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Moisture fluxes conducive to central European extreme precipitation events
- 1.0536346 - ÚFA 2022 RIV NL eng J - Journal Article
Gvoždíková, B. - Müller, Miloslav
Moisture fluxes conducive to central European extreme precipitation events.
Atmospheric Research. Roč. 248, Jan 15 (2021), č. článku 105182. ISSN 0169-8095. E-ISSN 1873-2895
R&D Projects: GA ČR(CZ) GA19-05011S
Institutional support: RVO:68378289
Keywords : heavy precipitation * vb cyclones * august 2002 * floods * windstorms * transport * anomalies * episodes * example * weather * Moisture flux * Vertical velocity * Extreme precipitation * Central Europe
OECD category: Meteorology and atmospheric sciences
Impact factor: 5.965, year: 2021
Method of publishing: Limited access
https://www.sciencedirect.com/science/article/pii/S0169809520311182
For the emergence of central European extreme precipitation events (EPEs), moisture supply mainly from the Atlantic or Mediterranean and an ascent of moist air are the most important ingredients. In the present study, we aim to define groups of EPEs with characteristic moisture flux conditions in the area of extra high upward vertical velocity, as well as to find the connection between the variants of moisture flux conditions and the spatio-seasonal distribution of extreme precipitation. Using ERA5 reanalysis data, we assigned one of three moisture flux variants to the set of 43 EPEs from 1979 to 2013 and thus specified (i) events with dominating moisture flux from the north (Nf), (ii) events with dominating moisture flux from the west (Wf), and (iii) other low-flux events (Ot). The classification of EPEs corresponds perfectly with seasonal and spatial patterns of extreme precipitation: while Nf events were concentrated only in the warm half-year and affected mainly eastern central Europe, Wf events occurred in the west and exclusively from September to March. Mainly in the case of Nf events, a direct link existing between anomalies in moisture flux and precipitation extremes can be beneficial for improving skill in forecasting EPEs.
Permanent Link: http://hdl.handle.net/11104/0314124
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