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| Titel |
Forecasting Low-Visibility Conditions at Vienna Airport with Tree-Based Statistical Models |
| VerfasserIn |
Sebastian Dietz, Philipp Kneringer, Georg J. Mayr, Achim Zeileis |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250132240
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| Publikation (Nr.) |
 EGU/EGU2016-12729.pdf |
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| Zusammenfassung |
| Low visibility conditions at airports can lead to capacity problems and therefore to delays or
cancelation of arriving and departing airplanes. To keep the capacity as high as
possible, accurate visibility forecasts are required. Therefore tree-based statistical
nowcasting models were developed, which split the data in the sense of decision rules
by recursive partitioning. Benefits of this models are fast update cycles and low
computation times. Highly-resolved meteorological observation data at the airport form
the large pool of input variables for the models. In this study we identify the most
important predictors for different lead times to create the most accurate forecasts. |
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