Extreme climate events and agricultural climate indices in China: CMIP5 model evaluation and projections

被引:61
|
作者
Sun, Qiaohong [1 ,2 ]
Miao, Chiyuan [1 ,2 ]
Duan, Qingyun [1 ,2 ]
机构
[1] Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Coll Global Change & Earth Syst Sci, Beijing 100875, Peoples R China
[2] Joint Ctr Global Change Studies, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
extreme climate; agricultural climate index; CMIP5; China; ACCUMULATED TEMPERATURE; SUMMER PRECIPITATION; FOOD SECURITY; SEDIMENT LOAD; SIMULATION; MOISTURE; IMPACTS; TRENDS; RANGE;
D O I
10.1002/joc.4328
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
This study evaluates the 14 global climate models in the Coupled Model Intercomparison Project Phase 5 in capturing the extreme climate events and the agricultural climate indices over China. Future climate event changes in different Representative Concentration Pathway scenarios in China are projected using the Reliability Ensemble Average method. The models can simulate the basic spatial distribution characteristics of indices and simulate temperature indices better than precipitation indices. The models overestimate the number of wet days over China, which is related to the tendency that rainfall is simulated too often and too lightly in models. The underestimation of the number of very heavy precipitation events is detected in most models, while overestimation occurred in northern China and the Qinghai-Tibet Plateau region. Some factors, such as the complex topography, the moist convection schemes in models, and the ability to simulate large-scale circulation, may result in the performances for precipitation. Higher active accumulated temperature and more summer days are projected, while the accumulated negative temperature and frost days are projected to decrease with the warming climate. Northern China would become wetter when the number of wet days (R1mm) increases. Extreme wet events are projected to be more probable in South and Central China and the Southwest Region, with increases in very heavy precipitation days (R20mm) in all scenarios. These changes in extreme climate events and agricultural climate indices would inevitably affect agriculture in China.
引用
收藏
页码:43 / 61
页数:19
相关论文
共 50 条
  • [21] Arctic sea ice in CMIP5 climate model projections and their seasonal variability
    HUANG Fei
    ZHOU Xiao
    WANG Hong
    Acta Oceanologica Sinica, 2017, 36 (08) : 1 - 8
  • [22] Arctic sea ice in CMIP5 climate model projections and their seasonal variability
    Fei Huang
    Xiao Zhou
    Hong Wang
    Acta Oceanologica Sinica, 2017, 36 : 1 - 8
  • [23] Arctic sea ice in CMIP5 climate model projections and their seasonal variability
    Huang Fei
    Zhou Xiao
    Wang Hong
    ACTA OCEANOLOGICA SINICA, 2017, 36 (08) : 1 - 8
  • [24] Climate hazard indices projections based on CORDEX-CORE, CMIP5 and CMIP6 ensemble
    Coppola, Erika
    Raffaele, Francesca
    Giorgi, Filippo
    Giuliani, Graziano
    Xuejie, Gao
    Ciarlo, James M.
    Sines, Taleena Rae
    Torres-Alavez, Jose Abraham
    Das, Sushant
    di Sante, Fabio
    Pichelli, Emanuela
    Glazer, Russell
    Mueller, Sebastian Karl
    Abba Omar, Sabina
    Ashfaq, Moetasim
    Bukovsky, Melissa
    Im, E. -S.
    Jacob, Daniela
    Teichmann, Claas
    Remedio, Armelle
    Remke, Thomas
    Kriegsmann, Arne
    Bulow, Katharina
    Weber, Torsten
    Buntemeyer, Lars
    Sieck, Kevin
    Rechid, Diana
    CLIMATE DYNAMICS, 2021, 57 (5-6) : 1293 - 1383
  • [25] Indices for extreme events in projections of anthropogenic climate change
    J. Sillmann
    E. Roeckner
    Climatic Change, 2008, 86 : 83 - 104
  • [26] Indices for extreme events in projections of anthropogenic climate change
    Sillmann, J.
    Roeckner, E.
    CLIMATIC CHANGE, 2008, 86 (1-2) : 83 - 104
  • [27] Regional response of runoff in CMIP5 multi-model climate projections of Jiangsu Province, China
    Wu, Zhiyong
    Chen, Xia
    Lu, Guihua
    Xiao, Heng
    He, Hai
    Zhang, Jianhua
    STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2017, 31 (10) : 2627 - 2643
  • [28] Regional response of runoff in CMIP5 multi-model climate projections of Jiangsu Province, China
    Zhiyong Wu
    Xia Chen
    Guihua Lu
    Heng Xiao
    Hai He
    Jianhua Zhang
    Stochastic Environmental Research and Risk Assessment, 2017, 31 : 2627 - 2643
  • [29] Projections of Greenland climate change from CMIP5 and CMIP6
    Zhang, Qinglin
    Huai, Baojuan
    Ding, Minghu
    Sun, Weijun
    Liu, Weigang
    Yan, Jinpei
    Zhao, Shuhui
    Wang, Yetang
    Wang, Yuzhe
    Wang, Lei
    Che, Jiahang
    Dou, Jiahui
    Kang, Limin
    GLOBAL AND PLANETARY CHANGE, 2024, 232
  • [30] The Mediterranean climate change hotspot in the CMIP5 and CMIP6 projections
    Cos, Josep
    Doblas-Reyes, Francisco
    Jury, Martin
    Marcos, Raul
    Bretonniere, Pierre-Antoine
    Samso, Margarida
    EARTH SYSTEM DYNAMICS, 2022, 13 (01) : 321 - 340