On the Response of the Greenland Ice Sheet to Greenhouse Climate Change

Numerical computations are performed with the three-dimensional polythermal ice-sheet model SICOPOLIS in order to investigate the possible impact of a greenhouse-gas-induced climate change on the Greenland ice sheet. The assumed increase of the mean annual air temperature above the ice covers a range from T = 1°C to 12°C, and several parameterizations for the snowfall and the surface melting are considered. The simulated shrinking of the ice sheet is a smooth function of the temperature rise, indications for the existence of critical thresholds of the climate input are not found. Within 1000 model years, the ice-volume decrease is limited to 10% of the present volume for T 3°C, whereas the most extreme scenario, T = 12°C, leads to an almost entire disintegration, which corresponds to a sea-level equivalent of 7 m. The different snowfall and melting parameterizations yield an uncertainty range of up to 20% of the present ice volume after 1000 model years.     

A Climate Change Scenario for the Tropics

This paper describes the construction of a climate change scenario for a region representing the extended Tropics – 30° N to 30° S – using a methodology that combines results from a simple climate model and a Global Climate Model (GCM) transient climate change experiment. The estimated date by which this climate change scenario might be realized ranges from as early as the end of the 2030s to as late as well into the 22nd century. The central estimate is for this scenario to describe the climate of the 2060s, which would represent a global warming rate of about 0.2 °C per decade, with associated atmospheric CO₂ concentrations estimated to be about 560 ppmv, 55% higher than 1990 levels. The role of anthropogenic aerosols in offsetting part of this future global warming and altering the regional character of the changes has not been considered. The paper presents changes in mean temperature; mean rainfall; rainfall seasonality, variability, frequency, and intensity and soil moisture. These patterns of change derive from only one GCM climate change experiment; different experiments would yield different patterns for the same global warming. There is also some discussion about possible changes in tropical cyclone (TC) activity, although since TCs remain poorly modelled in GCMs, the full range of possibilities (from reduced activity, through no change, to increased activity) should be considered in any impact assessment.     

Quantitative estimates of full glacial temperatures in equatorial Africa from palynological data*

This paper presents a new reconstruction of the mean annual temperature obtained from a high altitude pollen sequence in equatorial Africa (3°28S, 29°34E, 2240 m). It has been achieved with an extended modern African reference data set by adding spectra from 228 new sites and using another selection for pollen taxa. The purpose of this paper is to test how the obtained temperature value depends upon the availability of modern analogues. The results are in good agreement with those previously published, reinforcing the validity of the method. The mean standard error is reduced by 0.3°C. The mean temperature for the Holocene appears + 1.4°C warmer than the present and the last glacial maximum (25-18 kyrs BP) cooling is better specified at – 3 ± 1.9° C, a conservative value, more consistent with reconstructed sea surface temperature in the equatorial ocean.Contribution to Clima Locarno - Past and Present Climate Dynamics; Conference September 1990, Swiss Academy of Sciences — National Climate Program     

Urban heat island effect on annual mean temperature during the last 50 years in China

Summary Based on Chinas fifth population survey (2000) data and homogenized annual mean surface air temperature data, the urban heat island (UHI) effect on the warming during the last 50 years in China was analyzed in this study. In most cities with population over 10⁴, where there are national reference stations and principal stations, most of the temperature series are inevitably affected by the UHI effect. To detect the UHI effect, the annual mean surface air temperature (SAT) time series were firstly classified into 5 subregions by using Rotated Principal Components Analysis (RPCA) according to its high and low frequency climatic change features. Then the average UHI effect on each subregions regional annual mean STA was studied. Results indicate that the UHI effect on the annual mean temperatures includes three aspects: increase of the average values, decrease of variances and change of the climatic trends. The effect on the climatic trends is different from region to region. In the Yangtze River Valley and South China, the UHI effect enhances the warming trends by about 0.011°C/decade. In the other areas, such as Northeast, North-China, and Northwest, UHI has little impact on the warming trends of the regional annual temperature; while in the Southwest of China, introducing UHI stations slows down the warming trend by –0.006°C/decade. But no matter what subregion it is, the total warming/cooling of these effects is much smaller than the background change in regional temperature. The average UHI effect for the entire country, during the last 50 years is less than 0.06°C, which agrees well with the IPCC (2001). This suggests that we cannot conclude that urbanization during the last 50 years has had much obvious effect on the observed warming in China.     

Modeling Modern and Late Pleistocene Glacio-Climatological Conditions in the North Chilean Andes (29–30 °)

An empirical-statistical climate-glacier model is used to reconstruct Late Pleistocene climate conditions in the south-central Andes of northern Chile (29–30° S). The model was tested using modern climate data and the results compare favorably with key glaciological features presentlyobserved in this area. Using several glaciers at 29° S as casestudies, the results suggest an increase in annual precipitation( P = 580 ± 150 mm, today 400 mm), and a reduction inannual mean temperature ( T = –5.7 ± 0.7 ° C).These data suggest full glacial LGM (Last Glacial Maximum) conditionsfor the maximum glacier advances at 29° S, a scenario that is asynchronous with the timing of maximum advances north of the Arid Diagonal (18–24° S) where late-glacial climate was moderately cold but very humid.The reconstructed case study glaciers at 29° S do not allow conclusions to be drawn about the seasonality of precipitation. However, comparison with regional paleodata suggests intensified westerly winter precipitation and a stable position for the northern boundary of the westerlies at 27° S. However, the meridional precipitation gradients were much steeper than today while the core area of the Arid Diagonal remained fixed between 25–27° S.     

Present and future surface climate in the western USA as simulated by 15 global climate models

We analyze results of 15 global climate simulations contributed to the Coupled Model Intercomparison Project (CMIP). Focusing on the western USA, we consider both present climate simulations and predicted responses to increasing atmospheric CO₂. The models vary in their ability to predict the present climate. In the western USA, a few models produce a seasonal cycle for spatially averaged temperature and/or precipitation in good agreement with observational data. Other models tend to over-predict precipitation in the winter or exaggerate the amplitude of the seasonal cycle of temperature. The models also differ in their ability to reproduce the spatial patterns of temperature and precipitation in the USA. Considering the monthly mean precipitation responses to doubled atmospheric CO₂, averaged over the western USA, we find some models predict increases while others predict decreases. The predicted temperature response, on the other hand, is invariably positive over this region; however, for each month, the range of values given by the different models is large compared to the mean model response. We look for possible relationships between the models temperature and precipitation responses to doubled CO₂ concentration and their ability to simulate some aspects of the present climate. We find that these relationships are weak, at best. The precipitation response over the western USA in DJF and the precipitation response over the mid- and tropical latitudes seem to be correlated with the RMS error in simulated present-day precipitation, also calculated over the mid- and tropical latitudes. However, considering only the responses of the models with the smallest RMS errors does not provide a different estimate of the precipitation response to a doubled CO₂ concentration, because even among the most accurate models, the range of model responses is so large. For temperature, we find that models that have smaller RMS errors in present-climate temperature in the north eastern Pacific region predict a higher temperature response in the western USA than the models with larger errors. A similar relation exists between the temperature response over Europe in DJF and the RMS error calculated over the Northern Atlantic.     

The application of a two-dimensional numerical model of the planetary boundary layer to the Nanticoke region on the north shore of Lake Erie

A two-dimensional atmospheric boundary-layer model is applied to the Nanticoke region on the northern shore of Lake Erie (80 ° 03W and 42 ° 50N) to simulate numerically the observed wind and temperature profiles. In general, the profiles predicted by the model agree reasonably well with the observed profiles.     

Assessment of climatic suitability for the expansion of Solenopsis invicta Buren in Oklahoma using three general circulation models

Summary This study assessed the climatic suitability for the expansion of Solenopsis invicta Buren (red imported fire ant) in Oklahoma under the present climate and with a doubling of atmospheric CO₂ using three general circulation models (GCMs) (GFDL R30, OSU, UKMO). Oklahoma was chosen as the geographical focus because it has a dense network of meteorological stations and lies on the edge of the current biogeographic range of S. invicta. Meteorological data were spatially referenced with model data in GIS to produce a series of images of selected suitability indicators: (1) mean annual precipitation >510mm; (2) less than seven consecutive days with mean air temperature <1.1C; and (3) mean winter air temperature >9.4C. These indicator images were combined to produce suitability maps for the potential range of S. invicta. Under current climatic conditions, roughly three-quarters of Oklahoma is suitable for potential invasion by S. invicta. The GFDL R30, OSU, and UKMO show that the area suitable for colonization increases by approximately 26, 26, and 36%, respectively. In terms of actual land area, the increase with a warmer, wetter climate ranges from 35,300km² to 47,600km². The destructiveness of S. invicta on human livelihood necessitates a better understanding of the future expansion of the species for an uncertain future climate.     

Crop yield response to economic, site and climatic variables

This paper examines the effects of climatic and non-climatic factors on the mean and variance of corn, soybean and winter wheat yield in southwestern Ontario, Canada over a period of 26 years. Average crop yields increase at a decreasing rate with the quantity of inputs used, and decrease with the area planted to the crop. Climate variables have a major impact on mean yield with the length of the growing season being the primary determinant across all three crops. Increases in the variability of temperature and precipitation decrease mean yield and increase its variance. Yield variance is poorly explained by both seasonal and monthly climate variable models. Projections of future climate change suggest that average crop yield will increase with warmer temperatures and a longer growing season which is only partially offset by forecast increases in the variability of temperature and rainfall. The projections would also depend on future technological developments, which have generated significant increases in yield over time despite changing annual weather conditions.     

Permafrost Thaw Accelerates in Boreal Peatlands During Late-20th Century Climate Warming

Permafrost covers 25% of the land surface in the northern hemisphere, where mean annual ground temperature is less than 0°C. A 1.4–5.8 °C warming by 2100 will likely change the sign of mean annual air and ground temperatures over much of the zones of sporadic and discontinuous permafrost in the northern hemisphere, causing widespread permafrost thaw. In this study, I examined rates of discontinuous permafrost thaw in the boreal peatlands of northern Manitoba, Canada, using a combination of tree-ring analyses to document thaw rates from 1941–1991 and direct measurements of permanent benchmarks established in 1995 and resurveyed in 2002. I used instrumented records of mean annual and seasonal air temperatures, mean winter snow depth, and duration of continuous snow pack from climate stations across northern Manitoba to analyze temporal and spatial trends in these variables and their potential impacts on thaw. Permafrost thaw in central Canadian peatlands has accelerated significantly since 1950, concurrent with a significant, late-20th-century average climate warming of +1.32 °C in this region. There were strong seasonal differences in warming in northern Manitoba, with highest rates of warming during winter (+1.39 °C to +1.66 °C) and spring (+0.56 °C to +0.78 °C) at southern climate stations where permafrost thaw was most rapid. Projecting current warming trends to year 2100, I show that trends for north-central Canada are in good agreement with general circulation models, which suggest a 4–8 °C warming at high latitudes. This magnitude of warming will begin to eliminate most of the present range of sporadic and discontinuous permafrost in central Canada by 2100.     

Estimation of impact of climate change on the peak discharge probability of the river Rhine

RHINEFLOW is a GIS based water balance model that has been developed to study the changes in the water balance compartments of the river Rhine basin on a monthly time basis. The model has been designed to study the sensitivity of the Rhine discharge to a climate change. The calculated discharge has been calibrated and validated on the period 1956 to 1980. For this period the model efficiency of RHINEFLOW is between 0.74 and 0.81 both for the entire Rhine and for its tributaries. Also calculated values for variations in other compartments, e.g. snow storage and actual evapotranspiration, were in good agreement with the measured values.Since a high correlation between monthly discharge and peak discharge was found for the period 1900–1980 The RHINEFLOW model is used to assess the probability of exceedence for discharge peaks under possible future climate conditions.The probabilities of exceedence were calculated from the conditional probabilities of peak discharges for a series of 15 classes of monthly discharges. Comparison of a calculated frequency distribution of high discharge peaks with observed peaks in a test series showed that the method performs well.Scenarios for temperature changes between 0 °C and plus 4 °C and precipitation changes between plus 20% and minus 20% have been applied. Within this range flood frequencies are more sensitive for a precipitation change than for a temperature change. The present two-year return period peak flow (6500–7000 m³/s) decreases by about 6% due to a temperature rise of 4 °C; a precipitation decrease of 20% leads to 30% lower two-year peaks whilst 20% precipitation increase raises them by approximately 30%.Application of a Business As Usual (BAU) and an Accelerated Policy (AP) climate scenario resulted in a significant increase in probability of peak flows for the BAU scenario, while for the AP scenario no significant change could be found. Due to sampling errors, accurate estimations of recurrence times of discharge peaks7000 m³/s require a longer sampling time series than 90 years. For management purposes the method can be applied to estimate changes of probabilities of events with a relatively long recurrence time.     

Simple indices of global climate variability and change Part II: attribution of climate change during the twentieth century

Five simple indices of surface temperature are used to investigate the influence of anthropogenic and natural (solar irradiance and volcanic aerosol) forcing on observed climate change during the twentieth century. These indices are based on spatial fingerprints of climate change and include the global-mean surface temperature, the land-ocean temperature contrast, the magnitude of the annual cycle in surface temperature over land, the Northern Hemisphere meridional temperature gradient and the hemispheric temperature contrast. The indices contain information independent of variations in global-mean temperature for unforced climate variations and hence, considered collectively, they are more useful in an attribution study than global mean surface temperature alone. Observed linear trends over 1950–1999 in all the indices except the hemispheric temperature contrast are significantly larger than simulated changes due to internal variability or natural (solar and volcanic aerosol) forcings and are consistent with simulated changes due to anthropogenic (greenhouse gas and sulfate aerosol) forcing. The combined, relative influence of these different forcings on observed trends during the twentieth century is investigated using linear regression of the observed and simulated responses of the indices. It is found that anthropogenic forcing accounts for almost all of the observed changes in surface temperature during 1946–1995. We found that early twentieth century changes (1896–1945) in global mean temperature can be explained by a combination of anthropogenic and natural forcing, as well as internal climate variability. Estimates of scaling factors that weight the amplitude of model simulated signals to corresponding observed changes using a combined normalized index are similar to those calculated using more complex, optimal fingerprint techniques.     

Predicted Effects of Climatic Change on Distribution of Ecologically Important Native Tree and Shrub Species in Florida

A previously developed plant species-climatic envelope model was evaluated further and used to predict effects of hypothesized climatic change on the potential distribution of 124 native woody plant species in Florida, U.S.A. Twelve scenarios were investigated. These included mean annual temperature increases of 1 °C or 2 °C, achieved either by equal 1 °C or 2 °C increases on a monthly basis throughout the year, or by disproportionately larger seasonal increases in winter and smaller ones in summer. The various temperature increases were then combined with each of several precipitation changes, ranging from +10% to –20%, to produce the final set of scenarios. More detailed analysis involving six of the scenarios and a subset of 28 representative, ecologically important species suggested that (1) large decreases in the Florida range of many temperate species would result if 1 °C warming occurs predominantly in winter or with a 20% decrease in annual precipitation, or (2) if 2 °C warming occurs, with or without decrease in annual precipitation, and regardless of whether there is a uniform monthly warming pattern or one that is higher in winter than in summer. Available information concerning other factors that might also affect climatic-change responses suggests that these large predicted impacts on temperate Florida species may be underestimates. Subtropical Florida species will tend to move north and inland with warming but extensive human assistance may be needed, if they are to realize their newly expanded, potential natural ranges.     

Climate change impact on water and salt balances: an assessment of the impact of climate change on catchment salt and water balances in the Murray-Darling Basin, Australia

Climate change has potentially significant implications for hydrology and the quantity and quality of water resources. This study investigated the impacts of climate change and revegetation on water and salt balance, and stream salt concentration for catchments within the Murray-Darling Basin, Australia. The Biophysical Capacity to Change model was used with climate change scenarios obtained using the CSIRO DARLAM 125 (125 km resolution) and Cubic Conformal (50 km resolution) regional climate models. These models predicted up to 25% reduction in mean annual rainfall and a similar magnitude of increase in potential evapotranspiration by 2070. Relatively modest changes in rainfall and temperature can lead to significant reductions in mean annual runoff and salt yield and increases in stream salt concentrations within the Basin. The modelled reductions in mean annual runoff were up to 45% in the wetter/cooler southern catchments and up to 64% in the drier/hotter western and northern catchments. The maximum reductions in salt yield were estimated to be up to 34% in the southern catchments and up to 49% in the northern and western catchments. These changes are associated with average catchment rainfall decreases of 13 to 21%. The results suggest that percentage changes in rainfall will be amplified in runoff. This study demonstrates that climate change poses significant challenges to natural resource management in Australia.     

Bumping against a Gas Ceiling

The adoption of physical thresholds as a ceiling for permitted climate change sidesteps contentious issues such as: policy cost, impact valuation, discounting and equity. In this paper I offer some reflections on the concept of tolerable climate change. I also use an integrated climate assessment model (ICAM-3) to demonstrate how uncertainties in our understanding of socioeconomic and earth systems reduce the probability of success in keeping climate change within a pre-defined tolerable range. Finally, I explore the implications of socioeconomic thresholds for welfare loss in pursuit of a climate policy (e.g., tax rebellions). Crossing such regional socioeconomic thresholds will lead to local failures to pursue climate change mitigation policies — increasing the probability of straying beyond the tolerable window of global climate change. Given various uncertainties and the dynamics of the socioeconomic and the earth systems, the odds of success in staying within a climate change window of T 2°C, and T/yr 0.015°C are estimated to be no higher than 25% over the next century. A risk-risk tradeoff approach appears to hold promise, but while adoption of a larger window of tolerance increases the probability of success, it also opens the window specification criteria to contention.     

Sensitivity Analysis of Emissions Corridors for the 21st Century

We investigate the sensitivity of emissions corridors for the 21st century to various factors that are currently under debate in the climate change arena. Emissions corridors represent the range of admissible emissions futures that observe some predefined guardrails on the future development of the human-climate system. They are calculated on the conceptual and methodological basis of the tolerable windows approach. We assess the sensitivity of the corridors to the choice of time-resolved as well as intertemporally aggregated guardrails that exclude an intolerable amount of climate change on the one hand and unbearable mitigation burdens on the other. In addition, we investigate the influence of climate sensitivity on the corridors.Results show a large dependence of emissions corridors on the choice of guardrails and the value of climate sensitivity T _{2CO 2}. If the guardrail on climate change is specified in terms of a maximum admissible global mean temperature increase T _max to be observed at any time, the size of the corridors is predominantly determined by a climate impact resilience parameter =T _max/T _{2CO 2}. As is varied from values below 0.5 to values above 1.5, we move from cases where no emissions profile whatsoever can observe all guardrails, to cases where no significant emissions reduction seems necessary given the range of emissions scenarios for the 21st century. The limits on admissible mitigation efforts influence predominantly the timing and the economic viability of emissions reductions. A large mitigation flexibility allows for wait then run emissions paths, while low flexibility asks for a significantly more prudent approach.     

Study of the influence of katabatic flows on the Antarctic circulation using GCM simulations

Summary A one dimensional analytical model of katabatic wind over the Antarctica has been developed. This parametric model is derived from the bulk two-layer model of Ball including the surface friction and taking into account the Earth's rotation and the geostrophic wind in the upper layer.This model is validated using the data set (70 soundings) collected during IAGO experiment at D47 (67°24S, 138°43E, altitude 1 564m), 110 km inland from the coast of Adélie Land.The parameteric model is then introduced into a GCM which is a spectral global version of the operational numerical weather prediction model used by the French weather service. The most significant effect of the parameterization is a 50 m increase of the geopotential height over the South Pole. The surface temperature at the South Pole increases (2°C) reducing the pole-midlatitude thermal gradient. The westerly circulation at 50° S is slowed down (4m/s at 850 hPa), and the surface pressure at the South Pole increases (4hPa). These results, consistent with an increase of katabatic winds, would however be improved by a better coupling between the parameterization and the GCM boundary layer.With 8 Figures     

The impact of climate change on the river rhine: A scenario study

This paper concerns the impact of human-induced global climate change on the River Rhine discharge. For this purpose a model for climate assessment, named ESCAPE, is coupled to a water balance model, named RHINEFLOW. From climate scenarios, changes in regional annual water availability and seasonal discharge in the River Rhine Basin are estimated. The climate scenarios are based on greenhouse gases emissions scenarios. An assessment is made for best guess seasonal discharge changes and for changes in frequencies of low and high discharges in the downstream reaches of the river. In addition, a quantitative estimation of the uncertainties associated with this guess is arrived at.The results show that the extent and range of uncertainty is large with respect to the best guess changes. The uncertainty range is 2–3 times larger for the Business-as-Usual than for the Accelerated Policies scenarios. This large range stems from the doubtful precipitation simulations from the present General Circulation Models. This scenario study showed the precipitation scenarios to be the key-elements within the present range of reliable climate change scenarios.For the River Rhine best guess changes for annual water availability are small according to both scenarios. The river changes from a present combined snow-melt-rain fed river to an almost entirely rain fed river. The difference between present-day large average discharge in winter and the small average discharge in autumn should increase for all scenarios. This trend is largest in the Alpine part of the basin. Here, winter discharges should increase even for scenarios forecasting annual precipitation decreases. Summer discharge should decrease. Best guess scenarios should lead to increased frequencies of both low and high flow events in the downstream (Dutch) part of the river. The results indicate changes could be larger than presently assumed in worst case scenarios used by the Dutch water management authorities.     

MEAN AND VARIANCE CHANGE IN CLIMATE SCENARIOS: METHODS, AGRICULTURAL APPLICATIONS, AND MEASURES OF UNCERTAINTY

Our central goal is to determine the importance of including both mean and variability changes in climate change scenarios in an agricultural context. By adapting and applying a stochastic weather generator, we first tested the sensitivity of the CERES-Wheat model to combinations of mean and variability changes of temperature and precipitation for two locations in Kansas. With a 2°C increase in temperature with daily (and interannual) variance doubled, yields were further reduced compared to the mean only change. In contrast, the negative effects of the mean temperature increase were greatly ameliorated by variance decreased by one-half. Changes for precipitation are more complex, since change in variability naturally attends change in mean, and constraining the stochastic generator to mean change only is highly artificial. The crop model is sensitive to precipitation variance increases with increased mean and variance decreases with decreased mean. With increased mean precipitation and a further increase in variability Topeka (where wheat cropping is not very moisture limited) experiences decrease in yield after an initial increase from the 'mean change only case. At Goodland Kansas, a moisture-limited site where summer fallowing is practiced, yields are decreased with decreased precipitation, but are further decreased when variability is further reduced. The range of mean and variability changes to which the crop model is sensitive are within the range of changes found in regional climate modeling (RegCM) experiments for a CO₂ doubling (compared to a control run experiment). We then formed two types of climate change scenarios based on the changes in climate found in the control and doubled CO₂ experiments over the conterminous U. S. of RegCM: (1) one using only mean monthly changes in temperature, precipitation, and solar radiation; and (2) another that included these mean changes plus changes in daily (and interannual) variability. The scenarios were then applied to the CERES-Wheat model at four locations (Goodland, Topeka, Des Moines, Spokane) in the United States. Contrasting model responses to the two scenarios were found at three of the four sites. At Goodland, and Des Moines mean climate change increased mean yields and decreased yield variability, but the mean plus variance climate change reduced yields to levels closer to their base (unchanged) condition. At Spokane mean climate change increased yields, which were somewhat further increased with climate variability change. Three key aspects that contribute to crop response are identified: the marginality of the current climate for crop growth, the relative size of the mean and variance changes, and timing of these changes. Indices for quantifying uncertainty in the impact assessment were developed based on the nature of the climate scenario formed, and the magnitude of difference between model and observed values of relevant climate variables.     

Potential effect of nuclear war smokefall on sea ice

A large nuclear war could produce massive quantities of smoke from burning cities and industries. A portion of this smoke would fall out on Arctic sea ice, thus lowering its albedo and potentially increasing the solar energy absorbed by the ice and the snow that covers it. We use a one-dimensional thermodynamic sea ice model to examine the effect of smokefall on the seasonal variation of sea ice. In particular, we test the sensitivity of the model results to the time of year, duration, and latitude of smokefall.Sea ice thickness variations and the period of summer ice-free conditions are sensitive to the season of smokefall. The largest sea ice perturbations are generated by smokefall in spring. In this case the period of ice-free conditions during the summer can increase by 2 – 3.5 months between 67.5° N and 82.5° N. In any given season, the annual cycle of sea ice is not very sensitive to the duration of smokefall. The equilibrium annual cycle of sea ice variation is restored within a few years of smokefall when the smoke is flushed out of the ice/snow system.Since the sea ice model used here is not a comprehensive global climate model, it is difficult to predict the mid-latitude climate effects of the massive, but temporary, Arctic sea ice changes. However, our results suggest that future global climate model simulations of the effects of nuclear war smoke include interactive sea ice calculations.The National Center for Atmospheric Research is sponsored by the National Science Foundation.