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UAE Research Programme for Rain Enhancement Science reviews updates on 4th cycle research project

UAE Research Programme for Rain Enhancement Science reviews updates on 4th cycle research project
30 Jan 2024 16:32

ABU DHABI (WAM)


The UAE Research Programme for Rain Enhancement Science (UAEREP) recently hosted a meeting with Dr. Luca Delle Monache and his research team, winners of the 2021 fourth UAEREP grant cycle, to discuss the latest updates on their research project titled: “A Hybrid Machine Learning Framework for Enhanced Precipitation Nowcasting”.

The meeting additionally provided context on the National Center of Meteorology’s (NCM) operational infrastructure, including their cloud seeding standard operating procedures, radar networks, and high-performance computing systems, for the research team to complete their project deliverables to NCM. The team, led by Dr. Monache, includes researchers from the Scripps Institution of Oceanography at UC San Diego, Colorado State University and Khalifa University.

Alya Al Mazroui, Director of UAEREP, said, “Meetings like this allow us the opportunity to provide support and pool our joint expertise, ensuring Dr. Monache’s nowcast project will produce maximum impact and deliver on its ambitious, innovative goals. We are confident this project will further enhance our understanding of generating seedable cloud features and early precipitation forecasts. UAEREP, through the NCM, will continue to drive global research networks, leverage best-in-class advanced technology and AI, and propel rain enhancement research.”

AI-Generated Rain Model


Dr. Monache's project aims to create an AI research and operations test bed in the UAE, while building a novel AI framework to blend satellite observations, ground-based weather radar data, rain gauges, and numerical weather prediction estimates to extract features and generate products to determine optimal cloud seeding timing and location, and to generate more accurate quantitative precipitation estimation for rainfall enhancement programme evaluation.

The project features, along with extrapolated satellite and radar data and numerical weather prediction data and rain gauges, are utilised as input to an AI-based model to generate precipitation predictions six hours in the future.

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