Climatological Evaluation of Three Assimilation and Reanalysis Datasets on Soil Moisture over the Tibetan Plateau

Abstract

Soil moisture is critical in the linkage between the land and atmosphere of energy and water exchange, especially over the Tibetan Plateau (TP). However, due to the lack of in situ plateau soil moisture measurements, the reanalyzed and assimilated data are the major supplements for TP climate research. Based on observations from 1992 to 2013, this study provides a comprehensive evaluation of three sets of assimilation and reanalysis products (GLDAS, ERA5-Land, and MERRA-2) on the climatic mean and variability of soil moisture over the Tibetan Plateau (TPSM). For the climatic mean, GLDAS captures the spatial distribution and annual cycle of TPSM better than other datasets in terms of lower spatial RMSE (0.07 m3×m-3) and bias (0.06 m3×m-3). In terms of the climatic variability of TPSM, the multi-data average (MDA) highlights its advantages in reducing the bias relative to any single data product. MDA describes the TPSM anomalies more stably and accurately in terms of temporal trend and variation (r = 0.94), as well as the dipole spatial pattern in EOF1. When considering both the climatic mean and spatial variability, the performance of MDA is more accurate and balanced than that of a single data product. This study overcomes the deficiency of limited time and space in previous evaluations of TPSM and indicates that multi-data averaging may be a more effective approach in the climate investigation of TPSM.