A Simplified Coupled Model of Extended-Range Predictability

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  • 1 Climate Research Division, Scripps Institution of Oceanography, La Jolla, California
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Abstract

A simplified coupled atmosphere-ocean model is used to explore the influence of evolving midlatitude sea surface temperature (SST) anomalies on the theoretical extended-range predictability of the atmospheric wintertime circulation in the Northern Hemisphere. After approximately two weeks, SST anomalies begin to significantly influence the overlying atmospheric flow, compared to flow over the climatological SST field. If the evolving sea surface temperature field is specified from model “observed” flows, then predictions of atmospheric time-averaged flow, for one month and longer averages, are significantly enhanced over predictions based on the atmospheric model with climatological SST. Predictions using the coupled model, however, are not significantly different from predictions using the atmospheric model with persistent SST anomalies, because SST anomalies are forced increasingly erroneously by atmospheric variables that rapidly lose their predictability.

Abstract

A simplified coupled atmosphere-ocean model is used to explore the influence of evolving midlatitude sea surface temperature (SST) anomalies on the theoretical extended-range predictability of the atmospheric wintertime circulation in the Northern Hemisphere. After approximately two weeks, SST anomalies begin to significantly influence the overlying atmospheric flow, compared to flow over the climatological SST field. If the evolving sea surface temperature field is specified from model “observed” flows, then predictions of atmospheric time-averaged flow, for one month and longer averages, are significantly enhanced over predictions based on the atmospheric model with climatological SST. Predictions using the coupled model, however, are not significantly different from predictions using the atmospheric model with persistent SST anomalies, because SST anomalies are forced increasingly erroneously by atmospheric variables that rapidly lose their predictability.

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