Future projections of precipitation, surface temperatures and drought events over the monsoon transitional zone in China from bias‐corrected <scp>CMIP6</scp> models
Jinling Piao, Wen Chen, Lin Wang, Shangfeng Chen
Abstract
Abstract Bias‐corrected monthly precipitation and surface temperature datasets are constructed for the monsoon transitional zone (MTZ) in China during 1965–2100 based on 21 coupled climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) using the equi‐ratio and equidistant cumulative distribution function quantile‐based mapping methods (equi‐ratio cumulative distribution function [ERCDF] and equidistant cumulative distribution function [EDCDF]), respectively. The efficiencies of the two methods are verified via cross‐validation by the jack‐knife method, and the biases are remarkably reduced compared to those of the raw model outputs. Then, the bias‐corrected model outputs are applied to future projections of precipitation, surface temperatures and drought events under the medium (SSP2‐4.5) and high (SSP5‐8.5) shared socioeconomic pathway scenarios. The obtained results present pronounced increases in both the projected annual mean precipitation and temperature fields for the model ensemble mean. In accompany, the MTZ is predicted to become drier in the three future periods; this result was attributed to the dramatic increases in semiarid events and to the decreases in humid events. The drought tension showed more rapid development under SSP585 than under the other scenario, with comparable occurrence frequencies of relatively wet and dry events in the long‐term period, posing a serious threat to regional sustainable development.