The large observation footprint of low-frequency\r\nsatellite microwave emissions complicates the interpretation\r\nof near-surface soil moisture retrievals. While the effect of\r\nsub-footprint lateral heterogeneity is relatively limited under\r\nunsaturated conditions, open water bodies (if not accounted\r\nfor) cause a strong positive bias in the satellite-derived soil\r\nmoisture retrieval. This bias is generally assumed static and\r\nassociated with large, continental lakes and coastal areas.\r\nTemporal changes in the extent of smaller water bodies as\r\nsmall as a few percent of the sensor footprint size, however,\r\ncan cause significant and dynamic biases. We analysed the\r\ninfluence of such small open water bodies on near-surface\r\nsoil moisture products derived from actual (non-synthetic)\r\ndata from the Advanced Microwave Scanning Radiometer\r\nfor the Earth Observing System (AMSR-E) for three areas\r\nin Oklahoma, USA. Differences between on-ground observations,\r\nmodel estimates and AMSR-E retrievals were related\r\nto dynamic estimates of open water fraction, one retrieved\r\nfrom a global daily record based on higher frequency AMSRE\r\ndata, a second derived from the Moderate Resolution Imaging\r\nSpectroradiometer (MODIS) and a third through inversion\r\nof the radiative transfer model, used to retrieve soil\r\nmoisture. The comparison demonstrates the presence of relatively\r\nsmall areas (<0.05) of open water in or near the sensor\r\nfootprint, possibly in combination with increased, belowcritical\r\nvegetation density conditions (optical density <0.8),\r\nwhich contribute to seasonally varying biases in excess of\r\n0.2 (m3 m-3) soil water content. These errors need to be addressed,\r\neither through elimination or accurate characterisation,\r\nif the soil moisture retrievals are to be used effectively\r\nin a data assimilation scheme.
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