TBU Publications
Repository of TBU Publications

Success rate evaluation of severe storm phenomena and flash floods forecasting

DSpace Repository

Show simple item record


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 http://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
Find Full text

Files in this item

Show simple item record

Attribution 4.0 International Except where otherwise noted, this item's license is described as Attribution 4.0 International