Dr. James L. Foster Profile

Dr. James L. Foster

Senior Scientist at NASA Goddard Space Flight Ctr

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Publications (7)

Proceedings Article | 4 October 2011 Paper

Remote sensing of snow cover and snow water equivalent for the historic February snowstorms in the Baltimore/Washington D.C. area during February 2010

James Foster, Dorothy Hall, George Riggs

Proceedings Volume 8174, 817402 (2011) https://doi.org/10.1117/12.896002

KEYWORDS: Microwave radiation, Terbium, Remote sensing, Snow cover, Clouds, Scattering, Crystals, Radiometry, Sensors, Environmental sensing

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Proceedings Article | 17 October 2006 Paper

Satellite observations of the date of snowmelt at 60º and 70º north latitude

J. Foster, D. Robinson, D. Hall, Tom Estilow

Proceedings Volume 6359, 635904 (2006) https://doi.org/10.1117/12.685126

KEYWORDS: Snow cover, Satellites, Earth observing sensors, Climatology, Climate change, Meteorology, Oceanography, Atmospheric modeling, Geography, Microwave radiation

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Proceedings Article | 26 October 2004 Paper

Mapping random and systematic errors of satellite-derived snow-water equivalent observations in Eurasia

James Foster, Chaojiao Sun, Jeffrey Walker, Richard Kelly, Jiarui Dong, Alfred Chang

Proceedings Volume 5568, (2004) https://doi.org/10.1117/12.564641

KEYWORDS: Crystals, Satellites, Microwave radiation, Phase modulation, Vegetation, Scattering, Error analysis, Sensors, Remote sensing, Snow cover

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Proceedings Article | 30 April 2003 Paper

Estimation of global snow cover using passive microwave data

Alfred Chang, Richard Kelly, James Foster, Dorothy Hall

Proceedings Volume 4894, (2003) https://doi.org/10.1117/12.467769

KEYWORDS: Microwave radiation, Snow cover, Error analysis, Satellites, Algorithm development, Scattering, Radiometry, Imaging systems, Data analysis, Radiative transfer

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This paper describes an approach to estimate global snow cover using satellite passive microwave data. Snow cover is detected using the high frequency scattering signal from natural microwave radiation, which is observed by passive microwave instruments. Developed for the retrieval of global snow depth and snow water equivalent using Advanced Microwave Scanning Radiometer EOS (AMSR-E), the algorithm uses passive microwave radiation along with a microwave emission model and a snow grain growth model to estimate snow depth. The microwave emission model is based on the Dense Media Radiative Transfer (DMRT) model that uses the quasi-crystalline approach and sticky particle theory to predict the brightness temperature from a single layered snowpack. The grain growth model is a generic single layer model based on an empirical approach to predict snow grain size evolution with time. Gridding to the 25 km EASE-grid projection, a daily record of Special Sensor Microwave Imager (SSM/I) snow depth estimates was generated for December 2000 to March 2001. The estimates are tested using ground measurements from two continental-scale river catchments (Nelson River and the Ob River in Russia). This regional-scale testing of the algorithm shows that for passive microwave estimates, the average daily snow depth retrieval standard error between estimated and measured snow depths ranges from 0 cm to 40 cm of point observations. Bias characteristics are different for each basin. A fraction of the error is related to uncertainties about the grain growth initialization states and uncertainties about grain size changes through the winter season that directly affect the parameterization of the snow depth estimation in the DMRT model. Also, the algorithm does not include a correction for forest cover and this effect is clearly observed in the retrieval. Finally, error is also related to scale differences between in situ ground measurements and area-integrated satellite estimates. With AMSR-E data, improvements to snow depth and water equivalent estimates are expected since AMSR-E will have twice the spatial resolution of the SSM/I and will be able to characterize better the subnivean snow environment from an expanded range of microwave frequencies.

Proceedings Article | 17 March 2003 Paper

Comparison of relative errors in snow maps in North America and Eurasia in 2001-2002

James Foster, Dorothy Hall, R. Kelly, Alfred Chang, J. Chien

Proceedings Volume 4879, (2003) https://doi.org/10.1117/12.474411

KEYWORDS: MODIS, Snow cover, Microwave radiation, Clouds, Composites, Sensors, Crystals, Satellites, Reflectivity, Liquids

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Proceedings Article | 23 January 2001 Paper

Snow crystal and land cover effects on the scattering of passive microwave radiation for algorithm development

James Foster, J. Barton, Alfred Chang, Dorothy Hall

Proceedings Volume 4171, (2001) https://doi.org/10.1117/12.413927

KEYWORDS: Microwave radiation, Crystals, Algorithm development, Scattering, Satellites, Radiometry, Sensors, Liquids, Crystallography, Radiative transfer

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In developing and tuning passive microwave algorithms, which are used to estimate snow extent, snow water equivalent and snow depth, much of the effort has been directed towards better accounting for the effects of snow crystal size on the microwave response, and relatively little effort has been given to the role that crystal shape or orientation plays in this regard. Modeling using a discrete dipole scattering models has shown that the assumption used in radiative transfer approaches, where snow crystals are modeled as randomly oriented spheres, is adequate to account for the transfer of microwave energy emanating from the ground and passing through a snowpack. With this in mind and by having some knowledge of the size of the particles in the snowpack as well as the snowpack density, snow depth algorithms can be designed for specific basins to assess the snow water equivalent of the basin and to thus, estimate snowmelt runoff and seasonal streamflow. Work performed on an ongoing GCIP/GEWEX experiment for watersheds in the upper Mid West and the northern Great Plains (the Roseau river basin in Minnesota/Manitoba, and the Black river basin in Wisconsin) has shown that for each of these basins, a strong conelation exists between snow depth derived from SSMI passive microwave data and snow depth measured at meteorological stations and determined from airborne gamma overflights. For instance, for the Roseau basin in mid March (Julian day 75), during the period from 1992-1998, the coefficient of determination (R2) is a very strong 0.8975. Thus, ninety percent of the mid March snow depth variation in this basin, during these years, can be explained by the SSMI snow algorithm. Streamfiow has also been correlated with maximum seasonal snow depth for these two basins as well (Figure 3). Using only SSMI-derived snow depth as the predictor or dependent variable, the R2 value for the Roseau basin was 0.715 between the basin-wide snow depth on March 15 and ensuing streamfiow for the month of April. When there is a high degree of assurance that the satellite-derived estimates are reliable (the algorithms produce results which reflect the streamfiow — hydrographs), they can then be used to generate input to hydrologic models.

Proceedings Article | 31 January 1995 Paper

Snow mass in boreal forests derived from a modified passive microwave algorithm

James Foster, Alfred Chang, Dorothy Hall

Proceedings Volume 2314, (1995) https://doi.org/10.1117/12.200738

KEYWORDS: Microwave radiation, Vegetation, Satellites, Algorithm development, Reflectivity, Climatology, Radiometry, Crystals, Scattering, Solar radiation

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