Data assimilation of space-based passive microwave soil moisture retrievals and the correction for a dynamic open water fraction

The large observation footprint of low-frequency satellite microwave emissions complicates the interpretation of near-surface soil moisture retrievals. While the effect of sub-footprint lateral heterogeneity is relatively limited under unsaturated conditions, open water bodies, if not accounted for, cause a strong positive bias in the satellite-derived soil moisture retrieval. This bias is generally assumed to be static and associated with large continental lakes and coastal areas. Temporal changes in the extent of smaller water bodies as small as a few percent of the sensor footprint size, however, can also cause significant and dynamic biases. We analysed the influence of open water on near-surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) for three areas in Oklahoma, USA. Differences between on-ground observations or model estimates and AMSR-E retrievals were compared to dynamic estimates of open water fraction derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). The comparison indicates that seasonally varying biases of up to 20% soil water content can be attributed to the presence of relatively small areas (<5%) of open water in or near the sensor footprint. The analysis presented here will help determine which of the data fields, either the retrieved parameter or the observed microwave brightness temperature, is most suitable for assimilation with simulated fields from land surface models.