Uncertainty in Projection of Climate Extremes: A Comparison of CMIP5 and CMIP6

被引:40
|
作者
Zhang, Shaobo [1 ,2 ]
Chen, Jie [1 ,2 ]
机构
[1] Wuhan Univ, State Key Lab Water Resources &Hydropower Engn Sc, 299 Bayi Rd, Wuhan 430072, Peoples R China
[2] Wuhan Univ, Hubei Prov Key Lab Water Syst Sci Sponge City Con, Wuhan 430072, Peoples R China
基金
中国国家自然科学基金;
关键词
climate projection uncertainty; uncertainty contribution; Coupled Model Intercomparison Project (CMIP) phase 5 (CMIP5) and phase 6 (CMIP6); extreme precipitation and temperature; GENERAL-CIRCULATION MODELS; SURFACE HYDROLOGY PARAMETERIZATION; PRECIPITATION EXTREMES; VARIABILITY; TEMPERATURE; COMPONENTS; TRANSFERABILITY; ENSEMBLES; FEEDBACK; AMERICA;
D O I
10.1007/s13351-021-1012-3
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Climate projections by global climate models (GCMs) are subject to considerable and multi-source uncertainties. This study aims to compare the uncertainty in projection of precipitation and temperature extremes between Coupled Model Intercomparison Project (CMIP) phase 5 (CMIP5) and phase 6 (CMIP6), using 24 GCMs forced by 3 emission scenarios in each phase of CMIP. In this study, the total uncertainty (T) of climate projections is decomposed into the greenhouse gas emission scenario uncertainty (S, mean inter-scenario variance of the signals over all the models), GCM uncertainty (M, mean inter-model variance of signals over all emission scenarios), and internal climate variability uncertainty (V, variance in noises over all models, emission scenarios, and projection lead times); namely, T = S + M + V. The results of analysis demonstrate that the magnitudes of S, M, and T present similarly increasing trends over the 21st century. The magnitudes of S, M, V, and T in CMIP6 are 0.94-0.96, 1.38-2.07, 1.04-1.69, and 1.20-1.93 times as high as those in CMIP5. Both CMIP5 and CMIP6 exhibit similar spatial variation patterns of uncertainties and similar ranks of contributions from different sources of uncertainties. The uncertainty for precipitation is lower in midlatitudes and parts of the equatorial region, but higher in low latitudes and the polar region. The uncertainty for temperature is higher over land areas than oceans, and higher in the Northern Hemisphere than the Southern Hemisphere. For precipitation, T is mainly determined by M and V in the early 21st century, by M and S at the end of the 21st century; and the turning point will appear in the 2070s. For temperature, T is dominated by M in the early 21st century, and by S at the end of the 21st century, with the turning point occuring in the 2060s. The relative contributions of S to T in CMIP6 (12.5%-14.3% for precipitation and 31.6%-36.2% for temperature) are lower than those in CMIP5 (15.1%-17.5% for precipitation and 38.6%-43.8% for temperature). By contrast, the relative contributions of M in CMIP6 (50.6%-59.8% for precipitation and 59.4%-60.3% for temperature) are higher than those in CMIP5 (47.5%-57.9% for precipitation and 51.7%-53.6% for temperature). The higher magnitude and relative contributions of M in CMIP6 indicate larger difference among projections of various GCMs. Therefore, more GCMs are needed to ensure the robustness of climate projections.
引用
收藏
页码:646 / 662
页数:17
相关论文
共 50 条
  • [41] Wind energy resource over Europe under CMIP6 future climate projections: What changes from CMIP5 to CMIP6
    Carvalho, D.
    Rocha, A.
    Costoya, X.
    DeCastro, M.
    Gomez-Gesteira, M.
    RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2021, 151
  • [42] Added value of CMIP6 models over CMIP5 models in simulating the climatological precipitation extremes in China
    Luo, Neng
    Guo, Yan
    Chou, Jieming
    Gao, Zhibo
    INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2022, 42 (02) : 1148 - 1164
  • [43] Simulations of ENSO Phase-Locking in CMIP5 and CMIP6
    Chen, Han-Ching
    Jin, Fei-Fei
    JOURNAL OF CLIMATE, 2021, 34 (12) : 5135 - 5149
  • [44] Cloud Climatologies from Global Climate Models-A Comparison of CMIP5 and CMIP6 Models with Satellite Data
    Lauer, Axel
    Bock, Lisa
    Hassler, Birgit
    Schroeder, Marc
    Stengel, Martin
    JOURNAL OF CLIMATE, 2023, 36 (02) : 281 - 311
  • [45] On the spring stratospheric final warming in CMIP5 and CMIP6 models
    Hu, Jinggao
    Liu, Zexuan
    Xu, Haiming
    Ren, Rongcai
    Jin, Dachao
    SCIENCE CHINA-EARTH SCIENCES, 2023, 66 (01) : 129 - 145
  • [46] On the spring stratospheric final warming in CMIP5 and CMIP6 models
    Jinggao HU
    Zexuan LIU
    Haiming XU
    Rongcai REN
    Dachao JIN
    Science China(Earth Sciences), 2023, 66 (01) : 129 - 145
  • [47] On the spring stratospheric final warming in CMIP5 and CMIP6 models
    Jinggao Hu
    Zexuan Liu
    Haiming Xu
    Rongcai Ren
    Dachao Jin
    Science China Earth Sciences, 2023, 66 : 129 - 145
  • [48] A comparison of CMIP6 and CMIP5 projections for precipitation to observational data: the case of Northeastern Iran
    Yasin Zamani
    Seyed Arman Hashemi Monfared
    Mehdi Azhdari moghaddam
    Mohsen Hamidianpour
    Theoretical and Applied Climatology, 2020, 142 : 1613 - 1623
  • [49] Comparison of CMIP6 and CMIP5 simulations of precipitation in China and the East Asian summer monsoon
    Xin, Xiaoge
    Wu, Tongwen
    Zhang, Jie
    Yao, Junchen
    Fang, Yongjie
    INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2020, 40 (15) : 6423 - 6440
  • [50] Evolution of Uncertainty in Terrestrial Carbon Storage in Earth System Models from CMIP5 to CMIP6
    Wei, Ning
    Xia, Jianyang
    Zhou, Jian
    Jiang, Lifen
    Cui, Erqian
    Ping, Jiaye
    Luo, Yiqi
    JOURNAL OF CLIMATE, 2022, 35 (17) : 5483 - 5499