On the Disaggregation of Passive Microwave Soil Moisture Data using a Priori Knowledge of Temporally Persistent Soil Moisture Fields

Water and energy fluxes at the interface between the land surface and atmosphere are affected by the surface water content of the soil, which is highly variable in space and time. Recent satellite mission concepts, as e.g. the Soil Moisture and Ocean Salinity Mission (SMOS), are dedicated to provide global soil moisture information with a temporal frequency of a few days to capture the high temporal dynamics of surface soil moisture. As passive microwave sensors have a spatial resolution in the order of tens of kilometers, the application of the data in mesoscale flood forecasting or water balance models is hampered due to the different spatial scales. The paper investigates the potential of using prior information on spatially persistent soil moisture fields to disaggregate SMOS scale soil moisture products. The approach is based on a ten-year soil moisture climatology, derived from a state-of-the-art land surface scheme. The developed approach shows a generally good performance for large parts of the test site, where soil moisture can be disaggregated with an accuracy better than the 4 vol.% benchmark of the SMOS mission.