Abstract

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Best paper award in Weather session at the 36th DASC - Digital Avionics Systems Conference State-of-the-art weather data obtained from numerical weather predictions are unlikely to satisfy the requirements of the future air traffic management system. A potential approach to improve the resolution and accuracy of the weather predictions could consist on using airborne aircraft as meteorological sensors, which would provide up-to-date weather observations to the sur- rounding aircraft and ground systems. This paper proposes to use Kriging, a geostatistical interpolation technique, to create short- term weather predictions from scattered weather observations derived from surveillance data. Results show that this method can accurately capture the spatio-temporal distribution of the temperature and wind fields, allowing to obtain high-quality local, short-term weather predictions and providing at the same time a measure of the uncertainty associated with the prediction. Peer Reviewed Award-winning Document type: Conference object