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SCIENTIA SINICA Terrae, Volume 46, Issue 12: 1675-1688(2016) https://doi.org/10.1360/N072015-00465

CMIP5气候模式模拟的1850~2014年全球温度变化的集合经验模态分解

魏萌①,②,③, 乔方利①,②,③,*
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  • ReceivedMay 12, 2016
  • AcceptedAug 10, 2016
  • PublishedOct 25, 2016

Abstract

第五次耦合模式比较计划(CMIP5)集合了全球众多高水平气候模式, 代表了目前气候模拟和预测的最高水平, 然而这些模式均未能正确模拟出近期的全球增暖减缓现象, 所模拟的温度严重偏高. 基于HadCRUT4观测资料和CMIP5气候模式数据, 使用集合经验模态分解(EEMD)方法, 分析了1850~2014年全球温度的低频演变特征, 评价了33个模式对其模拟结果, 并探讨了模式对近年来全球增暖减缓模拟失败的原因. 结果显示, 受长期增暖趋势和多年代际振荡的主导, 1850~2014年全球平均表面温度(GMST)的长期变化呈现出冷暖相间、波动增暖的特点. 长期增暖趋势自20世纪以来一直较为稳定, 近50年的平均增暖速度为0.0883℃/decade; 多年代际振荡的平均周期为65年, 在1850~2014年出现了2.5个波动, 随时间推移, 波动有加深变陡的趋势. 20世纪后期的增暖加速现象是稳定的长期增暖趋势与多年代际振荡的暖位相相叠加的结果, 二者各贡献了1975~1998年全球温度增加的1/3. 近期多年代际振荡逐渐接近第3个波的峰值, 增暖速度迅速减慢, 受其影响全球温度的增暖步调也明显放缓, 出现增暖减缓现象. 在1850~2005年的历史试验期间, CMIP5气候模式对GMST的模拟结果与HadCRUT4观测较为接近, 对20世纪后期的全球增暖加速现象模拟的尤为出色. 但在RCP4.5情景下对2006~2014年的温度均值和线性趋势的预估严重偏高. 这是由于CMIP5模式未能正确区分全球温度演变过程中的长期趋势和多年代际变化, 所模拟的长期趋势偏高、偏快, 多年代际信号位相混乱且振幅偏小. 这说明大气CO2对气候的增暖效应可能被高估, 而气候系统的年代际自然变化则被低估, 这些偏差与目前对气候系统关键动力过程的认识不足密切相关. 这一发现将为新一代长期气候变化预测模式的发展提出新的检验标准: 气候模式应该有能力模拟全球温度变化的长期增暖趋势和周期约为65年的多年代际振荡.


Funded by

国家自然科学基金委员会-山东省人民政府联合海洋科学研究中心项目(U1406404)


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  • 图 1

    观测和模拟的年平均GMSTA时间序列()

  • 图 2

    CMIP5气候模式历史实验对1850~2005GMSTA的模拟效果

  • 图 3

    CMIP5模式在RCP4.5情景下对2006~2014GMSTA的预估效果

  • 图 4

    观测和模拟的年平均GMSTA序列的EEMD分解结果和显著性检验.

  • 图 5

    HadCRUT4观测序列的多年代际振荡项(MDV)、趋势项多年代际振荡与趋势项的叠加序列以及原始GMSTA序列

  • 图 6

    观测和模拟的长期趋势及多年代际振荡序列

  • 图 7

    HadCRUT4观测和CMIP5 MMM模拟的趋势项趋势项与多年代际振荡的叠加序列及原始GMSTA序列

  • 表 1   个气候模式的基本信息

    模式序号

    模式名称

    水平网格数

    研发机构和国家

    01

    ACCESS1-0

    145×192

    CSIRO, BOM, 澳大利亚

    02

    ACCESS1-3

    145×192

    CSIRO, BOM, 澳大利亚

    03

    BCC-CSM1-1-m

    160×320

    BCC, 中国

    04

    BCC-CSM1-1

    64×128

    BCC, 中国

    05

    BNU-ESM

    64×128

    BNU, 中国

    06

    CanESM2

    64×128

    CCCMA, 加拿大

    07

    CCSM4

    192×288

    NCAR, 美国

    08

    CESM1-BGC

    192×288

    NSF, DOE, NCAR, 美国

    09

    CESM1-CAM5

    192×288

    NSF, DOE, NCAR, 美国

    10

    CMCC-CM

    240×480

    CMCC, 意大利

    11

    CMCC-CMS

    96×192

    CMCC, 意大利

    12

    CNRM-CM5

    128×256

    CNRM, CERFACS, 法国

    13

    CSIRO-Mk3-6-0

    96×192

    CSIRO, QCCCE, 澳大利亚

    14

    EC-EARTH

    160×320

    ICHEC, 爱尔兰

    15

    FGOALS-g2

    60×128

    IAP, THU, 中国

    16

    FGOALS-s2

    108×128

    IAP, 中国

    17

    FIO-ESM

    64×128

    FIO, 中国

    18

    GISS-E2-H-CC

    90×144

    NASA/GISS, 美国

    19

    GISS-E2-H

    90×144

    NASA/GISS, 美国

    20

    GISS-E2-R-CC

    90×144

    NASA/GISS, 美国

    21

    GISS-E2-R

    90×144

    NASA/GISS, 美国

    22

    INM-CM4

    120×180

    INM, 俄罗斯

    23

    IPSL-CM5A-LR

    96×96

    IPSL, 法国

    24

    IPSL-CM5A-MR

    143×144

    IPSL, 法国

    25

    IPSL-CM5B-LR

    96×96

    IPSL, 法国

    26

    MIROC-ESM-CHEM

    64×128

    JAMSTEC, AORI, NIES, 日本

    27

    MIROC-ESM

    64×128

    JAMSTEC, AORI, NIES, 日本

    28

    MIROC5

    128×256

    AORI, NIES, JAMSTEC, 日本

    29

    MPI-ESM-LR

    96×192

    MPI-M, 德国

    30

    MPI-ESM-MR

    96×192

    MPI-M, 德国

    31

    MRI-CGCM3

    160×320

    MRI, 日本

    32

    NorESM1-M

    96×144

    NCC, 挪威

    33

    NorESM1-ME

    96×144

    NCC, 挪威

  • 表 2   观测和模拟的时间序列不同时段的线性趋势

    线性趋势(℃/decade)

    1850~2014

    1915~2014

    1965~2014

    1990~2014

    2005~2014

    HadCRUT4

    0.0479

    0.0739

    0.1530

    0.1459

    0.0112

    CMIP5 MMM

    0.0593

    0.0925

    0.2056

    0.2793

    0.2216

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