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Observations of Warm Water Volume Changes in the Equatorial Pacific and Their Relationship to El Niño and La Niña

C. S. Meinen1 and M. J. McPhaden2

1Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, Washington
2Pacific Marine Environmental Laboratory, National Oceanic and Atmospheric Administration, Seattle, Washington, 98115

Journal of Climate, 13(20), 3551–3559 (2000).
Copyright ©2000 by the American Meteorological Society. Further electronic distribution is not allowed.

5. Summary

This study utilized gridded datasets of subsurface temperature, SST, and zonal winds to test how well the "recharge oscillator," proposed by J97, agreed with observations over the time interval of 1980-99. The variation in the depth of the 20°C isotherm, Z20, was observed to consist of two main modes, which can be characterized as an "east-west tilting" mode and an "equatorial discharge-recharge" mode. The Niño-3 SST, zonal winds, and the tilting mode are all nearly in phase with one another while the recharge mode leads the tilting mode, zonal winds, and SST by about 7 months on average. The character of the ENSO cycle observed during 1980-99, especially the warm events with large WWV expressions in 1982-83, 1986-87, and 1997-98, is consistent with the recharge oscillator, as postulated in J97.

We found that the amplitudes of WWV anomalies are linearly related to the amplitudes of the Niño-3 SST anomalies, with larger anomalies in WWV preceding larger anomalies in SST. However, for a given magnitude of WWV anomaly, positive values are associated with larger-magnitude SST anomalies than negative values. This asymmetry implies differences in the relative importance of physical processes controlling SST during El Niño and La Niña events. It may be, for example, that air-sea fluxes, which are a negative feedback on SST anomaly growth in the equatorial cold tongue (Wang and McPhaden 2000), are more effective at heating the ocean during cold phases of ENSO than they are at cooling the ocean during warm phases of ENSO. Alternately, the ability of upwelling and vertical mixing to cool the surface may saturate at some threshold beyond which further thermocline shoaling does not lead to further SST cooling. In any case, more study is needed to determine the limiting mechanisms for SST anomalies during La Niña versus El Niño events.

Our study confirms that warm water volume changes in the western Pacific (Wyrtki 1975a) and zonally averaged along the equator (Wyrtki 1985; Cane et al. 1986) are useful predictors of ENSO timescale SST variations. The physical mechanisms responsible for these warm water changes involve wind-forced equatorial wave processes, as described by the delayed oscillator. Clearly, ocean models used for predicting ENSO variations should reproduce these changes. Furthermore, because measurements of upper-ocean thermal structure are now routinely available from the TAO array and from regular expendable bathythermograph (XBT) sections, models that assimilate these data can expect to see improvements in forecast skill for ENSO events (e.g., Ji and Leetmaa 1997). Changes in western Pacific warm water volume (VW) precede basinwide WWV changes, however they are less well correlated with subsequent Niño-3 SSTs. This implies a reduction in predictability at longer lead times, which reflects the irregularity of the ENSO cycle.

Description of the actual pathways by which the warm water moves between the Tropics and the higher latitudes are beyond the scope of this paper. A subsequent article will present a WWV balance for the equatorial Pacific and will discuss the mechanisms for WWV changes during 1993-99, when observations are the most plentiful (Meinen and McPhaden 1999, manuscript submitted to J. Phys. Oceanogr.). This study has provided the first step, however, by quantifying how the volume of warm water greater than 20°C changes on interannual timescales.

Acknowledgments. The authors would like to thank Dr. Neville Smith of the Australian BMRC for providing the subsurface temperature dataset. They would also like to thank Dr. James O’Brien and his group at The Florida State University for the wind dataset and Dr. Richard Reynolds at NCEP for the SST dataset. Funding for this project was provided by NOAA’s Office of Global Programs and Environmental Research Laboratories. This paper is PMEL contribution number 2119. This publication was also supported by the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement #NA67RJO155, contribution number 713.


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