In 2024, the UAE has been carrying out hundreds of cloud-seeding missions across the country to increase rainfall and tackle water scarcity. Now, the Emirates is using Artificial Intelligence (AI) to enhance these efforts and improve rainfall results.
The country has made significant investments in technology to secure its water supply, achieving an annual minimum increase of 15 percent in rainfall.
Advancements in Cloud-Seeding Technology
On Tuesday, officials at the National Centre of Meteorology (NCM) in Abu Dhabi shared that AI plays a vital role in optimizing cloud-seeding operations and improving decision-making for more effective rainfall enhancement.
Omar Al Yazeedi, deputy director general of NCM, explained, “The lifespan of clouds is very short, so if multiple clouds are present, AI can help forecasters choose the best locations by analyzing specific parameters. Currently, operations are manual. With AI, the operator can evaluate cloud characteristics and determine the best approach.”
Using AI for Real-Time Data Analysis
Yazeedi highlighted that AI algorithms allow meteorologists to process vast amounts of weather data in real time, helping them predict the optimal times and locations for cloud seeding. AI improves the accuracy of weather models and provides insights into how clouds form and behave, which enhances the chances of successful rainfall induction.
Drones equipped with sensors and AI capabilities are also part of this strategy. These drones can release seeding materials directly into clouds more accurately than traditional methods.
“AI is beneficial when using drones; if you have many aircraft, AI helps maximize operations, getting the most out of each cloud and identifying ideal locations for seeding,” he added.
Impact of Cloud-Seeding Efforts
The UAE’s cloud-seeding initiatives have created a usable water supply between 84 and 419 million cubic meters. This volume is a significant part of the approximately 6.7 billion cubic meters of rainfall the UAE receives each year, with cloud-seeding operations costing around Dh29,000 ($8,000) for every flight hour.
Alya Al Mazroui, director of the UAE Rain Enhancement Program (UAEREP), noted that the UAE’s technological and scientific advancements are gaining international recognition for their potential applications in countries facing similar water challenges.
“As we approach the tenth anniversary of our pioneering research and technology demonstrations, we remain committed to the UAE’s goals in water security, scientific research, and innovation, including AI,” she said.
Promoting Innovation and Research
Al Mazroui explained that the UAEREP collaborates with NCM to share data, expertise, and facilities, enhancing research teams’ capabilities. The program actively promotes innovation and interdisciplinary research in rain enhancement and weather modification, incorporating advancements in AI, drones, nanotechnology, and laser technology to create new seeding materials.
Another exciting project, in partnership with Mohamed bin Zayed University of Artificial Intelligence (MBZUI), uses AI to identify cloud seedability in a practical way.
On average, the UAE conducts over 900 hours of cloud-seeding missions every year, with substantial investments made in research and technology. The program also collaborates with key investigators to transition research results into scalable and commercial applications.
Future of Cloud-Seeding Technology
As the UAE advances its AI systems, experts noted that pilotless cloud-seeding is still in development, as accurately interpreting complex weather patterns like human pilots is a challenge.
“Right now, replacing a pilot is tough because the pilot’s instincts are essential for maneuvering the aircraft and confirming what the forecaster sees on the ground. We need a strong relationship between the pilot, forecaster, and cloud-seeding operator to confirm locations before proceeding. Pilotless seeding is part of our future goals, enhancing our capabilities while improving research in AI, drones, and other technologies,” Yazeedi explained.
