气象学报（英文版）

Zhiyu JIANG1; Zhan TIAN8; Guangtao DONG3; Laixiang SUN4; Peiqun ZHANG9; Erasmo BUONOMO10; Dongli FAN11

2020

Journal of Meteorological Research   影响因子和分区

2095-6037

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 precipita-tion 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 cor-rect 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 sim-ulation of continuous wet days (CWD) with reduced biases and more realistic spatial patterns compared to their driv-ing 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 pre-cipitation 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 precipita-tion will lead to a higher risk of increased flooding. The findings of this study can facilitate the efforts of climate ser-vice institutions and government agencies to improve climate services and to make climate-smart decisions.

climate change extreme precipitation dynamical downscaling regional climate models (RCMs) Co-ordinated Regional Downscaling Experiment (CORDEX)

英语

第一

(Supported by the National Key Research and Development Program of China)%(National Natural Science Founda-tion of China)%(UK–China Research and Innovation Partnership Fund through the Met Office Climate Sci-ence for Service Partnership)%(and Social Development Project of Science and Tech-nology Commission of Shanghai Municipality)

GEOSCIENCES

WanFang

perioarticalqxxb-e202005006

1.Shanghai Institute of Technology, Shanghai 201400, China;Shanghai Climate Center, Shanghai Meteorological Service, Shanghai 200030, China;School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
2.School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
3.Shanghai Climate Center, Shanghai Meteorological Service, Shanghai 200030, China;Key Laboratory of Cities' Mitigation and Adaptation to Climate Change in Shanghai, China Meteorological Administration, Shanghai 200030, China
4.Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA;School of Finance and Management, School of Oriental and African Studies of University of London, London WC1H 0XG, UK
5.Beijing Climate Center/National Climate Center, China Meteorological Administration, Beijing 100081, China
6.Met Office Hadley Centre, Exeter EX13PB, UK
7.Shanghai Institute of Technology, Shanghai 201400, China
8.南方科技大学
9.北京市气候中心
10.3pb市哈德利中心气象局
11.上海理工大学

Zhiyu JIANG,Zhan TIAN,Guangtao DONG,等. 气象学报（英文版）[J]. Journal of Meteorological Research,2020,34(5):965-985.

Zhiyu JIANG.,Zhan TIAN.,Guangtao DONG.,Laixiang SUN.,Peiqun ZHANG.,...&Dongli FAN.(2020).气象学报（英文版）.Journal of Meteorological Research,34(5),965-985.

Zhiyu JIANG,et al."气象学报（英文版）".Journal of Meteorological Research 34.5(2020):965-985.