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UAE researches AI use in cloud seeding for precise rain enhancement
The project aims to develop a real-time, data-driven system for assessing cloud seedability at the scale of convective cloud clusters
- PUBLISHED: Thu 25 Sept 2025, 6:50 PM
A UAE-backed international research project is using artificial intelligence and advanced modelling to assess cloud seedability in near real-time, aiming to make rain enhancement more precise and effective. The project is funded by the UAE Research Program for Rain Enhancement Science (UAEREP).
The Strategic Directions Committee (SDC) of UAEREP recently conducted a midterm site visit to Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) to evaluate the progress of its Cycle 5 awardee project, “Identification of Clouds’ Microphysical Seedability in an Actionable Manner".
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During the visit, the research team showcased key milestones, including the completion of the first customised WRF-SBM cloud-scale simulation over the UAE, executed on NCM’s supercomputer 'Atmosphere'.
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Dr Abdulla Al Mandous, Director General of NCM and President of the World Meteorological Organisation (WMO), said: “By bringing together leading institutions from across the globe, the programme is driving a shared scientific vision through coordinated research efforts that accelerate the development of sustainable solutions to global water security challenges."
Alya Al Mazroui, Director of UAEREP, added: “The integration of AI and advanced modeling into cloud seedability assessment marks a transformative step in rain enhancement research. By leveraging satellite data, machine learning, and validated simulations, this project is developing a decision-support tool that enables near real-time evaluation of cloud systems.”
Led by Professor Daniel Rosenfeld from the Hebrew University of Jerusalem (HUJI), the project is being implemented collaboratively with the National Center of Meteorology (NCM) and MBZUAI in the UAE, Wuhan University (WHU) in China, and the University of California San Diego (UCSD) in the United States.
The project aims to develop a real-time, data-driven system for assessing cloud seedability at the scale of convective cloud clusters, using satellite and meteorological data, advanced modeling, and machine learning to guide seeding decisions and estimate potential impact.
As Associate Editor, Sahim Salim helps tell the UAE story like no one else does — and leads a team of reporters that asks the questions to get news and headlines that matter.
