Crowdsourcing the El Reno 2013 Tornado: A New Approach for Collation and Display of Storm Chaser Imagery for Scientific ApplicationsSource: Bulletin of the American Meteorological Society:;2016:;volume( 097 ):;issue: 011::page 2069DOI: 10.1175/BAMS-D-15-00174.1Publisher: American Meteorological Society
Abstract: he 31 May 2013 El Reno, Oklahoma, tornado is used to demonstrate how a video imagery database crowdsourced from storm chasers can be time-corrected and georeferenced to inform severe storm research. The tornado?s exceptional magnitude (?4.3-km diameter and ?135 m s?1 winds) and the wealth of observational data highlight this storm as a subject for scientific investigation. The storm was documented by mobile research and fixed-base radars, lightning detection networks, and poststorm damage surveys. In addition, more than 250 individuals and groups of storm chasers navigating the tornado captured imagery, constituting a largely untapped resource for scientific investigation.The El Reno Survey was created to crowdsource imagery from storm chasers and to compile submitted materials in a quality-controlled, open-access research database. Solicitations to storm chasers via social media and e-mail yielded 93 registrants, each contributing still and/or video imagery and metadata. Lightning flash interval is used for precise time calibration of contributed video imagery; when combined with georeferencing from open-source geographical information software, this enables detailed mapping of storm phenomena. A representative set of examples is presented to illustrate how this standardized database and a web-based visualization tool can inform research on tornadoes, lightning, and hail. The project database offers the largest archive of visual material compiled for a single storm event, accessible to the scientific community through a registration process. This approach also offers a new model for poststorm data collection, with instructional materials created to facilitate replication for research into both past and future storm events.
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| contributor author | Seimon, Anton | |
| contributor author | Allen, John T. | |
| contributor author | Seimon, Tracie A. | |
| contributor author | Talbot, Skip J. | |
| contributor author | Hoadley, David K. | |
| date accessioned | 2017-06-09T16:46:08Z | |
| date available | 2017-06-09T16:46:08Z | |
| date copyright | 2016/11/01 | |
| date issued | 2016 | |
| identifier issn | 0003-0007 | |
| identifier other | ams-73752.pdf | |
| identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4215901 | |
| description abstract | he 31 May 2013 El Reno, Oklahoma, tornado is used to demonstrate how a video imagery database crowdsourced from storm chasers can be time-corrected and georeferenced to inform severe storm research. The tornado?s exceptional magnitude (?4.3-km diameter and ?135 m s?1 winds) and the wealth of observational data highlight this storm as a subject for scientific investigation. The storm was documented by mobile research and fixed-base radars, lightning detection networks, and poststorm damage surveys. In addition, more than 250 individuals and groups of storm chasers navigating the tornado captured imagery, constituting a largely untapped resource for scientific investigation.The El Reno Survey was created to crowdsource imagery from storm chasers and to compile submitted materials in a quality-controlled, open-access research database. Solicitations to storm chasers via social media and e-mail yielded 93 registrants, each contributing still and/or video imagery and metadata. Lightning flash interval is used for precise time calibration of contributed video imagery; when combined with georeferencing from open-source geographical information software, this enables detailed mapping of storm phenomena. A representative set of examples is presented to illustrate how this standardized database and a web-based visualization tool can inform research on tornadoes, lightning, and hail. The project database offers the largest archive of visual material compiled for a single storm event, accessible to the scientific community through a registration process. This approach also offers a new model for poststorm data collection, with instructional materials created to facilitate replication for research into both past and future storm events. | |
| publisher | American Meteorological Society | |
| title | Crowdsourcing the El Reno 2013 Tornado: A New Approach for Collation and Display of Storm Chaser Imagery for Scientific Applications | |
| type | Journal Paper | |
| journal volume | 97 | |
| journal issue | 11 | |
| journal title | Bulletin of the American Meteorological Society | |
| identifier doi | 10.1175/BAMS-D-15-00174.1 | |
| journal fristpage | 2069 | |
| journal lastpage | 2084 | |
| tree | Bulletin of the American Meteorological Society:;2016:;volume( 097 ):;issue: 011 | |
| contenttype | Fulltext |