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dc.title | Success rate evaluation of severe storm phenomena and flash floods forecasting | en |
dc.contributor.author | Šaur, David | |
dc.relation.ispartof | WSEAS Transactions on Environment and Development | |
dc.identifier.issn | 1790-5079 Scopus Sources, Sherpa/RoMEO, JCR | |
dc.date.issued | 2018 | |
utb.relation.volume | 14 | |
dc.citation.spage | 548 | |
dc.citation.epage | 560 | |
dc.type | article | |
dc.language.iso | en | |
dc.publisher | World Scientific and Engineering Academy and Society (WSEAS) | |
dc.subject | Convective storm | en |
dc.subject | Crisis management | en |
dc.subject | Flash floods | en |
dc.subject | Hailstorm | en |
dc.subject | Meteorological radars | en |
dc.subject | NWP models | en |
dc.subject | Strong wind gusts | en |
dc.subject | Torrential rainfall | en |
dc.subject | Weather forecasting | en |
dc.description.abstract | This article focuses on proposal new methods to predict strong convective storms that can cause flash floods. Flash flood is determined by the interaction of a number of factors such as the very intense convective precipitation (torrential rainfall accompanied by hail and strong wind gusts), slow motion of convective storms and the soil saturation. These factors have been included in the Algorithm of Storm Prediction, whose prediction results are presented in the two outcome of this article. The result section contains an assessment of the success rate of predictions of convective precipitation and storm intensity, which is complemented by the evaluation of the prediction success rate of severe storm phenomena. Primarily, the goal of the algorithm is to provide predictive information about risk of flash floods that comprise all the above mentioned outputs. Secondarily, the orieintally overview of other forecast outputs is part of the second result section. © 2018, World Scientific and Engineering Academy and Society. All rights reserved. | en |
utb.faculty | Faculty of Applied Informatics | |
dc.identifier.uri | http://hdl.handle.net/10563/1008489 | |
utb.identifier.obdid | 43878864 | |
utb.identifier.scopus | 2-s2.0-85061271975 | |
utb.source | j-scopus | |
dc.date.accessioned | 2019-07-08T11:59:51Z | |
dc.date.available | 2019-07-08T11:59:51Z | |
dc.rights | Attribution 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.rights.access | openAccess | |
utb.ou | CEBIA-Tech | |
utb.contributor.internalauthor | Šaur, David | |
utb.fulltext.affiliation | DAVID ŠAUR Regional research centre CEBIA-Tech Tomas Bata University in Zlin Faculty of Applied Informatics, Nad Stranemi 4511,760 05, Zlin CZECH REPUBLIC saur@utb.cz | |
utb.fulltext.dates | - | |
utb.scopus.affiliation | Regional research centre CEBIA-Tech, Tomas Bata University in Zlin, Faculty of Applied Informatics, Nad Stranemi 4511, Zlin, 760 05, Czech Republic | |
utb.fulltext.faculty | Faculty of Applied Informatics | |
utb.fulltext.ou | CEBIA-Tech |