Primary Convener:
Fan Mei, Pacific Northwest National Laboratory

Convener:
Greg McFarquhar, Cooperative Institute for Severe and High-Impact Weather Research and Operations
Darielle Dexheimer, Sandia National Laboratories
Gijs de Boer, Brookhaven National Laboratory

Chair:
Fan Mei, Pacific Northwest National Laboratory
Greg McFarquhar, Cooperative Institute for Severe and High-Impact Weather Research and Operations
Darielle Dexheimer, Sandia National Laboratories
Gijs de Boer, Brookhaven National Laboratory

Uncrewed Aerial Systems (UAS) and Tethered Balloon Systems (TBS) are revolutionizing atmospheric research by offering cost-effective, safe alternatives to crewed missions. These platforms excel in collecting data from hazardous or remote environments, enabling long-term, routine atmospheric sampling critical for understanding weather patterns and atmospheric chemistry. Recent advancements in sensors, platforms, and the integration of artificial intelligence (AI) and machine learning (ML) have significantly expanded the capabilities of both UAS and TBS. AI/ML algorithms enhance autonomous navigation and real-time data processing, improving efficiency and accuracy. This session invites abstracts on the use of UAS and TBS in advancing atmospheric sciences. Topics of interest include the development of new platforms and instrumentation, AI/ML-enhanced operations, improvements to weather prediction networks, and analysis and interpretation of data from UAS and TBS-supported field campaigns. Join us to explore groundbreaking innovations demonstrating how these systems, powered by AI/ML, are shaping the future of atmospheric research.

Index Terms
0394 Instruments and techniques
3311 Clouds and aerosols
3315 Data assimilation
3322 Land|atmosphere interactions

Suggested Itineraries:
Machine Learning and AI
Open Science and Open Data

Neighborhoods:
3. Earth Covering