Microwave remote sensing has been largely applied to retrieve soil moisture (SM) from active and passive sensors. The obvious advantage of microwave sensors is that SM can be obtained regardless of atmospheric conditions. However, existing global SM products only provide observations at coarse spatial resolutions, which often hamper their application in regional hydrological studies. On the other hand, the vegetation temperature condition index (VTCI) has been widely used to monitor the SM status. It is based on high-spatial-resolution visible and infrared satellite observations. The aim of this study is to develop a simple and efficient downscaling approach for estimating accurate SM at higher spatial resolution. The VTCI calculated from the Moderate Resolution Imaging Spectroradiometer is used to downscale the coarse-resolution SM product that has been developed under the framework of the European Space Agency's Climate Change Initiative (CCI) projects. The original and downscaled SM estimates are further validated against the in situ SM observations collected in the Yunnan province (southwest China). It is found that the accuracy level of CCI SM is similar to the results from previously published validation studies. The downscaled SM can maintain the accuracy of CCI SM and, at the same time, present more spatial details, demonstrating the feasibility of the proposed method. Overall, the notable advantages of the proposed method are simplicity, limited data requirements and purely relying on satellite measurements, and comparable accuracy level to other complex downscaling schemes. It will facilitate local hydrological applications, particularly in data-scarce regions, where the above-listed characteristics are important and useful.

Soil moisture retrieved from satellite microwave remote sensing normally has spatial resolution on the order of tens of kilometers, which are too coarse for many regional hydrological applications such as agriculture monitoring and drought prediction. Therefore, various downscaling methods have been proposed to enhance the spatial resolution of satellite soil moisture products. The aim of this study is to investigate the validity and robustness of the simple vegetation temperature condition index (VTCI) downscaling scheme over a dense soil moisture observational network (REMEDHUS) in Spain. First, the optimized VTCI was determined through sensitivity analyses of VTCI to surface temperature, vegetation index, cloud, topography, and land cover heterogeneity, using data from Moderate Resolution Imaging Spectroradiometer~(MODIS) and MSG SEVIRI (METEOSAT Second Generation – Spinning Enhanced Visible and Infrared Imager). Then the downscaling scheme was applied to improve the spatial resolution of the European Space Agency's Water Cycle Multi-mission Observation Strategy and Climate Change Initiative (ESA CCI) soil moisture, which is a merged product based on both active and passive microwave observations. The results from direct validation against soil moisture observations, spatial pattern comparison, as well as seasonal and land use analyses show that the downscaling method can significantly improve the spatial details of CCI soil moisture while maintaining the accuracy of CCI soil moisture. The accuracy level is comparable to other downscaling methods that were also validated against the REMEDHUS network. Furthermore, slightly better performance of MSG SEVIRI over MODIS was observed, which suggests the high potential of applying a geostationary satellite for downscaling soil moisture in the future. Overall, considering the simplicity, limited data requirements and comparable accuracy level to other complex methods, the VTCI downscaling method can facilitate relevant hydrological applications that require high spatial and temporal resolution soil moisture.

Long-term global satellite and reanalysis soil moisture products have been available for several years. In this study, in situ soil moisture measurements from 2008 to 2012 over Southwest China are used to evaluate the accuracy of four satellite-based products and one reanalysis soil moisture product. These products are the Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E), the Advanced Scatterometer (ASCAT), the Soil Moisture and Ocean Salinity (SMOS), the European Space Agency's Climate Change Initiative soil moisture (CCI SM), and the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim). The evaluation of soil moisture absolute values and anomalies shows that all the products can capture the temporal dynamics of in situ soil moisture well. For AMSR-E and SMOS, larger errors occur, which are likely due to the severe effects of radio frequency interference (RFI) over the test region. In general, the ERA-Interim (R = 0.782, ubRMSD = 0.035 m(3)/m(3)) and CCI SM (R = 0.723, ubRMSD = 0.046 m(3)/m(3)) perform the best compared to the other products. The accuracy levels obtained are comparable to validation results from other regions. Therefore, local hydrological applications and water resource management will benefit from the long-term ERA-Interim and CCI SM soil moisture products.