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Statistical, quantitative probability and nowcasting forecasting methods of severe convective storms

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dc.title Statistical, quantitative probability and nowcasting forecasting methods of severe convective storms 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 607
dc.citation.epage 618
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 Meteorological radars en
dc.subject NWP models en
dc.subject Statistics en
dc.subject Weather forecasting en
dc.description.abstract This paper deals with the comparison of the statistical, quantitative and nowcasting method of prediction of convective precipitation and the risk of flood floods, which are the main outputs calculated by the Algorithm of Storm Prediction. The evaluation of the success of these outputs was carried out on the basis of verified 63 thunderstorms and three floods that affected the Zlín Region between 2015 and 2017. The first part of the article focuses on the description and evaluation of the predictive outputs of the quantitative prediction of the probability of the occurrence and the intensity of convective precipitation computed from NWP models. At the same time, these outcomes are compared with the outputs of the statistical and nowcasting predictions of convective precipitation. The statistical prediction of convective precipitation is calculated on the selection of the predicted and historical situation from the statistics database. The nowcasting prediction works with the outputs of the MMR50 X-band meteorological radar of the Zlín Region. The second part explores the use of track storms for statistical prediction, which is intended as an indicative and complementary forecast for the method of quantitative prediction of precipitation. The conclusion of the two chapters is a comparison of the success of the predicted outputs of methods, which can be used and put into practice in particular for the prediction of convective precipitation and the risk of floods for purposes of warning and meteorological services and crisis management. © 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/10563/1008491
utb.identifier.obdid 43878865
utb.identifier.scopus 2-s2.0-85061254350
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.scopus.affiliation Regional research centre CEBIA-Tech, Tomas Bata University in Zlin, Faculty of Applied Informatics, Nad Stranemi 4511, Zlin, 760 05, Czech Republic
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Attribution 4.0 International Except where otherwise noted, this item's license is described as Attribution 4.0 International