Airborne Weather Observation Applications and Benefits Assessment for Air Traffic Management

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Monday, 5 January 2015: 2:00 PM
129A (Phoenix Convention Center - West and North Buildings)
Jarrod Lichty, AvMet Applications, Inc., Reston, VA; and T. J. Farrar, M. Phaneuf, R. S. Lee, J. L. Bewley, and D. O'Donnell

Airborne weather observations (e.g., radiosondes, satellites, aircraft observations) function as a key role in enabling air traffic management (ATM) to mitigate the impact of weather in the National Airspace System (NAS). For example, pilot reports (PIREP) are directly accessed in tactical situations to enhance situational awareness of airspace constraints (e.g., turbulence, icing, winds). However, limitations such as pilot subjectivity, time requirements associated with issuance and collection, and relatively sparse spatial coverage reduce PIREP effectiveness. Aircraft airborne weather observations are used for initialization and validation of Numerical Weather Prediction models and are therefore used indirectly by ATM via model forecast output during both tactical and strategic time periods.

The nature of NextGen operations requires a change in the way weather is collected, analyzed, predicted, and integrated into aviation decision-making. Aircraft airborne weather observation programs (e.g., Meteorological Data and Collecting Report System) offer rich meteorological data which could potentially be an asset to ATM for both NowGen and NextGen operations. In order to advance the use of this data within the Federal Aviation Administration, quality of service (e.g., latency, accuracy, reliability) requirements must be established for each ATM application of airborne observation information. This paper will describe the efforts taken to map airborne observations to ATM applications and identify operational enhancement opportunities which support current and future airborne observation requirements. Given these identified opportunities, use case benefits scenarios for ATM utilization of aircraft airborne observation data will be described and quantified through the use of a fast-time air traffic simulation model.