H21I-0827:
The SMAP Level 4 Surface and Root Zone Soil Moisture data assimilation product
Tuesday, 16 December 2014
Rolf H Reichle, NASA GSFC, Greenbelt, MD, United States, Gabrielle J.M. De Lannoy, NASA Goddard Space Flight Center, Greenbelt, MD, United States, Wade T Crow, Hydrol and Remote Sensing Lab, Beltsville, MD, United States, John S Kimball, The University of Montana, Flathead Lake Biological Station, Polson, MT, United States, Randal D Koster, NASA Goddard SFC, Greenbelt, MD, United States and Qing Liu, GMAO, building 33, Greenbelt, MD, United States
Abstract:
The NASA Soil Moisture Active Passive (SMAP) mission is scheduled for launch in January 2015 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 and pre-launch validation. Specifically, an L4_SM prototype product based on the assimilation of observations from the Soil Moisture and Ocean Salinity (SMOS) mission was validated using in situ measurements from SMAP core validation sites (densely instrumented watersheds) and from 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.
