Crowdsourcing the El Reno 2013 Tornado: A New Approach for Collation and Display of Storm Chaser Imagery for Scientific Applications
| Autor: | Anton Seimon, Tracie A. Seimon, David K. Hoadley, Skip J. Talbot, John T. Allen |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Lightning detection
Atmospheric Science 010504 meteorology & atmospheric sciences Meteorology business.industry 0208 environmental biotechnology Storm 02 engineering and technology Crowdsourcing 01 natural sciences Lightning 020801 environmental engineering law.invention Metadata Geography law Collation Georeference Tornado business 0105 earth and related environmental sciences |
| Zdroj: | Bulletin of the American Meteorological Society. 97:2069-2084 |
| ISSN: | 1520-0477 0003-0007 |
| DOI: | 10.1175/bams-d-15-00174.1 |
| Popis: | The 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. |
| Databáze: | OpenAIRE |
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