耦合模型比对项目
降水
环境科学
气候学
气候模式
代表性浓度途径
全球变暖
气候变化
洪水(心理学)
大洪水
气象学
地质学
地理
心理学
考古
心理治疗师
海洋学
作者
Yi Du,Dagang Wang,Jinxin Zhu,Dayang Wang,Xiaoxing Qi,Jingheng Cai
摘要
Abstract The warming climate can considerably alter the Earth's water cycle and change precipitation over land. Climate models are the primary tools for projecting precipitation changes and evaluating climate impacts in various fields. This study compares precipitation from 45 models in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and 49 models in Phase 6 (CMIP6) to observations. The results reveal that the CMIP6 models outperform the CMIP5 models in simulating precipitation patterns over the global land for the historical period. The cumulative distribution function matching method is used to correct the bias in the outputs of the selected CMIP5 and CMIP6 models, and the multi‐model ensemble (MME) of the corrected models is then utilized in projecting the precipitation changes under the future scenarios over the global land. The observation‐constrained projections show that there is a significant increasing trend in the annual global land precipitation during 2021–2100 under all four scenarios, and the rates are 3.0, 4.23, 6.77 and 8.96 mm/decade under the RCP4.5, SSP2‐4.5, RCP8.5 and SSP5‐8.5 scenarios, respectively. Moreover, the average annual global land precipitation is projected to increase by 4.9% (RCP4.5), 8.1% (RCP8.5), 4.6% (SSP2‐4.5) and 10.1% (SSP5‐8.5) by 2081–2100 relative to 1986–2005. Increases in global average precipitation may result in more flood, causing higher flooding risk in the future.
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