H14F-03
Development and Initial Assessment of the SMAP Passive Soil Moisture Product

Monday, 14 December 2015: 16:30
3022 (Moscone West)
Rajat Bindlish1, Steven Chan2, Peggy E O'Neill3, Thomas J Jackson4, Eni G Njoku5, Andreas Colliander2, Michael H Cosh6, Fan Chen1 and Wade T Crow6, (1)U. S. Dept. of Agriculture, Beltsville, MD, United States, (2)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (3)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (4)USDA ARS, Pendleton, OR, United States, (5)Jet Propulsion Laboratory, Pasadena, CA, United States, (6)USDA Agricultural Research Service New England Plant, Soil and Water Research Laboratory, East Wareham, MA, United States
Abstract:
The Soil Moisture Active Passive (SMAP) mission was launched on Jan 31, 2015. This presentation describes the development and validation of the SMAP radiometer-only soil moisture product (L2_SM_P). The SMAP L2_SM_P product uses the Level 1 brightness temperature observations on an Earth-fixed grid at a 36 km resolution. A variety of static ancillary data (e.g. water fraction, soil texture, land cover classification, vegetation index climatology) and dynamic ancillary data (e.g. near real-time soil temperature, freeze/thaw state, rainfall intensity) are also ingested in the retrieval process.

Several algorithms are being considered for the SMAP radiometer-only soil moisture retrieval: (a) Single Channel Algorithm (SCAH): based on a zero-order approximation to the radiative transfer equation and uses the H-polarization observations to estimate soil moisture. Brightness temperature is corrected for the effects of temperature, vegetation, and roughness (static ancillary data sets). (b) Single Channel Algorithm (SCAV): based on the radiative transfer equation and uses the V-polarization observations to estimate soil moisture. (c) Dual Channel Algorithm: uses the horizontal and vertical polarization observations to iteratively solve for soil moisture and vegetation opacity. (d) Microwave Polarization Ratio Algorithm (MPRA): an alternative two-parameter retrieval model (soil moisture and vegetation opacity) that uses the microwave polarization difference index at 1.4 GHz and emissivity to parameterize vegetation opacity and estimate soil moisture.

The accuracy of the preliminary product will be evaluated using in situ data, sparse networks, and other satellite data products. Initial results indicate that the SMAP L2_SM_P algorithms are making progress towards meeting the target accuracy requirement. This paper will focus on the implementation of the different SMAP L2_SM_P algorithms using the current version (beta release) of the SMAP radiometer data. Further analysis of these algorithms is ongoing. This work will help in the selection and development of the operational algorithm for the validated SMAP passive soil moisture product.

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