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dc.contributor.authorTrabing, Benjamin
dc.contributor.authorKnaff, John A.
dc.contributor.authorSchumacher, Andrea
dc.contributor.authorMusgrave, Kate
dc.contributor.authorDemaria, Mark
dc.date.accessioned2016-05-13T20:52:41Z
dc.date.available2016-05-13T20:52:41Z
dc.date.issued2016
dc.identifier.urihttps://hdl.handle.net/11244.46/70
dc.description.abstractThe new GOES-R satellite will be equipped with the Geostationary Lightning Mapper (GLM) that will provide unprecedented total lightning data with the potential to improve hurricane intensity forecasts. Past studies have provided conflicting interpretations of the role that lightning plays in forecasting tropical cyclone (TC) intensity changes. With the goal of improving the usefulness of total lightning, detailed case studies were conducted of five TCs that underwent rapid intensification (RI) within the domains of two unique ground-based long-range lightning detection networks, the World Wide Lightning Location Network (WWLLN) and Earth Networks Total Lightning Network (ENTLN). This analysis will provide greater details of the distribution of lightning within predefined storm features to highlight specific phenomena that large statistical studies cannot resolve.en_US
dc.description.abstractBoth WWLLN and ENTLN datasets showed similar spatial and temporal patterns in lightning that validates the independent use of either network for analysis. For the cases examined, a maxima in eyewall lightning was located downshear and in the front-right quadrants relative to storm motion. Results show that RI follows a burst of lightning in the eyewall when coinciding with a period of little environmental vertical shear. Eyewall lightning would cycle with greater frequency during intensification compared to weakening. Bursts of lightning were observed in the eyewall just prior to eye formation in both the infrared and microwave imagery. Eyewall lightning bursts in low shear environments could be used to indicate intensification and improve forecasts.en_US
dc.description.sponsorshipUniversity Libraries Undergraduate Research Awarden_US
dc.language.isoen_USen_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectGeostationary Lightning Mapperen_US
dc.subjecthurricane intensity forecastsen_US
dc.subjectWorld Wide Lightning Location Networken_US
dc.subjectEarth Networks Total Lightning Networken_US
dc.subjectUniversity Libraries Undergraduate Research Awarden_US
dc.titleAnalysis of Hurricanes Using Long-Range Lightning Detection Networksen_US
dc.typeOtheren_US


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Attribution-NonCommercial-ShareAlike 3.0 United States
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-ShareAlike 3.0 United States