A Model El Niñ–Southern Oscillation
1987/10/01 by Stephen E. Zebiak, Mark A. Cane · 1,693 citations
Chemistry · Earth and Planetary Sciences · Environmental Science · #Amplitude #Annual cycle #Atmosphere (unit) #Atmospheric sciences #Chemistry #Climate variability and models #Climatology #Coupling (piping) #Environmental science #Forcing (mathematics) #Geology #Materials science #Meteorological Phenomena and Simulations #Oceanographic and Atmospheric Processes #Oscillation (cell signaling) #Physics #Sea surface temperature #Thermodynamics
paper · pdf · doi:10.1175/1520-0493(1987)115<2262:ameno>2.0.co;2
published in Monthly Weather Review 115(10), 2262-2278 (American Meteorological Society)
openalex publication_date 1987/10/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/02
Abstract
A coupled atmosphere-ocean model is developed and used to study the ENSO (El Niñ/Southern Oscillation) phenomenon. With no anomalous external forcing, the coupled model reproduces certain key features of the observed phenomenon. including the recurrence of warm events at irregular intervals with a preference for three to four years. It is shown that the mean sea surface temperature, wind and ocean current fields determine the characteristic spatial structure of ENSO anomalies. The tendency for phase-locking of anomalies is explained in terms of a variation in coupling strength associated with the annual cycle in the mean fields. Sensitivity studies reveal that both the amplitude and the time of scale of the oscillation are sensitive to several parameters that affect the strength of the atmosphere–ocean coupling. Stronger coupling implies larger oscillations with a longer time scale. A critical element of the model oscilliation is the variability in the equatorial heat content of the upper ocean. Equatorial heat content increases prior to warm events and decreases sharply during the events. A theory for this variability and the associated transitions between the non-El Niño and El Niño states is presented. Implications of the model results for the prediction of El Niño events are discussed.
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