Spatiotemporal characteristics of soil Moisture and land – atmosphere coupling over the Tibetan Plateau derived from three gridded datasets

Soil moisture is a crucial component of the water cycle and plays an important role in regional weather and climate. However, owing to the lack of In Situ observations, an accurate understanding of the spatiotemporal variations of soil moisture (SM) on the Tibetan Plateau (TP) is still lacking. In this study, we used three gridded SM products to characterize the spatiotemporal features of SM on the TP during the warm season (May to August). We analyzed the fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis (ERA5), Global Land Data Assimilation System (GLDAS), and Soil Moisture Active Passive (SMAP) datasets and used station observation data and triple collocation to quantify product accuracy and consistency. Results of the evaluation based on observation data show that both ERA5 and GLDAS overestimate SM, while the accuracy of SMAP is high. In terms of capturing the temporal variations of SM measured at stations, the performance of ERA5 and that of SMAP are superior to that of GLDAS. According to the evaluation based on triple collocation, SMAP exhibits the smallest random error over the TP and the highest temporal correlation with the unknown true SM in eastern TP. For SMAP, SM variability is the largest in the southern TP. For ERA5 and GLDAS, variability in the western TP is substantially larger than that for SMAP. Low-frequency (30–90 days) variations are the largest contributor to TP SM intraseasonal variability. Relative to SMAP, the contribution of high-frequency variations is low in ERA5 and GLDAS. Land-atmosphere coupling is stronger (weaker) in the western (southeastern) TP, which is relatively dry (wet). Our evaluation of SM product performance over the TP may facilitate the use of these products for disaster monitoring and climate and hydrological studies.