Decadal prediction for the European energy sector

Hutchins, B. W. ORCID: https://orcid.org/0009-0001-0421-2399, Brayshaw, D. J. ORCID: https://orcid.org/0000-0002-3927-4362, Shaffrey, L. C. ORCID: https://orcid.org/0000-0003-2696-752X, Thornton, H. E. ORCID: https://orcid.org/0000-0001-5527-7558 and Smith, D. M. ORCID: https://orcid.org/0000-0001-5708-694X (2025) Decadal prediction for the European energy sector. Meteorological Applications, 32 (3). e70054. ISSN 1469-8080 doi: 10.1002/met.70054

Abstract/Summary

The timescale of decadal climate predictions, from a year‐ahead up to a decade, is an important planning horizon for stakeholders in the energy sector. With power systems transitioning towards a greater share of renewable energy sources, these systems become more sensitive to the variability of weather and climate, thus necessitating the provision of long‐range climate predictions to ensure effective planning and operation. As decadal predictions sample both the internal variability of the climate and the externally forced response, these forecasts potentially provide useful information for the upcoming decade. Here, we show for the first time that it is possible to make skillful decadal predictions for a range of energy sector relevant climate variables over the European region. We apply post‐processing techniques and identify skill in certain regions during both summer and winter for temperature, solar irradiance, and precipitation. We also show significant skill for 850 hPa zonal wind speed and the North Atlantic Oscillation during the extended winter period (October–March). We demonstrate how these forecasts can be used for important energy indicators, such as offshore wind capacity factors, comparing the skill of direct model output (using forecast variables directly) and pattern‐based approaches (e.g., using the NAO index). We find significant skill for predictions of modeled European energy variables, including Northern European offshore wind capacity factors ( r = 0.73), UK electricity demand ( r = 0.84), solar photovoltaic capacity factors in Spain ( r = 0.63), and precipitation in Scandinavia ( r = 0.64). Our results highlight the potential for skilful prediction of energy‐sector relevant quantities on decadal timescales. This could benefit both the planning and operation of the future energy system.

Item Type	Article
URI	https://centaur.reading.ac.uk/id/eprint/122800
Identification Number/DOI	10.1002/met.70054
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
Publisher	Elsevier
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