Estimating the limit of decadal-scale climate predictability using observational data
详细信息    查看全文
  • 作者:Ruiqiang Ding ; Jianping Li ; Fei Zheng ; Jie Feng ; Deqiang Liu
  • 关键词:Decadal ; scale climate predictability ; Nonlinear local Lyapunov exponent (NLLE) ; Initial ; value decadal predictability limit
  • 刊名:Climate Dynamics
  • 出版年:2016
  • 出版时间:March 2016
  • 年:2016
  • 卷:46
  • 期:5-6
  • 页码:1563-1580
  • 全文大小:4,671 KB
  • 参考文献:Allan R, Ansell T (2006) A new globally complete monthly historical gridded mean sea level pressure dataset (HadSLP2): 1850–2004. J Clim 19:5816–5842CrossRef
    Boer GJ (2000) A study of atmosphere–ocean predictability on long time scales. Clim Dyn 16:469–472CrossRef
    Boer GJ (2004) Long time-scale potential predictability in an ensemble of coupled climate models. Clim Dyn 23:29–44CrossRef
    Boer GJ (2011) Decadal potential predictability of twenty-first century climate. Clim Dyn 36:1119–1133CrossRef
    Bojariu R, Gimeno L (2003) The role of snow cover fluctuations in multiannual NAO persistence. Geophys Res Lett 30:1156. doi:10.​1029/​2002GL015651 CrossRef
    Branstator G, Teng H (2010) Two limits of initial-value decadal predictability in a CGCM. J Clim 23:6292–6311CrossRef
    Buermann W, Lintner B, Bonfils C (2005) A wintertime Arctic Oscillation signature on early-season Indian Ocean monsoon intensity. J Clim 18:2247–2269CrossRef
    Chang P, Saravanan R, Ji L (2003) Tropical Atlantic seasonal predictability: the roles of El Niño remote influence and thermodynamic air-sea feedback. Geophys Res Lett 30:1501. doi:10.​1029/​2002GL016119
    Chen BH, Li JP, Ding RQ (2006) Nonlinear local Lyapunov exponent and atmospheric predictability research. Sci Chin 49D:1111–1120CrossRef
    Codron F (2005) Relation between annular modes and the mean state: Southern Hemisphere Summer. J Clim 18:320–330CrossRef
    Collins M (2002) Climate predictability on interannual to decadal time scales: the initial value problem. Clim Dyn 19:671–692CrossRef
    Collins M, Sinha B (2003) Predictability of decadal variations in the thermohaline circulation and climate. Geophys Res Lett 30:1306. doi:10.​1029/​2002GL016504 CrossRef
    Collins M, Frame D, Sinha B, Wilson C (2002) How far ahead could we predict El Niño? Geophys Res Lett 29:1492. doi:10.​1029/​2001GL013919
    Delworth TL, Mann ME (2000) Observed and simulated multidecadal variability in the Northern Hemisphere. Clim Dyn 16:661–676CrossRef
    Deser C, Timlin M (1997) Atmosphere–ocean interaction on weekly timescales in the North Atlantic and Pacific. J Clim 10:393–408CrossRef
    Ding RQ, Li JP (2007) Nonlinear finite-time Lyapunov exponent and predictability. Phys Lett A 364:396–400CrossRef
    Ding RQ, Li JP, Ha KJ (2008) Trends and interdecadal changes of weather predictability during 1950s–1990s. J Geophys Res 113:D24112. doi:10.​1029/​2008JD010404 CrossRef
    Ding RQ, Li JP, Seo KH (2010) Predictability of the Madden–Julian oscillation estimated using observational data. Mon Weather Rev 138:1004–1013CrossRef
    Ding RQ, Li JP, Seo KH (2011) Estimate of the predictability of boreal summer and winter intraseasonal oscillations from observations. Mon Weather Rev 139:2421–2438CrossRef
    Eckmann JP, Ruelle D (1985) Ergodic theory of chaos and strange attractors. Rev Mod Phys 57:617–656CrossRef
    Flato G, Marotzke J, Abiodun B, Braconnot P, Chou SC, Collins W, Cox P, Driouech F, Emori S, Eyring V, Forest C, Gleckler P, Guilyardi E, Jakob C, Kattsov V, Reason C, Rummukainen M (2013) Evaluation of climate models. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp 741–866
    Gong DY, Wang SW (1999) Definition of Antarctic oscillation index. Geophys Res Lett 26:459–462. doi:10.​1029/​1999GL900003 CrossRef
    Goswami BN, Shukla J (1991) Predictability of the coupled ocean–atmosphere model. J Clim 4:3–22CrossRef
    Griffies SM, Bryan K (1997) A predictability study of simulated North Atlantic multidecadal variability. Clim Dyn 13:459–488CrossRef
    Han WQ, Vialard J, McPhaden MJ, Lee T, Masumoto Y, Feng M, de Ruijter WPM (2014) Indian Ocean decadal variability: a review. Bull Am Meteorol Soc. doi:10.​1175/​BAMS-D-13-00028.​1
    Hasselmann K (1976) Stochastic climate models. Part I: theory. Tellus 28:473–485CrossRef
    Hurrell JW, Kushnir Y, Visbeck M (2001) The North Atlantic Oscillation. Science 291:603–605CrossRef
    Jaswal AK, Singh V, Bhambak SR (2012) Relationship between sea surface temperature and surface air temperature over Arabian Sea, Bay of Bengal and Indian Ocean. J Ind Geophys Union 16:41–53
    Jin EK, Kinter JL, Wang B, Park CK, Kang IS, Kirtman BP, Kug JS, Kumar A, Luo JJ, Schemm J, Shukla J, Yamagata T (2008) Current status of ENSO prediction skill in coupled ocean–atmosphere models. Clim Dyn 31:647–664CrossRef
    Kaplan A, Cane M, Kushnir Y, Clement A, Blumenthal M, Rajagopalan B (1998) Analyses of global sea surface temperature 1856–1991. J Geophys Res 103:18567–18589. doi:10.​1029/​97JC01736 CrossRef
    Kazantsev E (1999) Local Lyapunov exponents of the quasi–geostrophic ocean dynamics. Appl Math Comput 104:217–257CrossRef
    Keenlyside NS, Latif M, Jungclaus J, Kornblueh L, Roeckner E (2008) Advancing decadal-scale climate prediction in the North Atlantic sector. Nature 453:84–88CrossRef
    Kim HM, Webster PJ, Curry JA (2012) Evaluation of short-term climate change prediction in multi-model CMIP5 decadal hindcasts. Geophys Res Lett 39:L10701. doi:10.​1029/​2012GL051644
    Kirtman BP, Schopf PS (1998) Decadal variability in ENSO predictability and prediction. J Clim 11:2804–2822CrossRef
    Knight JR, Folland CK, Scaife AA (2006) Climate impacts of the Atlantic Multidecadal Oscillation. Geophys Res Lett 33:L17706. doi:10.​1029/​2006GL026242 CrossRef
    Kumar A, Chen MY, Wang WQ (2013) Understanding prediction skill of seasonal mean precipitation over the tropics. J Clim 26:5674–5681CrossRef
    Lacarra JF, Talagrand O (1988) Short-range evolution of small perturbations in a baratropic model. Tellus 40A:81–95CrossRef
    Latif M, Anderson D, Barnett T, Cane M, Kleeman R, Leetmaa A, O’Brien J, Rosati A, Schneider E (1998) A review of the predictability and prediction of ENSO. J Geophys Res 103:14375–14394CrossRef
    Latif M, Roeckner E, Botzet M, Esch M, Haak H, Hagemann S, Jungclaus JH, Legutke S, Marsland SJ, Mikolajewicz U, Mitchell J (2004) Reconstructing, monitoring, and predicting multidecadal-scale changes in the North Atlantic thermohaline circulation with sea surface temperature. J Clim 17:1605–1614CrossRef
    Latif M, Collins M, Pohlmann H, Keenlyside N (2006) A review of predictability studies of Atlantic sector climate on decadal time scales. J Clim 19:5971–5987CrossRef
    Lau NC, Nath MJ (1996) The role of the atmospheric bridge in linking tropical Pacific ENSO events to extratropical SST anomalies. J Clim 9:2036–2057CrossRef
    Li JP, Ding RQ (2008) Temporal-spatial distributions of predictability limit of short-term climate. Chin J Atmos Sci 32:975–986 (in Chinese with English abstract)
    Li JP, Ding RQ (2011) Temporal–spatial distribution of atmospheric predictability limit by local dynamical analogues. Mon Weather Rev 139:3265–3283CrossRef
    Li JP, Ding RQ (2013) Temporal–spatial distribution of the predictability limit of monthly sea surface temperature in the global oceans. Int J Climatol 33:1936–1947CrossRef
    Li JP, Wang JXL (2003) A modified zonal index and its physical sense. Geophys Res Lett 30:1632. doi:10.​1029/​2003GL017441
    Li JP, Wang S (2008) Some mathematical and numerical issues in geophysical fluid dynamics and climate dynamics. Commun Comput Phys 3:759–793
    Lienert F, Doblas-Reyes FJ (2013) Decadal prediction of interannual tropical and North Pacific sea surface temperature. J Geophys Res Atmos 118:5913–5922. doi:10.​1002/​jgrd.​50469 CrossRef
    Lim EP, Hendon HH, Rashid H (2013) Seasonal predictability of the southern annular mode due to its association with ENSO. J Clim 26:8037–8054CrossRef
    Liu ZY (2012) Dynamics of interdecadal climate variability: a historical perspective. J Clim 25:1963–1995CrossRef
    Liu XH, Ding RQ (2007) The relationship between the spring Asian atmospheric circulation and the previous winter Northern Hemisphere annular mode. Theor Appl Climatol 88:71–81CrossRef
    Lorenz EN (1963) Deterministic nonperiodic flow. J Atmos Sci 20:130–141CrossRef
    Lorenz EN (1965) A study of the predictability of a 28-variable atmospheric model. Tellus 17:321–333CrossRef
    Lorenz EN (1969) Atmospheric predictability as revealed by naturally occurring analogues. J Atmos Sci 26:636–646CrossRef
    Luterbacher J, Xoplaki E, Dietrich D, Rickli R, Jacobeit J, Beck C, Gyalistras D, Schmutz C, Wanner H (2002) Reconstruction of sea level pressure fields over the Eastern North Atlantic and Europe back to 1500. Clim Dyn 18:545–561CrossRef
    Mantua NJ, Hare SR (2002) The Pacific decadal oscillation. J Oceanogr 58:35–44CrossRef
    Mantua NJ, Hare SR, Zhang Y, Wallace JM, Francis RC (1997) A Pacific interdecadal climate oscillation with impacts on salmon production. Bull Am Meteorol Soc 78:1069–1079CrossRef
    Marshall J, Kushner Y, Battisti D, Chang P, Czaja A, Dickson R, Hurrell J, McCartney M, Saravanan R, Visbeck M (2001) North Atlantic climate variability: phenomena, impacts, and mechanisms. Int J Climatol 21:1863–1898CrossRef
    Meehl GA, Goddard L, Murphy JM, Stouffer RJ, Boer G, Danabasoglu G, Dixon KW, Giorgetta MA, Greene AM, Hawkins E (2009) Decadal prediction: can it be skillful? Bull Am Met Soc 90:1467–1485CrossRef
    Mehta V, Meehl G, Goddard L, Knight J, Kumar A, Latif M, Lee T, Rosati A, Stammer D (2011) Decadal climate predictability and prediction: where are we? Bull Am Meteorol Soc 92:637–640CrossRef
    Molinari RL, Mestas-Nuñez AM (2003) North Atlantic decadal variability and the formation of tropical storms and hurricanes. Geophys Res Lett 30:1541. doi:10.​1029/​2002GL016462 CrossRef
    Msadek R, Dixon KW, Delworth TL, Hurlin W (2010) Assessing the predictability of the Atlantic meridional overturning circulation and associated fingerprints. Geophys Res Lett 37:L19608. doi:10.​1029/​2010GL044517
    Mu M (2000) Nonlinear singular vectors and nonlinear singular values. Sci Chin 43D:375–385CrossRef
    Mukougawa H, Hirooka T, Kuroda Y (2009) Influence of stratospheric circulation on the predictability of the tropospheric Northern Annular Mode. Geophys Res Lett 36:L08814. doi:10.​1029/​2008GL037127 CrossRef
    Murphy J, Kattsov V, Keenlyside N, Kimoto M, Meehl G, Mehta V, Pohlmann H, Scaife A, Smith D (2010) Towards prediction of decadal climate variability and change. Procedia Environ Sci 1:287–304CrossRef
    Nan SL, Li JP (2003) The relationship between summer precipitation in the Yangtze River valley and the boreal spring Southern Hemisphere annular mode. Geophys Res Lett 30:2266. doi:10.​1029/​2003GL018381 CrossRef
    Nidheesh A, Lengaigne M, Vialard J, Unnikrishnan A, Dayan H (2012) Decadal and long-term sea level variability in the tropical Indo-Pacific Ocean. Clim Dyn 41:381CrossRef
    O’Kanea TJ, Mateara RJ, Chamberlaina MA, Risbeya JS, Sloyana BM, Horenko I (2013) Decadal variability in an OGCM Southern Ocean: intrinsic modes, forced modes and metastable states. Ocean Model 69:1–21CrossRef
    Ostermeier GM, Wallace JM (2003) Trends in the North Atlantic Oscillation-Northern Hemisphere annular mode during the twentieth century. J Clim 16:336–341CrossRef
    Pohlmann H, Botzet M, Latif M, Roesch A, Wild M, Tschuck P (2004) Estimating the decadal predictability of a coupled AOGCM. J Clim 17:4463–4472CrossRef
    Pohlmann H, Jungclaus JH, Kohl A, Stammer D, Marotzke J (2009) Initializing decadal climate predictions with the GECCO oceanic synthesis: effects on the North Atlantic. J Clim 22:3926–3938CrossRef
    Prieto L, Garcia R, Diaz J, Hernandez E, del Teso T (2002) NAO influence on extreme winter temperatures in Madrid (Spain). Ann Geophys 20:2077–2085CrossRef
    Reynolds RW, Smith TM (1994) Improved global sea surface temperature analysis using optimum interpolation. J Clim 7:929–948CrossRef
    Schlesinger M, Ramankutty N (1994) An oscillation in the global climate system of period 65–70 years. Nature 367:723–726CrossRef
    Seo KH, Wang W, Gottschalck J, Zhang Q, Schemm JKE, Higgins WR, Kumar A (2009) Evaluation of MJO forecast skill from several statistical and dynamical forecast models. J Clim 22:2372–2388CrossRef
    Shukla J (1984) Predictability of time averages, Part II. The influence of the boundary forcing. In: Burridge DN, Kallen E (eds) Problems and prospects in long and medium range weather forecasting. Springer, Berlin, pp 155–206CrossRef
    Smith TM, Reynolds RW, Peterson TC, Lawrimore J (2008) Improvements to NOAA’s historical merged land-ocean surface temperature analysis (1880–2006). J Clim 21:2283–2296CrossRef
    Stammerjohn SE, Martinson DG, Smoth RC, Yuan XJ, Rind D (2008) Trends in Antarctic annual sea ice retreat and advance and their relation to El Nino-Southern oscillation and southern annular mode variability. J Geophys Res 113:C03S90. doi:10.​1029/​2007JC004269
    Sutton RT, Hodson DLR (2005) Atlantic Ocean forcing of North American and European summer climate. Science 309:115–118CrossRef
    Tang YM, Kleeman R, Moore AM (2005) Reliability of ENSO dynamical predictions. J Atmos Sci 62:1770–1791CrossRef
    Thompson DWJ, Wallace JM (1998) The Arctic oscillation signature in the wintertime geopotential height and temperature fields. Geophys Res Lett 25:1297–1300. doi:10.​1029/​98GL00950 CrossRef
    Trenberth KE, Jones PD, Ambenje P, Bojariu R, Easterling D, Tank AK, Parker D, Rahimzadeh F, Renwick JA, Rusticucci M, Soden B, Zhai P (2007) Observations: surface and atmospheric climate change. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp 235–336
    van Oldenborgh GJ, Doblas-Reyes FJ, Wouters B, Hazeleger W (2012) Decadal prediction skill in a multi-model ensemble. Clim Dyn 38:1263–1280CrossRef
    Verdy A, Marshall J, Czaja A (2005) Sea surface temperature variability along the path of the Antarctic circumpolar current. J Phys Oceanogr 36:1317–1331CrossRef
    Wang B et al (2009) Advance and prospectus of seasonal prediction: assessment of APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980–2004). Clim Dyn 33:93–117CrossRef
    Watanabe M, Nitta T (1999) Decadal changes in the atmospheric circulation and associated surface climate variations in the Northern Hemisphere winter. J Clim 12:494–510CrossRef
    Wheeler M, Hendon HH (2004) An all-season real-time multivariate MJO index: development of an index for monitoring and prediction. Mon Weather Rev 132:1917–1932CrossRef
    Yang XY, Wang DX, Wang J, Huang RX (2007) Connection between the decadal variability in the Southern Ocean circulation and the southern annular mode. Geophys Res Lett 34:L16604. doi:10.​1029/​2007GL030526
    Yeh SW, Kirtman BP (2004) The impact of internal atmospheric variability on the North Pacific SST variability. Clim Dyn 22:721–732CrossRef
    Yeh SW, Kirtman BP (2006) Origin of decadal El Niño–Southern Oscillation-like variability in a coupled general circulation model. J Geophys Res 111:C01009. doi:10.​1029/​2005JC002985
    Yoden S, Nomura M (1993) Finite-time Lyapunov stability analysis and its application to atmospheric predictability. J Atmos Sci 50:1531–1543CrossRef
    Yuan XJ, Yonekura E (2011) Decadal variability in the Southern Hemisphere. J Geophys Res 116:D19115. doi:10.​1029/​2011JD015673 CrossRef
    Zhang Y, Wallace JM, Battisti DS (1997) ENSO-like interdecadal variability. J Clim 10:1004–1020CrossRef
    Zhang R, Delworth TL, Held IM (2007) Can the Atlantic Ocean drive the observed multidecadal variability in Northern Hemisphere mean temperature? Geophys Res Lett 34:L02709. doi:10.​1029/​2006GL028683
    Zheng F, Zhu J, Zhang RH, Zhou GQ (2006) Ensemble hindcasts of SST anomalies in the tropical Pacific using an intermediate coupled model. Geophys Res Lett 33:L19604. doi:10.​1029/​2006GL026994 CrossRef
    Zhou TJ, Yu RC (2004) Sea-surface temperature induced variability of the southern annular mode in an atmospheric general circulation model. Geophys Res Lett 31:L24206. doi:10.​1029/​2004GL021473 CrossRef
    Ziehmann C, Smith LA, Kurths J (2000) Localized Lyapunov exponents and the prediction of predictability. Phys Lett A 4:237–251CrossRef
  • 作者单位:Ruiqiang Ding (1)
    Jianping Li (2) (3)
    Fei Zheng (4)
    Jie Feng (1)
    Deqiang Liu (1)

    1. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
    2. College of Global Change and Earth System Sciences (GCESS), Beijing Normal University, Beijing, 100875, China
    3. Joint Center for Global Change Studies, Beijing, 100875, China
    4. International Center for Climate and Environmental Sciences (ICCES), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
  • 刊物类别:Earth and Environmental Science
  • 刊物主题:Earth sciences
    Geophysics and Geodesy
    Meteorology and Climatology
    Oceanography
  • 出版者:Springer Berlin / Heidelberg
  • ISSN:1432-0894
文摘
Current coupled atmosphere–ocean general circulation models can not simulate decadal variability well, and model errors would have a significant impact on the estimation of decadal predictability. In this study, the nonlinear local Lyapunov exponent method is adopted to estimate the limit of decadal predictability based on 9-year low-pass filtered sea surface temperature (SST) and sea level pressure (SLP) observations. The results show that the limit of decadal predictability of the SST field is relatively large in the North Atlantic, North Pacific, Southern Ocean, tropical Indian Ocean, and western North Pacific, exceeding 7 years at most locations in these regions. In contrast, the limit of the SST field is relatively small in the tropical central–eastern Pacific (4–6 years). Similar to the SST field, the SLP field has a relatively large limit of decadal predictability over the Antarctic, North Pacific, and tropical Indian Ocean (>6 years). In addition, a relatively large limit of decadal predictability of the SLP field also occurs over the land regions of Africa, India, and South America. Distributions of the limit of decadal predictability of both the SST and SLP fields are almost consistent with those of their intensity and persistence on decadal timescales. By examining the limit of decadal predictability of several major climate modes, we found that the limit of decadal predictability of the Pacific decadal oscillation (PDO) is about 9 years, slightly lower than that of the Atlantic multidecadal oscillation (AMO) (about 11 years). In contrast, the northern and southern annular modes have limits of decadal predictability of about 4 and 9 years, respectively. However, the above limits estimated using time-filtered data may overestimate the predictability of decadal variability due to the use of time filtering. Filtered noise with the same spectral characteristics as the PDO and AMO, has a predictability of about 3 years. Future work is required with a longer period of observations or using a more realistic model of decadal variability to assess the real-time decadal predictability.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700