EMS Annual Meeting Abstracts
Vol. 20, EMS2023-510, 2023, updated on 06 Jul 2023
https://doi.org/10.5194/ems2023-510
EMS Annual Meeting 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Atmospheric fronts detection over Europe – methodological approach

Agnieszka Wypych1, Bogdan Bochenek2, Zbigniew Ustrnul1,2, and Dan Suri3
Agnieszka Wypych et al.
  • 1Jagiellonian University, Krakow, Poland (agnieszka.wypych@uj.edu.pl)
  • 2Institute of Meteorology and Water Management – NRI, Warsaw, Poland
  • 3Met Office, Exeter, UK

Weather conditions, including the threat of extreme weather, in the temperate zone are mainly related to the atmospheric circulation, including the presence of atmospheric fronts.

Despite many studies conducted on the distinction of atmospheric fronts in recent years, there is still no entirely satisfactory objective method of their discrimination with respect to traditional synoptic maps. Here we propose a method of distinguishing atmospheric fronts based on cluster analysis methodology treating border zones between air masses as fronts and testing the output against operational analyses

The basic data used for the calculations were meteorological fields taken from the ERA5 database for the period 1951-2020 in hourly time steps across a domain given by coordinates 30°W to 50°E and 30°N to 80°N. The following elements were taken into account: temperature, specific and relative humidity, geopotential height on pressure levels from 925 to 700 hPa as well as temperature and wind speed near the ground.

Using methods such as k-means and dbscan, division into 3, 4 and 5 clusters was conducted over Europe. This analysis was conducted for the whole period, as well as for specific months and seasons, and included considerations of spatial diversity and temporal changes in different regions of the domain.

Validation of the results, including comparative studies with traditional synoptic maps from DWD and the Met Office, confirms the 3-classes distinction of air masses as the most reliable. The proposed method seems to be effective and self-dependent (contrary to, for example, supervised machine learning methods). This approach enables a method to be developed allowing calculations of severity of fronts and trends in the behaviour of fronts with time.

How to cite: Wypych, A., Bochenek, B., Ustrnul, Z., and Suri, D.: Atmospheric fronts detection over Europe – methodological approach, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-510, https://doi.org/10.5194/ems2023-510, 2023.