubMed

Nakamura, Fabio Y; Flatt, Andrew A; Pereira, Lucas A; Ramirez-Campillo, Rodrigo; Loturco, Irineu; Esco, Michael R

2015-09-01

The aim of this study was to test the possibility of the ultra-short-term lnRMSSD (measured in 1-min post-1-min stabilization period) to detect training induced adaptations in futsal players. Twenty-four elite futsal players underwent HRV assessments pre- and post-three or four weeks preseason training. From the 10-min HRV recording period, lnRMSSD was analyzed in the following time segments: 1) from 0-5 min (i.e., stabilization period); 2) from 0-1 min; 1-2 min; 2-3 min; 3-4 min; 4-5 min and; 3) from 5-10 min (i.e., criterion period). The lnRMSSD was almost certainly higher (100/00/00) using the magnitude-based inference in all periods at the post- moment. The correlation between changes in ultra-short-term lnRMSSD (i.e., 0-1 min; 1-2 min; 2-3 min; 3-4 min; 4-5 min) and lnRMSSDCriterion ranged between 0.45-0.75, with the highest value (p = 0.75; 90% CI: 0.55 - 0.85) found between ultra-short-term lnRMDSSD at 1-2 min and lnRMSSDCriterion. In conclusion, lnRMSSD determined in a short period of 1-min is sensitive to training induced changes in futsal players (based on the very large correlation to the criterion measure), and can be used to track cardiac autonomic adaptations. Key pointsThe ultra-short-term (1 min) natural log of the root-mean-square difference of successive normal RR intervals (lnRMSSD) is sensitive to training effects in futsal playersThe ultra-short-term lnRMSSD may simplify the assessment of the cardiac autonomic changes in the field compared to the traditional and lengthier (10 min duration) analysisCoaches are encouraged to implement the ultra-short-term heart rate variability in their routines to monitor team sports athletes.

Ultra-Short-Term Heart Rate Variability is Sensitive to Training Effects in Team Sports Players

PubMed Central

Nakamura, Fabio Y.; Flatt, Andrew A.; Pereira, Lucas A.; Ramirez-Campillo, Rodrigo; Loturco, Irineu; Esco, Michael R.

2015-01-01

The aim of this study was to test the possibility of the ultra-short-term lnRMSSD (measured in 1-min post-1-min stabilization period) to detect training induced adaptations in futsal players. Twenty-four elite futsal players underwent HRV assessments pre- and post-three or four weeks preseason training. From the 10-min HRV recording period, lnRMSSD was analyzed in the following time segments: 1) from 0-5 min (i.e., stabilization period); 2) from 0-1 min; 1-2 min; 2-3 min; 3-4 min; 4-5 min and; 3) from 5-10 min (i.e., criterion period). The lnRMSSD was almost certainly higher (100/00/00) using the magnitude-based inference in all periods at the post- moment. The correlation between changes in ultra-short-term lnRMSSD (i.e., 0-1 min; 1-2 min; 2-3 min; 3-4 min; 4-5 min) and lnRMSSDCriterion ranged between 0.45-0.75, with the highest value (p = 0.75; 90% CI: 0.55 – 0.85) found between ultra-short-term lnRMDSSD at 1-2 min and lnRMSSDCriterion. In conclusion, lnRMSSD determined in a short period of 1-min is sensitive to training induced changes in futsal players (based on the very large correlation to the criterion measure), and can be used to track cardiac autonomic adaptations. Key points The ultra-short-term (1 min) natural log of the root-mean-square difference of successive normal RR intervals (lnRMSSD) is sensitive to training effects in futsal players The ultra-short-term lnRMSSD may simplify the assessment of the cardiac autonomic changes in the field compared to the traditional and lengthier (10 min duration) analysis Coaches are encouraged to implement the ultra-short-term heart rate variability in their routines to monitor team sports athletes PMID:26336347

Short-term heart rate variability (HRV) in healthy dogs.

PubMed

Bogucki, Sz; Noszczyk-Nowak, A

2015-01-01

Heart rate variability (HRV) is a well established mortality risk factor in both healthy dogs and those with heart failure. While the standards for short-term HRV analysis have been developed in humans, only reference values for HRV parameters determined from 24-hour ECG have been proposed in dogs. The aim of this study was to develop the reference values for short-term HRV parameters in a group of 50 healthy dogs of various breeds (age 4.86 ± 2.74 years, body weight 12.2 ± 3.88 kg). The ECG was recorded continuously for at least 180 min in a dark and quiet room. All electrocardiograms were inspected automatically and manually to eliminate atrial or ventricular premature complexes. Signals were transformed into a spectrum using the fast Fourier transform. The HRV parameters were measured at fixed times from 60-min ECG segments. The following time-domain parameters (ms) were analyzed: mean NN, SDNN, SDANN, SDNN index, rMSSD and pNN50. Moreover, frequency-domain parameters (Hz) were determined, including very low frequency (VLF), low frequency (LF) and high frequency (HF) components, total power (TP) and the LF/HF ratio. The results (means ± SD) were as follows: mean NN = 677.68 ± 126.89; SDNN = 208.86 ± 77.1; SDANN = 70.75 ± 30.9; SDNN index = 190.75 ± 76.12; rMSSD = 259 ± 120.17, pNN50 = 71.84 ± 13.96; VLF = 984.96 ± 327.7; LF = 1501.24 ± 736.32; HF = 5845.45 ± 2914.20; TP = 11065.31 ± 3866.87; LF/HF = 0.28 ± 0.11.

Effect of climatic variability on malaria trends in Baringo County, Kenya.

PubMed

Kipruto, Edwin K; Ochieng, Alfred O; Anyona, Douglas N; Mbalanya, Macrae; Mutua, Edna N; Onguru, Daniel; Nyamongo, Isaac K; Estambale, Benson B A

2017-05-25

Malaria transmission in arid and semi-arid regions of Kenya such as Baringo County, is seasonal and often influenced by climatic factors. Unravelling the relationship between climate variables and malaria transmission dynamics is therefore instrumental in developing effective malaria control strategies. The main aim of this study was to describe the effects of variability of rainfall, maximum temperature and vegetation indices on seasonal trends of malaria in selected health facilities within Baringo County, Kenya. Climate variables sourced from the International Research Institute (IRI)/Lamont-Doherty Earth Observatory (LDEO) climate database and malaria cases reported in 10 health facilities spread across four ecological zones (riverine, lowland, mid-altitude and highland) between 2004 and 2014 were subjected to a time series analysis. A negative binomial regression model with lagged climate variables was used to model long-term monthly malaria cases. The seasonal Mann-Kendall trend test was then used to detect overall monotonic trends in malaria cases. Malaria cases increased significantly in the highland and midland zones over the study period. Changes in malaria prevalence corresponded to variations in rainfall and maximum temperature. Rainfall at a time lag of 2 months resulted in an increase in malaria transmission across the four zones while an increase in temperature at time lags of 0 and 1 month resulted in an increase in malaria cases in the riverine and highland zones, respectively. Given the existence of a time lag between climatic variables more so rainfall and peak malaria transmission, appropriate control measures can be initiated at the onset of short and after long rains seasons.

Short-Term Behavior of Slag Concretes Exposed to a Real In Situ Mediterranean Climate Environment

PubMed Central

Sánchez, Isidro

2017-01-01

At present, one of the most suitable ways to get a more sustainable cement industry is to reduce the CO2 emissions generated during cement production. In order to reach that goal, the use of ground granulated blast-furnace slag as clinker replacement is becoming increasingly popular. Although the effects of this addition in the properties of cementitious materials are influenced by their hardening conditions, there are not too many experimental studies in which slag concretes have been exposed to real in situ environments. Then, the main objective of this research is to study the short-term effects of exposure to real Mediterranean climate environment of an urban site, where the action of airborne chlorides from sea water and the presence of CO2 are combined, in the microstructure and service properties of a commercial slag cement concrete, compared to ordinary Portland cement (OPC). The microstructure was studied with mercury intrusion porosimetry. The effective porosity, capillary suction coefficient, chloride migration coefficient, carbonation front depth, and compressive strength were also analyzed. Considering the results obtained, slag concretes exposed to a real in situ Mediterranean climate environment show good service properties in the short-term (180 days), in comparison with OPC. PMID:28786936

Short-Term Effects of Climatic Variables on Hand, Foot, and Mouth Disease in Mainland China, 2008–2013: A Multilevel Spatial Poisson Regression Model Accounting for Overdispersion

PubMed Central

Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying

2016-01-01

Background Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. Methods The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008–2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. Results The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse “V” shape and “V” shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. Conclusion We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic

Intraday and Interday Reliability of Ultra-Short-Term Heart Rate Variability in Rugby Union Players.

PubMed

Nakamura, Fábio Y; Pereira, Lucas A; Esco, Michael R; Flatt, Andrew A; Moraes, José E; Cal Abad, Cesar C; Loturco, Irineu

2017-02-01

Nakamura, FY, Pereira, LA, Esco, MR, Flatt, AA, Moraes, JE, Cal Abad, CC, and Loturco, I. Intraday and interday reliability of ultra-short-term heart rate variability in rugby union players. J Strength Cond Res 31(2): 548-551, 2017-The aim of this study was to examine the intraday and interday reliability of ultra-short-term vagal-related heart rate variability (HRV) in elite rugby union players. Forty players from the Brazilian National Rugby Team volunteered to participate in this study. The natural log of the root mean square of successive RR interval differences (lnRMSSD) assessments were performed on 4 different days. The HRV was assessed twice (intraday reliability) on the first day and once per day on the following 3 days (interday reliability). The RR interval recordings were obtained from 2-minute recordings using a portable heart rate monitor. The relative reliability of intraday and interday lnRMSSD measures was analyzed using the intraclass correlation coefficient (ICC). The typical error of measurement (absolute reliability) of intraday and interday lnRMSSD assessments was analyzed using the coefficient of variation (CV). Both intraday (ICC = 0.96; CV = 3.99%) and interday (ICC = 0.90; CV = 7.65%) measures were highly reliable. The ultra-short-term lnRMSSD is a consistent measure for evaluating elite rugby union players, in both intraday and interday settings. This study provides further validity to using this shortened method in practical field conditions with highly trained team sports athletes.

Climate variability and change scenarios for a marine commodity: Modelling small pelagic fish, fisheries and fishmeal in a globalized market

NASA Astrophysics Data System (ADS)

Merino, Gorka; Barange, Manuel; Mullon, Christian

2010-04-01

The world's small pelagic fish populations, their fisheries, fishmeal and fish oil production industries and markets are part of a globalised production and consumption system. The potential for climate variability and change to alter the balance in this system is explored by means of bioeconomic models at two different temporal scales, with the objective of investigating the interactive nature of environmental and human-induced changes on this globalised system. Short-term (interannual) environmental impacts on fishmeal production are considered by including an annual variable production rate on individual small pelagic fish stocks over a 10-year simulation period. These impacts on the resources are perceived by the fishmeal markets, where they are confronted by two aquaculture expansion hypotheses. Long-term (2080) environmental impacts on the same stocks are estimated using long-term primary production predictions as proxies for the species' carrying capacities, rather than using variable production rates, and are confronted on the market side by two alternative fishmeal management scenarios consistent with IPCC-type storylines. The two scenarios, World Markets and Global Commons, are parameterized through classic equilibrium solutions for a global surplus production bioeconomic model, namely maximum sustainable yield and open access, respectively. The fisheries explicitly modelled in this paper represent 70% of total fishmeal production, thus encapsulating the expected dynamics of the global production and consumption system. Both short and long-term simulations suggest that the sustainability of the small pelagic resources, in the face of climate variability and change, depends more on how society responds to climate impacts than on the magnitude of climate alterations per se.

Understanding Short-Term Nonmigrating Tidal Variability in the Ionospheric Dynamo Region from SABER Using Information Theory and Bayesian Statistics

NASA Astrophysics Data System (ADS)

Kumari, K.; Oberheide, J.

2017-12-01

Nonmigrating tidal diagnostics of SABER temperature observations in the ionospheric dynamo region reveal a large amount of variability on time-scales of a few days to weeks. In this paper, we discuss the physical reasons for the observed short-term tidal variability using a novel approach based on Information theory and Bayesian statistics. We diagnose short-term tidal variability as a function of season, QBO, ENSO, and solar cycle and other drivers using time dependent probability density functions, Shannon entropy and Kullback-Leibler divergence. The statistical significance of the approach and its predictive capability is exemplified using SABER tidal diagnostics with emphasis on the responses to the QBO and solar cycle. Implications for F-region plasma density will be discussed.

Statistical structure of intrinsic climate variability under global warming

NASA Astrophysics Data System (ADS)

Zhu, Xiuhua; Bye, John; Fraedrich, Klaus

2017-04-01

Climate variability is often studied in terms of fluctuations with respect to the mean state, whereas the dependence between the mean and variability is rarely discussed. We propose a new climate metric to measure the relationship between means and standard deviations of annual surface temperature computed over non-overlapping 100-year segments. This metric is analyzed based on equilibrium simulations of the Max Planck Institute-Earth System Model (MPI-ESM): the last millennium climate (800-1799), the future climate projection following the A1B scenario (2100-2199), and the 3100-year unforced control simulation. A linear relationship is globally observed in the control simulation and thus termed intrinsic climate variability, which is most pronounced in the tropical region with negative regression slopes over the Pacific warm pool and positive slopes in the eastern tropical Pacific. It relates to asymmetric changes in temperature extremes and associates fluctuating climate means with increase or decrease in intensity and occurrence of both El Niño and La Niña events. In the future scenario period, the linear regression slopes largely retain their spatial structure with appreciable changes in intensity and geographical locations. Since intrinsic climate variability describes the internal rhythm of the climate system, it may serve as guidance for interpreting climate variability and climate change signals in the past and the future.

Near-Term Actions to Address Long-Term Climate Risk

NASA Astrophysics Data System (ADS)

Lempert, R. J.

2014-12-01

Addressing climate change requires effective long-term policy making, which occurs when reflecting on potential events decades or more in the future causes policy makers to choose near-term actions different than those they would otherwise pursue. Contrary to some expectations, policy makers do sometimes make such long-term decisions, but not as commonly and successfully as climate change may require. In recent years however, the new capabilities of analytic decision support tools, combined with improved understanding of cognitive and organizational behaviors, has significantly improved the methods available for organizations to manage longer-term climate risks. In particular, these tools allow decision makers to understand what near-term actions consistently contribute to achieving both short- and long-term societal goals, even in the face of deep uncertainty regarding the long-term future. This talk will describe applications of these approaches for infrastructure, water, and flood risk management planning, as well as studies of how near-term choices about policy architectures can affect long-term greenhouse gas emission reduction pathways.

Investigating Inter-Individual Differences in Short-Term Intra-Individual Variability

ERIC Educational Resources Information Center

Wang, Lijuan; Hamaker, Ellen; Bergeman, C. S.

2012-01-01

Intra-individual variability over a short period of time may contain important information about how individuals differ from each other. In this article we begin by discussing diverse indicators for quantifying intra-individual variability and indicate their advantages and disadvantages. Then we propose an alternative method that models…

Relationship between rice yield and climate variables in southwest Nigeria using multiple linear regression and support vector machine analysis

NASA Astrophysics Data System (ADS)

Oguntunde, Philip G.; Lischeid, Gunnar; Dietrich, Ottfried

2018-03-01

This study examines the variations of climate variables and rice yield and quantifies the relationships among them using multiple linear regression, principal component analysis, and support vector machine (SVM) analysis in southwest Nigeria. The climate and yield data used was for a period of 36 years between 1980 and 2015. Similar to the observed decrease ( P < 0.001) in rice yield, pan evaporation, solar radiation, and wind speed declined significantly. Eight principal components exhibited an eigenvalue > 1 and explained 83.1% of the total variance of predictor variables. The SVM regression function using the scores of the first principal component explained about 75% of the variance in rice yield data and linear regression about 64%. SVM regression between annual solar radiation values and yield explained 67% of the variance. Only the first component of the principal component analysis (PCA) exhibited a clear long-term trend and sometimes short-term variance similar to that of rice yield. Short-term fluctuations of the scores of the PC1 are closely coupled to those of rice yield during the 1986-1993 and the 2006-2013 periods thereby revealing the inter-annual sensitivity of rice production to climate variability. Solar radiation stands out as the climate variable of highest influence on rice yield, and the influence was especially strong during monsoon and post-monsoon periods, which correspond to the vegetative, booting, flowering, and grain filling stages in the study area. The outcome is expected to provide more in-depth regional-specific climate-rice linkage for screening of better cultivars that can positively respond to future climate fluctuations as well as providing information that may help optimized planting dates for improved radiation use efficiency in the study area.

Effects of long- and short-term management on the functional structure of meadows through species turnover and intraspecific trait variability.

PubMed

Volf, Martin; Redmond, Conor; Albert, Ágnes J; Le Bagousse-Pinguet, Yoann; Biella, Paolo; Götzenberger, Lars; Hrázský, Záboj; Janeček, Štěpán; Klimešová, Jitka; Lepš, Jan; Šebelíková, Lenka; Vlasatá, Tereza; de Bello, Francesco

2016-04-01

The functional structures of communities respond to environmental changes by both species replacement (turnover) and within-species variation (intraspecific trait variability; ITV). Evidence is lacking on the relative importance of these two components, particularly in response to both short- and long-term environmental disturbance. We hypothesized that such short- and long-term perturbations would induce changes in community functional structure primarily via ITV and turnover, respectively. To test this we applied an experimental design across long-term mown and abandoned meadows, with each plot containing a further level of short-term management treatments: mowing, grazing and abandonment. Within each plot, species composition and trait values [height, shoot biomass, and specific leaf area (SLA)] were recorded on up to five individuals per species. Positive covariations between the contribution of species turnover and ITV occurred for height and shoot biomass in response to both short- and long-term management, indicating that species turnover and intraspecific adjustments selected for similar trait values. Positive covariations also occurred for SLA, but only in response to long-term management. The contributions of turnover and ITV changed depending on both the trait and management trajectory. As expected, communities responded to short-term disturbances mostly through changes in intraspecific trait variability, particularly for height and biomass. Interestingly, for SLA they responded to long-term disturbances by both species turnover and intraspecific adjustments. These findings highlight the importance of both ITV and species turnover in adjusting grassland functional trait response to environmental perturbation, and show that the response is trait specific and affected by disturbance regime history.

Food Prices and Climate Extremes: A Model of Global Grain Price Variability with Storage

NASA Astrophysics Data System (ADS)

Otto, C.; Schewe, J.; Frieler, K.

2015-12-01

Extreme climate events such as droughts, floods, or heat waves affect agricultural production in major cropping regions and therefore impact the world market prices of staple crops. In the last decade, crop prices exhibited two very prominent price peaks in 2007-2008 and 2010-2011, threatening food security especially for poorer countries that are net importers of grain. There is evidence that these spikes in grain prices were at least partly triggered by actual supply shortages and the expectation of bad harvests. However, the response of the market to supply shocks is nonlinear and depends on complex and interlinked processes such as warehousing, speculation, and trade policies. Quantifying the contributions of such different factors to short-term price variability remains difficult, not least because many existing models ignore the role of storage which becomes important on short timescales. This in turn impedes the assessment of future climate change impacts on food prices. Here, we present a simple model of annual world grain prices that integrates grain stocks into the supply and demand functions. This firstly allows us to model explicitly the effect of storage strategies on world market price, and thus, for the first time, to quantify the potential contribution of trade policies to price variability in a simple global framework. Driven only by reported production and by long--term demand trends of the past ca. 40 years, the model reproduces observed variations in both the global storage volume and price of wheat. We demonstrate how recent price peaks can be reproduced by accounting for documented changes in storage strategies and trade policies, contrasting and complementing previous explanations based on different mechanisms such as speculation. Secondly, we show how the integration of storage allows long-term projections of grain price variability under climate change, based on existing crop yield scenarios.

Non-stationarity of extreme weather events in a changing climate - an application to long-term droughts in the US Southwest

NASA Astrophysics Data System (ADS)

Grossmann, I.

2013-12-01

Return periods of many extreme weather events are not stationary over time, given increasing risks due to global warming and multidecadal variability resulting from large scale climate patterns. This is problematic as extreme weather events and long-term climate risks such as droughts are typically conceptualized via measures such as return periods that implicitly assume non-stationarity. I briefly review these problems and present an application to the non-stationarity of droughts in the US Southwest. The US Southwest relies on annual precipitation maxima during winter and the North American Monsoon (NAM), both of which vary with large-scale climate patterns, in particular ENSO, the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO). The latter two exhibit variability on longer (multi-decadal) time scales in addition to short-term variations. The region is also part of the subtropical belt projected to become more arid in a warming climate. The possible multidecadal impacts of the PDO on precipitation in the study region are analyzed with a focus on Arizona and New Mexico, using GPCC and CRU data since 1900. The projected impacts of the PDO on annual precipitation during the next three decades with GPCC data are similar in scale to the impacts of global warming on precipitation according to the A1B scenario and the CMIP2 multi-model means, while the combined impact of the PDO and AMO is about 19% larger. The effects according to the CRU dataset are about half as large as the projected global warming impacts. Given the magnitude of the projected impacts from both multidecadal variability and global warming, water management needs to explicitly incorporate both of these trends into long-term planning. Multi-decadal variability could be incorporated into the concept of return periods by presenting return periods as time-varying or as conditional on the respective 'phase' of relevant multidecadal patterns and on global warming. Problems

Range expansion through fragmented landscapes under a variable climate

PubMed Central

Bennie, Jonathan; Hodgson, Jenny A; Lawson, Callum R; Holloway, Crispin TR; Roy, David B; Brereton, Tom; Thomas, Chris D; Wilson, Robert J

2013-01-01

Ecological responses to climate change may depend on complex patterns of variability in weather and local microclimate that overlay global increases in mean temperature. Here, we show that high-resolution temporal and spatial variability in temperature drives the dynamics of range expansion for an exemplar species, the butterfly Hesperia comma. Using fine-resolution (5 m) models of vegetation surface microclimate, we estimate the thermal suitability of 906 habitat patches at the species' range margin for 27 years. Population and metapopulation models that incorporate this dynamic microclimate surface improve predictions of observed annual changes to population density and patch occupancy dynamics during the species' range expansion from 1982 to 2009. Our findings reveal how fine-scale, short-term environmental variability drives rates and patterns of range expansion through spatially localised, intermittent episodes of expansion and contraction. Incorporating dynamic microclimates can thus improve models of species range shifts at spatial and temporal scales relevant to conservation interventions. PMID:23701124

Rotational Properties of the Haumea Family Members and Candidates: Short-Term Variability

NASA Technical Reports Server (NTRS)

Thirouin, Audrey; Sheppard, Scott S.; Noll, Keith S.; Moskovitz, Nicholas A.; Oritiz, Jose Luis; Doressoundiram, Alain

2016-01-01

Haumea is one of the most interesting and intriguing trans-Neptunian objects (TNOs). It is a large, bright, fast rotator, and its spectrum indicates nearly pure water ice on the surface. It has at least two satellites and a dynamically related family of more than 10 TNOs with very similar proper orbital parameters and similar surface properties. The Haumean family is the only one currently known in the trans-Neptunian belt. Various models have been proposed, but the formation of the family remains poorly understood. In this work, we have investigated the rotational properties of the family members and unconfirmed family candidates with short-term variability studies, and report the most complete review to date. We present results based on five years of observations and report the short-term variability of five family members, and seven candidates. The mean rotational periods, from Maxwellian fits to the frequency distributions, are 6.27 +/- 1.19 hr for the confirmed family members, 6.44 +/- 1.16 hr for the candidates, and 7.65 +/- 0.54 hr for other TNOs (without relation to the family). According to our study, there is a possibility that Haumea family members rotate faster than other TNOs, however, the sample of family member is still too limited for a secure conclusion. We also highlight the fast rotation of 2002 GH(sub 32). This object has a 0.36 +/- 0.02 mag amplitude lightcurve and a rotational period of about 3.98 hr. Assuming 2002 GH(sub 32) is a triaxial object in hydrostatic equilibrium, we derive a lower limit to the density of 2.56 g cm(exp -3). This density is similar to Haumea's and much more dense than other small TNO densities.

Exploring Niches for Short-Season Grain Legumes in Semi-Arid Eastern Kenya - Coping with the Impacts of Climate Variability.

PubMed

Sennhenn, Anne; Njarui, Donald M G; Maass, Brigitte L; Whitbread, Anthony M

2017-01-01

Climate variability is the major risk to agricultural production in semi-arid agroecosystems and the key challenge to sustain farm livelihoods for the 500 million people who inhabit these areas worldwide. Short-season grain legumes have great potential to address this challenge and help to design more resilient and productive farming systems. However, grain legumes display a great diversity and differ widely in growth, development, and resource use efficiency. Three contrasting short season grain legumes common bean ( Phaseolus vulgaris L.), cowpea ( Vigna unguiculata (L.) Walp.] and lablab [ Lablab purpureus (L.) Sweet] were selected to assess their agricultural potential with respect to climate variability and change along the Machakos-Makueni transect in semi-arid Eastern Kenya. This was undertaken using measured data [a water response trial conducted during 2012/13 and 2013/14 in Machakos, Kenya] and simulated data using the Agricultural Production System sIMulator (APSIM). The APSIM crop model was calibrated and validated to simulate growth and development of short-season grain legumes in semi-arid environments. Water use efficiency (WUE) was used as indicator to quantify the production potential. The major traits of adaptation include early flowering and pod and seed set before the onset of terminal drought. Early phenology together with adapted canopy architecture allowed more optimal water use and greater partitioning of dry matter into seed (higher harvest index). While common bean followed a comparatively conservative strategy of minimizing water loss through crop transpiration, the very short development time and compact growth habit limited grain yield to rarely exceed 1,000 kg ha -1 . An advantage of this strategy was relatively stable yields independent of in-crop rainfall or season length across the Machakos-Makueni transect. The growth habit of cowpea in contrast minimized water loss through soil evaporation with rapid ground cover and dry matter

Visibility graph analysis of very short-term heart rate variability during sleep

NASA Astrophysics Data System (ADS)

Hou, F. Z.; Li, F. W.; Wang, J.; Yan, F. R.

2016-09-01

Based on a visibility-graph algorithm, complex networks were constructed from very short-term heart rate variability (HRV) during different sleep stages. Network measurements progressively changed from rapid eye movement (REM) sleep to light sleep and then deep sleep, exhibiting promising ability for sleep assessment. Abnormal activation of the cardiovascular controls with enhanced 'small-world' couplings and altered fractal organization during REM sleep indicates that REM could be a potential risk factor for adverse cardiovascular event, especially in males, older individuals, and people who are overweight. Additionally, an apparent influence of gender, aging, and obesity on sleep was demonstrated in healthy adults, which may be helpful for establishing expected sleep-HRV patterns in different populations.

A Meta-Analysis of the Impact of Short-Term Sleep Deprivation on Cognitive Variables

PubMed Central

Lim, Julian; Dinges, David F.

2012-01-01

A substantial amount of research has been conducted in an effort to understand the impact of short-term (<48 hr) total sleep deprivation (SD) on outcomes in various cognitive domains. Despite this wealth of information, there has been disagreement on how these data should be interpreted, arising in part because the relative magnitude of effect sizes in these domains is not known. To address this question, we conducted a meta-analysis to discover the effects of short-term SD on both speed and accuracy measures in 6 cognitive categories: simple attention, complex attention, working memory, processing speed, short-term memory, and reasoning. Seventy articles containing 147 cognitive tests were found that met inclusion criteria for this study. Effect sizes ranged from small and nonsignificant (reasoning accuracy: ḡ = −0.125, 95% CI [−0.27, 0.02]) to large (lapses in simple attention: ḡ = −0.776, 95% CI [−0.96, −0.60], p < .001). Across cognitive domains, significant differences were observed for both speed and accuracy; however, there were no differences between speed and accuracy measures within each cognitive domain. Of several moderators tested, only time awake was a significant predictor of between-studies variability, and only for accuracy measures, suggesting that heterogeneity in test characteristics may account for a significant amount of the remaining between-studies variance. The theoretical implications of these findings for the study of SD and cognition are discussed. PMID:20438143

A meta-analysis of the impact of short-term sleep deprivation on cognitive variables.

PubMed

Lim, Julian; Dinges, David F

2010-05-01

A substantial amount of research has been conducted in an effort to understand the impact of short-term (<48 hr) total sleep deprivation (SD) on outcomes in various cognitive domains. Despite this wealth of information, there has been disagreement on how these data should be interpreted, arising in part because the relative magnitude of effect sizes in these domains is not known. To address this question, we conducted a meta-analysis to discover the effects of short-term SD on both speed and accuracy measures in 6 cognitive categories: simple attention, complex attention, working memory, processing speed, short-term memory, and reasoning. Seventy articles containing 147 cognitive tests were found that met inclusion criteria for this study. Effect sizes ranged from small and nonsignificant (reasoning accuracy: g = -0.125, 95% CI [-0.27, 0.02]) to large (lapses in simple attention: g = -0.776, 95% CI [-0.96, -0.60], p < .001). Across cognitive domains, significant differences were observed for both speed and accuracy; however, there were no differences between speed and accuracy measures within each cognitive domain. Of several moderators tested, only time awake was a significant predictor of between-studies variability, and only for accuracy measures, suggesting that heterogeneity in test characteristics may account for a significant amount of the remaining between-studies variance. The theoretical implications of these findings for the study of SD and cognition are discussed. (c) 2010 APA, all rights reserved.

How important is interannual variability in the climatic interpretation of moraine sequences?

NASA Astrophysics Data System (ADS)

Leonard, E. M.; Laabs, B. J. C.; Plummer, M. A.

2017-12-01

Mountain glaciers respond to both long-term climate and interannual forcing. Anderson et al. (2014) pointed out that kilometer-scale fluctuations in glacier length may result from interannual variability in temperature and precipitation given a "steady" climate with no long-term trends in mean or variability of temperature and precipitation. They cautioned that use of outermost moraines from the Last Glacial Maximum (LGM) as indicators of LGM climate will, because of the role of interannual forcing, result in overestimation of the magnitude of long-term temperature depression and/or precipitation enhancement. Here we assess the implications of these ideas, by examining the effect of interannual variability on glacier length and inferred magnitude of LGM climate change from present under both an assumed steady LGM climate and an LGM climate with low-magnitude, long-period variation in summer temperature and annual precipitation. We employ both the original 1-stage linear glacier model (Roe and O'Neal, 2009) used by Anderson et al. (2014) and a newer 3-stage linear model (Roe and Baker, 2014). We apply the models to two reconstructed LGM glaciers in the Colorado Sangre de Cristo Mountains. Three-stage-model results indicate that, absent long-term variations through a 7500-year-long LGM, interannual variability would result in overestimation of mean LGM temperature depression from the outermost moraine of 0.2-0.6°C. If small long-term cyclic variations of temperature (±0.5°C) and precipitation (±5%) are introduced, the overestimation of LGM temperature depression reduces to less than 0.4°C, and if slightly greater long-term variation (±1.0°C and ±10% precipitation) is introduced, the magnitude of overestimation is 0.3°C or less. Interannual variability may produce a moraine sequence that differs from the sequence that would be expected were glacier length forced only by long-term climate. With small amplitude (±0.5°C and ±5% precipitation) long-term

New Perspectives on the Role of Internal Variability in Regional Climate Change and Climate Model Evaluation

NASA Astrophysics Data System (ADS)

Deser, C.

2017-12-01

Natural climate variability occurs over a wide range of time and space scales as a result of processes intrinsic to the atmosphere, the ocean, and their coupled interactions. Such internally generated climate fluctuations pose significant challenges for the identification of externally forced climate signals such as those driven by volcanic eruptions or anthropogenic increases in greenhouse gases. This challenge is exacerbated for regional climate responses evaluated from short (< 50 years) data records. The limited duration of the observations also places strong constraints on how well the spatial and temporal characteristics of natural climate variability are known, especially on multi-decadal time scales. The observational constraints, in turn, pose challenges for evaluation of climate models, including their representation of internal variability and assessing the accuracy of their responses to natural and anthropogenic radiative forcings. A promising new approach to climate model assessment is the advent of large (10-100 member) "initial-condition" ensembles of climate change simulations with individual models. Such ensembles allow for accurate determination, and straightforward separation, of externally forced climate signals and internal climate variability on regional scales. The range of climate trajectories in a given model ensemble results from the fact that each simulation represents a particular sequence of internal variability superimposed upon a common forced response. This makes clear that nature's single realization is only one of many that could have unfolded. This perspective leads to a rethinking of approaches to climate model evaluation that incorporate observational uncertainty due to limited sampling of internal variability. Illustrative examples across a range of well-known climate phenomena including ENSO, volcanic eruptions, and anthropogenic climate change will be discussed.

Terrestrial essential climate variables (ECVs) at a glance

USGS Publications Warehouse

Stitt, Susan; Dwyer, John; Dye, Dennis; Josberger, Edward

2011-01-01

The Global Terrestrial Observing System, Global Climate Observing System, World Meteorological Organization, and Committee on Earth Observation Satellites all support consistent global land observations and measurements. To accomplish this goal, the Global Terrestrial Observing System defined 'essential climate variables' as measurements of atmosphere, oceans, and land that are technically and economically feasible for systematic observation and that are needed to meet the United Nations Framework Convention on Climate Change and requirements of the Intergovernmental Panel on Climate Change. The following are the climate variables defined by the Global Terrestrial Observing System that relate to terrestrial measurements. Several of them are currently measured most appropriately by in-place observations, whereas others are suitable for measurement by remote sensing technologies. The U.S. Geological Survey is the steward of the Landsat archive, satellite imagery collected from 1972 to the present, that provides a potential basis for deriving long-term, global-scale, accurate, timely and consistent measurements of many of these essential climate variables.

Changing maternity leave policy: short-term effects on fertility rates and demographic variables in Germany.

PubMed

Thyrian, Jochen René; Fendrich, Konstanze; Lange, Anja; Haas, Johannes-Peter; Zygmunt, Marek; Hoffmann, Wolfgang

2010-08-01

Changes in reproductive behaviour and decreasing fertility rates have recently led to policy actions that attempt to counteract these developments. Evidence on the efficacy of such policy interventions, however, is limited. The present analysis examines fertility rates and demographic variables of a population in Germany in response to new maternity leave regulations, which were introduced in January 2007. As part of a population-based survey of neonates in Pomerania (SNiP), all births in the study region from the period 23 months prior to January 1st, 2007 until 23 months afterwards were examined. Crude Birth Rates (CBR) per month, General Fertility Rates (GFR) per month, parity and sociodemographic variables were compared using bivariate techniques. Logistic regression analysis was performed. No statistically significant difference in the CBR or GFR after Jan. 1st, 2007 was found. There were statistically significant differences in other demographic variables, however. The proportion of mothers who (a) were employed full-time before pregnancy; (b) came from a higher socioeconomic status; and (c) had higher income levels all increased after January 1st, 2007. The magnitude of these effects was higher in multigravid women. Forward stepwise logistic regression found an odds ratio of 1.79 for women with a family income of more than 3000 euro to give birth after the new law was introduced. This is the first analysis of population-based data that examines fertility rates and sociodemographic variables in response to new legal regulations. No short-term effects on birth rates were detected, but there was a differential effect on the subgroup of multigravidae. The focus of this policy was to provide financial support, which is certainly important, but the complexity of having a child suggests that attitudinal and motivational aspects also need to be taken into account. Furthermore, these analyses were only able to evaluate the short-term consequences of the policy

A Short Guide to the Climatic Variables of the Last Glacial Maximum for Biogeographers.

PubMed

Varela, Sara; Lima-Ribeiro, Matheus S; Terribile, Levi Carina

2015-01-01

Ecological niche models are widely used for mapping the distribution of species during the last glacial maximum (LGM). Although the selection of the variables and General Circulation Models (GCMs) used for constructing those maps determine the model predictions, we still lack a discussion about which variables and which GCM should be included in the analysis and why. Here, we analyzed the climatic predictions for the LGM of 9 different GCMs in order to help biogeographers to select their GCMs and climatic layers for mapping the species ranges in the LGM. We 1) map the discrepancies between the climatic predictions of the nine GCMs available for the LGM, 2) analyze the similarities and differences between the GCMs and group them to help researchers choose the appropriate GCMs for calibrating and projecting their ecological niche models (ENM) during the LGM, and 3) quantify the agreement of the predictions for each bioclimatic variable to help researchers avoid the environmental variables with a poor consensus between models. Our results indicate that, in absolute values, GCMs have a strong disagreement in their temperature predictions for temperate areas, while the uncertainties for the precipitation variables are in the tropics. In spite of the discrepancies between model predictions, temperature variables (BIO1-BIO11) are highly correlated between models. Precipitation variables (BIO12-BIO19) show no correlation between models, and specifically, BIO14 (precipitation of the driest month) and BIO15 (Precipitation Seasonality (Coefficient of Variation)) show the highest level of discrepancy between GCMs. Following our results, we strongly recommend the use of different GCMs for constructing or projecting ENMs, particularly when predicting the distribution of species that inhabit the tropics and the temperate areas of the Northern and Southern Hemispheres, because climatic predictions for those areas vary greatly among GCMs. We also recommend the exclusion of BIO14

A Short Guide to the Climatic Variables of the Last Glacial Maximum for Biogeographers

PubMed Central

Varela, Sara; Lima-Ribeiro, Matheus S.; Terribile, Levi Carina

2015-01-01

Ecological niche models are widely used for mapping the distribution of species during the last glacial maximum (LGM). Although the selection of the variables and General Circulation Models (GCMs) used for constructing those maps determine the model predictions, we still lack a discussion about which variables and which GCM should be included in the analysis and why. Here, we analyzed the climatic predictions for the LGM of 9 different GCMs in order to help biogeographers to select their GCMs and climatic layers for mapping the species ranges in the LGM. We 1) map the discrepancies between the climatic predictions of the nine GCMs available for the LGM, 2) analyze the similarities and differences between the GCMs and group them to help researchers choose the appropriate GCMs for calibrating and projecting their ecological niche models (ENM) during the LGM, and 3) quantify the agreement of the predictions for each bioclimatic variable to help researchers avoid the environmental variables with a poor consensus between models. Our results indicate that, in absolute values, GCMs have a strong disagreement in their temperature predictions for temperate areas, while the uncertainties for the precipitation variables are in the tropics. In spite of the discrepancies between model predictions, temperature variables (BIO1-BIO11) are highly correlated between models. Precipitation variables (BIO12- BIO19) show no correlation between models, and specifically, BIO14 (precipitation of the driest month) and BIO15 (Precipitation Seasonality (Coefficient of Variation)) show the highest level of discrepancy between GCMs. Following our results, we strongly recommend the use of different GCMs for constructing or projecting ENMs, particularly when predicting the distribution of species that inhabit the tropics and the temperate areas of the Northern and Southern Hemispheres, because climatic predictions for those areas vary greatly among GCMs. We also recommend the exclusion of BIO14

Implementation of a Time Series Analysis for the Assessment of the Role of Climate Variability in a Post-Disturbance Savanna System

NASA Astrophysics Data System (ADS)

Gibbes, C.; Southworth, J.; Waylen, P. R.

2013-05-01

How do climate variability and climate change influence vegetation cover and vegetation change in savannas? A landscape scale investigation of the effect of changes in precipitation on vegetation is undertaken through the employment of a time series analysis. The multi-national study region is located within the Kavango-Zambezi region, and is delineated by the Okavango, Kwando, and Zambezi watersheds. A mean-variance time-series analysis quantifies vegetation dynamics and characterizes vegetation response to climate. The spatially explicit approach used to quantify the persistence of vegetation productivity permits the extraction of information regarding long term climate-landscape dynamics. Results show a pattern of reduced mean annual precipitation and increased precipitation variability across key social and ecological areas within the study region. Despite decreased mean annual precipitation since the mid to late 1970's vegetation trends predominantly indicate increasing biomass. The limited areas which have diminished vegetative cover relate to specific vegetation types, and are associated with declines in precipitation variability. Results indicate that in addition to short term changes in vegetation cover, long term trends in productive biomass are apparent, relate to spatial differences in precipitation variability, and potentially represent shifts vegetation composition. This work highlights the importance of time-series analyses for examining climate-vegetation linkages in a spatially explicit manner within a highly vulnerable region of the world.

Environmental forcing and Southern Ocean marine predator populations: effects of climate change and variability.

PubMed

Trathan, P N; Forcada, J; Murphy, E J

2007-12-29

The Southern Ocean is a major component within the global ocean and climate system and potentially the location where the most rapid climate change is most likely to happen, particularly in the high-latitude polar regions. In these regions, even small temperature changes can potentially lead to major environmental perturbations. Climate change is likely to be regional and may be expressed in various ways, including alterations to climate and weather patterns across a variety of time-scales that include changes to the long interdecadal background signals such as the development of the El Niño-Southern Oscillation (ENSO). Oscillating climate signals such as ENSO potentially provide a unique opportunity to explore how biological communities respond to change. This approach is based on the premise that biological responses to shorter-term sub-decadal climate variability signals are potentially the best predictor of biological responses over longer time-scales. Around the Southern Ocean, marine predator populations show periodicity in breeding performance and productivity, with relationships with the environment driven by physical forcing from the ENSO region in the Pacific. Wherever examined, these relationships are congruent with mid-trophic-level processes that are also correlated with environmental variability. The short-term changes to ecosystem structure and function observed during ENSO events herald potential long-term changes that may ensue following regional climate change. For example, in the South Atlantic, failure of Antarctic krill recruitment will inevitably foreshadow recruitment failures in a range of higher trophic-level marine predators. Where predator species are not able to accommodate by switching to other prey species, population-level changes will follow. The Southern Ocean, though oceanographically interconnected, is not a single ecosystem and different areas are dominated by different food webs. Where species occupy different positions in

Poincaré plot analysis of ultra-short-term heart rate variability during recovery from exercise in physically active men.

PubMed

Gomes, Rayana L; Marques Vanderlei, Luiz C; Garner, David M; Ramos Santana, Milana D; de Abreu, Luiz C; Valenti, Vitor E

2017-04-26

Recently there has been increasing interest in the study of ultra-short- term heart rate variability (HRV) in sports performance and exercise physiology. In order to improve standardization of this specific analysis, we evaluated the ultra-short-term HRV analysis through SD1Poincaré index to identify exercise induced responses. We investigated 35 physically active men aged between 18 and 35 years old. Volunteers performed physical exercise on treadmill with intensity of 6.0 km / hour + 1% slope in the first five minutes for physical "warming up." This was followed by 25 minutes with intensity equivalent to 60% of Vmax, with the same slope according to the Conconi threshold. HRV was analyzed in the following periods: the five-minute period before the exercise and the five-minute period immediately after the exercise, the five minutes were divided into five segments of 60 RR intervals. Ultra-short-term RMSSD and SD1 analysis were performed. Ultra-short-term RMSSD and SD1 were significantly (p<0.0001) reduced during the initial five minutes divided into five segments of 60 RR intervals compared to (at rest) control. Heart rate was significantly (p<0.0001) increased 1 min and 3 min immediately after exercise compared to (at rest) control. At rest ultra-short-term SD1 presented significant correlation with short-term (256 RR intervals) RMSSD (r=0.78; p<0.0001), HF (r=0.574; p=0.0007) and SD1 (r=0.78; p<0.0001). Additionally, visual analysis with the Poincaré plot detected changes in HRV after exercise. Ultra-short-term HRV analysis through Poincaré plot identified heart rate autonomic responses induced by aerobic exercise.

Exploring Niches for Short-Season Grain Legumes in Semi-Arid Eastern Kenya — Coping with the Impacts of Climate Variability

PubMed Central

Sennhenn, Anne; Njarui, Donald M. G.; Maass, Brigitte L.; Whitbread, Anthony M.

2017-01-01

Climate variability is the major risk to agricultural production in semi-arid agroecosystems and the key challenge to sustain farm livelihoods for the 500 million people who inhabit these areas worldwide. Short-season grain legumes have great potential to address this challenge and help to design more resilient and productive farming systems. However, grain legumes display a great diversity and differ widely in growth, development, and resource use efficiency. Three contrasting short season grain legumes common bean (Phaseolus vulgaris L.), cowpea (Vigna unguiculata (L.) Walp.] and lablab [Lablab purpureus (L.) Sweet] were selected to assess their agricultural potential with respect to climate variability and change along the Machakos-Makueni transect in semi-arid Eastern Kenya. This was undertaken using measured data [a water response trial conducted during 2012/13 and 2013/14 in Machakos, Kenya] and simulated data using the Agricultural Production System sIMulator (APSIM). The APSIM crop model was calibrated and validated to simulate growth and development of short-season grain legumes in semi-arid environments. Water use efficiency (WUE) was used as indicator to quantify the production potential. The major traits of adaptation include early flowering and pod and seed set before the onset of terminal drought. Early phenology together with adapted canopy architecture allowed more optimal water use and greater partitioning of dry matter into seed (higher harvest index). While common bean followed a comparatively conservative strategy of minimizing water loss through crop transpiration, the very short development time and compact growth habit limited grain yield to rarely exceed 1,000 kg ha−1. An advantage of this strategy was relatively stable yields independent of in-crop rainfall or season length across the Machakos-Makueni transect. The growth habit of cowpea in contrast minimized water loss through soil evaporation with rapid ground cover and dry matter

Short- and Long-Term Feedbacks on Vegetation Water Use: Unifying Evidence from Observations and Modeling

NASA Astrophysics Data System (ADS)

Mackay, D. S.

2001-05-01

Recent efforts to measure and model the interacting influences of climate, soil, and vegetation on soil water and nutrient dynamics have identified numerous important feedbacks that produce nonlinear responses. In particular, plant physiological factors that control rates of transpiration respond to soil water deficits and vapor pressure deficits (VPD) in the short-term, and to climate, nutrient cycling and disturbance in the long-term. The starting point of this presentation is the observation that in many systems, in particular forest ecosystems, conservative water use emerges as a result of short-term closure of stomata in response to high evaporative demand, and long-term vegetative canopy development under nutrient limiting conditions. Evidence for important short-term controls is presented from sap flux measurements of stand transpiration, remote sensing, and modeling of transpiration through a combination of physically-based modeling and Monte Carlo analysis. A common result is a strong association between stomatal conductance (gs) and the negative evaporative gain (∂ gs/∂ VPD) associated with the sensitivity of stomatal closure to rates of water loss. The importance of this association from the standpoint of modeling transpiration depends on the degree of canopy-atmosphere coupling. This suggests possible simplifications to future canopy component models for use in watershed and larger-scale hydrologic models for short-term processes. However, further results are presented from theoretical modeling, which suggest that feedbacks between hydrology and vegetation in current long-term (inter-annual to century) models may be too simple, as they do not capture the spatially variable nature of slow nutrient cycling in response to soil water dynamics and site history. Memory effects in the soil nutrient pools can leave lasting effects on more rapid processes associated with soil, vegetation, atmosphere coupling.

Climate driven variability and detectability of temporal trends in low flow indicators for Ireland

NASA Astrophysics Data System (ADS)

Hall, Julia; Murphy, Conor; Harrigan, Shaun

2013-04-01

Observational data from hydrological monitoring programs plays an important role in informing decision makers of changes in key hydrological variables. To analyse how changes in climate influence stream flow, undisturbed river basins with near-natural conditions limited from human influences are needed. This study analyses low flow indicators derived from observations from the Irish Reference Network. Within the trend analysis approach the influence of individual years or sub-periods on the detected trend are analysed using sequential trend tests on all possible periods (of at least 10 years in length) by varying the start and end dates of records for various indicators. Results from this study highlight that the current standard approach using fixed periods to determine long term trends is not appropriate as statistical significance and direction of trends from short term records do not persist continuously over entire record and can be heavily influenced by extremes within the record. The importance of longer records in contextualising short term trends derived from fixed-periods influenced by natural annual, inter-annual and multi-decadal variability is highlighted. Due to the low signal (trend) to noise (variability) ratio, the apparent trends derived from the low flow indicators cannot be used as confident guides to inform future water resources planning and decision making on climate change. Infact, some derived trends contradict expected climate change impacts and even small changes in study design can change the outcomes to a high degree. Therefore it is important not only to evaluate the magnitude of trends derived from monitoring data but also when a trend of a certain magnitude in a given indicator will be detectable to inform decision making or what changes might be required to detect trends for a certain significance level. In this study, the influence of observed variance in the monitoring records on the expected detection times for trends with a

Short-term heart rate variability in asthmatic obese children: effect of exhaustive exercise and different humidity conditions.

PubMed

Rezvan, K; Dabidi Roshan, V; Mahmudi, S A

2015-11-01

Asthmatic obese children experience changes in functional capacity and autonomic control. Previous heart rate variability (HRV) studies were based on 24-hour recordings, little research has been conducted on the short-term HRV in asthmatic obese children, primarily during physical effort indifferent environmental humidity conditions. The aim of this study was to evaluate the effect of aerobic activity on short-term HRV in asthmatic obese children under two different environmental humidity conditions. Ten obese boys with mild asthma as experimental group and 15 obese healthy boys with the same conditions were involved as a control group. Protocol included progressive and exhaustive aerobic activities on a calibrated ergometer pedal bicycle in two various environmental humidity 35±5% and 65±5%. HRV was measured by PADSY MEDSET Holter monitoring device during three phases; pre-test, mid-test and post-test. Then, short-term HRV was assessed from calculation of the mean R-R interval measured on HRV at each phases. HRV significantly decreased at mid-test and post-test among asthmatic and health children. However, the aforesaid changes were significantly higher in the asthmatic than health children following. Moreover, decrease of short-term HRV was significantly greater in the 35±5% than 65±5% environmental humidity. Our findings suggest from the autonomic standpoint, asthmatic and non-asthmatic children respond differently to exhaustive exercise induced stress. Aerobic exercise at an environment with high humidity compared with the low humidity appears to have additional benefits on short-term HRV in that it enhances the parasympathetic and autonomic modulation of the heart in asthmatic obese children.

Evaluating the robustness of conceptual rainfall-runoff models under climate variability in northern Tunisia

NASA Astrophysics Data System (ADS)

Dakhlaoui, H.; Ruelland, D.; Tramblay, Y.; Bargaoui, Z.

2017-07-01

To evaluate the impact of climate change on water resources at the catchment scale, not only future projections of climate are necessary but also robust rainfall-runoff models that must be fairly reliable under changing climate conditions. The aim of this study was thus to assess the robustness of three conceptual rainfall-runoff models (GR4j, HBV and IHACRES) on five basins in northern Tunisia under long-term climate variability, in the light of available future climate scenarios for this region. The robustness of the models was evaluated using a differential split sample test based on a climate classification of the observation period that simultaneously accounted for precipitation and temperature conditions. The study catchments include the main hydrographical basins in northern Tunisia, which produce most of the surface water resources in the country. A 30-year period (1970-2000) was used to capture a wide range of hydro-climatic conditions. The calibration was based on the Kling-Gupta Efficiency (KGE) criterion, while model transferability was evaluated based on the Nash-Sutcliffe efficiency criterion and volume error. The three hydrological models were shown to behave similarly under climate variability. The models simulated the runoff pattern better when transferred to wetter and colder conditions than to drier and warmer ones. It was shown that their robustness became unacceptable when climate conditions involved a decrease of more than 25% in annual precipitation and an increase of more than +1.75 °C in annual mean temperatures. The reduction in model robustness may be partly due to the climate dependence of some parameters. When compared to precipitation and temperature projections in the region, the limits of transferability obtained in this study are generally respected for short and middle term. For long term projections under the most pessimistic emission gas scenarios, the limits of transferability are generally not respected, which may hamper the

Impact of internal variability on projections of Sahel precipitation change

NASA Astrophysics Data System (ADS)

Monerie, Paul-Arthur; Sanchez-Gomez, Emilia; Pohl, Benjamin; Robson, Jon; Dong, Buwen

2017-11-01

The impact of the increase of greenhouse gases on Sahelian precipitation is very uncertain in both its spatial pattern and magnitude. In particular, the relative importance of internal variability versus external forcings depends on the time horizon considered in the climate projection. In this study we address the respective roles of the internal climate variability versus external forcings on Sahelian precipitation by using the data from the CESM Large Ensemble Project, which consists of a 40 member ensemble performed with the CESM1-CAM5 coupled model for the period 1920-2100. We show that CESM1-CAM5 is able to simulate the mean and interannual variability of Sahel precipitation, and is representative of a CMIP5 ensemble of simulations (i.e. it simulates the same pattern of precipitation change along with equivalent magnitude and seasonal cycle changes as the CMIP5 ensemble mean). However, CESM1-CAM5 underestimates the long-term decadal variability in Sahel precipitation. For short-term (2010-2049) and mid-term (2030-2069) projections the simulated internal variability component is able to obscure the projected impact of the external forcing. For long-term (2060-2099) projections external forcing induced change becomes stronger than simulated internal variability. Precipitation changes are found to be more robust over the central Sahel than over the western Sahel, where climate change effects struggle to emerge. Ten (thirty) members are needed to separate the 10 year averaged forced response from climate internal variability response in the western Sahel for a long-term (short-term) horizon. Over the central Sahel two members (ten members) are needed for a long-term (short-term) horizon.

Short-term forecasting tools for agricultural nutrient management

USDA-ARS?s Scientific Manuscript database

The advent of real time/short term farm management tools is motivated by the need to protect water quality above and beyond the general guidance offered by existing nutrient management plans. Advances in high performance computing and hydrologic/climate modeling have enabled rapid dissemination of ...

Global Air Quality and Climate Impacts of Mitigating Short-lived Climate Pollution in China

NASA Astrophysics Data System (ADS)

Harper, K.; Unger, N.; Heyes, C.; Kiesewetter, G.; Klimont, Z.; Schoepp, W.; Wagner, F.

2014-12-01

China is a major emitter of harmful air pollutants, including the short-lived climate pollutants (SLCPs) and their precursors. Implementation of pollution control technologies provides a mechanism for simultaneously protecting human and ecosystem health and achieving near-term climate co-benefits; however, predicting the outcomes of technical and policy interventions is challenging because the SLCPs participate in both climate warming and cooling and share many common emission sources. Here, we present the results of a combined regional integrated assessment and global climate modeling study aimed at quantifying the near-term climate and air quality co-benefits of selective control of Chinese air pollution emissions. Results from IIASA's Greenhouse Gas - Air Pollution Interactions and Synergies (GAINS) integrated assessment model indicate that methane emission reductions make up > 75% of possible CO2-equivalent emission reductions of the SLCPs and their precursors in China in 2030. A multi-pollutant emission reduction scenario incorporating the 2030 Chinese pollution control measures with the highest potential for future climate impact is applied to the NASA ModelE2 - Yale Interactive Terrestrial Biosphere (NASA ModelE2-YIBs) global carbon - chemistry - climate model to assess the regional and long-range impacts of Chinese SLCP mitigation measures. Using model simulations that incorporate dynamic methane emissions and photosynthesis-dependent isoprene emissions, we quantify the impacts of Chinese reductions of the short-lived air pollutants on radiative forcing and on surface ozone and particulate air pollution. Present-day modeled methane mole fractions are evaluated against SCIAMACHY methane columns and NOAA ESRL/GMD surface flask measurements.

Climate responses to anthropogenic emissions of short-lived climate pollutants

NASA Astrophysics Data System (ADS)

Baker, L. H.; Collins, W. J.; Olivié, D. J. L.; Cherian, R.; Hodnebrog, Ø.; Myhre, G.; Quaas, J.

2015-07-01

Policies to control air quality focus on mitigating emissions of aerosols and their precursors, and other short-lived climate pollutants (SLCPs). On a local scale, these policies will have beneficial impacts on health and crop yields, by reducing particulate matter (PM) and surface ozone concentrations; however, the climate impacts of reducing emissions of SLCPs are less straightforward to predict. In this paper we consider a set of idealized, extreme mitigation strategies, in which the total anthropogenic emissions of individual SLCP emissions species are removed. This provides an upper bound on the potential climate impacts of such air quality strategies. We focus on evaluating the climate responses to changes in anthropogenic emissions of aerosol precursor species: black carbon (BC), organic carbon (OC) and sulphur dioxide (SO2). We perform climate integrations with four fully coupled atmosphere-ocean global climate models (AOGCMs), and examine the effects on global and regional climate of removing the total land-based anthropogenic emissions of each of the three aerosol precursor species. We find that the SO2 emissions reductions lead to the strongest response, with all models showing an increase in surface temperature focussed in the Northern Hemisphere mid and (especially) high latitudes, and showing a corresponding increase in global mean precipitation. Changes in precipitation patterns are driven mostly by a northward shift in the ITCZ (Intertropical Convergence Zone), consistent with the hemispherically asymmetric warming pattern driven by the emissions changes. The BC and OC emissions reductions give a much weaker response, and there is some disagreement between models in the sign of the climate responses to these perturbations. These differences between models are due largely to natural variability in sea-ice extent, circulation patterns and cloud changes. This large natural variability component to the signal when the ocean circulation and sea-ice are

Climate responses to anthropogenic emissions of short-lived climate pollutants

NASA Astrophysics Data System (ADS)

Baker, L. H.; Collins, W. J.; Olivié, D. J. L.; Cherian, R.; Hodnebrog, Ø.; Myhre, G.; Quaas, J.; Samset, B. H.

2015-02-01

Policies to control air quality focus on mitigating emissions of aerosols and their precursors, and other short-lived climate pollutants (SLCPs). On a local scale, these policies will have beneficial impacts on health and crop yields, by reducing particulate matter (PM) and surface ozone concentrations; however, the climate impacts of reducing emissions of SLCPs are less straightforward to predict. In this paper we consider a set of idealised, extreme mitigation strategies, in which the total anthropogenic emissions of individual SLCP emissions species are removed. This provides an upper bound on the potential climate impacts of such air quality strategies. We focus on evaluating the climate responses to changes in anthropogenic emissions of aerosol precursor species: black carbon (BC), organic carbon (OC) and sulphur dioxide (SO2). We perform climate integrations with four fully coupled atmosphere-ocean global climate models (AOGCMs), and examine the effects on global and regional climate of removing the total land-based anthropogenic emissions of each of the three aerosol precursor species. We find that the SO2 emissions reductions lead to the strongest response, with all three models showing an increase in surface temperature focussed in the northern hemisphere high latitudes, and a corresponding increase in global mean precipitation and run-off. Changes in precipitation and run-off patterns are driven mostly by a northward shift in the ITCZ, consistent with the hemispherically asymmetric warming pattern driven by the emissions changes. The BC and OC emissions reductions give a much weaker forcing signal, and there is some disagreement between models in the sign of the climate responses to these perturbations. These differences between models are due largely to natural variability in sea-ice extent, circulation patterns and cloud changes. This large natural variability component to the signal when the ocean circulation and sea-ice are free-running means that the

Creating Near-Term Climate Scenarios for AgMIP

NASA Astrophysics Data System (ADS)

Goddard, L.; Greene, A. M.; Baethgen, W.

2012-12-01

For the next assessment report of the IPCC (AR5), attention is being given to development of climate information that is appropriate for adaptation, such as decadal-scale and near-term predictions intended to capture the combined effects of natural climate variability and the emerging climate change signal. While the science and practice evolve for the production and use of dynamic decadal prediction, information relevant to agricultural decision-makers can be gained from analysis of past decadal-scale trends and variability. Statistical approaches that mimic the characteristics of observed year-to-year variability can indicate the range of possibilities and their likelihood. In this talk we present work towards development of near-term climate scenarios, which are needed to engage decision-makers and stakeholders in the regions in current decision-making. The work includes analyses of decadal-scale variability and trends in the AgMIP regions, and statistical approaches that capture year-to-year variability and the associated persistence of wet and dry years. We will outline the general methodology and some of the specific considerations in the regional application of the methodology for different AgMIP regions, such those for Western Africa versus southern Africa. We will also show some examples of quality checks and informational summaries of the generated data, including (1) metrics of information quality such as probabilistic reliability for a suite of relevant climate variables and indices important for agriculture; (2) quality checks relative to the use of this climate data in crop models; and, (3) summary statistics (e.g., for 5-10-year periods or across given spatial scales).

Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes

DOE PAGES

Paschalis, Athanasios; Fatichi, Simone; Katul, Gabriel G.; ...

2015-08-07

While the importance of ecosystem functioning is undisputed in the context of climate change and Earth system modeling, the role of short-scale temporal variability of hydrometeorological forcing (~1 h) on the related ecosystem processes remains to be fully understood. Additionally, various impacts of meteorological forcing variability on water and carbon fluxes across a range of scales are explored here using numerical simulations. Synthetic meteorological drivers that highlight dynamic features of the short temporal scale in series of precipitation, temperature, and radiation are constructed. These drivers force a mechanistic ecohydrological model that propagates information content into the dynamics of water andmore » carbon fluxes for an ensemble of representative ecosystems. The focus of the analysis is on a cross-scale effect of the short-scale forcing variability on the modeled evapotranspiration and ecosystem carbon assimilation. Interannual variability of water and carbon fluxes is emphasized in the analysis. The main study inferences are summarized as follows: (a) short-scale variability of meteorological input does affect water and carbon fluxes across a wide range of time scales, spanning from the hourly to the annual and longer scales; (b) different ecosystems respond to the various characteristics of the short-scale variability of the climate forcing in various ways, depending on dominant factors limiting system productivity; (c) whenever short-scale variability of meteorological forcing influences primarily fast processes such as photosynthesis, its impact on the slow-scale variability of water and carbon fluxes is small; and (d) whenever short-scale variability of the meteorological forcing impacts slow processes such as movement and storage of water in the soil, the effects of the variability can propagate to annual and longer time scales.« less

Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes

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

Paschalis, Athanasios; Fatichi, Simone; Katul, Gabriel G.

While the importance of ecosystem functioning is undisputed in the context of climate change and Earth system modeling, the role of short-scale temporal variability of hydrometeorological forcing (~1 h) on the related ecosystem processes remains to be fully understood. Additionally, various impacts of meteorological forcing variability on water and carbon fluxes across a range of scales are explored here using numerical simulations. Synthetic meteorological drivers that highlight dynamic features of the short temporal scale in series of precipitation, temperature, and radiation are constructed. These drivers force a mechanistic ecohydrological model that propagates information content into the dynamics of water andmore » carbon fluxes for an ensemble of representative ecosystems. The focus of the analysis is on a cross-scale effect of the short-scale forcing variability on the modeled evapotranspiration and ecosystem carbon assimilation. Interannual variability of water and carbon fluxes is emphasized in the analysis. The main study inferences are summarized as follows: (a) short-scale variability of meteorological input does affect water and carbon fluxes across a wide range of time scales, spanning from the hourly to the annual and longer scales; (b) different ecosystems respond to the various characteristics of the short-scale variability of the climate forcing in various ways, depending on dominant factors limiting system productivity; (c) whenever short-scale variability of meteorological forcing influences primarily fast processes such as photosynthesis, its impact on the slow-scale variability of water and carbon fluxes is small; and (d) whenever short-scale variability of the meteorological forcing impacts slow processes such as movement and storage of water in the soil, the effects of the variability can propagate to annual and longer time scales.« less

Solar variability, weather, and climate

NASA Technical Reports Server (NTRS)

1982-01-01

Advances in the understanding of possible effects of solar variations on weather and climate are most likely to emerge by addressing the subject in terms of fundamental physical principles of atmospheric sciences and solar-terrestrial physis. The limits of variability of solar inputs to the atmosphere and the depth in the atmosphere to which these variations have significant effects are determined.

Frontiers in Decadal Climate Variability: Proceedings of a Workshop

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

Purcell, Amanda

A number of studies indicate an apparent slowdown in the overall rise in global average surface temperature between roughly 1998 and 2014. Most models did not predict such a slowdown--a fact that stimulated a lot of new research on variability of Earth's climate system. At a September 2015 workshop, leading scientists gathered to discuss current understanding of climate variability on decadal timescales (10 to 30 years) and whether and how prediction of it might be improved. Many researchers have focused their attention on the climate system itself, which is known to vary across seasons, decades, and other timescales. Several naturalmore » variables produce "ups and downs" in the climate system, which are superimposed on the long-term warming trend due to human influence. Understanding decadal climate variability is important not only for assessing global climate change but also for improving decision making related to infrastructure, water resources, agriculture, energy, and other realms. Like the well-studied El Nino and La Nina interannual variations, decadal climate variability is associated with specific regional patterns of temperature and precipitation, such as heat waves, cold spells, and droughts. Several participants shared research that assesses decadal predictive capability of current models.« less

On climate prediction: how much can we expect from climate memory?

NASA Astrophysics Data System (ADS)

Yuan, Naiming; Huang, Yan; Duan, Jianping; Zhu, Congwen; Xoplaki, Elena; Luterbacher, Jürg

2018-03-01

Slowing variability in climate system is an important source of climate predictability. However, it is still challenging for current dynamical models to fully capture the variability as well as its impacts on future climate. In this study, instead of simulating the internal multi-scale oscillations in dynamical models, we discussed the effects of internal variability in terms of climate memory. By decomposing climate state x(t) at a certain time point t into memory part M(t) and non-memory part ɛ (t) , climate memory effects from the past 30 years on climate prediction are quantified. For variables with strong climate memory, high variance (over 20% ) in x(t) is explained by the memory part M(t), and the effects of climate memory are non-negligible for most climate variables, but the precipitation. Regarding of multi-steps climate prediction, a power law decay of the explained variance was found, indicating long-lasting climate memory effects. The explained variances by climate memory can remain to be higher than 10% for more than 10 time steps. Accordingly, past climate conditions can affect both short (monthly) and long-term (interannual, decadal, or even multidecadal) climate predictions. With the memory part M(t) precisely calculated from Fractional Integral Statistical Model, one only needs to focus on the non-memory part ɛ (t) , which is an important quantity that determines climate predictive skills.

Short-term variability and long-term change in the composition of the littoral zone fish community in Spirit Lake, Iowa

USGS Publications Warehouse

Pierce, C.L.; Sexton, M.D.; Pelham, M.E.; Larscheid, J.G.

2001-01-01

We assessed short-term variability and long-term change in the composition of the littoral fish community in Spirit Lake, Iowa. Fish were sampled in several locations at night with large beach seines during spring, summer and fall of 1995-1998. Long-term changes were inferred from comparison with a similar study conducted over 70 y earlier in Spirit Lake. We found 26 species in the littoral zone. The number of species per sample ranged from 4 to 18, averaging 11.8. The average number of species per sample was higher at stations with greater vegetation density. A distinct seasonal pattern was evident in the number of species collected per sample in most years, increasing steadily from spring to fall. Patterns of variability within our 1995-1998 study period suggest that: (1) numerous samples are necessary to adequately characterize a littoral fish community, (2) sampling should be done when vegetation and young-of-year densities are highest and (3) sampling during a single year is inadequate to reveal the full community. The number of native species has declined by approximately 25% over the last 70 y. A coincident decline in littoral vegetation and associated habitat changes during the same period are likely causes of the long-term community change.

Long-term streamflow response to climatic variability in the Loess Plateau, China

Treesearch

Shenping Wang; Zhiqiang Zhang; Ge Sun; Steven G. McNulty; Huayong Zhang; Jianlao Li; Manliang Zhang

2008-01-01

The Loess Plateau region in northwestern China has experienced severe water resource shortages due to the combined impacts of climate and land use changes and water resource exploitation during the past decades. This study was designed to examine the impacts of climatic variability on streamflow characteristics of a 12-km2 watershed near Tianshui City, Gansu Province...

NPOESS, Essential Climates Variables and Climate Change

NASA Astrophysics Data System (ADS)

Forsythe-Newell, S. P.; Bates, J. J.; Barkstrom, B. R.; Privette, J. L.; Kearns, E. J.

2008-12-01

Advancement in understanding, predicting and mitigating against climate change implies collaboration, close monitoring of Essential Climate Variable (ECV)s through development of Climate Data Record (CDR)s and effective action with specific thematic focus on human and environmental impacts. Towards this end, NCDC's Scientific Data Stewardship (SDS) Program Office developed Climate Long-term Information and Observation system (CLIO) for satellite data identification, characterization and use interrogation. This "proof-of-concept" online tool provides the ability to visualize global CDR information gaps and overlaps with options to temporally zoom-in from satellite instruments to climate products, data sets, data set versions and files. CLIO provides an intuitive one-stop web site that displays past, current and planned launches of environmental satellites in conjunction with associated imagery and detailed information. This tool is also capable of accepting and displaying Web-based input from Subject Matter Expert (SME)s providing a global to sub-regional scale perspective of all ECV's and their impacts upon climate studies. SME's can access and interact with temporal data from the past and present, or for future planning of products, datasets/dataset versions, instruments, platforms and networks. CLIO offers quantifiable prioritization of ECV/CDR impacts that effectively deal with climate change issues, their associated impacts upon climate, and this offers an intuitively objective collaboration and consensus building tool. NCDC's latest tool empowers decision makers and the scientific community to rapidly identify weaknesses and strengths in climate change monitoring strategies and significantly enhances climate change collaboration and awareness.

Heavy precipitation in a changing climate: Does short-term summer precipitation increase faster?

NASA Astrophysics Data System (ADS)

Ban, Nikolina; Schmidli, Juerg; Schär, Christoph

2015-04-01

it is inconsistent to extrapolate from present-day super-adiabatic precipitation scaling into the future. The applicability of the Clausius-Clapeyron scaling across the whole event spectrum is a potentially useful result for climate impact adaptation. Ban, N., J. Schmidli and C. Schär (2015): Heavy precipitation in a changing climate: Does short-term summer precipitation increase faster? Submitted to GRL. Ban, N., J. Schmidli and C. Schär (2014): Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations. J. Geophys. Res. Atmos.,119, 7889-7907, doi:10.1002/2014JD021478

Local air temperature tolerance: a sensible basis for estimating climate variability

NASA Astrophysics Data System (ADS)

Kärner, Olavi; Post, Piia

2016-11-01

The customary representation of climate using sample moments is generally biased due to the noticeably nonstationary behaviour of many climate series. In this study, we introduce a moment-free climate representation based on a statistical model fitted to a long-term daily air temperature anomaly series. This model allows us to separate the climate and weather scale variability in the series. As a result, the climate scale can be characterized using the mean annual cycle of series and local air temperature tolerance, where the latter is computed using the fitted model. The representation of weather scale variability is specified using the frequency and the range of outliers based on the tolerance. The scheme is illustrated using five long-term air temperature records observed by different European meteorological stations.

Disentangling the effects of CO2 and short-lived climate forcer mitigation.

PubMed

Rogelj, Joeri; Schaeffer, Michiel; Meinshausen, Malte; Shindell, Drew T; Hare, William; Klimont, Zbigniew; Velders, Guus J M; Amann, Markus; Schellnhuber, Hans Joachim

2014-11-18

Anthropogenic global warming is driven by emissions of a wide variety of radiative forcers ranging from very short-lived climate forcers (SLCFs), like black carbon, to very long-lived, like CO2. These species are often released from common sources and are therefore intricately linked. However, for reasons of simplification, this CO2-SLCF linkage was often disregarded in long-term projections of earlier studies. Here we explicitly account for CO2-SLCF linkages and show that the short- and long-term climate effects of many SLCF measures consistently become smaller in scenarios that keep warming to below 2 °C relative to preindustrial levels. Although long-term mitigation of methane and hydrofluorocarbons are integral parts of 2 °C scenarios, early action on these species mainly influences near-term temperatures and brings small benefits for limiting maximum warming relative to comparable reductions taking place later. Furthermore, we find that maximum 21st-century warming in 2 °C-consistent scenarios is largely unaffected by additional black-carbon-related measures because key emission sources are already phased-out through CO2 mitigation. Our study demonstrates the importance of coherently considering CO2-SLCF coevolutions. Failing to do so leads to strongly and consistently overestimating the effect of SLCF measures in climate stabilization scenarios. Our results reinforce that SLCF measures are to be considered complementary rather than a substitute for early and stringent CO2 mitigation. Near-term SLCF measures do not allow for more time for CO2 mitigation. We disentangle and resolve the distinct benefits across different species and therewith facilitate an integrated strategy for mitigating both short and long-term climate change.

Disentangling the effects of CO2 and short-lived climate forcer mitigation

PubMed Central

Rogelj, Joeri; Schaeffer, Michiel; Meinshausen, Malte; Shindell, Drew T.; Hare, William; Klimont, Zbigniew; Amann, Markus; Schellnhuber, Hans Joachim

2014-01-01

Anthropogenic global warming is driven by emissions of a wide variety of radiative forcers ranging from very short-lived climate forcers (SLCFs), like black carbon, to very long-lived, like CO2. These species are often released from common sources and are therefore intricately linked. However, for reasons of simplification, this CO2–SLCF linkage was often disregarded in long-term projections of earlier studies. Here we explicitly account for CO2–SLCF linkages and show that the short- and long-term climate effects of many SLCF measures consistently become smaller in scenarios that keep warming to below 2 °C relative to preindustrial levels. Although long-term mitigation of methane and hydrofluorocarbons are integral parts of 2 °C scenarios, early action on these species mainly influences near-term temperatures and brings small benefits for limiting maximum warming relative to comparable reductions taking place later. Furthermore, we find that maximum 21st-century warming in 2 °C-consistent scenarios is largely unaffected by additional black-carbon-related measures because key emission sources are already phased-out through CO2 mitigation. Our study demonstrates the importance of coherently considering CO2–SLCF coevolutions. Failing to do so leads to strongly and consistently overestimating the effect of SLCF measures in climate stabilization scenarios. Our results reinforce that SLCF measures are to be considered complementary rather than a substitute for early and stringent CO2 mitigation. Near-term SLCF measures do not allow for more time for CO2 mitigation. We disentangle and resolve the distinct benefits across different species and therewith facilitate an integrated strategy for mitigating both short and long-term climate change. PMID:25368182

Among-tree variability and feedback effects result in different growth responses to climate change at the upper treeline in the Swiss Alps.

PubMed

Jochner, Matthias; Bugmann, Harald; Nötzli, Magdalena; Bigler, Christof

2017-10-01

Upper treeline ecotones are important life form boundaries and particularly sensitive to a warming climate. Changes in growth conditions at these ecotones have wide-ranging implications for the provision of ecosystem services in densely populated mountain regions like the European Alps. We quantify climate effects on short- and long-term tree growth responses, focusing on among-tree variability and potential feedback effects. Although among-tree variability is thought to be substantial, it has not been considered systematically yet in studies on growth-climate relationships. We compiled tree-ring data including almost 600 trees of major treeline species ( Larix decidua , Picea abies , Pinus cembra , and Pinus mugo ) from three climate regions of the Swiss Alps. We further acquired tree size distribution data using unmanned aerial vehicles. To account for among-tree variability, we employed information-theoretic model selections based on linear mixed-effects models (LMMs) with flexible choice of monthly temperature effects on growth. We isolated long-term trends in ring-width indices (RWI) in interaction with elevation. The LMMs revealed substantial amounts of previously unquantified among-tree variability, indicating different strategies of single trees regarding when and to what extent to invest assimilates into growth. Furthermore, the LMMs indicated strongly positive temperature effects on growth during short summer periods across all species, and significant contributions of fall ( L. decidua ) and current year's spring ( L. decidua , P. abies ). In the longer term, all species showed consistently positive RWI trends at highest elevations, but different patterns with decreasing elevation. L. decidua exhibited even negative RWI trends compared to the highest treeline sites, whereas P. abies , P. cembra , and P. mugo showed steeper or flatter trends with decreasing elevation. This does not only reflect effects of ameliorated climate conditions on tree

Role of the Soil Thermal Inertia in the short term variability of the surface temperature and consequences for the soil-moisture temperature feedback

NASA Astrophysics Data System (ADS)

Cheruy, Frederique; Dufresne, Jean-Louis; Ait Mesbah, Sonia; Grandpeix, Jean-Yves; Wang, Fuxing

2017-04-01

A simple model based on the surface energy budget at equilibrium is developed to compute the sensitivity of the climatological mean daily temperature and diurnal amplitude to the soil thermal inertia. It gives a conceptual framework to quantity the role of the atmospheric and land surface processes in the surface temperature variability and relies on the diurnal amplitude of the net surface radiation, the sensitivity of the turbulent fluxes to the surface temperature and the thermal inertia. The performances of the model are first evaluated with 3D numerical simulations performed with the atmospheric (LMDZ) and land surface (ORCHIDEE) modules of the Institut Pierre Simon Laplace (IPSL) climate model. A nudging approach is adopted, it prevents from using time-consuming long-term simulations required to account for the natural variability of the climate and allow to draw conclusion based on short-term (several years) simulations. In the moist regions the diurnal amplitude and the mean surface temperature are controlled by the latent heat flux. In the dry areas, the relevant role of the stability of the boundary layer and of the soil thermal inertia is demonstrated. In these regions, the sensitivity of the surface temperature to the thermal inertia is high, due to the high contribution of the thermal flux to the energy budget. At high latitudes, when the sensitivity of turbulent fluxes is dominated by the day-time sensitivity of the sensible heat flux to the surface temperature and when this later is comparable to the thermal inertia term of the sensitivity equation, the surface temperature is also partially controlled by the thermal inertia which can rely on the snow properties; In the regions where the latent heat flux exhibits a high day-to-day variability, such as transition regions, the thermal inertia has also significant impact on the surface temperature variability . In these not too wet (energy limited) and not too dry (moisture-limited) soil moisture (SM

HIST-EU - a dataset of European relevance, a database to enable long-term climate variability studies on regional scale

NASA Astrophysics Data System (ADS)

Auer, I.; Böhm, R.; Ganekind, M.; Schöner, W.; Nemec, J.; Chimani, B.

2010-09-01

Instrumental time series of different climate elements are an important requisite for climate and climate impact studies. Long-term time series can improve our understanding of climate change during the instrumental period. During recent decades a number of national and international initiatives in European countries have significantly increased the number of existing long-term instrumental series; however a publically available data base covering Europe has not been created so far. For the "Greater Alpine Region" (4-19 deg E, 43-49 deg N, 0-3500m asl) the HISTALP data base has been established consisting of monthly homogenised temperature, pressure, precipitation, sunshine and cloudiness records. The data set may be described as follows: Long-term (fully exploiting the potential of systematically measured data). dense (network density adequate in respect to the spatial coherence of the given climate element) quality improved (outliers removed, gaps filled) homogenised (earlier sections adjusted to the recent state of the measuring site) multiple (covering more than one climate element) user friendly (well described and kept in different modes for different applications) HIST-EU is inteded to be a data set of European relevance allowing studying climate variability on regional scale. It focuses on data collection, data recovery and rescue, and homogenizing. HIST-EU will use the infrastructure of HISTALP (www.zamg.ac.at/histalp) and will allow free or restricted data access due to the regulations of data providers. HIST-EU will be carried out under the umbrella of ECSN/EUMETNET.

Exploring the Variability of Short-term Precipitation and Hydrological Response of Small Czech Watersheds

NASA Astrophysics Data System (ADS)

Kavka, Petr; Strouhal, Ludek; Weyskrabova, Lenka; Müller, Miloslav; Kozant, Petr

2017-04-01

The short-term rainfall temporal distribution is known to have a significant effect on the small watersheds' hydrological response. In Czech Republic there are limited publicly available data on rainfall patterns of short-term precipitation. On one side there are catalogues of very short-term synthetic rainfalls used in urban drainage planning and on the other side hourly distribution of daily totals of rainfalls with long return period for larger catchments analyses. This contribution introduces the preliminary outcomes of a running three years' project, which should bridge this gap and provide such data and methodology to the community of scientists, state administration as well as design planners. Six generalized 6-hours hyetographs with 1 minute resolution were derived from 10 years of radar and gauging stations data. These hyetographs are accompanied with information concerning the region of occurrence as well as their frequency related to the rainfall amount. In the next step these hyetographs are used in a complex sensitivity analysis focused on a rainfall-runoff response of small watersheds. This analysis takes into account the uncertainty related to type of the hydrological model, watershed characteristics and main model routines parameterization. Five models with different methods and structure are considered and each model is applied on 5 characteristic watersheds selected from a classification of 7700 small Czech watersheds. For each combination of model and watershed 30, rainfall scenarios were simulated and other scenarios will be used to address the parameters uncertainty. In the last step the variability of outputs will be assessed in the context of economic impacts on design of landscape water structures or mitigation measures. The research is supported by the grant QJ1520265 of the Czech Ministry of Agriculture, rainfall data were provided by the Czech Hydrometeorological Institute.

Climate variability and salmonellosis in Singapore - A time series analysis.

PubMed

Aik, Joel; Heywood, Anita E; Newall, Anthony T; Ng, Lee-Ching; Kirk, Martyn D; Turner, Robin

2018-10-15

Climate change is expected to bring about global warming and an increase in the frequency of extreme weather events. This may consequently influence the transmission of food-borne diseases. The short term associations between climatic conditions and Salmonella infections are well documented in temperate climates but not in the tropics. We conducted an ecological time series analysis to estimate the short term associations between non-outbreak, non-travel associated reports of Salmonella infections and observed climatic conditions from 2005 to 2015 for Singapore. We used a negative binomial time series regression model to analyse the associations on a weekly scale, controlling for season, long term trend, delayed weather effects, autocorrelation and the period where Salmonella was made legally notifiable. There were a total of 11,324 Salmonella infections reported during our study period. A 1 °C increase in mean ambient air temperature was associated with a 4.3% increase (Incidence Rate Ratio [IRR]: 1.043, 95% confidence interval [CI] = 1.003, 1.084) in reported Salmonella infections in the same week and a 6.3% increase (IRR: 1.063, 95% CI = 1.022, 1.105) three weeks later. A 1% increase in the mean relative humidity was associated with a 1.3% decrease (IRR: 0.987, 95% CI = 0.981, 0.994) in cases six weeks later, while a 10 mm increase in weekly cumulative rainfall was associated with a 0.8% increase (IRR: 1.008, 95% CI = 1.002, 1.015) in cases 2 weeks later but a 0.9% decrease (IRR: 0.991, 95% CI = 0.984, 0.998) in cases 5 weeks later. No thresholds for these weather effects were detected. This study confirms the short-term influence of climatic conditions on Salmonella infections in Singapore and the potential impact of climate change on Salmonellosis in the tropics. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Climate Impact of Solar Variability

NASA Technical Reports Server (NTRS)

Schatten, Kenneth H. (Editor); Arking, Albert (Editor)

1990-01-01

The conference on The Climate Impact of Solar Variability, was held at Goddard Space Flight Center from April 24 to 27, 1990. In recent years they developed a renewed interest in the potential effects of increasing greenhouse gases on climate. Carbon dioxide, methane, nitrous oxide, and the chlorofluorocarbons have been increasing at rates that could significantly change climate. There is considerable uncertainty over the magnitude of this anthropogenic change. The climate system is very complex, with feedback processes that are not fully understood. Moreover, there are two sources of natural climate variability (volcanic aerosols and solar variability) added to the anthropogenic changes which may confuse our interpretation of the observed temperature record. Thus, if we could understand the climatic impact of the natural variability, it would aid our interpretation and understanding of man-made climate changes.

Microgravity alters respiratory sinus arrhythmia and short-term heart rate variability in humans

NASA Technical Reports Server (NTRS)

Migeotte, P-F; Prisk, G. Kim; Paiva, M.; West, J. B. (Principal Investigator)

2003-01-01

We studied heart rate (HR), heart rate variability (HRV), and respiratory sinus arrhythmia (RSA) in four male subjects before, during, and after 16 days of spaceflight. The electrocardiogram and respiration were recorded during two periods of 4 min controlled breathing at 7.5 and 15 breaths/min in standing and supine postures on the ground and in microgravity. Low (LF)- and high (HF)-frequency components of the short-term HRV (< or =3 min) were computed through Fourier spectral analysis of the R-R intervals. Early in microgravity, HR was decreased compared with both standing and supine positions and had returned to the supine value by the end of the flight. In microgravity, overall variability, the LF-to-HF ratio, and RSA amplitude and phase were similar to preflight supine values. Immediately postflight, HR increased by approximately 15% and remained elevated 15 days after landing. LF/HF was increased, suggesting an increased sympathetic control of HR standing. The overall variability and RSA amplitude in supine decreased postflight, suggesting that vagal tone decreased, which coupled with the decrease in RSA phase shift suggests that this was the result of an adaptation of autonomic control of HR to microgravity. In addition, these alterations persisted for at least 15 days after return to normal gravity (1G).

Short-term memory and long-term memory are still different.

PubMed

Norris, Dennis

2017-09-01

A commonly expressed view is that short-term memory (STM) is nothing more than activated long-term memory. If true, this would overturn a central tenet of cognitive psychology-the idea that there are functionally and neurobiologically distinct short- and long-term stores. Here I present an updated case for a separation between short- and long-term stores, focusing on the computational demands placed on any STM system. STM must support memory for previously unencountered information, the storage of multiple tokens of the same type, and variable binding. None of these can be achieved simply by activating long-term memory. For example, even a simple sequence of digits such as "1, 3, 1" where there are 2 tokens of the digit "1" cannot be stored in the correct order simply by activating the representations of the digits "1" and "3" in LTM. I also review recent neuroimaging data that has been presented as evidence that STM is activated LTM and show that these data are exactly what one would expect to see based on a conventional 2-store view. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Short-Term Memory and Long-Term Memory are Still Different

PubMed Central

2017-01-01

A commonly expressed view is that short-term memory (STM) is nothing more than activated long-term memory. If true, this would overturn a central tenet of cognitive psychology—the idea that there are functionally and neurobiologically distinct short- and long-term stores. Here I present an updated case for a separation between short- and long-term stores, focusing on the computational demands placed on any STM system. STM must support memory for previously unencountered information, the storage of multiple tokens of the same type, and variable binding. None of these can be achieved simply by activating long-term memory. For example, even a simple sequence of digits such as “1, 3, 1” where there are 2 tokens of the digit “1” cannot be stored in the correct order simply by activating the representations of the digits “1” and “3” in LTM. I also review recent neuroimaging data that has been presented as evidence that STM is activated LTM and show that these data are exactly what one would expect to see based on a conventional 2-store view. PMID:28530428

Quantitative Assessment of Antarctic Climate Variability and Change

NASA Astrophysics Data System (ADS)

Ordonez, A.; Schneider, D. P.

2013-12-01

The Antarctic climate is both extreme and highly variable, but there are indications it may be changing. As the climate in Antarctica can affect global sea level and ocean circulation, it is important to understand and monitor its behavior. Observational and model data have been used to study climate change in Antarctica and the Southern Ocean, though observational data is sparse and models have difficulty reproducing many observed climate features. For example, a leading hypothesis that ozone depletion has been responsible for sea ice trends is struggling with the inability of ozone-forced models to reproduce the observed sea ice increase. The extent to which this data-model disagreement represents inadequate observations versus model biases is unknown. This research assessed a variety of climate change indicators to present an overview of Antarctic climate that will allow scientists to easily access this data and compare indicators with other observational data and model output. Indicators were obtained from observational and reanalysis data for variables such as temperature, sea ice area, and zonal wind stress. Multiple datasets were used for key variables. Monthly and annual anomaly data from Antarctica and the Southern Ocean as well as tropical indices were plotted as time series on common axes for comparison. Trends and correlations were also computed. Zonal wind, surface temperature, and austral springtime sea ice had strong relationships and were further discussed in terms of how they may relate to climate variability and change in the Antarctic. This analysis will enable hypothesized mechanisms of Antarctic climate change to be critically evaluated.

Beyond Quarterly Earnings: Preparing the Business Community for Long-term Climate Risks

NASA Astrophysics Data System (ADS)

Carlson, C.; Goldman, G. T.

2014-12-01

The business community stands to be highly impacted by climate change. In both short and long-term timescales, climate change presents material and financial risks to companies in diverse economic sectors. How the private sector accounts for long-term risks while making short-term decisions about operations is a complex challenge. Companies are accountable to shareholders and must report performance to them on a quarterly basis. At the same time, company investors are exposed to long-term climate-related risks and face losses if companies fail to prepare for climate impacts. The US Securities and Exchange Commission (SEC) obligates publicly traded companies to discuss risks that might materially affect their business and since 2010, the agency recommends that companies consider and discuss any significant risks to their business from climate change. Some companies have complied with this guidance and comprehensively analyze potential climate change impacts, yet others fail to consider climate change at all. Such omissions leave companies without plans for addressing future risks and expose investors and the public to potential catastrophic events from climate change impacts. Climate risk projections can inform companies about the vulnerability of their facilities, supply chains, transportation pathways, and other assets. Such projections can help put climate-related risks in terms of material costs for companies and their investors. Focusing on the vulnerability of coastal facilities, we will use climate change impact projections to demonstrate the economic impacts of climate change faced by the private sector. These risks are then compared to company disclosures to the SEC to assess the degree to which companies have considered their vulnerability to climate change. Finally, we will discuss ways that companies can better assess and manage long-term climate risks.

Changes in climate variability with reference to land quality and agriculture in Scotland.

PubMed

Brown, Iain; Castellazzi, Marie

2015-06-01

Classification and mapping of land capability represents an established format for summarising spatial information on land quality and land-use potential. By convention, this information incorporates bioclimatic constraints through the use of a long-term average. However, climate change means that land capability classification should also have a dynamic temporal component. Using an analysis based upon Land Capability for Agriculture in Scotland, it is shown that this dynamism not only involves the long-term average but also shorter term spatiotemporal patterns, particularly through changes in interannual variability. Interannual and interdecadal variations occur both in the likelihood of land being in prime condition (top three capability class divisions) and in class volatility from year to year. These changing patterns are most apparent in relation to the west-east climatic gradient which is mainly a function of precipitation regime and soil moisture. Analysis is also extended into the future using climate results for the 2050s from a weather generator which show a complex interaction between climate interannual variability and different soil types for land quality. In some locations, variability of land capability is more likely to decrease because the variable climatic constraints are relaxed and the dominant constraint becomes intrinsic soil properties. Elsewhere, climatic constraints will continue to be influential. Changing climate variability has important implications for land-use planning and agricultural management because it modifies local risk profiles in combination with the current trend towards agricultural intensification and specialisation.

Relationships between northern Adriatic Sea mucilage events and climate variability.

PubMed

Deserti, Marco; Cacciamani, Carlo; Chiggiato, Jacopo; Rinaldi, Attilio; Ferrari, Carla R

2005-12-15

A long term analysis (1865-2002) of meteorological data collected in the Po Valley and Northern Adriatic Basin have been analysed to find possible links between variability in the climatic parameters and the phenomenon of mucilage. Seasonal anomalies of temperature, calculated as spatial mean over the Po Valley area, and anomalies of North Atlantic Oscillation were compared with the historical record of mucilage episodes. Both climatic indices were found to be positively correlated with mucilage events, suggesting a possible relationship between climatic variability and the increased appearance of mucilage aggregates.

Facing the Future: Effects of Short-Term Climate Extremes on Isoprene-Emitting and Nonemitting Poplar.

PubMed

Vanzo, Elisa; Jud, Werner; Li, Ziru; Albert, Andreas; Domagalska, Malgorzata A; Ghirardo, Andrea; Niederbacher, Bishu; Frenzel, Juliane; Beemster, Gerrit T S; Asard, Han; Rennenberg, Heinz; Sharkey, Thomas D; Hansel, Armin; Schnitzler, Jörg-Peter

2015-09-01

Isoprene emissions from poplar (Populus spp.) plantations can influence atmospheric chemistry and regional climate. These emissions respond strongly to temperature, [CO2], and drought, but the superimposed effect of these three climate change factors are, for the most part, unknown. Performing predicted climate change scenario simulations (periodic and chronic heat and drought spells [HDSs] applied under elevated [CO2]), we analyzed volatile organic compound emissions, photosynthetic performance, leaf growth, and overall carbon (C) gain of poplar genotypes emitting (IE) and nonemitting (NE) isoprene. We aimed (1) to evaluate the proposed beneficial effect of isoprene emission on plant stress mitigation and recovery capacity and (2) to estimate the cumulative net C gain under the projected future climate. During HDSs, the chloroplastidic electron transport rate of NE plants became impaired, while IE plants maintained high values similar to unstressed controls. During recovery from HDS episodes, IE plants reached higher daily net CO2 assimilation rates compared with NE genotypes. Irrespective of the genotype, plants undergoing chronic HDSs showed the lowest cumulative C gain. Under control conditions simulating ambient [CO2], the C gain was lower in the IE plants than in the NE plants. In summary, the data on the overall C gain and plant growth suggest that the beneficial function of isoprene emission in poplar might be of minor importance to mitigate predicted short-term climate extremes under elevated [CO2]. Moreover, we demonstrate that an analysis of the canopy-scale dynamics of isoprene emission and photosynthetic performance under multiple stresses is essential to understand the overall performance under proposed future conditions. © 2015 American Society of Plant Biologists. All Rights Reserved.

Within-Session Stability of Short-Term Heart Rate Variability Measurement

PubMed Central

2016-01-01

Abstract The primary aim of this study was to assess the retest stability of the short-term heart rate variability (HRV) measurement performed within one session and without the use of any intervention. Additionally, a precise investigation of the possible impact of intrinsic biological variation on HRV reliability was also performed. First, a single test-retest HRV measurement was conducted with 20-30 min apart from one another. Second, the HRV measurement was repeated in ten non-interrupted consecutive intervals. The lowest typical error (CV = 21.1%) was found for the square root of the mean squared differences of successive RR intervals (rMSSD) and the highest for the low frequency power (PLF) (CV = 93.9%). The standardized changes in the mean were trivial to small. The correlation analysis revealed the highest level for ln rMSSD (ICC = 0.87), while ln PLF represented the worst case (ICC = 0.59). The reliability indices for ln rMSSD in 10 consecutive intervals improved (CV = 9.9%; trivial standardized changes in the mean; ICC = 0.96). In conclusion, major differences were found in the reliability level between the HRV indices. The rMSSD demonstrated the highest reliability level. No substantial influence of intrinsic biological variation on the HRV reliability was observed. PMID:28149345

Risk factors and prediction of very short term versus short/intermediate term post-stroke mortality: a data mining approach.

PubMed

Easton, Jonathan F; Stephens, Christopher R; Angelova, Maia

2014-11-01

Data mining and knowledge discovery as an approach to examining medical data can limit some of the inherent bias in the hypothesis assumptions that can be found in traditional clinical data analysis. In this paper we illustrate the benefits of a data mining inspired approach to statistically analysing a bespoke data set, the academic multicentre randomised control trial, U.K Glucose Insulin in Stroke Trial (GIST-UK), with a view to discovering new insights distinct from the original hypotheses of the trial. We consider post-stroke mortality prediction as a function of days since stroke onset, showing that the time scales that best characterise changes in mortality risk are most naturally defined by examination of the mortality curve. We show that certain risk factors differentiate between very short term and intermediate term mortality. In particular, we show that age is highly relevant for intermediate term risk but not for very short or short term mortality. We suggest that this is due to the concept of frailty. Other risk factors are highlighted across a range of variable types including socio-demographics, past medical histories and admission medication. Using the most statistically significant risk factors we build predictive classification models for very short term and short/intermediate term mortality. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Changing precipitation in western Europe, climate change or natural variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart

2017-04-01

Multi-model RCM-GCM ensembles provide high resolution climate projections, valuable for among others climate impact assessment studies. While the application of multiple models (both GCMs and RCMs) provides a certain robustness with respect to model uncertainty, the interpretation of differences between ensemble members - the combined result of model uncertainty and natural variability of the climate system - is not straightforward. Natural variability is intrinsic to the climate system, and a potentially large source of uncertainty in climate change projections, especially for projections on the local to regional scale. To quantify the natural variability and get a robust estimate of the forced climate change response (given a certain model and forcing scenario), large ensembles of climate model simulations of the same model provide essential information. While for global climate models (GCMs) a number of such large single model ensembles exists and have been analyzed, for regional climate models (RCMs) the number and size of single model ensembles is limited, and the predictability of the forced climate response at the local to regional scale is still rather uncertain. We present a regional downscaling of a 16-member single model ensemble over western Europe and the Alps at a resolution of 0.11 degrees (˜12km), similar to the highest resolution EURO-CORDEX simulations. This 16-member ensemble was generated by the GCM EC-EARTH, which was downscaled with the RCM RACMO for the period 1951-2100. This single model ensemble has been investigated in terms of the ensemble mean response (our estimate of the forced climate response), as well as the difference between the ensemble members, which measures natural variability. We focus on the response in seasonal mean and extreme precipitation (seasonal maxima and extremes with a return period up to 20 years) for the near to far future. For most precipitation indices we can reliably determine the climate change signal, given

Deglacial-Holocene short-term variability in sea-ice distribution on the Eurasian shelf (Arctic Ocean) - An IP25 biomarker reconstruction.

NASA Astrophysics Data System (ADS)

Hörner, Tanja; Stein, Ruediger; Fahl, Kirsten

2016-04-01

Four well-dated sediment cores from the Eurasian continental shelf, i.e., the Kara Sea (Cores BP99/07 and BP00/07) and Laptev Sea (Cores PS51/154 and PS51/159), were selected for high-resolution reconstruction of past Arctic environmental conditions during the deglacial-Holocene time interval. These marginal seas are strongly affected by the post-glacial sea-level rise of about 120m. The major focus of our study was the reconstruction of the paleo-sea-ice distribution as sea-ice plays a key role within the modern and past climate system. For reconstruction of paleo-sea ice, the sea-ice proxy IP25 in combination with open-water phytoplankton biomarkers was used (for approach see Belt et al., 2007; Müller et al., 2009, 2011). In addition, specific sterols were determined to reconstruct changes in river run-off and biological production. The post-glacial sea-level rise is especially reflected in prominent decrease in terrigenous biomarkers. Deglacial variations in sea-ice cover sustained for thousand of years, mostly following climatic changes like the Bølling/Allerød (14.7-12.9 ka), Younger Dryas (12.9-11.6 ka) and Holocene warm phase (10-8 ka). Superimposed on a (Late) Holocene cooling trend, short-term fluctuations in sea-ice cover (on centennial scale) are distinctly documented in the distal/off-shore Core BP00/07 from the Kara Sea, less pronounced in the proximal/near-shore Core PS99/07 and in the Laptev Sea cores. Interestingly, this short-term variability in sea-ice cover correlates quite well to changes in Siberian river run-off (e.g., Stein et al. 2004), pointing to a direct linkage between precipitation (atmospheric circulation) and sea-ice formation. References Belt, S.T., Massé, G., Rowland, S.J., Poulin, M., Michel, C., LeBlanc, B., 2007. A novel chemical fossil of palaeo sea ice: IP25. Organic Geochemistry 38, 16-27. Müller, J., Masse, G., Stein, R., Belt, S.T., 2009. Variability of sea-ice conditions in the Fram Strait over the past 30,000 years

Short-term meso-scale variability of mesozooplankton communities in a coastal upwelling system (NW Spain)

NASA Astrophysics Data System (ADS)

Roura, Álvaro; Álvarez-Salgado, Xosé A.; González, Ángel F.; Gregori, María; Rosón, Gabriel; Guerra, Ángel

2013-02-01

The short-term, meso-scale variability of the mesozooplankton community present in the coastal upwelling system of the Ría de Vigo (NW Spain) has been analysed. Three well-defined communities were identified: coastal, frontal and oceanic, according to their holoplankton-meroplankton ratio, richness, and total abundance. These communities changed from summer to autumn due to a shift from downwelling to upwelling-favourable conditions coupled with taxa dependent changes in life strategies. Relationships between the resemblance matrix of mesozooplankton and the resemblance matrices of meteorologic, hydrographic and community-derived biotic variables were determined with distance-based linear models (DistLM, 18 variables), showing an increasing amount of explained variability of 6%, 16.1% and 54.5%, respectively. A simplified model revealed that the variability found in the resemblance matrix of mesozooplankton was mainly described by the holoplankton-meroplankton ratio, the total abundance, the influence of lunar cycles, the upwelling index and the richness; altogether accounting for 64% of the total variability. The largest variability of the mesozooplankton resemblance matrix (39.6%) is accounted by the holoplankton-meroplankton ratio, a simple index that describes appropriately the coastal-ocean gradient. The communities described herein kept their integrity in the studied upwelling and downwelling episodes in spite of the highly advective environment off the Ría de Vigo, presumably due to behavioural changes in the vertical position of the zooplankton.

Analysis of rainfall and temperature time series to detect long-term climatic trends and variability over semi-arid Botswana

NASA Astrophysics Data System (ADS)

Byakatonda, Jimmy; Parida, B. P.; Kenabatho, Piet K.; Moalafhi, D. B.

2018-03-01

Arid and semi-arid environments have been identified with locations prone to impacts of climate variability and change. Investigating long-term trends is one way of tracing climate change impacts. This study investigates variability through annual and seasonal meteorological time series. Possible inhomogeneities and years of intervention are analysed using four absolute homogeneity tests. Trends in the climatic variables were determined using Mann-Kendall and Sen's Slope estimator statistics. Association of El Niño Southern Oscillation (ENSO) with local climate is also investigated through multivariate analysis. Results from the study show that rainfall time series are fully homogeneous with 78.6 and 50% of the stations for maximum and minimum temperature, respectively, showing homogeneity. Trends also indicate a general decrease of 5.8, 7.4 and 18.1% in annual, summer and winter rainfall, respectively. Warming trends are observed in annual and winter temperature at 0.3 and 1.5% for maximum temperature and 1.7 and 6.5% for minimum temperature, respectively. Rainfall reported a positive correlation with Southern Oscillation Index (SOI) and at the same time negative association with Sea Surface Temperatures (SSTs). Strong relationships between SSTs and maximum temperature are observed during the El Niño and La Niña years. These study findings could facilitate planning and management of agricultural and water resources in Botswana.

Phenological response of an Arizona dryland forest to short-term climatic extremes

USGS Publications Warehouse

Walker, Jessica; de Beurs, Kirsten; Wynne, Randolph

2015-01-01

Baseline information about dryland forest phenology is necessary to accurately anticipate future ecosystem shifts. The overarching goal of our study was to investigate the variability of vegetation phenology across a dryland forest landscape in response to climate alterations. We analyzed the influence of site characteristics and climatic conditions on the phenological patterns of an Arizona, USA, ponderosa pine (Pinus ponderosa) forest during a five-year period (2005 to 2009) that encompassed extreme wet and dry precipitation regimes. We assembled 80 synthetic Landsat images by applying the spatial and temporal adaptive reflectance fusion method (STARFM) to 500 m MODIS and 30 m Landsat-5 Thematic Mapper (TM) data. We tested relationships between site characteristics and the timing of peak Normalized Difference Vegetation Index (NDVI) to assess the effect of climatic stress on the green-up of individual pixels during or after the summer monsoon. Our results show that drought-induced stress led to a fragmented phenological response that was highly dependent on microsite parameters, as both the spatial autocorrelation of peak timing and the number of significant site variables increased during the drought year. Pixels at lower elevations and with higher proportions of herbaceous vegetation were more likely to exhibit dynamic responses to changes in precipitation conditions. Our study demonstrates the complexity of responses within dryland forest ecosystems and highlights the need for standardized monitoring of phenology trends in these areas. The spatial and temporal variability of phenological signals may provide a quantitative solution to the problem of how to evaluate dryland land surface trends across time.

Long- and short-term influence of environment on recruitment in a species with highly delayed maturity.

PubMed

Nevoux, Marie; Weimerskirch, Henri; Barbraud, Christophe

2010-02-01

Short-term effects of environmental perturbations on various life history traits are reasonably well documented in birds and mammals. But, in the present context of global climate change, there is a need to consider potential long-term effects of natal conditions to better understand and predict the consequences of these changes on population dynamics. The environmental conditions affecting offspring during their early development may determine their lifetime reproductive performance, and therefore the number of recruits produced by a cohort. In this study, we attempted to link recruitment to natal and recent (previous year) conditions in the long-lived black-browed albatross (Thalassarche melanophrys) at Kerguelen Islands. The environmental variability was described using both climatic variables over breeding (sea surface temperature anomaly) and non-breeding grounds (Southern Oscillation index), and variables related to the colony (breeding success and colony size). Immature survival was linked to the breeding success of the colony in the year of birth, which was expected to reflect the average seasonal parental investment. At the cohort level, this initial mortality event may act as a selective filter shaping the number, and presumably the quality (breeding frequency, breeding success probability), of the individuals that recruit into the breeding population. The decision to start breeding was strongly structured by the age of the individuals and adjusted according to recent conditions. An effect of natal conditions was not detected on this parameter, supporting the selection hypothesis. Recruitment, as a whole, was thus influenced by a combination of long- and short-term environmental impacts. Our results highlight the complexity of the influence of environmental factors on such long-lived species, due to the time-lag (associated with a delayed maturity) between the impact of natal conditions on individuals and their repercussion on the breeding population.

Energy Storage on the Grid and the Short-term Variability of Wind

NASA Astrophysics Data System (ADS)

Hittinger, Eric Stephen

profitability of wind farms. We find that market scenarios using existing price signals to motivate wind to reduce variability allow wind generators to participate in variability reduction when the market conditions are favorable, and can reduce short-term (30-minute) fluctuations while having little effect on wind farm revenue.

"Near-term" Natural Catastrophe Risk Management and Risk Hedging in a Changing Climate

NASA Astrophysics Data System (ADS)

Michel, Gero; Tiampo, Kristy

2014-05-01

Competing with analytics - Can the insurance market take advantage of seasonal or "near-term" forecasting and temporal changes in risk? Natural perils (re)insurance has been based on models following climatology i.e. the long-term "historical" average. This is opposed to considering the "near-term" and forecasting hazard and risk for the seasons or years to come. Variability and short-term changes in risk are deemed abundant for almost all perils. In addition to hydrometeorological perils whose changes are vastly discussed, earthquake activity might also change over various time-scales affected by earlier local (or even global) events, regional changes in the distribution of stresses and strains and more. Only recently has insurance risk modeling of (stochastic) hurricane-years or extratropical-storm-years started considering our ability to forecast climate variability herewith taking advantage of apparent correlations between climate indicators and the activity of storm events. Once some of these "near-term measures" were in the market, rating agencies and regulators swiftly adopted these concepts demanding companies to deploy a selection of more conservative "time-dependent" models. This was despite the fact that the ultimate effect of some of these measures on insurance risk was not well understood. Apparent short-term success over the last years in near-term seasonal hurricane forecasting was brought to a halt in 2013 when these models failed to forecast the exceptional shortage of hurricanes herewith contradicting an active-year forecast. The focus of earthquake forecasting has in addition been mostly on high rather than low temporal and regional activity despite the fact that avoiding losses does not by itself create a product. This presentation sheds light on new risk management concepts for over-regional and global (re)insurance portfolios that take advantage of forecasting changes in risk. The presentation focuses on the "upside" and on new opportunities

A Pilot Investigation of the Relationship between Climate Variability and Milk Compounds under the Bootstrap Technique

PubMed Central

Marami Milani, Mohammad Reza; Hense, Andreas; Rahmani, Elham; Ploeger, Angelika

2015-01-01

This study analyzes the linear relationship between climate variables and milk components in Iran by applying bootstrapping to include and assess the uncertainty. The climate parameters, Temperature Humidity Index (THI) and Equivalent Temperature Index (ETI) are computed from the NASA-Modern Era Retrospective-Analysis for Research and Applications (NASA-MERRA) reanalysis (2002–2010). Milk data for fat, protein (measured on fresh matter bases), and milk yield are taken from 936,227 milk records for the same period, using cows fed by natural pasture from April to September. Confidence intervals for the regression model are calculated using the bootstrap technique. This method is applied to the original times series, generating statistically equivalent surrogate samples. As a result, despite the short time data and the related uncertainties, an interesting behavior of the relationships between milk compound and the climate parameters is visible. During spring only, a weak dependency of milk yield and climate variations is obvious, while fat and protein concentrations show reasonable correlations. In summer, milk yield shows a similar level of relationship with ETI, but not with temperature and THI. We suggest this methodology for studies in the field of the impacts of climate change and agriculture, also environment and food with short-term data. PMID:28231215

The response of the southwest Western Australian wave climate to Indian Ocean climate variability

NASA Astrophysics Data System (ADS)

Wandres, Moritz; Pattiaratchi, Charitha; Hetzel, Yasha; Wijeratne, E. M. S.

2018-03-01

Knowledge of regional wave climates is critical for coastal planning, management, and protection. In order to develop a regional wave climate, it is important to understand the atmospheric systems responsible for wave generation. This study examines the variability of the southwest Western Australian (SWWA) shelf and nearshore wind wave climate and its relationship to southern hemisphere climate variability represented by various atmospheric indices: the southern oscillation index (SOI), the Southern Annular Mode (SAM), the Indian Ocean Dipole Mode Index (DMI), the Indian Ocean Subtropical Dipole (IOSD), the latitudinal position of the subtropical high-pressure ridge (STRP), and the corresponding intensity of the subtropical ridge (STRI). A 21-year wave hindcast (1994-2014) of the SWWA continental shelf was created using the third generation wave model Simulating WAves Nearshore (SWAN), to analyse the seasonal and inter-annual wave climate variability and its relationship to the atmospheric regime. Strong relationships between wave heights and the STRP and the STRI, a moderate correlation between the wave climate and the SAM, and no significant correlation between SOI, DMI, and IOSD and the wave climate were found. Strong spatial, seasonal, and inter-annual variability, as well as seasonal longer-term trends in the mean wave climate were studied and linked to the latitudinal changes in the subtropical high-pressure ridge and the Southern Ocean storm belt. As the Southern Ocean storm belt and the subtropical high-pressure ridge shifted southward (northward) wave heights on the SWWA shelf region decreased (increased). The wave height anomalies appear to be driven by the same atmospheric conditions that influence rainfall variability in SWWA.

Facing the Future: Effects of Short-Term Climate Extremes on Isoprene-Emitting and Nonemitting Poplar1

PubMed Central

Vanzo, Elisa; Jud, Werner; Li, Ziru; Albert, Andreas; Domagalska, Malgorzata A.; Ghirardo, Andrea; Niederbacher, Bishu; Frenzel, Juliane; Beemster, Gerrit T.S.; Asard, Han; Rennenberg, Heinz; Sharkey, Thomas D.; Hansel, Armin; Schnitzler, Jörg-Peter

2015-01-01

Isoprene emissions from poplar (Populus spp.) plantations can influence atmospheric chemistry and regional climate. These emissions respond strongly to temperature, [CO2], and drought, but the superimposed effect of these three climate change factors are, for the most part, unknown. Performing predicted climate change scenario simulations (periodic and chronic heat and drought spells [HDSs] applied under elevated [CO2]), we analyzed volatile organic compound emissions, photosynthetic performance, leaf growth, and overall carbon (C) gain of poplar genotypes emitting (IE) and nonemitting (NE) isoprene. We aimed (1) to evaluate the proposed beneficial effect of isoprene emission on plant stress mitigation and recovery capacity and (2) to estimate the cumulative net C gain under the projected future climate. During HDSs, the chloroplastidic electron transport rate of NE plants became impaired, while IE plants maintained high values similar to unstressed controls. During recovery from HDS episodes, IE plants reached higher daily net CO2 assimilation rates compared with NE genotypes. Irrespective of the genotype, plants undergoing chronic HDSs showed the lowest cumulative C gain. Under control conditions simulating ambient [CO2], the C gain was lower in the IE plants than in the NE plants. In summary, the data on the overall C gain and plant growth suggest that the beneficial function of isoprene emission in poplar might be of minor importance to mitigate predicted short-term climate extremes under elevated [CO2]. Moreover, we demonstrate that an analysis of the canopy-scale dynamics of isoprene emission and photosynthetic performance under multiple stresses is essential to understand the overall performance under proposed future conditions. PMID:26162427

Role of serial order in the impact of talker variability on short-term memory: testing a perceptual organization-based account.

PubMed

Hughes, Robert W; Marsh, John E; Jones, Dylan M

2011-11-01

In two experiments, we examined the impact of the degree of match between sequential auditory perceptual organization processes and the demands of a short-term memory task (memory for order vs. item information). When a spoken sequence of digits was presented so as to promote its perceptual partitioning into two distinct streams by conveying it in alternating female (F) and male (M) voices (FMFMFMFM)--thereby disturbing the perception of true temporal order--recall of item order was greatly impaired (as compared to recall of item identity). Moreover, an order error type consistent with the formation of voice-based streams was committed more quickly in the alternating-voice condition (Exp. 1). In contrast, when the perceptual organization of the sequence mapped well onto an optimal two-group serial rehearsal strategy--by presenting the two voices in discrete clusters (FFFFMMMM)--order, but not item, recall was enhanced (Exp. 2). The results are consistent with the view that the degree of compatibility between perceptual and deliberate sequencing processes is a key determinant of serial short-term memory performance. Alternative accounts of talker variability effects in short-term memory, based on the concept of a dedicated phonological short-term store and a capacity-limited focus of attention, are also reviewed.

Effects of climate variability on global scale flood risk

NASA Astrophysics Data System (ADS)

Ward, P.; Dettinger, M. D.; Kummu, M.; Jongman, B.; Sperna Weiland, F.; Winsemius, H.

2013-12-01

In this contribution we demonstrate the influence of climate variability on flood risk. Globally, flooding is one of the worst natural hazards in terms of economic damages; Munich Re estimates global losses in the last decade to be in excess of $240 billion. As a result, scientifically sound estimates of flood risk at the largest scales are increasingly needed by industry (including multinational companies and the insurance industry) and policy communities. Several assessments of global scale flood risk under current and conditions have recently become available, and this year has seen the first studies assessing how flood risk may change in the future due to global change. However, the influence of climate variability on flood risk has as yet hardly been studied, despite the fact that: (a) in other fields (drought, hurricane damage, food production) this variability is as important for policy and practice as long term change; and (b) climate variability has a strong influence in peak riverflows around the world. To address this issue, this contribution illustrates the influence of ENSO-driven climate variability on flood risk, at both the globally aggregated scale and the scale of countries and large river basins. Although it exerts significant and widespread influences on flood peak discharges in many parts of the world, we show that ENSO does not have a statistically significant influence on flood risk once aggregated to global totals. At the scale of individual countries, though, strong relationships exist over large parts of the Earth's surface. For example, we find particularly strong anomalies of flood risk in El Niño or La Niña years (compared to all years) in southern Africa, parts of western Africa, Australia, parts of Central Eurasia (especially for El Niño), the western USA (especially for La Niña), and parts of South America. These findings have large implications for both decadal climate-risk projections and long-term future climate change

Nitrogen deposition outweighs climatic variability in driving annual growth rate of canopy beech trees: Evidence from long-term growth reconstruction across a geographic gradient.

PubMed

Gentilesca, Tiziana; Rita, Angelo; Brunetti, Michele; Giammarchi, Francesco; Leonardi, Stefano; Magnani, Federico; van Noije, Twan; Tonon, Giustino; Borghetti, Marco

2018-07-01

In this study, we investigated the role of climatic variability and atmospheric nitrogen deposition in driving long-term tree growth in canopy beech trees along a geographic gradient in the montane belt of the Italian peninsula, from the Alps to the southern Apennines. We sampled dominant trees at different developmental stages (from young to mature tree cohorts, with tree ages spanning from 35 to 160 years) and used stem analysis to infer historic reconstruction of tree volume and dominant height. Annual growth volume (G V ) and height (G H ) variability were related to annual variability in model simulated atmospheric nitrogen deposition and site-specific climatic variables, (i.e. mean annual temperature, total annual precipitation, mean growing period temperature, total growing period precipitation, and standard precipitation evapotranspiration index) and atmospheric CO 2 concentration, including tree cambial age among growth predictors. Generalized additive models (GAM), linear mixed-effects models (LMM), and Bayesian regression models (BRM) were independently employed to assess explanatory variables. The main results from our study were as follows: (i) tree age was the main explanatory variable for long-term growth variability; (ii) GAM, LMM, and BRM results consistently indicated climatic variables and CO 2 effects on G V and G H were weak, therefore evidence of recent climatic variability influence on beech annual growth rates was limited in the montane belt of the Italian peninsula; (iii) instead, significant positive nitrogen deposition (N dep ) effects were repeatedly observed in G V and G H ; the positive effects of N dep on canopy height growth rates, which tended to level off at N dep values greater than approximately 1.0 g m -2  y -1 , were interpreted as positive impacts on forest stand above-ground net productivity at the selected study sites. © 2018 John Wiley & Sons Ltd.

Quantifying the increasing sensitivity of power systems to climate variability

NASA Astrophysics Data System (ADS)

Bloomfield, H. C.; Brayshaw, D. J.; Shaffrey, L. C.; Coker, P. J.; Thornton, H. E.

2016-12-01

Large quantities of weather-dependent renewable energy generation are expected in power systems under climate change mitigation policies, yet little attention has been given to the impact of long term climate variability. By combining state-of-the-art multi-decadal meteorological records with a parsimonious representation of a power system, this study characterises the impact of year-to-year climate variability on multiple aspects of the power system of Great Britain (including coal, gas and nuclear generation), demonstrating why multi-decadal approaches are necessary. All aspects of the example system are impacted by inter-annual climate variability, with the impacts being most pronounced for baseload generation. The impacts of inter-annual climate variability increase in a 2025 wind-power scenario, with a 4-fold increase in the inter-annual range of operating hours for baseload such as nuclear. The impacts on peak load and peaking-plant are comparably small. Less than 10 years of power supply and demand data are shown to be insufficient for providing robust power system planning guidance. This suggests renewable integration studies—widely used in policy, investment and system design—should adopt a more robust approach to climate characterisation.

Short-term improvements in public health from global-climate policies on fossil-fuel combustion: an interim report. Working Group on Public Health and Fossil-Fuel Combustion.

PubMed

1997-11-08

Most public-health assessments of climate-control policies have focused on long-term impacts of global change. Our interdisciplinary working group assesses likely short-term impacts on public health. We combined models of energy consumption, carbon emissions, and associated atmospheric particulate-matter (PM) concentration under two different forecasts: business-as-usual (BAU); and a hypothetical climate-policy scenario, where developed and developing countries undertake significant reductions in carbon emissions. We predict that by 2020, 700,000 avoidable deaths (90% CI 385,000-1,034,000) will occur annually as a result of additional PM exposure under the BAU forecasts when compared with the climate-policy scenario. From 2000 to 2020, the cumulative impact on public health related to the difference in PM exposure could total 8 million deaths globally (90% CI 4.4-11.9 million). In the USA alone, the avoidable number of annual deaths from PM exposure in 2020 (without climate-change-control policy) would equal in magnitude deaths associated with human immunodeficiency diseases or all liver diseases in 1995. The mortality estimates are indicative of the magnitude of the likely health benefits of the climate-policy scenario examined and are not precise predictions of avoidable deaths. While characterized by considerable uncertainty, the short-term public-health impacts of reduced PM exposures associated with greenhouse-gas reductions are likely to be substantial even under the most conservative set of assumptions.

Sleep Quality, Short-Term and Long-Term CPAP Adherence

PubMed Central

Somiah, Manya; Taxin, Zachary; Keating, Joseph; Mooney, Anne M.; Norman, Robert G.; Rapoport, David M.; Ayappa, Indu

2012-01-01

Study Objectives: Adherence to CPAP therapy is low in patients with obstructive sleep apnea/hypopnea syndrome (OSAHS). The purpose of the present study was to evaluate the utility of measures of sleep architecture and sleep continuity on the CPAP titration study as predictors of both short- and long-term CPAP adherence. Methods: 93 patients with OSAHS (RDI 42.8 ± 34.3/h) underwent in-laboratory diagnostic polysomnography, CPAP titration, and follow-up polysomnography (NPSG) on CPAP. Adherence to CPAP was objectively monitored. Short-term (ST) CPAP adherence was averaged over 14 days immediately following the titration study. Long-term (LT) CPAP adherence was obtained in 56/93 patients after approximately 2 months of CPAP use. Patients were grouped into CPAP adherence groups for ST (< 2 h, 2-4 h, and > 4 h) and LT adherence (< 4 h, > 4 h). Sleep architecture, sleep disordered breathing (SDB) indices, and daytime outcome variables from the diagnostic and titration NPSGs were compared between CPAP adherence groups. Results: There was a significant relationship between ST and LT CPAP adherence (r = 0.81, p < 0.001). Neither ST nor LT adherence were related to demographic variables, baseline severity of untreated SDB, sleep architecture, or measures of daytime impairment. Good CPAP adherence groups had significantly lower %N2 and greater %REM on the titration NPSG. A model combining change in sleep efficiency and change in sleep continuity between the diagnostic and titration NPSGs predicted 17% of the variance in LT adherence (p = 0.006). Conclusions: These findings demonstrate that characteristics of sleep architecture, even on the titration NPSG, may predict some of the variance in CPAP adherence. Better sleep quality on the titration night was related to better CPAP adherence, suggesting that interventions to improve sleep on/prior to the CPAP titration study might be used as a therapeutic intervention to improve CPAP adherence. Citation: Somiah M; Taxin Z; Keating

Variability of the recent climate of eastern Africa

NASA Astrophysics Data System (ADS)

Schreck, Carl J., III; Semazzi, Fredrick H. M.

2004-05-01

The primary objective of this study is to investigate the recent variability of the eastern African climate. The region of interest is also known as the Greater Horn of Africa (GHA), and comprises the countries of Burundi, Djibouti, Eritrea, Ethiopia, Kenya, Rwanda, Somalia, Sudan, Uganda, and Tanzania.The analysis was based primarily on the construction of empirical orthogonal functions (EOFs) of gauge rainfall data and on CPC Merged Analysis of Precipitation (CMAP) data, derived from a combination of rain-gauge observations and satellite estimates. The investigation is based on the period 1961-2001 for the short rains season of eastern Africa of October through to December. The EOF analysis was supplemented by projection of National Centers for Environmental Prediction wind data onto the rainfall eigenmodes to understand the rainfall-circulation relationships. Furthermore, correlation and composite analyses have been performed with the Climatic Research Unit globally averaged surface-temperature time series to explore the potential relationship between the climate of eastern Africa and global warming.The most dominant mode of variability (EOF1) based on CMAP data over eastern Africa corresponds to El Niño-southern oscillation (ENSO) climate variability. It is associated with above-normal rainfall amounts during the short rains throughout the entire region, except for Sudan. The corresponding anomalous low-level circulation is dominated by easterly inflow from the Indian Ocean, and to a lesser extent the Congo tropical rain forest, into the positive rainfall anomaly region that extends across most of eastern Africa. The easterly inflow into eastern Africa is part of diffluent outflow from the maritime continent during the warm ENSO events. The second eastern African EOF (trend mode) is associated with decadal variability. In distinct contrast from the ENSO mode pattern, the trend mode is characterized by positive rainfall anomalies over the northern sector of

An 8700 Year Record of Holocene Climate Variability from the Yucatan Peninsula

NASA Astrophysics Data System (ADS)

Wahl, D.; Byrne, R.; Anderson, L.

2013-12-01

Our understanding of Holocene climate change in the Maya lowlands of Central America has improved significantly during the last several decades thanks to the development of proxy climate records from lake cores and speleothems. One important finding is that longer-term climate changes (i.e., millennial scale) were driven primarily by precessional forcing; less clear, however, are the causes of abrupt shifts and higher frequency (centennial to decadal) change recognized in many Holocene climate reconstructions. The mechanisms driving climate change on these time scales have been difficult to identify in the region, in part because the Yucatan peninsula is influenced by climatic conditions linked to both the tropical Atlantic and Pacific oceans. Additional complications arise from the development of dense human populations following the initial introduction of agriculture ~5000 cal yr BP, which had significant impact on the environment as a whole. Here we present the results of analyses (stable isotope, pollen, magnetic susceptibility, and physical properties) of a 7.25 m sediment core from Lago Puerto Arturo, a closed basin lake in the northern Peten, Guatemala. An age-depth model, based on 6 AMS radiocarbon determinations and created using CLAM, indicates the record extends to 8700 cal yr BP. Proxy data suggest that, similar to other low latitude sites, millennial scale climate at Lago Puerto Arturo was driven by changes in insolation. Higher frequency variability is associated with El Niño/Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO) dynamics, reflecting latitudinal shifts in the Intertropical Convergence Zone in both the tropical North Atlantic and North Pacific. Solar forcing may also play a role in short-term climate change. The pollen and isotope records show that the entire period of prehispanic settlement and agricultural activity, i.e. ~5000-1000 cal yr B.P., was characterized by relatively dry conditions compared to before or after.

Short-term variability of blood pressure and heart rate in hyperthyroidism.

PubMed

Girard, A; Hugues, F C; Le Jeunne, C; Elghozi, J L

1998-06-01

The effect of hyperthyroidism on the short-term memory variability of blood pressure and heart rate was evaluated in 12 untreated hyperthyroid patients during thyrotoxicosis and after a 6 1/2 month treatment designed to achieve a stable euthyroid state. Beat-by-beat finger blood pressure was measured with a Finapres device. The pulse interval, from which pulse rate was derived, was obtained from the blood pressure signal. Due to the significant change in heart rhythm associated with thyrotoxicosis, both pulse interval (taken as a surrogate of heart period) and pulse rate (taken as a surrogate of heart rate) were computed. Power spectral analysis showed a reduction in the overall heart period variability in the supine position in the hyperthyroid compared to the euthyroid state. This effect was observed in the low-frequency (0.005-0.068 Hz), mid-frequency (0.068-0.127 Hz) and high-frequency (respiratory) domains as well, with a significant reduction of the modulus of these bands of 31%, 35% and 47%, respectively. The heart rate spectral modulus also exhibited a reduction of the high-frequency component (31%) in the supine position in the hyperthyroid subjects. These changes in heart rhythmicity corroborate a vagal deficit in hyperthyroidism. In addition, blood pressure spectral power exhibited a significant deficit in the orthostatism-induced mid-frequency systolic blood pressure rise in the hyperthyroid state (64%) compared with the euthyroid state. This observation may reflect a reduced vascular sympathetic activation with standing. The resulting vasodilatation could well contribute to normalize blood pressure in thyrotoxicosis in which cardiac output is increased.

Dynamical malaria models reveal how immunity buffers effect of climate variability

PubMed Central

Laneri, Karina; Paul, Richard E.; Tall, Adama; Faye, Joseph; Diene-Sarr, Fatoumata; Sokhna, Cheikh; Trape, Jean-François; Rodó, Xavier

2015-01-01

Assessing the influence of climate on the incidence of Plasmodium falciparum malaria worldwide and how it might impact local malaria dynamics is complex and extrapolation to other settings or future times is controversial. This is especially true in the light of the particularities of the short- and long-term immune responses to infection. In sites of epidemic malaria transmission, it is widely accepted that climate plays an important role in driving malaria outbreaks. However, little is known about the role of climate in endemic settings where clinical immunity develops early in life. To disentangle these differences among high- and low-transmission settings we applied a dynamical model to two unique adjacent cohorts of mesoendemic seasonal and holoendemic perennial malaria transmission in Senegal followed for two decades, recording daily P. falciparum cases. As both cohorts are subject to similar meteorological conditions, we were able to analyze the relevance of different immunological mechanisms compared with climatic forcing in malaria transmission. Transmission was first modeled by using similarly unique datasets of entomological inoculation rate. A stochastic nonlinear human–mosquito model that includes rainfall and temperature covariates, drug treatment periods, and population variability is capable of simulating the complete dynamics of reported malaria cases for both villages. We found that under moderate transmission intensity climate is crucial; however, under high endemicity the development of clinical immunity buffers any effect of climate. Our models open the possibility of forecasting malaria from climate in endemic regions but only after accounting for the interaction between climate and immunity. PMID:26124134

Dynamical malaria models reveal how immunity buffers effect of climate variability.

PubMed

Laneri, Karina; Paul, Richard E; Tall, Adama; Faye, Joseph; Diene-Sarr, Fatoumata; Sokhna, Cheikh; Trape, Jean-François; Rodó, Xavier

2015-07-14

Assessing the influence of climate on the incidence of Plasmodium falciparum malaria worldwide and how it might impact local malaria dynamics is complex and extrapolation to other settings or future times is controversial. This is especially true in the light of the particularities of the short- and long-term immune responses to infection. In sites of epidemic malaria transmission, it is widely accepted that climate plays an important role in driving malaria outbreaks. However, little is known about the role of climate in endemic settings where clinical immunity develops early in life. To disentangle these differences among high- and low-transmission settings we applied a dynamical model to two unique adjacent cohorts of mesoendemic seasonal and holoendemic perennial malaria transmission in Senegal followed for two decades, recording daily P. falciparum cases. As both cohorts are subject to similar meteorological conditions, we were able to analyze the relevance of different immunological mechanisms compared with climatic forcing in malaria transmission. Transmission was first modeled by using similarly unique datasets of entomological inoculation rate. A stochastic nonlinear human-mosquito model that includes rainfall and temperature covariates, drug treatment periods, and population variability is capable of simulating the complete dynamics of reported malaria cases for both villages. We found that under moderate transmission intensity climate is crucial; however, under high endemicity the development of clinical immunity buffers any effect of climate. Our models open the possibility of forecasting malaria from climate in endemic regions but only after accounting for the interaction between climate and immunity.

Bovine colostrum supplementation's lack of effect on immune variables during short-term intense exercise in well-trained athletes.

PubMed

Carol, Arnoud; Witkamp, Renger F; Wichers, Harry J; Mensink, Marco

2011-04-01

The purpose of this study was to investigate the potential of bovine colostrum to attenuate postexercise decline in immune function. The authors evaluated the time course of a number of immune variables after short-term intense exercise in 9 male athletes after 10 d of supplementation with either colostrum or skim-milk powder. To increase the stress on the immune system subjects performed a glycogen-depletion trial the evening before the endurance trial (90 min at 50% Wmax). Blood samples were taken before the glycogen-depletion trial, before and after the endurance trial, and the next morning, ~22 hr after cessation of the exercise. Plasma cortisol levels increased over time, reaching the highest level directly after exercise, and were still elevated ~22 hr after exercise compared with baseline values (p < .001). Neutrophil cell count was increased after exercise and dropped below starting values 22 hr after exercise (time effect p < .001). Circulating immunoglobulins did not change over time. A significant time effect was seen for interleukin (IL)-6, IL-10, IL-1-receptor agonist, and C-reactive protein, with levels being higher directly after exercise (p < .05). Other cytokines (interferon-γ, IL-1a, IL-8, tumor necrosis factor-a) did not show a time effect. No differences were seen between colostrum and skim-milk powder in any of the investigated variables. Our results are consistent with the hypothesis that intense exercise affects several variables of the immune system. Colostrum did not alter any of the postexercise immune variables compared with skim-milk powder, suggesting no role for bovine colostrum supplementation in preventing postexercise immune suppression after short-term intense exercise.

Past climate variability and change in the Arctic and at high latitudes

USGS Publications Warehouse

Alley, Richard B.; Brigham-Grette, Julie; Miller, Gifford H.; Polyak, Leonid; ,; ,; ,

2009-01-01

Paleoclimate records play a key role in our understanding of Earth's past and present climate system and in our confidence in predicting future climate changes. Paleoclimate data help to elucidate past and present active mechanisms of climate change by placing the short instrumental record into a longer term context and by permitting models to be tested beyond the limited time that instrumental measurements have been available.

Short-term association between personal exposure to noise and heart rate variability: The RECORD MultiSensor Study.

PubMed

El Aarbaoui, Tarik; Méline, Julie; Brondeel, Ruben; Chaix, Basile

2017-12-01

Studies revealed long-term associations between noise exposure and cardiovascular health, but the underlying short-term mechanisms remain uncertain. To explore the concomitant and lagged short-term associations between personal exposure to noise and heart rate variability (HRV) in a real life setting in the Île-de-France region. The RECORD MultiSensor Study collected between July 2014 and June 2015 noise and heart rate data for 75 participants, aged 34-74 years, in their living environments for 7 days using a personal dosimeter and electrocardiography (ECG) sensor on the chest. HRV parameters and noise levels were calculated for 5-min windows. Short-term relationships between noise level and log-transformed HRV parameters were assessed using mixed effects models with a random intercept for participants and a temporal autocorrelation structure, adjusted for heart rate, physical activity (accelerometry), and short-term trends. An increase by one dB(A) of A-weighted equivalent sound pressure level (Leq) was associated with a 0.97% concomitant increase of the Standard deviation of normal to normal intervals (SDNN) (95% CI: 0.92, 1.02), of 2.08% of the Low frequency band power (LF) (95% CI: 1.97, 2.18), of 1.30% of the High frequency band power (HF) (95% CI: 1.17, 1.43), and of 1.16% of the LF/HF ratio (95% CI: 1.10, 1.23). The analysis of lagged exposures to noise adjusted for the concomitant exposure illustrates the dynamic of recovery of the autonomic nervous system. Non-linear associations were documented with all HRV parameters with the exception of HF. Piecewise regression revealed that the association was almost 6 times stronger below than above 65 Leq dB(A) for the SDNN and LF/HF ratio. Personal noise exposure was found to be related to a concomitant increase of the overall HRV, with evidence of imbalance of the autonomic nervous system towards sympathetic activity, a pathway to increased cardiovascular morbidity and mortality. Copyright © 2017 Elsevier Ltd

Effect of antihypertensive drug therapy on short-term heart rate variability in newly diagnosed essential hypertension.

PubMed

Pavithran, Purushothaman; Prakash, E Sankaranarayanan; Dutta, Tarun K; Madanmohan, Trakroo

2010-02-01

1. Abnormalities of cardiac autonomic regulation are a potential mechanism for morbidity despite blood pressure (BP) lowering in hypertension. Analysis of short-term (5 min) heart rate variability (HRV) provides a non-invasive probe of autonomic regulation of sino-atrial (SA) node automaticity. 2. We hypothesized that antihypertensive drug therapy would be associated with an increase in 5 min overall HRV, along with a decrease in blood pressure (BP), at 8 weeks follow up in subjects with newly diagnosed, never-treated essential hypertension. 3. One hundred and fifty patients (84 men and 66 women; mean (+/-SD) age 48 +/- 10 years) with newly diagnosed essential hypertension were divided to five groups of 30 patients each to receive one of the following antihypertensive drugs (or drug combinations): 5 mg/day amlodipine; 50 mg/day atenolol; 5 mg/day enalapril; 25 mg/day hydrochlorothiazide; or a combination of 5 mg/day amlodipine and 50 mg/day atenolol. 4. The only significant change in HRV indices was an increase in total variability of RR intervals and an increase in high-frequency (HF) RR interval spectral power in the amlodipine + atenolol-treated group (P < 0.05). 5. The results indicate that there is a dissociation between changes in short-term HRV and mean RR interval and BP lowering in patients with newly diagnosed hypertension. 6. We interpret the increase in HF RR interval spectral power in the amlodipine + atenolol-treated group as being due to an increase in vagal modulation of RR intervals and/or diminution in sympathetic restraint of respiratory sinus arrhythmia.

The Role of Global Hydrologic Processes in Interannual and Long-Term Climate Variability

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.

1997-01-01

The earth's climate and its variability is linked inextricably with the presence of water on our planet. El Nino / Southern Oscillation-- the major mode of interannual variability-- is characterized by strong perturbations in oceanic evaporation, tropical rainfall, and radiation. On longer time scales, the major feedback mechanism in CO2-induced global warming is actually that due to increased water vapor holding capacity of the atmosphere. The global hydrologic cycle effects on climate are manifested through influence of cloud and water vapor on energy fluxes at the top of atmosphere and at the surface. Surface moisture anomalies retain the "memory" of past precipitation anomalies and subsequently alter the partitioning of latent and sensible heat fluxes at the surface. At the top of atmosphere, water vapor and cloud perturbations alter the net amount of radiation that the earth's climate system receives. These pervasive linkages between water, radiation, and surface processes present major complexities for observing and modeling climate variations. Major uncertainties in the observations include vertical structure of clouds and water vapor, surface energy balance, and transport of water and heat by wind fields. Modeling climate variability and change on a physical basis requires accurate by simplified submodels of radiation, cloud formation, radiative exchange, surface biophysics, and oceanic energy flux. In the past, we m safely say that being "data poor' has limited our depth of understanding and impeded model validation and improvement. Beginning with pre-EOS data sets, many of these barriers are being removed. EOS platforms with the suite of measurements dedicated to specific science questions are part of our most cost effective path to improved understanding and predictive capability. This talk will highlight some of the major questions confronting global hydrology and the prospects for significant progress afforded by EOS-era measurements.

Climate-informed stochastic hydrological modeling: Incorporating decadal-scale variability using paleoclimate data

NASA Astrophysics Data System (ADS)

Henley, B. J.; Thyer, M. A.; Kuczera, G. A.

2012-12-01

A hierarchical framework for incorporating modes of climate variability into stochastic simulations of hydrological data is developed, termed the climate-informed multi-time scale stochastic (CIMSS) framework. To characterize long-term variability for the first level of the hierarchy, paleoclimate and instrumental data describing the Interdecadal Pacific Oscillation (IPO) and the Pacific Decadal Oscillation (PDO) are analyzed. A new paleo IPO-PDO time series dating back 440 yrs is produced, combining seven IPO-PDO paleo sources using an objective smoothing procedure to fit low-pass filters to individual records. The paleo data analysis indicates that wet/dry IPO-PDO states have a broad range of run-lengths, with 90% between 3 and 33 yr and a mean of 15 yr. Model selection techniques were used to determine a suitable stochastic model to simulate these run-lengths. The Markov chain model, previously used to simulate oscillating wet/dry climate states, was found to underestimate the probability of wet/dry periods >5 yr, and was rejected in favor of a gamma distribution. For the second level of the hierarchy, a seasonal rainfall model is conditioned on the simulated IPO-PDO state. Application to two high-quality rainfall sites close to water supply reservoirs found that mean seasonal rainfall in the IPO-PDO dry state was 15%-28% lower than the wet state. The model was able to replicate observed statistics such as seasonal and multi-year accumulated rainfall distributions and interannual autocorrelations for the case study sites. In comparison, an annual lag-one autoregressive AR(1) model was unable to adequately capture the observed rainfall distribution within separate IPO-PDO states. Furthermore, analysis of the impact of the CIMSS framework on drought risk analysis found that short-term drought risks conditional on IPO/PDO state were considerably higher than the traditional AR(1) model.hort-term conditional water supply drought risks for the CIMSS and AR(1) models

Short-term variability on mesozooplankton community in a shallow mixed estuary (Bahía Blanca, Argentina): Influence of tidal cycles and local winds

NASA Astrophysics Data System (ADS)

Menéndez, María C.; Piccolo, María C.; Hoffmeyer, Mónica S.

2012-10-01

The short-term dynamics of zooplankton in coastal ecosystems are strongly influenced by physical processes such as tides, riverine runoff and winds. In this study, we investigated the short-term changes of the representative taxa within mesozooplankton in relation to the semidiurnal tidal cycles. Also, we evaluated the influence of local winds on this short-term variability. Sampling was carried out bimonthly from December 2004 to April 2006 in a fixed point located in the inner zone of the Bahía Blanca Estuary, Argentina. Mesozooplankton samples were taken by pumps during 14-h tidal cycles at 3-h intervals, from surface and bottom. Vertical profiles of temperature and salinity as well as water samples to determine suspended particulate matter were acquired at each sampling date. All data concerning winds were obtained from a meteorological station and water level was recorded with a tide gauge. Holoplankton dominated numerically on meroplankton and adventitious fraction. Concerning holoplanktonic abundance, the highest values were attained by the calanoid copepods Acartia tonsa and Eurytemora americana. Meroplankton occurred mainly as barnacle larvae while benthic harpacticoids and Corophium sp. dominated the adventitious component. Semidiurnal tide was the main influence on the A. tonsa variability. However, noticeable differences in the abundance pattern as function of wind intensity were detected. Meroplankton abundance did not show a clear variation along the tidal cycle. Distributional pattern of harpacticoids seemed to be mainly modulated by velocity asymmetries in the tidal currents, in the same way as suspended particulate matter. However, the Corophium sp. distribution indicated probable behavioural responses associated with tides. The obtained results show how variable the mesozooplankton community structure can be over short-term time scales in mesotidal temperate estuaries. This variability should be taken into account for any zooplankton monitoring

Earth System Science Education Centered on Natural Climate Variability

NASA Astrophysics Data System (ADS)

Ramirez, P. C.; Ladochy, S.; Patzert, W. C.; Willis, J. K.

2009-12-01

Several new courses and many educational activities related to climate change are available to teachers and students of all grade levels. However, not all new discoveries in climate research have reached the science education community. In particular, effective learning tools explaining natural climate change are scarce. For example, the Pacific Decadal Oscillation (PDO) is a main cause of natural climate variability spanning decades. While most educators are familiar with the shorter-temporal events impacting climate, El Niño and La Niña, very little has trickled into the climate change curriculum on the PDO. We have developed two online educational modules, using an Earth system science approach, on the PDO and its role in climate change and variability. The first concentrates on the discovery of the PDO through records of salmon catch in the Pacific Northwest and Alaska. We present the connection between salmon abundance in the North Pacific to changing sea surface temperature patterns associated with the PDO. The connection between sea surface temperatures and salmon abundance led to the discovery of the PDO. Our activity also lets students explore the role of salmon in the economy and culture of the Pacific Northwest and Alaska and the environmental requirements for salmon survival. The second module is based on the climate of southern California and how changes in the Pacific Ocean , such as the PDO and ENSO (El Niño-Southern Oscillation), influence regional climate variability. PDO and ENSO signals are evident in the long-term temperature and precipitation record of southern California. Students are guided in the module to discover the relationships between Pacific Ocean conditions and southern California climate variability. The module also provides information establishing the relationship between climate change and variability and the state's water, energy, agriculture, wildfires and forestry, air quality and health issues. Both modules will be

Surfing wave climate variability

NASA Astrophysics Data System (ADS)

Espejo, Antonio; Losada, Iñigo J.; Méndez, Fernando J.

2014-10-01

International surfing destinations are highly dependent on specific combinations of wind-wave formation, thermal conditions and local bathymetry. Surf quality depends on a vast number of geophysical variables, and analyses of surf quality require the consideration of the seasonal, interannual and long-term variability of surf conditions on a global scale. A multivariable standardized index based on expert judgment is proposed for this purpose. This index makes it possible to analyze surf conditions objectively over a global domain. A summary of global surf resources based on a new index integrating existing wave, wind, tides and sea surface temperature databases is presented. According to general atmospheric circulation and swell propagation patterns, results show that west-facing low to middle-latitude coasts are more suitable for surfing, especially those in the Southern Hemisphere. Month-to-month analysis reveals strong seasonal variations in the occurrence of surfable events, enhancing the frequency of such events in the North Atlantic and the North Pacific. Interannual variability was investigated by comparing occurrence values with global and regional modes of low-frequency climate variability such as El Niño and the North Atlantic Oscillation, revealing their strong influence at both the global and the regional scale. Results of the long-term trends demonstrate an increase in the probability of surfable events on west-facing coasts around the world in recent years. The resulting maps provide useful information for surfers, the surf tourism industry and surf-related coastal planners and stakeholders.

Metrics for comparing climate impacts of short- and long-lived climate forcing agents

NASA Astrophysics Data System (ADS)

Fuglestvedt, J.; Berntsen, T.

2013-12-01

Human activities emit a wide variety of gases and aerosols, with different characteristics that influence both air quality and climate. The emissions affect climate both directly and indirectly and operate on both short and long timescales. Tools that allow these emissions to be placed on a common scale in terms of climate impact, i.e. metrics, have a number of applications (e.g. agreements and emission trading schemes, when considering potential trade-offs between changes in emissions). The Kyoto Protocol compares greenhouse gas (GHG) emissions using the Global Warming Potential (GWP) over a 100 year time-horizon. The IPCC First Assessment Report states the GWP was presented to illustrate the difficulties in comparing GHGs. There have been many critiques of the GWP and several alternative emission metrics have been proposed, but there has been little focus on understanding the linkages between, and interpretations of, different emission metrics. Furthermore, the capability to compare components with very different lifetimes and temporal behaviour needs consideration. The temperature based metrics (e.g. the Global Temperature change Potential (GTP)) require a model for the temperature response, and additional uncertainty is thus introduced. Short-lived forcers may also give more spatially heterogeneous responses, and the possibilities to capture these spatial variations by using other indicators than global mean RF or temperature change in metrics will be discussed. The ultimate choice of emission metric(s) and time-horizon(s) should, however, depend on the objectives of climate policy. Alternatives to the current 'multi-gas and single-basket' approach will also be explored and discussed (e.g. how a two-target approach may be implemented using a two-basket approach). One example is measures to reduce near-term rate of warming and long-term stabilization which can be implemented through two separate targets and two baskets with separate set of metrics for each

Long-term forest management and climate effects on streamflow

Treesearch

Shelby G. Laird; C.R. Ford; S.H. Laseter; J.M. Vose

2011-01-01

Long-term watershed studies are a powerful tool for examining interactions among management activities, streamflow, and climatic variability. Understanding these interactions is critical for exploring the potential of forest management to adapt to or mitigate against the effects of climate change. The Coweeta Hydrologic Laboratory, located in North Carolina, USA, is a...

Assessing the associative deficit of older adults in long-term and short-term/working memory.

PubMed

Chen, Tina; Naveh-Benjamin, Moshe

2012-09-01

Older adults exhibit a deficit in associative long-term memory relative to younger adults. However, the literature is inconclusive regarding whether this deficit is attenuated in short-term/working memory. To elucidate the issue, three experiments assessed younger and older adults' item and interitem associative memory and the effects of several variables that might potentially contribute to the inconsistent pattern of results in previous studies. In Experiment 1, participants were tested on item and associative recognition memory with both long-term and short-term retention intervals in a single, continuous recognition paradigm. There was an associative deficit for older adults in the short-term and long-term intervals. Using only short-term intervals, Experiment 2 utilized mixed and blocked test designs to examine the effect of test event salience. Blocking the test did not attenuate the age-related associative deficit seen in the mixed test blocks. Finally, an age-related associative deficit was found in Experiment 3, under both sequential and simultaneous presentation conditions. Even while accounting for some methodological issues, the associative deficit of older adults is evident in short-term/working memory.

Chances of short-term cooling trends over Canada for the next decades

NASA Astrophysics Data System (ADS)

Grenier, Patrick; de Elia, Ramon; Chaumont, Diane

2014-05-01

As climate services continue to develop in Quebec, Canada, an increasing number of requests are made for providing information relevant for the near term. As a response, one approach has been to consider short-term cooling trends as a basis for climate products. This project comprises different aspects: technical steps, knowledge transfer, and societal use. Each step does represent a different challenge. The technical part, i.e. producing probabilistic distributions of short-term temperature trends, involves relatively complex scenario construction methods including bias-related post-processing, and access to wide simulation and observation databases. Calculations are performed on 60 CMIP5-based scenarios on a grid covering Canada during the period 2006-2035, and for 5, 10, 15, 20 and 25-year trend durations. Knowledge transfer implies overcoming misinterpretation, given that probabilistic projections based on simulation ensembles are not perfectly related to real-Earth possible outcomes. Finally, societal use of this information remains the biggest challenge. On the one hand, users clearly state their interest in near-term relevant information, and intuitively it seems clear that short-term cooling trends embedded within the long-term warming path should be considered in adaptation plans, for avoiding over-adaptation. On the other hand, the exact way of incorporating such information within a decision-making process has proven not to be obvious. Irrespective of that, the study and communication of short-term cooling chances is necessary for preventing decision-makers to infer from the eventual occurrence of such a trend that global warming isn't happening. The presentation will discuss the three aspects aforementioned.

How does complex terrain influence responses of carbon and water cycle processes to climate variability and climate change?

EPA Science Inventory

We are pursuing the ambitious goal of understanding how complex terrain influences the responses of carbon and water cycle processes to climate variability and climate change. Our studies take place in H.J. Andrews Experimental Forest, an LTER (Long Term Ecological Research) site...

Towards multi-resolution global climate modeling with ECHAM6-FESOM. Part II: climate variability

NASA Astrophysics Data System (ADS)

Rackow, T.; Goessling, H. F.; Jung, T.; Sidorenko, D.; Semmler, T.; Barbi, D.; Handorf, D.

2018-04-01

This study forms part II of two papers describing ECHAM6-FESOM, a newly established global climate model with a unique multi-resolution sea ice-ocean component. While part I deals with the model description and the mean climate state, here we examine the internal climate variability of the model under constant present-day (1990) conditions. We (1) assess the internal variations in the model in terms of objective variability performance indices, (2) analyze variations in global mean surface temperature and put them in context to variations in the observed record, with particular emphasis on the recent warming slowdown, (3) analyze and validate the most common atmospheric and oceanic variability patterns, (4) diagnose the potential predictability of various climate indices, and (5) put the multi-resolution approach to the test by comparing two setups that differ only in oceanic resolution in the equatorial belt, where one ocean mesh keeps the coarse 1° resolution applied in the adjacent open-ocean regions and the other mesh is gradually refined to 0.25°. Objective variability performance indices show that, in the considered setups, ECHAM6-FESOM performs overall favourably compared to five well-established climate models. Internal variations of the global mean surface temperature in the model are consistent with observed fluctuations and suggest that the recent warming slowdown can be explained as a once-in-one-hundred-years event caused by internal climate variability; periods of strong cooling in the model (`hiatus' analogs) are mainly associated with ENSO-related variability and to a lesser degree also to PDO shifts, with the AMO playing a minor role. Common atmospheric and oceanic variability patterns are simulated largely consistent with their real counterparts. Typical deficits also found in other models at similar resolutions remain, in particular too weak non-seasonal variability of SSTs over large parts of the ocean and episodic periods of almost absent

Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time.

PubMed

Limongi, Roberto; Silva, Angélica M

2016-11-01

The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production - where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.

Numerical experiments on short-term meteorological effects on solar variability

NASA Technical Reports Server (NTRS)

Somerville, R. C. J.; Hansen, J. E.; Stone, P. H.; Quirk, W. J.; Lacis, A. A.

1975-01-01

A set of numerical experiments was conducted to test the short-range sensitivity of a large atmospheric general circulation model to changes in solar constant and ozone amount. On the basis of the results of 12-day sets of integrations with very large variations in these parameters, it is concluded that realistic variations would produce insignificant meteorological effects. Any causal relationships between solar variability and weather, for time scales of two weeks or less, rely upon changes in parameters other than solar constant or ozone amounts, or upon mechanisms not yet incorporated in the model.

Effect of interannual climate variability on carbon storage in Amazonian ecosystems

USGS Publications Warehouse

Tian, H.; Melillo, J.M.; Kicklighter, D.W.; McGuire, David A.; Helfrich, J. V. K.; Moore, B.; Vorosmarty, C.J.

1998-01-01

The Amazon Basin contains almost one-half of the world's undisturbed tropical evergreen forest as well as large areas of tropical savanna. The forests account for about 10 per cent of the world's terrestrial primary productivity and for a similar fraction of the carbon stored in land ecosystems, and short-term field measurements suggest that these ecosystems are globally important carbon sinks. But tropical land ecosystems have experienced substantial interannual climate variability owing to frequent El Nino episodes in recent decades. Of particular importance to climate change policy is how such climate variations, coupled with increases in atmospheric CO2 concentration, affect terrestrial carbon storage. Previous model analyses have demonstrated the importance of temperature in controlling carbon storage. Here we use a transient process-based biogeochemical model of terrestrial ecosystems to investigate interannual variations of carbon storage in undisturbed Amazonian ecosystems in response to climate variability and increasing atmospheric CO2 concentration during the period 1980 to 1994. In El Nino years, which bring hot, dry weather to much of the Amazon region, the ecosystems act as a source of carbon to the atmosphere (up to 0.2 petagrams of carbon in 1987 and 1992). In other years, these ecosystems act as a carbon sink (up to 0.7 Pg C in 1981 and 1993). These fluxes are large; they compare to a 0.3 Pg C per year source to the atmosphere associated with deforestation in the Amazon Basin in the early 1990s. Soil moisture, which is affected by both precipitation and temperature, and which affects both plant and soil processes, appears to be an important control on carbon storage.

Back to the Future -Precipitation Extremes, Climate Variability, Environmental Planning and Adaptation

NASA Astrophysics Data System (ADS)

Barros, A. P.

2008-12-01

--"The last major climatic oscillation peak was about 1856, or 74 years ago. Practically all of our important railroad and public highway work has been done since that time. Most of our parks systems driveways, and roads of all type for auto travel, in the various States, have been completed within the past 30 years, namely, beginning at the very lowest point of our climatic swing (1900-1910). There is every reason to believe, therefore, as the next 20 years comes on apace, we will witness considerable damage to work done during the past regime of weather."-- Schuman, 1931 At the beginning of the 21st century, as at the beginning of the 20th century, the fundamental question is whether the nation is more prepared for natural disasters today than it was eight decades ago. Indeed, the question is whether the best science, engineering and policy tools are in place to prepare for and respond to extreme events. Changes in the risk and magnitude of extreme precipitation events rank among the most studied impacts, and indicators (symptoms) of climatic variations. Extreme precipitation translates generally into extreme flooding, landslides, collapse of lifeline infrastructure, and the breakdown of public health services among others. In approaching the problem of quantifying the risk and magnitude of extreme precipitation events, there are two major challenges: 1) it is difficult to characterize "observed" (20th century) conditions due to the lack of long-term observations - i.e., short and incomplete historical records; and 2) it is difficult to characterize "predicted" (21st century) conditions due to the lack of skill of precipitation forecasts at spatial and temporal scales meaningful for impact studies, and the short-duration of climate model simulations themselves. The first challenge translates in estimating the probability of occurrence (rare) and magnitude (very large) of events that may have not happened yet. The second challenge is that of quantifying

Describing temporal variability of the mean Estonian precipitation series in climate time scale

NASA Astrophysics Data System (ADS)

Post, P.; Kärner, O.

2009-04-01

Applicability of the random walk type models to represent the temporal variability of various atmospheric temperature series has been successfully demonstrated recently (e.g. Kärner, 2002). Main problem in the temperature modeling is connected to the scale break in the generally self similar air temperature anomaly series (Kärner, 2005). The break separates short-range strong non-stationarity from nearly stationary longer range variability region. This is an indication of the fact that several geophysical time series show a short-range non-stationary behaviour and a stationary behaviour in longer range (Davis et al., 1996). In order to model series like that the choice of time step appears to be crucial. To characterize the long-range variability we can neglect the short-range non-stationary fluctuations, provided that we are able to model properly the long-range tendencies. The structure function (Monin and Yaglom, 1975) was used to determine an approximate segregation line between the short and the long scale in terms of modeling. The longer scale can be called climate one, because such models are applicable in scales over some decades. In order to get rid of the short-range fluctuations in daily series the variability can be examined using sufficiently long time step. In the present paper, we show that the same philosophy is useful to find a model to represent a climate-scale temporal variability of the Estonian daily mean precipitation amount series over 45 years (1961-2005). Temporal variability of the obtained daily time series is examined by means of an autoregressive and integrated moving average (ARIMA) family model of the type (0,1,1). This model is applicable for daily precipitation simulating if to select an appropriate time step that enables us to neglet the short-range non-stationary fluctuations. A considerably longer time step than one day (30 days) is used in the current paper to model the precipitation time series variability. Each ARIMA (0

Long-term variability in sugarcane bagasse feedstock compositional methods: Sources and magnitude of analytical variability

DOE PAGES

Templeton, David W.; Sluiter, Justin B.; Sluiter, Amie; ...

2016-10-18

In an effort to find economical, carbon-neutral transportation fuels, biomass feedstock compositional analysis methods are used to monitor, compare, and improve biofuel conversion processes. These methods are empirical, and the analytical variability seen in the feedstock compositional data propagates into variability in the conversion yields, component balances, mass balances, and ultimately the minimum ethanol selling price (MESP). We report the average composition and standard deviations of 119 individually extracted National Institute of Standards and Technology (NIST) bagasse [Reference Material (RM) 8491] run by seven analysts over 7 years. Two additional datasets, using bulk-extracted bagasse (containing 58 and 291 replicates each),more » were examined to separate out the effects of batch, analyst, sugar recovery standard calculation method, and extractions from the total analytical variability seen in the individually extracted dataset. We believe this is the world's largest NIST bagasse compositional analysis dataset and it provides unique insight into the long-term analytical variability. Understanding the long-term variability of the feedstock analysis will help determine the minimum difference that can be detected in yield, mass balance, and efficiency calculations. The long-term data show consistent bagasse component values through time and by different analysts. This suggests that the standard compositional analysis methods were performed consistently and that the bagasse RM itself remained unchanged during this time period. The long-term variability seen here is generally higher than short-term variabilities. It is worth noting that the effect of short-term or long-term feedstock compositional variability on MESP is small, about $0.03 per gallon. The long-term analysis variabilities reported here are plausible minimum values for these methods, though not necessarily average or expected variabilities. We must emphasize the importance of training and

Long-term variability in sugarcane bagasse feedstock compositional methods: Sources and magnitude of analytical variability

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

Templeton, David W.; Sluiter, Justin B.; Sluiter, Amie

In an effort to find economical, carbon-neutral transportation fuels, biomass feedstock compositional analysis methods are used to monitor, compare, and improve biofuel conversion processes. These methods are empirical, and the analytical variability seen in the feedstock compositional data propagates into variability in the conversion yields, component balances, mass balances, and ultimately the minimum ethanol selling price (MESP). We report the average composition and standard deviations of 119 individually extracted National Institute of Standards and Technology (NIST) bagasse [Reference Material (RM) 8491] run by seven analysts over 7 years. Two additional datasets, using bulk-extracted bagasse (containing 58 and 291 replicates each),more » were examined to separate out the effects of batch, analyst, sugar recovery standard calculation method, and extractions from the total analytical variability seen in the individually extracted dataset. We believe this is the world's largest NIST bagasse compositional analysis dataset and it provides unique insight into the long-term analytical variability. Understanding the long-term variability of the feedstock analysis will help determine the minimum difference that can be detected in yield, mass balance, and efficiency calculations. The long-term data show consistent bagasse component values through time and by different analysts. This suggests that the standard compositional analysis methods were performed consistently and that the bagasse RM itself remained unchanged during this time period. The long-term variability seen here is generally higher than short-term variabilities. It is worth noting that the effect of short-term or long-term feedstock compositional variability on MESP is small, about $0.03 per gallon. The long-term analysis variabilities reported here are plausible minimum values for these methods, though not necessarily average or expected variabilities. We must emphasize the importance of training and

Achievement of target A1C levels with negligible hypoglycemia and low glucose variability in youth with short-term type 1 diabetes and residual β-cell function.

PubMed

Sherr, Jennifer; Tamborlane, William V; Xing, Dongyuan; Tsalikian, Eva; Mauras, Nelly; Buckingham, Bruce; White, Neil H; Arbelaez, Ana Maria; Beck, Roy W; Kollman, Craig; Ruedy, Katrina

2012-04-01

To determine exposure to hyper- and hypoglycemia using blinded continuous glucose monitoring (CGM) profiles in youth with type 1 diabetes (T1D) with residual β-cell function during the first year of insulin treatment. Blinded, 3-7 day CGM profiles were obtained in 16 short-term T1D patients (age 8-18 years, T1D duration 6-52 weeks) who had peak C-peptide levels ranging from 0.46 to 1.96 nmol/L during a mixed-meal tolerance test. Results in this short-term group were compared with those in 34 patients with well-controlled, longer-term T1D (duration ≥5 years), matched for age and A1C with the short-term T1D group, and with those in 26 age-matched nondiabetic individuals. Despite matching for A1C, and therefore similar mean sensor glucose levels in the two T1D groups, short-term T1D participants had a lower frequency of hypoglycemia (0.3 vs. 7.6%, P < 0.001), a trend toward less hyperglycemia (17 vs. 32%, P = 0.15), and a greater percentage in the target range (median 77 vs. 60%, P = 0.02). Indeed, the percentage of sensor glucose levels ≤70 mg/dL in the short-term T1D group (0.3%) did not differ from those in the nondiabetic group (1.7%, P = 0.73). The coefficient of variation of sensor glucose levels (an index of glucose variability) was lower in short-term vs. longer-term T1D participants (27 vs. 42%, respectively, P < 0.001). In youth with short-term T1D who retain residual β-cell function, there is negligible exposure to hypoglycemia and lower glucose variability than in youth with well-controlled T1D of longer duration.

Short-term Time Step Convergence in a Climate Model

DOE PAGES

Wan, Hui; Rasch, Philip J.; Taylor, Mark; ...

2015-02-11

A testing procedure is designed to assess the convergence property of a global climate model with respect to time step size, based on evaluation of the root-mean-square temperature difference at the end of very short (1 h) simulations with time step sizes ranging from 1 s to 1800 s. A set of validation tests conducted without sub-grid scale parameterizations confirmed that the method was able to correctly assess the convergence rate of the dynamical core under various configurations. The testing procedure was then applied to the full model, and revealed a slow convergence of order 0.4 in contrast to themore » expected first-order convergence. Sensitivity experiments showed without ambiguity that the time stepping errors in the model were dominated by those from the stratiform cloud parameterizations, in particular the cloud microphysics. This provides a clear guidance for future work on the design of more accurate numerical methods for time stepping and process coupling in the model.« less

Screening variability and change of soil moisture under wide-ranging climate conditions: Snow dynamics effects.

PubMed

Verrot, Lucile; Destouni, Georgia

2015-01-01

Soil moisture influences and is influenced by water, climate, and ecosystem conditions, affecting associated ecosystem services in the landscape. This paper couples snow storage-melting dynamics with an analytical modeling approach to screening basin-scale, long-term soil moisture variability and change in a changing climate. This coupling enables assessment of both spatial differences and temporal changes across a wide range of hydro-climatic conditions. Model application is exemplified for two major Swedish hydrological basins, Norrström and Piteälven. These are located along a steep temperature gradient and have experienced different hydro-climatic changes over the time period of study, 1950-2009. Spatially, average intra-annual variability of soil moisture differs considerably between the basins due to their temperature-related differences in snow dynamics. With regard to temporal change, the long-term average state and intra-annual variability of soil moisture have not changed much, while inter-annual variability has changed considerably in response to hydro-climatic changes experienced so far in each basin.

Impact of climate variability on runoff in the north-central United States

USGS Publications Warehouse

Ryberg, Karen R.; Lin, Wei; Vecchia, Aldo V.

2014-01-01

Large changes in runoff in the north-central United States have occurred during the past century, with larger floods and increases in runoff tending to occur from the 1970s to the present. The attribution of these changes is a subject of much interest. Long-term precipitation, temperature, and streamflow records were used to compare changes in precipitation and potential evapotranspiration (PET) to changes in runoff within 25 stream basins. The basins studied were organized into four groups, each one representing basins similar in topography, climate, and historic patterns of runoff. Precipitation, PET, and runoff data were adjusted for near-decadal scale variability to examine longer-term changes. A nonlinear water-balance analysis shows that changes in precipitation and PET explain the majority of multidecadal spatial/temporal variability of runoff and flood magnitudes, with precipitation being the dominant driver. Historical changes in climate and runoff in the region appear to be more consistent with complex transient shifts in seasonal climatic conditions than with gradual climate change. A portion of the unexplained variability likely stems from land-use change.

Current Climate Variability & Change

NASA Astrophysics Data System (ADS)

Diem, J.; Criswell, B.; Elliott, W. C.

2013-12-01

Current Climate Variability & Change is the ninth among a suite of ten interconnected, sequential labs that address all 39 climate-literacy concepts in the U.S. Global Change Research Program's Climate Literacy: The Essential Principles of Climate Sciences. The labs are as follows: Solar Radiation & Seasons, Stratospheric Ozone, The Troposphere, The Carbon Cycle, Global Surface Temperature, Glacial-Interglacial Cycles, Temperature Changes over the Past Millennium, Climates & Ecosystems, Current Climate Variability & Change, and Future Climate Change. All are inquiry-based, on-line products designed in a way that enables students to construct their own knowledge of a topic. Questions representative of various levels of Webb's depth of knowledge are embedded in each lab. In addition to the embedded questions, each lab has three or four essential questions related to the driving questions for the lab suite. These essential questions are presented as statements at the beginning of the material to represent the lab objectives, and then are asked at the end as questions to function as a summative assessment. For example, the Current Climate Variability & Change is built around these essential questions: (1) What has happened to the global temperature at the Earth's surface, in the middle troposphere, and in the lower stratosphere over the past several decades?; (2) What is the most likely cause of the changes in global temperature over the past several decades and what evidence is there that this is the cause?; and (3) What have been some of the clearly defined effects of the change in global temperature on the atmosphere and other spheres of the Earth system? An introductory Prezi allows the instructor to assess students' prior knowledge in relation to these questions, while also providing 'hooks' to pique their interest related to the topic. The lab begins by presenting examples of and key differences between climate variability (e.g., Mt. Pinatubo eruption) and

Human Responses to Climate Variability: The Case of South Africa

NASA Astrophysics Data System (ADS)

Oppenheimer, M.; Licker, R.; Mastrorillo, M.; Bohra-Mishra, P.; Estes, L. D.; Cai, R.

2014-12-01

Climate variability has been associated with a range of societal and individual outcomes including migration, violent conflict, changes in labor productivity, and health impacts. Some of these may be direct responses to changes in mean temperature or precipitation or extreme events, such as displacement of human populations by tropical cyclones. Others may be mediated by a variety of biological, social, or ecological factors such as migration in response to long-term changes in crops yields. Research is beginning to elucidate and distinguish the many channels through which climate variability may influence human behavior (ranging from the individual to the collective, societal level) in order to better understand how to improve resilience in the face of current variability as well as future climate change. Using a variety of data sets from South Africa, we show how climate variability has influenced internal (within country) migration in recent history. We focus on South Africa as it is a country with high levels of internal migration and dramatic temperature and precipitation changes projected for the 21st century. High poverty rates and significant levels of rain-fed, smallholder agriculture leave large portions of South Africa's population base vulnerable to future climate change. In this study, we utilize two complementary statistical models - one micro-level model, driven by individual and household level survey data, and one macro-level model, driven by national census statistics. In both models, we consider the effect of climate on migration both directly (with gridded climate reanalysis data) and indirectly (with agricultural production statistics). With our historical analyses of climate variability, we gain insights into how the migration decisions of South Africans may be influenced by future climate change. We also offer perspective on the utility of micro and macro level approaches in the study of climate change and human migration.

Evaluation of regression and neural network models for solar forecasting over different short-term horizons

DOE PAGES

Inanlouganji, Alireza; Reddy, T. Agami; Katipamula, Srinivas

2018-04-13

Forecasting solar irradiation has acquired immense importance in view of the exponential increase in the number of solar photovoltaic (PV) system installations. In this article, analyses results involving statistical and machine-learning techniques to predict solar irradiation for different forecasting horizons are reported. Yearlong typical meteorological year 3 (TMY3) datasets from three cities in the United States with different climatic conditions have been used in this analysis. A simple forecast approach that assumes consecutive days to be identical serves as a baseline model to compare forecasting alternatives. To account for seasonal variability and to capture short-term fluctuations, different variants of themore » lagged moving average (LMX) model with cloud cover as the input variable are evaluated. Finally, the proposed LMX model is evaluated against an artificial neural network (ANN) model. How the one-hour and 24-hour models can be used in conjunction to predict different short-term rolling horizons is discussed, and this joint application is illustrated for a four-hour rolling horizon forecast scheme. Lastly, the effect of using predicted cloud cover values, instead of measured ones, on the accuracy of the models is assessed. Results show that LMX models do not degrade in forecast accuracy if models are trained with the forecast cloud cover data.« less

Evaluation of regression and neural network models for solar forecasting over different short-term horizons

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

Inanlouganji, Alireza; Reddy, T. Agami; Katipamula, Srinivas

Forecasting solar irradiation has acquired immense importance in view of the exponential increase in the number of solar photovoltaic (PV) system installations. In this article, analyses results involving statistical and machine-learning techniques to predict solar irradiation for different forecasting horizons are reported. Yearlong typical meteorological year 3 (TMY3) datasets from three cities in the United States with different climatic conditions have been used in this analysis. A simple forecast approach that assumes consecutive days to be identical serves as a baseline model to compare forecasting alternatives. To account for seasonal variability and to capture short-term fluctuations, different variants of themore » lagged moving average (LMX) model with cloud cover as the input variable are evaluated. Finally, the proposed LMX model is evaluated against an artificial neural network (ANN) model. How the one-hour and 24-hour models can be used in conjunction to predict different short-term rolling horizons is discussed, and this joint application is illustrated for a four-hour rolling horizon forecast scheme. Lastly, the effect of using predicted cloud cover values, instead of measured ones, on the accuracy of the models is assessed. Results show that LMX models do not degrade in forecast accuracy if models are trained with the forecast cloud cover data.« less

Short-term variability in the ionosphere due to the nonlinear interaction between the 6 day wave and migrating tides

NASA Astrophysics Data System (ADS)

Gan, Quan; Oberheide, Jens; Yue, Jia; Wang, Wenbin

2017-08-01

Using the thermosphere-ionosphere-mesosphere electrodynamics general circulation model simulations, we investigate the short-term ionospheric variability due to the child waves and altered tides produced by the nonlinear interaction between the 6 day wave and migrating tides. Via the Fourier spectral diagnostics and least squares fittings, the [21 h, W2] and [13 h, W1] child waves, generated by the interaction of the 6 day wave with the DW1 and SW2, respectively, are found to play the leading roles on the subdiurnal variability (e.g., ±10 m/s in the ion drift and 50% in the NmF2) in the F region vertical ion drift changes through the dynamo modulation induced by the low-latitude zonal wind and the meridional wind at higher latitudes. The relatively minor contribution of the [11 h, W3] child wave is explicit as well. Although the [29 h, W0] child wave has the largest magnitude in the E region, its effect is totally absent in the vertical ion drift due to the zonally uniform structure. But the [29 h, W0] child wave shows up in the NmF2. It is found that the NmF2 short-term variability is attributed to the wave modulations on both E region dynamo and in situ F region composition. Also, the altered migrating tides due to the interaction will not contribute to the ionospheric changes significantly.

WRF model sensitivity to land surface model and cumulus parameterization under short-term climate extremes over the southern Great Plains of the United States

Treesearch

Lisi Pei; Nathan Moore; Shiyuan Zhong; Lifeng Luo; David W. Hyndman; Warren E. Heilman; Zhiqiu Gao

2014-01-01

Extreme weather and climate events, especially short-term excessive drought and wet periods over agricultural areas, have received increased attention. The Southern Great Plains (SGP) is one of the largest agricultural regions in North America and features the underlying Ogallala-High Plains Aquifer system worth great economic value in large part due to production...

Monitoring Climate Variability and Change in Northern Alaska: Updates to the U.S. Geological Survey (USGS) Climate and Permafrost Monitoring Network

NASA Astrophysics Data System (ADS)

Urban, F. E.; Clow, G. D.; Meares, D. C.

2004-12-01

Observations of long-term climate and surficial geological processes are sparse in most of the Arctic, despite the fact that this region is highly sensitive to climate change. Instrumental networks that monitor the interplay of climatic variability and geological/cryospheric processes are a necessity for documenting and understanding climate change. Improvements to the spatial coverage and temporal scale of Arctic climate data are in progress. The USGS, in collaboration with The Bureau of Land Management (BLM) and The Fish and Wildlife Service (FWS) currently maintains two types of monitoring networks in northern Alaska: (1) A 15 site network of continuously operating active-layer and climate monitoring stations, and (2) a 21 element array of deep bore-holes in which the thermal state of deep permafrost is monitored. Here, we focus on the USGS Alaska Active Layer and Climate Monitoring Network (AK-CLIM). These 15 stations are deployed in longitudinal transects that span Alaska north of the Brooks Range, (11 in The National Petroleum Reserve Alaska, (NPRA), and 4 in The Arctic National Wildlife Refuge (ANWR)). An informative overview and update of the USGS AK-CLIM network is presented, including insight to current data, processing and analysis software, and plans for data telemetry. Data collection began in 1998 and parameters currently measured include air temperature, soil temperatures (5-120 cm), snow depth, incoming and reflected short-wave radiation, soil moisture (15 cm), wind speed and direction. Custom processing and analysis software has been written that calculates additional parameters such as active layer thaw depth, thawing-degree-days, albedo, cloudiness, and duration of seasonal snow cover. Data from selected AK-CLIM stations are now temporally sufficient to begin identifying trends, anomalies, and inter-annual variability in the climate of northern Alaska.

Smallholder agriculture in India and adaptation to current and future climate variability and climate change

NASA Astrophysics Data System (ADS)

Murari, K. K.; Jayaraman, T.

2014-12-01

Modeling studies have indicated that global warming, in many regions, will increase the exposure of major crops to rainfall and temperature stress, leading to lower crop yields. Climate variability alone has a potential to decrease yield to an extent comparable to or greater than yield reductions expected due to rising temperature. For India, where agriculture is important, both in terms of food security as well as a source of livelihoods to a majority of its population, climate variability and climate change are subjects of serious concern. There is however a need to distinguish the impact of current climate variability and climate change on Indian agriculture, especially in relation to their socioeconomic impact. This differentiation is difficult to determine due to the secular trend of increasing production and yield of the past several decades. The current research in this aspect is in an initial stage and requires a multi-disciplinary effort. In this study, we assess the potential differential impacts of environmental stress and shock across different socioeconomic strata of the rural population, using village level survey data. The survey data from eight selected villages, based on the Project on Agrarian Relations in India conducted by the Foundation for Agrarian Studies, indicated that income from crop production of the top 20 households (based on the extent of operational land holding, employment of hired labour and asset holdings) is a multiple of the mean income of the village. In sharp contrast, the income of the bottom 20 households is a fraction of the mean and sometimes negative, indicating a net loss from crop production. The considerable differentials in output and incomes suggest that small and marginal farmers are far more susceptible to climate variability and climate change than the other sections. Climate change is effectively an immediate threat to small and marginal farmers, which is driven essentially by socioeconomic conditions. The impact

Climate variability has a stabilizing effect on the coexistence of prairie grasses

PubMed Central

Adler, Peter B.; HilleRisLambers, Janneke; Kyriakidis, Phaedon C.; Guan, Qingfeng; Levine, Jonathan M.

2006-01-01

How expected increases in climate variability will affect species diversity depends on the role of such variability in regulating the coexistence of competing species. Despite theory linking temporal environmental fluctuations with the maintenance of diversity, the importance of climate variability for stabilizing coexistence remains unknown because of a lack of appropriate long-term observations. Here, we analyze three decades of demographic data from a Kansas prairie to demonstrate that interannual climate variability promotes the coexistence of three common grass species. Specifically, we show that (i) the dynamics of the three species satisfy all requirements of “storage effect” theory based on recruitment variability with overlapping generations, (ii) climate variables are correlated with interannual variation in species performance, and (iii) temporal variability increases low-density growth rates, buffering these species against competitive exclusion. Given that environmental fluctuations are ubiquitous in natural systems, our results suggest that coexistence based on the storage effect may be underappreciated and could provide an important alternative to recent neutral theories of diversity. Field evidence for positive effects of variability on coexistence also emphasizes the need to consider changes in both climate means and variances when forecasting the effects of global change on species diversity. PMID:16908862

Emergent constraint on equilibrium climate sensitivity from global temperature variability.

PubMed

Cox, Peter M; Huntingford, Chris; Williamson, Mark S

2018-01-17

Equilibrium climate sensitivity (ECS) remains one of the most important unknowns in climate change science. ECS is defined as the global mean warming that would occur if the atmospheric carbon dioxide (CO 2 ) concentration were instantly doubled and the climate were then brought to equilibrium with that new level of CO 2 . Despite its rather idealized definition, ECS has continuing relevance for international climate change agreements, which are often framed in terms of stabilization of global warming relative to the pre-industrial climate. However, the 'likely' range of ECS as stated by the Intergovernmental Panel on Climate Change (IPCC) has remained at 1.5-4.5 degrees Celsius for more than 25 years. The possibility of a value of ECS towards the upper end of this range reduces the feasibility of avoiding 2 degrees Celsius of global warming, as required by the Paris Agreement. Here we present a new emergent constraint on ECS that yields a central estimate of 2.8 degrees Celsius with 66 per cent confidence limits (equivalent to the IPCC 'likely' range) of 2.2-3.4 degrees Celsius. Our approach is to focus on the variability of temperature about long-term historical warming, rather than on the warming trend itself. We use an ensemble of climate models to define an emergent relationship between ECS and a theoretically informed metric of global temperature variability. This metric of variability can also be calculated from observational records of global warming, which enables tighter constraints to be placed on ECS, reducing the probability of ECS being less than 1.5 degrees Celsius to less than 3 per cent, and the probability of ECS exceeding 4.5 degrees Celsius to less than 1 per cent.

Emergent constraint on equilibrium climate sensitivity from global temperature variability

NASA Astrophysics Data System (ADS)

Cox, Peter M.; Huntingford, Chris; Williamson, Mark S.

2018-01-01

Equilibrium climate sensitivity (ECS) remains one of the most important unknowns in climate change science. ECS is defined as the global mean warming that would occur if the atmospheric carbon dioxide (CO2) concentration were instantly doubled and the climate were then brought to equilibrium with that new level of CO2. Despite its rather idealized definition, ECS has continuing relevance for international climate change agreements, which are often framed in terms of stabilization of global warming relative to the pre-industrial climate. However, the ‘likely’ range of ECS as stated by the Intergovernmental Panel on Climate Change (IPCC) has remained at 1.5-4.5 degrees Celsius for more than 25 years. The possibility of a value of ECS towards the upper end of this range reduces the feasibility of avoiding 2 degrees Celsius of global warming, as required by the Paris Agreement. Here we present a new emergent constraint on ECS that yields a central estimate of 2.8 degrees Celsius with 66 per cent confidence limits (equivalent to the IPCC ‘likely’ range) of 2.2-3.4 degrees Celsius. Our approach is to focus on the variability of temperature about long-term historical warming, rather than on the warming trend itself. We use an ensemble of climate models to define an emergent relationship between ECS and a theoretically informed metric of global temperature variability. This metric of variability can also be calculated from observational records of global warming, which enables tighter constraints to be placed on ECS, reducing the probability of ECS being less than 1.5 degrees Celsius to less than 3 per cent, and the probability of ECS exceeding 4.5 degrees Celsius to less than 1 per cent.

A Short-Term Longitudinal Study of Memorial Development during Early Grade School.

ERIC Educational Resources Information Center

Kunzinger, Edward L., III

1985-01-01

Overt rehearsal and free recall performance was analyzed longitudinally in two experimental testing sessions at 7 and later at 9 years of age. Measures of short- and long-term memory recall, and two measures of input processing were obtained. Significant increases between age levels were exhibited by all variables except short-term memory.…

Limited short-term prognostic utility of cerebral NIRS during neonatal therapeutic hypothermia.

PubMed

Shellhaas, Renée A; Thelen, Brian J; Bapuraj, Jayapalli R; Burns, Joseph W; Swenson, Aaron W; Christensen, Mary K; Wiggins, Stephanie A; Barks, John D E

2013-07-16

We evaluated the utility of amplitude-integrated EEG (aEEG) and regional oxygen saturation (rSO2) measured using near-infrared spectroscopy (NIRS) for short-term outcome prediction in neonates with hypoxic ischemic encephalopathy (HIE) treated with therapeutic hypothermia. Neonates with HIE were monitored with dual-channel aEEG, bilateral cerebral NIRS, and systemic NIRS throughout cooling and rewarming. The short-term outcome measure was a composite of neurologic examination and brain MRI scores at 7 to 10 days. Multiple regression models were developed to assess NIRS and aEEG recorded during the 6 hours before rewarming and the 6-hour rewarming period as predictors of short-term outcome. Twenty-one infants, mean gestational age 38.8 ± 1.6 weeks, median 10-minute Apgar score 4 (range 0-8), and mean initial pH 6.92 ± 0.19, were enrolled. Before rewarming, the most parsimonious model included 4 parameters (adjusted R(2) = 0.59; p = 0.006): lower values of systemic rSO2 variability (p = 0.004), aEEG bandwidth variability (p = 0.019), and mean aEEG upper margin (p = 0.006), combined with higher mean aEEG bandwidth (worse discontinuity; p = 0.013), predicted worse short-term outcome. During rewarming, lower systemic rSO2 variability (p = 0.007) and depressed aEEG lower margin (p = 0.034) were associated with worse outcome (model-adjusted R(2) = 0.49; p = 0.005). Cerebral NIRS data did not contribute to either model. During day 3 of cooling and during rewarming, loss of physiologic variability (by systemic NIRS) and invariant, discontinuous aEEG patterns predict poor short-term outcome in neonates with HIE. These parameters, but not cerebral NIRS, may be useful to identify infants suitable for studies of adjuvant neuroprotective therapies or modification of the duration of cooling and/or rewarming.

Short-term stability of sleep and heart rate variability in good sleepers and patients with insomnia: for some measures, one night is enough.

PubMed

Israel, Benjamin; Buysse, Daniel J; Krafty, Robert T; Begley, Amy; Miewald, Jean; Hall, Martica

2012-09-01

Quantify the short-term stability of multiple indices of sleep and nocturnal physiology in good sleeper controls and primary insomnia patients. Intra-class correlation coefficients (ICC) were used to quantify the short-term stability of study outcomes. Sleep laboratory. Fifty-four adults with primary insomnia (PI) and 22 good sleeper controls (GSC). Visually scored sleep outcomes included indices of sleep duration, continuity, and architecture. Quantitative EEG outcomes included power in the delta, theta, alpha, sigma, and beta bands during NREM sleep. Power spectral analysis was used to estimate high-frequency heart rate variability (HRV) and the ratio of low- to high-frequency HRV power during NREM and REM sleep. With the exception of percent stage 3+4 sleep; visually scored sleep outcomes did not exhibit short-term stability across study nights. Most QEEG outcomes demonstrated short-term stability in both groups. Although power in the beta band was stable in the PI group (ICC = 0.75), it tended to be less stable in GSCs (ICC = 0.55). Both measures of cardiac autonomic tone exhibited short-term stability in GSCs and PIs during NREM and REM sleep. Most QEEG bandwidths and HRV during sleep show high short-term stability in good sleepers and patients with insomnia alike. One night of data is, thus, sufficient to derive reliable estimates of these outcomes in studies focused on group differences or correlates of QEEG and/or HRV. In contrast, one night of data is unlikely to generate reliable estimates of PSG-assessed sleep duration, continuity or architecture, with the exception of slow wave sleep.

Processes Understanding of Decadal Climate Variability

NASA Astrophysics Data System (ADS)

Prömmel, Kerstin; Cubasch, Ulrich

2016-04-01

The realistic representation of decadal climate variability in the models is essential for the quality of decadal climate predictions. Therefore, the understanding of those processes leading to decadal climate variability needs to be improved. Several of these processes are already included in climate models but their importance has not yet completely been clarified. The simulation of other processes requires sometimes a higher resolution of the model or an extension by additional subsystems. This is addressed within one module of the German research program "MiKlip II - Decadal Climate Predictions" (http://www.fona-miklip.de/en/) with a focus on the following processes. Stratospheric processes and their impact on the troposphere are analysed regarding the climate response to aerosol perturbations caused by volcanic eruptions and the stratospheric decadal variability due to solar forcing, climate change and ozone recovery. To account for the interaction between changing ozone concentrations and climate a computationally efficient ozone chemistry module is developed and implemented in the MiKlip prediction system. The ocean variability and air-sea interaction are analysed with a special focus on the reduction of the North Atlantic cold bias. In addition, the predictability of the oceanic carbon uptake with a special emphasis on the underlying mechanism is investigated. This addresses a combination of physical, biological and chemical processes.

Climate variability drives population cycling and synchrony

Treesearch

Lars Y. Pomara; Benjamin Zuckerberg

2017-01-01

Aim There is mounting concern that climate change will lead to the collapse of cyclic population dynamics, yet the influence of climate variability on population cycling remains poorly understood. We hypothesized that variability in survival and fecundity, driven by climate variability at different points in the life cycle, scales up from...

Short-term variability in amplitude and motor topography of whole-body involuntary movements in Parkinson's disease dyskinesias and in Huntington's chorea.

PubMed

Fenney, Alison; Jog, Mandar S; Duval, Christian

2008-02-01

Clinical observations have noted variability in amplitude of levodopa-induced dyskinesias (LID) in Parkinson's disease (PD) and chorea in Huntington's disease (HD) during the day. However, no studies have examined whether both the amplitude and body location (motor topography) of whole-body involuntary movement (WBIM) varied over short periods of time (seconds or minutes), which may have a distinct and significant effect on how disruptive these WBIM may be. The present study quantified the variability of WBIM amplitude and motor topography in patients with PD having LID and in patients with HD having chorea. WBIM was quantified using the MotionMonitor magnetic motion tracker system. Five patients in each group were tested in two conditions: sitting and standing. WBIM increased from sitting to standing, more so in choreic patients. WBIM varied from 17% to 102% of total WBIM amplitude. Chorea tended to present with greater variability than LID in absolute terms in the standing condition, but not when the mean WBIM amplitude was taken into consideration. Motor topography of WBIM also varied more in the HD group, but mostly in the seated condition where more limbs were free to move. Neither group expressed any laterality of involuntary movement, with amplitude being equally distributed on both sides of the body. Results show significant short-term variability in amplitude of chorea and LID, as well as, variability in location of these involuntary movements, illustrating the complexity of the adaptations required to live and be active with involuntary movements such as HD chorea or PD dyskinesias.

Surface clay formation during short-term warmer and wetter conditions on a largely cold ancient Mars

NASA Astrophysics Data System (ADS)

Bishop, Janice L.; Fairén, Alberto G.; Michalski, Joseph R.; Gago-Duport, Luis; Baker, Leslie L.; Velbel, Michael A.; Gross, Christoph; Rampe, Elizabeth B.

2018-03-01

The ancient rock record for Mars has long been at odds with climate modelling. The presence of valley networks, dendritic channels and deltas on ancient terrains points towards running water and fluvial erosion on early Mars1, but climate modelling indicates that long-term warm conditions were not sustainable2. Widespread phyllosilicates and other aqueous minerals on the Martian surface3-6 provide additional evidence that an early wet Martian climate resulted in surface weathering. Some of these phyllosilicates formed in subsurface crustal environments5, with no association with the Martian climate, while other phyllosilicate-rich outcrops exhibit layered morphologies and broad stratigraphies7 consistent with surface formation. Here, we develop a new geochemical model for early Mars to explain the formation of these clay-bearing rocks in warm and wet surface locations. We propose that sporadic, short-term warm and wet environments during a generally cold early Mars enabled phyllosilicate formation without requiring long-term warm and wet conditions. We conclude that Mg-rich clay-bearing rocks with lateral variations in mixed Fe/Mg smectite, chlorite, talc, serpentine and zeolite occurrences formed in subsurface hydrothermal environments, whereas dioctahedral (Al/Fe3+-rich) smectite and widespread vertical horizonation of Fe/Mg smectites, clay assemblages and sulphates formed in variable aqueous environments on the surface of Mars. Our model for aluminosilicate formation on Mars is consistent with the observed geological features, diversity of aqueous mineralogies in ancient surface rocks and state-of-the-art palaeoclimate scenarios.

Climate Variability Program

NASA Technical Reports Server (NTRS)

Halpern, David (Editor)

2002-01-01

The Annual Report of the Climate Variability Program briefly describes research activities of Principal Investigators who are funded by NASA's Earth Science Enterprise Research Division. The report is focused on the year 2001. Utilization of satellite observations is a singularity of research on climate science and technology at JPL (Jet Propulsion Laboratory). Research at JPL has two foci: generate new knowledge and develop new technology.

Short-term Operation of Multi-purpose Reservoir using Model Predictive Control

NASA Astrophysics Data System (ADS)

Uysal, Gokcen; Schwanenberg, Dirk; Alvarado Montero, Rodolfo; Sensoy, Aynur; Arda Sorman, Ali

2017-04-01

Operation of water structures especially with conflicting water supply and flood mitigation objectives is under more stress attributed to growing water demand and changing hydro-climatic conditions. Model Predictive Control (MPC) based optimal control solutions has been successfully applied to different water resources applications. In this study, Feedback Control (FBC) and MPC get combined and an improved joint optimization-simulation operating scheme is proposed. Water supply and flood control objectives are fulfilled by incorporating the long term water supply objectives into a time-dependent variable guide curve policy whereas the extreme floods are attenuated by means of short-term optimization based on MPC. A final experiment is carried out to assess the lead time performance and reliability of forecasts in a hindcasting experiment with imperfect, perturbed forecasts. The framework is tested in Yuvacık Dam reservoir where the main water supply reservoir of Kocaeli City in the northwestern part of Turkey (the Marmara region) and it requires a challenging gate operation due to restricted downstream flow conditions.

Interactions of Mean Climate Change and Climate Variability on Food Security Extremes

NASA Technical Reports Server (NTRS)

Ruane, Alexander C.; McDermid, Sonali; Mavromatis, Theodoros; Hudson, Nicholas; Morales, Monica; Simmons, John; Prabodha, Agalawatte; Ahmad, Ashfaq; Ahmad, Shakeel; Ahuja, Laj R.

2015-01-01

Recognizing that climate change will affect agricultural systems both through mean changes and through shifts in climate variability and associated extreme events, we present preliminary analyses of climate impacts from a network of 1137 crop modeling sites contributed to the AgMIP Coordinated Climate-Crop Modeling Project (C3MP). At each site sensitivity tests were run according to a common protocol, which enables the fitting of crop model emulators across a range of carbon dioxide, temperature, and water (CTW) changes. C3MP can elucidate several aspects of these changes and quantify crop responses across a wide diversity of farming systems. Here we test the hypothesis that climate change and variability interact in three main ways. First, mean climate changes can affect yields across an entire time period. Second, extreme events (when they do occur) may be more sensitive to climate changes than a year with normal climate. Third, mean climate changes can alter the likelihood of climate extremes, leading to more frequent seasons with anomalies outside of the expected conditions for which management was designed. In this way, shifts in climate variability can result in an increase or reduction of mean yield, as extreme climate events tend to have lower yield than years with normal climate.C3MP maize simulations across 126 farms reveal a clear indication and quantification (as response functions) of mean climate impacts on mean yield and clearly show that mean climate changes will directly affect the variability of yield. Yield reductions from increased climate variability are not as clear as crop models tend to be less sensitive to dangers on the cool and wet extremes of climate variability, likely underestimating losses from water-logging, floods, and frosts.

Variability in climate change simulations affects needed long-term riverine nutrient reductions for the Baltic Sea.

PubMed

Bring, Arvid; Rogberg, Peter; Destouni, Georgia

2015-06-01

Changes to runoff due to climate change may influence management of nutrient loading to the sea. Assuming unchanged river nutrient concentrations, we evaluate the effects of changing runoff on commitments to nutrient reductions under the Baltic Sea Action Plan. For several countries, climate projections point to large variability in load changes in relation to reduction targets. These changes either increase loads, making the target more difficult to reach, or decrease them, leading instead to a full achievement of the target. The impact of variability in climate projections varies with the size of the reduction target and is larger for countries with more limited commitments. In the end, a number of focused actions are needed to manage the effects of climate change on nutrient loads: reducing uncertainty in climate projections, deciding on frameworks to identify best performing models with respect to land surface hydrology, and increasing efforts at sustained monitoring of water flow changes.

Variability in climate change simulations affects needed long-term riverine nutrient reductions for the Baltic Sea

DOE PAGES

Bring, Arvid; Rogberg, Peter; Destouni, Georgia

2015-05-28

Changes to runoff due to climate change may influence management of nutrient loading to the sea. Assuming unchanged river nutrient concentrations, we evaluate the effects of changing runoff on commitments to nutrient reductions under the Baltic Sea Action Plan. For several countries, climate projections point to large variability in load changes in relation to reduction targets. These changes either increase loads, making the target more difficult to reach, or decrease them, leading instead to a full achievement of the target. The impact of variability in climate projections varies with the size of the reduction target and is larger for countriesmore » with more limited commitments. Finally, in the end, a number of focused actions are needed to manage the effects of climate change on nutrient loads: reducing uncertainty in climate projections, deciding on frameworks to identify best performing models with respect to land surface hydrology, and increasing efforts at sustained monitoring of water flow changes.« less

Variability in climate change simulations affects needed long-term riverine nutrient reductions for the Baltic Sea

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

Bring, Arvid; Rogberg, Peter; Destouni, Georgia

Changes to runoff due to climate change may influence management of nutrient loading to the sea. Assuming unchanged river nutrient concentrations, we evaluate the effects of changing runoff on commitments to nutrient reductions under the Baltic Sea Action Plan. For several countries, climate projections point to large variability in load changes in relation to reduction targets. These changes either increase loads, making the target more difficult to reach, or decrease them, leading instead to a full achievement of the target. The impact of variability in climate projections varies with the size of the reduction target and is larger for countriesmore » with more limited commitments. Finally, in the end, a number of focused actions are needed to manage the effects of climate change on nutrient loads: reducing uncertainty in climate projections, deciding on frameworks to identify best performing models with respect to land surface hydrology, and increasing efforts at sustained monitoring of water flow changes.« less

Short-term Forecasting Tools for Agricultural Nutrient Management.

PubMed

Easton, Zachary M; Kleinman, Peter J A; Buda, Anthony R; Goering, Dustin; Emberston, Nichole; Reed, Seann; Drohan, Patrick J; Walter, M Todd; Guinan, Pat; Lory, John A; Sommerlot, Andrew R; Sharpley, Andrew

2017-11-01

The advent of real-time, short-term farm management tools is motivated by the need to protect water quality above and beyond the general guidance offered by existing nutrient management plans. Advances in high-performance computing and hydrologic or climate modeling have enabled rapid dissemination of real-time information that can assist landowners and conservation personnel with short-term management planning. This paper reviews short-term decision support tools for agriculture that are under various stages of development and implementation in the United States: (i) Wisconsin's Runoff Risk Advisory Forecast (RRAF) System, (ii) New York's Hydrologically Sensitive Area Prediction Tool, (iii) Virginia's Saturated Area Forecast Model, (iv) Pennsylvania's Fertilizer Forecaster, (v) Washington's Application Risk Management (ARM) System, and (vi) Missouri's Design Storm Notification System. Although these decision support tools differ in their underlying model structure, the resolution at which they are applied, and the hydroclimates to which they are relevant, all provide forecasts (range 24-120 h) of runoff risk or soil moisture saturation derived from National Weather Service Forecast models. Although this review highlights the need for further development of robust and well-supported short-term nutrient management tools, their potential for adoption and ultimate utility requires an understanding of the appropriate context of application, the strategic and operational needs of managers, access to weather forecasts, scales of application (e.g., regional vs. field level), data requirements, and outreach communication structure. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Short-term Variability of Extinction by Broadband Stellar Photometry

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

Musat, I.C.; Ellingson, R.G.

2005-03-18

Aerosol optical depth variation over short-term time intervals is determined from broadband observations of stars with a whole sky imager. The main difficulty in such measurements consists of accurately separating the star flux value from the non-stellar diffuse skylight. Using correction method to overcome this difficulty, the monochromatic extinction at the ground due to aerosols is extracted from heterochromatic measurements. A form of closure is achieved by comparison with simultaneous or temporally close measurements with other instruments, and the total error of the method, as a combination of random error of measurements and systematic error of calibration and model, ismore » assessed as being between 2.6 and 3% rms.« less

[Serotonin receptor (5-HTR2A) and dysbindin (DTNBP1) genes and component process variables of short-term verbal memory in schizophrenia].

PubMed

Alfimova, M V; Monakhov, M V; Abramova, L I; Golubev, S A; Golimbet, V E

2009-01-01

An association study of variations in the DTNBP1 (P1763 and P1578) and 5-HTR2A (T102C and A-1438G) genes with short-term verbal memory efficiency and its component process variables was carried out in 405 patients with schizophrenia and 290 healthy controls. All subjects were asked to recall immediately two sets of 10 words. Total recall, List 1 recall, immediate recall or attention span, proactive interference and a number of intrusions were measured. Patients significantly differed from controls by all memory variables. The efficiency of test performance, efficiency of immediate memory, effect of proactive interference as well as number of intrusions were decreased in the group of patients. Both 5-HTR2A polymorphisms were associated with short-term verbal memory efficiency in the combined sample, with the worst performance observed in carriers of homozygous CC (T102C) and GG (A-1438G) genotypes. The significant effect of the P1763 (DTNBP1) marker on the component process variables (proactive interference and intrusions) was found while its effect on the total recall was non-significant. The homozygotes for GG (P1763) had the worst scores. Overall, the data obtained are in line with the conception of DTNBP1 and 5-HTR2A involvement in different component process variables of memory in healthy subjects and patients with schizophrenia.

The long- and short-term variability of breathing induced tumor motion in lung and liver over the course of a radiotherapy treatment.

PubMed

Dhont, Jennifer; Vandemeulebroucke, Jef; Burghelea, Manuela; Poels, Kenneth; Depuydt, Tom; Van Den Begin, Robbe; Jaudet, Cyril; Collen, Christine; Engels, Benedikt; Reynders, Truus; Boussaer, Marlies; Gevaert, Thierry; De Ridder, Mark; Verellen, Dirk

2018-02-01

To evaluate the short and long-term variability of breathing induced tumor motion. 3D tumor motion of 19 lung and 18 liver lesions captured over the course of an SBRT treatment were evaluated and compared to the motion on 4D-CT. An implanted fiducial could be used for unambiguous motion information. Fast orthogonal fluoroscopy (FF) sequences, included in the treatment workflow, were used to evaluate motion during treatment. Several motion parameters were compared between different FF sequences from the same fraction to evaluate the intrafraction variability. To assess interfraction variability, amplitude and hysteresis were compared between fractions and with the 3D tumor motion registered by 4D-CT. Population based margins, necessary on top of the ITV to capture all motion variability, were calculated based on the motion captured during treatment. Baseline drift in the cranio-caudal (CC) or anterior-poster (AP) direction is significant (ie. >5 mm) for a large group of patients, in contrary to intrafraction amplitude and hysteresis variability. However, a correlation between intrafraction amplitude variability and mean motion amplitude was found (Pearson's correlation coefficient, r = 0.72, p < 10 -4 ). Interfraction variability in amplitude is significant for 46% of all lesions. As such, 4D-CT accurately captures the motion during treatment for some fractions but not for all. Accounting for motion variability during treatment increases the PTV margins in all directions, most significantly in CC from 5 mm to 13.7 mm for lung and 8.0 mm for liver. Both short-term and day-to-day tumor motion variability can be significant, especially for lesions moving with amplitudes above 7 mm. Abandoning passive motion management strategies in favor of more active ones is advised. Copyright © 2017 Elsevier B.V. All rights reserved.

Connectivity clues from short-term variability in settlement and geochemical tags of mytilid mussels

NASA Astrophysics Data System (ADS)

Fodrie, F. Joel; Becker, Bonnie J.; Levin, Lisa A.; Gruenthal, Kristen; McMillan, Pat A.

2011-01-01

The use of geochemical tags in calcified structures of fish and invertebrates is an exciting tool for investigating larval population connectivity. Tag evaluation over relatively short intervals (weeks) may detect environmental and ecological variability at a temporal scale highly relevant to larval transport and settlement. We collected newly settled mussels ( Mytilus californianus and M. galloprovincialis) weekly during winter/spring of 2002 along the coast of San Diego, CA, USA, at sites on the exposed coast (SIO) and in a protected coastal bay (HI), to investigate temporal patterns of geochemical tags in mussel shells. Analyses of post-settlement shell via LA-ICP-MS revealed statistically significant temporal variability for all elements we examined (Mg, Mn, Cu, Sr, Cd, Ba, Pb and U). Despite this, our ability to distinguish multielemental signatures between sites was largely conserved. Throughout our 13-week study, SIO and HI mussels could be chemically distinguished from one another in 78-87% of all cases. Settlement varied between 2 and 27 settlers gram-byssus -1 week -1 at SIO and HI, and both sites were characterized by 2-3 weeks with "high" settlement. Geochemical tags recorded in early larval shell of newly settled mussels differed between "high" and "low" settlement weeks at both sites (MANOVA), driven by Mg and Sr at SIO (p = 0.013) and Sr, Cd, Ba and Pb at HI (p < 0.001). These data imply that shifts in larval sources or transport corridors were responsible for observed settlement variation, rather than increased larval production. In particular, increased settlement at HI was observed concurrent with the appearance of geochemical tags (e.g., elevated Cd), suggesting that those larvae were retained in upwelled water near the mouth of the bay. Such shifts may reflect short-term changes in connectivity among sites due to altered transport corridors, and influence the demography of local populations.

Long-term variability and changes in thunderstorm induced extreme precipitation in Slovakia over 1951-2010

NASA Astrophysics Data System (ADS)

Pecho, J.; Faško, P.; Bližák, V.; Kajaba, P.; Košálová, J.; Bochníček, O.; Lešková, L.

2012-04-01

It is well known that extreme precipitation associated with intensive rains, in summer induced mostly by local thunderstorm activity, could cause very significant problems in economical and social spheres of the countries. Heavy precipitation and consecutive flash-floods are the most serious weather-related hazards over the territory of Slovakia. The extreme precipitation analyses play a strategic role in many climatological and hydrological evaluations designed for the wide range of technical and engineering applications as well as climate change impact assessments. A thunderstorm, as a violent local storm produced by a cumulonimbus cloud and accompanied by thunder and lightning, represents extreme convective activity in the atmosphere depending upon the release of latent heat, by the condensation of water vapor, for most of its energy. Under the natural conditions of Slovakia the incidence of thunderstorms has been traditionally concentrated in the summer or warm half-year (Apr.-Sept.), but increasing air temperature resulting in higher water vapor content and more intense short-term precipitation is associated with more frequent thunderstorm occurrence in early spring as well as autumn. It is the main reason why the studies of thunderstorm phenomena have increased in Slovakia in recent years. It was found that thunderstorm occurrence, in terms of incidence of storm days, has profoundly changed particularly in spring season (~ 30 % in April and May). The present contribution is devoted to verifying the hypothesis that recently the precipitation has been more intense and significant shifts in seasonal incidence have occurred in particular regions in Slovakia. On the basis of the 60-year (1951-2010) meteorological observation series obtained from more than 20 synoptic stations, the analysis of trends and long-term variability of the days with thunderstorms and the accompanying precipitation for seasons was undertaken. Contribution also attempts to explain the main

Timing of climate variability and grassland productivity

PubMed Central

Craine, Joseph M.; Nippert, Jesse B.; Elmore, Andrew J.; Skibbe, Adam M.; Hutchinson, Stacy L.; Brunsell, Nathaniel A.

2012-01-01

Future climates are forecast to include greater precipitation variability and more frequent heat waves, but the degree to which the timing of climate variability impacts ecosystems is uncertain. In a temperate, humid grassland, we examined the seasonal impacts of climate variability on 27 y of grass productivity. Drought and high-intensity precipitation reduced grass productivity only during a 110-d period, whereas high temperatures reduced productivity only during 25 d in July. The effects of drought and heat waves declined over the season and had no detectable impact on grass productivity in August. If these patterns are general across ecosystems, predictions of ecosystem response to climate change will have to account not only for the magnitude of climate variability but also for its timing. PMID:22331914

Weather uncertainty versus climate change uncertainty in a short television weather broadcast

NASA Astrophysics Data System (ADS)

Witte, J.; Ward, B.; Maibach, E.

2011-12-01

For TV meteorologists talking about uncertainty in a two-minute forecast can be a real challenge. It can quickly open the way to viewer confusion. TV meteorologists understand the uncertainties of short term weather models and have different methods to convey the degrees of confidence to the viewing public. Visual examples are seen in the 7-day forecasts and the hurricane track forecasts. But does the public really understand a 60 percent chance of rain or the hurricane cone? Communication of climate model uncertainty is even more daunting. The viewing public can quickly switch to denial of solid science. A short review of the latest national survey of TV meteorologists by George Mason University and lessons learned from a series of climate change workshops with TV broadcasters provide valuable insights into effectively using visualizations and invoking multimedia-learning theories in weather forecasts to improve public understanding of climate change.

Short-term herbivory has long-term consequences in warmed and ambient high Arctic tundra

NASA Astrophysics Data System (ADS)

Little, Chelsea J.; Cutting, Helen; Alatalo, Juha; Cooper, Elisabeth

2017-02-01

Climate change is occurring across the world, with effects varying by ecosystem and region but already occurring quickly in high-latitude and high-altitude regions. Biotic interactions are important in determining ecosystem response to such changes, but few studies have been long-term in nature, especially in the High Arctic. Mesic tundra plots on Svalbard, Norway, were subjected to grazing at two different intensities by captive Barnacle geese from 2003-2005, in a factorial design with warming by Open Top Chambers. Warming manipulations were continued through 2014, when we measured vegetation structure and composition as well as growth and reproduction of three dominant species in the mesic meadow. Significantly more dead vascular plant material was found in warmed compared to ambient plots, regardless of grazing history, but in contrast to many short-term experiments no difference in the amount of living material was found. This has strong implications for nutrient and carbon cycling and could feed back into community productivity. Dominant species showed increased flowering in warmed plots, especially in those plots where grazing had been applied. However, this added sexual reproduction did not translate to substantial shifts in vegetative cover. Forbs and rushes increased slightly in warmed plots regardless of grazing, while the dominant shrub, Salix polaris, generally declined with effects dependent on grazing, and the evergreen shrub Dryas octopetala declined with previous intensive grazing. There were no treatment effects on community diversity or evenness. Thus despite no changes in total live abundance, a typical short-term response to environmental conditions, we found pronounced changes in dead biomass indicating that tundra ecosystem processes respond to medium- to long-term changes in conditions caused by 12 seasons of summer warming. We suggest that while high arctic tundra plant communities are fairly resistant to current levels of climate warming

Limited influence of climate change mitigation on short-term glacier mass loss

NASA Astrophysics Data System (ADS)

Marzeion, Ben; Kaser, Georg; Maussion, Fabien; Champollion, Nicolas

2018-04-01

Glacier mass loss is a key contributor to sea-level change1,2, slope instability in high-mountain regions3,4 and the changing seasonality and volume of river flow5-7. Understanding the causes, mechanisms and time scales of glacier change is therefore paramount to identifying successful strategies for mitigation and adaptation. Here, we use temperature and precipitation fields from the Coupled Model Intercomparison Project Phase 5 output to force a glacier evolution model, quantifying mass responses to future climatic change. We find that contemporary glacier mass is in disequilibrium with the current climate, and 36 ± 8% mass loss is already committed in response to past greenhouse gas emissions. Consequently, mitigating future emissions will have only very limited influence on glacier mass change in the twenty-first century. No significant differences between 1.5 and 2 K warming scenarios are detectable in the sea-level contribution of glaciers accumulated within the twenty-first century. In the long-term, however, mitigation will exert strong control, suggesting that ambitious measures are necessary for the long-term preservation of glaciers.

Comparative study of different stochastic weather generators for long-term climate data simulation

USDA-ARS?s Scientific Manuscript database

Climate is one of the single most important factors affecting watershed ecosystems and water resources. The effect of climate variability and change has been studied extensively in some places; in many places, however, assessments are hampered by limited availability of long term continuous climate ...

Climate Variability and Weather Extremes: Model-Simulated and Historical Data. Chapter 9

NASA Technical Reports Server (NTRS)

Schubert, Siegfried D.; Lim, Young-Kwon

2012-01-01

Extremes in weather and climate encompass a wide array of phenomena including tropical storms, mesoscale convective systems, snowstorms, floods, heat waves, and drought. Understanding how such extremes might change in the future requires an understanding of their past behavior including their connections to large-scale climate variability and trends. Previous studies suggest that the most robust findings concerning changes in short-term extremes are those that can be most directly (though not completely) tied to the increase in the global mean temperatures. These include the findings that (IPCC 2007): There has been a widespread reduction in the number of frost days in mid-latitude regions in recent decades, an increase in the number of warm extremes, particularly warm nights, and a reduction in the number of cold extremes, particularly cold nights. For North America in particular (CCSP SAP 3.3, 2008): There are fewer unusually cold days during the last few decades. The last 10 years have seen a lower number of severe cold waves than for any other 10-year period in the historical record that dates back to 1895. There has been a decrease in the number of frost days and a lengthening of the frost-free season, particularly in the western part of North America. Other aspects of extremes such as the changes in storminess have a less clear signature of long term change, with considerable interannual, and decadal variability that can obscure any climate change signal. Nevertheless, regarding extratropical storms (CCSP SAP 3.3, 2008): The balance of evidence suggests that there has been a northward shift in the tracks of strong low pressure systems (storms) in both the North Atlantic and North Pacific basins. For North America: Regional analyses suggest that there has been a decrease in snowstorms in the South and lower Midwest of the United States, and an increase in snowstorms in the upper Midwest and Northeast. Despite the progress already made, our understanding of the

Simulation of long-term influence from technical systems on permafrost with various short-scale and hourly operation modes in Arctic region

NASA Astrophysics Data System (ADS)

Vaganova, N. A.

2017-12-01

Technogenic and climatic influences have a significant impact on the degradation of permafrost. Long-term forecasts of such changes during long-time periods have to be taken into account in the oil and gas and construction industries in view to development the Arctic and Subarctic regions. There are considered constantly operating technical systems (for example, oil and gas wells) that affect changes in permafrost, as well as the technical systems that have a short-term impact on permafrost (for example, flare systems for emergency flaring of associated gas). The second type of technical systems is rather complex for simulation, since it is required to reserve both short and long-scales in computations with variable time steps describing the complex technological processes. The main attention is paid to the simulation of long-term influence on the permafrost from the second type of the technical systems.

Phenological responses of Icelandic subarctic grasslands to short-term and long-term natural soil warming.

PubMed

Leblans, Niki I W; Sigurdsson, Bjarni D; Vicca, Sara; Fu, Yongshuo; Penuelas, Josep; Janssens, Ivan A

2017-11-01

The phenology of vegetation, particularly the length of the growing season (LOS; i.e., the period from greenup to senescence), is highly sensitive to climate change, which could imply potent feedbacks to the climate system, for example, by altering the ecosystem carbon (C) balance. In recent decades, the largest extensions of LOS have been reported at high northern latitudes, but further warming-induced LOS extensions may be constrained by too short photoperiod or unfulfilled chilling requirements. Here, we studied subarctic grasslands, which cover a vast area and contain large C stocks, but for which LOS changes under further warming are highly uncertain. We measured LOS extensions of Icelandic subarctic grasslands along natural geothermal soil warming gradients of different age (short term, where the measurements started after 5 years of warming and long term, i.e., warmed since ≥50 years) using ground-level measurements of normalized difference vegetation index. We found that LOS linearly extended with on average 2.1 days per °C soil warming up to the highest soil warming levels (ca. +10°C) and that LOS had the potential to extend at least 1 month. This indicates that the warming impact on LOS in these subarctic grasslands will likely not saturate in the near future. A similar response to short- and long-term warming indicated a strong physiological control of the phenological response of the subarctic grasslands to warming and suggested that genetic adaptations and community changes were likely of minor importance. We conclude that the warming-driven extension of the LOSs of these subarctic grasslands did not saturate up to +10°C warming, and hence that growing seasons of high-latitude grasslands are likely to continue lengthening with future warming (unless genetic adaptations or species shifts do occur). This persistence of the warming-induced extension of LOS has important implications for the C-sink potential of subarctic grasslands under climate

Climate Variability and Sugarcane Yield in Louisiana.

NASA Astrophysics Data System (ADS)

Greenland, David

2005-11-01

This paper seeks to understand the role that climate variability has on annual yield of sugarcane in Louisiana. Unique features of sugarcane growth in Louisiana and nonclimatic, yield-influencing factors make this goal an interesting and challenging one. Several methods of seeking and establishing the relations between yield and climate variables are employed. First, yield climate relations were investigated at a single research station where crop variety and growing conditions could be held constant and yield relations could be established between a predominant older crop variety and a newer one. Interviews with crop experts and a literature survey were used to identify potential climatic factors that control yield. A statistical analysis was performed using statewide yield data from the American Sugar Cane League from 1963 to 2002 and a climate database. Yield values for later years were adjusted downward to form an adjusted yield dataset. The climate database was principally constructed from daily and monthly values of maximum and minimum temperature and daily and monthly total precipitation for six cooperative weather-reporting stations representative of the area of sugarcane production. The influence of 74 different, though not independent, climate-related variables on sugarcane yield was investigated. The fact that a climate signal exists is demonstrated by comparing mean values of the climate variables corresponding to the upper and lower third of adjusted yield values. Most of these mean-value differences show an intuitively plausible difference between the high- and low-yield years. The difference between means of the climate variables for years corresponding to the upper and lower third of annual yield values for 13 of the variables is statistically significant at or above the 90% level. A correlation matrix was used to identify the variables that had the largest influence on annual yield. Four variables [called here critical climatic variables (CCV

Future Warming Patterns Linked to Today's Climate Variability.

PubMed

Dai, Aiguo

2016-01-11

The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models' ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21(st) century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today's climate, with areas of larger variations during 1950-1979 having more GHG-induced warming in the 21(st) century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950-2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21(st) century in models and in the real world. They support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.

Investigating annually-resovled natural climate variability during MIS 11 using lacustrine records

NASA Astrophysics Data System (ADS)

Tye, G. J.; Palmer, A. P.; Candy, I.; Coxon, P.; Hardiman, M.

2012-04-01

Marine isotope stage 11 (MIS 11, ca 410,000 yrs BP) is considered to be one of the best analogues for current and future climate change due to the similarity of orbital forcing patterns during these two interglacials. Marine and ice-core records suggest that MIS 11 was a particularly long interglacial, characterised by stable climates. The investigation of high-resolution climate records from MIS 11 can, therefore, allow us to understand how the climate of a Holocene-like interglacial might evolve in the absence of anthropogenic modification. MIS 11 sediments preserved in the palaeolake basin at Marks Tey, eastern England, offer the potential for such a study as they are considered to be annually-laminated (varved) throughout a large part of the interglacial (Turner, 1970, 1975). The lamination sets appear to be comprised, primarily, of three regularly occurring laminae types; 1) authigenic carbonate, 2) diatom blooms, and 3) organic detritus, although there appears to be some variability in the microfacies of these laminations. The carbonate laminations are the key to the study of climate variability during MIS 11, as they represent authigenic carbonate precipitation, consistent with temperature/biologically driven changes in lake chemistry during the summer months. Oxygen isotopic analysis of the carbonate therefore gives a proxy for summer temperature. A period of key interest in the MIS 11 sequence at Marks Tey occurs during the early part of the interglacial, where there is a short-lived increase in grass pollen relative to tree pollen, termed the Non-Arboreal Pollen Zone (NAPZ). The cause of this shift in pollen has been subject to debate, with natural wildfire (Turner, 1970) or climatic deterioration (e.g. Kelly, 1964) being suggested as possible forcing mechanisms. In this study, as well as discussing the main characteristics of the MIS 11 sequence at Marks Tey, we will focus on the sedimentary, micromorphological and geochemical record of the NAPZ. In

A glimpse at short-term controls of evapotranspiration along the southern slopes of Kilimanjaro.

PubMed

Detsch, Florian; Otte, Insa; Appelhans, Tim; Nauss, Thomas

2017-08-23

Future climate characteristics of the southern Kilimanjaro region, Tanzania, are mainly determined by local land-use and global climate change. Reinforcing increasing dryness throughout the twentieth century, ongoing land transformation processes emphasize the need for a proper understanding of the regional-scale water budget and possible implications on related ecosystem functioning and services. Here, we present an analysis of scintillometer-based evapotranspiration (ET) covering seven distinct habitat types across a massive climate gradient from the colline savanna woodlands to the upper-mountain Helichrysum zone (940 to 3960 m.a.s.l.). Random forest-based mean variable importance indicates an outstanding significance of net radiation (R net ) on the observed ET across all elevation levels. Accordingly, topography and frequent cloud/fog events have a dampening effect at high elevations, whereas no such constraints affect the energy and moisture-rich submontane coffee/grassland level. By contrast, long-term moisture availability is likely to impose restrictions upon evapotranspirative net water loss in savanna, which particularly applies to the pronounced dry season. At plot scale, ET can thereby be approximated reasonably using R net , soil heat flux, and to a lesser degree, vapor pressure deficit and rainfall as predictor variables (R 2 0.59 to 1.00). While multivariate regression based on pooled meteorological data from all plots proves itself useful for predicting hourly ET rates across a broader range of ecosystems (R 2 = 0.71), additional gains in explained variance can be achieved when vegetation characteristics as seen from the NDVI are considered (R 2 = 0.87). To sum up, our results indicate that valuable insights into land cover-specific ET dynamics, including underlying drivers, may be derived even from explicitly short-term measurements in an ecologically highly diverse landscape.

The prediction of the impact of climatic factors on short-term electric power load based on the big data of smart city

NASA Astrophysics Data System (ADS)

Qiu, Yunfei; Li, Xizhong; Zheng, Wei; Hu, Qinghe; Wei, Zhanmeng; Yue, Yaqin

2017-08-01

The climate changes have great impact on the residents’ electricity consumption, so the study on the impact of climatic factors on electric power load is of significance. In this paper, the effects of the data of temperature, rainfall and wind of smart city on short-term power load is studied to predict power load. The authors studied the relation between power load and daily temperature, rainfall and wind in the 31 days of January of one year. In the research, the authors used the Matlab neural network toolbox to establish the combinational forecasting model. The authors trained the original input data continuously to get the internal rules inside the data and used the rules to predict the daily power load in the next January. The prediction method relies on the accuracy of weather forecasting. If the weather forecasting is different from the actual weather, we need to correct the climatic factors to ensure accurate prediction.

Climate Factors as Important Determinants of Dengue Incidence in Curaçao.

PubMed

Limper, M; Thai, K T D; Gerstenbluth, I; Osterhaus, A D M E; Duits, A J; van Gorp, E C M

2016-03-01

Macro- and microclimates may have variable impact on dengue incidence in different settings. We estimated the short-term impact and delayed effects of climate variables on dengue morbidity in Curaçao. Monthly dengue incidence data from 1999 to 2009 were included to estimate the short-term influences of climate variables by employing wavelet analysis, generalized additive models (GAM) and distributed lag nonlinear models (DLNM) on rainfall, temperature and relative humidity in relation to dengue incidence. Dengue incidence showed a significant irregular 4-year multi-annual cycle associated with climate variables. Based on GAM, temperature showed a U-shape, while humidity and rainfall exhibited a dome-shaped association, suggesting that deviation from mean temperature increases and deviation from mean humidity and rainfall decreases dengue incidence, respectively. Rainfall was associated with an immediate increase in dengue incidence of 4.1% (95% CI: 2.2-8.1%) after a 10-mm increase, with a maximum increase of 6.5% (95% CI: 3.2-10.0%) after 1.5 month lag. A 1 °C decrease of mean temperature was associated with a RR of 17.4% (95% CI: 11.2-27.0%); the effect was inversed for a 1°C increase of mean temperature (RR= 0.457, 95% CI: 0.278-0.752). Climate variables are important determinants of dengue incidence and provide insight into its short-term effects. An increase in mean temperature was associated with lower dengue incidence, whereas lower temperatures were associated with higher dengue incidence. © 2015 Blackwell Verlag GmbH.

Catchments' hedging strategy on evapotranspiration for climatic variability

NASA Astrophysics Data System (ADS)

Ding, W.; Zhang, C.; Li, Y.; Tang, Y.; Wang, D.; Xu, B.

2017-12-01

Hydrologic responses to climate variability and change are important for human society. Here we test the hypothesis that natural catchments utilize hedging strategies for evapotranspiration and water storage carryover with uncertain future precipitation. The hedging strategy for evapotranspiration in catchments under different levels of water availability is analytically derived from the economic perspective. It is found that there exists hedging between evapotranspiration for current and future only with a portion of water availability. Observation data sets of 160 catchments in the United States covering the period from 1983 to 2003 demonstrate the existence of hedging in catchment hydrology and validate the proposed hedging strategies. We also find that more water is allocated to carryover storage for hedging against the future evapotranspiration risk in the catchments with larger aridity indexes or with larger uncertainty in future precipitation, i.e., long-term climate and precipitation variability control the degree of hedging.

Increased Short-Term Variability of the QT Interval in Professional Soccer Players: Possible Implications for Arrhythmia Prediction

PubMed Central

Lengyel, Csaba; Orosz, Andrea; Hegyi, Péter; Komka, Zsolt; Udvardy, Anna; Bosnyák, Edit; Trájer, Emese; Pavlik, Gábor; Tóth, Miklós; Wittmann, Tibor; Papp, Julius Gy.; Varró, András; Baczkó, István

2011-01-01

Background Sudden cardiac death in competitive athletes is rare but it is significantly more frequent than in the normal population. The exact cause is seldom established and is mostly attributed to ventricular fibrillation. Myocardial hypertrophy and slow heart rate, both characteristic changes in top athletes in response to physical conditioning, could be associated with increased propensity for ventricular arrhythmias. We investigated conventional ECG parameters and temporal short-term beat-to-beat variability of repolarization (STVQT), a presumptive novel parameter for arrhythmia prediction, in professional soccer players. Methods Five-minute 12-lead electrocardiograms were recorded from professional soccer players (n = 76, all males, age 22.0±0.61 years) and age-matched healthy volunteers who do not participate in competitive sports (n = 76, all males, age 22.0±0.54 years). The ECGs were digitized and evaluated off-line. The temporal instability of beat-to-beat heart rate and repolarization were characterized by the calculation of short-term variability of the RR and QT intervals. Results Heart rate was significantly lower in professional soccer players at rest (61±1.2 vs. 72±1.5/min in controls). The QT interval was prolonged in players at rest (419±3.1 vs. 390±3.6 in controls, p<0.001). QTc was significantly longer in players compared to controls calculated with Fridericia and Hodges correction formulas. Importantly, STVQT was significantly higher in players both at rest and immediately after the game compared to controls (4.8±0.14 and 4.3±0.14 vs. 3.5±0.10 ms, both p<0.001, respectively). Conclusions STVQT is significantly higher in professional soccer players compared to age-matched controls, however, further studies are needed to relate this finding to increased arrhythmia propensity in this population. PMID:21526208

Climate variability decreases species richness and community stability in a temperate grassland.

PubMed

Zhang, Yunhai; Loreau, Michel; He, Nianpeng; Wang, Junbang; Pan, Qingmin; Bai, Yongfei; Han, Xingguo

2018-06-26

Climate change involves modifications in both the mean and the variability of temperature and precipitation. According to global warming projections, both the magnitude and the frequency of extreme weather events are increasing, thereby increasing climate variability. The previous studies have reported that climate warming tends to decrease biodiversity and the temporal stability of community primary productivity (i.e., community stability), but the effects of the variability of temperature and precipitation on biodiversity, community stability, and their relationship have not been clearly explored. We used a long-term (from 1982 to 2014) field data set from a temperate grassland in northern China to explore the effects of the variability of mean temperature and total precipitation on species richness, community stability, and their relationship. Results showed that species richness promoted community stability through increases in asynchronous dynamics across species (i.e., species asynchrony). Both species richness and species asynchrony were positively associated with the residuals of community stability after controlling for its dependence on the variability of mean temperature and total precipitation. Furthermore, the variability of mean temperature reduced species richness, while the variability of total precipitation decreased species asynchrony and community stability. Overall, the present study revealed that species richness and species asynchrony promoted community stability, but increased climate variability may erode these positive effects and thereby threaten community stability.

Long-term associative learning predicts verbal short-term memory performance.

PubMed

Jones, Gary; Macken, Bill

2018-02-01

Studies using tests such as digit span and nonword repetition have implicated short-term memory across a range of developmental domains. Such tests ostensibly assess specialized processes for the short-term manipulation and maintenance of information that are often argued to enable long-term learning. However, there is considerable evidence for an influence of long-term linguistic learning on performance in short-term memory tasks that brings into question the role of a specialized short-term memory system separate from long-term knowledge. Using natural language corpora, we show experimentally and computationally that performance on three widely used measures of short-term memory (digit span, nonword repetition, and sentence recall) can be predicted from simple associative learning operating on the linguistic environment to which a typical child may have been exposed. The findings support the broad view that short-term verbal memory performance reflects the application of long-term language knowledge to the experimental setting.

On the dynamic forcing of short-term climate fluctuations by feedback mechanisms

NASA Technical Reports Server (NTRS)

Reiter, E. R.

1979-01-01

Various internal feedback mechanisms in the ocean atmosphere system were studied. A variability pattern of sea surface temperature with a quasibiennial oscillation (QBO) was detected off the coast of Senegal, in the Gulf of Guinea and even in the Gulf Stream as it leaves the North American continental shelf. Possible physical connections between some of these QBO's were pointed out by a hypothetical feedback model. Interaction of a QBO with the annual cycle may lead to beating frequencies resembling climatic trends of a duration of several years.

Effects of climate and fire on short-term vegetation recovery in the boreal larch forests of Northeastern China.

PubMed

Liu, Zhihua

2016-11-18

Understanding the influence of climate variability and fire characteristics in shaping postfire vegetation recovery will help to predict future ecosystem trajectories in boreal forests. In this study, I asked: (1) which remotely-sensed vegetation index (VI) is a good proxy for vegetation recovery? and (2) what are the relative influences of climate and fire in controlling postfire vegetation recovery in a Siberian larch forest, a globally important but poorly understood ecosystem type? Analysis showed that the shortwave infrared (SWIR) VI is a good indicator of postfire vegetation recovery in boreal larch forests. A boosted regression tree analysis showed that postfire recovery was collectively controlled by processes that controlled seed availability, as well as by site conditions and climate variability. Fire severity and its spatial variability played a dominant role in determining vegetation recovery, indicating seed availability as the primary mechanism affecting postfire forest resilience. Environmental and immediate postfire climatic conditions appear to be less important, but interact strongly with fire severity to influence postfire recovery. If future warming and fire regimes manifest as expected in this region, seed limitation and climate-induced regeneration failure will become more prevalent and severe, which may cause forests to shift to alternative stable states.

Effects of climate and fire on short-term vegetation recovery in the boreal larch forests of Northeastern China

PubMed Central

Liu, Zhihua

2016-01-01

Understanding the influence of climate variability and fire characteristics in shaping postfire vegetation recovery will help to predict future ecosystem trajectories in boreal forests. In this study, I asked: (1) which remotely-sensed vegetation index (VI) is a good proxy for vegetation recovery? and (2) what are the relative influences of climate and fire in controlling postfire vegetation recovery in a Siberian larch forest, a globally important but poorly understood ecosystem type? Analysis showed that the shortwave infrared (SWIR) VI is a good indicator of postfire vegetation recovery in boreal larch forests. A boosted regression tree analysis showed that postfire recovery was collectively controlled by processes that controlled seed availability, as well as by site conditions and climate variability. Fire severity and its spatial variability played a dominant role in determining vegetation recovery, indicating seed availability as the primary mechanism affecting postfire forest resilience. Environmental and immediate postfire climatic conditions appear to be less important, but interact strongly with fire severity to influence postfire recovery. If future warming and fire regimes manifest as expected in this region, seed limitation and climate-induced regeneration failure will become more prevalent and severe, which may cause forests to shift to alternative stable states. PMID:27857204

Periodization effects during short-term resistance training with equated exercise variables in females.

PubMed

Pelzer, Thiemo; Ullrich, Boris; Pfeiffer, Mark

2017-03-01

During resistance training, volume and load can be altered either gradually (traditional periodization: TP) or with frequent changes between subsequent sessions (daily undulating periodization: DUP). We hypothesized that the periodization model employed would not impact upon training-induced adaptations when exercise variables are equated. Nineteen females (22.0 years, moderate resistance training experience of 27.9 months) performed 6 weeks of knee extensor training with 3 weekly sessions exercising one leg using TP and the contralateral leg using DUP. Training load varied between 40, 60, and 80% of one repetition maximum (1RM). Volume, range of motion, and time under tension were equated for each leg with a biofeedback software. Dynamometry, surface EMG and ultrasonography were used to determine temporal changes of knee extensor maximum voluntary strength (MVC), neural drive of the M. quadriceps femoris (QF) and vastus lateralis (VL) and rectus femoris (RF) muscle architecture. Significant (P < 0.05) gains for isometric (TP 15%, DUP 13%) and isokinetic-concentric (TP 8%, DUP 10%) MVC and knee extensor 1RM (TP 18%, DUP 24%) occurred post training. VL and RF-muscle thickness showed significant (P < 0.05) increases ranging from 12 to 20% for TP and from 13 to 19% for DUP. Furthermore, significant (P < 0.05) increases in VL-pennation angle and VL-fascicle length occurred in both legs while QF EMG remained unchanged. No significant temporal differences were found between both models, displaying similar small to large effect sizes. Periodization is no adaptation trigger during short-term resistance training with equated exercise variables.

Climate Variability Impacts on Watershed Nutrient Delivery and Reservoir Production

NASA Astrophysics Data System (ADS)

White, J. D.; Prochnow, S. J.; Zygo, L. M.; Byars, B. W.

2005-05-01

Reservoirs in agricultural dominated watersheds tend to exhibit pulse-system behavior especially if located in climates dominated by summer convective precipitation inputs. Concentration and bulk mass of nutrient and sediment inputs into reservoir systems vary in terms of timing and magnitude of delivery from watershed sources to reservoirs under these climate conditions. Reservoir management often focuses on long-term average inputs without considering short and long-term impacts of variation in loading. In this study we modeled a watershed-reservoir system to assess how climate variability affects reservoir primary production through shifts in external loading and internal recycling of limiting nutrients. The Bosque watershed encompasses 423,824 ha in central Texas which delivers water to Lake Waco, a 2900 ha reservoir that is the primary water source for the city of Waco and surrounding areas. Utilizing the Soil Water Assessment Tool for the watershed and river simulations and the CE-Qual-2e model for the reservoir, hydrologic and nutrient dynamics were simulated for a 10 year period encompassing two ENSO cycles. The models were calibrated based on point measurement of water quality attributes for a two year time period. Results indicated that watershed delivery of nutrients was affected by the presence and density of small flood-control structure in the watershed. However, considerable nitrogen and phosphorus loadings were derived from soils in the upper watershed which have had long-term waste-application from concentrated animal feeding operations. During El Niño years, nutrient and sediment loads increased by 3 times above non-El Niño years. The simulated response within the reservoir to these nutrient and sediment loads had both direct and indirect. Productivity evaluated from chlorophyll a and algal biomass increased under El Niño conditions, however species composition shifts were found with an increase in cyanobacteria dominance. In non-El Niño years

Projected Applications of a ``Climate in a Box'' Computing System at the NASA Short-term Prediction Research and Transition (SPoRT) Center

NASA Astrophysics Data System (ADS)

Jedlovec, G.; Molthan, A.; Zavodsky, B.; Case, J.; Lafontaine, F.

2010-12-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique observations and research capabilities to the operational weather community, with a goal of improving short-term forecasts on a regional scale. Advances in research computing have lead to “Climate in a Box” systems, with hardware configurations capable of producing high resolution, near real-time weather forecasts, but with footprints, power, and cooling requirements that are comparable to desktop systems. The SPoRT Center has developed several capabilities for incorporating unique NASA research capabilities and observations with real-time weather forecasts. Planned utilization includes the development of a fully-cycled data assimilation system used to drive 36-48 hour forecasts produced by the NASA Unified version of the Weather Research and Forecasting (WRF) model (NU-WRF). The horsepower provided by the “Climate in a Box” system is expected to facilitate the assimilation of vertical profiles of temperature and moisture provided by the Atmospheric Infrared Sounder (AIRS) aboard the NASA Aqua satellite. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASA’s Aqua and Terra satellites provide high-resolution sea surface temperatures and vegetation characteristics. The development of MODIS normalized difference vegetation index (NVDI) composites for use within the NASA Land Information System (LIS) will assist in the characterization of vegetation, and subsequently the surface albedo and processes related to soil moisture. Through application of satellite simulators, NASA satellite instruments can be used to examine forecast model errors in cloud cover and other characteristics. Through the aforementioned application of the “Climate in a Box” system and NU-WRF capabilities, an end goal is the establishment of a real-time forecast system that fully integrates modeling and analysis capabilities developed

Projected Applications of a "Climate in a Box" Computing System at the NASA Short-Term Prediction Research and Transition (SPoRT) Center

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Molthan, Andrew L.; Zavodsky, Bradley; Case, Jonathan L.; LaFontaine, Frank J.

2010-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique observations and research capabilities to the operational weather community, with a goal of improving short-term forecasts on a regional scale. Advances in research computing have lead to "Climate in a Box" systems, with hardware configurations capable of producing high resolution, near real-time weather forecasts, but with footprints, power, and cooling requirements that are comparable to desktop systems. The SPoRT Center has developed several capabilities for incorporating unique NASA research capabilities and observations with real-time weather forecasts. Planned utilization includes the development of a fully-cycled data assimilation system used to drive 36-48 hour forecasts produced by the NASA Unified version of the Weather Research and Forecasting (WRF) model (NU-WRF). The horsepower provided by the "Climate in a Box" system is expected to facilitate the assimilation of vertical profiles of temperature and moisture provided by the Atmospheric Infrared Sounder (AIRS) aboard the NASA Aqua satellite. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASA s Aqua and Terra satellites provide high-resolution sea surface temperatures and vegetation characteristics. The development of MODIS normalized difference vegetation index (NVDI) composites for use within the NASA Land Information System (LIS) will assist in the characterization of vegetation, and subsequently the surface albedo and processes related to soil moisture. Through application of satellite simulators, NASA satellite instruments can be used to examine forecast model errors in cloud cover and other characteristics. Through the aforementioned application of the "Climate in a Box" system and NU-WRF capabilities, an end goal is the establishment of a real-time forecast system that fully integrates modeling and analysis capabilities developed within the NASA SPo

Applications of VIC for Climate Land Cover Change Imapacts

NASA Technical Reports Server (NTRS)

Markert, Kel

2017-01-01

Study focuses on the Lower Mekong Basin (LMB), the LMB is an economically and ecologically important region: (1) One of the largest exporters of rice and fish products, (2) Within top three most biodiverse river basins in the world. Natural climate variability plays an important role in water supply within the region: (1) Short-term climate variability (ENSO, MJO), (2) Long-term climate variability (climate change). Projections of climate change show there will be a decrease in water availability world wide which has implications for food security and ecology. Additional studies show there may be socioeconomic turmoil due to water wars and food security in developing regions such as the Mekong Basin. Southeast Asia has experienced major changes in land use and land cover from 1980 – 2000. Major economic reforms resulting in shift from subsistence farming to market-based agricultural production. Changes in land cover continue to occur which have an important role within the land surface aspect of hydrology.

Impacts of climate change and variability on European agriculture: results of inventory analysis in COST 734 countries.

PubMed

Orlandini, Simone; Nejedlik, Pavol; Eitzinger, Josef; Alexandrov, Vesselin; Toulios, Leonidas; Calanca, Pierluigi; Trnka, Miroslav; Olesen, Jørgen E

2008-12-01

Climate plays a fundamental role in agriculture because of to its influence on production. All processes are regulated by specific climatic requirements. Furthermore, European agriculture, based on highly developed farming techniques, is mainly oriented to high quality food production that is more susceptible to meteorological hazards. These hazards can modify environment-genotype interactions, which can affect the quality of production. The COST 734 Action (Impacts of Climate Change and Variability on European Agriculture), launched in 2006, is composed of 28 signature countries and is funded by the European Commission. The main objective of the Action is the evaluation of possible impacts arising from climate change and variability on agriculture and the assessment of critical thresholds for various European areas. The Action will concentrate on four different tasks: agroclimatic indices and simulation models, including review and assessment of tools used to relate climate and agricultural processes; evaluation of the current trends of agroclimatic indices and model outputs, including remote sensing; developing and assessing future regional and local scenarios of agroclimatic conditions; and risk assessment and foreseen impacts on agriculture. The work will be carried out by respective Working Groups. This paper presents the results of the analysis of the first phase of inventory activity. Specific questionnaires were disseminated among COST 734 countries to collect information on climate change analysis, studies, and impact at the European level. The results were discussed with respect to their spatial distribution in Europe and to identify possible common long- and short-term strategies for adaptation.

Long-term (in)stability of the climate-streamflow relationship

NASA Astrophysics Data System (ADS)

Saft, Margarita; Peel, Murray; Coxon, Gemma; Freer, Jim; Parajka, Juraj; Woods, Ross

2017-04-01

Land use changes have long been known to alter streamflow production for a given climatic input. Recently, extended shifts in climate were also shown to be capable of altering catchment internal functioning and streamflow production for a given climatic input. This study investigates the stability of climate-streamflow relationships in natural catchments in different regions of the world for the first time, using datasets of natural/reference catchments from Europe, US, and Australia. Changes in climate-streamflow relationships are investigated statistically on the interannual to interdecadal timescale and related to interdecadal climate variability. We compare the frequency and magnitude of shifts in climate-streamflow relationship between different regions, and discuss what any differences in shift frequency and magnitude might be related to. This study draws attention to the issues of catchment vulnerability to changes in external factors, catchment-climate co-evolution, and long-term catchment memory.

Fishing, fast growth and climate variability increase the risk of collapse

PubMed Central

Pinsky, Malin L.; Byler, David

2015-01-01

Species around the world have suffered collapses, and a key question is why some populations are more vulnerable than others. Traditional conservation biology and evidence from terrestrial species suggest that slow-growing populations are most at risk, but interactions between climate variability and harvest dynamics may alter or even reverse this pattern. Here, we test this hypothesis globally. We use boosted regression trees to analyse the influences of harvesting, species traits and climate variability on the risk of collapse (decline below a fixed threshold) across 154 marine fish populations around the world. The most important factor explaining collapses was the magnitude of overfishing, while the duration of overfishing best explained long-term depletion. However, fast growth was the next most important risk factor. Fast-growing populations and those in variable environments were especially sensitive to overfishing, and the risk of collapse was more than tripled for fast-growing when compared with slow-growing species that experienced overfishing. We found little evidence that, in the absence of overfishing, climate variability or fast growth rates alone drove population collapse over the last six decades. Expanding efforts to rapidly adjust harvest pressure to account for climate-driven lows in productivity could help to avoid future collapses, particularly among fast-growing species. PMID:26246548

Fishing, fast growth and climate variability increase the risk of collapse.

PubMed

Pinsky, Malin L; Byler, David

2015-08-22

Species around the world have suffered collapses, and a key question is why some populations are more vulnerable than others. Traditional conservation biology and evidence from terrestrial species suggest that slow-growing populations are most at risk, but interactions between climate variability and harvest dynamics may alter or even reverse this pattern. Here, we test this hypothesis globally. We use boosted regression trees to analyse the influences of harvesting, species traits and climate variability on the risk of collapse (decline below a fixed threshold) across 154 marine fish populations around the world. The most important factor explaining collapses was the magnitude of overfishing, while the duration of overfishing best explained long-term depletion. However, fast growth was the next most important risk factor. Fast-growing populations and those in variable environments were especially sensitive to overfishing, and the risk of collapse was more than tripled for fast-growing when compared with slow-growing species that experienced overfishing. We found little evidence that, in the absence of overfishing, climate variability or fast growth rates alone drove population collapse over the last six decades. Expanding efforts to rapidly adjust harvest pressure to account for climate-driven lows in productivity could help to avoid future collapses, particularly among fast-growing species. © 2015 The Author(s).

Climate variation explains a third of global crop yield variability

PubMed Central

Ray, Deepak K.; Gerber, James S.; MacDonald, Graham K.; West, Paul C.

2015-01-01

Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32–39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability. PMID:25609225

Intercomparison of model response and internal variability across climate model ensembles

NASA Astrophysics Data System (ADS)

Kumar, Devashish; Ganguly, Auroop R.

2017-10-01

Characterization of climate uncertainty at regional scales over near-term planning horizons (0-30 years) is crucial for climate adaptation. Climate internal variability (CIV) dominates climate uncertainty over decadal prediction horizons at stakeholders' scales (regional to local). In the literature, CIV has been characterized indirectly using projections of climate change from multi-model ensembles (MME) instead of directly using projections from multiple initial condition ensembles (MICE), primarily because adequate number of initial condition (IC) runs were not available for any climate model. Nevertheless, the recent availability of significant number of IC runs from one climate model allows for the first time to characterize CIV directly from climate model projections and perform a sensitivity analysis to study the dominance of CIV compared to model response variability (MRV). Here, we measure relative agreement (a dimensionless number with values ranging between 0 and 1, inclusive; a high value indicates less variability and vice versa) among MME and MICE and find that CIV is lower than MRV for all projection time horizons and spatial resolutions for precipitation and temperature. However, CIV exhibits greater dominance over MRV for seasonal and annual mean precipitation at higher latitudes where signals of climate change are expected to emerge sooner. Furthermore, precipitation exhibits large uncertainties and a rapid decline in relative agreement from global to continental, regional, or local scales for MICE compared to MME. The fractional contribution of uncertainty due to CIV is invariant for precipitation and decreases for temperature as lead time progresses towards the end of the century.

Ice_Sheets_CCI: Essential Climate Variables for the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Forsberg, R.; Sørensen, L. S.; Khan, A.; Aas, C.; Evansberget, D.; Adalsteinsdottir, G.; Mottram, R.; Andersen, S. B.; Ahlstrøm, A.; Dall, J.; Kusk, A.; Merryman, J.; Hvidberg, C.; Khvorostovsky, K.; Nagler, T.; Rott, H.; Scharrer, M.; Shepard, A.; Ticconi, F.; Engdahl, M.

2012-04-01

As part of the ESA Climate Change Initiative (www.esa-cci.org) a long-term project "ice_sheets_cci" started January 1, 2012, in addition to the existing 11 projects already generating Essential Climate Variables (ECV) for the Global Climate Observing System (GCOS). The "ice_sheets_cci" goal is to generate a consistent, long-term and timely set of key climate parameters for the Greenland ice sheet, to maximize the impact of European satellite data on climate research, from missions such as ERS, Envisat and the future Sentinel satellites. The climate parameters to be provided, at first in a research context, and in the longer perspective by a routine production system, would be grids of Greenland ice sheet elevation changes from radar altimetry, ice velocity from repeat-pass SAR data, as well as time series of marine-terminating glacier calving front locations and grounding lines for floating-front glaciers. The ice_sheets_cci project will involve a broad interaction of the relevant cryosphere and climate communities, first through user consultations and specifications, and later in 2012 optional participation in "best" algorithm selection activities, where prototype climate parameter variables for selected regions and time frames will be produced and validated using an objective set of criteria ("Round-Robin intercomparison"). This comparative algorithm selection activity will be completely open, and we invite all interested scientific groups with relevant experience to participate. The results of the "Round Robin" exercise will form the algorithmic basis for the future ECV production system. First prototype results will be generated and validated by early 2014. The poster will show the planned outline of the project and some early prototype results.

Impacts of short-term heatwaves on sun-induced chlorophyll fluorescence(SiF) in temperate tree species

NASA Astrophysics Data System (ADS)

Wang, F.; Gu, L.; Guha, A.; Han, J.; Warren, J.

2017-12-01

The current projections for global climate change forecast an increase in the intensity and frequency of extreme climatic events, such as droughts and short-term heat waves. Understanding the effects of short-term heat wave on photosynthesis process is of critical importance to predict global impacts of extreme weather event on vegetation. The diurnal and seasonal characteristics of SIF emitted from natural vegetation, e.g., forest and crop, have been studied at the ecosystem-scale, regional-scale and global-scale. However, the detailed response of SIF from different plant species under extremely weather event, especially short-term heat wave, have not been reported. The purpose of this study was to study the response of solar-induced chlorophyll fluorescence, gas exchange and continuous fluorescence at leaf scale for different temperate tree species. The short-term heatwave experiment was conducted using plant growth chamber (CMP6050, Conviron Inc., Canada). We developed an advanced spectral fitting method to obtain the plant SIF in the plant growth chamber. We compared SIF variation among different wavelength and chlorophyll difference among four temperate tree species. The diurnal variation of SIF signals at leaf-scales for temperate tree species are different under heat stress. The SIF response at leaf-scales and their difference for four temperate tree species are different during a cycle of short-term heatwave stress. We infer that SIF be used as a measure of heat tolerance for temperate tree species.

The contrasting effects of short-term climate change on the early recruitment of tree species.

PubMed

Ibáñez, Inés; Katz, Daniel S W; Lee, Benjamin R

2017-07-01

Predictions of plant responses to climate change are frequently based on organisms' presence in warmer locations, which are then assumed to reflect future performance in cooler areas. However, as plant life stages may be affected differently by environmental changes, there is little empirical evidence that this approach provides reliable estimates of short-term responses to global warming. Under this premise, we analyzed 8 years of early recruitment data, seed production and seedling establishment and survival, collected for two tree species at two latitudes. We quantified recruitment to a wide range of environmental conditions, temperature, soil moisture and light, and simulated recruitment under two forecasted climatic scenarios. Annual demographic transitions were affected by the particular conditions taking place during their onset, but the effects of similar environmental shifts differed among the recruitment stages; seed production was higher in warmer years, while seedling establishment and survival peaked during cold years. Within a species, these effects also varied between latitudes; increasing temperatures at the southern location will have stronger detrimental effects on recruitment than similar changes at the northern locations. Our simulations illustrate that warmer temperatures may increase seed production, but they will have a negative effect on establishment and survival. When the three early recruitment processes were simultaneously considered, simulations showed little change in recruitment dynamics at the northern site and a slight decrease at the southern site. It is only when we considered these three stages that we were able to assess likely changes in early recruitment under the predicted conditions.

Improved water allocation utilizing probabilistic climate forecasts: Short-term water contracts in a risk management framework

NASA Astrophysics Data System (ADS)

Sankarasubramanian, A.; Lall, Upmanu; Souza Filho, Francisco Assis; Sharma, Ashish

2009-11-01

Probabilistic, seasonal to interannual streamflow forecasts are becoming increasingly available as the ability to model climate teleconnections is improving. However, water managers and practitioners have been slow to adopt such products, citing concerns with forecast skill. Essentially, a management risk is perceived in "gambling" with operations using a probabilistic forecast, while a system failure upon following existing operating policies is "protected" by the official rules or guidebook. In the presence of a prescribed system of prior allocation of releases under different storage or water availability conditions, the manager has little incentive to change. Innovation in allocation and operation is hence key to improved risk management using such forecasts. A participatory water allocation process that can effectively use probabilistic forecasts as part of an adaptive management strategy is introduced here. Users can express their demand for water through statements that cover the quantity needed at a particular reliability, the temporal distribution of the "allocation," the associated willingness to pay, and compensation in the event of contract nonperformance. The water manager then assesses feasible allocations using the probabilistic forecast that try to meet these criteria across all users. An iterative process between users and water manager could be used to formalize a set of short-term contracts that represent the resulting prioritized water allocation strategy over the operating period for which the forecast was issued. These contracts can be used to allocate water each year/season beyond long-term contracts that may have precedence. Thus, integrated supply and demand management can be achieved. In this paper, a single period multiuser optimization model that can support such an allocation process is presented. The application of this conceptual model is explored using data for the Jaguaribe Metropolitan Hydro System in Ceara, Brazil. The performance

Interannual and spatial variability of maple syrup yield as related to climatic factors

PubMed Central

Houle, Daniel

2014-01-01

Sugar maple syrup production is an important economic activity for eastern Canada and the northeastern United States. Since annual variations in syrup yield have been related to climate, there are concerns about the impacts of climatic change on the industry in the upcoming decades. Although the temporal variability of syrup yield has been studied for specific sites on different time scales or for large regions, a model capable of accounting for both temporal and regional differences in yield is still lacking. In the present study, we studied the factors responsible for interregional and interannual variability in maple syrup yield over the 2001–2012 period, by combining the data from 8 Quebec regions (Canada) and 10 U.S. states. The resulting model explained 44.5% of the variability in yield. It includes the effect of climatic conditions that precede the sapflow season (variables from the previous growing season and winter), the effect of climatic conditions during the current sapflow season, and terms accounting for intercountry and temporal variability. Optimal conditions for maple syrup production appear to be spatially restricted by less favourable climate conditions occurring during the growing season in the north, and in the south, by the warmer winter and earlier spring conditions. This suggests that climate change may favor maple syrup production northwards, while southern regions are more likely to be negatively affected by adverse spring conditions. PMID:24949244

Impact of Land Model Depth on Long Term Climate Variability and Change.

NASA Astrophysics Data System (ADS)

Gonzalez-Rouco, J. F.; García-Bustamante, E.; Hagemann, S.; Lorentz, S.; Jungclaus, J.; de Vrese, P.; Melo, C.; Navarro, J.; Steinert, N.

2017-12-01

The available evidence indicates that the simulation of subsurface thermodynamics in current General Circulation Models (GCMs) is not accurate enough due to the land-surface model imposing a zero heat flux boundary condition that is too close to the surface. Shallow land model components distort the amplitude and phase of the heat propagation in the subsurface with implications for energy storage and land-air interactions. Off line land surface model experiments forced with GCM climate change simulations and comparison with borehole temperature profiles indicate there is a large reduction of the energy storage of the soil using the typical shallow land models included in most GCMs. However, the impact of increasing the depth of the soil model in `on-line' GCM simulations of climate variability or climate change has not yet been systematically explored. The JSBACH land surface model has been used in stand alone mode, driven by outputs of the MPIESM to assess the impacts of progressively increasing the depth of the soil model. In a first stage, preindustrial control simulations are developed increasing the lower depth of the zero flux bottom boundary condition placed for temperature at the base of the fifth model layer (9.83 m) down to 294.6 m (layer 9), thus allowing for the bottom layers to reach equilibrium. Starting from piControl conditions, historical and scenario simulations have been performed since 1850 yr. The impact of increasing depths on the subsurface layer temperatures is analysed as well as the amounts of energy involved. This is done also considering permafrost processes (freezing and thawing). An evaluation on the influence of deepening the bottom boundary on the simulation of low frequency variability and temperature trends is provided.

Ordered short-term memory differs in signers and speakers: Implications for models of short-term memory

PubMed Central

Bavelier, Daphne; Newport, Elissa L.; Hall, Matt; Supalla, Ted; Boutla, Mrim

2008-01-01

Capacity limits in linguistic short-term memory (STM) are typically measured with forward span tasks in which participants are asked to recall lists of words in the order presented. Using such tasks, native signers of American Sign Language (ASL) exhibit smaller spans than native speakers (Boutla, Supalla, Newport, & Bavelier, 2004). Here, we test the hypothesis that this population difference reflects differences in the way speakers and signers maintain temporal order information in short-term memory. We show that native signers differ from speakers on measures of short-term memory that require maintenance of temporal order of the tested materials, but not on those in which temporal order is not required. In addition, we show that, in a recall task with free order, bilingual subjects are more likely to recall in temporal order when using English than ASL. We conclude that speakers and signers do share common short-term memory processes. However, whereas short-term memory for spoken English is predominantly organized in terms of temporal order, we argue that this dimension does not play as great a role in signers’ short-term memory. Other factors that may affect STM processes in signers are discussed. PMID:18083155

The role of internal climate variability for interpreting climate change scenarios

NASA Astrophysics Data System (ADS)

Maraun, Douglas

2013-04-01

When communicating information on climate change, the use of multi-model ensembles has been advocated to sample uncertainties over a range as wide as possible. To meet the demand for easily accessible results, the ensemble is often summarised by its multi-model mean signal. In rare cases, additional uncertainty measures are given to avoid loosing all information on the ensemble spread, e.g., the highest and lowest projected values. Such approaches, however, disregard the fundamentally different nature of the different types of uncertainties and might cause wrong interpretations and subsequently wrong decisions for adaptation. Whereas scenario and climate model uncertainties are of epistemic nature, i.e., caused by an in principle reducible lack of knowledge, uncertainties due to internal climate variability are aleatory, i.e., inherently stochastic and irreducible. As wisely stated in the proverb "climate is what you expect, weather is what you get", a specific region will experience one stochastic realisation of the climate system, but never exactly the expected climate change signal as given by a multi model mean. Depending on the meteorological variable, region and lead time, the signal might be strong or weak compared to the stochastic component. In cases of a low signal-to-noise ratio, even if the climate change signal is a well defined trend, no trends or even opposite trends might be experienced. Here I propose to use the time of emergence (TOE) to quantify and communicate when climate change trends will exceed the internal variability. The TOE provides a useful measure for end users to assess the time horizon for implementing adaptation measures. Furthermore, internal variability is scale dependent - the more local the scale, the stronger the influence of internal climate variability. Thus investigating the TOE as a function of spatial scale could help to assess the required spatial scale for implementing adaptation measures. I exemplify this proposal with

Long-Term Climate Forcing in Loggerhead Sea Turtle Nesting

PubMed Central

Van Houtan, Kyle S.; Halley, John M.

2011-01-01

The long-term variability of marine turtle populations remains poorly understood, limiting science and management. Here we use basin-scale climate indices and regional surface temperatures to estimate loggerhead sea turtle (Caretta caretta) nesting at a variety of spatial and temporal scales. Borrowing from fisheries research, our models investigate how oceanographic processes influence juvenile recruitment and regulate population dynamics. This novel approach finds local populations in the North Pacific and Northwest Atlantic are regionally synchronized and strongly correlated to ocean conditions—such that climate models alone explain up to 88% of the observed changes over the past several decades. In addition to its performance, climate-based modeling also provides mechanistic forecasts of historical and future population changes. Hindcasts in both regions indicate climatic conditions may have been a factor in recent declines, but future forecasts are mixed. Available climatic data suggests the Pacific population will be significantly reduced by 2040, but indicates the Atlantic population may increase substantially. These results do not exonerate anthropogenic impacts, but highlight the significance of bottom-up oceanographic processes to marine organisms. Future studies should consider environmental baselines in assessments of marine turtle population variability and persistence. PMID:21589639

Long-term climate forcing in loggerhead sea turtle nesting.

PubMed

Van Houtan, Kyle S; Halley, John M

2011-04-27

The long-term variability of marine turtle populations remains poorly understood, limiting science and management. Here we use basin-scale climate indices and regional surface temperatures to estimate loggerhead sea turtle (Caretta caretta) nesting at a variety of spatial and temporal scales. Borrowing from fisheries research, our models investigate how oceanographic processes influence juvenile recruitment and regulate population dynamics. This novel approach finds local populations in the North Pacific and Northwest Atlantic are regionally synchronized and strongly correlated to ocean conditions--such that climate models alone explain up to 88% of the observed changes over the past several decades. In addition to its performance, climate-based modeling also provides mechanistic forecasts of historical and future population changes. Hindcasts in both regions indicate climatic conditions may have been a factor in recent declines, but future forecasts are mixed. Available climatic data suggests the Pacific population will be significantly reduced by 2040, but indicates the Atlantic population may increase substantially. These results do not exonerate anthropogenic impacts, but highlight the significance of bottom-up oceanographic processes to marine organisms. Future studies should consider environmental baselines in assessments of marine turtle population variability and persistence.

24 h urinary free cortisol in large-scale epidemiological studies: short-term and long-term stability and sources of variability.

PubMed

Rosmalen, Judith G M; Kema, Ido P; Wüst, Stefan; van der Ley, Claude; Visser, Sipke T; Snieder, Harold; Bakker, Stephan J L

2014-09-01

Function of the hypothalamus-pituitary-adrenal (HPA) axis has been associated with several somatic and psychiatric health problems. The amount of free cortisol excreted in the urine during 24h (24-h UFC) has often been used as a proxy for HPA-axis function. Reference values for 24-h UFC and their stability in the short and long term, as well as sources of variability, are largely lacking. This study was performed in a general population cohort. Participants collected 24-h UFC on two consecutive days (T1), and repeated this collection approximately 2 years later (T2). Cortisol in urine was measured using LC-MS/MS. Height and weight were measured at the research facilities; glomerular filtration rate was estimated using creatinine clearance. Psychological distress (General Health Questionnaire), smoking, alcohol use and exercise were measured by means of questionnaires. 24-h UFC stability on a day-to-day basis was 0.69 (T1, N=1192) and 0.72 (T2, N=963) (both p<0.001). Long-term stability as indicated by correlation between 2-day averages of T1 and T2 was 0.60 (N=972, p<0.001). Multivariable linear regression analysis revealed that 24-h UFC was predicted by urine volume (standardized beta 0.282 (T1, N=1556) and 0.276 (T2, N=1244); both p<0.001) and glomerular filtration rate (standardized beta 0.137 (T1) and 0.179 (T2); both p<0.001), while also sex explained a small part (standardized beta for female sex -0.057 (T1) and -0.080 (T2); both p<0.05). 24-h UFC is moderately stable both in the short and the long term. The effects of urine volume and glomerular filtration rate on 24-h UFC are much stronger than those of sex. Copyright © 2014 Elsevier Ltd. All rights reserved.

Utilization of Short-Simulations for Tuning High-Resolution Climate Model

NASA Astrophysics Data System (ADS)

Lin, W.; Xie, S.; Ma, P. L.; Rasch, P. J.; Qian, Y.; Wan, H.; Ma, H. Y.; Klein, S. A.

2016-12-01

Many physical parameterizations in atmospheric models are sensitive to resolution. Tuning the models that involve a multitude of parameters at high resolution is computationally expensive, particularly when relying primarily on multi-year simulations. This work describes a complementary set of strategies for tuning high-resolution atmospheric models, using ensembles of short simulations to reduce the computational cost and elapsed time. Specifically, we utilize the hindcast approach developed through the DOE Cloud Associated Parameterization Testbed (CAPT) project for high-resolution model tuning, which is guided by a combination of short (< 10 days ) and longer ( 1 year) Perturbed Parameters Ensemble (PPE) simulations at low resolution to identify model feature sensitivity to parameter changes. The CAPT tests have been found to be effective in numerous previous studies in identifying model biases due to parameterized fast physics, and we demonstrate that it is also useful for tuning. After the most egregious errors are addressed through an initial "rough" tuning phase, longer simulations are performed to "hone in" on model features that evolve over longer timescales. We explore these strategies to tune the DOE ACME (Accelerated Climate Modeling for Energy) model. For the ACME model at 0.25° resolution, it is confirmed that, given the same parameters, major biases in global mean statistics and many spatial features are consistent between Atmospheric Model Intercomparison Project (AMIP)-type simulations and CAPT-type hindcasts, with just a small number of short-term simulations for the latter over the corresponding season. The use of CAPT hindcasts to find parameter choice for the reduction of large model biases dramatically improves the turnaround time for the tuning at high resolution. Improvement seen in CAPT hindcasts generally translates to improved AMIP-type simulations. An iterative CAPT-AMIP tuning approach is therefore adopted during each major tuning

Climate variability in the subarctic area for the last 2 millennia

NASA Astrophysics Data System (ADS)

Nicolle, Marie; Debret, Maxime; Massei, Nicolas; Colin, Christophe; deVernal, Anne; Divine, Dmitry; Werner, Johannes P.; Hormes, Anne; Korhola, Atte; Linderholm, Hans W.

2018-01-01

To put recent climate change in perspective, it is necessary to extend the instrumental climate records with proxy data from paleoclimate archives. Arctic climate variability for the last 2 millennia has been investigated using statistical and signal analyses from three regionally averaged records from the North Atlantic, Siberia and Alaska based on many types of proxy data archived in the Arctic 2k database v1.1.1. In the North Atlantic and Alaska, the major climatic trend is characterized by long-term cooling interrupted by recent warming that started at the beginning of the 19th century. This cooling is visible in the Siberian region at two sites, warming at the others. The cooling of the Little Ice Age (LIA) was identified from the individual series, but it is characterized by wide-range spatial and temporal expression of climate variability, in contrary to the Medieval Climate Anomaly. The LIA started at the earliest by around AD 1200 and ended at the latest in the middle of the 20th century. The widespread temporal coverage of the LIA did not show regional consistency or particular spatial distribution and did not show a relationship with archive or proxy type either. A focus on the last 2 centuries shows a recent warming characterized by a well-marked warming trend parallel with increasing greenhouse gas emissions. It also shows a multidecadal variability likely due to natural processes acting on the internal climate system on a regional scale. A ˜ 16-30-year cycle is found in Alaska and seems to be linked to the Pacific Decadal Oscillation, whereas ˜ 20-30- and ˜ 50-90-year periodicities characterize the North Atlantic climate variability, likely in relation with the Atlantic Multidecadal Oscillation. These regional features are probably linked to the sea ice cover fluctuations through ice-temperature positive feedback.

[A method to estimate the short-term fractal dimension of heart rate variability based on wavelet transform].

PubMed

Zhonggang, Liang; Hong, Yan

2006-10-01

A new method of calculating fractal dimension of short-term heart rate variability signals is presented. The method is based on wavelet transform and filter banks. The implementation of the method is: First of all we pick-up the fractal component from HRV signals using wavelet transform. Next, we estimate the power spectrum distribution of fractal component using auto-regressive model, and we estimate parameter 7 using the least square method. Finally according to formula D = 2- (gamma-1)/2 estimate fractal dimension of HRV signal. To validate the stability and reliability of the proposed method, using fractional brown movement simulate 24 fractal signals that fractal value is 1.6 to validate, the result shows that the method has stability and reliability.

Estimating the impact of internal climate variability on ice sheet model simulations

NASA Astrophysics Data System (ADS)

Tsai, C. Y.; Forest, C. E.; Pollard, D.

2016-12-01

Rising sea level threatens human societies and coastal habitats and melting ice sheets are a major contributor to sea level rise (SLR). Thus, understanding uncertainty of both forcing and variability within the climate system is essential for assessing long-term risk of SLR given their impact on ice sheet evolution. The predictability of polar climate is limited by uncertainties from the given forcing, the climate model response to this forcing, and the internal variability from feedbacks within the fully coupled climate system. Among those sources of uncertainty, the impact of internal climate variability on ice sheet changes has not yet been robustly assessed. Here we investigate how internal variability affects ice sheet projections using climate fields from two Community Earth System Model (CESM) large-ensemble (LE) experiments to force a three-dimensional ice sheet model. Each ensemble member in an LE experiment undergoes the same external forcings but with unique initial conditions. We find that for both LEs, 2m air temperature variability over Greenland ice sheet (GrIS) can lead to significantly different ice sheet responses. Our results show that the internal variability from two fully coupled CESM LEs can cause about 25 35 mm differences of GrIS's contribution to SLR in 2100 compared to present day (about 20% of the total change), and 100m differences of SLR in 2300. Moreover, only using ensemble-mean climate fields as the forcing in ice sheet model can significantly underestimate the melt of GrIS. As the Arctic region becomes warmer, the role of internal variability is critical given the complex nonlinear interactions between surface temperature and ice sheet. Our results demonstrate that internal variability from coupled atmosphere-ocean general circulation model can affect ice sheet simulations and the resulting sea-level projections. This study highlights an urgent need to reassess associated uncertainties of projecting ice sheet loss over the next few

Change in Measured Noncognitive Variables: A Quantitative Examination of the Influence of Short-Term Study Abroad Experiences

ERIC Educational Resources Information Center

Motley, Reginald James

2013-01-01

Students have different motivations for participating in education abroad experiences. Short-term study abroad programs offer students the opportunity to experience education abroad without spending an entire semester or year abroad. As a result of these opportunities, short-term study abroad programs have emerged to meet the demands for students…

A multiscale climate emulator for long-term morphodynamics (MUSCLE-morpho)

NASA Astrophysics Data System (ADS)

Antolínez, José Antonio A.; Méndez, Fernando J.; Camus, Paula; Vitousek, Sean; González, E. Mauricio; Ruggiero, Peter; Barnard, Patrick

2016-01-01

Interest in understanding long-term coastal morphodynamics has recently increased as climate change impacts become perceptible and accelerated. Multiscale, behavior-oriented and process-based models, or hybrids of the two, are typically applied with deterministic approaches which require considerable computational effort. In order to reduce the computational cost of modeling large spatial and temporal scales, input reduction and morphological acceleration techniques have been developed. Here we introduce a general framework for reducing dimensionality of wave-driver inputs to morphodynamic models. The proposed framework seeks to account for dependencies with global atmospheric circulation fields and deals simultaneously with seasonality, interannual variability, long-term trends, and autocorrelation of wave height, wave period, and wave direction. The model is also able to reproduce future wave climate time series accounting for possible changes in the global climate system. An application of long-term shoreline evolution is presented by comparing the performance of the real and the simulated wave climate using a one-line model. This article was corrected on 2 FEB 2016. See the end of the full text for details.

Evaluation of Stochastic Rainfall Models in Capturing Climate Variability for Future Drought and Flood Risk Assessment

NASA Astrophysics Data System (ADS)

Chowdhury, A. F. M. K.; Lockart, N.; Willgoose, G. R.; Kuczera, G. A.; Kiem, A.; Nadeeka, P. M.

2016-12-01

One of the key objectives of stochastic rainfall modelling is to capture the full variability of climate system for future drought and flood risk assessment. However, it is not clear how well these models can capture the future climate variability when they are calibrated to Global/Regional Climate Model data (GCM/RCM) as these datasets are usually available for very short future period/s (e.g. 20 years). This study has assessed the ability of two stochastic daily rainfall models to capture climate variability by calibrating them to a dynamically downscaled RCM dataset in an east Australian catchment for 1990-2010, 2020-2040, and 2060-2080 epochs. The two stochastic models are: (1) a hierarchical Markov Chain (MC) model, which we developed in a previous study and (2) a semi-parametric MC model developed by Mehrotra and Sharma (2007). Our hierarchical model uses stochastic parameters of MC and Gamma distribution, while the semi-parametric model uses a modified MC process with memory of past periods and kernel density estimation. This study has generated multiple realizations of rainfall series by using parameters of each model calibrated to the RCM dataset for each epoch. The generated rainfall series are used to generate synthetic streamflow by using a SimHyd hydrology model. Assessing the synthetic rainfall and streamflow series, this study has found that both stochastic models can incorporate a range of variability in rainfall as well as streamflow generation for both current and future periods. However, the hierarchical model tends to overestimate the multiyear variability of wet spell lengths (therefore, is less likely to simulate long periods of drought and flood), while the semi-parametric model tends to overestimate the mean annual rainfall depths and streamflow volumes (hence, simulated droughts are likely to be less severe). Sensitivity of these limitations of both stochastic models in terms of future drought and flood risk assessment will be discussed.

Short-term rainfall: its scaling properties over Portugal

NASA Astrophysics Data System (ADS)

de Lima, M. Isabel P.

2010-05-01

The characterization of rainfall at a variety of space- and time-scales demands usually that data from different origins and resolution are explored. Different tools and methodologies can be used for this purpose. In regions where the spatial variation of rain is marked, the study of the scaling structure of rainfall can lead to a better understanding of the type of events affecting that specific area, which is essential for many engineering applications. The relevant factors affecting rain variability, in time and space, can lead to contrasting statistics which should be carefully taken into account in design procedures and decision making processes. One such region is Mainland Portugal; the territory is located in the transitional region between the sub-tropical anticyclone and the subpolar depression zones and is characterized by strong north-south and east-west rainfall gradients. The spatial distribution and seasonal variability of rain are particularly influenced by the characteristics of the global circulation. One specific feature is the Atlantic origin of many synoptic disturbances in the context of the regional geography (e.g. latitude, orography, oceanic and continental influences). Thus, aiming at investigating the statistical signature of rain events of different origins, resulting from the large number of mechanisms and factors affecting the rainfall climate over Portugal, scale-invariant analyses of the temporal structure of rain from several locations in mainland Portugal were conducted. The study used short-term rainfall time series. Relevant scaling ranges were identified and characterized that help clarifying the small-scale behaviour and statistics of this process.

Association Between Short-Term Systolic Blood Pressure Variability and Carotid Intima-Media Thickness in ELSA-Brasil Baseline.

PubMed

Ribeiro, Adèle H; Lotufo, Paulo A; Fujita, André; Goulart, Alessandra C; Chor, Dora; Mill, José G; Bensenor, Isabela M; Santos, Itamar S

2017-10-01

Blood pressure (BP) is associated with carotid intima-media thickness (CIMT), but few studies have explored the association between BP variability and CIMT. We aimed to investigate this association in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) baseline. We analyzed data from 7,215 participants (56.0% women) without overt cardiovascular disease (CVD) or antihypertensive use. We included 10 BP readings in varying positions during a 6-hour visit. We defined BP variability as the SD of these readings. We performed a 2-step analysis. We first linearly regressed the CIMT values on main and all-order interaction effects of the variables age, sex, body mass index, race, diabetes diagnosis, dyslipidemia diagnosis, family history of premature CVD, smoking status, and ELSA-Brasil site, and calculated the residuals (residual CIMT). We used partial least square path analysis to investigate whether residual CIMT was associated with BP central tendency and BP variability. Systolic BP (SBP) variability was significantly associated with residual CIMT in models including the entire sample (path coefficient [PC]: 0.046; P < 0.001), and in women (PC: 0.046; P = 0.007) but not in men (PC: 0.037; P = 0.09). This loss of significance was probably due to the smaller subsample size, as PCs were not significantly different according to sex. We found a small but significant association between SBP variability and CIMT values. This was additive to the association between SBP central tendency and CIMT values, supporting a role for high short-term SBP variability in atherosclerosis. © American Journal of Hypertension, Ltd 2017. All rights reserved. For Permissions, please email: journals.permissions@oup.com

The Performance of Short-Term Heart Rate Variability in the Detection of Congestive Heart Failure

PubMed Central

Barros, Allan Kardec; Ohnishi, Noboru

2016-01-01

Congestive heart failure (CHF) is a cardiac disease associated with the decreasing capacity of the cardiac output. It has been shown that the CHF is the main cause of the cardiac death around the world. Some works proposed to discriminate CHF subjects from healthy subjects using either electrocardiogram (ECG) or heart rate variability (HRV) from long-term recordings. In this work, we propose an alternative framework to discriminate CHF from healthy subjects by using HRV short-term intervals based on 256 RR continuous samples. Our framework uses a matching pursuit algorithm based on Gabor functions. From the selected Gabor functions, we derived a set of features that are inputted into a hybrid framework which uses a genetic algorithm and k-nearest neighbour classifier to select a subset of features that has the best classification performance. The performance of the framework is analyzed using both Fantasia and CHF database from Physionet archives which are, respectively, composed of 40 healthy volunteers and 29 subjects. From a set of nonstandard 16 features, the proposed framework reaches an overall accuracy of 100% with five features. Our results suggest that the application of hybrid frameworks whose classifier algorithms are based on genetic algorithms has outperformed well-known classifier methods. PMID:27891509

24 CFR 576.106 - Short-term and medium-term rental assistance.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 24 Housing and Urban Development 3 2012-04-01 2012-04-01 false Short-term and medium-term rental... and Eligible Activities § 576.106 Short-term and medium-term rental assistance. (a) General provisions... assistance may be short-term rental assistance, medium-term rental assistance, payment of rental arrears, or...

24 CFR 576.106 - Short-term and medium-term rental assistance.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 24 Housing and Urban Development 3 2013-04-01 2013-04-01 false Short-term and medium-term rental... and Eligible Activities § 576.106 Short-term and medium-term rental assistance. (a) General provisions... assistance may be short-term rental assistance, medium-term rental assistance, payment of rental arrears, or...

24 CFR 576.106 - Short-term and medium-term rental assistance.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 24 Housing and Urban Development 3 2014-04-01 2013-04-01 true Short-term and medium-term rental... and Eligible Activities § 576.106 Short-term and medium-term rental assistance. (a) General provisions... assistance may be short-term rental assistance, medium-term rental assistance, payment of rental arrears, or...

Hurricane Arthur and its effect on the short-term variability of pCO2 on the Scotian Shelf, NW Atlantic

NASA Astrophysics Data System (ADS)

Lemay, Jonathan; Thomas, Helmuth; Craig, Susanne E.; Burt, William J.; Fennel, Katja; Greenan, Blair J. W.

2018-04-01

The understanding of the seasonal variability of carbon cycling on the Scotian Shelf in the NW Atlantic Ocean has improved in recent years; however, very little information is available regarding its short-term variability. In order to shed light on this aspect of carbon cycling on the Scotian Shelf we investigate the effects of Hurricane Arthur, which passed the region on 5 July 2014. The hurricane caused a substantial decline in the surface water partial pressure of CO2 (pCO2), even though the Scotian Shelf possesses CO2-rich deep waters. High-temporal-resolution data of moored autonomous instruments demonstrate that there is a distinct layer of relatively cold water with low dissolved inorganic carbon (DIC) slightly above the thermocline, presumably due to a sustained population of phytoplankton. Strong storm-related wind mixing caused this cold intermediate layer with high phytoplankton biomass to be entrained into the surface mixed layer. At the surface, phytoplankton begin to grow more rapidly due to increased light. The combination of growth and the mixing of low DIC water led to a short-term reduction in the partial pressure of CO2 until wind speeds relaxed and allowed for the restratification of the upper water column. These hurricane-related processes caused a (net) CO2 uptake by the Scotian Shelf region that is comparable to the spring bloom, thus exerting a major impact on the annual CO2 flux budget.

Pacific Decadal Variability and Central Pacific Warming El Niño in a Changing Climate

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

Di Lorenzo, Emanuele

This research aimed at understanding the dynamics controlling decadal variability in the Pacific Ocean and its interactions with global-scale climate change. The first goal was to assess how the dynamics and statistics of the El Niño Southern Oscillation and the modes of Pacific decadal variability are represented in global climate models used in the IPCC. The second goal was to quantify how decadal dynamics are projected to change under continued greenhouse forcing, and determine their significance in the context of paleo-proxy reconstruction of long-term climate.

Linking the variability of atmospheric carbon monoxide to climate modes in the Southern Hemisphere

NASA Astrophysics Data System (ADS)

Buchholz, Rebecca; Monks, Sarah; Hammerling, Dorit; Worden, Helen; Deeter, Merritt; Emmons, Louisa; Edwards, David

2017-04-01

Biomass burning is a major driver of atmospheric carbon monoxide (CO) variability in the Southern Hemisphere. The magnitude of emissions, such as CO, from biomass burning is connected to climate through both the availability and dryness of fuel. We investigate the link between CO and climate using satellite measured CO and climate indices. Observations of total column CO from the satellite instrument MOPITT are used to build a record of interannual variability in CO since 2001. Four biomass burning regions in the Southern Hemisphere are explored. Data driven relationships are determined between CO and climate indices for the climate modes: El Niño Southern Oscillation (ENSO); the Indian Ocean Dipole (IOD); the Tropical Southern Atlantic (TSA); and the Southern Annular Mode (SAM). Stepwise forward and backward regression is used to select the best statistical model from combinations of lagged indices. We find evidence for the importance of first-order interaction terms of the climate modes when explaining CO variability. Implications of the model results are discussed for the Maritime Southeast Asia and Australasia regions. We also draw on the chemistry-climate model CAM-chem to explain the source contribution as well as the relative contributions of emissions and meteorology to CO variability.

Short-term variability of gamma radiation at the ARM Eastern North Atlantic facility (Azores).

PubMed

Barbosa, S M; Miranda, P; Azevedo, E B

2017-06-01

This work addresses the short-term variability of gamma radiation measured continuously at the Eastern North Atlantic (ENA) facility located in the Graciosa island (Azores, 39N; 28W), a fixed site of the Atmospheric Radiation Measurement programme (ARM). The temporal variability of gamma radiation is characterized by occasional anomalies over a slowly-varying signal. Sharp peaks lasting typically 2-4 h are coincident with heavy precipitation and result from the scavenging effect of precipitation bringing radon progeny from the upper levels to the ground surface. However the connection between gamma variability and precipitation is not straightforward as a result of the complex interplay of factors such as the precipitation intensity, the PBL height, the cloud's base height and thickness, or the air mass origin and atmospheric concentration of sub-micron aerosols, which influence the scavenging processes and therefore the concentration of radon progeny. Convective precipitation associated with cumuliform clouds forming under conditions of warming of the ground relative to the air does not produce enhancements in gamma radiation, since the drop growing process is dominated by the fast accretion of liquid water, resulting in the reduction of the concentration of radionuclides by dilution. Events of convective precipitation further contribute to a reduction in gamma counts by inhibiting radon release from the soil surface and by attenuating gamma rays from all gamma-emitting elements on the ground. Anomalies occurring in the absence of precipitation are found to be associated with a diurnal cycle of maximum gamma counts before sunrise decreasing to a minimum in the evening, which are observed in conditions of thermal stability and very weak winds enabling the build-up of near surface radon progeny during the night. Copyright © 2017 Elsevier Ltd. All rights reserved.

Long-term rise of the Water Table in the Northeast US: Climate Variability, Land-Use Change, or Angry Beavers?

NASA Astrophysics Data System (ADS)

Boutt, D. F.

2011-12-01

The scientific evidence that humans are directly influencing the Earth's natural climate is increasingly compelling. Numerous studies suggest that climate change will lead to changes in the seasonality of surface water availability thereby increasing the need for groundwater development to offset those shortages. Research suggests that the Northeast region of the U.S. is experiencing significant changes to its' natural climate and hydrologic systems. Previous analysis of a long-term regional compilation of the water table response to the last 60 years of climate variability in New England documented a wide range of variability. The investigation evaluated the physical mechanisms, natural variability and response of aquifers in New England using 100 long term groundwater monitoring stations with 20 or more years of data coupled with 67 stream gages, 75 precipitation stations, and 43 temperature stations. Groundwater trends were calculated as normalized anomalies and analyzed with respect to regional compiled precipitation, temperature, and streamflow anomalies to understand the sensitivity of the aquifer systems to change. Interestingly, a trend and regression analysis demonstrate that water level fluctuations are producing statistically significant results with increasing water levels over at least the past thirty years at most (80 out of 100) well sites. In this contribution we investigate the causal mechanisms behind the observed ground water level trends using site-by-site land-use change assessments, cluster analysis, and spatial analysis of beaver populations (a possible proxy for beaver activity). Regionally, average annual precipitation has been slightly increasing since 1900, with 95% of the stations having statistically significant positive trends. Despite this, no correlation is observed between the magnitude of the annual precipitation trends and the magnitude of the groundwater level changes. Land-use change throughout the region has primarily taken

Functional adjustments of xylem anatomy to climatic variability: insights from long-term Ilex aquifolium tree-ring series.

PubMed

Rita, Angelo; Cherubini, Paolo; Leonardi, Stefano; Todaro, Luigi; Borghetti, Marco

2015-08-01

The present study assessed the effects of climatic conditions on radial growth and functional anatomical traits, including ring width, vessel size, vessel frequency and derived variables, i.e., potential hydraulic conductivity and xylem vulnerability to cavitation in Ilex aquifolium L. trees using long-term tree-ring time series obtained at two climatically contrasting sites, one mesic site in Switzerland (CH) and one drought-prone site in Italy (ITA). Relationships were explored by examining different xylem traits, and point pattern analysis was applied to investigate vessel clustering. We also used generalized additive models and bootstrap correlation functions to describe temperature and precipitation effects. Results indicated modified radial growth and xylem anatomy in trees over the last century; in particular, vessel frequency increased markedly at both sites in recent years, and all xylem traits examined, with the exception of xylem cavitation vulnerability, were higher at the CH mesic compared with the ITA drought site. A significant vessel clustering was observed at the ITA site, which could contribute to an enhanced tolerance to drought-induced embolism. Flat and negative relationships between vessel size and ring width were observed, suggesting carbon was not allocated to radial growth under conditions which favored stem water conduction. Finally, in most cases results indicated that climatic conditions influenced functional anatomical traits more substantially than tree radial growth, suggesting a crucial role of functional xylem anatomy in plant acclimation to future climatic conditions. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

High-resolution regional climate model evaluation using variable-resolution CESM over California

NASA Astrophysics Data System (ADS)

Huang, X.; Rhoades, A.; Ullrich, P. A.; Zarzycki, C. M.

2015-12-01

Understanding the effect of climate change at regional scales remains a topic of intensive research. Though computational constraints remain a problem, high horizontal resolution is needed to represent topographic forcing, which is a significant driver of local climate variability. Although regional climate models (RCMs) have traditionally been used at these scales, variable-resolution global climate models (VRGCMs) have recently arisen as an alternative for studying regional weather and climate allowing two-way interaction between these domains without the need for nudging. In this study, the recently developed variable-resolution option within the Community Earth System Model (CESM) is assessed for long-term regional climate modeling over California. Our variable-resolution simulations will focus on relatively high resolutions for climate assessment, namely 28km and 14km regional resolution, which are much more typical for dynamically downscaled studies. For comparison with the more widely used RCM method, the Weather Research and Forecasting (WRF) model will be used for simulations at 27km and 9km. All simulations use the AMIP (Atmospheric Model Intercomparison Project) protocols. The time period is from 1979-01-01 to 2005-12-31 (UTC), and year 1979 was discarded as spin up time. The mean climatology across California's diverse climate zones, including temperature and precipitation, is analyzed and contrasted with the Weather Research and Forcasting (WRF) model (as a traditional RCM), regional reanalysis, gridded observational datasets and uniform high-resolution CESM at 0.25 degree with the finite volume (FV) dynamical core. The results show that variable-resolution CESM is competitive in representing regional climatology on both annual and seasonal time scales. This assessment adds value to the use of VRGCMs for projecting climate change over the coming century and improve our understanding of both past and future regional climate related to fine

Legacy effects of simulated short-term climate change on ammonia oxidisers, denitrifiers, and nitrous oxide emissions in an acid soil.

PubMed

Xu, Xiaoya; Liu, Xiaorui; Li, Yong; Ran, Yu; Liu, Yapeng; Zhang, Qichun; Li, Zheng; He, Yan; Xu, Jianming; Di, Hongjie

2017-04-01

Although the effect of simulated climate change on nitrous oxide (N 2 O) emissions and on associated microbial communities has been reported, it is not well understood if these effects are short-lived or long-lasting. Here, we conducted a field study to determine the interactive effects of simulated warmer and drier conditions on nitrifier and denitrifier communities and N 2 O emissions in an acidic soil and the longevity of the effects. A warmer (+2.3 °C) and drier climate (-7.4% soil moisture content) was created with greenhouses. The variation of microbial population abundance and community structure of ammonia-oxidizing archaea (AOA), bacteria (AOB), and denitrifiers (nirK/S, nosZ) were determined using real-time PCR and high-throughput sequencing. The results showed that the simulated warmer and drier conditions under the greenhouse following urea application significantly increased N 2 O emissions. There was also a moderate legacy effect on the N 2 O emissions when the greenhouses were removed in the urea treatment, although this effect only lasted a short period of time (about 60 days). The simulated climate change conditions changed the composition of AOA with the species affiliated to marine group 1.1a-associated lineage increasing significantly. The abundance of all the functional denitrifier genes decreased significantly under the simulated climate change conditions and the legacy effect, after the removal of greenhouses, significantly increased the abundance of AOB, AOA (mainly the species affiliated to marine group 1.1a-associated lineage), and nirK and nosZ genes in the urea-treated soil. In general, the effect of the simulated climate change was short-lived, with the denitrifier communities being able to return to ambient levels after a period of adaptation to ambient conditions. Therefore, the legacy effect of simulated short-time climate change conditions on the ammonia oxidizer and denitrifier communities and N 2 O emissions were temporary and

The patient safety climate in healthcare organizations (PSCHO) survey: Short-form development.

PubMed

Benzer, Justin K; Meterko, Mark; Singer, Sara J

2017-08-01

Measures of safety climate are increasingly used to guide safety improvement initiatives. However, cost and respondent burden may limit the use of safety climate surveys. The purpose of this study was to develop a 15- to 20-item safety climate survey based on the Patient Safety Climate in Healthcare Organizations survey, a well-validated 38-item measure of safety climate. The Patient Safety Climate in Healthcare Organizations was administered to all senior managers, all physicians, and a 10% random sample of all other hospital personnel in 69 private sector hospitals and 30 Veterans Health Administration hospitals. Both samples were randomly divided into a derivation sample to identify a short-form subset and a confirmation sample to assess the psychometric properties of the proposed short form. The short form consists of 15 items represented 3 overarching domains in the long-form scale-organization, work unit, and interpersonal. The proposed short form efficiently captures 3 important sources of variance in safety climate: organizational, work-unit, and interpersonal. The short-form development process was a practical method that can be applied to other safety climate surveys. This safety climate short form may increase response rates in studies that involve busy clinicians or repeated measures. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Long-term resistance to simulated climate change in an infertile grassland.

PubMed

Grime, J Philip; Fridley, Jason D; Askew, Andrew P; Thompson, Ken; Hodgson, John G; Bennett, Chris R

2008-07-22

Climate shifts over this century are widely expected to alter the structure and functioning of temperate plant communities. However, long-term climate experiments in natural vegetation are rare and largely confined to systems with the capacity for rapid compositional change. In unproductive, grazed grassland at Buxton in northern England (U.K.), one of the longest running experimental manipulations of temperature and rainfall reveals vegetation highly resistant to climate shifts maintained over 13 yr. Here we document this resistance in the form of: (i) constancy in the relative abundance of growth forms and maintained dominance by long-lived, slow-growing grasses, sedges, and small forbs; (ii) immediate but minor shifts in the abundance of several species that have remained stable over the course of the experiment; (iii) no change in productivity in response to climate treatments with the exception of reduction from chronic summer drought; and (iv) only minor species losses in response to drought and winter heating. Overall, compositional changes induced by 13-yr exposure to climate regime change were less than short-term fluctuations in species abundances driven by interannual climate fluctuations. The lack of progressive compositional change, coupled with the long-term historical persistence of unproductive grasslands in northern England, suggests the community at Buxton possesses a stabilizing capacity that leads to long-term persistence of dominant species. Unproductive ecosystems provide a refuge for many threatened plants and animals and perform a diversity of ecosystem services. Our results support the view that changing land use and overexploitation rather than climate change per se constitute the primary threats to these fragile ecosystems.

Millennial- to century-scale variability in Gulf of Mexico Holocene climate records

USGS Publications Warehouse

Poore, R.Z.; Dowsett, H.J.; Verardo, S.; Quinn, T.M.

2003-01-01

Proxy records from two piston cores in the Gulf of Mexico (GOM) provide a detailed (50-100 year resolution) record of climate variability over the last 14,000 years. Long-term (millennial-scale) trends and changes are related to the transition from glacial to interglacial conditions and movement of the average position of the Intertropical Convergence Zone (ITCZ) related to orbital forcing. The ??18O of the surface-dwelling planktic foraminifer Globigerinoides ruber show negative excursions between 14 and 10.2 ka (radiocarbon years) that reflect influx of meltwater into the western GOM during melting of the Laurentide Ice Sheet. The relative abundance of the planktic foraminifer Globigerinoides sacculifer is related to transport of Caribbean water into the GOM. Maximum transport of Caribbean surface waters and moisture into the GOM associated with a northward migration of the average position of the ITCZ occurs between about 6.5 and 4.5 ka. In addition, abundance variations of G. sacculifer show century-scale variability throughout most of the Holocene. The GOM record is consistent with records from other areas, suggesting that century-scale variability is a pervasive feature of Holocene climate. The frequency of several cycles in the climate records is similar to cycles identified in proxy records of solar variability, indicating that at least some of the century-scale climate variability during the Holocene is due to external (solar) forcing.

Characterization of large-scale fluctuations and short-term variability of Seine river daily streamflow (France) over the period 1950-2008 by empirical mode decomposition and the Hilbert-Huang transform

NASA Astrophysics Data System (ADS)

Massei, N.; Fournier, M.

2010-12-01

Daily Seine river flow from 1950 to 2008 was analyzed using Hilbert-Huang Tranform (HHT). For the last ten years, this method which combines the so-called Empirical Mode Decomposition (EMD) multiresolution analysis and the Hilbert transform has proven its efficiency for the analysis of transient oscillatory signals, although the mathematical definition of the EMD is not totally established yet. HHT also provides an interesting alternative to other time-frequency or time-scale analysis of non-stationary signals, the most famous of which being wavelet-based approaches. In this application of HHT to the analysis of the hydrological variability of the Seine river, we seek to characterize the interannual patterns of daily flow, differenciate them from the short-term dynamics and eventually interpret them in the context of regional climate regime fluctuations. In this aim, HHT is also applied to the North-Atlantic Oscillation (NAO) through the annual winter-months NAO index time series. For both hydrological and climatic signals, dominant variability scales are extracted and their temporal variations analyzed by determination of the intantaneous frequency of each component. When compared to previous ones obtained from continuous wavelet transform (CWT) on the same data, HHT results highlighted the same scales and somewhat the same internal components for each signal. However, HHT allowed the identification and extraction of much more similar features during the 1950-2008 period (e.g., around 7-yr, between NAO and Seine flow than what was obtained from CWT, which comes to say that variability scales in flow likely to originate from climatic regime fluctuations were much properly identified in river flow. In addition, a more accurate determination of singularities in the natural processes analyzed were authorized by HHT compared to CWT, in which case the time-frequency resolution partly depends on the basic properties of the filter (i.e., the reference wavelet chosen

Perspectives for short timescale variability studies with Gaia

NASA Astrophysics Data System (ADS)

Roelens, M.; Eyer, L.; Mowlavi, N.; Lecoeur-Taïbi, I.; Rimoldini, L.; Blanco-Cuaresma, S.; Palaversa, L.; Süveges, M.; Charnas, J.; Wevers, T.

2017-12-01

We assess the potential of Gaia for detecting and characterizing short timescale variables, i.e. at timescale from a few seconds to a dozen hours, through extensive light-curve simulations for various short timescale variable types, including both periodic and non-periodic variability. We evidence that the variogram analysis applied to Gaia photometry should enable to detect such fast variability phenomena, down to amplitudes of a few millimagnitudes, with limited contamination from longer timescale variables or constant sources. This approach also gives valuable information on the typical timescale(s) of the considered variation, which could complement results of classical period search methods, and help prepare ground-based follow-up of the Gaia short timescale candidates.

How resilient are ecosystems in adapting to climate variability

NASA Astrophysics Data System (ADS)

Savenije, Hubert H. G.

2015-04-01

The conclusion often drawn in the media is that ecosystems may perish as a result of climate change. Although climatic trends may indeed lead to shifts in ecosystem composition, the challenge to adjust to climatic variability - even if there is no trend - is larger, particularly in semi-arid or topical climates where climatic variability is large compared to temperate climates. How do ecosystems buffer for climatic variability? The most powerful mechanism is to invest in root zone storage capacity, so as to guarantee access to water and nutrients during period of drought. This investment comes at a cost of having less energy available to invest in growth or formation of fruits. Ecosystems are expected to create sufficient buffer to overcome critical periods of drought, but not more than is necessary to survive or reproduce. Based on this concept, a methodology has been developed to estimate ecosystem root zone storage capacity at local, regional and global scale. These estimates correspond well with estimates made by combining soil and ecosystem information, but are more accurate and more detailed. The methodology shows that ecosystems have intrinsic capacity to adjust to climatic variability and hence have a high resilience to both climatic variability and climatic trends.

Variable climatic conditions dominate recent phytoplankton dynamics in Chesapeake Bay

NASA Astrophysics Data System (ADS)

Harding, Lawrence W., Jr.; Mallonee, Michael E.; Perry, Elgin S.; Miller, W. David; Adolf, Jason E.; Gallegos, Charles L.; Paerl, Hans W.

2016-03-01

Variable climatic conditions strongly influence phytoplankton dynamics in estuaries globally. Our study area is Chesapeake Bay, a highly productive ecosystem providing natural resources, transportation, and recreation for nearly 16 million people inhabiting a 165,000-km2 watershed. Since World War II, nutrient over-enrichment has led to multiple ecosystem impairments caused by increased phytoplankton biomass as chlorophyll-a (chl-a). Doubled nitrogen (N) loadings from 1945-1980 led to increased chl-a, reduced water clarity, and low dissolved oxygen (DO), while decreased N loadings from 1981-2012 suggest modest improvement. The recent 30+ years are characterized by high inter-annual variability of chl-a, coinciding with irregular dry and wet periods, complicating the detection of long-term trends. Here, we synthesize time-series data for historical and recent N loadings (TN, NO2 + NO3), chl-a, floral composition, and net primary productivity (NPP) to distinguish secular changes caused by nutrient over-enrichment from spatio-temporal variability imposed by climatic conditions. Wet years showed higher chl-a, higher diatom abundance, and increased NPP, while dry years showed lower chl-a, lower diatom abundance, and decreased NPP. Our findings support a conceptual model wherein variable climatic conditions dominate recent phytoplankton dynamics against a backdrop of nutrient over-enrichment, emphasizing the need to separate these effects to gauge progress toward improving water quality in estuaries.

Variable climatic conditions dominate recent phytoplankton dynamics in Chesapeake Bay

PubMed Central

Harding, Jr., Lawrence W.; Mallonee, Michael E.; Perry, Elgin S.; Miller, W. David; Adolf, Jason E.; Gallegos, Charles L.; Paerl, Hans W.

2016-01-01

Variable climatic conditions strongly influence phytoplankton dynamics in estuaries globally. Our study area is Chesapeake Bay, a highly productive ecosystem providing natural resources, transportation, and recreation for nearly 16 million people inhabiting a 165,000-km2 watershed. Since World War II, nutrient over-enrichment has led to multiple ecosystem impairments caused by increased phytoplankton biomass as chlorophyll-a (chl-a). Doubled nitrogen (N) loadings from 1945–1980 led to increased chl-a, reduced water clarity, and low dissolved oxygen (DO), while decreased N loadings from 1981–2012 suggest modest improvement. The recent 30+ years are characterized by high inter-annual variability of chl-a, coinciding with irregular dry and wet periods, complicating the detection of long-term trends. Here, we synthesize time-series data for historical and recent N loadings (TN, NO2 + NO3), chl-a, floral composition, and net primary productivity (NPP) to distinguish secular changes caused by nutrient over-enrichment from spatio-temporal variability imposed by climatic conditions. Wet years showed higher chl-a, higher diatom abundance, and increased NPP, while dry years showed lower chl-a, lower diatom abundance, and decreased NPP. Our findings support a conceptual model wherein variable climatic conditions dominate recent phytoplankton dynamics against a backdrop of nutrient over-enrichment, emphasizing the need to separate these effects to gauge progress toward improving water quality in estuaries. PMID:27026279

Variable climatic conditions dominate recent phytoplankton dynamics in Chesapeake Bay.

PubMed

Harding, Lawrence W; Mallonee, Michael E; Perry, Elgin S; Miller, W David; Adolf, Jason E; Gallegos, Charles L; Paerl, Hans W

2016-03-30

Variable climatic conditions strongly influence phytoplankton dynamics in estuaries globally. Our study area is Chesapeake Bay, a highly productive ecosystem providing natural resources, transportation, and recreation for nearly 16 million people inhabiting a 165,000-km(2) watershed. Since World War II, nutrient over-enrichment has led to multiple ecosystem impairments caused by increased phytoplankton biomass as chlorophyll-a (chl-a). Doubled nitrogen (N) loadings from 1945-1980 led to increased chl-a, reduced water clarity, and low dissolved oxygen (DO), while decreased N loadings from 1981-2012 suggest modest improvement. The recent 30+ years are characterized by high inter-annual variability of chl-a, coinciding with irregular dry and wet periods, complicating the detection of long-term trends. Here, we synthesize time-series data for historical and recent N loadings (TN, NO2 + NO3), chl-a, floral composition, and net primary productivity (NPP) to distinguish secular changes caused by nutrient over-enrichment from spatio-temporal variability imposed by climatic conditions. Wet years showed higher chl-a, higher diatom abundance, and increased NPP, while dry years showed lower chl-a, lower diatom abundance, and decreased NPP. Our findings support a conceptual model wherein variable climatic conditions dominate recent phytoplankton dynamics against a backdrop of nutrient over-enrichment, emphasizing the need to separate these effects to gauge progress toward improving water quality in estuaries.

Short-Term Energy Outlook Model Documentation: Macro Bridge Procedure to Update Regional Macroeconomic Forecasts with National Macroeconomic Forecasts

EIA Publications

2010-01-01

The Regional Short-Term Energy Model (RSTEM) uses macroeconomic variables such as income, employment, industrial production and consumer prices at both the national and regional1 levels as explanatory variables in the generation of the Short-Term Energy Outlook (STEO). This documentation explains how national macroeconomic forecasts are used to update regional macroeconomic forecasts through the RSTEM Macro Bridge procedure.

Exploring late Miocene climate stability: constraining background variability using high-resolution benthic δ18O and δ13C records from Site U1338

NASA Astrophysics Data System (ADS)

Drury, A.; John, C. M.; Lee, G.; Shevenell, A.

2012-12-01

The late Miocene (11.61 - 5.33 Ma) was one of the more stable climatic periods of the Cenozoic. Superimposed on this stable background climate, a number of threshold events occurred, including the late Miocene Carbon Isotope Shift (CIS, 7.6-6.6 Ma) and the Messinian Salinity Crisis (MSC, 5.96-5.33 Ma). The goal of our study is to constrain the background climate cyclicity during the late Miocene. A better knowledge of the background cyclicity in the Earth's climate system is required to advance understanding of, and to successfully model, climate variability. Improving understanding of how changes in background climate variability affect important parameters and fluxes, such as ice volume and the carbon pump, is crucial for explaining the occurrence of threshold events such as the CIS and MSC during an otherwise climatically stable period. The study site is located in the Eastern Equatorial Pacific (IODP Site U1338, Expedition 321). U1338 was chosen, as the equatorial Pacific is an important component of the global climate system, representing half of the total tropical ocean and a quarter of the global ocean. We present δ18O and δ13C records from 3.5 to 8.5 Ma using the benthic foraminiferal species Cibicidoides mundulus, with a resolution of 3-4 kyr, which resolves all Milankovitch scale cycles. We present a revised shipboard age model, generated from new biostratigraphic age constraints based on planktic foraminiferal datums. Benthic δ18O records at IODP Site U1338 reflect the stable nature of the late Miocene climate accurately, with long-term trends showing low-amplitude (0.2‰) variations. Superimposed on this are higher-amplitude short-term fluctuations (0.3-0.4‰). Deep-sea benthic foraminferal δ18O records both temperature and the δ18O composition of global deep seawater (δ18Odsw). δ18Odsw largely reflects glacio-eustatic change. Our benthic δ18O implies that long-term trends in ice volume were minimal during the late Miocene. However, the short-term

Small mammals as indicators of short-term and long-term disturbance in mixed prairie

USGS Publications Warehouse

Leis, S.A.; Leslie, David M.; Engle, David M.; Fehmi, J.S.

2008-01-01

Disturbance by military maneuvers over short and long time scales may have differential effects on grassland communities. We assessed small mammals as indicators of disturbance by military maneuvers in a mixed prairie in southern Oklahoma USA. We examined sites on two soil series, Foard and Lawton, across a gradient of disturbance intensity. A MANOVA showed that abundance of small mammals was associated (p = 0.03) with short-term (cover of vehicle tracks) disturbance but was not associated (p = 0.12) with long-term (loss of soil organic carbon, SOC) disturbance intensity. At the individual species level, Sigmodon hispidus (cotton rat) and Peromyscus maniculatus (deer mouse) occurred across all levels of disturbance and in both soil types. Only P. maniculatus abundance changed (p < 0.01) with short-term disturbance and increased by about one individual per 5% of additional track-cover. Abundance of P. maniculatus also increased (p = 0.04) by about three individuals per 1% increase in soil carbon. Chaetodipus hispidus (hispid pocket mouse) and Reithrodontomys fulvescens (fulvous harvest mouse) only occurred in single soil types limiting their potential as more general indicators. Abundance of P. maniculatus was positively related to shifts in plant species composition and likely reflected changes in vegetation structure (i.e. litter depth) and forage availability resulting from disturbance. Peromyscus maniculatus may be a useful biological indicator of ecosystem change because it responded predictably to both long-term and short-term disturbance and, when coupled with soil, plant, and disturbance history variables, can reveal land condition trends. ?? Springer Science+Business Media B.V. 2007.

Future warming patterns linked to today’s climate variability

DOE PAGES

Dai, Aiguo

2016-01-11

The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models’ ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21 st century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today’s climate, with areas of larger variations duringmore » 1950–1979 having more GHG-induced warming in the 21 st century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950–2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21 st century in models and in the real world. Furthermore, they support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.« less

Future warming patterns linked to today’s climate variability

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

Dai, Aiguo

The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models’ ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21 st century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today’s climate, with areas of larger variations duringmore » 1950–1979 having more GHG-induced warming in the 21 st century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950–2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21 st century in models and in the real world. Furthermore, they support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.« less

US Climate Variability and Predictability Project

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

Patterson, Mike

The US CLIVAR Project Office administers the US CLIVAR Program with its mission to advance understanding and prediction of climate variability and change across timescales with an emphasis on the role of the ocean and its interaction with other elements of the Earth system. The Project Office promotes and facilitates scientific collaboration within the US and international climate and Earth science communities, addressing priority topics from subseasonal to centennial climate variability and change; the global energy imbalance; the ocean’s role in climate, water, and carbon cycles; climate and weather extremes; and polar climate changes. This project provides essential one-year supportmore » of the Project Office, enabling the participation of US scientists in the meetings of the US CLIVAR bodies that guide scientific planning and implementation, including the scientific steering committee that establishes program goals and evaluates progress of activities to address them, the science team of funded investigators studying the ocean overturning circulation in the Atlantic, and two working groups tackling the priority research topics of Arctic change influence on midlatitude climate and weather extremes and the decadal-scale widening of the tropical belt.« less

Long-term Photometric Variability in Kepler Full-frame Images: Magnetic Cycles of Sun–like Stars

NASA Astrophysics Data System (ADS)

Montet, Benjamin T.; Tovar, Guadalupe; Foreman-Mackey, Daniel

2017-12-01

Photometry from the Kepler mission is optimized to detect small, short-duration signals like planet transits at the expense of long-term trends. This long-term variability can be recovered in photometry from the full-frame images (FFIs), a set of calibration data collected approximately monthly during the Kepler mission. Here we present f3, an open-source package to perform photometry on the Kepler FFIs in order to detect changes in the brightness of stars in the Kepler field of view over long time baselines. We apply this package to a sample of 4000 Sun–like stars with measured rotation periods. We find that ≈10% of these targets have long-term variability in their observed flux. For the majority of targets, we find that the luminosity variations are either correlated or anticorrelated with the short-term variability due to starspots on the stellar surface. We find a transition between anticorrelated (starspot-dominated) variability and correlated (facula-dominated) variability between rotation periods of 15 and 25 days, suggesting the transition between the two modes is complete for stars at the age of the Sun. We also identify a sample of stars with apparently complete cycles, as well as a collection of short-period binaries with extreme photometric variation over the Kepler mission.

Disease in a more variable and unpredictable climate

NASA Astrophysics Data System (ADS)

McMahon, T. A.; Raffel, T.; Rohr, J. R.; Halstead, N.; Venesky, M.; Romansic, J.

2014-12-01

Global climate change is shifting the dynamics of infectious diseases of humans and wildlife with potential adverse consequences for disease control. Despite this, the role of global climate change in the decline of biodiversity and the emergence of infectious diseases remains controversial. Climate change is expected to increase climate variability in addition to increasing mean temperatures, making climate less predictable. However, few empirical or theoretical studies have considered the effects of climate variability or predictability on disease, despite it being likely that hosts and parasites will have differential responses to climatic shifts. Here we present a theoretical framework for how temperature variation and its predictability influence disease risk by affecting host and parasite acclimation responses. Laboratory experiments and field data on disease-associated frog declines in Latin America support this framework and provide evidence that unpredictable temperature fluctuations, on both monthly and diurnal timescales, decrease frog resistance to the pathogenic chytrid fungus Batrachochytrium dendrobatidis (Bd). Furthermore, the pattern of temperature-dependent growth of the fungus on frogs was inconsistent with the pattern of Bd growth in culture, emphasizing the importance of accounting for the host-parasite interaction when predicting climate-dependent disease dynamics. Consistent with our laboratory experiments, increased regional temperature variability associated with global El Niño climatic events was the best predictor of widespread amphibian losses in the genus Atelopus. Thus, incorporating the effects of small-scale temporal variability in climate can greatly improve our ability to predict the effects of climate change on disease.

Impacts of climate variability and extreme events on soil hydrological processes

NASA Astrophysics Data System (ADS)

Ramos, M. C.; Mulligan, M.

2003-04-01

The Mediterranean climate (dry subhumid), characterised by a high variability, produces in many situations an insufficient water supply to support stable agriculture. Not only is there insufficient rainfall, but its occurrence is also highly variable between years, during the year, and spatially, during a single rainfall event. One of the main climatic characteristics affecting the vulnerability of the Mediterranean region is the high intensity rainfalls which fall after a very dry summer and the high degree of climatic fluctuation in the short and long term, especially in rainfall quantity. In addition, the rainwater penetration and storage of water in the soil are conditioned by the soil characteristics, in some cases modified by changes in land use and with new management practices. The aim of this study was to evaluate the impact of this high variability, from year to year and through the year, on soil hydrological processes, in fields resulted of the mechanisation works in vineyards in a Mediterranean environment. The PATTERNlight model, a simplified two-dimensional version of the hydrological and growth PATTERN model (Mulligan, 1996) is used here to simulate the water balance for three situations: normal, wet and dry years. Ssignificant differences in soil moisture and recharge were observed under vine culture from year to year, giving rise very often, to critical situations for the development of the crops. The distribution of the rainfall through the year together with the intensity of the recorded rainfalls is much very significant for soil hydrology than the total annual rainfall. Very low soil moisture conditions are raised when spring rainfall is scarce, which contribute to exhaustion of profile soil water over the summer, especially if the antecedent soil moisture is low. This low soil moisture has a significant effect on the development of the vine crop. The simulations of leaf and root biomass carried out with the PATTERNLIGHT model indicate the

Short-term stream water temperature observations permit rapid assessment of potential climate change impacts

Treesearch

Peter Caldwell; Catalina Segura; Shelby Gull Laird; Ge Sun; Steven G. McNulty; Maria Sandercock; Johnny Boggs; James M. Vose

2015-01-01

Assessment of potential climate change impacts on stream water temperature (Ts) across large scales remains challenging for resource managers because energy exchange processes between the atmosphere and the stream environment are complex and uncertain, and few long-term datasets are available to evaluate changes over time. In this study, we...

Impacts of climate change and internal climate variability on french rivers streamflows

NASA Astrophysics Data System (ADS)

Dayon, Gildas; Boé, Julien; Martin, Eric

2016-04-01

The assessment of the impacts of climate change often requires to set up long chains of modeling, from the model to estimate the future concentration of greenhouse gases to the impact model. Throughout the modeling chain, sources of uncertainty accumulate making the exploitation of results for the development of adaptation strategies difficult. It is proposed here to assess the impacts of climate change on the hydrological cycle over France and the associated uncertainties. The contribution of the uncertainties from greenhouse gases emission scenario, climate models and internal variability are addressed in this work. To have a large ensemble of climate simulations, the study is based on Global Climate Models (GCM) simulations from the Coupled Model Intercomparison Phase 5 (CMIP5), including several simulations from the same GCM to properly assess uncertainties from internal climate variability. Simulations from the four Radiative Concentration Pathway (RCP) are downscaled with a statistical method developed in a previous study (Dayon et al. 2015). The hydrological system Isba-Modcou is then driven by the downscaling results on a 8 km grid over France. Isba is a land surface model that calculates the energy and water balance and Modcou a hydrogeological model that routes the surface runoff given by Isba. Based on that framework, uncertainties uncertainties from greenhouse gases emission scenario, climate models and climate internal variability are evaluated. Their relative importance is described for the next decades and the end of this century. In a last part, uncertainties due to internal climate variability on streamflows simulated with downscaled GCM and Isba-Modcou are evaluated against observations and hydrological reconstructions on the whole 20th century. Hydrological reconstructions are based on the downscaling of recent atmospheric reanalyses of the 20th century and observations of temperature and precipitation. We show that the multi-decadal variability

Short-term load forecasting using neural network for future smart grid application

NASA Astrophysics Data System (ADS)

Zennamo, Joseph Anthony, III

Short-term load forecasting of power system has been a classic problem for a long time. Not merely it has been researched extensively and intensively, but also a variety of forecasting methods has been raised. This thesis outlines some aspects and functions of smart meter. It also presents different policies and current statuses as well as future projects and objectives of SG development in several countries. Then the thesis compares main aspects about latest products of smart meter from different companies. Lastly, three types of prediction models are established in MATLAB to emulate the functions of smart grid in the short-term load forecasting, and then their results are compared and analyzed in terms of accuracy. For this thesis, more variables such as dew point temperature are used in the Neural Network model to achieve more accuracy for better short-term load forecasting results.

A Latent Variable Analysis of Working Memory Capacity, Short-Term Memory Capacity, Processing Speed, and General Fluid Intelligence.

ERIC Educational Resources Information Center

Conway, Andrew R. A.; Cowan, Nelsin; Bunting, Michael F.; Therriault, David J.; Minkoff, Scott R. B.

2002-01-01

Studied the interrelationships among general fluid intelligence, short-term memory capacity, working memory capacity, and processing speed in 120 young adults and used structural equation modeling to determine the best predictor of general fluid intelligence. Results suggest that working memory capacity, but not short-term memory capacity or…

What are the differences between long-term, short-term, and working memory?

PubMed

Cowan, Nelson

2008-01-01

In the recent literature there has been considerable confusion about the three types of memory: long-term, short-term, and working memory. This chapter strives to reduce that confusion and makes up-to-date assessments of these types of memory. Long- and short-term memory could differ in two fundamental ways, with only short-term memory demonstrating (1) temporal decay and (2) chunk capacity limits. Both properties of short-term memory are still controversial but the current literature is rather encouraging regarding the existence of both decay and capacity limits. Working memory has been conceived and defined in three different, slightly discrepant ways: as short-term memory applied to cognitive tasks, as a multi-component system that holds and manipulates information in short-term memory, and as the use of attention to manage short-term memory. Regardless of the definition, there are some measures of memory in the short term that seem routine and do not correlate well with cognitive aptitudes and other measures (those usually identified with the term "working memory") that seem more attention demanding and do correlate well with these aptitudes. The evidence is evaluated and placed within a theoretical framework depicted in Fig. 1.

Long-term coastal measurements for large-scale climate trends characterization

NASA Astrophysics Data System (ADS)

Pomaro, Angela; Cavaleri, Luigi; Lionello, Piero

2017-04-01

Multi-decadal time-series of observational wave data beginning in the late 1970's are relatively rare. The present study refers to the analysis of the 37-year long directional wave time-series recorded between 1979 and 2015 at the CNR-ISMAR (Institute of Marine Sciences of the Italian National Research Council) "Acqua Alta" oceanographic research tower, located in the Northern Adriatic Sea, 15 km offshore the Venice lagoon, on 16 m depth. The extent of the time series allows to exploit its content not only for modelling purposes or short-term statistical analyses, but also at the climatological scale thanks to the peculiar meteorological and oceanographic aspects of the coastal area where this relevant infrastructure has been installed. We explore the dataset both to characterize the local average climate and its variability, and to detect the possible long-term trends that might be suggestive of, or emphasize, large scale circulation patterns and trends. Measured data are essential for the assessment, and often for the calibration, of model data, generally, if long enough, also the reference also for climate studies. By applying this analysis to an area well characterized from the meteorological point of view, we first assess the changes in time based on measured data, and then we compare them to the ones derived from the ERA-Interim regional simulation over the same area, thus showing the strong improvement that is still needed to get reliable climate models projections on coastal areas and the Mediterranean Region as a whole. Moreover, long term hindcast aiming at climatic considerations are well known for 1) underestimating, if their resolution is not high enough, the actual wave heights as well as for 2) being strongly affected by different conditions over time that are likely to introduce spurious trends of variable magnitude. In particular the different amount, in time, of assimilated data by the hindcast models, directly and indirectly affects the results

Impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling

NASA Astrophysics Data System (ADS)

Chen, Jie; Li, Chao; Brissette, François P.; Chen, Hua; Wang, Mingna; Essou, Gilles R. C.

2018-05-01

Bias correction is usually implemented prior to using climate model outputs for impact studies. However, bias correction methods that are commonly used treat climate variables independently and often ignore inter-variable dependencies. The effects of ignoring such dependencies on impact studies need to be investigated. This study aims to assess the impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling. To this end, a joint bias correction (JBC) method which corrects the joint distribution of two variables as a whole is compared with an independent bias correction (IBC) method; this is considered in terms of correcting simulations of precipitation and temperature from 26 climate models for hydrological modeling over 12 watersheds located in various climate regimes. The results show that the simulated precipitation and temperature are considerably biased not only in the individual distributions, but also in their correlations, which in turn result in biased hydrological simulations. In addition to reducing the biases of the individual characteristics of precipitation and temperature, the JBC method can also reduce the bias in precipitation-temperature (P-T) correlations. In terms of hydrological modeling, the JBC method performs significantly better than the IBC method for 11 out of the 12 watersheds over the calibration period. For the validation period, the advantages of the JBC method are greatly reduced as the performance becomes dependent on the watershed, GCM and hydrological metric considered. For arid/tropical and snowfall-rainfall-mixed watersheds, JBC performs better than IBC. For snowfall- or rainfall-dominated watersheds, however, the two methods behave similarly, with IBC performing somewhat better than JBC. Overall, the results emphasize the advantages of correcting the P-T correlation when using climate model-simulated precipitation and temperature to assess the impact of climate change on watershed

Information transfer across the scales of climate data variability

NASA Astrophysics Data System (ADS)

Palus, Milan; Jajcay, Nikola; Hartman, David; Hlinka, Jaroslav

2015-04-01

Multitude of scales characteristic of the climate system variability requires innovative approaches in analysis of instrumental time series. We present a methodology which starts with a wavelet decomposition of a multi-scale signal into quasi-oscillatory modes of a limited band-with, described using their instantaneous phases and amplitudes. Then their statistical associations are tested in order to search for interactions across time scales. In particular, an information-theoretic formulation of the generalized, nonlinear Granger causality is applied together with surrogate data testing methods [1]. The method [2] uncovers causal influence (in the Granger sense) and information transfer from large-scale modes of climate variability with characteristic time scales from years to almost a decade to regional temperature variability on short time scales. In analyses of daily mean surface air temperature from various European locations an information transfer from larger to smaller scales has been observed as the influence of the phase of slow oscillatory phenomena with periods around 7-8 years on amplitudes of the variability characterized by smaller temporal scales from a few months to annual and quasi-biennial scales [3]. In sea surface temperature data from the tropical Pacific area an influence of quasi-oscillatory phenomena with periods around 4-6 years on the variability on and near the annual scale has been observed. This study is supported by the Ministry of Education, Youth and Sports of the Czech Republic within the Program KONTAKT II, Project No. LH14001. [1] M. Palus, M. Vejmelka, Phys. Rev. E 75, 056211 (2007) [2] M. Palus, Entropy 16(10), 5263-5289 (2014) [3] M. Palus, Phys. Rev. Lett. 112, 078702 (2014)

Effects of changing climate on European stream invertebrate communities: A long-term data analysis.

PubMed

Jourdan, Jonas; O'Hara, Robert B; Bottarin, Roberta; Huttunen, Kaisa-Leena; Kuemmerlen, Mathias; Monteith, Don; Muotka, Timo; Ozoliņš, Dāvis; Paavola, Riku; Pilotto, Francesca; Springe, Gunta; Skuja, Agnija; Sundermann, Andrea; Tonkin, Jonathan D; Haase, Peter

2018-04-15

Long-term observations on riverine benthic invertebrate communities enable assessments of the potential impacts of global change on stream ecosystems. Besides increasing average temperatures, many studies predict greater temperature extremes and intense precipitation events as a consequence of climate change. In this study we examined long-term observation data (10-32years) of 26 streams and rivers from four ecoregions in the European Long-Term Ecological Research (LTER) network, to investigate invertebrate community responses to changing climatic conditions. We used functional trait and multi-taxonomic analyses and combined examinations of general long-term changes in communities with detailed analyses of the impact of different climatic drivers (i.e., various temperature and precipitation variables) by focusing on the response of communities to climatic conditions of the previous year. Taxa and ecoregions differed substantially in their response to climate change conditions. We did not observe any trend of changes in total taxonomic richness or overall abundance over time or with increasing temperatures, which reflects a compensatory turnover in the composition of communities; sensitive Plecoptera decreased in response to warmer years and Ephemeroptera increased in northern regions. Invasive species increased with an increasing number of extreme days which also caused an apparent upstream community movement. The observed changes in functional feeding group diversity indicate that climate change may be associated with changes in trophic interactions within aquatic food webs. These findings highlight the vulnerability of riverine ecosystems to climate change and emphasize the need to further explore the interactive effects of climate change variables with other local stressors to develop appropriate conservation measures. Copyright © 2017 Elsevier B.V. All rights reserved.

Large-Scale Circulation and Climate Variability. Chapter 5

NASA Technical Reports Server (NTRS)

Perlwitz, J.; Knutson, T.; Kossin, J. P.; LeGrande, A. N.

2017-01-01

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

Inferring climate variability from skewed proxy records

NASA Astrophysics Data System (ADS)

Emile-Geay, J.; Tingley, M.

2013-12-01

Many paleoclimate analyses assume a linear relationship between the proxy and the target climate variable, and that both the climate quantity and the errors follow normal distributions. An ever-increasing number of proxy records, however, are better modeled using distributions that are heavy-tailed, skewed, or otherwise non-normal, on account of the proxies reflecting non-normally distributed climate variables, or having non-linear relationships with a normally distributed climate variable. The analysis of such proxies requires a different set of tools, and this work serves as a cautionary tale on the danger of making conclusions about the underlying climate from applications of classic statistical procedures to heavily skewed proxy records. Inspired by runoff proxies, we consider an idealized proxy characterized by a nonlinear, thresholded relationship with climate, and describe three approaches to using such a record to infer past climate: (i) applying standard methods commonly used in the paleoclimate literature, without considering the non-linearities inherent to the proxy record; (ii) applying a power transform prior to using these standard methods; (iii) constructing a Bayesian model to invert the mechanistic relationship between the climate and the proxy. We find that neglecting the skewness in the proxy leads to erroneous conclusions and often exaggerates changes in climate variability between different time intervals. In contrast, an explicit treatment of the skewness, using either power transforms or a Bayesian inversion of the mechanistic model for the proxy, yields significantly better estimates of past climate variations. We apply these insights in two paleoclimate settings: (1) a classical sedimentary record from Laguna Pallcacocha, Ecuador (Moy et al., 2002). Our results agree with the qualitative aspects of previous analyses of this record, but quantitative departures are evident and hold implications for how such records are interpreted, and

The role of early visual cortex in visual short-term memory and visual attention.

PubMed

Offen, Shani; Schluppeck, Denis; Heeger, David J

2009-06-01

We measured cortical activity with functional magnetic resonance imaging to probe the involvement of early visual cortex in visual short-term memory and visual attention. In four experimental tasks, human subjects viewed two visual stimuli separated by a variable delay period. The tasks placed differential demands on short-term memory and attention, but the stimuli were visually identical until after the delay period. Early visual cortex exhibited sustained responses throughout the delay when subjects performed attention-demanding tasks, but delay-period activity was not distinguishable from zero when subjects performed a task that required short-term memory. This dissociation reveals different computational mechanisms underlying the two processes.

Gender-specific responses to climate variability in a semi-arid ecosystem in northern Benin.

PubMed

Dah-Gbeto, Afiavi P; Villamor, Grace B

2016-12-01

Highly erratic rainfall patterns in northern Benin complicate the ability of rural farmers to engage in subsistence agriculture. This research explores gender-specific responses to climate variability in the context of agrarian Benin through a household survey (n = 260) and an experimental gaming exercise among a subset of the survey respondents. Although men and women from the sample population are equally aware of climate variability and share similar coping strategies, their specific land-use strategies, preferences, and motivations are distinct. Over the long term, these differences would likely lead to dissimilar coping strategies and vulnerability to the effects of climate change. Examination of gender-specific land-use responses to climate change and anticipatory learning can enhance efforts to improve adaptability and resilience among rural subsistence farmers.

Assessing the climate-scale variability of atmospheric rivers affecting western North America

NASA Astrophysics Data System (ADS)

Gershunov, Alexander; Shulgina, Tamara; Ralph, F. Martin; Lavers, David A.; Rutz, Jonathan J.

2017-08-01

A new method for automatic detection of atmospheric rivers (ARs) is developed and applied to an atmospheric reanalysis, yielding an extensive catalog of ARs land-falling along the west coast of North America during 1948-2017. This catalog provides a large array of variables that can be used to examine AR cases and their climate-scale variability in exceptional detail. The new record of AR activity, as presented, validated and examined here, provides a perspective on the seasonal cycle and the interannual-interdecadal variability of AR activity affecting the hydroclimate of western North America. Importantly, AR intensity does not exactly follow the climatological pattern of AR frequency. Strong links to hydroclimate are demonstrated using a high-resolution precipitation data set. We describe the seasonal progression of AR activity and diagnose linkages with climate variability expressed in Pacific sea surface temperatures, revealing links to Pacific decadal variability, recent regional anomalies, as well as a generally rising trend in land-falling AR activity. The latter trend is consistent with a long-term increase in vapor transport from the warming North Pacific onto the North American continent. The new catalog provides unprecedented opportunities to study the climate-scale behavior and predictability of ARs affecting western North America.

A first look at global flash drought: long term change and short term predictability

NASA Astrophysics Data System (ADS)

Yuan, Xing; Wang, Linying; Ji, Peng

2017-04-01

"Flash drought" became popular after the unexpected 2012 central USA drought, mainly due to its rapid development, low predictability and devastating impacts on water resources and crop yields. A pilot study by Mo and Lettenmaier (2015) found that flash drought, based on a definition of concurrent heat extreme, soil moisture deficit and evapotranspiration (ET) enhancement at pentad scale, were in decline over USA during recent 100 years. Meanwhile, a recent work indicated that the occurrence of flash drought in China was doubled during the past 30 years, where a severe flash drought in the summer of 2013 ravaged 13 provinces in southern China. As global warming increases the frequency of heat waves and accelerates the hydrological cycle, the flash drought is expected to increase in general, but its trend might also be affected by interannual to decadal climate oscillations. To consolidate the hotspots of flash drought and the effects of climate change on flash drought, a global inventory is being conducted by using multi-source observations (in-situ, satellite and reanalysis), CMIP5 historical simulations and future projections under different forcing scenarios, as well as global land surface hydrological modeling for key variables including surface air temperature, soil moisture and ET. In particular, a global picture of the flash drought distribution, the contribution of naturalized and anthropogenic forcings to global flash drought change, and the risk of global flash drought in the future, will be presented. Besides investigating the long-term change of flash drought, providing reliable early warning is also essential to developing adaptation strategies. While regional drought early warning systems have been emerging in recent decade, forecasting of flash drought is still at an exploratory stage due to limited understanding of flash drought predictability. Here, a set of sub-seasonal to seasonal (S2S) hindcast datasets are being used to assess the short term

Seasonal controls of the short term variability of pCO2 at the Scotian Shelf

NASA Astrophysics Data System (ADS)

Thomas, H.; Craig, S.; Greenan, B. J. W.; Burt, W.; Herndl, G. J.; Higginson, S.; Salt, L.; Shadwick, E. H.; Urrego-Blanco, J.

2012-04-01

Much of the surface ocean carbon cycle variability can be attributed to the availability of sunlight, through processes such as heat fluxes or photosynthesis, which regulate the ocean carbon cycle over a wide range of time scales. The critical processes occurring on timescales of a day or less, however, have undergone few investigations, and most of those have been limited to a time span of several days to months, or exceptionally, for longer periods. Optical methods have helped to infer short-term biological variability, however lacking corresponding investigations of oceanic CO2 system. Here, we employ high-frequency CO2 system and optical observations covering the full seasonal cycle on the Scotian Shelf, Northwestern Atlantic Ocean, in order to unravel daily periodicity of the surface ocean carbon cycle and its effects on annual budgets. We show that significant daily periodicity occurs only if the water column is sufficiently stable as observed during seasonal warming. During that time biological CO2 drawdown, or net community production (NCP), is delayed for several hours relative to the daylight cycle due the daily build-up of essential Chlorophyll a, to cell physiology and to grazing effects, all restricting or hindering photosynthesis in the early morning hours. NCP collapses in summer by more than 90%, when the mixed layer depth reaches the seasonal minimum, which eventually makes the observed daily periodicity of the CO2 system vanish.

Linking Short and Long Term Sediment Delivery to Morphology and Seascape Evolution of Continental Margins

DTIC Science & Technology

1999-09-30

history. OBJECTIVES 1) Is the variability in a river’s sediment load, observed over the last 100 years or less, adequate to provide a proxy for longer-term...experiments, small basins are able to capture in terms of textural proxies , both the natural variability associated with precipitation and temperature...as well as realistic scenarios of abrupt climate change. Open ocean basins, like the Eel River, are less likely to record the proxy record of ambient

What are the differences between long-term, short-term, and working memory?

PubMed Central

Cowan, Nelson

2008-01-01

In the recent literature there has been considerable confusion about the three types of memory: long-term, short-term, and working memory. This chapter strives to reduce that confusion and makes up-to-date assessments of these types of memory. Long- and short-term memory could differ in two fundamental ways, with only short-term memory demonstrating (1) temporal decay and (2) chunk capacity limits. Both properties of short-term memory are still controversial but the current literature is rather encouraging regarding the existence of both decay and capacity limits. Working memory has been conceived and defined in three different, slightly discrepant ways: as short-term memory applied to cognitive tasks, as a multi-component system that holds and manipulates information in short-term memory, and as the use of attention to manage short-term memory. Regardless of the definition, there are some measures of memory in the short term that seem routine and do not correlate well with cognitive aptitudes and other measures (those usually identified with the term “working memory”) that seem more attention demanding and do correlate well with these aptitudes. The evidence is evaluated and placed within a theoretical framework depicted in Fig. 1. PMID:18394484

The Demonstration of Short-Term Consolidation.

ERIC Educational Resources Information Center

Jolicoeur, Pierre; Dell'Acqua, Roberto

1998-01-01

Results of seven experiments involving 112 college students or staff using a dual-task approach provide evidence that encoding information into short-term memory involves a distinct process termed short-term consolidation (STC). Results suggest that STC has limited capacity and that it requires central processing mechanisms. (SLD)

Exploring the impact of climate variability during the Last Glacial Maximum on the pattern of human occupation of Iberia.

PubMed

Burke, Ariane; Levavasseur, Guillaume; James, Patrick M A; Guiducci, Dario; Izquierdo, Manuel Arturo; Bourgeon, Lauriane; Kageyama, Masa; Ramstein, Gilles; Vrac, Mathieu

2014-08-01

The Last Glacial Maximum (LGM) was a global climate event, which had significant repercussions for the spatial distribution and demographic history of prehistoric populations. In Eurasia, the LGM coincides with a potential bottleneck for modern humans and may mark the divergence date for Asian and European populations (Keinan et al., 2007). In this research, the impact of climate variability on human populations in the Iberian Peninsula during the Last Glacial Maximum (LGM) is examined with the aid of downscaled high-resolution (16 × 16 km) numerical climate experiments. Human sensitivity to short time-scale (inter-annual) climate variability during this key time period, which follows the initial modern human colonisation of Eurasia and the extinction of the Neanderthals, is tested using the spatial distribution of archaeological sites. Results indicate that anatomically modern human populations responded to small-scale spatial patterning in climate variability, specifically inter-annual variability in precipitation levels as measured by the standard precipitation index. Climate variability at less than millennial scale, therefore, is shown to be an important component of ecological risk, one that played a role in regulating the spatial behaviour of prehistoric human populations and consequently affected their social networks. Copyright © 2014 Elsevier Ltd. All rights reserved.

Using an improved understanding of current climate variability to develop increased drought resilience in UK irrigated agriculture

NASA Astrophysics Data System (ADS)

Holman, I.; Rey Vicario, D.

2016-12-01

Improving community preparedness for climate change can be supported by developing resilience to past events, focused on those changes of particular relevance (such as floods and droughts). However, communities' perceptions of impacts and risk can be influenced by an incomplete appreciation of historical baseline climate variability. This can arise from a number of factors including individual's age, access to long term data records and availability of local knowledge. For example, the most significant recent drought in the UK occurred in 1976/77 but does it represent the worst drought that did occur (or could have occurred) without climate change? We focus on the east of England where most irrigated agriculture is located and where many local farmers interviewed were either not in business then or have an incomplete memory of the impacts of the drought. This paper describes a comparison of an annual agroclimatic indicator closely linked to irrigation demand (maximum Potential Soil Moisture Deficit) calculated from three sources of long term observational and simulated historical weather data with recent data. These long term datasets include gridded measured / calculated datasets of precipitation and reference evapotranspiration; a dynamically downscaled 20th Century Re-analysis dataset, and two Regional Climate Model ensemble datasets (FutureFlows and the MaRIUS event set) which each provide between 110 and 3000 years of baseline weather. The comparison shows that the long term datasets provide a wider characterisation of current climate variability and affect the perception of current drought frequency and severity. The paper will show that using a more comprehensive understanding of current climate variability and drought risk as a basis for adapting irrigated systems to droughts can provide substantial increased resilience to (uncertain) climate change.

Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

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

Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef

Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth’s climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modesmore » and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this article, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.« less

Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

DOE PAGES

Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef; ...

2016-10-04

Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth’s climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modesmore » and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this article, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.« less

Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

NASA Astrophysics Data System (ADS)

Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef; Hu, Aixue; Hamlington, Benjamin; Kenigson, Jessica; Palanisamy, Hindumathi; Thompson, Philip

2017-01-01

Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth's climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modes and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this paper, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.

Do bioclimate variables improve performance of climate envelope models?

USGS Publications Warehouse

Watling, James I.; Romañach, Stephanie S.; Bucklin, David N.; Speroterra, Carolina; Brandt, Laura A.; Pearlstine, Leonard G.; Mazzotti, Frank J.

2012-01-01

Climate envelope models are widely used to forecast potential effects of climate change on species distributions. A key issue in climate envelope modeling is the selection of predictor variables that most directly influence species. To determine whether model performance and spatial predictions were related to the selection of predictor variables, we compared models using bioclimate variables with models constructed from monthly climate data for twelve terrestrial vertebrate species in the southeastern USA using two different algorithms (random forests or generalized linear models), and two model selection techniques (using uncorrelated predictors or a subset of user-defined biologically relevant predictor variables). There were no differences in performance between models created with bioclimate or monthly variables, but one metric of model performance was significantly greater using the random forest algorithm compared with generalized linear models. Spatial predictions between maps using bioclimate and monthly variables were very consistent using the random forest algorithm with uncorrelated predictors, whereas we observed greater variability in predictions using generalized linear models.

Changing flood frequencies under opposing late Pleistocene eastern Mediterranean climates.

PubMed

Ben Dor, Yoav; Armon, Moshe; Ahlborn, Marieke; Morin, Efrat; Erel, Yigal; Brauer, Achim; Schwab, Markus Julius; Tjallingii, Rik; Enzel, Yehouda

2018-05-31

Floods comprise a dominant hydroclimatic phenomenon in aridlands with significant implications for humans, infrastructure, and landscape evolution worldwide. The study of short-term hydroclimatic variability, such as floods, and its forecasting for episodes of changing climate therefore poses a dominant challenge for the scientific community, and predominantly relies on modeling. Testing the capabilities of climate models to properly describe past and forecast future short-term hydroclimatic phenomena such as floods requires verification against suitable geological archives. However, determining flood frequency during changing climate is rarely achieved, because modern and paleoflood records, especially in arid regions, are often too short or discontinuous. Thus, coeval independent climate reconstructions and paleoflood records are required to further understand the impact of climate change on flood generation. Dead Sea lake levels reflect the mean centennial-millennial hydrological budget in the eastern Mediterranean. In contrast, floods in the large watersheds draining directly into the Dead Sea, are linked to short-term synoptic circulation patterns reflecting hydroclimatic variability. These two very different records are combined in this study to resolve flood frequency during opposing mean climates. Two 700-year-long, seasonally-resolved flood time series constructed from late Pleistocene Dead Sea varved sediments, coeval with significant Dead Sea lake level variations are reported. These series demonstrate that episodes of rising lake levels are characterized by higher frequency of floods, shorter intervals between years of multiple floods, and asignificantly larger number of years that experienced multiple floods. In addition, floods cluster into intervals of intense flooding, characterized by 75% and 20% increased frequency above their respective background frequencies during rising and falling lake-levels, respectively. Mean centennial precipitation in

Short-term heart rate variability in dogs with sick sinus syndrome or chronic mitral valve disease as compared to healthy controls.

PubMed

Bogucki, Sz; Noszczyk-Nowak, A

2017-03-28

Heart rate variability is an established risk factor for mortality in both healthy dogs and animals with heart failure. The aim of this study was to compare short-term heart rate variability (ST-HRV) parameters from 60-min electrocardiograms in dogs with sick sinus syndrome (SSS, n=20) or chronic mitral valve disease (CMVD, n=20) and healthy controls (n=50), and to verify the clinical application of ST-HRV analysis. The study groups differed significantly in terms of both time - and frequency- domain ST-HRV parameters. In the case of dogs with SSS and healthy controls, particularly evident differences pertained to HRV parameters linked directly to the variability of R-R intervals. Lower values of standard deviation of all R-R intervals (SDNN), standard deviation of the averaged R-R intervals for all 5-min segments (SDANN), mean of the standard deviations of all R-R intervals for all 5-min segments (SDNNI) and percentage of successive R-R intervals >50 ms (pNN50) corresponded to a decrease in parasympathetic regulation of heart rate in dogs with CMVD. These findings imply that ST-HRV may be useful for the identification of dogs with SSS and for detection of dysautonomia in animals with CMVD.

Interannual and seasonal variability in short-term grazing impact of Euphausia superba in nearshore and offshore waters west of the Antarctic Peninsula

NASA Astrophysics Data System (ADS)

Ross, R. M.; Quetin, L. B.; Haberman, K. L.

1998-11-01

Our focus in this paper is the interaction between macrozooplanktonic grazers and primary producers, and the interannual and seasonal variability in the Palmer Long-Term Ecological Research (Palmer LTER) study region from Anvers Island to Adelaide Island. Short-term grazing estimates are calculated by integrating (1) theoretical and experimental estimates of ingestion rates in response to the standing stock of phytoplankton, and (2) field measurements of phytoplankton standing stock and grazer biomass. Field data come from three austral summer cruises (January/February of 1993, 1994, and 1995) and one sequence of seasonal cruises (summer, fall and winter 1993). The relative and absolute abundance of the dominant macrozooplankton grazers, Euphausia superba and Salpa thompsoni, varied by at least an order of magnitude on the spatial and temporal scales observed. Mean grazing rates ranged from 0.4 to 9.0 μg chlorophyll m -2 h -1 for the Antarctic krill and salp populations over the three summer cruises. This leads to variability in the flow of carbon from the primary producers through the grazers on the same scales. Temporal and spatial variability in grazing impact and faecal pellet production are high.

Climatic variability in Princess Elizabeth Land (East Antarctica) over the last 350 years

NASA Astrophysics Data System (ADS)

Ekaykin, Alexey A.; Vladimirova, Diana O.; Lipenkov, Vladimir Y.; Masson-Delmotte, Valérie

2017-01-01

We use isotopic composition (δD) data from six sites in Princess Elizabeth Land (PEL) in order to reconstruct air temperature variability in this sector of East Antarctica over the last 350 years. First, we use the present-day instrumental mean annual surface air temperature data to demonstrate that the studied region (between Russia's Progress, Vostok and Mirny research stations) is characterized by uniform temperature variability. We thus construct a stacked record of the temperature anomaly for the whole sector for the period of 1958-2015. A comparison of this series with the Southern Hemisphere climatic indices shows that the short-term inter-annual temperature variability is primarily governed by the Antarctic Oscillation (AAO) and Interdecadal Pacific Oscillation (IPO) modes of atmospheric variability. However, the low-frequency temperature variability (with period > 27 years) is mainly related to the anomalies of the Indian Ocean Dipole (IOD) mode. We then construct a stacked record of δD for the PEL for the period of 1654-2009 from individual normalized and filtered isotopic records obtained at six different sites (PEL2016 stacked record). We use a linear regression of this record and the stacked PEL temperature record (with an apparent slope of 9 ± 5.4 ‰ °C-1) to convert PEL2016 into a temperature scale. Analysis of PEL2016 shows a 1 ± 0.6 °C warming in this region over the last 3 centuries, with a particularly cold period from the mid-18th to the mid-19th century. A peak of cooling occurred in the 1840s - a feature previously observed in other Antarctic records. We reveal that PEL2016 correlates with a low-frequency component of IOD and suggest that the IOD mode influences the Antarctic climate by modulating the activity of cyclones that bring heat and moisture to Antarctica. We also compare PEL2016 with other Antarctic stacked isotopic records. This work is a contribution to the PAGES (Past Global Changes) and IPICS (International

The rise of the mediocre forest: why chronically stressed trees may better survive extreme episodic climate variability

Treesearch

Steven G. McNulty; Johnny L. Boggs; Ge Sun

2014-01-01

Anthropogenic climate change is a relatively new phenomenon, largely occurring over the past 150 years, and much of the discussion on climate change impacts to forests has focused on long-term shifts in temperature and precipitation. However, individual trees respond to the much shorter impacts of climate variability. Historically, fast growing, fully canopied, non-...

Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability.

PubMed

Booth, Ben B B; Dunstone, Nick J; Halloran, Paul R; Andrews, Timothy; Bellouin, Nicolas

2012-04-04

Systematic climate shifts have been linked to multidecadal variability in observed sea surface temperatures in the North Atlantic Ocean. These links are extensive, influencing a range of climate processes such as hurricane activity and African Sahel and Amazonian droughts. The variability is distinct from historical global-mean temperature changes and is commonly attributed to natural ocean oscillations. A number of studies have provided evidence that aerosols can influence long-term changes in sea surface temperatures, but climate models have so far failed to reproduce these interactions and the role of aerosols in decadal variability remains unclear. Here we use a state-of-the-art Earth system climate model to show that aerosol emissions and periods of volcanic activity explain 76 per cent of the simulated multidecadal variance in detrended 1860-2005 North Atlantic sea surface temperatures. After 1950, simulated variability is within observational estimates; our estimates for 1910-1940 capture twice the warming of previous generation models but do not explain the entire observed trend. Other processes, such as ocean circulation, may also have contributed to variability in the early twentieth century. Mechanistically, we find that inclusion of aerosol-cloud microphysical effects, which were included in few previous multimodel ensembles, dominates the magnitude (80 per cent) and the spatial pattern of the total surface aerosol forcing in the North Atlantic. Our findings suggest that anthropogenic aerosol emissions influenced a range of societally important historical climate events such as peaks in hurricane activity and Sahel drought. Decadal-scale model predictions of regional Atlantic climate will probably be improved by incorporating aerosol-cloud microphysical interactions and estimates of future concentrations of aerosols, emissions of which are directly addressable by policy actions.

Projected climate change impacts and short term predictions on staple crops in Sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Mereu, V.; Spano, D.; Gallo, A.; Carboni, G.

2013-12-01

Agriculture in Sub-Saharan Africa (SSA) drives the economy of many African countries and it is mainly rain-fed agriculture used for subsistence. Increasing temperatures, changed precipitation patterns and more frequent droughts may lead to a substantial decrease of crop yields. The projected impacts of future climate change on agriculture are expected to be significant and extensive in the SSA due to the shortening of the growing seasons and the increasing of water-stress risk. Differences in Agro-Ecological Zones and geographical characteristics of SSA influence the diverse impacts of climate change, which can greatly differ across the continent and within countries. The vulnerability of African Countries to climate change is aggravated by the low adaptive capacity of the continent, due to the increasing of its population, the widespread poverty, and other social factors. In this contest, the assessment of climate change impact on agricultural sector has a particular interest to stakeholder and policy makers, in order to identify specific agricultural sectors and Agro-Ecological Zones that could be more vulnerable to changes in climatic conditions and to develop the most appropriate policies to cope with these threats. For these reasons, the evaluation of climate change impacts for key crops in SSA was made exploring climate uncertainty and focusing on short period monitoring, which is particularly useful for food security and risk management analysis. The DSSAT-CSM (Decision Support System for Agrotechnology Transfer - Cropping System Model) software, version 4.5 was used for the analysis. Crop simulation models included in DSSAT-CSM are tools that allow to simulate physiological process of crop growth, development and production, by combining genetic crop characteristics and environmental (soil and weather) conditions. For each selected crop, the models were used, after a parameterization phase, to evaluate climate change impacts on crop phenology and production

Short-term variability in body weight predicts long-term weight gain.

PubMed

Lowe, Michael R; Feig, Emily H; Winter, Samantha R; Stice, Eric

2015-11-01

Body weight in lower animals and humans is highly stable despite a very large flux in energy intake and expenditure over time. Conversely, the existence of higher-than-average variability in weight may indicate a disruption in the mechanisms responsible for homeostatic weight regulation. In a sample chosen for weight-gain proneness, we evaluated whether weight variability over a 6-mo period predicted subsequent weight change from 6 to 24 mo. A total of 171 nonobese women were recruited to participate in this longitudinal study in which weight was measured 4 times over 24 mo. The initial 3 weights were used to calculate weight variability with the use of a root mean square error approach to assess fluctuations in weight independent of trajectory. Linear regression analysis was used to examine whether weight variability in the initial 6 mo predicted weight change 18 mo later. Greater weight variability significantly predicted amount of weight gained. This result was unchanged after control for baseline body mass index (BMI) and BMI change from baseline to 6 mo and for measures of disinhibition, restrained eating, and dieting. Elevated weight variability in young women may signal the degradation of body weight regulatory systems. In an obesogenic environment this may eventuate in accelerated weight gain, particularly in those with a genetic susceptibility toward overweight. Future research is needed to evaluate the reliability of weight variability as a predictor of future weight gain and the sources of its predictive effect. The trial on which this study is based is registered at clinicaltrials.gov as NCT00456131. © 2015 American Society for Nutrition.

Potential Impact of North Atlantic Climate Variability on Ocean Biogeochemical Processes

NASA Astrophysics Data System (ADS)

Liu, Y.; Muhling, B.; Lee, S. K.; Muller-Karger, F. E.; Enfield, D. B.; Lamkin, J. T.; Roffer, M. A.

2016-02-01

Previous studies have shown that upper ocean circulations largely determine primary production in the euphotic layers, here the global ocean model with biogeochemistry (GFDL's Modular Ocean Model with TOPAZ biogeochemistry) forced with the ERA-Interim is used to simulate the natural variability of biogeochemical processes in global ocean during 1979-present. Preliminary results show that the surface chlorophyll is overall underestimated in MOM-TOPAZ, but its spatial pattern is fairly realistic. Relatively high chlorophyll variability is shown in the subpolar North Atlantic, northeastern tropical Atlantic, and equatorial Atlantic. Further analysis suggests that the chlorophyll variability in the North Atlantic Ocean is affected by long-term climate variability. For the subpolar North Atlantic region, the chlorophyll variability is light-limited and is significantly correlated with North Atlantic Oscillation. A dipole pattern of chlorophyll variability is found between the northeastern tropical Atlantic and equatorial Atlantic. For the northeastern North Atlantic, the chlorophyll variability is significantly correlated with Atlantic Meridional Mode (AMM) and Atlantic Multidecadal Oscillation (AMO). During the negative phase of AMM and AMO, the increased trade wind in the northeast North Atlantic can lead to increased upwelling of nutrients. In the equatorial Atlantic region, the chlorophyll variability is largely link to Atlantic-Niño and associated equatorial upwelling of nutrients. The potential impact of climate variability on the distribution of pelagic fishes (i.e. yellowfin tuna) are discussed.

Urban green land cover changes and their relation to climatic variables in an anthropogenically impacted area

NASA Astrophysics Data System (ADS)

Zoran, Maria A.; Dida, Adrian I.

2017-10-01

Urban green areas are experiencing rapid land cover change caused by human-induced land degradation and extreme climatic events. Vegetation index time series provide a useful way to monitor urban vegetation phenological variations. This study quantitatively describes Normalized Difference Vegetation Index NDVI) /Enhanced Vegetation Index (EVI) and Leaf Area Index (LAI) temporal changes for Bucharest metropolitan region land cover in Romania from the perspective of vegetation phenology and its relation with climate changes and extreme climate events. The time series from 2000 to 2016 of the NOAA AVHRR and MODIS Terra/Aqua satellite data were analyzed to extract anomalies. Time series of climatic variables were also analyzed through anomaly detection techniques and the Fourier Transform. Correlations between NDVI/EVI time series and climatic variables were computed. Temperature, rainfall and radiation were significantly correlated with almost all land-cover classes for the harmonic analysis amplitude term. However, vegetation phenology was not correlated with climatic variables for the harmonic analysis phase term suggesting a delay between climatic variations and vegetation response. Training and validation were based on a reference dataset collected from IKONOS high resolution remote sensing data. The mean detection accuracy for period 2000- 2016 was assessed to be of 87%, with a reasonable balance between change commission errors (19.3%), change omission errors (24.7%), and Kappa coefficient of 0.73. This paper demonstrates the potential of moderate - and high resolution, multispectral imagery to map and monitor the evolution of the physical urban green land cover under climate and anthropogenic pressure.

Land plants and DNA barcodes: short-term and long-term goals.

PubMed

Chase, Mark W; Salamin, Nicolas; Wilkinson, Mike; Dunwell, James M; Kesanakurthi, Rao Prasad; Haider, Nadia; Haidar, Nadia; Savolainen, Vincent

2005-10-29

Land plants have had the reputation of being problematic for DNA barcoding for two general reasons: (i) the standard DNA regions used in algae, animals and fungi have exceedingly low levels of variability and (ii) the typically used land plant plastid phylogenetic markers (e.g. rbcL, trnL-F, etc.) appear to have too little variation. However, no one has assessed how well current phylogenetic resources might work in the context of identification (versus phylogeny reconstruction). In this paper, we make such an assessment, particularly with two of the markers commonly sequenced in land plant phylogenetic studies, plastid rbcL and internal transcribed spacers of the large subunits of nuclear ribosomal DNA (ITS), and find that both of these DNA regions perform well even though the data currently available in GenBank/EBI were not produced to be used as barcodes and BLAST searches are not an ideal tool for this purpose. These results bode well for the use of even more variable regions of plastid DNA (such as, for example, psbA-trnH) as barcodes, once they have been widely sequenced. In the short term, efforts to bring land plant barcoding up to the standards being used now in other organisms should make swift progress. There are two categories of DNA barcode users, scientists in fields other than taxonomy and taxonomists. For the former, the use of mitochondrial and plastid DNA, the two most easily assessed genomes, is at least in the short term a useful tool that permits them to get on with their studies, which depend on knowing roughly which species or species groups they are dealing with, but these same DNA regions have important drawbacks for use in taxonomic studies (i.e. studies designed to elucidate species limits). For these purposes, DNA markers from uniparentally (usually maternally) inherited genomes can only provide half of the story required to improve taxonomic standards being used in DNA barcoding. In the long term, we will need to develop more

Land plants and DNA barcodes: short-term and long-term goals

PubMed Central

Chase, Mark W; Salamin, Nicolas; Wilkinson, Mike; Dunwell, James M; Kesanakurthi, Rao Prasad; Haidar, Nadia; Savolainen, Vincent

2005-01-01

Land plants have had the reputation of being problematic for DNA barcoding for two general reasons: (i) the standard DNA regions used in algae, animals and fungi have exceedingly low levels of variability and (ii) the typically used land plant plastid phylogenetic markers (e.g. rbcL, trnL-F, etc.) appear to have too little variation. However, no one has assessed how well current phylogenetic resources might work in the context of identification (versus phylogeny reconstruction). In this paper, we make such an assessment, particularly with two of the markers commonly sequenced in land plant phylogenetic studies, plastid rbcL and internal transcribed spacers of the large subunits of nuclear ribosomal DNA (ITS), and find that both of these DNA regions perform well even though the data currently available in GenBank/EBI were not produced to be used as barcodes and BLAST searches are not an ideal tool for this purpose. These results bode well for the use of even more variable regions of plastid DNA (such as, for example, psbA-trnH) as barcodes, once they have been widely sequenced. In the short term, efforts to bring land plant barcoding up to the standards being used now in other organisms should make swift progress. There are two categories of DNA barcode users, scientists in fields other than taxonomy and taxonomists. For the former, the use of mitochondrial and plastid DNA, the two most easily assessed genomes, is at least in the short term a useful tool that permits them to get on with their studies, which depend on knowing roughly which species or species groups they are dealing with, but these same DNA regions have important drawbacks for use in taxonomic studies (i.e. studies designed to elucidate species limits). For these purposes, DNA markers from uniparentally (usually maternally) inherited genomes can only provide half of the story required to improve taxonomic standards being used in DNA barcoding. In the long term, we will need to develop more

Climate variability slows evolutionary responses of Colias butterflies to recent climate change.

PubMed

Kingsolver, Joel G; Buckley, Lauren B

2015-03-07

How does recent climate warming and climate variability alter fitness, phenotypic selection and evolution in natural populations? We combine biophysical, demographic and evolutionary models with recent climate data to address this question for the subalpine and alpine butterfly, Colias meadii, in the southern Rocky Mountains. We focus on predicting patterns of selection and evolution for a key thermoregulatory trait, melanin (solar absorptivity) on the posterior ventral hindwings, which affects patterns of body temperature, flight activity, adult and egg survival, and reproductive success in Colias. Both mean annual summer temperatures and thermal variability within summers have increased during the past 60 years at subalpine and alpine sites. At the subalpine site, predicted directional selection on wing absorptivity has shifted from generally positive (favouring increased wing melanin) to generally negative during the past 60 years, but there is substantial variation among years in the predicted magnitude and direction of selection and the optimal absorptivity. The predicted magnitude of directional selection at the alpine site declined during the past 60 years and varies substantially among years, but selection has generally been positive at this site. Predicted evolutionary responses to mean climate warming at the subalpine site since 1980 is small, because of the variability in selection and asymmetry of the fitness function. At both sites, the predicted effects of adaptive evolution on mean population fitness are much smaller than the fluctuations in mean fitness due to climate variability among years. Our analyses suggest that variation in climate within and among years may strongly limit evolutionary responses of ectotherms to mean climate warming in these habitats. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Short-term memory across eye blinks.

PubMed

Irwin, David E

2014-01-01

The effect of eye blinks on short-term memory was examined in two experiments. On each trial, participants viewed an initial display of coloured, oriented lines, then after a retention interval they viewed a test display that was either identical or different by one feature. Participants kept their eyes open throughout the retention interval on some blocks of trials, whereas on others they made a single eye blink. Accuracy was measured as a function of the number of items in the display to determine the capacity of short-term memory on blink and no-blink trials. In separate blocks of trials participants were instructed to remember colour only, orientation only, or both colour and orientation. Eye blinks reduced short-term memory capacity by approximately 0.6-0.8 items for both feature and conjunction stimuli. A third, control, experiment showed that a button press during the retention interval had no effect on short-term memory capacity, indicating that the effect of an eye blink was not due to general motoric dual-task interference. Eye blinks might instead reduce short-term memory capacity by interfering with attention-based rehearsal processes.

Short-term memory and dual task performance

NASA Technical Reports Server (NTRS)

Regan, J. E.

1982-01-01

Two hypotheses concerning the way in which short-term memory interacts with another task in a dual task situation are considered. It is noted that when two tasks are combined, the activity of controlling and organizing performance on both tasks simultaneously may compete with either task for a resource; this resource may be space in a central mechanism or general processing capacity or it may be some task-specific resource. If a special relationship exists between short-term memory and control, especially if there is an identity relationship between short-term and a central controlling mechanism, then short-term memory performance should show a decrement in a dual task situation. Even if short-term memory does not have any particular identity with a controlling mechanism, but both tasks draw on some common resource or resources, then a tradeoff between the two tasks in allocating resources is possible and could be reflected in performance. The persistent concurrence cost in memory performance in these experiments suggests that short-term memory may have a unique status in the information processing system.

LAMPPOST: A Mnemonic Device for Teaching Climate Variables

ERIC Educational Resources Information Center

Fahrer, Chuck; Harris, Dan

2004-01-01

This article introduces the word "LAMPPOST" as a mnemonic device to aid in the instruction of climate variables. It provides instructors with a framework for discussing climate patterns that is based on eight variables: latitude, altitude, maritime influence and continentality, pressure systems, prevailing winds, ocean currents, storms, and…

Making the best of climatic variability: options for upgrading rainfed farming in water scarce regions.

PubMed

Rockström, J

2004-01-01

Coping with climatic variability for livelihood security is part of everyday life for rural communities in semi-arid and dry sub-humid savannas. Water scarcity caused by rainfall fluctuations is common, causing meteorological droughts and dry spells. However, this paper indicates, based on experiences in sub-Saharan Africa and India, that the social impact on rural societies of climatically induced droughts is exaggerated. Instead, water scarcity causing food deficits is more often caused by management induced droughts and dry spells. A conceptual framework to distinguish between manageable and unmanageable droughts is presented. It is suggested that climatic droughts require focus on social resilience building instead of land and water resource management. Focus is then set on the manageable part of climatic variability, namely the almost annual occurrence of dry spells, short 2-4 week periods of no rainfall, affecting farmer yields. On-farm experiences in savannas of sub-Saharan Africa of water harvesting systems for dry spell mitigation are presented. It is shown that bridging dry spells combined with soil fertility management can double and even triple on-farm yield levels. Combined with innovative systems to ensure maximum plant water availability and water uptake capacity, through adoption of soil fertility improvement and conservation tillage systems, there is a clear opportunity to upgrade rainfed farming systems in vulnerable savanna environments, through appropriate local management of climatic variability.

Role of Satellite Rainfall Information in Improving Understanding of the Dynamical Link Between the Tropics and Extratropics Prospects of Improved Forecasts of Weather and Short-Term Climate Variability on Sub-Seasonal Time Scales

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.

2002-01-01

The tropics and extratropics are two dynamically distinct regimes. The coupling between these two regimes often defies simple analytical treatment. Progress in understanding of the dynamical interaction between the tropics and extratropics relies on better observational descriptions to guide theoretical development. However, global analyses currently contain significant errors in primary hydrological variables such as precipitation, evaporation, moisture, and clouds, especially in the tropics. Tropical analyses have been shown to be sensitive to parameterized precipitation processes, which are less than perfect, leading to order-one discrepancies between estimates produced by different data assimilation systems. One strategy for improvement is to assimilate rainfall observations to constrain the analysis and reduce uncertainties in variables physically linked to precipitation. At the Data Assimilation Office at the NASA Goddard Space Flight Center, we have been exploring the use of tropical rain rates derived from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments in global data assimilation. Results show that assimilating these data improves not only rainfall and moisture fields but also related climate parameters such as clouds and radiation, as well as the large-scale circulation and short-range forecasts. These studies suggest that assimilation of microwave rainfall observations from space has the potential to significantly improve the quality of 4-D assimilated datasets for climate investigations (Hou et al. 2001). In the next few years, there will be a gradual increase in microwave rain products available from operational and research satellites, culminating to a target constellation of 9 satellites to provide global rain measurements every 3 hours with the proposed Global Precipitation Measurement (GPM) mission in 2007. Continued improvements in assimilation methodology, rainfall error estimates, and model

Barriers to use of geospatial data for adaptation to climate change and variability: case studies in public health.

PubMed

Aron, Joan L

2006-11-01

This paper presents two case studies of the barriers to the use of geospatial data in the context of public health adaptation to climate change and variability. The first case study is on the hazards of coastal zone development in the United States with the main emphasis on Hurricane Katrina. An important barrier to the use of geospatial data is that the legal system does not support restrictions on land use intended to protect the coastal zone. Economic interests to develop New Orleans and the Mississippi River, both over the long term and the short term, had the effect of increasing the impact of the hurricane. The second case study is epidemics of climate-sensitive diseases with the main emphasis on malaria in Africa. Limits to model accuracy may present a problem in using climate data for an early warning system, and some geographic locations are likely to be more suitable than others. Costs of the system, including the costs of errors, may also inhibit implementation. Deriving societal benefits from geospatial data requires an understanding of the particular decision contexts and organizational processes in which knowledge is developed and used. The data by themselves will not usually generate a societal response. Scientists working in applications should develop partnerships to address the use of geospatial data for societal benefit.

Impact of Holocene climate variability on Arctic vegetation

NASA Astrophysics Data System (ADS)

Gajewski, K.

2015-10-01

This paper summarizes current knowledge about the postglacial history of the vegetation of the Canadian Arctic Archipelago (CAA) and Greenland. Available pollen data were used to understand the initial migration of taxa across the Arctic, how the plant biodiversity responded to Holocene climate variability, and how past climate variability affected primary production of the vegetation. Current evidence suggests that most of the flora arrived in the area during the Holocene from Europe or refugia south or west of the region immediately after local deglaciation, indicating rapid dispersal of propagules to the region from distant sources. There is some evidence of shrub species arriving later in Greenland, but it is not clear if this is dispersal limited or a response to past climates. Subsequent climate variability had little effect on biodiversity across the CAA, with some evidence of local extinctions in areas of Greenland in the late Holocene. The most significant impact of climate changes is on vegetation density and/or plant production.

Lessons Learned on Health Adaptation to Climate Variability and Change: Experiences Across Low- and Middle-Income Countries

PubMed Central

Otmani del Barrio, Mariam

2017-01-01

Background: There is limited published evidence of the effectiveness of adaptation in managing the health risks of climate variability and change in low- and middle-income countries. Objectives: To document lessons learned and good practice examples from health adaptation pilot projects in low- and middle-income countries to facilitate assessing and overcoming barriers to implementation and to scaling up. Methods: We evaluated project reports and related materials from the first five years of implementation (2008–2013) of multinational health adaptation projects in Albania, Barbados, Bhutan, China, Fiji, Jordan, Kazakhstan, Kenya, Kyrgyzstan, Philippines, Russian Federation, Tajikistan, and Uzbekistan. We also collected qualitative data through a focus group consultation and 19 key informant interviews. Results: Our recommendations include that national health plans, policies, and budget processes need to explicitly incorporate the risks of current and projected climate variability and change. Increasing resilience is likely to be achieved through longer-term, multifaceted, and collaborative approaches, with supporting activities (and funding) for capacity building, communication, and institutionalized monitoring and evaluation. Projects should be encouraged to focus not just on shorter-term outputs to address climate variability, but also on establishing processes to address longer-term climate change challenges. Opportunities for capacity development should be created, identified, and reinforced. Conclusions: Our analyses highlight that, irrespective of resource constraints, ministries of health and other institutions working on climate-related health issues in low- and middle-income countries need to continue to prepare themselves to prevent additional health burdens in the context of a changing climate and socioeconomic development patterns. https://doi.org/10.1289/EHP405 PMID:28632491

Stimulus-specific suppression preserves information in auditory short-term memory.

PubMed

Linke, Annika C; Vicente-Grabovetsky, Alejandro; Cusack, Rhodri

2011-08-02

Philosophers and scientists have puzzled for millennia over how perceptual information is stored in short-term memory. Some have suggested that early sensory representations are involved, but their precise role has remained unclear. The current study asks whether auditory cortex shows sustained frequency-specific activation while sounds are maintained in short-term memory using high-resolution functional MRI (fMRI). Investigating short-term memory representations within regions of human auditory cortex with fMRI has been difficult because of their small size and high anatomical variability between subjects. However, we overcame these constraints by using multivoxel pattern analysis. It clearly revealed frequency-specific activity during the encoding phase of a change detection task, and the degree of this frequency-specific activation was positively related to performance in the task. Although the sounds had to be maintained in memory, activity in auditory cortex was significantly suppressed. Strikingly, patterns of activity in this maintenance period correlated negatively with the patterns evoked by the same frequencies during encoding. Furthermore, individuals who used a rehearsal strategy to remember the sounds showed reduced frequency-specific suppression during the maintenance period. Although negative activations are often disregarded in fMRI research, our findings imply that decreases in blood oxygenation level-dependent response carry important stimulus-specific information and can be related to cognitive processes. We hypothesize that, during auditory change detection, frequency-specific suppression protects short-term memory representations from being overwritten by inhibiting the encoding of interfering sounds.

Surface Variability of Short-wavelength Radiation and Temperature on Exoplanets around M Dwarfs

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

Zhang, Xin; Tian, Feng; Wang, Yuwei

2017-03-10

It is a common practice to use 3D General Circulation Models (GCM) with spatial resolution of a few hundred kilometers to simulate the climate of Earth-like exoplanets. The enhanced albedo effect of clouds is especially important for exoplanets in the habitable zones around M dwarfs that likely have fixed substellar regions and substantial cloud coverage. Here, we carry out mesoscale model simulations with 3 km spatial resolution driven by the initial and boundary conditions in a 3D GCM and find that it could significantly underestimate the spatial variability of both the incident short-wavelength radiation and the temperature at planet surface.more » Our findings suggest that mesoscale models with cloud-resolving capability be considered for future studies of exoplanet climate.« less

Evaluating short-term hydro-meteorological fluxes using GRACE-derived water storage changes

NASA Astrophysics Data System (ADS)

Eicker, A.; Jensen, L.; Springer, A.; Kusche, J.

2017-12-01

Atmospheric and terrestrial water budgets, which represent important boundary conditions for both climate modeling and hydrological studies, are linked by evapotranspiration (E) and precipitation (P). These fields are provided by numerical weather prediction models and atmospheric reanalyses such as ERA-Interim and MERRA-Land; yet, in particular the quality of E is still not well evaluated. Via the terrestrial water budget equation, water storage changes derived from products of the Gravity Recovery and Climate Experiment (GRACE) mission, combined with runoff (R) data can be used to assess the realism of atmospheric models. In this contribution we will investigate the closure of the water balance for short-term fluxes, i.e. the agreement of GRACE water storage changes with P-E-R flux time series from different (global and regional) atmospheric reanalyses, land surface models, as well as observation-based data sets. Missing river runoff observations will be extrapolated using the calibrated rainfall-runoff model GR2M. We will perform a global analysis and will additionally focus on selected river basins in West Africa. The investigations will be carried out for various temporal scales, focusing on short-term fluxes down to daily variations to be detected in daily GRACE time series.

Increase of Short-Term Heart Rate Variability Induced by Blood Pressure Measurements during Ambulatory Blood Pressure Monitoring.

PubMed

Frigy, Attila; Magdás, Annamária; Moga, Victor-Dan; Coteț, Ioana Georgiana; Kozlovszky, Miklós; Szilágyi, László

2017-01-01

Objective. The possible effect of blood pressure measurements per se on heart rate variability (HRV) was studied in the setting of concomitant ambulatory blood pressure monitoring (ABPM) and Holter ECG monitoring (HM). Methods. In 25 hypertensive patients (14 women and 11 men, mean age: 58.1 years), 24-hour combined ABPM and HM were performed. For every blood pressure measurement, 2-minute ECG segments (before, during, and after measurement) were analyzed to obtain time domain parameters of HRV: SDNN and rMSSD. Mean of normal RR intervals (MNN), SDNN/MNN, and rMSSD/MNN were calculated, too. Parameter variations related to blood pressure measurements were analyzed using one-way ANOVA with multiple comparisons. Results. 2281 measurements (1518 during the day and 763 during the night) were included in the analysis. Both SDNN and SDNN/MNN had a constant (the same for 24-hour, daytime, and nighttime values) and significant change related to blood pressure measurements: an increase during measurements and a decrease after them ( p < 0.01 for any variation). Conclusion. In the setting of combined ABPM and HM, the blood pressure measurement itself produces an increase in short-term heart rate variability. Clarifying the physiological basis and the possible clinical value of this phenomenon needs further studies.

Sources and Impacts of Modeled and Observed Low-Frequency Climate Variability

NASA Astrophysics Data System (ADS)

Parsons, Luke Alexander

Here we analyze climate variability using instrumental, paleoclimate (proxy), and the latest climate model data to understand more about the sources and impacts of low-frequency climate variability. Understanding the drivers of climate variability at interannual to century timescales is important for studies of climate change, including analyses of detection and attribution of climate change impacts. Additionally, correctly modeling the sources and impacts of variability is key to the simulation of abrupt change (Alley et al., 2003) and extended drought (Seager et al., 2005; Pelletier and Turcotte, 1997; Ault et al., 2014). In Appendix A, we employ an Earth system model (GFDL-ESM2M) simulation to study the impacts of a weakening of the Atlantic meridional overturning circulation (AMOC) on the climate of the American Tropics. The AMOC drives some degree of local and global internal low-frequency climate variability (Manabe and Stouffer, 1995; Thornalley et al., 2009) and helps control the position of the tropical rainfall belt (Zhang and Delworth, 2005). We find that a major weakening of the AMOC can cause large-scale temperature, precipitation, and carbon storage changes in Central and South America. Our results suggest that possible future changes in AMOC strength alone will not be sufficient to drive a large-scale dieback of the Amazonian forest, but this key natural ecosystem is sensitive to dry-season length and timing of rainfall (Parsons et al., 2014). In Appendix B, we compare a paleoclimate record of precipitation variability in the Peruvian Amazon to climate model precipitation variability. The paleoclimate (Lake Limon) record indicates that precipitation variability in western Amazonia is 'red' (i.e., increasing variability with timescale). By contrast, most state-of-the-art climate models indicate precipitation variability in this region is nearly 'white' (i.e., equally variability across timescales). This paleo-model disagreement in the overall

High-altitude forest sensitivity to global warming: results from long-term and short-term analyses in the eastern italian alps

NASA Astrophysics Data System (ADS)

Carrer, Marco; Anfodillo, Tommaso; Urbinati, Carlo; Carraro, Vinicio

Dendroecological (long-term) analysis and ecophysiological (short-term) monitoring were used interactively to study the responses of tree-ring growth to climate in timberline mixed forests (consisting of Larix decidua Mill., Picea abies (L.) Karst. and Pinus cembra (L.)) in the Italian Eastern Alps (2000-2100 m a.s.l.). Climate-growth linear response functions (LRF) revealed that warm temperatures in June and July have a positive effect on radial growth whereas precipitation during the vegetation period has no effect. Monitoring of the intra-annual radial growth dynamics using band dendrometers confirmed that the radial growth rate of the three species in June and July was greater when air temperatures were higher. Tree-ring formation lasted about 50-60 days (from mid-June to the beginning of August).

Quantitative estimates of Mid- to late Holocene Climate Variability in northeastern Siberia inferred from chironomids in lake sediments

NASA Astrophysics Data System (ADS)

Nazarova, Larisa; Diekmann, Bernhard; Pestrjakova, Ludmila; Herzschuh, Ulrike; Subetto, Dmitry

2010-05-01

faunistic changes take place after 4500 yBP. Temperature reconstruction has shown that around 4500 ka BP air temperature went down up to 2oC below modern temperature. These observations confirm end of Holocene climate optimum at this time. The lake status record reveals a long-term trend towards lake-level lowering in the course of climate deterioration after 4.2 cal. ka BP and reduced evaporation as well as progressive sediment infill. This long-term trend is overprinted by short-term fluctuations at centennial time scales with high lake levels and decreased biological productivity during cool climate spells with reduced evaporation, as also observed in modern thermokarst lakes of Central Yakutia.

Analyzing climate variations at multiple timescales can guide Zika virus response measures.

PubMed

Muñoz, Ángel G; Thomson, Madeleine C; Goddard, Lisa; Aldighieri, Sylvain

2016-10-06

The emergence of Zika virus (ZIKV) in Latin America and the Caribbean in 2014-2016 occurred during a period of severe drought and unusually high temperatures, conditions that have been associated with the 2015-2016 El Niño event, and/or climate change; however, no quantitative assessment has been made to date. Analysis of related flaviviruses transmitted by the same vectors suggests that ZIKV dynamics are sensitive to climate seasonality and longer-term variability and trends. A better understanding of the climate conditions conducive to the 2014-2016 epidemic may permit the development of climate-informed short and long-term strategies for ZIKV prevention and control. Using a novel timescale-decomposition methodology, we demonstrate that the extreme climate anomalies observed in most parts of South America during the current epidemic are not caused exclusively by El Niño or climate change, but by a combination of climate signals acting at multiple timescales. In Brazil, the dry conditions present in 2013-2015 are primarily explained by year-to-year variability superimposed on decadal variability, but with little contribution of long-term trends. In contrast, the warm temperatures of 2014-2015 resulted from the compound effect of climate change, decadal and year-to-year climate variability. ZIKV response strategies made in Brazil during the drought concurrent with the 2015-2016 El Niño event, may require revision in light of the likely return of rainfall associated with the borderline La Niña event expected in 2016-2017. Temperatures are likely to remain warm given the importance of long term and decadal scale climate signals. The Author(s)

Climate change impacts on global food security.

PubMed

Wheeler, Tim; von Braun, Joachim

2013-08-02

Climate change could potentially interrupt progress toward a world without hunger. A robust and coherent global pattern is discernible of the impacts of climate change on crop productivity that could have consequences for food availability. The stability of whole food systems may be at risk under climate change because of short-term variability in supply. However, the potential impact is less clear at regional scales, but it is likely that climate variability and change will exacerbate food insecurity in areas currently vulnerable to hunger and undernutrition. Likewise, it can be anticipated that food access and utilization will be affected indirectly via collateral effects on household and individual incomes, and food utilization could be impaired by loss of access to drinking water and damage to health. The evidence supports the need for considerable investment in adaptation and mitigation actions toward a "climate-smart food system" that is more resilient to climate change influences on food security.

Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos

2016-01-01

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

Sensitivity of global terrestrial ecosystems to climate variability.

PubMed

Seddon, Alistair W R; Macias-Fauria, Marc; Long, Peter R; Benz, David; Willis, Kathy J

2016-03-10

The identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global relevance. Here we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognizing that systems closer to critical thresholds respond more sensitively to external perturbations. We develop a new metric, the vegetation sensitivity index, that identifies areas sensitive to climate variability over the past 14 years. The metric uses time series data derived from the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index, and three climatic variables that drive vegetation productivity (air temperature, water availability and cloud cover). Underlying the analysis is an autoregressive modelling approach used to identify climate drivers of vegetation productivity on monthly timescales, in addition to regions with memory effects and reduced response rates to external forcing. We find ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, the Caatinga deciduous forest in eastern South America, and eastern areas of Australia. Our study provides a quantitative methodology for assessing the relative response rate of ecosystems--be they natural or with a strong anthropogenic signature--to environmental variability, which is the first step towards addressing why some regions appear to be more sensitive than others, and what impact this has on the resilience of ecosystem service provision and human well-being.