Constructing a Supercell Database in Spain Using Publicly Available Two-Dimensional Radar Images and Citizen Science
Bibliographic Data
| ID | 3151817 |
|---|---|
| Authors | Yago Martins (0000-0002-0375-8971, University of Central Florida), Miguel Cívica (Agencia Estatal de Meteorología), Erika Pham, Erika O Pham (University of South Carolina) |
| Year | 2021 |
| Volume | 111 |
| Issue | 5 |
| Pages | 1346-1366 |
| Publication date | 2021-07-29 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Annals of the American Association of Geographers (JOURNAL) |
| Journal identifiers | ISSN: 2469-4452 • E-ISSN: 2469-4460 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/24694452.2020.1812371 |
| OpenAlex | W3102313980 |
| Language | EN |
| References cited | 51 |
Supercell thunderstorms are often associated with severe weather conditions, such as tornadoes, hail, strong wind gusts, and heavy rainfall, bringing about potentially significant consequences to populations and assets. Despite potential impacts, a lack of publicly available data has hindered the analysis and characterization of supercell climatology in Spain. We address this problem through a volunteered, collaborative, public effort to develop a database on supercell events from January 2014 through December 2019. Using multiple inclusion criteria and validation steps, we identified 703 thunderstorms with supercell characteristics during the six-year study period. With public participation, we were able to confirm 20.5 percent of the medium-high confidence supercells identified by two-dimensional radar images. Further analyses reveal a spatial distribution with a high degree of activity in the eastern half of Spain, primarily the Mediterranean and northeastern regions. Our data and results show the value of citizen science and public participation and could serve as a foundation for more thorough and sophisticated climatological investigation
Climatology · Database · Geography · Meteorology · Nowcasting · Supercell · Thunderstorm · Tornado · Computer Science · Flood Risk Assessment and Management · Meteorological Phenomena and Simulations · Precipitation Measurement and Analysis · Geology
| Highly cited | No |
|---|