Incorporating a semi-stochastic model of ocean-modulated westerly wind bursts into an ENSO prediction model
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Prediction models of the El Niño-Southern Oscillation (ENSO) phenomenon often represent westerly wind bursts (WWBs), a significant player in ENSO dynamics, as stochastic forcing. A recent paper developed an observationally motivated semi-stochastic statistical model that quantifies the dependence of WWBs on large-scale sea-surface temperature. This WWB model is added here to a hybrid coupled model, thus activating a two-way SST-WWB feedback. The WWB model represents both the deterministic and stochastic elements of WWBs and thus is especially appropriate for ensemble ENSO prediction experiments. An ensemble of retrospective forecasts is performed for the years 1979–2002. Overall statistical measures of predictability are neither degraded nor improved relative to the hybrid, coupled general circulation model, perhaps because of the limitations of the hybrid coupled model and the initialization procedure used. While the present work is meant as a proof-of-concept, it is found that the addition of the WWB model does improve the prediction of the onset and the development of the large 1997 warm event, pointing to the potential for ENSO prediction skill improvement using this approach.
KeywordsWind Stress Prediction Skill Anomaly Correlation Geophysical Fluid Dynamics Laboratory Warm Event
This work was funded by the NSF Climate Dynamics program, grant ATM-0351123, NSF climate dynamics ATM-0754332, NASA (ECCO2 project). ET thanks the Weizmann Institute for the hospitality during parts of this work.
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