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Forcing of intraseasonal Kelvin waves in the equatorial Pacific

William S. Kessler and Michael J. McPhaden

Pacific Marine Environmental Laboratory, NOAA, Seattle, Washington

Klaus M. Weickmann

Climate Diagnostics Center, NOAA, Boulder, Colorado

J. Geophys. Res., 100(C6), 10,613-10,631 (1995)
This paper is not subject to U.S. copyright. Published in 1995 by the American Geophysical Union.

5. Summary

We have used 10-year time series of SST, 20°C depth, and zonal winds measured by moored buoys across the equatorial Pacific to define the intraseasonal Kelvin waves and compare them to an index of tropical convection. Previous studies have described and diagnosed the oceanic Kelvin waves; here we establish that the low-frequency modulation of the intraseasonal energy in the ocean coincides with that of the Madden-Julian Oscillation, and hence this signal should be seen as part of a planetary-scale phenomenon, and not internal to the Pacific. During the boreal fall/winter season, typically two to four intraseasonal convection events propagate into the western Pacific from their generation region over the central Indian Ocean. Westerly winds associated with the convection generate downwelling first-baroclinic-mode Kelvin waves that efficiently carry the signal across the basin; this composes a substantial fraction of eastern Pacific thermocline depth variability. During El Niņo onset years (1986 and 1991 in this study), the convection extends further east (in association with the warmest SST), which gives more fetch to the westerlies and thus unusually intense downwelling Kelvin events.

A simple model is formulated that shows that a coupled feedback is possible in which intraseasonal wind forcing alone results in a slow, steplike eastward progression of high SST and westerly wind anomalies across much of the Pacific in a manner not unlike the onset stage of El Niņo. The model is highly idealized, isolating a single process: the feedback between intraseasonal Kelvin wave zonal advection of SST interacting with eastward penetration of convection over the Pacific. The model solution implies that low-frequency modulation of the intraseasonal variability could lead to low-frequency climate fluctuations in the Pacific. Some of this modulation can presumably be due to changes in the Indian Ocean and south Asian monsoon circulation systems, so the intraseasonal band may be a "window" through which the Pacific reacts to signals originating outside the basin, and this may be part of the process that occurs during the onset stage of El Niņo. We note, however, that intraseasonal equatorial Kelvin waves are a ubiquitous feature of the equatorial Pacific, evident during non-El Niņo years as well. Thus the occurrence of these waves alone is not a sufficient condition for the onset of El Niņo. A further application of the simple model suggests that the discrepancy between the typical 30- to 50-day periods of the most energetic atmospheric intraseasonal variability and the 60- to 75-day periods of the corresponding signal in the ocean may occur because of the correspondence between the relatively short periods of the intraseasonal wind and the time for a Kelvin wave to cross the wind patches.

It is presently a subject of controversy as to whether high-frequency variability such as the intraseasonal band is important to resolve, or whether it is enough to simply work with low-frequency averages, when the desired result is understanding of interannual variability [e.g., Latif et al., 1988; Zebiak, 1989; Webster and Lukas, 1992]. Our results suggest an intimate connection between large-amplitude intraseasonal waves and the onset of El Niņo and raise the possibility that the waves themselves provide a feedback to the atmosphere that could be crucial to the spreading of the coupled anomalies across the Pacific.

Acknowledgments. The existence of the TOGA/TAO buoy array is due in large part to the vision and perseverance of the late Stanley P. Hayes. Without his efforts this study would not have been possible. We thank Nick Graham and Bob Weisberg for thorough reviews of an earlier version of the manuscript and many helpful comments and suggestions. We thank Eric Johnson for the use of his computer program to find the complex EOFs shown in Figure 14 and for discussions that helped clarify some of our ideas on statistical estimators. Marguerite McCarty expertly performed some of the computations. Support from the Equatorial Pacific Ocean Climate Studies (EPOCS) Program is gratefully acknowledged. This is NOAA PMEL contribution 1565.


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