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近百年及未来百年PDO位相年代际转变检测及其早期预警信号研究

吴浩 颜鹏程 侯威 赵俊虎 封国林

吴浩, 颜鹏程, 侯威, 等. 2022. 近百年及未来百年PDO位相年代际转变检测及其早期预警信号研究[J]. 大气科学, 46(2): 225−236 doi: 10.3878/j.issn.1006-9895.2108.20127
引用本文: 吴浩, 颜鹏程, 侯威, 等. 2022. 近百年及未来百年PDO位相年代际转变检测及其早期预警信号研究[J]. 大气科学, 46(2): 225−236 doi: 10.3878/j.issn.1006-9895.2108.20127
WU Hao, YAN Pengcheng, HOU Wei, et al. 2022. Detection of Decadal Phase Transition and Early Warning Signals of PDO in Recent and Next 100 Years [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 46(2): 225−236 doi: 10.3878/j.issn.1006-9895.2108.20127
Citation: WU Hao, YAN Pengcheng, HOU Wei, et al. 2022. Detection of Decadal Phase Transition and Early Warning Signals of PDO in Recent and Next 100 Years [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 46(2): 225−236 doi: 10.3878/j.issn.1006-9895.2108.20127

近百年及未来百年PDO位相年代际转变检测及其早期预警信号研究

doi: 10.3878/j.issn.1006-9895.2108.20127
基金项目: 国家自然科学基金项目42005058、41675092、41775078、42005056,湖南省自然科学基金项目2020JJ5298,干旱气象科学研究基金项目IAM202104
详细信息
    作者简介:

    吴浩,男,1988年出生,硕士、工程师,主要从事气候变化、极端天气气候事件方面的研究。E-mail: wuhaophy@163.com

    通讯作者:

    封国林,E-mail: fenggl@cam.gov.cn

  • 中图分类号: P467

Detection of Decadal Phase Transition and Early Warning Signals of PDO in Recent and Next 100 Years

Funds: National Natural Science Foundation of China (Grants 42005058, 41675092, 41775078, 42005056), Hunan Provence Natural Science Foundation of China (Grant 2020JJ5298), Foundation of drought Meteorological Science Research (Grant IAM202104)
  • 摘要: 本文基于临界慢化的理论,采用太平洋年代际振荡(Pacific Decadal Oscillation, PDO)指数的近百年(1900~2019年)历史数据及未来百年(2006~2100年)模式模拟数据,首先通过滑动t检验确定PDO位相转变的时间,进而借助于表征临界慢化现象的方差和自相关系数,研究了PDO年代际位相转折的早期预警信号。结果表明:(1)近百年来PDO发生了4次显著的位相转变,每次位相转变前的5~10年可以提取到早期预警信号;(2)通过对CMIP5气候模式资料计算得到的PDO进行统计合成得到未来百年的PDO序列,检测结果表明在2040年和2080年前后发生年代际转折,转折前的5~10年能够检测到早期预警信号;(3)近百年和未来百年PDO序列的位相转变及早期预警信号研究证实在PDO发生位相转变之前方差和自相关系数总能提前数年给出预警信号,也揭示了未来PDO的转折时间。
  • 图  1  (a)滑动计算方差、(b)滑动计算自相关系数示意图。L1L2L3、···Ln···,L12L22L32、···Ln2···代表长度相同的各个窗口(ML),s1s2s3、···sn···代表对应窗口长度数据的均方差,L为序列总长度,MT为滑动步长,α1代表L1L12的自相关系数,α2代表L2L22的自相关系数,···αn代表LnLn2的自相关系数,LT表示滞后时间

    Figure  1.  (a) Calculation of the variance and (b) autocorrelation coefficient using the sliding window method. L1, L2, L3, ···, Ln···and L12, L22, L32,···Ln2···denote windows of the same length; s1, s2, s3,···sn··· denote the variances of the corresponding windows; L is the total length of the sequence; MT is the sliding step; α1 denotes the autocorrelation coefficients of L1 and L12, α2 denotes the autocorrelation coefficients of L2 and L22, αn denotes the autocorrelation coefficients of Ln and Ln2; LT denotes the lag time

    图  2  近百年PDO指数(柱状;红色:正值;蓝色:负值)的时间变化曲线。黑色曲线为51个月滑动平均提取的趋势信息

    Figure  2.  Curves of the PDO (Pacific Decadal Oscillation) index (bars; red: positive value; blue: negative value) changing with time in the recent 100 years. Black curve denotes the trend information extracted from the 51-month moving average

    图  3  基于MTT方法的近百年PDO序列位相转变检测:(a)滑动窗口t为5年;(b)滑动窗口t为12年。虚线表示显著性水平为0.05

    Figure  3.  Phase transition detection of the PDO sequence in the recent 100 years based on the MTT (Moving t-test) method: (a) Sliding window t is 5 years; (b) sliding window t is 12 years. Dashed lines denote the 0.05 significance level

    图  4  近百年PDO序列方差信号检测:(a)1921年位相转变的方差信号检测;(b)1942年位相转变的方差信号检测;(c)1976年位相转变的方差信号检测;(d)1998年位相转变的方差信号检测。滑动窗口(ML)为10年,滑动步长(MT)为3个月

    Figure  4.  Signals detection of the variance of the PDO sequence in the recent 100 years: (a) Variance signal detection of phase transitions in 1921; (b) variance signal detection of phase transitions in 1942; (c) variance signal detection of phase transitions in 1976; (d) variance signal detection of phase transitions in 1998. ML (sliding window) is 10 years and MT (sliding step) is 3 months

    图  5  近百年PDO序列自相关系数信号检测:(a)1921年位相转变的自相关系数信号检测;(b)1942年位相转变的自相关系数信号检测;(c)1976年位相转变的自相关系数信号检测;(d)1998年位相转变的自相关系数信号检测。ML为10年、MT为3个月、滞后时间(LT)为1个月

    Figure  5.  Signals detection of the autocorrelation coefficient of the PDO sequence in the recent 100 years: (a) Autocorrelation signal detection of phase transitions in 1921; (b) autocorrelation signal detection of phase transitions in 1942; (c) autocorrelation signal detection of phase transitions in 1976; (d) autocorrelation signal detection of phase transitions in 1998. ML is 10 years, MT is 3 months, and LT (lag time) is 1 month

    图  6  未来百年PDO指数(柱状;红色:正值;蓝色:负值)的时间变化曲线。黑色曲线为51个月滑动平均提取的趋势信息

    Figure  6.  Curves of the PDO index (bars; red: positive value; blue: negative value) changing with time in the next 100 years. Black curve denotes the trend information extracted from the 51-month moving average

    图  7  基于MTT方法的未来百年PDO序列位相转变检测:(a)滑动窗口t为10年;(b)滑动窗口t为12年。虚线表示显著性水平为0.05

    Figure  7.  Phase transition detection of the PDO sequence in the next 100 years based on the MTT method: (a) Sliding window t is 10 years; (b) the sliding window t is 12 years. Dashed lines denote the 0.05 significance level

    图  8  未来百年PDO序列方差信号检测:(a)2040年位相转变的方差信号检测;(b)2080年位相转变的方差信号检测。ML为10年,MT为3个月

    Figure  8.  Signals detection of the variance of the PDO sequence in the next 100 years: (a) Variance signal detection of phase transitions in 2040; (b) variance signal detection of phase transitions in 2080. ML is 10 years and MT is 3 months

    图  9  未来百年PDO序列自相关系数信号检测:(a)2040年位相转变的自相关系数信号检测;(b)2080年位相转变的自相关系数信号检测。ML为10年,MT为3个月,LT为1个月

    Figure  9.  Signals detection of the autocorrelation coefficient of the PDO sequence in the next 100 years: (a) Autocorrelation signal detection of phase transitions in 2040; (b) autocorrelation signal detection of phase transitions in 2080. ML is 10 years, MT is 3 months, and LT is 1 month

    表  1  CMIP5(phase 5 of Coupled Model Intercomparison Project)的36个气候模式

    Table  1.   The 36 climate models of CMIP5 (phase 5 of Coupled Model Intercomparison Project)

    编号模式名称编号模式名称编号模式名称编号模式名称
    1ACCESS1-010CMCC-CMS19GISS-E2-H-CC28IPSL-CM5B-LR
    2ACCESS1-311CNRM-CM520GISS-E2-R29MIROC-ESM
    3BCC-CSM1-112CSIRO-Mk3-6-021GISS-E2-R-CC30MIROC-ESM-CHEM
    4BCC-CSM1-1-M13FGOALS-g222HadGEM2-AO31MIROC5
    5BNU-ESM14FIO-ESM23HadGEM2-CC32MPI-ESM-LR
    6CanESM215GFDL-CM324HadGEM2-ES33MPI-ESM-MR
    7CCSM416GFDL-ESM2G25inmcm434MRI-CGCM3
    8CESM1-BGC17GFDL-ESM2M26IPSL-CM5A-LR35NorESM1-M
    9CMCC-CM18GISS-E2-H27IPSL-CM5A-MR36NorESM1-ME
    注:加粗字体模式表示选中的最具代表性的模式。
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-03-10
  • 录用日期:  2021-10-18
  • 网络出版日期:  2021-09-29
  • 刊出日期:  2022-03-16

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