Prediction of Clausius–Clapeyron Scaling of Daily Precipitation Extremes over China

Abstract

Abstract Observations and model simulations have confirmed that the higher percentiles of precipitation intensity of all wet days have increased with the local daily dewpoint temperature at the Clausius–Clapeyron (C-C) rate of 7% °C−1 using the binning technique over China. It is uncertain whether the binning scaling rates will remain constant in the future climate. Here, we use daily precipitation and dewpoint temperature (DPT) over China from 20 CMIP6 models to examine and project the change of binning scaling of precipitation extremes. The results of the study suggest that the multimodel ensemble median (MEM) generally captures the spatial distribution of binning scaling rates and binning curves in different climate zones across China. The binning scaling rates have stability in the future but with a large increasing trend (more than 30%) in southeast China in the far future (2061–2100) under the SSP5-8.5 scenario. CMIP6 models project that both the peak of extreme precipitation and the temperature for the plateau mountain zone will increase in the far future under the SSP5-8.5 scenario, implying that the peak structure does not provide an upper limit for future precipitation extremes. Significance Statement The binning scaling rates describe the relationship between precipitation extremes and temperature based on their day-to-day variations. However, it is still unclear whether the binning scaling rates of daily precipitation extremes with daily temperature will change in the future. We use 20 CMIP6 models to project the scaling rates of precipitation extremes with dewpoint temperature over China in the future. The results show that the sensitivity of precipitation extremes to dewpoint temperature will generally be stable, except that southeast China shows an increasing trend of up to 30%. Moreover, the peak of extreme precipitation and the temperature will increase with warming in the plateau mountain zone. Our results have implications for precipitation prediction and risk assessment.