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CWRF downscaling and understanding of China precipitation projections

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Abstract

The regional Climate-Weather Research and Forecasting model (CWRF) was used to downscale the NCAR Community Climate System Model V4.0 (CCSM4) projection of China precipitation changes from the present (1974–2005) to future (2019–2050) under the high emission scenario RCP8.5. The CWRF downscaling at 30-km improved CCSM4 in capturing observed key precipitation spatiotemporal characteristics, correcting rainband dislocations, seasonal-mean biases, extreme-rainfall underestimates and rainy-day overestimates. For the future, CWRF generally reduced CCSM4 projected changes in magnitude, producing still significant increases mostly in summer for mean precipitation in the Northeast, North China and Southwest and for extreme precipitation in North China, South China and the Southwest. These regional precipitation increases were direct responses to enhanced ascending motions and moisture transports from adjacent oceans as the east Asian jet shrunk westward and the Hadley circulation widened northward under global warming. The identification of such robust physical mechanisms added confidence in the CWRF downscaled regional precipitation changes. Furthermore, the CWRF downscaling corrections were systematically carried from the present into future, accounting for projection uncertainties up to 40%. Regional biases, however, could not be simply removed from projected changes because their correspondences were strongly nonlinear, highlighting CWRF’s ability to project more reliable changes by reducing model structural uncertainties.

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adopted from Liang et al. (2019)

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Acknowledgements

The research was supported by the U.S. National Science Foundation Innovations at the Nexus of Food, Energy and Water Systems under Grant EAR1903249 and the China Meteorological Administration/National Climate Center research subcontract 2211011816501. The simulations and analyses were conducted on supercomputers, including the Maryland Advanced Research Computing Center's Bluecrab and the Computational and Information Systems Lab of the National Center for Atmospheric Research.

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Correspondence to Xin-Zhong Liang.

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Jiang, R., Sun, L., Sun, C. et al. CWRF downscaling and understanding of China precipitation projections. Clim Dyn 57, 1079–1096 (2021). https://doi.org/10.1007/s00382-021-05759-z

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  • DOI: https://doi.org/10.1007/s00382-021-05759-z

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