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dc.contributor.authorFoss, Gregen_US
dc.contributor.authorMcGovern, Amyen_US
dc.contributor.authorPotvin, Coreyen_US
dc.contributor.authorAbram, Gregen_US
dc.contributor.authorBowen, Anneen_US
dc.contributor.authorHulkoti, Neenaen_US
dc.contributor.authorKaul, Arnaven_US
dc.contributor.editorEnrico Gobbetti and Wes Bethelen_US
dc.date.accessioned2016-06-09T09:43:28Z
dc.date.available2016-06-09T09:43:28Z
dc.date.issued2016en_US
dc.identifier.isbn978-3-03868-006-2en_US
dc.identifier.issn1727-348Xen_US
dc.identifier.urihttp://dx.doi.org/10.2312/pgv.20161186en_US
dc.identifier.urihttps://diglib.eg.org:443/handle/10
dc.description.abstractWe investigate the value of 3-D visualization to data mining techniques for identifying tornadogenesis precursors in supercell thunderstorm simulations. We've found results will assist defining storm objects extracted and input to the data mining. The video shows samples of updrafts, downdrafts, cold pools, and regions of strong vorticity.en_US
dc.publisherThe Eurographics Associationen_US
dc.titleData Mining Tornadogenesis Precursorsen_US
dc.description.seriesinformationEurographics Symposium on Parallel Graphics and Visualizationen_US
dc.description.sectionheadersVisualization Showcaseen_US
dc.identifier.doi10.2312/pgv.20161186en_US
dc.identifier.pages99-99en_US


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