Climatological Tools for Low Visibility Forecasting |
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| Authors: | Otto Hyvärinen Jukka Julkunen Vesa Nietosvaara |
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| Institution: | (1) Finnish Meteorological Institute, Remote Sensing for Weather Applications, Helsinki, Finland;(2) Finnish Meteorological Institute, Aviation and Military Weather Service, Rovaniemi, Finland;(3) Finnish Meteorological Institute, Remote Sensing for Weather Applications, Turku, Finland |
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| Abstract: | Forecasters need climatological forecasting tools because of limitations of numerical weather prediction models. In this article,
using Finnish SYNOP observations and ERA-40 model reanalysis data, low visibility cases are studied using subjective and objective
analysis techniques. For the objective analysis, we used an AutoClass clustering algorithm, concentrating on three Finnish
airports, namely, the Rovaniemi in northern Finland, Kauhava in western Finland, and Maarianhamina in southwest Finland. These
airports represent different climatological conditions. Results suggested that combining of subjective analysis with an objective
analysis, e.g., clustering algorithms such as the AutoClass method, can be used to construct climatological guides for forecasters.
Some higher level subjective “meta-clustering” was used to make the results physically more reasonable and easier to interpret
by the forecasters. |
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| Keywords: | Low visibility fog clustering forecast model reanalysis |
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