资源环境科技发展态势分析平台

The European Space Agency (ESA), through the Climate Change Initiative (CCI), is currently providing nearly 4 decades of global satellite‐observed, fully homogenized soil moisture data for the uppermost 2‐5 cm of the soil layer. This data is valuable as it comprises one of the most complete remotely sensed soil moisture datasets available in time and space. One main limitation of the ESA CCI soil moisture dataset is the limited soil depth at which the moisture content is represented. In order to address this critical gap, we a) estimate and calibrate the Soil Water Index (SWI) using ESA CCI soil moisture against in situ observations from the International Soil Moisture Network and then b) leverage machine learning techniques and physical soil, climate, and vegetation descriptors at a global scale to regionalize the calibration. We use this calibration to assess the root zone soil moisture for the period 2001 – 2018. The results are compared against the European Centre for Medium‐Range Weather Forecasts, ERA5 Land and the Famine Early Warning Land Data Assimilation System (FLDAS) reanalyses soil moisture datasets, showing a good agreement, mainly over mid‐latitudes. This work contributes to the exploitation of ESA CCI soil moisture data, while the produced data can support large scale soil moisture related studies.

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