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Influence of Westerly Wind Events stochasticity on El Niño amplitude: the case of 2014 vs. 2015

  • Martin Puy
  • Jérôme Vialard
  • Matthieu Lengaigne
  • Eric Guilyardi
  • Pedro N. DiNezio
  • Aurore Voldoire
  • Magdalena Balmaseda
  • Gurvan Madec
  • Christophe Menkes
  • Michael J. Mcphaden
Article

Abstract

The weak El Niño of 2014 was preceded by anomalously high equatorial Pacific Warm Water Volume (WWV) and strong Westerly Wind Events (WWEs), which typically lead to record breaking El Nino, like in 1997 and 2015. Here, we use the CNRM–CM5 coupled model to investigate the causes for the stalled El Niño in 2014 and the necessary conditions for extreme El Niños. This model is ideally suited to study this problem because it simulates all the processes thought to be critical for the onset and development of El Niño. It captures El Niño preconditioning by WWV, the WWEs characteristics and their deterministic behaviour in response to warm pool displacements. Our main finding is, that despite their deterministic control, WWEs display a sufficiently strong stochastic component to explain the distinct evolutions of El Niño in 2014 and 2015. A 100-member ensemble simulation initialized with early-spring equatorial conditions analogous to those observed in 2014 and 2015 demonstrates that early-year elevated WWV and strong WWEs preclude the occurrence of a La Niña but lead to El Niños that span the weak (with few WWEs) to extreme (with many WWEs) range. Sensitivity experiments confirm that numerous/strong WWEs shift the El Niño distribution toward larger amplitudes, with a particular emphasis on summer/fall WWEs occurrence which result in a five-fold increase of the odds for an extreme El Niño. A long simulation further demonstrates that sustained WWEs throughout the year and anomalously high WWV are necessary conditions for extreme El Niño to develop. In contrast, we find no systematic influence of easterly wind events (EWEs) on the El Niño amplitude in our model. Our results demonstrate that the weak amplitude of El Niño in 2014 can be explained by WWEs stochastic variations without invoking EWEs or remote influences from outside the tropical Pacific and therefore its peak amplitude was inherently unpredictable at long lead-time.

Keywords

El Niño Westerly Wind Events Easterly wind events Predictability Extreme El Niño events El Niño predictors 

Notes

Acknowledgements

JV and ML acknowledge funding by Institut de Recherche pour le Développement (IRD). EG acknowledges funding by the Centre National de la Recherche Scientifique (CNRS) and from the National Centre for Atmospheric Science, a UK Natural Environment Research Council collaborative centre. This work was co-funded by a French Ministère de l’Education Nationale et de la Recherche grant, by a grant from the Agence Nationale de la Recherche MORDICUS, under the “Programme Environnement et Société” [Grant no. ANR-13-SENV-0002-02] and by the GOTHAM Belmont project (Grant no. ANR-15-JCLI-0004-01). This is PMEL contribution xxxx.

References

  1. Balmaseda MA, Mogensen K, Weaver AT (2013) Evaluation of the ECMWF ocean reanalysis system ORAS4. Q J R Meteorol Soc 139(674):1132–1161CrossRefGoogle Scholar
  2. Barnston AG, Tippett MK, L’Heureux ML, Li S, DeWitt DG (2012) Skill of real-time seasonal ENSO model predictions during 2002–11: is our capability increasing? Bull Am Meteorol Soc 93(5):631–651. doi: 10.1175/BAMS-D-11-00111.1 CrossRefGoogle Scholar
  3. Bellenger H, Guilyardi E, Leloup J, Lengaigne M, Vialard J (2014) ENSO representation in climate models: from CMIP3 to CMIP5. Clim Dyn 42(7–8):1999–2018. doi: 10.1007/s00382-013-1783-z CrossRefGoogle Scholar
  4. Bjerknes J (1966) A possible response of the atmospheric Hadley circulation to equatorial anomalies of ocean temperature. Tellus 18(4):820–829. doi: 10.3402/tellusa.v18i4.9712 CrossRefGoogle Scholar
  5. Blanke B, Delecluse P (1993) Variability of the tropical atlantic ocean simulated by a general circulation model with two different mixed-layer physics. J Phys Oceanogr 23(7):1363–1388CrossRefGoogle Scholar
  6. Bougeault P (1985) A simple parameterization of the large-scale effects of cumulus convection. Mon Weather Rev 113(12):2108–2121CrossRefGoogle Scholar
  7. Boulanger JP, Durand E, Duvel JP, Menkes C, Delecluse P, Imbard M, Lengaigne M, Madec G, Masson S (2001) Role of non-linear oceanic processes in the response to Westerly Wind Events: new implications for the 1997 El Niñoonset. Geophys Res Lett 28(8):1603–1606. doi: 10.1029/2000GL012364 CrossRefGoogle Scholar
  8. Boulanger JP, Menkes C, Lengaigne M (2004) Role of high- and low-frequency winds and wave reflection in the onset, growth and termination of the 1997–1998 El Niño. Clim Dyn 22(2–3):267–280. doi: 10.1007/s00382-003-0383-8 CrossRefGoogle Scholar
  9. Cai W, Borlace S, Lengaigne M, van Rensch P, Collins M, Vecchi G, Timmermann A, Santoso A, McPhaden MJ, Wu L, England MH, Wang G, Guilyardi E, Jin FF (2014) Increasing frequency of extreme El Niño events due to greenhouse warming. Nat Clim Change 5(2):1–6. doi: 10.1038/nclimate2100 Google Scholar
  10. Chang P, Zhang L, Saravanan R, Vimont DJ, Chiang JC, Ji L, Seidel H, Tippett MK (2007) Pacific meridional mode and El Niño—Southern Oscillation. Geophys Res Lett. doi: 10.1029/2007GL030302 Google Scholar
  11. Chiodi AM, Harrison D (2015) Equatorial pacific easterly wind surges and the onset of la nina events. J Clim 28(2):776–792CrossRefGoogle Scholar
  12. Eisenman I, Yu L, Tziperman E (2005) Westerly wind bursts: ENSO’s tail rather than the dog? J Clim 18(24):5224–5238. doi: 10.1175/JCLI3588.1 CrossRefGoogle Scholar
  13. Fedorov AV, Harper SL, Philander SG, Winter B, Wittenberg A (2003) How predictable is El Niño? Bull Am Meteorol Soc 84(7):911–919. doi: 10.1175/BAMS-84-7-911 CrossRefGoogle Scholar
  14. Fedorov AV, Hu S, Lengaigne M, Guilyardi E (2015) The impact of westerly wind bursts and ocean initial state on the development, and diversity of El Niño events. Clim Dyn 44(5–6):1381–1401CrossRefGoogle Scholar
  15. Gebbie G, Tziperman E (2009a) Incorporating a semi-stochastic model of ocean-modulated westerly wind bursts into an ENSO prediction model. Theoret Appl Climatol 97(1–2):65–73. doi: 10.1007/s00704-008-0069-6 CrossRefGoogle Scholar
  16. Gebbie G, Tziperman E (2009b) Predictability of SST-modulated westerly wind bursts. J Clim 22(14):3894–3909. doi: 10.1175/2009JCLI2516.1 CrossRefGoogle Scholar
  17. Gebbie G, Eisenman I, Wittenberg AT, Tziperman E (2007) Modulation of westerly wind bursts by sea surface temperature: a semistochastic feedback for ENSO. J Atmos Sci 64(9):3281–3295. doi: 10.1175/JAS4029.1 CrossRefGoogle Scholar
  18. Guilyardi E (2006) El Niño—mean state—seasonal cycle interactions in a multi-model ensemble. Clim Dyn 26:229–348CrossRefGoogle Scholar
  19. Guilyardi É, Madec G, Terray L (2001) The role of lateral ocean physics in the upper ocean thermal balance of a coupled ocean–atmosphere GCM. Clim Dyn 17(8):589–599CrossRefGoogle Scholar
  20. Harrison DE, Vecchi GA (1997) Westerly Wind Events in the tropical Pacific, 1986–1995. J Clim 10(12):3131–3156. doi: 10.1175/1520-0442(1997)010<3131:WWEITT>2.0.CO;2 CrossRefGoogle Scholar
  21. Hewitt H, Copsey D, Culverwell I, Harris C, Hill R, Keen A, McLaren A, Hunke E (2011) Design and implementation of the infrastructure of HADGEM3: the next-generation met office climate modelling system. Geosci Model Dev 4(2):223–253CrossRefGoogle Scholar
  22. Hu S, Fedorov AV (2016) Exceptionally strong easterly wind burst stalling El Niño of 2014. Proc Natl Acad Sci 113(8):201514,182. doi: 10.1073/pnas.1514182113 CrossRefGoogle Scholar
  23. Hu S, Fedorov AV (2017) The extreme El Niño of 2015–2016: the role of westerly and easterly wind bursts, and preconditioning by the failed 2014 event. Clim Dyn. doi: 10.1007/s00382-017-3531-2 Google Scholar
  24. Huang B, Banzon VF, Freeman E, Lawrimore J, Liu W, Peterson TC, Smith TM, Thorne PW, Woodruff SD, Zhang HM (2015) Extended reconstructed sea surface temperature version 4 (ERSST. v4). part I: Upgrades and intercomparisons. J Clim 28(3):911–930CrossRefGoogle Scholar
  25. Jin FF (1997) An equatorial ocean recharge paradigm for ENSO. Part II: A stripped-down coupled model. doi:10.1175/1520-0469(1997)054<0830:AEORPF>2.0.CO;2Google Scholar
  26. Jin FF, Lin L, Timmermann A, Zhao J (2007) Ensemble-mean dynamics of the ENSO recharge oscillator under state-dependent stochastic forcing. Geophys Res Lett 34(3):L03,807. doi: 10.1029/2006GL027372 CrossRefGoogle Scholar
  27. Kessler WS, McPhaden MJ, Weickmann KM (1995) Forcing of intraseasonal Kelvin waves in the equatorial Pacific. J Geophys Res 100(C6):10,613. doi: 10.1029/95JC00382 CrossRefGoogle Scholar
  28. Kleeman R, Moore AM (1997) A theory for the limitation of ENSO predictability due to stochastic atmospheric transients. J Atmos Sci 54(6):753–767CrossRefGoogle Scholar
  29. Kumar BP, Vialard J, Lengaigne M, Murty V, Mcphaden MJ, Cronin M, Pinsard F, Reddy KG (2013) Tropflux wind stresses over the tropical oceans: evaluation and comparison with other products. Clim Dyn 40(7–8):2049–2071CrossRefGoogle Scholar
  30. Larson SM, Kirtman BP (2015) An alternate approach to ensemble ENSO forecast spread: application to the 2014 forecast. Geophys Res Lett 42(21):9411–9415CrossRefGoogle Scholar
  31. Le Moigne P, Boone A, Calvet J, Decharme B, Faroux S, Gibelin A, Lebeaupin C, Mahfouf J, Martin E, Masson V, et al (2009) Surfex scientific documentation. Note de centre (CNRM/GMME), Météo-France, Toulouse, FranceGoogle Scholar
  32. Lengaigne M, Boulanger JP, Menkes C, Masson S, Madec G, Delecluse P (2002) Ocean response to the March 1997 westerly wind event. J Geophys Res Oceans. doi: 10.1029/2001JC000841 Google Scholar
  33. Lengaigne M, Boulanger JP, Menkes C, Madec G, Delecluse P, Guilyardi E, Slingo J (2003) The March 1997 Westerly Wind Event and the onset of the 1997/98 El Niño: understanding the role of the atmospheric response. J Clim 16(20):3330–3343. doi: 10.1175/1520-0442(2003)016<3330:TMWWEA>2.0.CO;2 CrossRefGoogle Scholar
  34. Lengaigne M, Boulanger JP, Menkes C, Delecluse P, Slingo J (2004a) Westerly Wind Events in the tropical Pacific and their influence on the coupled ocean–atmosphere system: a review. Earth’s Clim Ocean atmos Interact:49–69. doi: 10.1029/147GM03
  35. Lengaigne M, Guilyardi E, Boulanger JP, Menkes C, Delecluse P, Inness P, Cole J, Slingo J (2004b) Triggering of El Niño by Westerly Wind Events in a coupled general circulation model. Clim Dyn 23(6):601–620. doi: 10.1007/s00382-004-0457-2 CrossRefGoogle Scholar
  36. Lengaigne M, Menkes C, Aumont O, Gorgues T, Bopp L, André JM, Madec G (2007) Influence of the oceanic biology on the tropical Pacific climate in a coupled general circulation model. Clim Dyn 28(5):503–516CrossRefGoogle Scholar
  37. Levine AF, McPhaden MJ (2016) How the July 2014 easterly wind burst gave the 2015–2016 El Niño a head start. Geophys Res Lett 43(12):6503–6510CrossRefGoogle Scholar
  38. Lian T, Chen D, Tang Y, Wu Q (2014) Effects of westerly wind bursts on El Niño: a new perspective. Geophys Res Lett 41(10):3522–3527. doi: 10.1002/2014GL059989 CrossRefGoogle Scholar
  39. Lopez H, Kirtman BP (2014) WWBS, ENSO predictability, the spring barrier and extreme events. J Geophys Res Atmos. doi: 10.1002/2014JD021908 Google Scholar
  40. Lorenz E (1993) The essence of chaosuniversity of washington press. Seattle, WAGoogle Scholar
  41. Ludescher J, Gozolchiani A, Bogachev MI, Bunde A, Havlin S, Schellnhuber HJ (2014) Very early warning of next El Niño. Proc Nat Acad Sci 111(6):2064–2066Google Scholar
  42. McPhaden M (2015) Playing hide and seek with El Niño. Nat Clim Change 5(9):791–795. doi: 10.1038/nclimate2775 CrossRefGoogle Scholar
  43. McPhaden MJ, Yu X (1999) Equatorial waves and the 1997–98 el nino. Geophys Res Lett 26(19):2961–2964CrossRefGoogle Scholar
  44. McPhaden MJ, Zebiak SE, Glantz MH (2006a) ENSO as an integrating concept in earth science. Science (New York, NY) 314(5806):1740–1745. doi: 10.1126/science.1132588 CrossRefGoogle Scholar
  45. McPhaden MJ, Zhang X, Hendon HH, Wheeler MC (2006b) Large scale dynamics and MJO forcing of ENSO variability. Geophys Res Lett 33(16):L16,702. doi: 10.1029/2006GL026786 CrossRefGoogle Scholar
  46. Meinen CS, McPhaden MJ (2000) Observations of warm water volume changes in the equatorial Pacific and their relationship to El Nino and La Nina. J Clim 13(20):3551–3559. doi: 10.1175/1520-0442(2000)013<3551:OOWWVC>2.0.CO;2 CrossRefGoogle Scholar
  47. Menkes CE, Lengaigne M, Vialard J, Puy M, Marchesiello P, Cravatte S, Cambon G (2014) About the role of Westerly Wind Events in the possible development of an El Niño in 2014. Geophys Res Lett 41(18):6476–6483. doi: 10.1002/2014GL061186 CrossRefGoogle Scholar
  48. Min Q, Su J, Zhang R, Rong X (2015) What hindered the El Niño pattern in 2014? Geophys Res Lett 42(16):6762–6770CrossRefGoogle Scholar
  49. Molteni F, Buizza R, Palmer TN, Petroliagis T (1996) The ECMWF ensemble prediction system: methodology and validation. Q J R Meteorol Soc 122(529):73–119CrossRefGoogle Scholar
  50. Molteni F, Stockdale T, Balmaseda MA, Balsamo G, Buizza R, Ferranti L, Magnusson L, Mogensen K, Palmer T, Vitart F (2011) The new ECMWF seasonal forecast system (system 4)Google Scholar
  51. Paulson CA, Simpson JJ (1977) Irradiance measurements in the upper ocean. J Phys Oceanogr 7(6):952–956CrossRefGoogle Scholar
  52. Penland C, Sardeshmukh PD (1995) The optimal growth of tropical sea surface temperature anomalies. J Clim 8(8):1999–2024. doi: 10.1175/1520-0442(1995)008<1999:TOGOTS>2.0.CO;2 CrossRefGoogle Scholar
  53. Puy M (2016) L’influence des coups de vent d’ouest dans le pacifique équatorial sur el niño: origines atmosphériques et impacts océaniques. PhD Thesis, Paris 6Google Scholar
  54. Puy M, Vialard J, Lengaigne M, Guilyardi E, Madec G (2015) Modulation of equatorial pacific wind events and their ocean response by atmospheric and oceanic large scale conditions Why are equatorial pacific wind events important to 1(July)Google Scholar
  55. Puy M, Vialard J, Lengaigne M, Guilyardi E, Voldoire A, Madec G (2016) Modulation of equatorial Pacific sea surface temperature response to Westerly Wind Events by the oceanic background state. Clim Dyn:1–25Google Scholar
  56. Rayner N, Parker DE, Horton E, Folland C, Alexander L, Rowell D, Kent E, Kaplan A (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res Atmos. doi: 10.1029/2002JD002670 Google Scholar
  57. Reynolds RW, Rayner NA, Smith TM, Stokes DC, Wang W (2002) An improved in situ and satellite sst analysis for climate. J Clim 15(13):1609–1625CrossRefGoogle Scholar
  58. Roullet G, Madec G (2000) Salt conservation, free surface, and varying levels: a new formulation for ocean general circulation models. J Geophys Res Oceans 105(C10):23,927–23,942CrossRefGoogle Scholar
  59. Seiki A, Takayabu YN (2007a) Westerly wind bursts and their relationship with intraseasonal variations and ENSO. Part II: energetics over the western and central Pacific. Mon Weather Rev 135(10):3346–3361. doi: 10.1175/MWR3503.1 CrossRefGoogle Scholar
  60. Seiki A, Takayabu YN (2007b) Westerly wind bursts and their relationship with intraseasonal variations and ENSO. Part II: energetics over the western and central Pacific. Mon Weather Rev 135(10):3346–3361. doi: 10.1175/MWR3503.1 CrossRefGoogle Scholar
  61. Smith R (1990) A scheme for predicting layer clouds and their water content in a general circulation model. Q J R Meteorol Soc 116(492):435–460CrossRefGoogle Scholar
  62. Stockdale TN, Anderson DL, Alves JOS, Balmaseda MA (1998) Global seasonal rainfall forecasts using a coupled ocean–atmosphere model. Nature 392(6674):370–373CrossRefGoogle Scholar
  63. Tollefson J (2014) El niño tests forecasters. Nature 508(7494):20CrossRefGoogle Scholar
  64. Valcke S, Caubel A, Declat D, Terray L (2003) Oasis3 ocean atmosphere sea ice soil users guide. Prisim project report 2Google Scholar
  65. Vecchi GA, Harrison D (2000) Tropical pacific sea surface temperature anomalies, El Niño, and equatorial Westerly Wind Events. J Clim 13(11):1814–1830CrossRefGoogle Scholar
  66. Vitart F, Alonso Balmaseda M, Ferranti L, Anderson D (2003) Westerly Wind Events and the 1997/98 El Niño event in the ecmwf seasonal forecasting system: a case study. J Clim 16(19):3153–3170CrossRefGoogle Scholar
  67. Voldoire A, Sanchez-Gomez E, y Mélia DS, Decharme B, Cassou C, Sénési S, Valcke S, Beau I, Alias A, Chevallier M et al (2013) The CNRM–CM5 1 global climate model: description and basic evaluation. Clim Dyn 40(9–10):2091–2121CrossRefGoogle Scholar
  68. Weisheimer A, Corti S, Palmer T, Vitart F (2014) Addressing model error through atmospheric stochastic physical parametrizations: impact on the coupled ECMWF seasonal forecasting system. Philos Trans R Soc A 372(2018):20130,290CrossRefGoogle Scholar
  69. Yu L, Rienecker MM (1999) Mechanisms for the Indian ocean warming during the 1997–98 el nino. Geophys Res Lett 26(6):735–738CrossRefGoogle Scholar
  70. Zhang T, Sun DZ (2014) Enso asymmetry in CMIP5 models. J Clim 27(11):4070–4093CrossRefGoogle Scholar
  71. Zhu J, Kumar A, Huang B, Balmaseda MA, Hu ZZ, Marx L, Kinter III JL (2016) The role of off-equatorial surface temperature anomalies in the 2014 el niño prediction. Sci Rep:6Google Scholar

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© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.LOCEAN/IPSL, Sorbonne Universités/UPMC-CNRS-IRD-MNHNParisFrance
  2. 2.Indo-French Cell for Water Sciences, IISc-NIO-IITM-IRD Joint International Laboratory, NIOGoaIndia
  3. 3.NCAS-ClimateUniversity of ReadingReadingUK
  4. 4.Institute for Geophysics, Jackson School of GeosciencesUniversity of Texas at AustinAustinUSA
  5. 5.CNRM, Météo France/UMR 3589ToulouseFrance
  6. 6.European Centre of Medium Range Weather ForecastsReadingUK
  7. 7.Centre IRDNouméaNew Caledonia
  8. 8.NOAA PMELSeattleUSA

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