Spatiotemporal variability of terrestrial water storage and climate response processes in the Tianshan from geodetic observations

The Tianshan region Against the backdrop of ongoing global climate warming, the terrestrial water storage (TWS) changes are a complex dynamic process closely linked to climate change in the Tianshan. However, current researches in the Tianshan only focus on a specific component of TWS and are mainly analysed and discussed by using the Gravity Recovery and Climate Experiment (GRACE) observations, while the inversion results from Global Navigation Satellite System (GNSS) observations with high sensitivity and temporal resolution and their response analysis to extreme climate events are lacking. The synthetic test show that (1) the GNSS stations in the Tianshan are able to recover the TWS changes in this region, and the recovery is better in the east Tianshan. The actual inversion results show that (2) the TWS changes inferred from various datasets exhibit good consistency in the spatiotemporal characteristics. Seasonal TWS changes all show a decreasing trend from western Tianshan to eastern Tianshan, but the GNSS observations show a larger magnitude than the GRACE and Global Land Data Assimilation System (GLDAS) observations. The annual phases in the southern Tianshan are about 2 months later than those in the northern Tianshan. Additionally, we also investigate the relationship between the interannual TWS changes and El Niño/Southern Oscillation (ENSO). The results show that (3) the interannual TWS changes inferred from the GNSS observations can more accurately detect hydrological anomalies induced by ENSO and better correspond to the abrupt years of spatial grid anomalies in the precipitation and atmospheric water vapor content, indicating that precipitation is a main driving factor of the TWS changes in the Tianshan. Our goal is to emphasize the significant potential of GNSS in estimating the TWS changes and to help monitor the impact of extreme climate changes on the hydrological processes. • Inferring first the TWS changes in the Tianshan using GNSS observations. • Multi-source data are applied to analyze hydrologic processes in the Tianshan. • The sudden changes of TWS in the Tianshan closely agree precipitation anomaly associated with extreme climatic events. • GNSS-inferred TWS changes provide additional constraints for understanding hydrological dynamics in the Tianshan.