Science China Earth Sciences

, Volume 60, Issue 9, pp 1601–1613 | Cite as

Processes involved in the second-year warming of the 2015 El Niño event as derived from an intermediate ocean model

Research Paper Special Topic: Challenges and uncertainties of ENSO prediction: Enlightenments from El Niño event of 2015–2016

Abstract

The tropical Pacific experienced a sustained warm sea surface condition that started in 2014 and a very strong El Niño event in 2015. One striking feature of this event was the horseshoe-like pattern of positive subsurface thermal anomalies that was sustained in the western-central equatorial Pacific throughout 2014–2015. Observational data and an intermediate ocean model are used to describe the sea surface temperature (SST) evolution during 2014–2015. Emphasis is placed on the processes involved in the 2015 El Niño event and their relationships with SST anomalies, including remote effects associated with the propagation and reflection of oceanic equatorial waves (as indicated in sea level (SL) signals) at the boundaries and local effects of the positive subsurface thermal anomalies. It is demonstrated that the positive subsurface thermal anomaly pattern that was sustained throughout 2014–2015 played an important role in maintaining warm SST anomalies in the equatorial Pacific. Further analyses of the SST budget revealed the dominant processes contributing to SST anomalies during 2014–2015. These analyses provide an improved understanding of the extent to which processes associated with the 2015 El Niño event are consistent with current El Niño and Southern Oscillation theories.

Keywords

2015 El Niño event Intermediate ocean model Process analyses SST budget 

References

  1. Bjerknes J. 1969. Atmospheric teleconnections from the equatorial pacific. Mon Weather Rev, 97: 163–172CrossRefGoogle Scholar
  2. Chen D, Lian T, Fu C, Cane M A, Tang Y, Murtugudde R, Song X, Wu Q, Zhou L. 2015. Strong influence of westerly wind bursts on El Niño diversity. Nat Geosci, 8: 339–345CrossRefGoogle Scholar
  3. Gao C, Zhang R H. 2017. The roles of atmospheric wind and entrained water temperature (Te) in the second-year cooling of the 2010–12 La Niña event. Clim Dyn, 48: 597–617CrossRefGoogle Scholar
  4. Hu S, Fedorov A V. 2016. Exceptionally strong easterly wind burst stalling El Niño of 2014. Proc Natl Acad Sci USA, 113: 2005–2010CrossRefGoogle Scholar
  5. Jin F F, An S I. 1999. Thermocline and zonal advective feedbacks within the Equatorial ocean recharge oscillator model for ENSO. Geophys Res Lett, 26: 2989–2992CrossRefGoogle Scholar
  6. Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y, Leetmaa A, Reynolds R, Chelliah M, Ebisuzaki W, Higgins W, Janowiak J, Mo K C, Ropelewski C, Wang J, Jenne R, Joseph D. 1996. The NCEP/NCAR 40-year reanalysis project. Bull Amer Meteorol Soc, 77: 437–471CrossRefGoogle Scholar
  7. Keenlyside N, Kleeman R. 2002. Annual cycle of equatorial zonal currents in the Pacific. J Geophys Res, 107: 3093CrossRefGoogle Scholar
  8. Levine A F Z, McPhaden M J. 2016. How the July 2014 easterly wind burst gave the 2015-2016 El Niño a head start. Geophys Res Lett, 43: 6503–6510CrossRefGoogle Scholar
  9. Liu B Q, Li J Y, Mao J Y, Ren R C, Liu Y M. 2015. Possible mechanism for the development and suspending of El Niño event in 2014 (in Chinese). Chin Sci Bull, 60: 2136CrossRefGoogle Scholar
  10. McCreary J P. 1981. A linear stratified ocean model of the equatorial undercurrent. Philos Trans R Soc A-Math Phys Eng Sci, 298: 603–635CrossRefGoogle Scholar
  11. McPhaden M J. 2015. Playing hide and seek with El Niño. Nat Clim Change, 5: 791–795CrossRefGoogle Scholar
  12. Min Q, Su J, Zhang R, Rong X. 2015. What hindered the El Niño pattern in 2014? Geophys Res Lett, 42: 6762–6770CrossRefGoogle Scholar
  13. Reynolds R W, Smith T M. 1994. Improved global sea surface temperature analyses using optimum interpolation. J Clim, 7: 929–948CrossRefGoogle Scholar
  14. Zebiak S E, Cane M A. 1987. A model El Ni&ntilde-southern oscillation. Mon Weather Rev, 115: 2262–2278CrossRefGoogle Scholar
  15. Zhang C, Li S. 2015. Why is the El Niño event during the 2014 winter not a strong one? (in Chinese). Chin Sci Bull, 60: 1941–1951CrossRefGoogle Scholar
  16. Zhang R H, Zebiak S E, Kleeman R, Keenlyside N. 2003. A new intermediate coupled model for El Niño simulation and prediction. Geophys Res Lett, 30: 2012CrossRefGoogle Scholar
  17. Zhang R H, Kleeman R, Zebiak S E, Keenlyside N, Raynaud S. 2005. An empirical parameterization of subsurface entrainment temperature for improved SST anomaly simulations in an intermediate ocean model. J Clim, 18: 350–371CrossRefGoogle Scholar
  18. Zhang R H, Zheng F, Zhu J, Wang Z. 2013. A successful real-time forecast of the 2010–11 La Niña event. Sci Rep, 3: 1108CrossRefGoogle Scholar
  19. Zhang R H, Gao C. 2016a. Role of subsurface entrainment temperature (Te) in the onset of El Niño events, as represented in an intermediate coupled model. Clim Dyn, 46: 1417–1435CrossRefGoogle Scholar
  20. Zhang R H, Gao C. 2016b. The IOCAS intermediate coupled model (IOCAS ICM) and its real-time predictions of the 2015–2016 El Niño event. Sci Bull, 61: 1061–1070CrossRefGoogle Scholar
  21. Zhu J, Kumar A, Huang B, 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: 19677CrossRefGoogle Scholar

Copyright information

© Science China Press and Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Key Laboratory of Ocean Circulation and Waves, Institute of OceanologyChinese Academy of SciencesQingdaoChina
  2. 2.Laboratory for Ocean and Climate DynamicsQingdao National Laboratory for Marine Science and TechnologyQingdaoChina
  3. 3.University of Chinese Academy of SciencesBeijingChina

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