{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/129975"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/129975","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Tornado track deviation: a possible approach to statistical warnings","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. 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The submission was exported from vireo on 2025-10-20 without embargo terms","The student, Jessica Skocinski, accepted the attached license on 2025-07-22 at 11:29.","The student, Jessica Skocinski, submitted this Thesis for approval on 2025-07-22 at 11:39.","This Thesis was approved for publication on 2025-07-25 at 11:26.","DSpace SAF Submission Ingestion Package generated from Vireo submission #22691 on 2025-10-20 at 20:15:39","Current warning strategies for tornadoes have significant spatial inefficiencies owing to uncertainty in tornado movement. Quantifying the historical deviation of tornado tracks in a given storm environment may allow for multiple warning probabilities and could decrease false alarm ratios while increasing effective lead time in warnings. Prior literature on this topic has been limited to small sample sizes investigating singular tornadoes or tornado outbreaks. Tornado tracks obtained from the Tornado Archive are correlated with storm mode and meteorological model data and plotted in a novel method allowing for statistical comparisons of tracks. Results quantify that tornadoes in environments with low storm-relative helicity move more erratically and therefore less predictably than tornadoes in environments with high storm-relative helicity."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Tornado track deviation: a possible approach to statistical warnings"]}]}],"canonical_facts":{"dc:contributor":["Jewett, Brian"],"dc:creator":["Skocinski, Jessica Olivia"],"dc:date":["2025-07-25","2025-08"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo terms","The student, Jessica Skocinski, accepted the attached license on 2025-07-22 at 11:29.","The student, Jessica Skocinski, submitted this Thesis for approval on 2025-07-22 at 11:39.","This Thesis was approved for publication on 2025-07-25 at 11:26.","DSpace SAF Submission Ingestion Package generated from Vireo submission #22691 on 2025-10-20 at 20:15:39","Current warning strategies for tornadoes have significant spatial inefficiencies owing to uncertainty in tornado movement. Quantifying the historical deviation of tornado tracks in a given storm environment may allow for multiple warning probabilities and could decrease false alarm ratios while increasing effective lead time in warnings. Prior literature on this topic has been limited to small sample sizes investigating singular tornadoes or tornado outbreaks. Tornado tracks obtained from the Tornado Archive are correlated with storm mode and meteorological model data and plotted in a novel method allowing for statistical comparisons of tracks. Results quantify that tornadoes in environments with low storm-relative helicity move more erratically and therefore less predictably than tornadoes in environments with high storm-relative helicity."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/129975"],"dc:language":["en","eng"],"dc:rights":["Copyright 2025 Jessica Skocinski"],"dc:subject":["Tornado","Severe Weather","Meteorology"],"dc:title":["Tornado track deviation: a possible approach to statistical warnings"],"dc:type":["text"],"thesis:degree_discipline":["Atmospheric Sciences"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:06Z"}