High-Resolution Projections of Mean and Extreme Precipitation over China by Two Regional Climate Models

In this study, we employ two regional climate models(RCMs or RegCMs), which are RegCM4 and PRECIS(Providing Regional Climates for Impact Studies), with a horizontal grid spacing of 25 km, to simulate the precipitation dynamics across China for the baseline climate of 1981–2010 and two future climates of 2031–2060 and 2061–2090. The global climate model(GCM)—Hadley Centre Global Environment Model version 2-Earth Systems(HadGEM2-ES) is used to drive the two RCMs. The results of baseline simulations show that the two RCMs can correct the obvious underestimation of light rain below 5 mm day^-1 and the overestimation of precipitation above 5 mm day^-1 in Northwest China and the Qinghai–Tibetan Plateau, as being produced by the driving GCM. While PRECIS outperforms RegCM4 in simulating annual precipitation and wet days in several sub-regions of Northwest China, its underperformance shows up in eastern China. For extreme precipitation, the two RCMs provide a more accurate simulation of continuous wet days(CWD) with reduced biases and more realistic spatial patterns compared to their driving GCM. For other extreme precipitation indices, the RCM simulations show limited benefit except for an improved performance in some localized regions. The future projections of the two RCMs show an increase in the annual precipitation amount and the intensity of extreme precipitation events in most regions. Most areas of Southeast China will experience fewer number of wet days, especially in summer, but more precipitation per wet day(≥ 30 mm day^-1). By contrast, number of wet days will increase in the Qinghai–Tibetan Plateau and some areas of northern China. The increase in both the maximum precipitation for five consecutive days and the regional extreme precipitation will lead to a higher risk of increased flooding. The findings of this study can facilitate the efforts of climate service institutions and government agencies to improve climate services and to make climate-smart decisions.

Projected heat wave increasing trends over China based on combined dynamical and multiple statistical downscaling methods

Extensive investigations on the projection of heat waves(HWs)were conducted on the basis of coarse-resolution global climate models(GCMs).However,these investigations still fail to characterise the future changes in HWs regionally over China.PRECIS dynamical downscaling with a horizontal resolution of 25 km×25 km was employed on the basis of GCM-HadCM3 to provide reliable projections on HWs over the Chinese mainland,and six statistical downscaling methods were used for bias correction under RCP4.5 and RCP8.5 scenarios.The multi-method ensemble(MME)of the top three dynamical downscaling methods with good performance was used to project future changes.Results showed that PRECIS primarily replicated the detailed spatiotemporal pattern of HWs.However,PRECIS overestimated the HWs in the Northwest and Southeast and expanded the areas of HWs in the Northeast and Southwest.Three statistical downscaling methods(quantile mapping,CDF-t and quantile delta mapping)demonstrated good performance in improving PRECIS simulation for reproducing HWs.By contrast,parametric-based trend-preserving approaches such as scaled distribution mapping and ISI-MIP are outperformed by the three aforementioned methods in downscaling HWs,particularly in the high latitudes of China.Based on MME projections,at the end of the 21st century,the national average of the number of HW days each year,the length of the longest HW event in the year and the extreme maximum temperature in HW will increase by 3 times,1 time and 1.3℃,respectively,under the RCP4.5 scenario,whilst that under the RCP8.5 scenario will increase by 8 times,3 times and 3.7℃,respectively,relative to 1986-2005.The Northwest is regionally projected to suffer long and hot HWs,whilst the South and Southeast will experience frequent consecutive HWs.Thus,HWs projected by the combined dynamical and statistical downscaling method are highly reliable in projecting HWs over China.

Climatic warming in Shanghai during 1873-2019 based on homogenised temperature records

Xujahui(XJH)station in downtown Shanghai holds the longest continuous daily temperature series in China,which is unique for assessing modern climate change and impacts but must be homogenised.The present work established a set of homogenised monthly and daily surface air temperature(SAT)series during 1873-2019 at XJH.Two major inhomogeneous break points(around 1954 and 1993)were identified in the original SAT series,which had been overlooked in previous works.The inhomogeneous biases were adjusted via the inter-station deviation analysis.The adjusted SAT series shows a warming trend of 1.9℃ per century compared with 1.7℃ per century in the original series.The multi-decadal variations of quasi-32-year and quasi-64-year periods are weaker in the adjusted series than in the original series,suggesting overestimated multi-decadal variability in the original data due to inhomogeneous biases.Relative to the early period 1873-1900,the recent decade(the 2010s)is warmer by 2.2℃.Urbanisation has been responsible for approximately 19.3%of the rapid warming since the 1980s.The high and low SAT extremes exhibit significant warming,especially after the 1970s.The trend in the low SAT extremes in the adjusted series is substantially larger than that in the original series,implying that previous studies might underestimate the warming in cold extremes.