Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/20.500.11765/17468
Seasonal Predictions and Their Applications in the Mediterranean Region: Part I—Sources of Predictability and Prediction Skill
Título : Seasonal Predictions and Their Applications in the Mediterranean Region: Part I—Sources of Predictability and Prediction Skill
Autor : Gualdi, SilvioGarcía Serrano, JavierArdilouze, ConstantinTerzago, SilviaTorralba, VerónicaBadi, WafaeBatté, LaurianeDriouech, FatimaFröhlich, KristinaRodríguez Camino, Ernesto ORCID Autor AEMETRodríguez Guisado, EstebanAutor AEMETPasqui, MassimilianoToreti, Andrea
Palabras clave : Mediterranean region; Seasonal predictions; Climate variability; Predictability drivers
Fecha de publicación : 2026
Editor: Wiley; Royal Meteorological Society
Citación : International Journal of Climatology. 2026 [Early view], e70274
Versión del editor: https://doi.org/10.1002/joc.70274
Resumen : The capability to predict climate fluctuations from sub–seasonal–to–decadal timescales would yield large and significant socio–economic benefits. On the other hand, our limited understanding of the mechanisms and processes responsible for predictability and systematic model errors hampers our ability to simulate and forecast climate variability. As a result, current forecast quality remains relatively unsatisfactory, particularly in the mid-latitudes and in the Mediterranean basin. In recent years, several research studies and collaborative projects have been conducted in order to improve the skill of forecasting systems and the quality of the data and climatic information they produce. This effort has led to substantial advancements in understanding Mediterranean climate variability and its drivers, as well as to improvements in the capability to provide reliable climate predictions for this region. The main objective of this paper is to review and discuss the current understanding of climate variability and sources of predictability in the Mediterranean basin and surrounding areas, to assess the current capability of climate prediction systems in order to provide skilful predictions in this region to feed services in relevant socio-economic sectors. Examples of advanced tools and innovative methodologies recently developed to enhance predictions, both in terms of forecast skill and of the quality of the data they provide (e.g., sub–sampling and bias correction), will also be discussed.
Patrocinador: This work was supported by EU Horizon 2020 Cost-ACTION. Ministero dell'Università e della Ricerca (MUR). Ministry of Research and Universities of Catalonia. EU Horizon 2020 Marie Skłodowska-Curie.
URI : http://hdl.handle.net/20.500.11765/17468
ISSN : 0899-8418
1097-0088
Colecciones: Artículos científicos 2023-2026


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