Classification of Synoptic Conditions of Summer Floods in Polish Sudeten Mountains

Atmospheric processes leading to extreme floods in the Polish Sudeten Mountains were described in this study. A direct impact of heavy precipitation on extremely high runoff episodes was confirmed, and an essential role of synoptic conditions in triggering abundant rainfall was proved. Synoptic cond...

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Bibliographic Details
Main Authors: Ewa Bednorz, Dariusz Wrzesiński, Arkadiusz M. Tomczyk, Dominika Jasik
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Water
Subjects:
Online Access:https://www.mdpi.com/2073-4441/11/7/1450
Description
Summary:Atmospheric processes leading to extreme floods in the Polish Sudeten Mountains were described in this study. A direct impact of heavy precipitation on extremely high runoff episodes was confirmed, and an essential role of synoptic conditions in triggering abundant rainfall was proved. Synoptic conditions preceding each flood event were taken into consideration and the evolution of the pressure field as well as the moisture transport was investigated using the anomaly-based method. Maps of anomalies, constructed for the days prior to floods, enabled recognizing an early formation of negative centers of sea level pressure and also allowed distinguishing areas of positive departures of precipitable water content over Europe. Five cyclonic circulation patterns of different origin, and various extent and intensity, responsible for heavy, flood-triggering precipitation in the Sudetes, were assigned. Most rain-bringing cyclones form over the Mediterranean Sea and some of them over the Atlantic Ocean. A meridional southern transport of moisture was identified in most of the analyzed cases of floods. Recognizing the specific meteorological mechanisms of precipitation enhancement, involving evolution of pressure patterns, change in atmospheric moisture and occurrence of precipitation may contribute to a better understanding of the atmospheric forcing of floods in mountain areas and to improve predicting thereof.
ISSN:2073-4441