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Enhanced long-range forecast skill in boreal winter following stratospheric strong vortex conditions

Tripathi, O. P., Charlton-Perez, A., Sigmond, M. and Vitart, F. (2015) Enhanced long-range forecast skill in boreal winter following stratospheric strong vortex conditions. Environmental Research Letters, 10 (10). 104007. ISSN 1748-9326

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To link to this item DOI: 10.1088/1748-9326/10/10/104007


There has been a great deal of recent interest in producing weather forecasts on the 2–6 week sub-seasonal timescale, which bridges the gap between medium-range (0–10 day) and seasonal (3–6 month) forecasts. While much of this interest is focused on the potential applications of skilful forecasts on the sub-seasonal range, understanding the potential sources of sub-seasonal forecast skill is a challenging and interesting problem, particularly because of the likely state-dependence of this skill (Hudson et al 2011). One such potential source of state-dependent skill for the Northern Hemisphere in winter is the occurrence of stratospheric sudden warming (SSW) events (Sigmond et al 2013). Here we show, by analysing a set of sub-seasonal hindcasts, that there is enhanced predictability of surface circulation not only when the stratospheric vortex is anomalously weak following SSWs but also when the vortex is extremely strong. Sub-seasonal forecasts initialized during strong vortex events are able to successfully capture the associated surface temperature and circulation anomalies. This results in an enhancement of Northern annular mode forecast skill compared to forecasts initialized during the cases when the stratospheric state is close to climatology. We demonstrate that the enhancement of skill for forecasts initialized during periods of strong vortex conditions is comparable to that achieved for forecasts initialized during weak events. This result indicates that additional confidence can be placed in sub-seasonal forecasts when the stratospheric polar vortex is significantly disturbed from its normal state.

Item Type:Article
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:51843
Publisher:Institute of Physics


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