Towards an operationally capable error-characterized 0-100 cm soil moisture dataset from C3S

Abstract

Global surface soil moisture (SSM) datasets derived from satellite observations in the microwave domain are nowadays available at a variety of resolutions and cover a variety of periods. Most of these records only incorporate measurements from a single satellite (e.g. from SMOS) and are therefore limited by its lifespan. However, there are ways to generate long-term data records by harmonising the observations of multiple (active and passive) satellite sensors (e.g. ESA CCI SM). The Copernicus Climate Change Service (C3S) has adapted these methods and currently provides a more than 40-year long SSM record with a delay of only 10-20 days. However, satellite-based soil moisture observations are limited to the topmost layer of the soil (0-5 cm) and do not provide information on water content in the root-zone (0-100 cm). Root-zone soil moisture (RZSM) controls evapotranspiration and is a key parameter for closing the water cycle, studying hydrological processes as well as drought monitoring and forecasting. While at present no satellite mission is capable of measuring RZSM directly, it can be approximated from SSM using land surface models. Alternatively, conditions in the root-zone can also be propagated from SSM using Soil Water Index (SWI) – a simplified two-layer infiltration model – by smoothing and delaying SSM temporal dynamics using an exponential filter. The method’s single parameter T (temporal lengths ruling the infiltration) is assumed to represent all environmental and climatic factors controlling the soil moisture’s temporal dynamics. While it has been demonstrated in a selection of studies that T generally increases with soil’s depth, the influence of other processes remains contested. Here we introduce the advances in our work on the operationally capable, depth-translated and error characterized 0-100 cm soil moisture dataset from the C3S Soil Moisture v202012 COMBINED product. The uniqueness of this global dataset lays in the fact that the SWI characteristic T-values were translated into particular soil depths based on correlation metrics with in situ measurements. This makes the data much more intuitive, easily applicable and user friendly compared to SWI products for various T-values. Available are volumetric soil moisture values for the top 1 m of the soil profile at 10 cm intervals with uncertainty estimates obtained with an exponential filter-adapted error-propagation technique. Additionally we present the results of an extensive global validation against in situ measurements from the International Soil Moisture Network (ISMN) and modelled SM from ERA5-Land.