Multiple Metrics Informed Projections of Future Precipitation in China. Issue 18 (16th September 2021)

• Record Type: Journal Article
• Authors: Wang, Lei; Qian, Yun; Leung, L. Ruby; Chen, Xiaodong; Sarangi, Chandan; Lu, Jian; Song, Fengfei; Gao, Yang; Lin, Guangxing; Zhang, Yaocun
• Is Part Of: Geophysical research letters. Volume 48:Issue 18(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-09-16
• Subjects: climate models -- climate projection -- model evaluation -- precipitation; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2021GL093810
• Languages: English
• ISSNs: 0094-8276

Abstract

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. Plain Language Summary: Precipitation is a fundamental driver of land surface hydrology and water resources, but large biases in climate model simulations of precipitation and large uncertainties in the future projections hinder the use of climate models in climate impact studies. Metrics of precipitation used in climate model evaluation usually focus on different precipitation characteristics, while ignoring important physical mechanisms linking precipitation with its environments. In this study, a two‐dimensional metric is proposed to evaluate both the simulated precipitation and its relationship with large‐scale circulation patterns in East Asia. This metric is applied to the Coupled Model Intercomparison Project Phase 5 (CMIP5) models to classify 31 models into three groups based on model performances. The metric is able to discriminate model responses: models in the top performing group show more consistent and similar responses of precipitation to future warming, featuring larger increases of future precipitation than the CMIP5 ensemble mean over China. Key Points: A two‐dimensional metric is developed to evaluate precipitation and its relationships with the large‐scale circulation in climate models The new metric identifies a subset of models skillful in simulating both precipitation and its relationship with the monsoon circulation This subset of models projects a more robust and larger increase of future precipitation than the multimodel ensemble mean over China