• Atmosphere
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• v.34 no.4
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• pp.359-369
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• 2024

This study evaluates the performance of various soil moisture reanalysis datasets over the East Asian region to identify the most suitable product for climate and hydrological studies. The analysis includes land reanalysis products generated by the Noah, VIC, and Catchment land surface models (LSMs), driven by GLDAS2.0 near-surface atmospheric forcing, alongside MERRA2 and ERA5-land datasets. The 62 in-situ soil moisture measurements observed from 1980 to 2014 are used to validate the modeled data across the entire study period, while 58 of these measurements are used for the May to September (MJJAS) period. Results indicate that, when driven by the same atmospheric forcing, the Noah and Catchment models outperform VIC, and MERRA2 shows lower errors compared to ERA5-land. Seasonal soil moisture variability, primarily driven by the East Asian monsoon, peaks in September, with MERRA2 providing the most realistic simulation of seasonal phase and amplitude. Daily soil moisture variations are better captured by MERRA2 and ERA5-land than by GLDAS2.0-based products. Overall, MERRA2 emerges as the most reliable reanalysis dataset for evaluating both the climatological mean and variability of soil moisture in East Asia. Additionally, multi-model mean analysis reveals a long-term trend of drying soil moisture and enhanced land-atmosphere coupling in northern East Asia.

• Journal of Korea Water Resources Association
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• v.53 no.4
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• pp.285-291
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• 2020

The Noah 3.3 Land Surface Model (LSM) was used to estimate the global soil moisture in this study and these soil moisture datasets were assessed against satellite-based and reanalysis soil moisture products. The Noah 3.3 LSM simulated soil moistures in four soil layers and root-zone soil moistures defined as a depth-weighted average in the first three soil layers (i.e., up to 1.0 m deep). The Noah LSM soil moisture products were then compared with a satellite-based soil moisture dataset (European Space Agency Climate Change Initiatives (ESA CCI) SM v04.4) and reanalysis soil moisture datasets (ERA-interim). In addition, the five major basins (Yangtze, Mekong, Mississippi, Murray-Darling, Amazon) were selected for the assesment with the Gravity Recovery and Climate Experiment (GRACE)-based Total Water Storage Anomaly (TWSA) and TWS Change (TWSC). The results revealed that high anomaly correlations were found in most of the Asia-Pacific regions including East Asia, South Asia, Australia, and Noth and South America. While the anomaly correlations in the Murray-Darling basin were somewhat low, relatively higher anomaly correlations in the other basins were found. It is concluded that this study can be useful for the development of soil moisture based drought indices and subsequently can be helpful to reduce damages from drought by timely providing an efficacious strategy.