Tedesco, M., P. Narvekar, R. Kelly, J. Foster, and R. H. Reichle:
"Assessment and development of the NASA AMSR-E SWE algorithm"
Presentation at the 11th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRAD), Washington, DC, USA, 2010.

Abstract:
We report results regarding the assessment and validation of the current NASA AMSR-E SWE operational product and its refinement and development. For the validation, we use either Snow Data Assimilation System (SNODAS) data and snow depth values measured by weather stations of the World Meteorological Organization (WMO). The validation is reported for different forest cover fraction and density values. Density values used in the AMSR-E SWE product are also compared with those derived from SNODAS. Effective grain size is estimated from the inversion of an electromagnetic model and the relative spatio-temporal distribution discussed in conjunction with the dynamic coefficients used in the current operational algorithm to derive snow depth from the brightness temperature differences.

On the development side, we report results obtained by using either an approach based on the ingestion of land surface model outputs into an electromagnetic physically-based inversion framework or an alternative approach based on an architecture of neural networks trained with ground and satellite observations spatially scaled by means of kriging techniques. The pros and cons of the above mentioned approaches are discussed in conjunction with the more 'classical' brightness temperature gradient approach. Lastly, a potential strategy for the future NASA AMSR-E product is outlined and discussed.


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