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Uncrewed Aircraft System Demonstration to Identify Seedable Regions for Precipitation Enhancement

Cloud seeding operations can be made more effective by improving the operational targeting of seeding material. However, a key challenge when attempting to improve the effectiveness of cloud seeding through the current standard practice involves identifying and utilizing sub-cloud features in real-time to deliver the seeding material to the right time and location within the identified cloud. Overcoming this challenge is crucial for maximizing the operational and outreach benefits of cloud seeding while working within the constraints of nature.


To address this challenge, a team led by Prof. Eric Frew, University of Colorado, Boulder, and the 3rd cycle awardee of the UAE Research Program for Rain Enhancement Science (UAEREP), worked on a project titled “Targeted Observation and Seeding Using Autonomous Uncrewed Aircraft Systems’’. The study aimed to demonstrate the feasibility of deploying Uncrewed Aircraft Systems (UAS) to identify regions suitable for precipitation enhancement through cloud seeding, representing a first implementation of an engineering approach utilizing autonomous UAS technology for cloud seeding programs.


The autonomous system design, implementation, and field deployment were based on a dispersed autonomy architecture that simultaneously incorporated sensors, algorithms, operators, and observers from around the world to search, identify, carry out, monitor, and evaluate cloud seeding operations to enhance precipitation.


The team conducted a 3-week long field campaign in the U.S. Great Plains during August 2021 to demonstrate and validate the Concept of Operations (CONOPS) and autonomous system implementation. They initially used a single-aircraft CONOPS to ensure the proper functioning and communication of all system components. After successfully completing the single-aircraft CONOPS, a two-aircraft CONOPS was deployed for tandem cloud measurements and seeding maneuvers.


A total of 9 flights on 8 different days were conducted, accumulating over 8 hours of flight time, including approximately 3 hours of multi-aircraft flights.


The dual UAS mission demonstrated the required level of capability in a typical rain enhancement seeding operational environment. Similarly, a single UAS successfully flew to a region of interest derived from remote sensing data, identified a seedable region, initiated the seeding maneuver, and continued seeding while measuring seedable conditions and conducting evaluation maneuvers multiple times.


These results highlight the potential utility of UAS for cloud seeding operations, positioning the technology at a readiness level between Prototype and Near-Operational environments. Another advantage compared to the current standard practice is the potential for improved targeting efficiency, leading to enhanced results with higher confidence in the seeding effect.


The technology transfer of the UAS and customized sensor payloads to the UAE National Center of Meteorology (NCM) was completed during the first quarter of 2023.


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