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The European Space Agency&#x0027;s Climate Change Initiative (ESA CCI) soil moisture could provide long-time microwave-retrieved soil moisture data but is limited to regional applications due to the low resolution (25 km). A new method of downscaling ESA CCI soil moisture to 1 km is presented in this study. First, the soil and vegetation component temperatures (SVCT) were estimated using MODIS land surface temperature and normalized difference vegetation index (NDVI) data. Following this, the relationship between ESA CCI soil moisture and 1-km SVCT was constructed based on the negative linear relationship between the temperature vegetation dryness index (TVDI) and soil moisture. The dry and wet lines used to estimate TVDI need not to be obtained in the method. The coefficients were obtained directly from 25-km ESA CCI soil moisture and 1-km SVCT by the upscaling algorithm of soil moisture. The method was applied to the Naqu area on the Tibetan Plateau. Downscaled soil moisture was validated with ground measurements collected at five sites within the soil moisture&#x002F;temperature monitoring network on the central Tibetan Plateau from May to October 2014. The results show that the trend of the time series of the downscaled soil moisture is similar to the ground measurements during this period, and the root-mean-square error is 0.0568 m<sup>3</sup>&#x002F;m<sup>3</sup>. The method is suitable for the condition with an NDVI higher than 0.4. The key points of the approach are to obtain SVCT and the relationship between soil moisture and SVCT.

Downscaling ESA CCI Soil Moisture Based on Soil and Vegetation Component Temperatures Derived From MODIS Data