This review paper examines the development and application of climate predictions, primarily at seasonal timescales, as actionable information for decision-making, with a specific focus on the Mediterranean region. It illustrates and analyses the steps required to transform climate model probabilistic forecasts into user-defined information, emphasising the iterative nature of climate service development. By leveraging tools such as bias adjustment, downscaling, probabilistic calibration and impact models, these services provide tailored solutions to key sectors including energy, water supply, transport and agriculture. The paper discusses the contributions of global initiatives, such as the Global Framework for Climate Services (GFCS), and EU-funded projects like EUPORIAS, MEDSCOPE and MED-GOLD, which have advanced sector-specific applications of climate predictions in the region. These initiatives illustrate how tailored climate services can address critical challenges ranging from renewable energy planning to drought risk mitigation and agricultural yield forecasting. The review highlights persistent challenges, including limited forecasting skill in the Mediterranean area, data accessibility issues and the need for robust impact-based verification. To enhance the uptake and effectiveness of climate services, the review recommends fostering interdisciplinary collaboration, promoting iterative co-production with users, improving the communication of uncertainty and forecast skill, and ensuring the sustainability of services beyond project lifetimes. This work underscores the potential of climate services to enhance resilience in the Mediterranean region, bridging the gap between scientific advances and practical applications.

Seasonal Predictions and Their Applications in the Mediterranean Region: Part II—Prediction‐Based Services

Pasqui, Massimiliano
Secondo
;
Terzago, Silvia
Ultimo
;
2026

Abstract

This review paper examines the development and application of climate predictions, primarily at seasonal timescales, as actionable information for decision-making, with a specific focus on the Mediterranean region. It illustrates and analyses the steps required to transform climate model probabilistic forecasts into user-defined information, emphasising the iterative nature of climate service development. By leveraging tools such as bias adjustment, downscaling, probabilistic calibration and impact models, these services provide tailored solutions to key sectors including energy, water supply, transport and agriculture. The paper discusses the contributions of global initiatives, such as the Global Framework for Climate Services (GFCS), and EU-funded projects like EUPORIAS, MEDSCOPE and MED-GOLD, which have advanced sector-specific applications of climate predictions in the region. These initiatives illustrate how tailored climate services can address critical challenges ranging from renewable energy planning to drought risk mitigation and agricultural yield forecasting. The review highlights persistent challenges, including limited forecasting skill in the Mediterranean area, data accessibility issues and the need for robust impact-based verification. To enhance the uptake and effectiveness of climate services, the review recommends fostering interdisciplinary collaboration, promoting iterative co-production with users, improving the communication of uncertainty and forecast skill, and ensuring the sustainability of services beyond project lifetimes. This work underscores the potential of climate services to enhance resilience in the Mediterranean region, bridging the gap between scientific advances and practical applications.
2026
Istituto per la BioEconomia - IBE - Sede Secondaria Roma
Istituto di Scienze dell'Atmosfera e del Clima - ISAC - Sede Secondaria Torino
actionable information for decision making
climate prediction-based services
mediterranean region
risk management
seasonal prediction applications
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/591822
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ente

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 1
social impact