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 m3m-3), followed by ERA5-Land (0.036 m3m-3). Among the SMOS SM, SMOS-IC had the lowest error (0.046 m3m-3), SMOS-BEC showed an intermediate value (0.048 m3m-3), and SMOS-CATDS had the highest error (0.055 m3m-3). © 2021 IEEE.
This work has been supported by the Spanish Ministry of Science and Innovation through the projects ESP2017-89463-C3-1R and ESP2017-89463-C3-2R, the ICM-CSIC Severo Ochoa Excellence Award CEX2019-000928-S, the CommSensLab-UPC María de Maeztu Excellence Award MDM-2016-0600, and the CSIC Interdisciplinary Thematic Platform TELEDETECT.
Peer Reviewed
Postprint (author's final draft)