Enhanced mid-to-late winter predictability of the storm track variability in the North Pacific as a contrast with the North Atlantic

Author:

Nie YuORCID,Ren Hong-Li,Scaife Adam A

Abstract

Abstract The storm tracks are a major driver of regional extreme weather events. Using the daily output of reanalysis and a latest generation ensemble seasonal forecasting system, this study examines the interannual variability and predictability of the boreal winter storm tracks in the North Pacific and North Atlantic. In both basins, the leading mode of storm track variability describes a latitudinal shifting of the climatological storm tracks. The shifting mode is closely connected with the extratropical large-scale teleconnection patterns (i.e. Pacific-North America teleconnection and North Atlantic Oscillation). The main predictability source for the shifting mode of the North Pacific storm tracks are the ENSO-related sea surface temperature anomalies. Assessment of the seasonal prediction skill further shows that the shifting mode of the North Pacific storm tracks is in general better predicted than that of the North Atlantic storm tracks likely due to stronger ENSO effects. Our analyses also find that, through the modulations of ENSO and the subtropical jet, the shifting mode of the North Pacific storm tracks exhibit a mid-to-late winter predictability enhancement. During El Niño phases, the North Pacific subtropical jet shifts equatorward and becomes strongest in mid-to-late winter, which dominates the upper-level flow and guides the storm track most equatorward. We argue that the intensification and equatorward shift of the North Pacific subtropical jet in mid-to-late winter of El Niño years provide the main reason for the increased mid-to-late winter predictability for the storm tracks. The results imply that good representation of the background subtropical jet in models is important for winter climate prediction of storm tracks.

Funder

NSF of China

National Key Research and Development Program on monitoring, Early Warning and Prevention of Major Natural Disaster

the UK-China Research \& Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund

Publisher

IOP Publishing

Subject

Public Health, Environmental and Occupational Health,General Environmental Science,Renewable Energy, Sustainability and the Environment

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