Climate Dynamics

, Volume 51, Issue 7–8, pp 3061–3075 | Cite as

Relationship between the North Pacific Gyre Oscillation and the onset of stratospheric final warming in the northern Hemisphere

  • Jinggao Hu
  • Tim Li
  • Haiming Xu


The seasonal timing or onset date of the stratospheric final warming (SFWOD) events has a considerable interannual variability. This paper reports a statistically significant relationship between the North Pacific Gyre Oscillation (NPGO) and SFWOD in the Northern Hemisphere in two sub-periods (1951–1978 and 1979–2015). Specifically, in the first (second) sub-period, the NPGO is negatively (positively) linked with SFWOD. Composite analyses associated with anomalous NPGO years are conducted to diagnose the dynamic processes of the NPGO–SFWOD link. During 1951–1978, positive NPGO years tend to strengthen the Pacific–North America (PNA) pattern in the mid-troposphere in boreal winter. The strengthened PNA pattern in February leads to strong planetary wave activity in the extratropical stratosphere from late February to March and causes the early onset of SFW in early April. By contrast, a strengthened Western Pacific pattern from January to early February in negative NPGO years causes a burst of planetary waves in both the troposphere and extratropical stratosphere from late January to mid-February and results in more winter stratospheric sudden warming events, which, in turn, leads to a dormant spring and a late onset of SFW in late April. During 1979–2015, positive (negative) NPGO years strongly strengthen (weaken) the mid-tropospheric Aleutian low and the Western Pacific pattern from January to mid-March, leading to increased (decreased) planetary wavenumber-1 activity in the stratosphere from mid- to late winter and thus more (less) winter stratospheric sudden warming events and late (early) onsets of SFW in early May (mid-April).


North Pacific Gyre Oscillation Stratospheric final warming Spring season Stratospheric sudden warming Interannual time scale 



We thank three anonymous reviewers and the Editor for their assistance in evaluating this paper. This work was jointly supported by China National R&D Program (2017YFA0603802 and 2015CB453200), the NSFC Project (41505034, 41630423, 41575057 and 41490643), NSF AGS-1565653, Jiangsu NSF Key Project (BK20150062), the Startup Foundation for Introducing Talent of NUIST (2014R010), and the Priority Academic Program Development of Jiangsu Higher Education Institutions. Jinggao Hu thanks the China Scholarship Council for funding and travel support.


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© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environmental Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)Nanjing University of Information Science and TechnologyNanjingChina
  2. 2.International Pacific Research Center, Department of Atmospheric SciencesUniversity of Hawaii at ManoaHonoluluUSA

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