Abstract

Abstract Accurately capturing the observed mean period of ENSO in general circulation models (GCMs) is often challenging, and it is therefore useful to understand which parameters and processes affect this period. A computationally efficient simulation-based approach is used to extract both the dominant eigenvalues and corresponding eigenvectors of the linearized model from the Zebiak–Cane intermediate-complexity model of ENSO without having to directly construct the linearization. The sensitivity of the period to a variety of parameters is examined, including atmosphere–ocean coupling, atmospheric heating parameterization, thermocline depth zonal profile, western boundary reflection coefficient, atmospheric and ocean wave speeds or Rossby radii of deformation, ocean decay time, and the strength of the annual cycle. In addition to the sensitivity information, the spatial structures of the main fields (SST, thermocline thickness, and more) that are involved in period changes are obtained to aid in the physical interpretation of the sensitivities. There are three main time lags that together compose one-half of a model ENSO period: the Rossby-plus-Kelvin wave propagation time for a wind-caused central Pacific disturbance to propagate to the western ocean and back, SST dynamics that determine the lag between eastern ocean thermocline anomalies and eastern ocean SST anomalies, and the “accumulation” lag of integrating a sufficient delayed wave signal arriving from the western ocean to cancel the eastern ocean anomalies. For any of the parameter changes considered, the eigenvector changes show that the largest contributor to the period change is from changes to the last of these three mechanisms. Physical mechanisms that affect this accumulation delay are discussed, and the case is made that any significant change to ENSO’s period is in turn likely to involve changes to this delay.

Highlights

  • ENSO’s period varies between 2 and 7 yr, with the average being quite robust around 4 yr

  • The observed irregular periodicity has been explained either as the result of self-sustained, possibly chaotic behavior (Jin et al 1994; Tziperman et al 1994, 1995), such as the output of a damped stable system driven by weather “noise” external to the ENSO dynamics excited through nonnormal growth (Kleeman and Moore 1997; Penland and Sardeshmukh 1995; Burgers 1999; Philander and Fedorov 2003; Wang et al 1999; Thompson and Battisti 2000), or as a combination of the two (Kirtman and Schopf 1998)

  • We find that changes to the period of ENSO can result from changes to one of three possible delays that affect it: the wave propagation delay (Suarez and Schopf 1988; Battisti 1988), the accumulation delay (Cane et al 1990; Kirtman 1997), or the SST dynamics delay in the eastern Pacific (Jin and Neelin 1993a,b; Neelin and Jin 1993)

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Summary

Introduction

ENSO’s period varies between 2 and 7 yr, with the average being quite robust around 4 yr. The observed irregular periodicity has been explained either as the result of self-sustained, possibly chaotic behavior (Jin et al 1994; Tziperman et al 1994, 1995), such as the output of a damped stable system driven by weather “noise” external to the ENSO dynamics excited through nonnormal growth (Kleeman and Moore 1997; Penland and Sardeshmukh 1995; Burgers 1999; Philander and Fedorov 2003; Wang et al 1999; Thompson and Battisti 2000), or as a combination of the two (Kirtman and Schopf 1998). In the self-sustained or chaotic cases, the behavior of the eigenvalues is still useful in describing the output, nonlinear effects will certainly be relevant in this case and can affect the period (Münnich et al 1991; Jin 1997a,b; Eccles and Tziperman 2004)

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