== Abstract ==

​

ft have to be rerouted around severe weather to ensure safe operation. Consequent changes in the flight plan often leads to arrival delays. Due to the complexity of the weather patterns and the traffic flow structure, the uncertainties in aircraft arrival rates cannot be predicted analytically from the uncertainties in the weather forecasts. This paper demonstrates the use of Monte-Carlo simulation to transform the uncertainties in severe weather prediction into uncertainties in the arrival flow rate at given airports. The aircraft trajectories are propagated using a simulation model of the air traffic environment. A rerouting algorithm is defined to modify the aircraft flight plans for avoiding severe weather regions. Using the traffic data for a typical day as the baseline, 300 Monte-Carlo runs are carried out and the variations in the aircraft arrival patterns are quantified as a function of the weather prediction uncertainty for several airports in the continental United States.

​

​

== Original document ==

​

The different versions of the original document can be found in:

​

* [http://pdfs.semanticscholar.org/b02f/6efee75e610d2df5116421ac13bc4b9f8520.pdf http://pdfs.semanticscholar.org/b02f/6efee75e610d2df5116421ac13bc4b9f8520.pdf]

​

* [http://arc.aiaa.org/doi/pdf/10.2514/6.2007-6550 http://arc.aiaa.org/doi/pdf/10.2514/6.2007-6550],

: [http://dx.doi.org/10.2514/6.2007-6550 http://dx.doi.org/10.2514/6.2007-6550]

​

* [http://www.optisyn.com/research/publications/2007/TandaleEstimation2007.pdf http://www.optisyn.com/research/publications/2007/TandaleEstimation2007.pdf],

: [https://academic.microsoft.com/#/detail/2325051263 https://academic.microsoft.com/#/detail/2325051263]

​