Development of a Physically Based Land Surface Emissivity for TMI
Abstract
Over-land precipitation retrieval using active or passive microwave spaceborne measurements requires accurate estimates of the radiometric signature of the surface to constrain the rainfall solutions. Such measurements are a vital part of the Tropical Rainfall Measuring Mission (TRMM) and the Global Precipitation Mission (GPM). For a passive microwave (PMW) radiometer, the radiometric signature is the land surface emissivity, which is characterized by uncertainties introduced by temporal variations of temperature, soil moisture and vegetation water content. Because no such characterization of the surface signature is available at microwave frequencies above L-band, current PMW land rainfall algorithms rely upon scattering-induced signatures at high frequencies (≥ 85 GHz) and are empirical in nature. Typically, not only is it difficult to quantify the spatial and temporal variability of the surface characteristics that are due to the rain itself, one would also need to know how the surface signature under the rain differs from the signature in neighboring clear areas. Therefore, an improved assessment of the surface emissivities are crucial if one is to make better use of emission-based channels (< 85 GHz) over land for TRMM and future GPM algorithms. In principle, accurate estimates of surface characteristics require accurate knowledge of land surface parameters including surface type, soil moisture and vegetation water content, and the forward modeling to convert land surface parameters to rain-affected surface emissivity. We demonstrate an adaptation of the land surface forward and inverse models that were developed for the AMSR-E and WindSat radiometers, to construct dynamic land surface emissivity datasets for use in physically-based precipitation retrievals over land. TRMM’s long life provides ample data to examine the surface properties under a wide range of environmental conditions, seasons, rain events, etc., and provides the means to examine the variability of the background state under clear and precipitating conditions.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2010
- Bibcode:
- 2010AGUFM.H21E1101T
- Keywords:
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- 0394 ATMOSPHERIC COMPOSITION AND STRUCTURE / Instruments and techniques;
- 1854 HYDROLOGY / Precipitation;
- 1866 HYDROLOGY / Soil moisture;
- 3354 ATMOSPHERIC PROCESSES / Precipitation