留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于弱耦合资料同化的冬季北大西洋涛动年际变率预测

李斐斐 徐彩艳

李斐斐,徐彩艳. 2023. 基于弱耦合资料同化的冬季北大西洋涛动年际变率预测. 气象学报,81(1):1-13 doi: 10.11676/qxxb2023.20220062
引用本文: 李斐斐,徐彩艳. 2023. 基于弱耦合资料同化的冬季北大西洋涛动年际变率预测. 气象学报,81(1):1-13 doi: 10.11676/qxxb2023.20220062
Li Feifei, Xu Caiyan. 2023. Improved interannual predictability of winter North Atlantic Oscillation with a weakly coupled data assimilation scheme. Acta Meteorologica Sinica, 81(1):1-13 doi: 10.11676/qxxb2023.20220062
Citation: Li Feifei, Xu Caiyan. 2023. Improved interannual predictability of winter North Atlantic Oscillation with a weakly coupled data assimilation scheme. Acta Meteorologica Sinica, 81(1):1-13 doi: 10.11676/qxxb2023.20220062

基于弱耦合资料同化的冬季北大西洋涛动年际变率预测

doi: 10.11676/qxxb2023.20220062
基金项目: 山东省气象局气象科学技术研究项目(2019sdqxz06)
详细信息
    作者简介:

    李斐斐,主要从事耦合资料同化和气候预测研究。E-mail:lifeifei007@126.com

    通讯作者:

    徐彩艳,主要从事智慧气象服务研究。E-mail:xucaiyan008@163.com

  • 中图分类号:  

Improved interannual predictability of winter North Atlantic Oscillation with a weakly coupled data assimilation scheme

  • 摘要: 北大西洋涛动作为冬季北大西洋地区大气环流的主模态之一,其年际变率对全球许多地区气候变率具有重要影响,但目前其预测技巧并不高。采用降维投影四维变分同化方法,在耦合模式中建立了基于全球大气资料的弱耦合资料同化系统,直接同化月平均再分析资料,并进行了年代际后报试验。结果表明,通过耦合资料同化的手段,可以显著提升耦合模式对冬季北大西洋涛动年际变率及其相关的欧洲北部、美国东部、欧亚大陆北部的冬季近地面温度年际变率的后报效果,相关系数均至少通过了95%信度的t检验。该后报效果的改进主要与在耦合同化过程中通过耦合模式中自由发展的海-气相互作用将大气的观测信息储存在耦合模式的海洋分量中,改进了冬季北大西洋地区海表温度“三极”型分布的时空变率及其时间序列的后报效果有关。该研究强调了耦合模式初始状态的准确度对提升冬季北大西洋涛动年际变率的后报技巧具有重要作用。

     

  • 图 1  基于全球大气资料的弱耦合资料同化系统

    Figure 1.  Weakly coupled data assimilation system of global atmospheric data

    图 2  北大西洋地区 (20°—80°N,90°W—40°E) 1961—2005年冬季 (12月—次年2月) 海平面气压经验正交函数分解的第一模态(EOF1)(a、c、e、g. 空间型态,b、d、f、h. 时间系数)(a、b. NCEP/NCAR Reanalysis 1再分析资料,c、d. 对照试验,e、f. 同化试验,g、h. 后报试验;左下角的数字表示各试验的原始序列与NCEP/NCAR Reanalysis 1再分析资料的相关系数,右上角的数字表示EOF1的方差贡献,时间系数中黑线为11 a滑动平均的结果,*和**分别表示该相关系数通过了95%和99%信度的t检验)

    Figure 2.  Spatial patterns (a,c,e,g) and corresponding time coefficients (b,d,f,h) of EOF1 of winter (December to February) sea level pressure over the North Atlantic (20°—80°N,90°W—40°E) from 1961 to 2005. (a) and (b) represent NCEP/NCAR Reanalysis 1; (c) and (d) represent CTL; (e) and (f) represent ASSIM; (g) and (h) represent HCST (The correlation coefficients of the spatial pattern and time coefficients between these experiments and the reanalysis data are shown at the bottom left corner of each panel. The explained variance of each EOF1 mode is shown at the top right corner in a,c,e and g. The 11-year running averages of the time coefficients are represented by black lines. The correlation coefficients at the confidence levels above 0.05 and 0.01 t-test are marked by subscripts "*" and "**",respectively)

    图 3  1961—2005年标准化的冬季 (12月—次年2月) 亚速尔高压 (a—d) 和冰岛低压 (e—h) 指数随时间的变化(a、e. NCEP/NCAR再分析资料,b、f. 对照试验,c、g. 同化试验,d、h. 后报试验;图中的黑线为11 a滑动平均结果,左下角的数字表示各试验结果的原始序列与观测的相关系数,*和**分别表示相关系数通过了95%和99%信度的t检验(单位:hPa/σ))

    Figure 3.  Normalized time series of winter (December to February) Azores High (a—d) and Icelandic Low (e—h) indexes from 1961 to 2005 (a, c. NCEP/NCAR Reanalysis 1,b, f. CTL,c, g. ASSIM,d, h. HCST;The 11-year running averages of the time coefficients are represented by black lines. The correlation coefficients of the time series between these experiments and the reanalysis data are shown at the bottom left corner of individual panels. The correlation coefficients at the confidence levels above 0.05 and 0.01 t-test are marked by the subscripts "*" and "**"”,respectively (unit:hPa/σ))

    图 4  1961—2005年标准化的冬季 (12月—次年2月) NAO指数与北半球陆地部分去趋势的冬季 (12月—次年2月) 2 m气温异常 (单位:K) 的回归场 (a. NCEP/NCAR 再分析资料,b. 对照试验,c. 同化试验,d. 后报试验;图中打点区域表示该区域的回归系数通过了95%的信度t检验)

    Figure 4.  Regression fields of detrended winter (December to February) 2 m temperature anomalies (unit:K) over the northern hemisphere land with the normalized winter (December to February) NAO index (a. NCEP/NCAR Reanalysis 1,b. CTL,c. ASSIM,d. HCST;the dotted areas indicate the regression coefficients over these areas are at/above the significance level of 0.05 t-test)

    图 5  1961—2005年标准化的欧洲北部 (50°—70°N,5°—50°E) 冬季 (12月—次年2月) 去趋势的2 m气温异常的时间序列 (a. NCEP/NCAR再分析资料,b. 对照试验,c. 同化试验,d. 后报试验;图中的黑线为11 a滑动平均的结果,左下角的数字表示各试验结果的原始序列与观测的相关系数,*和**分别表示相关系数通过了95%和99%信度的t检验; 单位:K/σ)

    Figure 5.  Normalized time series of detrended winter (December to February) 2 m temperature anomalies (unit:K) over northern Europe (50°—70°N,5°—50°E) (a. NCEP/NCAR Reanalysis 1,b. CTL,c.ASSIM,d. HCST; the 11-year running averages of the time coefficients are represented by black lines; the correlation coefficients of the time series between these experiments and the reanalysis data are shown at the bottom left corner of each panel; the correlation coefficients at the significance levels above 0.05 and 0.01 t-test are marked by the subscripts "*" and "**",respectively;unit:K/σ)

    图 6  同图5,但为美国东部 (30°—40°N,75°—105°W)

    Figure 6.  Same as Fig. 5 but for the eastern USA (30°—40°N,75°—105°W)

    图 7  1961—2005年冬季 (12月—次年2月) 北大西洋地区SST异常EOF分解第一模态的空间型态 (a—d) 及其时间序列 (e—h)(a、e. HadISST资料,b、f. 对照试验,c、g. 同化试验,d、h. 后报试验;a—d中右上角的数字表示方差贡献,e—h中的黑线为11 a滑动平均的结果,图中左下角的数字表示各试验结果的原始序列与观测的相关系数,*和**分别表示相关系数通过了95%和99%信度的t检验)

    Figure 7.  Spatial patterns (a—d) and the corresponding time coefficients (e—h) of the first EOF mode (EOF1) of winter (December to February) SST anomalies in the North Atlantic from 1961 to 2005 (a,e. HadISST analysis;b,f. CTL;c. g. ASSIM;d,h. HCST. The explained variance of each EOF1 mode is shown at the top right corner in each panel of a—d. The 11-year running averages of the time coefficients are represented by black lines in panels of e—h,and the correlation coefficients of the time coefficients between these experiments and the reanalysis data are shown at the bottom left corner of each panel. The correlation coefficients at the significance levels above 0.05 and 0.01 t-test are marked by the subscripts "*" and "**",respectively)

    图 8  同图5,但为1961—2005年冬季 (12月—次年2月) 北大西洋地区SST异常“三极”型分布的标准化时间序列 (单位:K/σ)

    Figure 8.  Same as Fig. 5 but for the normalized time series of winter (December to February) "tripole" pattern of SST anomalies over the North Atlantic from 1961 to 2005 (unit:K/σ)

  • 顾薇,李崇银. 2010. IPCC AR4中海气耦合模式对中国东部夏季降水及PDO、NAO年代际变化的模拟能力分析. 大气科学学报,33(4):401-411

    Gu W,Li C Y. 2010. Evaluation of the IPCC AR4 climate models in simulating the interdecadal variations of the east China summer precipitation,PDO and NAO. Trans Atmos Sci,33(4):401-411 (in Chinese)
    祁莉,泮琬楠. 2021. 东亚气温前冬与后冬反相的变化特征及可能影响因子. 大气科学,45(5):1039-1056

    Qi L,Pan W N. 2021. Variability of the phase reversal of the East Asia temperature from early to late winter and the possible influencing factors. Chinese J Atmos Sci,45(5):1039-1056 (in Chinese)
    施春华,孙伟佳,郭栋. 2021. WP和NAO对中国东南部冬季温度的协同影响. 大气科学学报,44(3):394-404

    Shi C H,Sun W J,Guo D. 2021. Synergistic effects of WP and NAO on winter surface temperature in southeastern China. Trans Atmos Sci,44(3):394-404 (in Chinese)
    周天军,宇如聪,郜永祺等. 2006. 北大西洋年际变率的海气耦合模式模拟Ⅰ:局地海气相互作用. 气象学报,64(1):1-17 doi: 10.11676/qxxb2006.001

    Zhou T J,Yu R C,Gao Y Q,et al. 2006. Ocean-atmosphere coupled model simulation of North Atlantic interannual variability I:Local air-sea interaction. Acta Meteor Sinica,64(1):1-17 (in Chinese) doi: 10.11676/qxxb2006.001
    Arribas A,Glover M,Maidens A,et al. 2011. The GloSea4 ensemble prediction system for seasonal forecasting. Mon Wea Rev,139(6):1891-1910 doi: 10.1175/2010MWR3615.1
    Bellenger H,Guilyardi E,Leloup J,et al. 2014. ENSO representation in climate models:From CMIP3 to CMIP5. Climate Dyn,42(7):1999-2018
    Bretherton C S,Battisti D S. 2000. An interpretation of the results from atmospheric general circulation models forced by the time history of the observed sea surface temperature distribution. Geophys Res Lett,27(6):767-770 doi: 10.1029/1999GL010910
    Craig A P, Jacob R, Kauffman B, et al 2005. CPL6: The new extensible, high performance parallel coupler for the community climate system model. Int J High Perform Comput Appl, 19(3): 309-327
    Czaja A,Marshall J. 2001. Observations of atmosphere-ocean coupling in the North Atlantic. Quart J Roy Meteor Soc,127(576):1893-1916 doi: 10.1002/qj.49712757603
    Czaja A,Frankignoul C. 2002. Observed impact of Atlantic SST anomalies on the North Atlantic oscillation. J Climate,15(6):606-623 doi: 10.1175/1520-0442(2002)015<0606:OIOASA>2.0.CO;2
    Czaja A,Robertson A W,Huck T. 2003. The role of Atlantic Ocean-atmosphere coupling in affecting North Atlantic oscillation variability∥Hurrell J W,Kushnir Y,Ottersen G,et al. The North Atlantic Oscillation:Climatic Significance and Environmental Impact. Washington:American Geophysical Union,134:147-172
    Dee D P,Uppala S M,Simmons A J,et al. 2011. The ERA-Interim reanalysis:Configuration and performance of the data assimilation system. Quart J Roy Meteor Soc,137(656):553-597 doi: 10.1002/qj.828
    Deser C,Blackmon M L. 1993. Surface climate variations over the North Atlantic ocean during winter:1900-1989. J Climate,6(9):1743-1753 doi: 10.1175/1520-0442(1993)006<1743:SCVOTN>2.0.CO;2
    Dunstone N,Smith D,Scaife A,et al. 2016. Skilful predictions of the winter North Atlantic Oscillation one year ahead. Nat Geosci,9(11):809-814 doi: 10.1038/ngeo2824
    He Y J,Wang B,Liu M M,et al. 2017. Reduction of initial shock in decadal predictions using a new initialization strategy. Geophys Res Lett,44(16):8538-8547 doi: 10.1002/2017GL074028
    He Y J,Wang B,Liu L,et al. 2020a. A DRP-4DVar-based coupled data assimilation system with a simplified off-line localization technique for decadal predictions. J Adv Model Earth Syst,12(4):e2019MS001768
    He Y J,Wang B,Huang W Y,et al. 2020b. A new DRP-4DVar-based coupled data assimilation system for decadal predictions using a fast online localization technique. Climate Dyn,54(7-8):3541-3559 doi: 10.1007/s00382-020-05190-w
    Hoffman F M,Vertenstein M,Kitabata H,et al. 2005. Vectorizing the community land model. Int J High Perform Comput Appl,19(3):247-260 doi: 10.1177/1094342005056113
    Hurrell J W. 1995. Decadal trends in the North Atlantic oscillation:Regional temperatures and precipitation. Science,269(5224):676-679 doi: 10.1126/science.269.5224.676
    Hurrell J W. 1996. Influence of variations in extratropical wintertime teleconnections on Northern Hemisphere temperature. Geophys Res Lett,23(6):665-668 doi: 10.1029/96GL00459
    Hurrell J W,Van Loon H. 1997. Decadal variations in climate associated with the North Atlantic Oscillation. Climatic Change,36(3-4):301-326
    Hurrell J W,Kushnir Y,Visbeck M. 2001. The North Atlantic oscillation. Science,291(5504):603-605 doi: 10.1126/science.1058761
    Hurrell J W,Kushnir Y,Ottersen G,et al. 2003. An overview of the North Atlantic oscillation∥Hurrell J W,Kushnir Y,Ottersen G,et al. The North Atlantic Oscillation:Climatic Significance and Environmental Impact. Washington:American Geophysical Union,1-35
    Iqbal M J,Hameed S,Khan F. 2013. Influence of Azores high pressure on middle eastern rainfall. Theor Appl Climatol,111(1-2):211-221 doi: 10.1007/s00704-012-0648-4
    Iqbal M J,Rashid S F. 2016. A re-interpretation of impact of the Icelandic Low and Azores High on winter precipitation over Iberian Peninsula. Arab J Geosci,9(2):102 doi: 10.1007/s12517-015-2086-y
    Kim H M,Webster P J,Curry J A. 2012. Seasonal prediction skill of ECMWF System 4 and NCEP CFSv2 retrospective forecast for the Northern Hemisphere Winter. Climate Dyn,39(12):2957-2973 doi: 10.1007/s00382-012-1364-6
    Kistler R,Kalnay E,Collins W,et al. 2001. The NCEP-NCAR 50-year reanalysis:Monthly means CD-ROM and documentation. Bull Amer Meteor Soc,82(2):247-268 doi: 10.1175/1520-0477(2001)082<0247:TNNYRM>2.3.CO;2
    Latif M,Arpe K,Roeckner E. 2000. Oceanic control of decadal North Atlantic sea level pressure variability in winter. Geophys Res Lett,27(5):727-730 doi: 10.1029/1999GL002370
    Latif M,Böning C,Willebrand J,et al. 2006. Is the thermohaline circulation changing?. J Climate,19(18):4631-4637 doi: 10.1175/JCLI3876.1
    Li F F,Wang B,He Y J,et al. 2021a. Important role of North Atlantic air-sea coupling in the interannual predictability of summer precipitation over the eastern Tibetan Plateau. Climate Dyn,56(5-6):1433-1448 doi: 10.1007/s00382-020-05542-6
    Li F F,Wang B,He Y J,et al. 2021b. Improved decadal predictions of East Asian summer monsoon with a weakly coupled data assimilation scheme. Int J Climatol,41(12):5550-5571 doi: 10.1002/joc.7141
    Li L J,Lin P F,Yu Y Q,et al. 2013a. The flexible global ocean-atmosphere-land system model,Grid-point Version 2:FGOALS-g2. Adv Atmos Sci,30(3):543-560 doi: 10.1007/s00376-012-2140-6
    Li L J,Wang B,Dong L,et al. 2013b. Evaluation of grid-point atmospheric model of IAP LASG version 2 (GAMIL2). Adv Atmos Sci,30(3):855-867 doi: 10.1007/s00376-013-2157-5
    Liu H L,Lin P F,Yu Y Q,et al. 2012. The baseline evaluation of LASG/IAP climate system ocean model (LICOM) version 2. Acta Meteor Sinica,26(3):318-329 doi: 10.1007/s13351-012-0305-y
    Liu J P,Song M R,Wang X C. 2014. LASG/IAP sea ice model∥Zhou T J,Yu Y Q,Liu Y M,et al. Flexible Global Ocean-Atmosphere-Land System Model. Berlin,Heidelberg:Springer, 27-31
    Marshall J,Kushnir Y,Battisti D,et al. 2001. North Atlantic climate variability:Phenomena,impacts and mechanisms. Int J Climatol,21(15):1863-1898 doi: 10.1002/joc.693
    Moron V,Vautard R,Ghil M. 1998. Trends,interdecadal and interannual oscillations in global sea-surface temperatures. Climate Dyn,14(7-8):545-569 doi: 10.1007/s003820050241
    Osborn T J,Briffa K R,Tett S F B,et al. 1999. Evaluation of the North Atlantic Oscillation as simulated by a coupled climate model. Climate Dyn,15(9):685-702 doi: 10.1007/s003820050310
    Penny S G, Hamill T M. 2017. Coupled data assimilation for integrated earth system analysis and prediction: Goals, challenges, and recommendations. WWRP
    Rayner N A,Parker D E,Horton E B,et al. 2003. Global analyses of sea surface temperature,sea ice,and night marine air temperature since the late nineteenth century. J Geophys Res:Atmos,108(D14):4407 doi: 10.1029/2002JD002670
    Rodwell M J,Rowell D P,Folland C K. 1999. Oceanic forcing of the wintertime North Atlantic Oscillation and European climate. Nature,398(6725):320-323 doi: 10.1038/18648
    Scaife A A,Arribas A,Blockley E,et al. 2014. Skillful long-range prediction of European and North American winters. Geophys Res Lett,41(7):2514-2519 doi: 10.1002/2014GL059637
    Shi P F,Lu H,Leung L R,et al. 2021. Significant land contributions to interannual predictability of East Asian summer monsoon rainfall. Earth's Future,9(2):e2020EF001762
    Shi P F,Wang B,He Y J,et al. 2022. Contributions of weakly coupled data assimilation-based land initialization to interannual predictability of summer climate over Europe. J Climate,35(2):517-535 doi: 10.1175/JCLI-D-20-0506.1
    Smith D M,Scaife A A,Eade R,et al. 2016. Seasonal to decadal prediction of the winter North Atlantic Oscillation:Emerging capability and future prospects. Quart J Roy Meteor Soc,142(695):611-617 doi: 10.1002/qj.2479
    Sun C,Li J P,Jin F F. 2015. A delayed oscillator model for the quasi-periodic multidecadal variability of the NAO. Climate Dyn,45(7-8):2083-2099 doi: 10.1007/s00382-014-2459-z
    Sutton R T,Allen M R. 1997. Decadal predictability of North Atlantic sea surface temperature and climate. Nature,388(6642):563-567 doi: 10.1038/41523
    Tourre Y M,Rajagopalan B,Kushnir Y. 1999. Dominant patterns of climate variability in the Atlantic ocean during the last 136 years. J Climate,12(8):2285-2299 doi: 10.1175/1520-0442(1999)012<2285:DPOCVI>2.0.CO;2
    Uppala S M,Kållberg P W,Simmons A J,et al. 2005. The ERA-40 Re-analysis. Quart J Roy Meteor Soc,131(612):2961-3012 doi: 10.1256/qj.04.176
    Venzke S,Allen M R,Sutton R T,et al. 1999. The atmospheric response over the North Atlantic to decadal changes in sea surface temperature. J Climate,12(8):2562-2584 doi: 10.1175/1520-0442(1999)012<2562:TAROTN>2.0.CO;2
    Wallace J M,Gutzler D S. 1981. Teleconnections in the geopotential height field during the northern hemisphere winter. Mon Wea Rev,109(4):784-812 doi: 10.1175/1520-0493(1981)109<0784:TITGHF>2.0.CO;2
    Wang B,Liu J J,Wang S D,et al. 2010. An economical approach to four-dimensional variational data assimilation. Adv Atmos Sci,27(4):715-727 doi: 10.1007/s00376-009-9122-3
    Wang B,Liu M M,Yu Y Q,et al. 2013. Preliminary evaluations of FGOALS-g2 for decadal predictions. Adv Atmos Sci,30(3):674-683 doi: 10.1007/s00376-012-2084-x
    Wu L X,Liu Z Y. 2005. North Atlantic decadal variability:Air-sea coupling,oceanic memory,and potential northern hemisphere resonance. J Climate,18(2):331-349 doi: 10.1175/JCLI-3264.1
  • 加载中
图(8)
计量
  • 文章访问数:  41
  • HTML全文浏览量:  7
  • PDF下载量:  6
  • 被引次数: 0
出版历程
  • 收稿日期:  2022-04-13
  • 录用日期:  2022-12-20
  • 修回日期:  2022-07-10
  • 网络出版日期:  2022-07-12

目录

    /

    返回文章
    返回