Projection of Spatiotemporal Changes in the Probability Distribution of Extreme Dry Periods in China under a 2°C Stable Warming Scenario

According to the Sixth Assessment Report of the IPCC, the global surface temperature has been higher in each of the last 4 decades compared to any previous decade since 1850. With the ongoing intensification of global warming, the intensity and frequency of extreme drought events have significantly increased. Based on the CN05.1 observational dataset and the results of five regional simulations from RegCM4.0 under future warming scenarios from the CORDEX (Regional Climate Downscaling Experiment), extreme dry periods are characterized by the number of consecutive dry days (CDD index). The Generalized Extreme Value (GEV) distribution is used to model the probability distribution of the CDD index in China to assess the spatiotemporal variations of extreme dry periods. By analyzing the spatiotemporal trends of the CDD index in China over the past 60 years and utilizing simulation techniques to assess the probability distribution characteristics of the CDD index, the study incorporates the Taylor diagram to evaluate the simulation performance of RegCM4.0. Finally, projections of the temporal and spatial distribution of the CDD index in China under a stable 2°C warming scenario, as well as changes in the ensemble mean of the five regional simulations relative to historical climate conditions, are presented.

The results indicate that the spatial distribution of the CDD index in China gradually decreases from northwest China and the Qinghai-Tibet Plateau to the eastern coastal areas. Over the past 60 years, the CDD index has decreased in northwest China and the Qinghai-Tibet Plateau, while it has increased in the eastern coastal regions, Northeast China, and North China, showing significant trends in these areas. The eastern coastal areas exhibit the lowest CDD index and minimal inter-annual variability, while northwest China and the Qinghai-Tibet Plateau show the highest CDD index values and the most significant inter-annual variability. According to the Taylor diagram, under the RCP4.5 emission scenario, the CDD index from simulations using the RegCM4.0 regional climate model, corrected by the Quantile Delta Mapping (QDM) method, shows better performance than uncorrected simulations. The corrected model results are strongly correlated with the CN05.1 observational dataset, with minimal error. Under a 2°C steady warming scenario, Generalized Extreme Value (GEV) analysis of the CDD index and return periods suggests that extreme dry periods will increase in northwest China, the Qinghai-Tibet Plateau, and Northeast China, with a growing disparity in extreme dry periods between the northern and southern regions as the return period increases. Multi-model ensemble projections for future periods under a 2°C stable warming scenario indicate a decreasing trend in the annual mean CDD index in northern China and an increasing trend in southern China.