Extreme climate events pose significant threats to ecosystems and economies. Compound extreme events (CEEs), where multiple extreme events occur simultaneously or consecutively, exacerbate these risks. Compound heatwave and drought events (CHDEs) are a common type of CEE, characterized by a negative thermodynamic relationship between temperature and rainfall. Persistent heatwaves lead to moisture deficiency and drought, while drought intensifies heatwaves through increased sensible heat release. Global warming has increased CHDE frequency and probability globally, with devastating consequences like the 2010 Russian CHDE, which caused tens of thousands of deaths and significant agricultural losses. Understanding the anthropogenic contribution to CHDEs is crucial. Various methods define CHDEs, using indices combining rainfall and temperature data. These indices, often analyzed using bivariate copula methods or time of emergence methods, allow for assessment of CHDE intensity and frequency in observations and climate model simulations. Previous studies have shown anthropogenic climate change significantly increases summer CHDE likelihood globally. However, the response of heatwaves and droughts to different forcings can vary, necessitating region-specific analysis. The 2022 summer witnessed record-breaking heatwaves and droughts across the Northern Hemisphere, including the YRV, resulting in severe consequences. The YRV experienced a particularly intense CHDE, lasting from early to late August, with record durations of heatwave and drought. This study investigates the anthropogenic influence on this 2022 YRV CHDE, focusing on the role of total anthropogenic forcing, greenhouse gases, and aerosols, and predicting future likelihood.

Numerous studies have explored compound heatwave and drought events (CHDEs), employing different methods to define and analyze them. Some studies utilized composite indices of rainfall and surface air temperature (SAT), others used composite anomalies of meteorological drought and SAT, and still others focused on the combined deficit of potential evapotranspiration and rainfall. Methods for analyzing CHDEs include the bivariate copula method, which allows for simultaneous consideration of heatwave and drought, and the time of emergence method. These approaches help estimate CHDE intensity and frequency, enabling detection and attribution analyses. Previous research using the bivariate copula method demonstrated that anthropogenic climate change significantly increased the likelihood of summer CHDEs across various continents. Other studies highlighted the substantial increase in CHDEs over global land areas due to anthropogenic forcing, with trends exceeding those under natural forcing. However, when attributing heatwaves and droughts separately, the probability of heatwave events often exceeded that of drought events under anthropogenic forcing, complicating the interpretation of CHDE probability changes.

This study used daily surface maximum temperature (Tmax) and rainfall datasets from the National Meteorological Information Center of China for 751 meteorological stations in the YRV from 1961 to 2022. CMIP6 simulations from nine climate models were used, including simulations with all external forcing (ALL), greenhouse gas forcing (GHG), anthropogenic aerosol forcing (AER), and natural forcing (NAT). Heatwave events were defined as daily Tmax exceeding the 90th percentile for at least five consecutive days during June-July-August, while drought events were defined as daily rainfall below the 10th percentile for at least five consecutive days (using a 5-day running mean for rainfall). The bivariate copula method, specifically the Gumbel copula (selected based on RMSE, AIC, and Dn comparisons), was used to construct the joint cumulative probability distribution of heatwave and drought, defining CHDE intensity using a probability-based index (PI). A lower PI indicates a more severe CHDE. The optimal fingerprinting method, based on the generalized extreme value (GEV) distribution, was employed to detect anthropogenic influence on the observed CHDEs. This involved comparing observed and simulated PI time series under different forcings, estimating scaling factors to quantify the effect of each forcing. A two-stage spatiotemporal block bootstrap procedure accounted for uncertainty. The probability ratio (PR) quantified the anthropogenic influence by comparing the probabilities of extreme events under different forcings. Finally, future changes in CHDE severity were projected using SSP2-4.5 simulations from the climate models.

The 2022 YRV CHDE was exceptionally severe, with the longest heatwave and drought durations since 1961. The PI for this event was 0.06, corresponding to a return period of approximately 662 years. Fingerprinting analysis revealed a significant anthropogenic influence on the observed PI time series, with scaling factors significantly greater than zero under ALL and GHG forcings. In contrast, scaling factors were not significantly different from zero under NAT and AER forcings, suggesting that greenhouse gas forcing was the primary driver. Quantifying the anthropogenic influence under the present climate (2000-2022), the probability of a CHDE as severe as the 2022 event was much higher under ALL and GHG forcings than under NAT forcing. The probability ratio (PR) between ALL and NAT forcings was approximately 9.92, and the PR for GHG forcing was 11.66, highlighting the dominant role of GHGs. Projections under SSP2-4.5 simulations showed a consistent decrease in PI from around 0.30 at the present climate to around 0.14 at a 3°C global warming level, indicating more extreme CHDEs in the future. This decrease in PI was primarily attributed to increases in heatwave intensity. The models showed less agreement on drought projections.

The findings strongly support the conclusion that anthropogenic climate change, primarily driven by greenhouse gas emissions, significantly increased the likelihood of the extreme 2022 YRV CHDE. The event's severity was exceptionally rare even in the current climate, becoming practically impossible in a pre-industrial climate. The dominant role of greenhouse gas forcing is further emphasized by the comparison of probability density functions under different forcings. Future projections indicate a worsening trend, with more frequent and intense CHDEs expected as global warming continues. The strong correlation between the PI and heatwave intensity points towards heatwaves as the primary driver of CHDE severity in both the 2022 event and future projections. While the models struggled to replicate observed drought trends, the consistent decrease in PI projects a future with more extreme CHDEs. This highlights the urgency of mitigation efforts to reduce greenhouse gas emissions and adapt to the changing climate.

This study demonstrates that anthropogenic climate change, especially greenhouse gas forcing, significantly increased the probability of the extreme 2022 YRV CHDE and projections indicate a future of even more extreme events. Heatwave intensity is the dominant factor driving CHDE severity. These findings underscore the need for adaptation strategies to mitigate the impacts of future CHDEs in the YRV and similar regions. Future research should focus on refining climate models, improving drought simulations, and investigating the specific mechanisms driving the observed increase in CHDEs.

The study's reliance on a limited number of CMIP6 models might affect the generalizability of the results. The models exhibited some biases in simulating the historical evolution of drought and heatwaves, particularly in the early decades. This necessitates caution in interpreting the projections for drought. The choice of a specific copula function and thresholds for defining heatwaves and droughts could potentially influence the results. Further research could investigate the sensitivity of results to these choices. Finally, uncertainties remain in the projections of future changes, especially concerning the precise magnitude of the increases in CHDE frequency and intensity.