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https://doi.org/10.1117/12.220...
Article . 2015 . Peer-reviewed
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Forecast of extreme weather conditions that promote aircraft icing during take-off or landing

Authors: Sitnikov, Grigoriy I.; Terenteva, Maria V.; Barashkova, Nadezhda K.; Volkova, Marina A.; Kuzhevskaya, Irina V.; Kizhner, Lubov I.; Starchenko, Alexander V.;

Forecast of extreme weather conditions that promote aircraft icing during take-off or landing

Abstract

This work presents the results of forecasting meteorological conditions that promote aircrafts icing in the atmospheric boundary layer; the forecasting results were obtained based on mesoscale meteorological model TSU-NM3. Godske formula which is based on the calculation of saturation temperature above ice, NCEP method, and statistical method of Hydrometeorological Centre of Russia were used as criteria of probability of aircraft icing during take-off or landing. Numeric forecast results were compared with physical observations made in the atmospheric boundary layer in October 2012 at the Tomsk airport. A good agreement obtained provided an opportunity to be certain about the above approach viability.

Keywords

численное прогнозирование, обледенение, мезомасштабные модели, метеорологические прогнозы

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green