Description:

The development of drone technologies has led to new in situ and remote sensing methodologies. Drones, or unmanned aerial vehicles (UAVs), have use cases including weather modification, atmospheric observations, hydrological studies, general GIS, and greenhouse gas emissions monitoring. This technology has become more prevalent in these fields over the past decade (Miller 2023, Jung et all, 2022, Henneberg 2023, many more). 

This presentation aims to provide a comprehensive review of modern drone observations in meteorological research and emphasize the need for drone platform standardization and autonomy. We will discuss the current state of drone technologies used in various meteorological applications, focusing on their capabilities, limitations, and potential for future improvements and standardization. By examining these case studies, we will showcase the diversity of drone platforms and the challenges associated with integrating data from various sources. The lack of standardization in drone platforms and autonomy can present challenges to data sharing, and the reproducibility of research findings at scale. 

The development of autonomous drone systems can obtain airborne observations in novel ways. Autonomous drones can operate beyond visual line of sight collecting data for extended periods without human intervention. However, the lack of standardized protocols and regulations for autonomous drone operations poses challenges in terms of human safety, reliability, and data quality assurance.  

By addressing these challenges, we can foster collaboration among researchers and support the reproducibility of data. This will be critical as drone studies and in field use continue to become more prevalent. The insights gained from this review will inform future research directions, policy recommendations, and technology development efforts in the field of meteorological drone applications. 

References:  

Henneberg et al, 2023, Seeding of Supercooled Low Stratus CLouds with a UAV to Study Microphsyical Ice Processes: An Introduction to the CLOUDLAB Project, BAMS, 104, https://doi.org/10.1175/BAMS-D-22-0178.1 

Miller et al, 2023, Two new multirotor uncrewed aerial vehiclesor glaciogenic cloud seeding and aerosol measurments within the CLOUDLAB project, European Geoscience Union, 12, https://doi.org/10.5194/amt-17-601-2024 

Jung, 2022, Progressive and Prospective Technology for Cloud Seeding Experiment by Unmanned Aerial Vehicle and Atmospheric Research Aircraft in Korea, Advance in Meteorology, 2022, https://doi.org/10.1155/2022/3128657