Abstract:
The assimilation of remotely sensed near-surface soil moisture, typically retrieved from active or passive microwave
observations, has been shown to improve modeled profile soil moisture. The assimilation of passive and
active microwave soil moisture data has not yet been directly compared, and so this study compares the impact
on soil moisture skill of assimilating soil moisture observations retrieved from the passive microwave Advanced
Microwave Scanning Radiometer (AMSR-E) and the active microwave Advanced Scatterometer (ASCAT). The
assimilation is performed with the NASA Catchment land surface model, using an Ensemble Kalman Filter (EnKF)
over 3.5 years. The impact of each assimilation is evaluated using in situ soil moisture observations from 85 sites
in the US and Australia, in terms of the anomaly time series correlation-coefficient, R. The skill gained by assimilating
either ASCAT, AMSR-E, or both was very similar, even when considered by land cover type. For each land
cover type represented, all of the assimilation experiments increased the mean surface and root-zone R, and each
assimilation also significantly increased the surface and root-zone R averaged across all 85 sites. Assimilating both
data sets consistently matched or slightly exceeded the best results from assimilating either ASCAT or AMSR-E.
Also, the ASCAT soil moisture retrieval skill was significantly lower over complex terrain, while assimilating the
AMSR-E data generated small improvements at these locations. For maximum accuracy and coverage it is then
recommended that active and passive microwave observations be assimilated together.