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NASA NTRS1995

Satellite Snow-Cover Mapping: A Brief Review

Satellite snow mapping has been accomplished since 1966, initially using data from the reflective part of the electromagnetic spectrum, and now also employing data from the microwave part of the spectrum. Visible and near-infrared sensors can provide excellent spatial resolution from space enabling detailed snow mapping. When digital elevation models are also used, snow mapping can provide realistic measurements of snow extent even in mountainous areas. Passive-microwave satellite data permit global snow cover to be mapped on a near-daily basis and estimates of snow depth to be made, but with relatively poor spatial resolution (approximately 25 km). Dense forest cover limits both techniques and optical remote sensing is limited further by cloudcover conditions. Satellite remote sensing of snow cover with imaging radars is still in the early stages of research, but shows promise at least for mapping wet or melting snow using C-band (5.3 GHz) synthetic aperture radar (SAR) data. Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data beginning with the launch of the first EOS platform in 1998. Digital maps will be produced that will provide daily, and maximum weekly global snow, sea ice and lake ice cover at 1-km spatial resolution. Statistics will be generated on the extent and persistence of snow or ice cover in each pixel for each weekly map, cloudcover permitting. It will also be possible to generate snow- and ice-cover maps using MODIS data at 250- and 500-m resolution, and to study and map snow and ice characteristics such as albedo. been under development. Passive-microwave data offer the potential for determining not only snow cover, but snow water equivalent, depth and wetness under all sky conditions. A number of algorithms have been developed to utilize passive-microwave brightness temperatures to provide information on snow cover and water equivalent. The variability of vegetative Algorithms are being developed to map global snow and ice cover using Earth Algorithms to map global snow cover using passive-microwave data have also cover and of snow grain size, globally, limits the utility of a single algorithm to map global snow cover.

Hall, Dorothy K.↗

NASA NTRSDate not supplied

Terrestrial sedimentation impact on coral and macroalgal cover in Puerto Rico's southwest coral reefs.

The coral reefs in southwest Puerto Rico (PR) have faced coral cover reduction in the last decades due to changes in its environment that can be related to sedimentation entrance resulting from anthropogenic activities in the watershed (i.e., agriculture and urban development). The Guánica Bay and La Parguera reef platforms are two natural reserves important for recreational and fishing activities. Nonetheless, their respective coral cover has decreased dramatically. Data from a previous NASA-funded project (HICE-PR) conducted between 2014-2018 was analyzed to better understand how the terrigenous sedimentation can affect the coral reef benthic composition in Guánica Bay and La Parguera. A one-way Nested ANOVA and a Tukey's HSD analyses were applied to find differences in benthic cover composition within and among the sites and location. The preliminary results showed differences in coral cover and macroalgae cover between the platforms reefs sites. The coral cover in La Parguera was higher and averaged 11.5% compared to that of Guánica (8.6%), while the macroalgae cover followed a similar pattern. Both coral cover and macroalgae in La Parguera and Guánica varied between from 2016 to 2018 with a general trend of increased coral cover in La Parguera and increase in macroalgae in Guánica. These trends can be related to the distance to the coastline as those reefs located closer to the coastline showed a greater percentage in macroalgal cover than those located farther. Cover of macroalgae and corals at reefs located a mid-distance to the coastline varied with no definite pattern detected. These results will be further correlated with variations in water quality obtained from remotely-sensed data (patterns of chlorophyll a, total suspended sediments, vertical attenuation coefficient) to support the prediction and tracking of coral cover changes in PR's southwest region.

macroalgal↗

NASA NTRS1994

Light transmission and reflection in perennially ice-covered Lake Hoare, Antarctica

We have investigated the transmission and albedo of the perennial ice cover on Lake Hoare, Antarctica. Our database consists of year-round measurements of the photosynthetically active radiation (400-700 nm) under the ice, measurements of the spatial variation of the under-ice light in midsummer, and spectrally resolved measurements from 400 to 700 nm of the albedo and transmission of the ice cover in early (November) and in midsummer (January). Our results show that the transmission decreases in the first part of summer, dropping by a factor of approximately 4 from November to January. We suggest that this is due to heating in the upper layers of the ice cover and the formation of Tyndall figures. Later in the summer when a significant liquid water fraction occurs within the ice cover, the transmission increases. In the fall when the ice cover freezes solid the transmission drops markedly. The spectrally resolved measurements from 400 to 700 nm show that approximately 2-5% of the incident light in this spectral region penetrates the 3.5-m thick ice cover. We have analyzed the spectral data using a two-stream scattering solution to the radiative transfer equation with three vertical layers in the ice cover. A surficial glaze of scattering ice 1 cm thick overlies a layer of sandy, bubbly ice about a meter thick, and below this is a thick layer of sand-free ice with bubbles. We find that the ice cover is virtually opaque at wavelengths longer than 800 nm. The net transmission of solar energy is approximately 2%. Significant changes in the thickness of the ice cover have been reported at Lake Hoare. These are due primarily to changes in the thickness of the bottom layer only. Because this layer is relatively clear, the effect on the transmission through the ice cover from these changes is less than would be predicted assuming a homogeneous ice cover.

Mckay, C. P.↗

NASA NTRS2009

MODIS Tree Cover Validation for the Circumpolar Taiga-Tundra Transition Zone

A validation of the 2005 500m MODIS vegetation continuous fields (VCF) tree cover product in the circumpolar taiga-tundra ecotone was performed using high resolution Quickbird imagery. Assessing the VCF's performance near the northern limits of the boreal forest can help quantify the accuracy of the product within this vegetation transition area. The circumpolar region was divided into longitudinal zones and validation sites were selected in areas of varying tree cover where Quickbird imagery is available in Google Earth. Each site was linked to the corresponding VCF pixel and overlaid with a regular dot grid within the VCF pixel's boundary to estimate percent tree crown cover in the area. Percent tree crown cover was estimated using Quickbird imagery for 396 sites throughout the circumpolar region and related to the VCF's estimates of canopy cover for 2000-2005. Regression results of VCF inter-annual comparisons (2000-2005) and VCF-Quickbird image-interpreted estimates indicate that: (1) Pixel-level, inter-annual comparisons of VCF estimates of percent canopy cover were linearly related (mean R(sup 2) = 0.77) and exhibited an average root mean square error (RMSE) of 10.1 % and an average root mean square difference (RMSD) of 7.3%. (2) A comparison of image-interpreted percent tree crown cover estimates based on dot counts on Quickbird color images by two different interpreters were more variable (R(sup 2) = 0.73, RMSE = 14.8%, RMSD = 18.7%) than VCF inter-annual comparisons. (3) Across the circumpolar boreal region, 2005 VCF-Quickbird comparisons were linearly related, with an R(sup 2) = 0.57, a RMSE = 13.4% and a RMSD = 21.3%, with a tendency to over-estimate areas of low percent tree cover and anomalous VCF results in Scandinavia. The relationship of the VCF estimates and ground reference indicate to potential users that the VCF's tree cover values for individual pixels, particularly those below 20% tree cover, may not be precise enough to monitor 500m pixel-level tree cover in the taiga-tundra transition zone.

Montesano, P. M.↗

NASA NTRS1998

Theoretical Accuracy of Global Snow-Cover Mapping Using Satellite Data in the Earth Observing System (EOS) Era

Following the launch of the Earth Observing System first morning (EOS-AM1) satellite, daily, global snow-cover mapping will be performed automatically at a spatial resolution of 500 m, cloud-cover permitting, using Moderate Resolution Imaging Spectroradiometer (MODIS) data. A technique to calculate theoretical accuracy of the MODIS-derived snow maps is presented. Field studies demonstrate that under cloud-free conditions when snow cover is complete, snow-mapping errors are small (less than 1%) in all land covers studied except forests where errors are greater and more variable. The theoretical accuracy of MODIS snow-cover maps is largely determined by percent forest cover north of the snowline. Using the 17-class International Geosphere-Biosphere Program (IGBP) land-cover maps of North America and Eurasia, the Northern Hemisphere is classified into seven land-cover classes and water. Snow-mapping errors estimated for each of the seven land-cover classes are extrapolated to the entire Northern Hemisphere for areas north of the average continental snowline for each month. Average monthly errors for the Northern Hemisphere are expected to range from 5 - 10%, and the theoretical accuracy of the future global snow-cover maps is 92% or higher. Error estimates will be refined after the first full year that MODIS data are available.

Hall, D. K.↗

NASA NTRS2011

Characterizing Vegetation Cover in Global Savannas with an Annual Foliage Clumping Index Derived from the MODIS BRDF Product

The global savanna biome is characterized by enormous diversity in the physiognomy and spatial structure of the vegetation. The foliage clumping index can be calculated from bidirectional reflectance distribution function (BRDF) data. It measures the response of the darkspot reflectance to increased shadow associated with clumped vegetation and is related to leaf area index. Clumping index theoretically declines with increasing woody cover until the tree canopy begins to become uniform. In this study, clumping index is calculated for Moderate Resolution Imaging Spectroradiometer BRDF data for the Australian tropical savanna, the tropical savannas of South America, and the tropical savannas of east, west and southern Africa and compared with site-based measurements of tree canopy cover, and with area-based classifications of land cover. There were differences in sensitivity of clumping index between red and near-infrared reflectance channels, and between savanna systems with markedly different woody vegetation physiognomy. Clumping index was broadly related to foliage cover from historical site data in Australia and in West Africa and Kenya, but not in Southern Africa nor with detailed site-based demographic data in the cerrado of Brazil. However, clumping index decreased with proportion of woody cover in land cover datasets for east Africa, Australia and the Colombian Llanos. There was overlap in the range of clumping index values for forest, cerrado and campo land covers in Brazil. Clumping index was generally negatively correlated with percentage tree cover from the MODIS Vegetation Continuous Fields product, but regional differences in the relationship were evident. There were large differences in the frequency distributions of clumping index from savanna, woody savanna and grassland land cover classes between global ecoregions. The clumping index shows differing sensitivity to savanna woody cover for red and NIR reflectance, and requires regional calibration for application as a universal indicator.

Hill, Michael J.↗

NASA NTRS2011

Monitoring Areal Snow Cover Using NASA Satellite Imagery

The objective of this project is to develop products and tools to assist in the hydrologic modeling process, including tools to help prepare inputs for hydrologic models and improved methods for the visualization of streamflow forecasts. In addition, this project will facilitate the use of NASA satellite imagery (primarily snow cover imagery) by other federal and state agencies with operational streamflow forecasting responsibilities. A GIS software toolkit for monitoring areal snow cover extent and producing streamflow forecasts is being developed. This toolkit will be packaged as multiple extensions for ArcGIS 9.x and an opensource GIS software package. The toolkit will provide users with a means for ingesting NASA EOS satellite imagery (snow cover analysis), preparing hydrologic model inputs, and visualizing streamflow forecasts. Primary products include a software tool for predicting the presence of snow under clouds in satellite images; a software tool for producing gridded temperature and precipitation forecasts; and a suite of tools for visualizing hydrologic model forecasting results. The toolkit will be an expert system designed for operational users that need to generate accurate streamflow forecasts in a timely manner. The Remote Sensing of Snow Cover Toolbar will ingest snow cover imagery from multiple sources, including the MODIS Operational Snowcover Data and convert them to gridded datasets that can be readily used. Statistical techniques will then be applied to the gridded snow cover data to predict the presence of snow under cloud cover. The toolbar has the ability to ingest both binary and fractional snow cover data. Binary mapping techniques use a set of thresholds to determine whether a pixel contains snow or no snow. Fractional mapping techniques provide information regarding the percentage of each pixel that is covered with snow. After the imagery has been ingested, physiographic data is attached to each cell in the snow cover image. This data can be obtained from a digital elevation model (DEM) for the area of interest.

Harshburger, Brian J.↗

NASA NTRS2011

Object-Based Mapping of the Circumpolar Taiga-Tundra Ecotone with MODIS Tree Cover

The circumpolar taiga tundra ecotone was delineated using an image-segmentation-based mapping approach with multi-annual MODIS Vegetation Continuous Fields (VCF) tree cover data. Circumpolar tree canopy cover (TCC) throughout the ecotone was derived by averaging MODIS VCF data from 2000 to 2005 and adjusting the averaged values using linear equations relating MODIS TCC to Quickbird-derived tree cover estimates. The adjustment helped mitigate VCF's overestimation of tree cover in lightly forested regions. An image segmentation procedure was used to group pixels representing similar tree cover into polygonal features (segmentation objects) that form the map of the transition zone. Each polygon represents an area much larger than the 500 m MODIS pixel and characterizes the patterns of sparse forest patches on a regional scale. Those polygons near the boreal/tundra interface with either (1) mean adjusted TCC values from5 to 20%, or (2) mean adjusted TCC values greater than 5% but with a standard deviation less than 5% were used to identify the ecotone. Comparisons of the adjusted average tree cover data were made with (1) two existing tree line definitions aggregated for each 1 degree longitudinal interval in North America and Eurasia, (2) Landsat-derived Canadian proportion of forest cover for Canada, and (3) with canopy cover estimates extracted from airborne profiling lidar data that transected 1238 of the TCC polygons. The adjusted TCC from MODIS VCF shows, on average, less than 12% TCC for all but one regional zone at the intersection with independently delineated tree lines. Adjusted values track closely with Canadian proportion of forest cover data in areas of low tree cover. A comparison of the 1238 TCC polygons with profiling lidar measurements yielded an overall accuracy of 67.7%.

Ranson, K. J.↗

NASA NTRS2016

Calibration and Validation of Landsat Tree Cover in the Taiga-Tundra Ecotone

Monitoring current forest characteristics in the taiga-tundra ecotone (TTE) at multiple scales is critical for understanding its vulnerability to structural changes. A 30 m spatial resolution Landsat-based tree canopy cover map has been calibrated and validated in the TTE with reference tree cover data from airborne LiDAR and high resolution spaceborne images across the full range of boreal forest tree cover. This domain-specific calibration model used estimates of forest height to determine reference forest cover that best matched Landsat estimates. The model removed the systematic under-estimation of tree canopy cover greater than 80% and indicated that Landsat estimates of tree canopy cover more closely matched canopies at least 2 m in height rather than 5 m. The validation improved estimates of uncertainty in tree canopy cover in discontinuous TTE forests for three temporal epochs (2000, 2005, and 2010) by reducing systematic errors, leading to increases in tree canopy cover uncertainty. Average pixel-level uncertainties in tree canopy cover were 29.0%, 27.1% and 31.1% for the 2000, 2005 and 2010 epochs, respectively. Maps from these calibrated data improve the uncertainty associated with Landsat tree canopy cover estimates in the discontinuous forests of the circumpolar TTE.

Montesano, Paul Mannix↗

NASA NTRS2017

Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records

Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6) and VIIRS Collection 1 (C1) represent the state-of-the-art global snow cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map.The increased data content allows flexibility in using the datasets for specific regions and end-user applications.Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375m native resolution compared to MODIS 500 m), the snow detection algorithms and data products are designed to be as similar as possible so that the 16C year MODIS ESDR of global SCE can be extended into the future with the S-NPP VIIRS snow products and with products from future Joint Polar Satellite System (JPSS) platforms.These NASA datasets are archived and accessible through the NASA Distributed Active Archive Center at the National Snow and Ice Data Center in Boulder, Colorado.

Earth System Data Record↗

NASA NTRS1979

Cloud cover models derived from satellite radiation measurements

Using daily measurement of day and night infrared and incoming and absorbed solar radiation obtained from a TIROS satellite over a period of approximately 45 months, and integrated over 2.5 degree latitude-longitude grids, the proportion of cloud cover over each grid each day was derived for the entire period. For each of four three-month periods, estimates a and b of the two parameters of the best-fit beta distribution were obtained for each grid location. The (a,b) plane was divided into a number of regions. All the geographical locations whose (a,b) estimates were in the same region in the (a,b) plane were said to have the same cloud cover type for that season. For each season, the world was thus divided into separate cloud cover types. Using estimates of mean cloud cover for each season, the world was again divided into separate cloud cover types. The process was repeated for standard deviations. Thus for each season, three separate cloud cover models were obtained using the criteria of shape of frequency distribution, mean cloud cover, and variability of cloud cover. The cloud cover statistics were derived from once-a-day, near-local-noon satellite radiation measurements.

Bean, S. J.↗

NASA NTRS1999

Utilizing Multiple Datasets for Snow Cover Mapping

Snow-cover maps generated from surface data are based on direct measurements, however they are prone to interpolation errors where climate stations are sparsely distributed. Snow cover is clearly discernable using satellite-attained optical data because of the high albedo of snow, yet the surface is often obscured by cloud cover. Passive microwave (PM) data is unaffected by clouds, however, the snow-cover signature is significantly affected by melting snow and the microwaves may be transparent to thin snow (less than 3cm). Both optical and microwave sensors have problems discerning snow beneath forest canopies. This paper describes a method that combines ground and satellite data to produce a Multiple-Dataset Snow-Cover Product (MDSCP). Comparisons with current snow-cover products show that the MDSCP draws together the advantages of each of its component products while minimizing their potential errors. Improved estimates of the snow-covered area are derived through the addition of two snow-cover classes ("thin or patchy" and "high elevation" snow cover) and from the analysis of the climate station data within each class. The compatibility of this method for use with Moderate Resolution Imaging Spectroradiometer (MODIS) data, which will be available in 2000, is also discussed. With the assimilation of these data, the resolution of the MDSCP would be improved both spatially and temporally and the analysis would become completely automated.

Tait, Andrew B.↗

NASA NTRS2011

Object-based Mapping of the Circumpolar Taiga-Tundra Ecotone with MODIS Tree Cover

The circumpolar taiga-tundra ecotone was delineated using an image segmentation based mapping approach with multi-annual MODIS Vegetation Continuous Fields (VCF) tree cover data. Circumpolar tree canopy cover (TCC) throughout the ecotone was derived by averaging MODIS VCF data from 2000 - 2005 and adjusting the averaged values using linear equations relating MODIS TCC to Quickbird-derived tree cover estimates. The adjustment helped mitigate VCF's overestimation of tree cover in lightly forested regions. An image segmentation grouped pixels representing similar tree cover into polygonal features (objects) that form the map of the transition zone. Eachfeature represents an area much larger than the 500m MODIS pixel to characterize thepatterns of sparse forest patches on a regional scale. Comparisons of the adjusted average tree cover data were made with (1) two existing tree line definitions aggregated for each 1deg longitudinal interval in North America and Eurasia and (2) Landsat-derived Canadianproportion of forest cover for Canada. The adjusted TCC from MODIS VCF shows, on average, greater than 12% TCC for all but one regional zone at the intersection with independently delineated tree lines. Adjusted values track closely with Canadian proportion of forest cover data in areas of low tree cover. Those polygons near the boreal/tundra interface with either (1) mean adjusted TCC values between 5-20% , or (2) mean adjusted TCC values <5% but with a standard deviation > 5% were used to identify the ecotone.

Ransom, Kenneth J.↗

NASA NTRS2012

Variability and Anomalous Trends in the Global Sea Ice Cover

The advent of satellite data came fortuitously at a time when the global sea ice cover has been changing rapidly and new techniques are needed to accurately assess the true state and characteristics of the global sea ice cover. The extent of the sea ice in the Northern Hemisphere has been declining by about -4% per decade for the period 1979 to 2011 but for the period from 1996 to 2010, the rate of decline became even more negative at -8% per decade, indicating an acceleration in the decline. More intriguing is the drastically declining perennial sea ice area, which is the ice that survives the summer melt and observed to be retreating at the rate of -14% per decade during the 1979 to 2012 period. Although a slight recovery occurred in the last three years from an abrupt decline in 2007, the perennial ice extent was almost as low as in 2007 in 2011. The multiyear ice, which is the thick component of the perennial ice and regarded as the mainstay of the Arctic sea ice cover is declining at an even higher rate of -19% per decade. The more rapid decline of the extent of this thicker ice type means that the volume of the ice is also declining making the survival of the Arctic ice in summer highly questionable. The slight recovery in 2008, 2009 and 2010 for the perennial ice in summer was likely associated with an apparent cycle in the time series with a period of about 8 years. Results of analysis of concurrent MODIS and AMSR-E data in summer also provide some evidence of more extensive summer melt and meltponding in 2007 and 2011 than in other years. Meanwhile, the Antarctic sea ice cover, as observed by the same set of satellite data, is showing an unexpected and counter intuitive increase of about 1 % per decade over the same period. Although a strong decline in ice extent is apparent in the Bellingshausen/ Amundsen Seas region, such decline is more than compensated by increases in the extent of the sea ice cover in the Ross Sea region. The results of analysis of MODIS, AMSR-E and SSM/I data reveal that the sea ice production rate at the coastal polynyas along the Ross Ice Shelf has been increasing since 1992. This also means that the salinization rate and the formation of bottom water in the region are going up as well. Simulation studies indicate that the stronger production rate is likely associated with the ozone hole that has caused a deepening of the lows in the West Antarctic region and therefore stronger winds off the Ross Ice Shelf. Stronger winds causes larger coastal polynyas near the shelf and hence an enhanced ice production in the region during the autumn and winter period. Results of analysis of temperature data from MODIS and AMSR-E shows that the area and concentration of the sea ice cover are highly correlated with surface temperature for both the Arctic and Antarctic, especially in the seasonal regions where the correlation coefficients are about 0.9. Abnormally high sea surface temperatures (SSTs) and surface ice temperatures (SITs) were also observed in 2007 and 2011when drastic reductions in the summer ice cover occurred, This phenomenon is consistent with the expected warming of the upper layer of the Arctic Ocean on account of ice-albedo feedback. Changes in atmospheric circulation are also expected to have a strong influence on the sea ice cover but the results of direct correlation analyses of the sea ice cover with the Northern and the Southern Annular Mode indices show relatively weak correlations, This might be due in part to the complexity of the dynamics of the system that can be further altered by some phenomena like the Antarctic Circumpolar Wave and extra polar processes like the El Nino Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (POD),

Comiso, Josefino C.↗

NASA NTRS2016

GC23G-1310: Investigation Into the Effects of Climate Variability and Land Cover Change on the Hydrologic System of the Lower Mekong Basin

The Lower Mekong Basin (LMB) is an economically and ecologically important region that experiences hydrologic hazards such as floods and droughts, which can directly affect human well-being and limit economic growth and development. To effectively develop long-term plans for addressing hydrologic hazards, the regional hydrological response to climate variability and land cover change needs to be evaluated. This research aims to investigate how climate variability, specifically variations in the precipitation regime, and land cover change will affect hydrologic parameters both spatially and temporally within the LMB. The research goal is achieved by (1) modeling land cover change for a baseline land cover change scenario as well as changes in land cover with increases in forest or agriculture and (2) using projected climate variables and modeled land cover data as inputs into the Variable Infiltration Capacity (VIC) hydrologic model to simulate the changes to the hydrologic system. The VIC model outputs were analyzed against historic values to understand the relative contribution of climate variability and land cover to change, where these changes occur, and to what degree these changes affect the hydrology. This study found that the LMB hydrologic system is more sensitive to climate variability than land cover change. On average, climate variability was found to increase discharge and evapotranspiration (ET) while decreasing water storage. The change in land cover show that increasing forest area will slightly decrease discharge and increase ET while increasing agriculture area increases discharge and decreases ET. These findings will help the LMB by supporting individual country policy to plan for future hydrologic changes as well as policy for the basin as a whole.

Hydrology↗

NASA NTRS2001

Soil Moisture and Snow Cover: Active or Passive Elements of Climate?

A key question in the study of the hydrologic cycle is the extent to which surface effects such as soil moisture and snow cover are simply passive elements or whether they can affect the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. GAPP region in determining the subsequent evolution of soil moisture and of snow cover. We have also made sensitivity studies with exaggerated soil moisture and snow cover anomalies in order to determine the physical processes that may be important. Results from simulations with realistic soil moisture anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. The initial state of soil moisture does not appear important, a result that held whether simulations were started in late winter or late spring. Model runs with exaggerated soil moisture reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in soil moisture, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and hence climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly affected the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectivity of snow is the most important process by which snow cover can impact climate, through lower surface temperatures and increased surface pressures. In early winter, the amount of solar radiation is very small and so this albedo, effect is inconsequential while in late winter, with the sun higher in the sky and period of daylight longer, the effect is much stronger. The results to date were obtained for model runs with present-day conditions. We are currently analyzing runs made with projected forcings for the 21st century to see if these results are modified in any way under likely scenarios of future climate change.

Oglesby, Robert J.↗

NASA NTRS2002

Soil Moisture and Snow Cover: Active or Passive Elements of Climate?

A key question in the study of the hydrologic cycle is the extent to which surface effects such as soil moisture and snow cover are simply passive elements or whether they can affect the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. in determining the subsequent evolution of soil moisture and of snow cover. We have also made sensitivity studies with exaggerated soil moisture and snow cover anomalies in order to determine the physical processes that may be important. Results from simulations with realistic soil moisture anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. The initial state of soil moisture does not appear important, a result that held whether simulations were started in late winter or late spring. Model runs with exaggerated soil moisture reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in soil moisture, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and hence climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly affected the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectively of snow is the most important process by which snow cover cart impact climate, through lower surface temperatures and increased surface pressures. In early winter, the amount of solar radiation is very small and so this albedo effect is inconsequential while in late winter, with the sun higher in the sky and period of daylight longer, the effect is much stronger.

Oglesby, Robert J.↗

NASA NTRS2005

Impacts of the Variability of Ice Types on the Decline of the Arctic Perennial Sea Ice Cover

The observed rapid decline in the Arctic perennial ice cover is one of the most remarkable signal of change in the Arctic region. Updated data now show an even higher rate of decline of 9.8% per decade than the previous report of 8.9% per decade mainly because of abnormally low values in the last 4 years. To gain insights into this decline, the variability of the second year ice, which is the relatively thin component of the perennial ice cover, and other ice types is studied. The perennial ice cover in the 1990s was observed to be highly variable which might have led to higher production of second year ice and may in part explain the observed ice thinning during the period and triggered further decline. The passive microwave signature of second year ice is also studied and results show that while the signature is different from that of the older multiyear ice, it is surprisingly more similar to that of first year ice. This in part explains why previous estimates of the area of multiyear ice during the winter period are considerably lower than the area of the perennial ice cover during the preceding summer. Four distinct clusters representing radiometrically different types have been identified using multi-channel cluster analysis of passive microwave data. Data from two of these clusters, postulated to come from second year and older multiyear ice regions are also shown to have average thicknesses of 2.4 and 4.1 m, respectively, indicating that the passive microwave data may contain some ice thickness information that can be utilized for mass balance studies. The yearly anomaly maps indicate high gains of first year ice cover in the Arctic during the last decade which means higher production of second year ice and fraction of this type in the declining perennial ice cover. While not the only cause, the rapid decline in the perennial ice cover is in part caused by the increasing fractional component of the thinner second year ice cover that is very vulnerable to total melt due to warming in the Arctic, especially in spring.

Comiso, Josefino C.↗