United Arab Emirates – Unmanned aircraft systems (UAS) can make cloud seeding operations more effective as it improves operational targeting of the spread material, a new study suggests.
Cloud seeding using autonomous drone technology is represented by a team led by Eric Frew, a professor at the University of Colorado Boulder and a third-round winner of the UAE Rainfall Enhancement Scientific Research Program (UAEREP). First implementation of the planned engineering approach. Collaborate with National Meteorological Centers on Feasibility Projects.
The study notes that a key challenge when attempting to increase the effectiveness of cloud seeding through current standard practices is identifying and exploiting sub-cloud characteristics in real time to deliver seeding material at the correct time and location within the identified cloud.
Overcoming this challenge is critical to maximizing the operational and deployment benefits of cloud seeding within natural constraints.
The design, implementation, and field deployment of autonomous systems are based on a decentralized autonomous architecture that simultaneously combines sensors, algorithms, operators, and observers from around the world to search, identify, execute, monitor, and evaluate cloud seeding operations to enhance precipitation quantity.
how the research was done
The team conducted a 3-week field event in August 2021 in the Great Plains, USA, to demonstrate and validate concept of operations (CONOPS) and implementation of autonomous systems.
They initially used stand-alone CONOPS to ensure proper functioning and communication of all system components. After successful single-aircraft CONOPS, a two-aircraft CONOPS was deployed for tandem cloud survey and seeding maneuvers.
A total of 9 flights were carried out in 8 days, and the cumulative flight time was more than 8 hours, of which the multi-aircraft flight was about 3 hours.
The dual-drone mission demonstrated the level of capability required in a typical rain-enhancing seeding operation environment. Likewise, a UAV successfully flew to an area of interest based on remote sensing data, identified a sowing area, initiated a sowing operation, and continued to measure sowing conditions and conduct evaluation operations several times.
These results highlight the potential utility of UAS for cloud seeding operations, placing the technology at a level of readiness between a prototype environment and a near-operational environment. An additional advantage over current standard practice is the potential to increase targeting efficiency, thereby improving outcomes and increasing confidence in seeding efficacy.
The technology transfer of the UAV system and custom sensor payloads to the UAE NCM has been completed in the first quarter of 2023.
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