Regional compound drought and heatwave events over China and evaluation of ERA5-Land dataset based on classification approach

Compound events often exert more severe and widespread consequences than isolated extremes, and this effect is especially pronounced for those occurring at a regional scale. Here, we define and apply the concept of regional compound drought and heatwave events (RCDHEs) on daily scale to investigate spatiotemporally contiguous compound drought and heatwave events (CDHEs) across China during 1961–2022. We use homogenized observational data adapted from the China Meteorological Administration (CMA), and assess the performance of the state-of-the-art ERA5-Land reanalysis for its potential in supporting future studies. Rather than identifying events within fixed regions, we extract RCDHEs considering spatial and temporal coherence and characterize their dominant patterns through cluster analysis. The results reveal a marked increase in RCDHEs severity and duration across China over the recent decades. Over the mainland China RCDHEs can be grouped into eleven patterns. Most of these RCDHE patterns exhibit larger spatial extent, longer durations, and greater intensities during the recent decades. ERA5-Land effectively reproduces the various spatiotemporal features of these events; however, it consistently overestimates the frequency of RCDHEs across all region types since the late 1990s, limiting its reliability for assessing long-term trends. These findings enhance understanding of regional compound extremes in China and inform the appropriate application of ERA5-Land in future investigations of compound drought and heatwave events. • A new definition of regional compound drought and heatwave events (RCDHEs) is proposed and applied to assess their spatiotemporal characteristics across China. • Increasing trends in the severity and duration of RCDHEs were observed over mainland China. More frequent and severe RCDHEs occurred during the early 1960s and late 1990s. • Instead of relying on fixed regions, dominant RCDHE patterns are classified and extracted by cluster analysis, considering both spatial and temporal continuity. • The ERA5-Land dataset captures the main spatiotemporal characteristics of RCDHEs but largely overestimate the event frequency since the late-1990s, limiting its reliability for long-term trend assessment.