Skillful prediction of winter Arctic Oscillation from previous summer in a linear empirical model
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illful prediction of winter Arctic Oscillation from previous summer in a linear empirical model Hong-Li REN
1,2,3*
2
& Yu NIE
1
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China; Laboratory for Climate Studies & CMA-NJU Joint Laboratory for Climate Prediction Studies, National Climate Center, China Meteorological Administration, Beijing 100081, China; Department of Atmospheric Science, School of Environmental Studies, China University of Geoscience, Wuhan 430074, China 2
3
Received April 4, 2020; revised June 14, 2020; accepted July 21, 2020; published online October 26, 2020
Abstract 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. Keywords model Citation:
Arctic Oscillation (AO), Winter AO prediction, Sea ice concentration, Sea surface temperature, Linear empirical
Ren H, Nie Y. 2020. Skillful prediction of winter Arctic Oscillation from previous summer in a linear empirical model. Science China Earth Sciences, 63, https://doi.org/10.1007/s11430-020-9665-3
1. Introduction The winter Arctic Oscillation (denoted as WAO) has been well known as a primary atmospheric variability mode in the Northern Hemisphere (NH, Thompson and Wallace, 1998, 2000; Wallace, 2000) and plays a key role in affecting weather events and climate variations at mid-high latitudes (e.g., Thompson and Wallace, 2001; Zuo et al., 2015 and their review). Previous studies have focused on the features, mechanisms, and impacts of WAO in recent two decades. The WAO prediction, as the heart of mid-high-latitude pre* Corresponding author (email: [email protected])
dictions, is of a great importance but a challenging issue to the operational weather forecast and climate prediction due to highly chaotic and stormy atmospheric activity (Cohen et al., 2002). However, the W
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