Variability of weather conditions in the temperate zone is mainly related to the atmospheric circulation, including the presence of atmospheric fronts. Especially extreme weather phenomena such as wind gusts, heavy precipitation, hail, thunderstorms, and many others are usually occurred with passing of weather front. Climatology of weather fronts is difficult, since they are usually drawn manually by forecasters on maps, therefore the database of them is limited and the process itself is very subjective in its nature. In this study front analysis climatology over Central Europe (5°–30° W and 45°–60° N) is presented. It is based on an objective method.
The key issue in the study was to develop a method for the detection of atmospheric fronts. After many attempts and analyzes, the method based on based on random forest machine learning technique was used to distinguish the fronts. On the basis of a 3-year testing sample (2019-2021) of digitized synoptic maps developed by DWD, a system was built using the AI method.
The digitized weather fronts were used for further analysis based on data from an ERA5 meteorological reanalysis. We used surface data as well as data from 4 pressure levels (925, 850, 750, and 500 hPa) and 16 available meteorological fields that can indicate changes in weather conditions in the selected area. Due to relatively high dependency between original frontal information and automatically detected fronts the next step was performed, i.e., the preparation of fronts database for the entire 30-years 1991-2020. Finally, it enabled to create fronts climatology for the area of interest.
Therefore, the frequency of the occurrence of fronts over Central Europe was assessed. Due to methodological conditions, the analysis covered the number of days with the front over the investigated area. The study was made for an individual sub-areas with the size of 5x5° for the period 1991-2020. The analysis showed a slightly higher frequency of the number of days with a front in the year and in individual seasons in the NW part of the study area. The analysis of the variability of the number of days with fronts in the analyzed multiannual period did not show any significant differences between individual years. Larger differentiation was found only when analyzing the number of days with fronts in individual months.
How to cite: Wypych, A., Ustrnul, Z., Bochenek, B., and Kubacka, D.: Atmospheric fronts climatology over Central Europe, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-563, https://doi.org/10.5194/ems2022-563, 2022.
