Abstract
Anomalous zonal wind stress in the central-to-western Pacific plays a crucial role in ENSO evolution by exciting oceanic waves that propagate eastward or westward. However, compared to its intensity, the importance of its spatial pattern is an overlooked aspect in ENSO theory. Using a linear regression model and numerical simulations with the Zebiak-Cane model, we here show that the zonal wind stress anomaly pattern significantly affects the development of El Niño and its type. Specifically, if the westerly wind stress is closer to the western Pacific (WP), the excited upwelling Rossby waves will take less time to reach the WP coast before they are reflected as Kelvin waves. This significantly weakens sea surface temperature anomalies in the eastern Pacific region since less time is provided for their amplification due to positive feedbacks. This causes the anomalous warming center to be closer to the central Pacific (CP) region, leading to a CP-type El Niño.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
The GODAS reanalysis is obtained at https://www.psl.noaa.gov//data/gridded/data.godas.html, the GPCP data is at https://psl.noaa.gov/data/gridded/data.gpcp.html.
References
An S-I, Kug J-S, Ham Y-G et al (2008) Successive modulation of ENSO to the future greenhouse warming. J Clim 21(1):3–21. https://doi.org/10.1175/2007JCLI1500.1
Battisti DS (1988) Dynamics and thermodynamics of a warming event in a coupled tropical atmosphere–ocean model. J Atmos Sci 45(20):2889–2919. https://doi.org/10.1175/1520-0469(1988)045%3C2889:DATOAW%3E2.0.CO;2
Behringer D, Xue Y (2004) Evaluation of the global ocean data assimilation system at NCEP: The Pacific Ocean. Proceedings eighth symposium on integrated observing and assimilation systems for atmosphere, oceans, and land surface [Dataset]. Retrieved from https://www.researchgate.net/publication/2288
Bjerknes J (1969) Atmospheric teleconnections from the equatorial Pacific. Mon Weather Rev 97(3):163–172. https://doi.org/10.1175/1520-0493(1969)097%3C0163:ATFTEP%3E2.3.CO;2
Cai W-J et al (2019) Pantropical climate interactions. Science 363:944. https://doi.org/10.1126/science.aav4236
Capotondi A et al (2015) Understanding ENSO diversity. Bull Am Meteorological Soc 96:921–938. https://doi.org/10.1175/BAMS-D-13-00117.1
Chen N, Fang X (2023) A simple Multiscale Intermediate coupled Stochastic Model for El Niño Diversity and Complexity. J Adv Model Earth Syst 15(4). https://doi.org/10.1029/2022MS003469
Chen N, Fang X, Yu J-Y (2022) A multiscale model for El Niño complexity. Npj Clim Atmospheric Sci 5:16. https://doi.org/10.1038/s41612-022-00241-x
Clarke AJ, van Gorder S (2001) ENSO prediction using an ENSO trigger and a proxy for western equatorial pacific warm Pool Movement. Geophys Res Lett 28(4):579–582. https://doi.org/10.1029/2000GL012201
Fang X, Chen N (2023) Quantifying the predictability of ENSO complexity using a statistically accurate multiscale stochastic model and information theory. J Clim 36(8):2681–2702. https://doi.org/10.1175/JCLI-D-22-0151.1
Fang X, Mu M (2018a) Both air-sea components are crucial for El Niño forecast from boreal spring. Sci Rep 8(1):1–8. https://doi.org/10.1038/s41598-018-28964-z
Fang X, Mu M (2018b) A three-region conceptual model for central Pacific El Niño including zonal advective feedback. J Clim 31:4965–4979. https://doi.org/10.1175/JCLI-D-17-0633.1
Fang X, Zheng F (2021) Effect of the air-sea coupled system change on the ENSO evolution from boreal spring. Clim Dyn 57:109–120. https://doi.org/10.1007/s00382-021-05697-w
Fang X, Zheng F, Zhu J (2015) The cloud-radiative effect when simulating strength asymmetry in two types of El Niño events using CMIP5 models. J Geophys Research: Oceans 120(6):4357–4369. https://doi.org/10.1002/2014JC010683
Fang X, Dijkstra H, Wieners C, Guardamagna F (2024) A nonlinear full-field conceptual model for ENSO diversity. J Clim. https://doi.org/10.1175/JCLI-D-23-0382.1
Geng L, Jin F-F (2022) ENSO diversity simulated in a revised Cane-Zebiak model. Front Earth Sci 10:899323. https://doi.org/10.3389/feart.2022.899323
Geng L, Jin F-F (2023) Insights into ENSO Diversity from an intermediate coupled model. Part II: role of Nonlinear Dynamics and Stochastic forcing. J Clim 36:7527–7547. https://doi.org/10.1175/JCLI-D-23-0044.1
Geng T, Cai W, Wu L (2020) Two types of ENSO varying in tandem facilitated by nonlinear atmospheric convection. Geophys Res Lett 47(15). https://doi.org/10.1029/2020GL088784
Ham Y-G, Kim J-H, Luo J-J (2019) Deep learning for multi-year ENSO forecasts. Nature 573:568–572. https://doi.org/10.1038/s41586-019-1559-7
Harrison DE, Giese BS (1988) Remote westerly wind forcing of the eastern equatorial Pacific; some model results. Geophys Res Lett 15(8):804–807. https://doi.org/10.1029/GL015i008p00804
Jin F-F (1997) An equatorial ocean recharge paradigm for ENSO. Part I: conceptual model. J Atmos Sci 54(7):811–829. https://doi.org/10.1175/1520-0469(1997)054%3C0811:AEORPF%3E2.0.CO;2
Kao H-Y, Yu J-Y (2009) Contrasting eastern-pacific and central-pacific types of ENSO. J Clim 22(3):615–632. https://doi.org/10.1175/2008JCLI2309.1
Klein SA, Soden BJ, Lau N-C (1999) Remote sea surface temperature variations during ENSO: evidence for a tropical atmospheric bridge. J Clim 12:917–932. https://doi.org/10.1175/1520-0442(1999)012%3C0917:RSSTVD%3E2.0.CO;2
Kug J-S, Kang I-S, An S-I (2003) Symmetric and antisymmetric mass exchanges between the equatorial and off-equatorial Pacific associated with ENSO. J Geophys Research: Oceans 108(C8). https://doi.org/10.1029/2002JC001671
Kug JS, Jin F-F, An SI (2009) Two types of El Niño events: Cold tongue El Niño and warm pool El Niño. J Clim 22(6):1499–1515. https://doi.org/10.1175/2008JCLI2624.1
Lian T, Tang Y, Zhou L et al (2018) Westerly wind bursts simulated in CAM4 and CCSM4. Clim Dyn 50:1353–1371. https://doi.org/10.1007/s00382-017-3689-7
McPhaden MJ (2003) Tropical Pacific Ocean heat content variations and ENSO persistence barriers. Geophys Res Lett 30(9). https://doi.org/10.1029/2003GL016872
McPhaden MJ, Zebiak SE, Glantz MH (2006) ENSO as an integrating concept in Earth science. Science 314:1740–1745. https://doi.org/10.1126/science.1132588
Meinen CS, McPhaden MJ (2000) Observations of warm water volume changes in the equatorial Pacific and their relationship to El Niño and La Niña. J Clim 13(20):3551–3559. https://doi.org/10.1175/1520-0442(2000)013%3C3551:OOWWVC%3E2.0.CO;2
Pang D, Fang X, Wang L (2023) Importance of realistic zonal currents in depicting the evolution of tropical central Pacific sea surface temperature. Environ Res Lett 18(12):124031. https://doi.org/10.1088/1748-9326/ad0b21
Philander S (1983) El Niño Southern Oscillation phenomena. Nature 302(5906):295–301. https://doi.org/10.1038/302295a0
Ren HL, Zuo J, Deng Y (2019) Statistical predictability of Niño indices for two types of ENSO. Clim Dyn 52:5361–5382. https://doi.org/10.1007/s00382-018-4453-3
Ropelewski CF, Halpert MS (1987) Global and regional scale precipitation patterns associated with the El Niño/Southern Oscillation. Mon Weather Rev 115:1606–1626. https://doi.org/10.1175/1520-0493(1987)115%3C1606:GARSPP%3E2.0.CO;2
Ruiz JE, Cordery I, Sharma A (2005) Integrating ocean subsurface temperatures in statistical ENSO forecasts. J Clim 18(17):3571–3586. https://doi.org/10.1175/JCLI3477.1
Schopf PS, Suarez MJ (1988) Vacillations in a coupled ocean–atmosphere model. J Atmos Sci 45:549–566. https://doi.org/10.1175/1520-0469(1988)045%3C0549:VIACOM%3E2.0.CO;2
Tang Y et al (2018) Progress in ENSO prediction and predictability study. Natl Sci Rev 5:826–839. https://doi.org/10.1093/nsr/nwy105
Timmermann A et al (2018) El Niño–Southern Oscillation complexity. Nature 559:535–545. https://doi.org/10.1038/s41586-018-0252-6
Wang C (2018) A review of ENSO theories. Natl Sci Rev 5(6):813–825. https://doi.org/10.1093/nsr/nwy104
Wang J, Zhang S, Jiang H, Yuan D (2022) Effects of 2019 subsurface Indian Ocean initialization on the forecast of the 2020/2021 La Niña event. Clim Dyn 1–17. https://doi.org/10.1007/s00382-022-06442-7
Zebiak SE, Cane MA (1987) A model El Niño–Southern Oscillation. Mon Weather Rev 115(10):2262–2278. https://doi.org/10.1175/1520-0493(1987)115%3C2262:ameno%3E2.0.co;2
Zhang R, Min Q, Su J (2017) Impact of El Niño on atmospheric circulations over East Asia and rainfall in China: role of the anomalous western North Pacific anticyclone. Sci China Earth Sci 60:1124–1132. https://doi.org/10.1007/s11430-016-9026-x
Zheng F, Fang X, Yu J-Y, Zhu J (2014) Asymmetry of the bjerknes positive feedback between the two types of El Niño. Geophys Res Lett 41(21):7651–7657. https://doi.org/10.1002/2014GL062125
Funding
This work of Xianghui Fang was carried out at Utrecht University, the Netherlands and supported by the National Natural Science Foundation of China (Grant Nos. 42288101 and 42192564), Ministry of Science and Technology of the People’s Republic of China (Grant No. 2020YFA0608802), Guangdong Major Project of Basic and Applied Basic Research (Grant No. 2020B0301030004), and the scholarship provided by the China Scholarship Council (CSC, Grant No. 202106105010). The work of Francesco Guardamagna, Claudia Wieners and Henk Dijkstra was supported by the Netherlands Organization for Scientific Research (NWO) under grant OCENW.M20.277.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Fang, X., Dijkstra, H., Wieners, C. et al. An overlooked aspect concerning the effect of the spatial pattern of zonal wind stress anomalies on El Niño evolution and diversity. Clim Dyn (2024). https://doi.org/10.1007/s00382-024-07264-5
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s00382-024-07264-5