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- Title
What do large-scale patterns teach us about extreme precipitation over the Mediterranean at medium-and extended-range forecasts?
- Authors
Mastrantonas, Nikolaos; Magnusson, Linus; Pappenberger, Florian; Matschullat, Jörg
- Abstract
Extreme precipitation events (EPEs) can have devastating consequences, such as floods and landslides, posing a great threat to society and economy. Predicting such events long in advance can support the mitigation of negative impacts. Here, we focus on EPEs over the Mediterranean, a region that is frequently affected by such hazards. Previous work identified strong connections between localized EPEs and large-scale atmospheric flow patterns, affecting weather over the entire Mediterranean. We analyse the predictive skill of these patterns in the European Centre for Medium-Range Weather Forecasts (ECMWF) extended range forecasts and assess if and where these patterns can be used for indirect predictions of EPEs, using the Brier skill score. The results show that the ECMWF model provides skilful predictions of the Mediterranean patterns up to 2 weeks in advance. Moreover, using the forecasted patterns for indirect predictability of EPEs outperforms the reference score up to ∼10 days lead time for many locations. For high orography locations or coastal areas in particular, like parts of western Turkey, western Balkans, Iberian Peninsula, and Morocco, this limit extends to 11–14 days lead time. This study demonstrates that the connections between localized EPEs and large-scale patterns over the Mediterranean extend the forecasting horizon of the model by over 3 days in many locations, in comparison with forecasting based on the predicted precipitation. Thus, it is beneficial to use the predicted patterns rather than the predicted precipitation at longer lead times for EPE forecasting. The model’s performance is also assessed from a user perspective, showing that the EPE forecasting based on the patterns increases the economic benefits at medium/extended range lead times. Such information could support higher confidence in the decision-making of various users; for example, the agricultural sector and (re)insurance companies.
- Subjects
BALKAN Peninsula; IBERIAN Peninsula; EUROPEAN Centre for Medium-Range Weather Forecasts (Organization); LEAD time (Supply chain management); FORECASTING; LONG-range weather forecasting; INSURANCE companies
- Publication
Quarterly Journal of the Royal Meteorological Society, 2022, Vol 148, Issue 743, p875
- ISSN
0035-9009
- Publication type
Article
- DOI
10.1002/qj.4236