A Novel Metric for Quantifying Precipitation-Driven Variability in Global Terrestrial Water Storage

Under global climate change and human intervention, an increased frequency of alternating drought and flood events exists, making such extreme conditions seemingly the new normal. These frequent events result in greater variability in terrestrial water storage anomalies (TWSA) (i.e., nonstationary behavior). In this study, we introduce a novel and straightforward metric, i.e., the standard deviation of TWSA (STDTWSA), to detect regions with nonstationary in TWSA and gain insight into the impact of global change on regional TWSA. TWSA estimates from the Center for Space Research (CSR) Mascon are used to calculate STDTWSAand estimated in a rolling window approach, and the results are compared with STD in precipitation anomalies (PA) and temperature anomalies (TA). Our results reveal that 63.8% of global land areas show significant prevalence of increasing TWSA variability with nonstationary, while only 3.5% exhibit a decrease. Among the 40 large basins analyzed, 11 show significant upward trends in STDTWSA, with only one basin showing a significant decline from 2002 to 2022. In 34 of these basins, precipitation accounts for over 50% of TWSA variability, suggesting that variabilities in precipitation anomalies can be used to model and explain the nonstationary behavior of TWSA in these regions. Additionally, in 3 of the remaining 6 basins, we observed significant correlations between TWSA and PA variability at five-year window. Furthermore, WGHM-modeled STDTWSAestimates align with the STDTWSAfrom CSR and show consistent trends in most basins. By linking precipitation-driven dynamics to TWSA variability, this study demonstrates the utility of STDTWSAas a practical tool for identifying regions vulnerable to hydrological extremes. This study provides valuable insights into global TWSA nonstationarity and enhances our understanding of the impacts of global climate change and human intervention on water storage changes.