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Enhancing Forecast Precision and Data Usability with AI-based Multi-Model Data Fusion for DestinE

Enhancing Forecast Precision and Data Usability with AI-based Multi-Model Data Fusion for DestinE

The project Enhancing Forecast Precision and Data Usability with AI-based Multi-Model Data Fusion for DestinE, developed under the European Destination Earth (DestinE) program, aims to develop and test SynCast, an advanced machine learning-based system designed to integrate the results of multiple forecast models into a single optimized product.

SynCast will leverage the capabilities of the Destination Earth (DestinE) Digital Twin infrastructure and high-performance computing (HPC) to provide real-time, high-resolution forecasts and increased reliability, addressing the growing need for accuracy in the face of increasingly extreme weather events.

The main objective is to improve the accuracy and reliability of forecasts for critical near-surface weather parameters (near-surface parameters), such as wind, temperature, and humidity.

The system will be deployed as a scalable weather forecasting solution in the EuroHPC environment, offering services tailored to specific needs and high-level performance, providing decision-makers with a state-of-the-art tool to improve operational planning and reduce the impact of extreme weather events.

The project is coordinated by DWD (Deutscher Wetterdienst), the German Meteorological Service, and involves strategic partners such as Agenzia ItaliaMeteo, Italian National Meteorological Service, CIMA Foundation, Competence Centre of the Italian Civil Protection System for the hydrometeorological sector and disaster risk mitigation, and CINECA, one of Europe’s largest HPC centres.

*Destination Earth is a European Union-funded initiative launched in 2022 aimed at creating a digital replica of the Earth system by 2030. It is jointly implemented under the leadership of Directorate-General Communications Networks, Content and Technology (DG CNECT) by three entrusted entities ECMWF (responsible for the Digital Twins and Digital Twin Engine), ESA (responsible for the Core Service Platform), and EUMETSAT (responsible for the Data Lake).