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dc.contributor.advisorFox, Neil I. (Neil Ian)eng
dc.contributor.authorLack, Steven A., 1979-eng
dc.date.issued2007eng
dc.date.submitted2007 Falleng
dc.descriptionThe entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.eng
dc.descriptionTitle from title screen of research.pdf file (viewed on March 11, 2008)eng
dc.descriptionThesis (Ph. D.) University of Missouri-Columbia 2007.eng
dc.description.abstract[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] The use of object-oriented approaches in both the verification of meteorological variables (especially precipitation) and the short-term forecasting of storms (nowcasting) has recently expanded. This two-part dissertation addresses the issue of verification and the possible nowcasting application of using shape analysis. Part one deals with a newly developed object-oriented verification tool using Procrustes shape analysis methodology. Using the Procrustes verification tool, the examination of the errors of matched truth and forecast objects for the different nowcasts can be assessed via a penalty function. This penalty function is based on errors in translation, rotation, dilation, shape, and intensity of a forecast object and, as these penalties can be assessed separately, the mode of the error in the forecast can be determined. Part two deals with the potential to classify convective storm cells based on shape characteristics combined with radar-derived products and near-storm environmental (NSE) data. Obtaining radar-derived products and NSE data from the Warning Decision Support System-Integrated Information (WDSS-II) system allows for fields of data to be easily overlaid for an identifiable cell in a domain. The ability to use this data overlay with classification trees may result in the ability to add physical information to a nowcast system for growth, decay, and morphology as well as provide grounds for correctly matching storm cells in an object-oriented verification technique.eng
dc.description.bibrefIncludes bibliographical referenceseng
dc.identifier.merlinb62634951eng
dc.identifier.oclc213340119eng
dc.identifier.urihttps://doi.org/10.32469/10355/6017eng
dc.identifier.urihttps://hdl.handle.net/10355/6017
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcommunityUniversity of Missouri--Columbia. Graduate School. Theses and Dissertationseng
dc.rightsAccess is limited to the campuses of the University of Missouri.eng
dc.subject.lcshWeather forecastingeng
dc.subject.lcshProbability forecasts (Meteorology)eng
dc.subject.lcshObject-oriented methods (Computer science)eng
dc.subject.lcshPrecipitation (Meteorology)eng
dc.titleCell identification, verification, and classification using shape analysis techniqueseng
dc.typeThesiseng
thesis.degree.disciplineSoil, environmental and atmospheric sciences (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelDoctoraleng
thesis.degree.namePh. D.eng


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