Dai Panxi, Nie Ji, Yu Yan, Wu Renguang
Department of Atmospheric Sciences, School of Earth Sciences, Zhejiang University, Hangzhou 310058, China.
Department of Atmospheric and Oceanic Sciences, Laboratory for Climate and Ocean-Atmosphere Studies, School of Physics, Peking University, Beijing 100871, China.
Proc Natl Acad Sci U S A. 2024 Mar 12;121(11):e2312400121. doi: 10.1073/pnas.2312400121. Epub 2024 Mar 4.
The projected changes in the hydrological cycle under global warming remain highly uncertain across current climate models. Here, we demonstrate that the observational past warming trend can be utilized to effectively co1nstrain future projections in mean and extreme precipitation on both global and regional scales. The physical basis for such constraints relies on the relatively constant climate sensitivity in individual models and the reasonable consistency of regional hydrological sensitivity among the models, which is dominated and regulated by the increases in atmospheric moisture. For the high-emission scenario, on the global average, the projected changes in mean precipitation are lowered from 6.9 to 5.2% and those in extreme precipitation from 24.5 to 18.1%, with the inter-model variances reduced by 31.0 and 22.7%, respectively. Moreover, the constraint can be applied to regions in middle-to-high latitudes, particularly over land. These constraints result in spatially resolved corrections that deviate substantially and inhomogeneously from the global mean corrections. This study provides regionally constrained hydrological responses over the globe, with direct implications for climate adaptation in specific areas.
在当前的气候模型中，全球变暖下水文循环的预测变化仍然极不确定。在此，我们证明过去观测到的变暖趋势可用于有效约束全球和区域尺度上平均降水量和极端降水量的未来预测。这种约束的物理基础依赖于各模型中相对恒定的气候敏感性以及各模型间区域水文敏感性的合理一致性，而这种一致性主要由大气湿度增加主导和调节。对于高排放情景，在全球平均水平上，预测的平均降水量变化从6.9%降至5.2%，极端降水量变化从24.5%降至18.1%，模型间方差分别减少31.0%和22.7%。此外，这种约束可应用于中高纬度地区，特别是陆地地区。这些约束导致空间分辨率的校正，与全球平均校正存在显著且不均匀的偏差。本研究提供了全球范围内区域约束的水文响应，对特定地区的气候适应具有直接影响。
