Aviation Decision Support during High-Impact Weather Events via Hyperlocal Remote Sensing Observations

Weather plays a critical role in aviation operations from both an economic and safety perspective. While general weather conditions are important, understanding and forecasting high-impact hyperlocal events is key to maintaining safe and efficient operations. This study seeks to evaluate four types of atmospheric phenomena that pose significant risk to the aviation industry including (1) wind shear, (2) evolution of the low-level jet, (3) severe convection and lightning risk, and (4) icing potential. The analysis will focus on the use of thermodynamic profiling radiometer data and radar wind profiler data to evaluate case studies for each event type from data collected around the world. The study will also demonstrate the use of such remote sensing technology to make informed decisions and short term forecasts integral to both ground operations and aircraft performance during take-off/climb-out and landing.