Fei Huo, Li Xu, Yanping Li, Zhenhua Li (2022). Detection of climate change in terrestrial water storage from global weather patterns. Proceedings of the GWF Annual Open Science Meeting, May 16-18, 2022.

Climatologists use formal detection and attribution methods to identify externally forced signals in the observed climate record. Even with these widely used methods, it is still difficult to detect climate change in terrestrial water storage (TWS) at global scale due to the brevity of the time series from global freshwater observations. In this study, we applied a novel method to identify relationship between annual global mean TWS and daily weather patterns (including surface air temperature and humidity fields) using hydrological simulations from ISIMIP2b, yielding fingerprints of anthropogenically forced change. Reanalysis datasets are projected onto the fingerprints to detect climate change at daily scale. It is found that approximately 80% of days for most years since 2016 have informed climate change signals, with high inter-annual variability. While strong signals of forced climate change in global mean TWS could not be uniformly detected from each day during the studied period, the fraction of days detected started to surge from the mid-1970s. Climate change signals in global mean TWS have been accumulated over the last few decades, and our results show that such signals will probably be uniformly detected in every day in the next few decades.

AOSM2022 GWF modeling core First Author: Fei Huo, Global Institute for Water Security, University of Saskatchewan Additional Authors: Li Xu, Global Institute for Water Security; Yanping Li, Global Institute for Water Security; Zhenhua Li, Global Institute for Water Security.