The increasing frequency of extreme climate events (ECEs) is expected to significantly affect crop yields in the future, threatening regional and global food security. However, uncertainties in yield projections persist due to regional variability, model differences, and scenario assumptions. Leveraging historical agricultural disaster and meteorological data from China (1995–2014), this study employs the vulnerability curve assessment to determine the most appropriate models for assessing crop yields affected by different ECEs (drought, extreme precipitation, extreme low temperature, and extreme wind) across six regions. By integrating multi-model and multi-scenario (SSP1-2.6, SSP3-7.0, SSP5-8.5) future climate data from Coupled Model Intercomparison Project Phase 6 (CMIP6), we conducted pooled prediction of the individual and combined impacts of different ECEs on crop yields for the near-term (2020–2040) and mid-term (2041–2060). The median of multi-model prediction of crop yield reductions in China was −16.0% (range: −32.5% to −2.6%), with more severe losses in Northeast, Northwest, and North China, particularly under higher radiative forcing scenarios. Drought is the most destructive of the four types of ECEs. These results will aid decision-makers in identifying high-risk zones for crop yields affected by ECEs and provide a scientific basis for the developing targeted adaptation strategies in various regions.
Liu et al. (Tue,) studied this question.