PREVENT

PREVENT: Improved Predictability of Extremes over the Mediterranean from Seasonal to Decadal Timescales

Project Website: https://preventmed-climate.eu/

LinkedIn Page: https://www.linkedin.com/in/prevent-project-728b542a3/

Implementation Period: October 2023 – September 2026

Duration: 36 months

Project Partners:

The kick-off meeting was held successfully on Monday & Tuesday 13-14/11/2023 in Thessaloniki, Greece.

Project Summary

It is well-established that the Mediterranean is a climate change hot spot that warms faster than the global mean rates and the frequency of extremes increases. Moreover, climate models often fail to provide sufficient skill in predicting extremes. Extremes are of utmost importance for many socio-economic sectors and activities, including human health, agriculture and water resource management, ecology, and tourism. Most of these activities are dominant drivers of the Mediterranean macro- and micro-economy.

The overall objective of PREVENT is to improve the predictability of impact-relevant extremes in the Mediterranean region on timescales from seasonal to decadal using state-of-the-art dynamical, statistical, and machine learning methods. Additionally, PREVENT brings together experts in different disciplines and geographical regions for a comprehensive study of impact-relevant climate extremes in the Mediterranean to improve their seasonal and decadal predictions in a changing climate.

PREVENT intends to a) Define local climate extreme hotspot regions in the Mediterranean; b) Provide new management tools that can be used in many domains to guide and direct processes, support monitoring activities, and increase organizational efficiency; and c) Develop awareness and competencies by enabling policymakers, industry, and other stakeholders to understand, promote and practice including seasonal and decadal predictions in their planning. PREVENT has a small, flexible consortium consisting of colleagues with significant experience in the Mediterranean climate, especially in the analysis of extreme events and the application of impact models.

Prevent Newsletter #1

This project has received funding from the European Union’s Horizon Research and Innovation Actions, under grant agreement No 101081276

EUROPEAN CLIMATE, INFRASTRUCTURE AND ENVIRONMENT EXECUTIVE AGENCY (CINEA)