EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Seasonal prediction of UK mean and extreme winds

Julia Lockwood1, Nicky Stringer1, Katie Hodge1, Philip Bett1, Jeff Knight1, Doug Smith1, Adam Scaife1,2, Matthew Patterson3, Nick Dunstone1, and Hazel Thornton1
Julia Lockwood et al.
  • 1Met Office Hadley Centre, Monthly to decadal forecasting, Exeter, United Kingdom of Great Britain – England, Scotland, Wales (
  • 2College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
  • 3Atmospheric, Oceanic and Planetary Physics, University of Oxford, Parks Road, OX1 3PU, Oxford, UK

For several years the Met Office has produced a seasonal outlook for the UK every month, which is issued to the UK Government and contingency planners.  The outlook gives predictions of the probability of having average, low, or high seasonal mean UK temperature and precipitation for the coming three-months.  In recent years, there has been increasing demand from sectors such as energy and insurance to include similar probabilistic predictions of UK wind speed: both for the seasonal mean and for measures of extreme winds such as storm numbers.  In this presentation we show the skill of the Met Office’s GloSea system in predicting seasonal (three-month average) UK mean wind and a measure of UK storminess throughout the year, and discuss the drivers of predictability.  Skill in predicting the UK mean wind speed and storminess peaks in winter (December–February), owing to predictability of the North Atlantic oscillation.  In summer (June–August), there is evidence that a significant proportion of variability in UK winds is driven by a Rossby wave train which the model has little skill in predicting. Nevertheless there are signs that the wave is potentially predictable and skill may be improved by reducing model errors.

How to cite: Lockwood, J., Stringer, N., Hodge, K., Bett, P., Knight, J., Smith, D., Scaife, A., Patterson, M., Dunstone, N., and Thornton, H.: Seasonal prediction of UK mean and extreme winds, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-13639,, 2023.