Imagine having a super-smart weather app that doesn't just tell you it will rain, but predicts exactly which buildings will flood and how much money will be lost. It connects data from different countries to spot patterns in wildfires, floods, and heatwaves before they hit. This helps cities and businesses move resources to the right place before the disaster actually happens.
Existing early warning systems are fragmented and fail to predict the actual economic and societal impact of disasters. This leads to inefficient resource deployment and massive financial losses during extreme weather events.
A risk transfer and impact forecasting platform and a dedicated API for delivering multi-hazard forecasts and impact assessment services.
If you are an insurance provider dealing with unpredictable climate payouts — this project developed parametric insurance and risk transfer tools that trigger automatic payments based on forecast data. This reduces manual claims processing and speeds up recovery for clients.
If you are a port operator dealing with coastal floods and storm surges in the Mediterranean — this project developed an API for multi-hazard forecasts. This allows you to reroute ships and protect cargo based on precise impact assessments.
If you are a farm management company dealing with droughts and heatwaves — this project developed AI-based forecasting models. This helps you optimize water use and protect crops by predicting extreme events in regions like Spain or Ethiopia.
Based on available project data, no specific commercial pricing or cost structure is mentioned; the project is funded by an EU contribution of EUR 4,999,874.
Yes, the project uses eight pilot regions across Europe, the Mediterranean, and Africa to ensure the tools are adaptable and transferable to different geographical and climatic contexts.
Based on available project data, specific IP and licensing terms are not provided, though the project involves 29 partners including 3 industry entities and 5 SMEs.
The project delivers a modular, interoperable Decision Support and Dissemination System (DSDS) and an API to deliver forecasts directly into existing workflows.
The initial versions of the risk transfer platform and the API are scheduled for delivery in month 18 (M18) of the project.
The consortium is heavily research-driven with 14 research organizations and 1 university, but maintains a 10% industry ratio with 3 industry partners and 5 SMEs. This balance suggests a transition from academic theory to practical application, leveraging 29 partners across 16 countries to ensure the software works across diverse regulatory and geographic zones.
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