Evolution, severity, and spatial extent of compound drought and heat events in north China based on copula model

Compound drought and heat (CDHE) is frequently occurred worldwide and leads to disproportionate impacts on agricultural production than univariate climate extremes, hence continues to receive research attention. However, the driving mechanism and occurrence characteristics of CDHEs remain unclear in some agro-ecological sensitive regions. Here, we adopted standardized precipitation index (SPI) and standardized temperature index (STI) to identify the intensity of drought and heat, respectively, in north China, and then to identify the month and area that most prone to CDHEs. Copulas can simulate the dependence between variables, hence were proposed to construct joint cumulative probability distributions of SPI and STI, so as to simulate the occurrence characteristic of CDHEs. The results demonstrated that in cold season, there were some stations with significant positive correlations between the SPI and STI. However, ∼ 80 % of stations had significant negative correlations between the two variables in July (the month of the year with the most stations). Hence, July is considered as the month most prone to CDHEs among the year in north China. We also found that the Symmetrized Joe-Clayton copula was the best to construct joint probability distributions of SPI and STI in most stations. In July, CDHEs occurred more frequently after 1990s with much higher intensity and wider spatial extent, which was mainly attributed to more severe heats. Spatially, mid-western plain and north mountainous areas were more prone to CDHEs. Our findings provide a better understanding of CDHEs in north China and could offer valuable references for meteorological disaster risk prevention in agriculture production.