Skilful sub-seasonal forecasts of aggregated temperature over Europe

Baker, L. ORCID: https://orcid.org/0000-0003-0738-9488, Charlton-Perez, A. ORCID: https://orcid.org/0000-0001-8179-6220 and Mattu, K. L. (2023) Skilful sub-seasonal forecasts of aggregated temperature over Europe. Meteorological Applications, 30 (6). e2169. ISSN 1469-8080 doi: 10.1002/met.2169

Abstract/Summary

Subseasonal-to-seasonal (S2S) forecasts span the prediction range of weeks to 2–3 months ahead, bridging the gap between medium-range and seasonal weather forecasts. There has been growing interest in S2S forecasts in recent years, largely because of the many potential uses of forecasts spanning these timescales. However, the skill of S2S forecasts beyond the first 2 weeks or so is poor, potentially limiting the usability of these forecasts. We show in this study that when considering accumulated temperatures, there is in fact good forecasting skill over Europe for accumulation periods up to 30 days ahead. Using a set of S2S hindcasts, we show using both a deterministic and a probabilistic measure of skill that the accumulated 2-metre temperature forecasts out to 30 days are skilful over most of Europe. In summer, South West Europe has highest skill, while in winter North East Europe has highest skill. As an example application of such forecasts, we also evaluate the skill for summer cooling degree-days (CDD) and winter heating degree-days (HDD). For 30-day winter HDD, there is good skill in all four European regions; for 30-day summer CDD, the skill is limited in North West Europe, but still good in other regions.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/114443
Item Type	Article
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > NCAS Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Royal Meteorological Society
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