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Two data sets of satellite surface soil moisture retrievals are first compared and then assimilated into the NASA Catchment land surface model. The first satellite data set is derived from 4 years of X‐band (10.7 GHz) passive microwave brightness temperature observations by the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E), and the second is from 9 years of C‐band (6.6 GHz) brightness temperature observations by the Scanning Multichannel Microwave Radiometer (SMMR). Despite the similarity in the satellite instruments, the retrieved soil moisture data exhibit very large differences in their multiyear means and temporal variability, primarily because they are computed with different retrieval algorithms. The satellite retrievals are also compared to a soil moisture product generated by the NASA Catchment land surface model when driven with surface meteorological data derived from observations. The climatologies of both satellite data sets are different from those of the model products. Prior to assimilation of the satellite retrievals into the land model, satellite‐model biases are removed by scaling the satellite retrievals into the land model's climatology through matching of the respective cumulative distribution functions. Validation against in situ data shows that for both data sets the soil moisture fields from the assimilation are superior to either satellite data or model data alone. A global analysis of the innovations (defined as the difference between the observations and the corresponding model values prior to the assimilation update) reveals how changes in model and observations error parameters may enhance filter performance in future experiments.
Reichle et al. (Mon,) studied this question.