Assimilation of SMOS Brightness Temperature to Improve Surface and Root-Zone Soil Moisture
We evaluate the assimilation of multi-angular, horizontally and vertically polarized observations of L-band (1.4 GHz) microwave brightness temperature from SMOS mission in a land-only data assimilation system. The assimilation system consists of an ensemble Kalman filter (EnKF) and the NASA Catchment land surface model, supplemented with a tau-omega radiative transfer model. The Catchment model is driven with surface meteorological forcing data from the NASA GEOS-5 atmospheric analysis system, with precipitation corrected towards gauge-based observations. The radiative transfer model is calibrated to deal with long-term biases, whereas shorter-term biases are addressed inside the assimilation system. The assimilation system includes downscaling of coarse-scale (~ 36 km) observations and provides improved surface and root zone soil moisture estimates at a horizontal resolution of 9 km every three hours.
We assess the performance of the assimilation system by validating the SMOS-based soil moisture assimilation results against independent in situ measurements for select watersheds and for sparse networks. Our results indicate that the SMAP L4_SM root zone soil moisture data product will meet its accuracy requirement of 0.04 m3/m3 (after removal of the long-term mean bias).