Validation of SMOS, SMAP, and ESA CCI Soil Moisture Over a Humid Region
With recent advances in satellite microwave soil moisture estimation, there is a demand for up-to-date validation of satellite soil moisture products. This article presents a sparse network validation over a humid region within the Laurentian Great Lakes basin for five state-of-the-art satellite soi...
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| Autores principales: | , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
IEEE
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/042f0e2d7e9e441bb6b4802ac688e534 |
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| Sumario: | With recent advances in satellite microwave soil moisture estimation, there is a demand for up-to-date validation of satellite soil moisture products. This article presents a sparse network validation over a humid region within the Laurentian Great Lakes basin for five state-of-the-art satellite soil moisture datasets, including the Soil Moisture and Ocean Salinity (SMOS) Level 2 Soil Moisture User Data Product (MIR_SMUDP2) V650, the Soil Moisture Active Passive (SMAP) Enhanced Level 3 Radiometer Soil Moisture (SPL3SMP_E) Version 4, and the European Space Agency Climate Change Initiative (CCI) Soil Moisture v05.2 (containing the Active, Passive, and Combined sets). Unsurprisingly, the five sets of soil moisture products performed differently. With respect to the unbiased root-mean-squared error (ubRMSE), the CCI Combined product performed best (an average ubRMSE of about 0.04 m<sup>3</sup> m<sup>−3</sup>), whereas the CCI Passive had the lowest performance with an average ubRMSE exceeding 0.10 m<sup>3</sup> m<sup>−3</sup>. Overall, in terms of correlation measure, the SMAP and CCI Combined performed better than other products, with the lowest skill from the SMOS product. The SMAP product performed best in the context of the soil moisture anomaly detection, whereas the SMOS and CCI Passive showed the lowest anomaly correlation with the <italic>in situ</italic> observations. The validation results provide an important guidance for hydrological and meteorological applications involving satellite soil moisture datasets in the study region or other similar areas. |
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