Skillful prediction of winter Arctic Oscillation from previous summer in a linear empirical model

作者：Hong-Li REN,Yu NIE

摘要：The winter Arctic Oscillation(WAO),as a primary atmospheric variability mode in the Northern Hemisphere,plays a key role in influencing mid-high-latitude climate variations.However,current dynamical seasonal forecasting systems have limited skills in predicting WAO with lead time longer than two months.In this study,we design a linear empirical model using two effective precursors from anomalies of the Arctic sea ice concentration(SIC)and the tropical sea surface temperature(SST)initiated in preceding late summer(August)which are both significantly correlated with WAO in recent four decades.This model can provide a skillful prediction of WAO at about half-year lead started from previous summer and perform much better than the dynamical models.Such a significantly prolonged lead time is owed to the stable precursor signals extracted from the SIC and SST anomalies over specific areas,which can persist from previous August and be further enhanced through autumn months.Validation results show that this model can produce a 20-year independent-validated prediction skill of 0.45 for 1999–2018 and a 39-year cross-validated skill of 0.67 for 1980–2018,providing a potentially effective tool for earlier predictions of winter climate variations at mid-high latitudes.

发文机构：State Key Laboratory of Severe Weather Laboratory for Climate Studies&CMA-NJU Joint Laboratory for Climate Prediction Studies Department of Atmospheric Science

关键词：ArcticOscillation(AO)WinterAOpredictionSeaiceconcentrationSeasurfacetemperatureLinearempiricalmodel

分类号： P73[天文地球—海洋科学]