Abstract
AbstractSudden stratospheric warmings (SSWs) during boreal winter are one of the main drivers of sub‐seasonal climate variability in the Northern Hemisphere. Although the impact of SSW events on surface climate and climate extremes has been clearly demonstrated, the impact of the resulting climate anomalies on society has not been so widely considered. In the United Kingdom (UK), SSWs are associated with cold weather, which is linked to significant increases in mortality. This study demonstrates, for the first time, that SSWs are linked to increases in mortality in the UK. A distributed lag nonlinear model and standard parameter settings from the literature is used to construct a daily time series of UK deaths attributable to cold weather between 1991 and 2018. Weekly mortality associated with SSWs is diagnosed using a superposed epoch analysis of attributed mortality for the 15 SSW events in this period. SSW associated mortality peaks between 3 and 5 weeks after SSW central date and leads to, on average, 620 additional deaths in the same period. Given that the impacts of SSWs can be skilfully predicted on sub‐seasonal timescales, this suggests that health and social care systems could derive substantial benefit from sub‐seasonal forecasts during SSWs.
Highlights
Major, sudden stratospheric warming (SSW) events are one of the most dramatic and long-lived events in the wintertime extra-tropical atmosphere (O'Neill et al, 2015)
In the United Kingdom (UK), SSWs are associated with cold weather, which is linked to significant increases in mortality
This study demonstrates, for the first time, that SSWs are linked to increases in mortality in the UK
Summary
Sudden stratospheric warming (SSW) events are one of the most dramatic and long-lived events in the wintertime extra-tropical atmosphere (O'Neill et al, 2015). During the period 1991–2018, over which we have mortality data, there are 15 SSWs. We model the relationship between temperature and mortality for each sub-region of the UK and for the total mortality over the UK using a distributed lag non-linear model, following the tutorial in Vicedo-Cabrera et al (2019). We use forward estimates ( with a lower case “f” prepended) to determine the effect of a given temperature value on mortality for the following 21 days. Climatological attributable mortality is calculated by taking multi-year daily averages excluding dates with 31 days of an SSW central date and smoothing the resulting estimate using a B-spline with knots placed every 30 days and the series repeated three times to avoid edge effects
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
