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Multiple Metrics Informed Projections of Future Precipitation in China
Author(s) -
Wang Lei,
Qian Yun,
Leung L. Ruby,
Chen Xiaodong,
Sarangi Chandan,
Lu Jian,
Song Fengfei,
Gao Yang,
Lin Guangxing,
Zhang Yaocun
Publication year - 2021
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2021gl093810
Subject(s) - precipitation , coupled model intercomparison project , environmental science , climatology , metric (unit) , climate change , scale (ratio) , climate model , general circulation model , china , meteorology , geography , geology , oceanography , operations management , cartography , archaeology , economics
Abstract Predicting how regional precipitation will respond to future warming is among the most challenging undertaking in climate change projection. Despite sustained efforts to improve modeling and understanding of precipitation, the overall uncertainty in projecting regional precipitation has not been reduced substantially. Here, the potential for more robust precipitation projections is demonstrated through the use of discriminating metrics to subsample a multimodel ensemble. Using a two‐dimensional metric of precipitation and its relationship with large‐scale circulation indices in East Asia, 31 models in the Coupled Model Intercomparison Project Phase 5 (CMIP5) are classified into three groups. Models in the top performing group projected statistically significant increasing trends in precipitation and the regional precipitation patterns are more similar to each other than to the patterns in the bottom performing group. In contrast, models in the bottom performing group projected diverse responses, with overall small drying or no significant trends in precipitation.