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dc.contributor.advisorDurkee, Philip A.
dc.contributor.authorHarris, Ryan J.
dc.date.accessioned2012-03-14T17:45:17Z
dc.date.available2012-03-14T17:45:17Z
dc.date.issued2010-03
dc.identifier.urihttp://hdl.handle.net/10945/5393
dc.descriptionApproved for public release; distribution is unlimiteden_US
dc.description.abstractA cumulus cloud field may develop within a conditionally unstable environment, but only a fraction of the cumulus elements eventually develop into thunderstorms. Determining which of these convective elements is most likely to generate lightning--a critical need for the aviation community and Department of Defense--often starts with little more than a qualitative visual satellite analysis. To protect personnel and property, lightning nowcast tools (e.g., an automated geostationary satellite-based Lightning Initiation (LI) algorithm) require measurable research. This work quantifies the behavior of ten previously identified Geostationary Operational Environmental Satellite (GOES-12) Infrared (IR) Interest Fields (IFs) in the hour before LI. A total of 172 lightning-producing storms that occurred during the 2009 convective season are manually tracked and studied over four regions--Northern Alabama, Oklahoma, Kennedy Space Center and Washington D.C. Four-dimensional and cloud-to-ground lightning arrays provide precise lightning initiation points for each storm in both time and space. Individual tendencies are identified for the ten LI IFs. Statistical significance tests are conducted to determine the potential predictive capability and regional dependence of each IF. This study found that eight out of ten LI IFs exhibited at least 15 minutes of potential predictive capability and 35 minutes on average. Additionally, eight out of ten fields can likely be applied across a large geographical area with minimal error. Future operational applications identified and briefly explored in this work include the use of a lightning probability optimization tool.en_US
dc.description.urihttp://archive.org/details/optimizationndst109455393
dc.format.extentxx, 103 p. : ill. (some col.), 1 col. map ;en_US
dc.publisherMonterey, California. Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, may not be copyrighted.en_US
dc.subject.lcshMeteorologyen_US
dc.subject.lcshLightningen_US
dc.subject.lcshThunderen_US
dc.titleOptimization and statistical evaluation of GOES cloud-top properties for nowcasting lightning initiationen_US
dc.typeThesisen_US
dc.contributor.secondreaderNielsen, Kurt E.
dc.contributor.corporateNaval Postgraduate School (U.S.)
dc.contributor.departmentMeteorology
dc.description.recognitionOutstanding Thesisen_US
dc.description.serviceUS Air Force (USAF) authoren_US
dc.identifier.oclc609710573
etd.thesisdegree.nameM.S.en_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineMeteorologyen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
etd.verifiednoen_US


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