Please use this identifier to cite or link to this item: https://doi.org/10.1144/SP361.15
DC FieldValue
dc.titleExploratory spatial analysis of typhoon characteristics in the North Pacific basin
dc.contributor.authorFeng, C.-C.
dc.contributor.authorTerry, J.P.
dc.date.accessioned2014-04-02T08:18:04Z
dc.date.available2014-04-02T08:18:04Z
dc.date.issued2012
dc.identifier.citationFeng, C.-C.,Terry, J.P. (2012). Exploratory spatial analysis of typhoon characteristics in the North Pacific basin. Geological Society Special Publication 361 (1) : 187-194. ScholarBank@NUS Repository. <a href="https://doi.org/10.1144/SP361.15" target="_blank">https://doi.org/10.1144/SP361.15</a>
dc.identifier.issn03058719
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/49727
dc.description.abstractThis paper analyses the spatial pattern of three tropical storm migratory behaviour parameters - track sinuosity, minimum pressure and duration of intense typhoons. The besttrack data of the western North Pacific basin archived by the Regional Specialized Meteorological Center in Tokyo were used. The local Getis-Ord G* i(d) statistic (where d is distance) was employed in a geographical information system (GIS) environment to identify clusters of hot spots and cold spots of the three parameters. The analysis of storm-track sinuosity identified one dominant hot-spot cluster of sinuously tracking storms far from the continental margins of the North Pacific Ocean, with three small cold-spot clusters of straight-tracking storms relatively close to mainland SE Asia. The analysis of the second and third parameters revealed extensive overlap between the cluster of very intense typhoons (i.e. hot-spot cluster of minimum pressure, mean 926 hPa) and the cluster of long-duration typhoons (i.e. hot-spot cluster of duration at typhoon intensity, mean 5.4 days). The findings suggest that the Philippines and the Northern Marianas Islands are vulnerable to strike by both longer-lived and extremely violent typhoons. Overall, the technique highlights the strong potential for statistical clustering analysis to visualize and understand geospatial patterns in typhoon meteorological characteristics. © The Geological Society of London 2012.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1144/SP361.15
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentGEOGRAPHY
dc.description.doi10.1144/SP361.15
dc.description.sourcetitleGeological Society Special Publication
dc.description.volume361
dc.description.issue1
dc.description.page187-194
dc.identifier.isiutNOT_IN_WOS
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