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At least 307 records · Page 17

Surface Hydrology in Global River Basins in the Off-Line Land-Surface GEOS Assimilation (OLGA) System

Land surface hydrology for the Off-line Land-surface GEOS Analysis (OLGA) system and Goddard Earth Observing System (GEOS-1) Data Assimilation System (DAS) has been examined using a river routing model. The GEOS-1 DAS land-surface parameterization is very simple, using an energy balance prediction of surface temperature and prescribed soil water. OLGA uses near-surface atmospheric data from the GEOS-1 DAS to drive a more comprehensive parameterization of the land-surface physics. The two global systems are evaluated using a global river routing model. The river routing model uses climatologic surface runoff from each system to simulate the river discharge from global river basins, which can be compared to climatologic river discharge. Due to the soil hydrology, the OLGA system shows a general improvement in the simulation of river discharge compared to the GEOS-1 DAS. Snowmelt processes included in OLGA also have a positive effect on the annual cycle of river discharge and source runoff. Preliminary tests of a coupled land-atmosphere model indicate improvements to the hydrologic cycle compared to the uncoupled system. The river routing model has provided a useful tool in the evaluation of the GCM hydrologic cycle, and has helped quantify the influence of the more advanced land surface model.

Bosilovich, Michael G.↗

Internal Physical Features of a Land Surface Model Employing a Tangent Linear Model

The Earth's land surface, including its biomass, is an integral part of the Earth's weather and climate system. Land surface heterogeneity, such as the type and amount of vegetative covering., has a profound effect on local weather variability and therefore on regional variations of the global climate. Surface conditions affect local weather and climate through a number of mechanisms. First, they determine the re-distribution of the net radiative energy received at the surface, through the atmosphere, from the sun. A certain fraction of this energy increases the surface ground temperature, another warms the near-surface atmosphere, and the rest evaporates surface water, which in turn creates clouds and causes precipitation. Second, they determine how much rainfall and snowmelt can be stored in the soil and how much instead runs off into waterways. Finally, surface conditions influence the near-surface concentration and distribution of greenhouse gases such as carbon dioxide. The processes through which these mechanisms interact with the atmosphere can be modeled mathematically, to within some degree of uncertainty, on the basis of underlying physical principles. Such a land surface model provides predictive capability for surface variables including ground temperature, surface humidity, and soil moisture and temperature. This information is important for agriculture and industry, as well as for addressing fundamental scientific questions concerning global and local climate change. In this study we apply a methodology known as tangent linear modeling to help us understand more deeply, the behavior of the Mosaic land surface model, a model that has been developed over the past several years at NASA/GSFC. This methodology allows us to examine, directly and quantitatively, the dependence of prediction errors in land surface variables upon different vegetation conditions. The work also highlights the importance of accurate soil moisture information. Although surface variables are predicted imperfectly due to inherent uncertainties in the modeling process, our study suggests how satellite observations can be combined with the model, through land surface data assimilation, to improve their prediction.

Yang, Runhua↗

Modeling the Effect of Wetlands, Flooding, and Irrigation on River Flow: Application to the Aral Sea

As the world's population continues to increase, additional stress is placed on water resources. This stress, coupled with future uncertainties regarding climate change, makes arid and semi-arid regions particularly vulnerable. One example is the Aral Sea where the freshwater inflow, which is dominated by snowmelt runoff, has decreased significantly since the expansion of intensive irrigation in the 1960s. The purpose of this paper is to use a river routing scheme from a global climate model to examine the flow of the Amu Dar'ya River into the Aral Sea. The river routing scheme is modified to include groundwater flow, flooding, and evaporative losses in the river's wetlands and floodplain, and anthropogenic withdrawals for irrigation. A set of scenarios is designed to test the sensitivity of river flow to the inclusion of these modifications into the river routing scheme. When riverine wetlands and floodplains are present, the river flow is reduced significantly and is similar to the observed flow. In addition the model results show that it is essential to incorporate human diversions to accurately represent the inflow to the Aral Sea, and they also indicate potential management strategies that might be appropriate to maintain a balance between inflow to the Sea and upstream diversions for irrigation.

Ferrari, Michael R.↗

Land-Atmosphere Interactions: Successes, Problems and Prospects

After two decades of active research, a much better understanding of the broader role of biospheric processes on the local climate has emerged. A surface-albedo increase, particularly in desert border regions of the subtropics (as well as the deforested tropical regions), leads to a net surface energy deficit, which in turn leads to a relative sinking and reduced rainfall. On the other hand, studies of the influence of altered ratios of evapotranspiration and sensible fluxes, in situations where the net solar income is unchanged, show that evapotranspiration is a more desirable flux for increased precipitation and vitality of the biosphere. Besides providing water vapor and convective available potential energy (CAPE) to the lower troposphere, evapotranspiration helps in building larger CAPE before "turning on" the moist-convection. Larger CAPE in the lower troposphere enables convection to reach into the deeper atmosphere thereby heating the upper troposphere; indeed, moist-convection is also accompanied by the evaporation of falling precipitation that cools and moistens the lower atmosphere. While convective, as opposed to stratiform, precipitation reduces the fractional cloud cover; it also allows more solar radiation to reach the surface thereby invigorating surface fluxes. These, together with moist convection and associated downdrafts help to maintain the characteristic upper temperature limit(s) of the moist-land as well as oceanic regions. Regardless of the above understanding, several important problems continue to hinder the accurate simulation of a realistic land atmosphere interaction in a numerical model (both GCM and/or Meso-scale models). Among the unsolved problems are parameterization of sub-grid scale land processes that include small-scale variability of soil moisture, snow-cover and snow-physics, the biodiversity of the biosphere, orography, local drainage characteristics under natural conditions, and surface flow over the natural terrain. A well-known non-linear response of surface fluxes to these variations makes the problem of parameterizing land-atmosphere interaction processes hard-to-address and simulate, particularly in a GCM. In our presentation, we will discuss how orographic, snow-cover, and water table interactions can be included into a Simple Biosphere Model such as SiB/SSiB. Figure I shows how, in the Russian region, spring snowmelt affects the soil moisture profile. Corresponding figure 2 shows how interaction with the water table decreases the natural evapotranspiration in the Sahel region simulation. While these simulations need better validation with data, the simulations reveal that surface processes are sensitive to these parameterizations. With these developments, we continue to advance our understanding of the interaction of land with the atmosphere aloft, but the intrinsic variability of the newer parameters, e. g., hydraulic properties of the soil, diminish the positive influences of these advances on the improved climate simulation with GCMs.

Sud, Y. C.↗

BOREAS HYD-9 Streamflow Data

The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-9 team collected several data sets containing precipitation and streamflow measurements over the BOREAS study areas. These streamflow data were collected by the HYD-09 science team to support its research into meltwater supply to the soil during the spring melt period. These data were also collected for HYD-09's research into the evolution of soil moisture, evaporation, and runoff from the end of the snowmelt period through freeze up. Data were collected in the BOREAS Southern Study Area (SSA) and Northern Study Area (NSA) from April until October in 1994, 1995, and 1996. Gauges southwest-1 and northwest-1 were operated year-round; however, data may not be available for both gauges for all three years. The data are available in tabular ASCII files. The HYD-09 streamflow data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Hall, Forrest G.↗

Using Climate Models to Evaluate Mechanisms of Glacial Inception

The initiation and subsequent growth of an ice sheet or large glacier is based on two primary factors: 1. Most fundamentally, a region must exist with a positive net snow accumulation, that is, cold season snowfall exceeds warm season snowmelt. Because snow can melt very rapidly, in a practical sense this probably means that little or no snow melt should occur in the warm season (mountain glaciers being one possible exception). 2. When sufficient ice builds in a region with a positive net snow accumulation, the ice will flow into adjoining regions with a negative mass balance. Feedbacks can also then arise between the emerging ice sheet and the overall climate, which, among other effects, may cause the mass balance in that region to turn positive. A key question is the relative importance of these two factors. In particular, is it possible for a large lowland region to experience a positive mass balance, such that the ice sheet can arise largely 'in-situ'? Or instead are uplands necessary, such that essentially mountain glaciers form first, and then, under the right conditions, grow and coalesce, eventually spreading out into the lowlands? This is probably the single most fundamental question to be addressed in the modeling of glacial inception. Other key questions then focus on how the (upland or low-land) positive mass balance is obtained at some times, but not others (the ice sheets are not continuously present). For Northern Hemisphere ice sheets in particular, what climatic conditions can lead to abundant winter snowfall in the Canadian Arctic and northern Labrador in conjunction with cool summertime conditions? Are both required, or will cool summer conditions alone suffice? Conversely, are a few years of abnormally heavy snowfall all that is required to trigger glacial inception? A major need at present is for carefully constructed climate model studies aimed at addressing these questions. A successful strategy will almost certainly require more than just a global model; while the global climate model might be necessary to properly simulate large-scale forcing, such models have insufficient spatial resolution to adequately address the roles of topography and the nature of the land surface. Necessary also is the use of a high-resolution regional climate model (in conjunction with a global model). Possible forcing mechanisms of Pleistocene ice ages are well known (e.g., orbital forcing; CO2 fluctuations) but we must understand and be able to successfully model the actual processes involved in glacial inception before we can fully understand the true roles played by these forcing mechanisms.

Oglesby, Robert J.↗

Formation of Gullies on Mars: What Do We Learn from Earth?

The observation of gullies on Mars indicates the presence of liquid water in recent times [1]. They have been proposed to result of subsurface seepage of water [1], geothermal activity [2] or brines [3], near-surface ice melting at recent periods of high obliquity [4], snowmelt in more recent periods [5] or liquid CO2 breakout [6]. In this study, we describe how terrestrial studies help to understand better the formation of Martian gullies. We show that all characteristics of Martian gullies are consistent with some external process triggered by seasonal melting at high obliquity.

Mangold, N.↗

Lunar and Planetary Science XXXV: Mars: Hydrology, Drainage, and Valley Systems

The titles in this section include: 1) Analysis of Orientation Dependence of Martian Gullies; 2) A Preliminary Relationship between the Depth of Martian Gullies and the Abundance of Hydrogen on Near-Surface Mars; 3) Water Indicators in Sirenum Terra and around the Argyre Impact Basin, Mars; 4) The Distribution of Gullies and Tounge-shaped Ridges and Their Role in the Degradation of Martian Craters; 5) A Critical Evaluation of Crater Lake Systems in Memnonia Quadrangle, Mars; 6) Impact-generated Hydrothermal Activity at Gusev Crater: Implications for the Spirit Mission; 7) Characterization of the Distributary Fan in Holden NE Crater using Stereo Analysis; 8) Computational Analysis of Drainage Basins on Mars: Appraising the Drainage Density; 9) Hypsometric Analyses of Martian Basins: A Comparison to Terrestrial, Lunar, and Venusian Hypsometry; 10) Morphologic Development of Harmakhis Vallis, Mars; 11) Mangala Valles, Mars: Investigations of the source of Flood Water and Early Stages of Flooding; 12) The Formation of Aromatum Chaos and the Water Discharge Rate at Ravi Vallis; 13) Inferring Hydraulics from Geomorphology for Athabasca Valles, Mars; 14) The Origin and Evolution of Dao Vallis: Formation and Modification of Martian Channels by Structural Collapse and Glaciation; 15) Snowmelt and the Formation of Valley Networks on Martian Volcanoes; 16) Extent of Floating Ice in an Ancient Echus Chasma/Kasei Valley System, Mars.

Source record↗

Depths and Geologic Setting of Northern Hemisphere Gullies (and Comparison to Their Southern Counterparts)

Gullies are recognized as having an incised (often sinuous) channel, alcove, and apron morphology as defined. Previous detailed work has focused on the characteristics of southern hemisphere gullies; here we examine the distribution, morphology and depth of northern hemisphere gullies. Gully locations (both hemispheres) were compiled from the literature, not a global search, and thus the gullies studied here are the subset of the whole for which corresponding MOLA tracks are available. We find that the heads of the majority of N. hemisphere gullies commence in a specific cliff-forming layer, and average 250 m below the local surface. This observation suggests that the rock layer has a genetic relationship to gullies and is difficult at present to reconcile with gully formation from snowmelt, which predicts no correlation to rock layers. Gully locations and depths correspond to specific geologic units. We propose that in addition to ground ice and a melting mechanism, gully formation requires groundwater flow along or within specific rock units.

Gilmore, Martha S.↗

Northern Hemisphere Gullies on Mars: Analysis of Spacecraft Data and Implications for Formation Mechanisms

The origin of geologically recent gullies on Mars has remained controversial since the discovery of these features by Malin and Edgett in 2000. Numerous models have been proposed which invoke various physical processes as well as various agents of erosion to explain the origin of the Martian gullies. Hypotheses to explain the formation of the gullies invoke shallow liquid water aquifers, deep liquid water aquifers, melting ground ice, snowmelt, dry landslides, and carbon dioxide aquifers. We test the validity of such gully formation mechanisms by analyzing data from the Mars Global Surveyor and Mars Odyssey spacecrafts to uncover trends in the dimensional and physical properties of the gullies and their surrounding terrain. A similar study has previously been completed for gullies located in the southern hemisphere of Mars. The work presented here focuses exclusively on gullies in the northern hemisphere based on the identification of 136 Mars Orbiter Camera (MOC) images containing clear evidence of gully landforms, distributed in the northern mid and high latitudes. These sites have been analyzed in combination with Mars Orbiter Laser Altimeter (MOLA), Thermal Emission Spectrometer (TES), and Gamma Ray Spectrometer (GRS) data to provide quantitative measurements of numerous gully characteristics. Parameters measured include apparent source depth and distribution, vertical and horizontal dimensions, slopes, compass orientations, near-surface ice content, and factors controlling present-day climatic conditions.

Heldmann, J. L.↗

Melting in Martian Snowbanks

Precipitation as snow is an emerging paradigm for understanding water flow on Mars, which gracefully resolves many outstanding uncertainties in climatic and geomorphic interpretation. Snowfall does not require a powerful global greenhouse to effect global precipitation. It has long been assumed that global average temperatures greater than 273K are required to sustain liquid water at the surface via rainfall and runoff. Unfortunately, the best greenhouse models to date predict global mean surface temperatures early in Mars' history that differ little from today's, unless exceptional conditions are invoked. Snowfall however, can occur at temperatures less than 273K; all that is required is saturation of the atmosphere. At global temperatures lower than 273K, H2O would have been injected into the atmosphere by impacts and volcanic eruptions during the Noachian, and by obliquity-driven climate oscillations more recently. Snow cover can accumulate for a considerable period, and be available for melting during local spring and summer, unless sublimation rates are sufficient to remove the entire snowpack. We decided to explore the physics that controls the melting of snow in the high-latitude regions of Mars to understand the frequency and drainage of snowmelt in the high martian latitudes.

Zent, A. P.↗

An Agent-Based Interface to Terrestrial Ecological Forecasting

The latest generation of NASA Earth Observing System (EOS) satellites has brought a new dimension to continuous monitoring of the living part of the Earth System, the biosphere. EOS data can now provide weekly global measures of vegetation productivity and ocean chlorophyll, and many related biophysical factors such as land cover changes or snowmelt rates. However, the highest economic value would come from forecasting impending conditions of the biosphere, to allow decision makers to mitigate dangers or exploit positive trends. NASA's strategic plan for the Earth Science Enterprise i d e n a s ecological forecasting as a focus for research. Ecological forecasting predicts the effects of changes in the physical, chemical and biological environment on ecosystem activity. Possible applications of such a system include predicting shortfalls or bumper crops of agricultural production, populations of threatened or invasive species or wildfire danger in time to allow improves preparation and logistical efficiency. Petabytes of remote sensing data are now available to help measure, understand and forecast changes in the Earth system, but using these data effectively can be surprisingly hard. The volume and variety of data files and formats are daunting. Simple data management activities, such as locating and transferring files, changing file formats, gridding point data, and scaling and reprojecting gridded data, can consume far more personnel time and resources than the actual data analysis. Some scientists commit to a particular data source or resolution just because using anything different would be more effort that it's worth. Better tools can help, but most of the tools developed to date are little more than shell scripts; they lack the flexibility to meet the diverse needs of users and are difficult to extend to handle changes in available data sources.

Golden, Keith↗

Analysis of Terrestrial Water Storage Changes from GRACE and GLDAS

Since March 2002, the Gravity Recovery and Climate Experiment (GRACE) has provided first estimates of land water storage variations by monitoring the time-variable component of Earth's gravity field. Here we characterize spatial-temporal variations in terrestrial water storage changes (TWSC) from GRACE and compare them to those simulated with the Global Land Data Assimilation System (GLDAS). Additionally, we use GLDAS simulations to infer how TWSC is partitioned into snow, canopy water and soil water components, and to understand how variations in the hydrologic fluxes act to enhance or dissipate the stores. Results quantify the range of GRACE-derived storage changes during the studied period and place them in the context of seasonal variations in global climate and hydrologic extremes including drought and flood, by impacting land memory processes. The role of the largest continental river basins as major locations for freshwater redistribution is highlighted. GRACE-based storage changes are in good agreement with those obtained from GLDAS simulations. Analysis of GLDAS-simulated TWSC illustrates several key characteristics of spatial and temporal land water storage variations. Global averages of TWSC were partitioned nearly equally between soil moisture and snow water equivalent, while zonal averages of TWSC revealed the importance of soil moisture storage at low latitudes and snow storage at high latitudes. Evapotranspiration plays a key role in dissipating globally averaged terrestrial water storage. Latitudinal averages showed how precipitation dominates TWSC variations in the tropics, evapotranspiration is most effective in the midlatitudes, and snowmelt runoff is a key dissipating flux at high latitudes. Results have implications for monitoring water storage response to climate variability and change, and for constraining land model hydrology simulations.

Syed, Tajdarul H.↗

Spring Snow Melt Timing and Changes over Arctic Lands

Spring snow cover over Arctic lands has, on average, melted approximately 4-7 days earlier since the late 1980s compared to the previous 20 years. The earlier disappearance of snow has been identified in non-mountainous regions at the 60 deg and 70 deg N parallels over Eurasia and North America using visible satellite observations of continental snow cover extent (SCE) mapped by the National Oceanic and Atmospheric Administration. The change was greater in the farthest north continental locations. Northern hemisphere SCE declined by almost 10% (May) to 20% (June) between the two intervals. At latitude 70 deg N, eight segments of longitude (each 10 deg in width) show significant (negative) trends. However, only two longitudinal segments at 60 deg N show significant trends, (one positive and one negative). SCE changes coincide with increasing spring warmth and the earlier diminution of sea ice in the last several decades. However, while sea ice has continued to decrease during this recent interval, snowmelt dates in the Arctic changed in a step-like fashion during the mid to late 1980s and have remained much the same since that time.

Foster, J. L.↗

Mapping Snow Grain Size over Greenland from MODIS

This paper presents a new automatic algorithm to derive optical snow grain size (SGS) at 1 km resolution using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. Differently from previous approaches, snow grains are not assumed to be spherical but a fractal approach is used to account for their irregular shape. The retrieval is conceptually based on an analytical asymptotic radiative transfer model which predicts spectral bidirectional snow reflectance as a function of the grain size and ice absorption. The analytical form of solution leads to an explicit and fast retrieval algorithm. The time series analysis of derived SGS shows a good sensitivity to snow metamorphism, including melting and snow precipitation events. Preprocessing is performed by a Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, which includes gridding MODIS data to 1 km resolution, water vapor retrieval, cloud masking and an atmospheric correction. MAIAC cloud mask (CM) is a new algorithm based on a time series of gridded MODIS measurements and an image-based rather than pixel-based processing. Extensive processing of MODIS TERRA data over Greenland shows a robust performance of CM algorithm in discrimination of clouds over bright snow and ice. As part of the validation analysis, SGS derived from MODIS over selected sites in 2004 was compared to the microwave brightness temperature measurements of SSM\I radiometer, which is sensitive to the amount of liquid water in the snowpack. The comparison showed a good qualitative agreement, with both datasets detecting two main periods of snowmelt. Additionally, MODIS SGS was compared with predictions of the snow model CROCUS driven by measurements of the automatic whether stations of the Greenland Climate Network. We found that CROCUS grain size is on average a factor of two larger than MODIS-derived SGS. Overall, the agreement between CROCUS and MODIS results was satisfactory, in particular before and during the first melting period in mid-June. Following detailed time series analysis of SGS for four permanent sites, the paper presents SGS maps over the Greenland ice sheet for the March-September period of 2004.

Lyapustin, Alexei↗

A Blended Global Snow Product using Visible, Passive Microwave and Scatterometer Satellite Data

A joint U.S. Air Force/NASA blended, global snow product that utilizes Earth Observation System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and QuikSCAT (Quick Scatterometer) (QSCAT) data has been developed. Existing snow products derived from these sensors have been blended into a single, global, daily, user-friendly product by employing a newly-developed Air Force Weather Agency (AFWA)/National Aeronautics and Space Administration (NASA) Snow Algorithm (ANSA). This initial blended-snow product uses minimal modeling to expeditiously yield improved snow products, which include snow cover extent, fractional snow cover, snow water equivalent (SWE), onset of snowmelt, and identification of actively melting snow cover. The blended snow products are currently 25-km resolution. These products are validated with data from the lower Great Lakes region of the U.S., from Colorado during the Cold Lands Processes Experiment (CLPX), and from Finland. The AMSR-E product is especially useful in detecting snow through clouds; however, passive microwave data miss snow in those regions where the snow cover is thin, along the margins of the continental snowline, and on the lee side of the Rocky Mountains, for instance. In these regions, the MODIS product can map shallow snow cover under cloud-free conditions. The confidence for mapping snow cover extent is greater with the MODIS product than with the microwave product when cloud-free MODIS observations are available. Therefore, the MODIS product is used as the default for detecting snow cover. The passive microwave product is used as the default only in those areas where MODIS data are not applicable due to the presence of clouds and darkness. The AMSR-E snow product is used in association with the difference between ascending and descending satellite passes or Diurnal Amplitude Variations (DAV) to detect the onset of melt, and a QSCAT product will be used to map areas of snow that are actively melting.

Foster, James L.↗

Spatial Patterns of Snow Cover in North Carolina: Surface and Satellite Perspectives

Snow mapping is a common practice in regions that receive large amounts of snowfall annually, have seasonally-continuous snow cover, and where snowmelt contributes significantly to the hydrologic cycle. Although higher elevations in the southern Appalachian Mountains average upwards of 100 inches of snow annually, much of the remainder of the Southeast U.S. receives comparatively little snowfall (< 10 inches). Recent snowy winters in the region have provided an opportunity to assess the fine-grained spatial distribution of snow cover and the physical processes that act to limit or improve its detection across the Southeast. In the present work, both in situ and remote sensing data are utilized to assess the spatial distribution of snow cover for a sample of recent snowfall events in North Carolina. Specifically, this work seeks to determine how well ground measurements characterize the fine-grained patterns of snow cover in relation to Moderate- Resolution Imaging Spectroradiometer (MODIS) snow cover products (in this case, the MODIS Fractional Snow Cover product).

Fuhrmann, Christopher M.↗

Potential for Monitoring Snow Cover in Boreal Forests by Combining MODIS Snow Cover and AMSR-E SWE Maps

Monitoring of snow cover extent and snow water equivalent (SWE) in boreal forests is important for determining the amount of potential runoff and beginning date of snowmelt. The great expanse of the boreal forest necessitates the use of satellite measurements to monitor snow cover. Snow cover in the boreal forest can be mapped with either the Moderate Resolution Imaging Spectroradiometer (MODIS) or the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) microwave instrument. The extent of snow cover is estimated from the MODIS data and SWE is estimated from the AMSR-E. Environmental limitations affect both sensors in different ways to limit their ability to detect snow in some situations. Forest density, snow wetness, and snow depth are factors that limit the effectiveness of both sensors for snow detection. Cloud cover is a significant hindrance to monitoring snow cover extent Using MODIS but is not a hindrance to the use of the AMSR-E. These limitations could be mitigated by combining MODIS and AMSR-E data to allow for improved interpretation of snow cover extent and SWE on a daily basis and provide temporal continuity of snow mapping across the boreal forest regions in Canada. The purpose of this study is to investigate if temporal monitoring of snow cover using a combination of MODIS and AMSR-E data could yield a better interpretation of changing snow cover conditions. The MODIS snow mapping algorithm is based on snow detection using the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to enhance snow detection in dense vegetation. (Other spectral threshold tests are also used to map snow using MODIS.) Snow cover under a forest canopy may have an effect on the NDVI thus we use the NDVI in snow detection. A MODIS snow fraction product is also generated but not used in this study. In this study the NDSI and NDVI components of the snow mapping algorithm were calculated and analyzed to determine how they changed through the seasons. A blended snow product, the Air Force Weather Agency and NASA (ANSA) snow algorithm and product has recently been developed. The ANSA algorithm blends the MODIS snow cover and AMSR-E SWE products into a single snow product that has been shown to improve the performance of snow cover mapping. In this study components of the ANSA snow algorithm are used along with additional MODIS data to monitor daily changes in snow cover over the period of 1 February to 30 June 2008.

Riggs, George A.↗