Multi-Model Ensemble Projection of Precipitation Changes over China under Global Warming of 1.5 and 2°C with Consideration of Model Performance and Independence - CNRS - Centre national de la recherche scientifique Accéder directement au contenu
Article Dans Une Revue Journal of Meteorological Research Année : 2021

Multi-Model Ensemble Projection of Precipitation Changes over China under Global Warming of 1.5 and 2°C with Consideration of Model Performance and Independence

Résumé

A weighting scheme jointly considering model performance and independence (PI-based weighting scheme) is employed to deal with multi-model ensemble of precipitation over China from 17 global climate models. Four precipitation properties including mean and extremes are used to evaluate model performance and independence. The PI-based scheme is also compared to a Rank-based weighting scheme and to the simple arithmetic mean (AM) scheme. It is shown that the PI-based scheme achieves notable improvements in western China, with biases decreasing for all parameters. However, improvements are small and almost insignificant in eastern China. After calibration and validation, the scheme is used for future precipitation projection under the 1.5°C and 2°C global warming targets (above preindustrial level). There is a general tendency to wetness for most regions in China, especially in terms of extreme precipitation. The PI scheme shows larger inhomogeneity in spatial distribution. For total precipitation PRCPTOT (95 th percentile extreme precipitation R95P), the land fraction for a change larger than 10% (20%) is 22.8% (53.4%) in PI, while 13.3% (36.8%) in AM, under 2°C global warming. Most noticeable increase exists in the central and east part of western China.
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Dates et versions

hal-03195080 , version 1 (10-04-2021)

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Tong Li, Zhihong Jiang, Lilong Zhao, Laurent Li. Multi-Model Ensemble Projection of Precipitation Changes over China under Global Warming of 1.5 and 2°C with Consideration of Model Performance and Independence. Journal of Meteorological Research, 2021, 35 (1), pp.184-197. ⟨10.1007/s13351-021-0067-5⟩. ⟨hal-03195080⟩
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