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Skilful seasonal prediction of winter gas demand

Thornton, H. E., Scaife, A., Hoskins, B., Brayshaw, D. ORCID: https://orcid.org/0000-0002-3927-4362, Smith, D., Dunstone, N., Stringer, N. and Bett, P. E. (2019) Skilful seasonal prediction of winter gas demand. Environmental Research Letters, 14 (2). 024009. ISSN 1748-9326

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To link to this item DOI: 10.1088/1748-9326/aaf338

Abstract/Summary

In Britain, residential properties are predominantly heated using gas central heating systems. Ensuring a reliable supply of gas is therefore vital in protecting vulnerable sections of society from the adverse effects of cold weather. Ahead of the winter, the grid operator makes a prediction of gas demand to better anticipate possible conditions. Seasonal weather forecasts are not currently used to inform this demand prediction. Here we assess whether seasonal weather forecasts can skilfully predict the weather-driven component of both winter mean gas demand and the number of extreme gas demand days over the winter period. We find that both the mean and the number of extreme days are predicted with some skill from early November using seasonal forecasts of the large-scale atmospheric circulation (r > 0.5). Although temperature is most strongly correlated with gas demand, the more skilful prediction of the atmospheric circulation means it is a better predictor of demand. If seasonal weather forecasts are incorporated into pre-winter gas demand planning, they could help improve the security of gas supplies and reduce the impacts associated with extreme demand events.

Item Type:Article
Refereed:Yes
Divisions:Interdisciplinary centres and themes > Energy Research
Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:80919
Publisher:Institute of Physics

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