Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/180171 
Erscheinungsjahr: 
2017
Schriftenreihe/Nr.: 
Working Papers in Economics and Statistics No. 2017-21
Verlag: 
University of Innsbruck, Research Platform Empirical and Experimental Economics (eeecon), Innsbruck
Zusammenfassung: 
Airport operations are sensitive to visibility conditions. Low-visibility events may lead to capacity reduction, delays and economic losses. Different levels of low-visibility procedures (lvp) are enacted to ensure aviation safety. A nowcast of the probabilities for each of the lvp categories helps decision makers to optimally schedule their operations. An ordered logistic regression (OLR) model is used to forecast these probabilities directly. It is applied to cold season forecasts at Vienna International Airport for lead times of 30-min out to two hours. Model inputs are standard meteorological measurements. The skill of the forecasts is accessed by the ranked probability score. OLR outperforms persistence, which is a strong contender at the shortest lead times. The ranked probability score of the OLR is even better than the one of nowcasts from human forecasters. The OLR-based nowcasting system is computationally fast and can be updated instantaneously when new data become available.
Schlagwörter: 
aviation meteorology
low visibility
probabilistic nowcasting
statistical forecasts
ordered logistic regression
Dokumentart: 
Working Paper

Datei(en):
Datei
Größe
477.51 kB





Publikationen in EconStor sind urheberrechtlich geschützt.