A New Addition to Global Soil Moisture Mapping: CFOSAT Scatterometer Algorithm Development and Validation

Abstract

The monitoring of global soil moisture is crucial for understanding the hydrological cycle and managing terrestrial water resources. The China–France Oceanography Satellite (CFOSAT), equipped with the first sector-beam rotary scanning microwave scatterometer (CSCAT), provides a novel opportunity for global soil moisture mapping. However, the capability of CFOSAT’s Ku-band for soil moisture retrieval remains underexplored and lacks systematic evaluation. In this study, an Adaptive Backscatter Change Tracking (ABCT) algorithm is designed to retrieve absolute soil moisture from CFOSAT’s CSCAT measurements. The ABCT algorithm assumes a stable roughness, where changes in backscattering are primarily attributed to soil moisture variation based on a logarithmic relationship. It incorporates a vegetation influence coefficient, which quantifies how vegetation impacts the backscatter signal. This coefficient adaptively scales with changes in the Normalized Difference Vegetation Index to adjust the backscattering appropriately to include the effect of vegetation growth or decay. This allows the algorithm to isolate changes in the backscatter signal that are due to soil moisture while minimizing the false readings from vegetation growth or wilting. The CFOSAT ABCT algorithm’s performance was evaluated against extensive in-situ soil moisture data, demonstrating a robust correlation, with the Vertical-Vertical Polarization Ascending Orbit (VV Asc) result showing the highest accuracy, indicated by Pearson’s correlation coefficient (R) of 0.68 and unbiased root mean squared error (ubRMSE) of 0.057 m3/m3. Comparative analysis with the Advanced Scatterometer (ASCAT) data revealed that, while the ABCT algorithm’s correlation was slightly lower than that of the official EUMETSAT H SAF product, it notably improved the bias and ubRMSE metrics. This study underscores that the CFOSAT ABCT soil moisture retrieval algorithm and product are a valuable addition to global soil moisture mapping, complementing existing satellite missions or sensors such as SMAP, SMOS, ASCAT, AMSR2, and FY-3/MWRI.