Projecting the spatio-temporal variations of drought event frequency in the Chinese mainland based on CMIP6 models dataset and intensity–area–duration algorithm

In this study, five CMIP6 models data for the medium-emission SSP2-4.5 and high-emission SSP5-8.5 scenarios, corresponding to sustained conditions of 1.5°C and 2.0°C temperature rises under the global warming were selected. Following resampling of the selected climate model datasets (1°×1° monthly temperature and precipitation), an ensemble mean approach was employed to generate a Standardized Precipitation-Evapotranspiration Index (SPEI) dataset, which was then calibrated using quantile mapping with CN05.1 meteorological station observations. Drought events were identified via the Intensity-Area-Duration (IAD) algorithm, enabling spatiotemporal evolution analysis of future drought frequency over mainland China. It was found that under the SSP2-4.5 scenario model, compared with a 1.5°C temperature rise, the frequency of droughts at a 2°C temperature rise showed a continuous upward tendency in northern and Southwestern QTP, southern XJ. As well as a decreasing tendency in the southern SC, northeastern SW, and western NC. Under the SSP5-8.5 scenario model, compared with a 1.5°C temperature rise, the frequency of drought events at a 2°C shows an increasing trend in southern XJ and western NW, but less than the increase in drought frequency for the SSP2-4.5 scenario model, whereas it shown a weaken tendency in SC, which is less than the weaken of frequency for the SSP2-4.5 scenario model. In summary, the frequency of drought events has a tendency to shift to the northwest mainland China as the temperature continues to warm up in both the medium and high emission scenario models.