| Autor: |
Fang, Bin, Lakshmi, Venkataraman, Zhang, Runze |
| Předmět: |
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| Zdroj: |
Vadose Zone Journal; Mar2024, Vol. 23 Issue 2, p1-30, 30p |
| Abstrakt: |
Soil moisture (SM) is an important component for many applications in agriculture, hydrology, meteorology, and ecology. In past decades, passive/active microwave sensors onboard Earth observation satellites are utilized to obtain SM estimates from radiometer or radar observations. In this study, the Soil Moisture and Ocean Salinity (SMOS) Level 3 daily SM retrievals at 25‐km spatial resolution between 2010 and 2021 were downscaled through an apparent thermal inertia principle‐based algorithm. The 1‐km downscaled SMOS SM retrievals were validated by in situ measurements from 635 sites of 19 SM networks in the world, which were acquired from the International Soil Moisture Network and Texas Soil Observation Network. Additionally, the validation results of the SMOS SM products were compared with those of the Soil Moisture Active Passive (SMAP) global Level 2 enhanced SM products at 1‐km downscaled and original 9‐km resolution in 2015–2021. It shows that the downscaled SMOS SM data have an overall improved accuracy and outperform the coarse‐resolution 25‐km data, with a lower unbiased Root Mean Squared Error of 0.114 m3/m3 on average. Core Ideas: Downscaled Soil Moisture and Ocean Salinity (SMOS) soil moisture (SM) retrievals have better accuracy and more spatial features than coarse SM.Soil Moisture and Ocean Salinity (SMOS) soil moisture (SM) retrievals show a drier trend and higher spatial variability than SMAP SM.Soil Moisture and Ocean Salinity (SMOS) soil moisture (SM) data quality is improved more from the downscaling algorithm than Soil Moisture Active Passive (SMAP). [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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