UAEREP Evaluates Midterm Progress Of Cycle 5 Project On AI-Driven Cloud Seedability Assessment

The UAE Research Programme for Rain Enhancement Science (UAEREP) is making strides in rain enhancement research. A midterm site visit was conducted by the Strategic Directions Committee to Mohamed bin Zayed University of Artificial Intelligence (MBZUAI). The focus was on evaluating the progress of a Cycle 5 project titled "Identification of Clouds’ Microphysical Seedability in an Actionable Manner." This initiative is led by Professor Daniel Rosenfeld from the Hebrew University of Jerusalem.

Dr. Abdulla Al Mandous, Director General of the National Center of Meteorology (NCM), emphasised the project's significance. He stated, "This project highlights UAEREP’s commitment to advancing rain enhancement research through international collaboration. 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."

The project involves collaboration between NCM, MBZUAI, Wuhan University in China, and the University of California San Diego (UCSD) in the United States. It aims to create a real-time system for assessing cloud seedability using satellite data, advanced modeling, and machine learning. This approach guides seeding decisions and estimates potential impacts at the scale of convective cloud clusters.

Alya Al Mazroui, Director of UAEREP, highlighted the integration of AI and advanced modeling as transformative for rain enhancement research. She noted that leveraging satellite data and machine learning helps develop a decision-support tool for real-time cloud system evaluation. These innovations build on previous UAEREP cycles while fostering new talent in data-driven rain enhancement science.

During the visit, significant achievements were showcased. The team completed a customized WRF-SBM cloud-scale simulation over the UAE using NCM's supercomputer "Atmosphere." This simulation aids in developing an AI-powered Seedability Guidance Tool with UCSD. Additionally, MBZUAI applied super-resolution techniques to enhance Meteosat satellite imagery quality for better detection of seedable clouds.

Wuhan University contributed by developing software that automates sampling and visualisation of cloud microphysical properties crucial for seedability assessment. The project also demonstrated strong academic engagement with graduate students and postdoctoral researchers actively involved across HUJI, MBZUAI, WHU, and UCSD.

Long-term Water Security Goals

The collaborative nature of this project underscores UAEREP's commitment to global partnerships in advancing impactful solutions for rain enhancement. NCM provides comprehensive technical support and state-of-the-art facilities, facilitating continuous knowledge exchange across borders to achieve long-term water security in the UAE and beyond.

This initiative not only strengthens research quality but also reinforces UAE's role as a global leader in addressing water security challenges through innovation and partnership. By fostering international collaboration, UAEREP aims to drive sustainable solutions to global water security issues.

With inputs from WAM