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

A weighting scheme jointly considering model performance and independence (PI-based weighting scheme) is employed to deal with multi-model ensemble prediction of precipitation over China from 17 global climate models. Four precipitation metrics on mean and extremes are used to evaluate the model performance and independence. The PI-based scheme is also compared with a rank-based weighting scheme and 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 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 the total precipitation PRCPTOT (95th 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 central and east parts of western China.