UAE researchers harness AI to assess cloud seedability in real time

Abu Dhabi: The Strategic Directions Committee (SDC) of the UAE Research Program for Rain Enhancement Science (UAEREP) carried out a midterm site visit to Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) to review progress on a major international research project.

The study, titled “Identification of Clouds’ Microphysical Seedability in an Actionable Manner”, is one of the Cycle 5 awardee projects under UAEREP. It is led by Professor Daniel Rosenfeld from the Hebrew University of Jerusalem (HUJI) and brings together partners from the UAE, China, and the United States.

The project is being implemented jointly by the National Centre of Meteorology (NCM) and MBZUAI, along with Wuhan University (WHU) in China and the University of California San Diego (UCSD) in the US.

Its main aim is to develop a real-time, data-driven system that can assess cloud seedability on the scale of convective cloud clusters. Using satellite observations, meteorological data, advanced modelling, and machine learning, the system will help guide seeding decisions and predict their potential impact.

The cross-border nature of the research underlines UAEREP’s focus on international partnerships to develop effective, science-backed approaches to water security. NCM’s technical support and cutting-edge facilities have been key in enabling this collaboration, encouraging knowledge sharing and capacity building across institutions.

Dr Abdulla Al Mandous, Director General of NCM and President of the World Meteorological Organization (WMO), said the project reflects UAEREP’s mission of advancing research through global cooperation.

“By bringing together leading institutions from across the globe, the programme is driving a shared scientific vision. This model not only strengthens the quality and impact of our research, but also reinforces the UAE’s role as a global convener in addressing water security challenges through innovation and partnership,” he said.

Alya Al Mazroui, Director of UAEREP, added that integrating AI and modelling into seedability studies represents a “transformative step” in rain enhancement science. “By combining satellite data, machine learning, and validated simulations, the project is creating a decision-support tool that allows near real-time evaluation of cloud systems,” she said.

During the visit, the team presented several milestones. These included the first customised WRF-SBM cloud-scale simulation over the UAE, run on NCM’s supercomputer Atmosphere. The simulation provides critical input for developing an AI-powered Seedability Guidance Tool in collaboration with UCSD.

MBZUAI researchers also demonstrated advances in satellite image enhancement, using super-resolution methods to improve Meteosat geostationary imagery, which enables more accurate detection of seedable clouds.

At the same time, Wuhan University has developed software that automates the sampling and visualisation of cloud microphysical properties needed for seedability studies.

The project has also engaged graduate students and postdoctoral researchers across HUJI, MBZUAI, WHU, and UCSD, ensuring a new generation of scientists are trained in data-driven rain enhancement research.