Assessment of GCMs simulation performance for precipitation and temperature from CMIP5 to CMIP6 over the Tibetan Plateau

被引:119
|
作者
Lun, Yurui [1 ]
Liu, Liu [1 ,2 ]
Cheng, Lei [3 ,4 ,5 ]
Li, Xiuping [6 ]
Li, Hao [7 ]
Xu, Zongxue [8 ,9 ]
机构
[1] China Agr Univ, Coll Water Resources & Civil Engn, 17 Tsinghua East Rd, Beijing, Peoples R China
[2] China Agr Univ, Ctr Agr Water Res China, Beijing, Peoples R China
[3] Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan, Peoples R China
[4] Hubei Prov Collaborat Innovat Ctr Water Resources, Wuhan, Peoples R China
[5] Wuhan Univ, Hubei Prov Key Lab Water Syst Sci Sponge City Con, Wuhan, Peoples R China
[6] Chinese Acad China, Inst Tibetan Plateau Res, Beijing, Peoples R China
[7] Univ Ghent, Lab Hydrol & Water Management, Ghent, Belgium
[8] Beijing Normal Univ, Coll Water Sci, Beijing, Peoples R China
[9] Beijing Key Lab Urban Hydrol Cycle & Sponge City, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
climate change; Coupled Model Intercomparison Project; elevation dependency; ensemble; Tibetan Plateau; uncertainty; GLOBAL CLIMATE MODELS; INTERANNUAL VARIABILITY; INDIAN SUBCONTINENT; RAINFALL; EXTREMES; CHINA; PROJECTIONS; IMPACTS;
D O I
10.1002/joc.7055
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
General circulation models (GCMs) are indispensable for climate change adaptive study over the Tibetan Plateau (TP), which is the potential trigger and amplifier in global climate fluctuations. With the release of Coupled Model Intercomparison Project Phase 6 (CMIP6), 24 GCMs from CMIP5 and CMIP6 were comparatively evaluated for precipitation and air temperature simulations based on the China Meteorological Forcing Dataset (CMFD). Rank score results showed that CMIP6 models generally performed better than CMIP5 for precipitation and surface air temperature over the TP. According to multimodel ensembles (MMEs) of the optimal GCMs for each climate variable, the overestimation of precipitation was both present in CMIP5 and CMIP6, but the results of CMIP6 MMEs were relatively lower in the mid-west and northern edge of the TP. Furthermore, CMIP6 offered a better performance of precipitation in summer and autumn. For temperature, CMIP6 MMEs were able to reduce the relatively large cold bias that appeared in CMIP5 MMEs in northwest areas to about 1 degrees C and had a smaller bias in spring and winter. Moreover, the investigation into the simulation effects of precipitation at different elevation zones demonstrated that the improved ability of CMIP6 MMEs to reduce bias was mainly concentrated in the elevation zones of 2,000-3,000 m and over 5,000 m, where the precipitation bias was more than 200%. Additionally, CMIP6 MMEs of temperature were able to reduce the bias to less than 2 degrees C in each elevation zone, with the minimum bias of -0.22 degrees C distributed in the region with altitudes from 3,000 to 4,000 m, while the biases of CMIP5 MMEs in the region of 4,000-5,000 m and over 5,000 m were smaller than those of CMIP6 MMEs. Findings obtained in this study could provide a scientific reference for related climate change research over the TP. GCMs of CMIP6 perform better than those of CMIP5 for precipitation and temperature over the TP. Multimodel ensembles (MMEs) of CMIP6 effectively reduce the overestimation of precipitation from CMIP5 MMEs by 40 mm at the annual scale. Improved ability of CMIP6 MMEs shows a significant elevation dependency, especially in elevation zones of 2,000-3,000 m and over 5,000 m for precipitation.
引用
收藏
页码:3994 / 4018
页数:25
相关论文
共 50 条
  • [1] Evaluation of CMIP6 for historical temperature and precipitation over the Tibetan Plateau and its comparison with CMIP5
    Zhu Yu-Yao
    Yang Saini
    ADVANCES IN CLIMATE CHANGE RESEARCH, 2020, 11 (03) : 239 - 251
  • [2] Replicability of Annual and Seasonal Precipitation by CMIP5 and CMIP6 GCMs over East Asia
    Shiru, Mohammed Sanusi
    Shahid, Shamsuddin
    Chae, Seung-Taek
    Chung, Eun-Sung
    KSCE JOURNAL OF CIVIL ENGINEERING, 2022, 26 (04) : 1978 - 1989
  • [3] An assessment of temperature simulations by CMIP6 climate models over the Tibetan Plateau and differences with CMIP5 climate models
    Qin Hu
    Wei Hua
    Kaiqing Yang
    Jing Ming
    Pan Ma
    Yong Zhao
    Guangzhou Fan
    Theoretical and Applied Climatology, 2022, 148 : 223 - 236
  • [4] An assessment of temperature simulations by CMIP6 climate models over the Tibetan Plateau and differences with CMIP5 climate models
    Hu, Qin
    Hua, Wei
    Yang, Kaiqing
    Ming, Jing
    Ma, Pan
    Zhao, Yong
    Fan, Guangzhou
    THEORETICAL AND APPLIED CLIMATOLOGY, 2022, 148 (1-2) : 223 - 236
  • [5] Replicability of Annual and Seasonal Precipitation by CMIP5 and CMIP6 GCMs over East Asia
    Mohammed Sanusi Shiru
    Shamsuddin Shahid
    Seung-Taek Chae
    Eun-Sung Chung
    KSCE Journal of Civil Engineering, 2022, 26 : 1978 - 1989
  • [6] Blocking Simulations in GFDL GCMs for CMIP5 and CMIP6
    Liu, Ping
    Reed, Kevin A.
    Garner, Stephen T.
    Zhao, Ming
    Zhu, Yuejian
    JOURNAL OF CLIMATE, 2022, 35 (15) : 5053 - 5070
  • [7] Evaluation and projections of surface air temperature over the Tibetan Plateau from CMIP6 and CMIP5: warming trend and uncertainty
    Minpei Zhou
    Zhongbo Yu
    Huanghe Gu
    Qin Ju
    Yiyan Gao
    Lei Wen
    Tangkai Huang
    Wei Wang
    Climate Dynamics, 2023, 60 : 3863 - 3883
  • [8] Evaluation and projections of surface air temperature over the Tibetan Plateau from CMIP6 and CMIP5: warming trend and uncertainty
    Zhou, Minpei
    Yu, Zhongbo
    Gu, Huanghe
    Ju, Qin
    Gao, Yiyan
    Wen, Lei
    Huang, Tangkai
    Wang, Wei
    CLIMATE DYNAMICS, 2023, 60 (11-12) : 3863 - 3883
  • [9] Assessment of CMIP5 GCM Simulation Performance for Temperature Projection in the Tibetan Plateau
    Jia, Kun
    Ruan, Yunfeng
    Yang, Yanzhao
    You, Zhen
    EARTH AND SPACE SCIENCE, 2019, 6 (12) : 2362 - 2378
  • [10] Evaluation and projection of the summer precipitation recycling over the Tibetan plateau based on CMIP6 GCMs
    Xu, Ying
    Han, Zhenyu
    Liu, Yanju
    Wu, Jie
    INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2024, 44 (08) : 2666 - 2680