The SMAP Level 4 Surface and Root Zone Soil Moisture (L4_SM) data assimilation product

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Tuesday, 6 January 2015: 11:15 AM
127ABC (Phoenix Convention Center - West and North Buildings)
Rolf H. Reichle, NASA/GSFC, Greenbelt, MD; and G. J. M. De Lannoy, W. T. Crow, J. Kimball, R. D. Koster, and Q. Liu

The NASA Soil Moisture Active Passive (SMAP) mission is scheduled for launch in November 2014 and will provide L-band radar and radiometer observations that are sensitive to surface soil moisture (in the top few centimeters of the soil column). For several of the key applications targeted by SMAP, however, knowledge of root zone soil moisture (defined here nominally as soil moisture in the top 1 m of the soil column) is needed. The SMAP mission will therefore provide a value-added Level 4 Surface and Root Zone Soil Moisture (L4_SM) product with the two key objectives: (i) to provide estimates of root zone soil moisture based on SMAP observations, and (ii) to provide a global surface and root zone soil moisture product that is spatially and temporally complete. The L4_SM algorithm uses an ensemble Kalman filter (EnKF) to merge SMAP observations with soil moisture estimates from the NASA GEOS-5 Catchment land surface model. The model describes the vertical transfer of soil moisture between the surface and root zone reservoirs and will be driven with observation-based surface meteorological forcing data, including precipitation, on a global 9 km Earth-fixed grid.

The presentation provides an overview of the SMAP L4_SM algorithm development, testing, and pre-launch validation using observations from the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission launched in November 2009. Specifically, multi-year, multi-angular L-band (1.4 GHz) brightness temperature observations from SMOS were used to (i) calibrate the parameters of the microwave radiative transfer model used in the L4_SM system and (ii) derive brightness temperature observations at 40 degrees incidence angle that mimic the SMAP Radiometer data. The latter observations were then assimilated into the L4_SM system and a prototype L4_SM data product was derived. This prototype product was validated using in situ measurements from four densely instrumented watersheds in the United States and more than 100 single-profile sensors scattered across the United States. The validation results indicate that the prototype soil moisture product satisfies the formal RMSE requirement for the L4_SM product of 0.04 m3/m3 (after removal of the long-term mean bias). An examination of the observation-minus-forecast residuals from the L4_SM system suggests where the system could be improved further.