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Stephanie Fiedler, Traute Crueger, Roberta D’Agostino, Karsten Peters, Tobias Becker, David Leutwyler, Laura Paccini, Jörg Burdanowitz, Stefan A. Buehler, Alejandro Uribe Cortes, Thibaut Dauhut, Dietmar Dommenget, Klaus Fraedrich, Leonore Jungandreas, Nicola Maher, Ann Kristin Naumann, Maria Rugenstein, Mirjana Sakradzija, Hauke Schmidt, Frank Sielmann, Claudia Stephan, Claudia Timmreck, Xiuhua Zhu, and Bjorn Stevens

Abstract

The representation of tropical precipitation is evaluated across three generations of models participating in phases 3, 5, and 6 of the Coupled Model Intercomparison Project (CMIP). Compared to state-of-the-art observations, improvements in tropical precipitation in the CMIP6 models are identified for some metrics, but we find no general improvement in tropical precipitation on different temporal and spatial scales. Our results indicate overall little changes across the CMIP phases for the summer monsoons, the double-ITCZ bias, and the diurnal cycle of tropical precipitation. We find a reduced amount of drizzle events in CMIP6, but tropical precipitation occurs still too frequently. Continuous improvements across the CMIP phases are identified for the number of consecutive dry days, for the representation of modes of variability, namely, the Madden–Julian oscillation and El Niño–Southern Oscillation, and for the trends in dry months in the twentieth century. The observed positive trend in extreme wet months is, however, not captured by any of the CMIP phases, which simulate negative trends for extremely wet months in the twentieth century. The regional biases are larger than a climate change signal one hopes to use the models to identify. Given the pace of climate change as compared to the pace of model improvements to simulate tropical precipitation, we question the past strategy of the development of the present class of global climate models as the mainstay of the scientific response to climate change. We suggest the exploration of alternative approaches such as high-resolution storm-resolving models that can offer better prospects to inform us about how tropical precipitation might change with anthropogenic warming.

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