Projected changes in temperature and precipitation in ten river basins over China in 21st century

ABSTRACT Present and future climate change information is required to develop adaptation and mitigation strategies at national and international levels. This study assessed the simulated surface air temperature ( SAT ) and precipitation ( PR ) over China from 24 models involved in the Coupled Model Intercomparison Project Phase 5 ( CMIP5 ). The reliability ensemble average ( REA ) is applied to project the SAT and PR change under representative concentration pathway ( RCP ) scenarios over China in the 21st century. The results show that most CMIP5 models tend to underestimate SAT and overestimate PR in China. Models generally agree better with the observed SAT than PR . For SAT , the ensemble prediction shows that warming is expected all over China for all RCPs . The warming trend from 2006 to 2099 in China is 0.87 ± 0.14 °C 100 year −1 , 2.47 ± 0.48 °C 100 year −1 , 5.85 ± 0.73 °C 100 year −1 for RCP 2.6, RCP 4.5 and RCP 8.5, respectively. Northern regions experience more warming than southern regions. The Songhua River basin warms the most, considering the ten studied basins for RCP 4.5 and RCP 8.5. Under RCP 2.6, the largest warming trend occurs in the Huaihe River basin. For PR , the spatial pattern of PR change has zonal characteristics. The girds with the maximum linear trend, i.e. >7.5 mm decade −1 , are concentrated in the upper Yangtze River basin. For temporal scale, PR in China is also projected to increase during the 21st century by 4.89 ± 2.30% 100 year −1 , 8.67 ± 6.27% 100 year −1 and 13.39 ± 12.58% 100 year −1 for RCP 2.6, RCP 4.5 and RCP 8.5, respectively. PR tends to decrease in the Yangtze River basin, Southeast River Drainage and Pearl River basin during the early period (2011–2030) for all RCPs , largely increase thereafter. However, uncertainties are unavoidable for SAT and PR projections. The PR uncertainty exceeds the temperature uncertainty. More studies regarding the analysis of narrowing uncertainties are essential for a better understanding of climate change.