A005
Advances in Weather Prediction for Unmanned Aircraft Systems
Advances in Weather Prediction for Unmanned Aircraft Systems
Session ID#: 159181
Session Description:
Unmanned Aircraft System (UAS) operations in the National Airspace System are rapidly increasing, and the trend is expected to continue as regulations are refined to allow broader access to the airspace. The unique characteristics of UAS may drive the need for new and unique operational strategies, many of which are highly dependent on weather conditions. Numerous gaps still exist today such as the reliability of forecasts tailored for on-airport operations that are not sufficient for off-airport, Beyond Visual Line Of Sight and urban operations. Moreover, weather models and fusion systems are time consuming and cannot support the requirements of this latency-sensitive application that engages multiple stakeholders. Fortunately, artificial intelligence is gaining popularity among the aviation weather community because it has the potential to bring high-resolution numerical models and fusing approaches into operations to reduce UAS mission uncertainty and increase its situational awareness. This session invites abstracts discussing scientific contributions addressing weather operational needs that enable UAS navigation over urban, suburban and rural areas through the use of novel approaches that involve coupled simulations, artificial intelligence and the use of targeted sensing.
Co-Sponsor(s):
- AMS: American Meteorological Society -
- EGU: European Geosciences Union -
Index Terms:
0555 Neural networks, fuzzy logic, machine learning [COMPUTATIONAL GEOPHYSICS]
1910 Data assimilation, integration and fusion [INFORMATICS]
1952 Modeling [INFORMATICS]
3360 Remote sensing [ATMOSPHERIC PROCESSES]
Primary Convener: Mounir Chrit, University of North Dakota, Department of Atmospheric Sciences, Grand Forks, ND, United States
Convener: Marwa Majdi, University of North Dakota, Atmospheric Sciences, Grand Forks, United States
See more of: Atmospheric Sciences