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Correlated Triple Collocation to Estimate SMOS, SMAP and ERA5-Land Soil Moisture Errors

The novel Correlated Triple Collocation (CTC) analysis allows to assess three different data sources of similar spatial resolutions, but with two of them being correlated. In this study, the CTC was applied to estimate the unbiased random errors of the global soil moisture (SM) data provided by two L-band satellite missions —the Soil Moisture and Ocean Salinity (SMOS) and the Soil Moisture Active Passive (SMAP)— and one numerical model—the ERA5-Land. The three existing SMOS SM products distributed by different research institutions were also analyzed. Preliminary results revealed that errors of SMOS and SMAP SM are correlated, with correlations of ∼0.5-0.6. Thus, only ERA5-Land can be considered as independent. The lowest error was obtained for SMAP (0.025 m<sup>3</sup>m<sup>−3</sup>), followed by ERA5-Land (0.036 m<sup>3</sup>m<sup>−3</sup>). Among the SMOS SM, SMOS-IC had the lowest error (0.046 m<sup>3</sup>m<sup>−3</sup>), SMOS-BEC showed an intermediate value (0.048 m<sup>3</sup>m<sup>−3</sup>), and SMOS-CATDS had the highest error (0.055 m<sup>3</sup>m<sup>−3</sup>).