A statistical retrieval algorithm for root zone soil moisture

An algorithm for the estimation of root zone soil moisture is presented. Global fields of the soil moisture within the uppermost metre of soil are derived with a temporal resolution of 10 days. For calibration, long-term soil moisture observations from the former Soviet Union are used. The variance of the measurements is largely dominated by the spatial variability of the long-term mean soil moisture, while the temporal variability gives comparatively small contribution. Consequently, the algorithm is organised into two steps. The first step concentrates on the retrieval of the spatial variance of the long-term means, which comprises more than 85% of the total soil moisture variability. A major part of the spatial variance can be explained by four easily available fields: the climatological precipitation, land use, soil texture, and terrain slope. The second step of the algorithm is dedicated to the local temporal variability. This part of variability is recovered by using passive microwave data from scanning multichannel microwave radiometre (SMMR) supported by monthly averaged fields of air temperature and precipitation. The 6-GHz channel of SMMR is shown to be severely disturbed by radio frequency interference, so that information from the 10-GHz channel is used instead. The algorithm provides reasonable soil moisture fields which is confirmed by a comparison with independent measurements from Illinois.