Abstract
We investigated the intraseasonal variability of equatorial Pacific subsurface temperature and its relationship with El Niño-Southern Oscillation (ENSO) using Self-Organizing Maps (SOM) analysis. Variation in intraseasonal subsurface temperature is mainly found along the thermocline. The SOM patterns concentrate in basin-wide seesaw or sandwich structures along an east-west axis. Both the seesaw and sandwich SOM patterns oscillate with periods of 55 to 90 days, with the sequence of them showing features of equatorial intraseasonal Kelvin wave, and have marked interannual variations in their occurrence frequencies. Further examination shows that the interannual variability of the SOM patterns is closely related to ENSO; and maxima in composite interannual variability of the SOM patterns are located in the central Pacific during CP El Niño and in the eastern Pacific during EP El Niño. These results imply that some of the ENSO forcing is manifested through changes in the occurrence frequency of intraseasonal patterns, in which the change of the intraseasonal Kelvin wave plays an important role.
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References
Ashok H, Yamagata T. 2009. Climate change: the El Niño with a diff erence. Nature, 61 (7263): 481–484, https://doi.org/10.1038/461481a.
Ashok K, Behera S K, Rao S A, Weng H Y, Yamagata T. 2007. El Niño Modoki and its possible teleconnection. J. Geophys. Res., 112 (C11): C11007, https://doi.org/10.1029/2006JC003798.
Bjornsson H, Venegas S A. 1997. A manual for EOF and SVD Analyses of Climate Data. Centre for Climate and Global Change Research, McGill University, Montreal.
Cai W J, Borlace S, Lengaigne M, Van Rensch P, Collins M, Vecchi G, Timmermann A, Santoso A, McPhaden M J, Wu L X, England M H, Wang G J, Guilyardi E, Jin F F. 2014. Increasing frequency of extreme El Niño events due to greenhouse warming. Nat. Climate Change, 4 (2): 111–116, https://doi.org/10.1038/NCLIMATE2100.
Choi J, An S I, Kug J S, Yeh S W. 2011. The role of mean state on changes in El Niño’s flavor. Climate Dyn., 37 (5-6): 1 205–1 215, https://doi.org/10.1007/s00382-010-0912-1.
Chung P H, Li T. 2013. Interdecadal Relationship between the mean State and El Niño types. J. Climate, 26 (2): 361–379, https://doi.org/10.1175/JCLI-D-12-00106.1.
Clarke A J. 2010. Analytical theory for the quasi-steady and lowfrequency equatorial ocean response to wind forcing: the “tilt” and “warm water volume” modes. J. Phys. Oceanogr., 40 (1): 121–137, https://doi.org/10.1175/2009JPO4263.1.
Feldstein S B, Lee S. 2014. Intraseasonal and interdecadal jet shifts in the northern Hemisphere: the role of warm pool tropical convection and sea ice. J. Climate, 27 (17): 6 497–6 518, https://doi.org/10.1175/JCLI-D-14-00057.1.
Feng J Q, Wang Q Y, Hu S J, Hu D X. 2016. Intraseasonal variability of the tropical Pacific subsurface temperature in the two flavours of El Niño. Int. J. Climatol., 36 (2): 867–884, https://doi.org/10.1002/joc.4389.
Feng J, Chen W, Tam C T, Zhou W. 2011. Diff erent impacts of El Niño and El Niño Modoki on China rainfall in the decaying phases. Int. J. Climatol., 31 (14): 2 091–2 101, https://doi.org/10.1002/joc.2217.
Feng J, Li J P. 2011. Influence of El Niño Modoki on spring rainfall over south China. J. Geophys. Res., 116 (D13): D13102, https://doi.org/10.1029/2010JD015160.
Gutiérrez J M, Cano R, Cofiño A S, Sordo C. 2005. Analysis and downscaling multi-model seasonal forecasts in Peru using self-organizing maps. Tellus A: Dyn. Meteorol. Oceanogr., 57 (3): 435–447 url.
Hendon H H, Liebmann B, Glick J D. 1998. Oceanic Kelvin waves and the Madden-Julian oscillation. J. Atmos. Sci., 55 (1): 88–101, https://doi.org/10.1175/1520-0469(1998)055<0088:OKWATM>2.0.CO;2.
Hu Z Z, Kumar A, Zhu J S, Peng P T, Huang B H. 2019. On the challenge for ENSO cycle prediction: an example from NCEP Climate Forecast System, version 2. J. Climate, 32 (1): 183–194, https://doi.org/10.1175/JCLI-D-18-0285.1.
Huang B H, Shin C S, Shukla J, Marx L, Balmaseda M A, Halder S, Dirmeyer P, Kinter III J L. 2017. Reforecasting the ENSO events in the past 57 years (1958–2014). J. Climate, 30 (19): 7 669–7 693, https://doi.org/10.1175/JCLI-D-16-0642.1.
Johnson N C, Feldstein S B, Tremblay B. 2008. The continuum of Northern Hemisphere teleconnection patterns and a description of the NAO shift with the use of selforganizing maps. J. Climate, 21 (23): 6 354–6 371, https://doi.org/10.1175/2008JCLI2380.1.
Johnson N C, Feldstein S B. 2010. The continuum of North Pacific sea level pressure patterns: intraseasonal, interannual, and interdecadal variability. J. Climate, 23 (4): 851–867, https://doi.org/10.1175/2009JCLI3099.1.
Johnson N C. 2013. How many ENSO flavors can we distinguish? J. Climate, 26 (13): 4 816–4 827.
Kessler W S, McPhaden M J, Weickmann K M. 1995. Forcing of intraseasonal Kelvin waves in the equatorial Pacific. J. Geophys. Res., 100 (C6): 10 613–10 631, https://doi.org/10.1029/95JC00382.
Kim S T, Yu J Y, Kumar A, Wang H. 2012. Examination of the two types of ENSO in the NCEP CFS Model and its extratropical associations. Mon. Wea. Rev., 140 (6): 1 908–1 923, https://doi.org/10.1175/MWR-D-11-00300.1.
Kohonen T. 1981. Construction of Similarity Diagrams for Phonemes by a Self-Organizing Algorithm. Helsinki University of Technology, Espoo.
Kohonen T. 1995. Self-Organizing Maps. Springer-Verlag, Berlin, Heidelberg. p. 106–107.
Kohonen T. 2001. Self-Organizing Maps. 3rd edn. Springer, Berlin, Heidelberg. 501p.
Kug J S, Jin F F, An S I. 2009. Two types of El Niño events: cold tongue El Niño and warm pool El Niño. J. Climate, 22 (6): 1 499–1 515, https://doi.org/10.1175/2008JCLI2624.1.
Kumar A, Hu Z Z. 2014. Interannual and interdecadal variability of ocean temperature along the equatorial Pacific in conjunction with ENSO. Climate Dyn., 42 (5-6): 1 243–1 258, https://doi.org/10.1007/s00382-013-1721-0.
Kutsuwada K, McPhaden M. 2002. Intraseasonal variations in the upper equatorial Pacific Ocean prior to and during the 1997–98 El Niño. J. Phys. Oceanogr., 32 (4): 1 133–1 149, https://doi.org/10.1175/1520-0485(2002)032<1133:IVITUE>2.0.CO;2.
L’Heureux M L, Collins D C, Hu Z Z. 2013. Linear trends in sea surface temperature of the tropical Pacific Ocean and implications for the El Niño-southern Oscillation. Climate Dyn., 40 (5-6): 1 223–1 236, https://doi.org/10.1007/s00382-012-1331-2.
L'Heureux M L, Takahashi K, Watkins A B, Barnston A G, Becker E J, Di Liberto T E, Gamble F, Gottschalck J, Halpert M S, Huang B Y, Mosquera-Vásquez K, Wittenberg A T, 2017. Observing and predicting the 2015/16 El Niño. Bull. Amer. Meteor. Soc., 98 (7): 1 363–1 382, https://doi.org/10.1175/BAMS-D-16-0009.1.
Lee S, Feldstein S B. 2013. Detecting ozone- and greenhouse gas-driven wind trends with observational data. Science, 339 (6119): 563–567, https://doi.org/10.1126/science.1225154.
Lee T, McPhaden M J. 2010. Increasing intensity of El Niño in the central-equatorial Pacific. Geophys. Res. Lett., 37 (14): L14603, https://doi.org/10.1029/2010GL044007.
Leloup J A, Lachkar Z, Boulanger J P, Thiria S. 2007. Detecting decadal changes in ENSO using neural networks. Climate Dyn., 28 (2-3): 147–162 url.
Liu Y, Weisberg R H. 2005. Patterns of ocean current variability on the West Florida Shelf using the self-organizing map. J. Geophys. Res., 110: C06003, https://doi.org/10.1029/2004JC002786.
Lyu Y L, Li Y L, Tang X H, Wang F, Wang J N. 2018. Contrasting Intraseasonal Variations of the Equatorial Pacific Ocean between the 1997–1998 and 2015–2016 El Niño Events. Geophy. Res. Lett., 45 (18): 9 748–9 756, https://doi.org/10.1029/2018GL078915.
McPhaden M J, Lee T, McClurg D. 2011. El Niño and its relationship to changing background conditions in the tropical Pacific Ocean. Geophys. Res. Lett., 38 (15): L15709, https://doi.org/10.1029/2011GL048275.
Meinen C S, McPhaden M J. 2000. Observations of warm water volume changes in the equatorial Pacific and their relationship to El Niño and La Niña. J. Climate, 13 (20): 3 551–3 559 url.
Overland J E, Preisendorfer R W. 1982. A significance test for principal components applied to a cyclone climatology. Mon. Wea. Rev., 110 (1): 1–4, https://doi.org/10.1175/1520-0493(1982)110<0001:ASTFPC>2.0.CO;2.
Ren H L, Wang R, Zhai P M, Ding Y H, Lu B. 2017. Upperocean dynamical features and prediction of the super El Niño in 2015/16: a comparison with the cases in 1982/83 and 1997/98. J. Meteor. Res., 31 (2): 278–294, https://doi.org/10.1007/s13351-017-6194-3.
Santoso A, Mcphaden M J, Cai W J. 2017. The defining characteristics of ENSO extremes and the strong 2015/2016 El Niño. Rev. Geophy., 55 (4): 1 079–1 129, https://doi.org/10.1002/2017RG000560.
Smith T M, Reynolds R W, Peterson T C, Lawrimore J. 2008. Improvements to NOAA’s historical merged land-ocean surface temperature analysis (1880-2006). J. Climate, 21 (10): 2 283–2 296, https://doi.org/10.1175/2007JCLI2100.1.
Xue Y, Kumar A. 2017. Evolution of the 2015/16 el Niño and historical perspective since 1979. Sci. China Earth Sci., 60 (9): 1 572–1 588, https://doi.org/10.1007/s11430-016-0106-9.
Xue Y, Smith T M, Reynolds R W. 2003. Interdecadal changes of 30-Yr SST normals during 1871–2000. J. Climate, 16 (10): 1 601–1 612.
Yeh S W, Kug J S, Dewitte B, Kwon M H, Kirtman B P, Jin F F. 2009. El Niño in a changing climate. Nature, 61 (7263): 511–515, https://doi.org/10.1038/nature08316.
Yu J Y, Kao H Y. 2007. Decadal changes of ENSO persistence barrier in SST and ocean heat content indices: 1958–2001. J. Geophys. Res., 112 (D13): D13106, https://doi.org/10.1029/2006JD007654.
Yuan J C, Tan B K, Feldstein S B, Lee S. 2015, Wintertime North Pacific teleconnection patterns: seasonal and interannual variability. J. Climate, 28 (20): 8 247–8 263, https://doi.org/10.1175/JCLI-D-14-00749.1.
Zhang C Z. 2001. Intraseasonal perturbations in sea surface temperatures of the equatorial eastern Pacific and their association with the Madden-Julian oscillation. J. Climate, 14 (6): 1 309–1 322, https://doi.org/10.1175/1520-0442(2001)014<1309:IPISST>2.0.CO;2.
Zhang R H, Zheng F, Zhu J, Wang Z G. 2013. A successful real-time forecast of the 2010–11 La Niña event. Sci. Rep., 3: 1–108, https://doi.org/10.1038/srep01108.
Zhu J S, Kumar A, Huang B H, Balmaseda M A, Hu Z Z, Marx L, Kinter III J L. 2016. The role of off-equatorial surface temperature anomalies in the 2014 El Niño prediction. Sci. Rep., 6: 19 677, https://doi.org/10.1038/srep19677.
Acknowledgment
The TAO/TRITON array observation data from the TAO Project Office of NOAA/PMEL. The NOAA_ ERSST_V3b data were provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA and were obtained from their web site at https://www.esrl.noaa.gov/psd/. We thank Tina Tin, PhD, from Liwen Bianji, Edanz Group China (http://www.liwenbianji.cn/ac), for editing the English text of a draft of this manuscript.
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Supported by the National Natural Science Foundation of China (NSFC) (Nos. 41976027, 41976011, 41730534, 41476017, 41576014) and the Bureau of International Cooperation Chinese Academy of Sciences (No. 132B61KYSB20170005)
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Feng, J., Wang, F., Wang, Q. et al. Intraseasonal variability of the equatorial Pacific Ocean and its relationship with ENSO based on Self-Organizing Maps analysis. J. Ocean. Limnol. 38, 1108–1122 (2020). https://doi.org/10.1007/s00343-020-9328-x
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DOI: https://doi.org/10.1007/s00343-020-9328-x