Can climate change signals be detected from the terrestrial water storage at daily timescales?

Abstract

Abstract Global terrestrial water storage (TWS) serves as a crucial indicator of freshwater availability on Earth, yet detecting climate change trends in TWS poses challenges due to uneven hydrological responses, limited observations, and internal climate variability. To overcome these limitations, we present a novel approach leveraging extensive observed and simulated meteorological data at daily scales to project global TWS based on its fingerprints embedded in weather patterns. By establishing the relationship between annual global mean TWS and daily surface air temperature and humidity fields in reanalyses and multi-model hydrological simulations till the end of 21st century, we successfully detect climate change signals emerging above internal variability noise. Our analysis reveals that, since 2016, climate change signals have been detected in approximately 50% of days for most years. Furthermore, the signals of climate change in global mean TWS have exhibited consistent growth over recent decades and are anticipated to surpass the influence of natural climate variability in the future under various emission scenarios. Our findings highlight the urgency of mitigating greenhouse gas emissions to not only mitigate warming risks but also to ensure future water security. This daily-scale detection of TWS provides valuable insights into the evolving impacts of climate change on global TWS dynamics, enhances our understanding of climate change impacts, and facilitates informed decision-making in multiple sectors.