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Conference Paper: Identifying weather systems from numerical weather prediction data

TitleIdentifying weather systems from numerical weather prediction data
Authors
Issue Date2006
Citation
Proceedings - International Conference On Pattern Recognition, 2006, v. 4, p. 841-844 How to Cite?
AbstractWeather systems such as tropical cyclones, fronts, troughs and ridges affect our daily lives. Yet, they are often manually located and drawn on weather charts based on forecasters' experience. To identify them, multiple atmospheric elements need to be considered, and the results may vary among forecasters. In this paper, we contribute to the fields of pattern recognition and meteorological computing by designing a generic model of weather systems, along with a genetic algorithm-based framework for finding them from multidimensional numerical weather prediction data. It was found that our method not only can locate weather systems with 80% to 100% precision, but also discover features that could indicate the genesis or dissipation of such systems that could be ignored by forecasters. © 2006 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/93075
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorWong, KYen_HK
dc.contributor.authorYip, CLen_HK
dc.contributor.authorLi, PWen_HK
dc.date.accessioned2010-09-25T14:50:08Z-
dc.date.available2010-09-25T14:50:08Z-
dc.date.issued2006en_HK
dc.identifier.citationProceedings - International Conference On Pattern Recognition, 2006, v. 4, p. 841-844en_HK
dc.identifier.issn1051-4651en_HK
dc.identifier.urihttp://hdl.handle.net/10722/93075-
dc.description.abstractWeather systems such as tropical cyclones, fronts, troughs and ridges affect our daily lives. Yet, they are often manually located and drawn on weather charts based on forecasters' experience. To identify them, multiple atmospheric elements need to be considered, and the results may vary among forecasters. In this paper, we contribute to the fields of pattern recognition and meteorological computing by designing a generic model of weather systems, along with a genetic algorithm-based framework for finding them from multidimensional numerical weather prediction data. It was found that our method not only can locate weather systems with 80% to 100% precision, but also discover features that could indicate the genesis or dissipation of such systems that could be ignored by forecasters. © 2006 IEEE.en_HK
dc.languageengen_HK
dc.relation.ispartofProceedings - International Conference on Pattern Recognitionen_HK
dc.titleIdentifying weather systems from numerical weather prediction dataen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailWong, KY:kywong@cs.hku.hken_HK
dc.identifier.emailYip, CL:clyip@cs.hku.hken_HK
dc.identifier.authorityWong, KY=rp00187en_HK
dc.identifier.authorityYip, CL=rp00205en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ICPR.2006.677en_HK
dc.identifier.scopuseid_2-s2.0-33750733436en_HK
dc.identifier.hkuros120787en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33750733436&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume4en_HK
dc.identifier.spage841en_HK
dc.identifier.epage844en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridWong, KY=7404759205en_HK
dc.identifier.scopusauthoridYip, CL=7101665547en_HK
dc.identifier.scopusauthoridLi, PW=27171545800en_HK

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