Global Compound Hot‐Drought Diagnostic From a Non‐Stationary Perspective

Abstract Compound hot‐drought events (CHDEs) are intensifying under climate change and human pressures, posing mounting threats to socio‐economic stability. Such intensification underscores the non‐stationary nature of extreme climatic events, including droughts and heat, which are continuously evolving in response to a changing climate. However, conventional risk assessment frameworks, which relied on stationarity, often failed to capture evolving dependencies as external forcing alters hydroclimatic baselines. Therefore, we propose a non‐stationary standardized compound hot‐drought index (NSCHDI) to assess CHDEs using a time‐varying copula framework. This approach incorporates some major climate oscillations, such as ENSO and PDO, through principal component analysis to ensure temporal adaptability. Using global land data from 1950 to 2022, our results highlight three key insights: (a) The SPI 3 ‐STI coupling exhibited pronounced temporal variability, indicating a teleconnection modulated, non‐stationary dependence structure; (b) Compared to the conventional stationary index (SCHDI), NSCHDI enhanced the identification of severe‐to‐extreme CHDE occurrences by explicitly modeling climate‐conditioned, time‐varying dependence; (c) Beyond event identification, NSCHDI provided more reliable diagnostics of CHDE characteristics. Validation based on representative ENSO years (1997, 2010, and 2015) further demonstrated that NSCHDI‐based diagnostics better capture the timing and escalation of CHDE conditions, supporting enhanced early‐warning capabilities for detecting CHDEs. These results underscore the value of incorporating non‐stationary climate dynamics into multivariate indices to better quantify and manage to cascade risks from concurrent heat and drought extremes.