Automated classification of rainfall systems using statistical characterization.

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dc.contributor.advisorCarr, Frederick H.,en_US
dc.contributor.authorBaldwin, Michael Eugene.en_US
dc.date.accessioned2013-08-16T12:18:59Z
dc.date.available2013-08-16T12:18:59Z
dc.date.issued2003en_US
dc.description.abstractA general, completely automated procedure for classifying rainfall systems is developed. The technique is flexible and universally applicable, in that any rainfall system can be classified regardless of size, location, time of day or year, degree of organization, etc. The knowledge obtained from previous research was used to develop a relatively straightforward and unique classification system. To test the performance of the method, results were validated against a subjective classification based upon objective criteria. From an independent random sample, the automated classification system accurately placed events into stratiform, linear, and cellular classes 85% of the time.en_US
dc.format.extentxxi, 195 leaves :en_US
dc.identifier.urihttp://hdl.handle.net/11244/609
dc.noteAdviser: Frederick H. Carr.en_US
dc.noteSource: Dissertation Abstracts International, Volume: 64-03, Section: B, page: 1290.en_US
dc.subjectGeophysics.en_US
dc.subjectData mining.en_US
dc.subjectRain and rainfall.en_US
dc.subjectPhysics, Atmospheric Science.en_US
dc.subjectPrecipitation (Meteorology)en_US
dc.thesis.degreePh.D.en_US
dc.thesis.degreeDisciplineSchool of Meteorologyen_US
dc.titleAutomated classification of rainfall systems using statistical characterization.en_US
dc.typeThesisen_US
ou.groupCollege of Atmospheric & Geographic Sciences::School of Meteorology
ou.identifier(UMI)AAI3085711en_US

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