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Seasonal-to-decadal prediction of El Niño-Southern Oscillation and Pacific Decadal Oscillation

Earth Sciences

Seasonal-to-decadal prediction of El Niño-Southern Oscillation and Pacific Decadal Oscillation

J. Choi and S. Son

This study by Jung Choi and Seok-Woo Son reveals the exciting capabilities of predicting the El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) well ahead of time. Discover how improved radiative forcing and model initialization can enhance our understanding of climate patterns across the Pacific Basin!

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~3 min • Beginner • English
Abstract
The growing demand for skillful near-term climate prediction encourages an improved prediction of low-frequency sea surface temperature (SST) variabilities such as the El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). This study assesses their seasonal-to-decadal prediction skills using large ensembles of the Coupled Model Intercomparison Project phases 5 and 6 retrospective decadal predictions. A multi-model ensemble reforecast successfully predicts ENSO over a year in advance. While its seasonal prediction skill in the following spring and summer is achieved by multi-model ensemble averaging of relatively smaller ensemble members, the multi-year prediction of winter ENSO needs a larger ensemble size. The PDO is significantly predicted at a lead time of five-to-nine years but such a long-lead prediction is sourced from external radiative forcing instead of initialization, as evidenced from uninitialized historical simulations. The effect of model initialization lasts only two years. These results confirm that both the model initialization and the proper estimate of near-term radiative forcing are required to improve the seasonal-to-decadal prediction in the Pacific Basin.
Publisher
npj Climate and Atmospheric Science
Published On
Apr 14, 2022
Authors
Jung Choi, Seok-Woo Son
Tags
El Niño-Southern Oscillation
Pacific Decadal Oscillation
decadal prediction
climate modeling
radiative forcing
multi-model ensemble
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