EGU2020-8669, updated on 21 Apr 2023
https://doi.org/10.5194/egusphere-egu2020-8669
EGU General Assembly 2020
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

The Northern Hemisphere Winter Polar Jet Stream and its Connection to the Seasonal Prediction Skill of Weather Regimes over Europe

Lara Hellmich1, Marc Rautenhaus2, Panos Athanasiadis3, Mikhail Dobrynin4, André Düsterhus1,5, Paolo Ruggieri3, and Johanna Baehr1
Lara Hellmich et al.
  • 1Institute of Oceanography, CEN, Universität Hamburg, Germany
  • 2Regional Computing Centre, CEN, Universität Hamburg, Germany
  • 3Euro-Mediterranean Center on Climate Change (CMCC), Bologna, Italy
  • 4Deutscher Wetterdienst (DWD), Hamburg, Germany
  • 5ICARUS, Department of Geography, National University of Ireland, Maynooth, Ireland

Over the North Atlantic, the frequency of extreme weather events, such as storms or cold spells, is critically dependent on the prevailing weather regime. In consequence, seasonal predictability of these regimes is important. Currently, the ability of seasonal prediction systems to predict such weather regimes over Europe is limited. Weather regimes and the location of the northern hemisphere polar jet stream, hereinafter referred to as jet stream, interact with each other. Specific weather regimes are associated with a northern, central or southern position of the jet stream. Therefore, we investigate whether the relationship between weather regimes and the location of the jet stream can be used to improve seasonal winter forecasts over Europe. For our analysis, we use a seasonal prediction system based on the Max-Planck-Institute Earth-System- Model (MPI-ESM) and investigate a 30-member ensemble, as well as the global reanalysis ERA-Interim as an observational reference.

Our results show that the jet stream’s latitude is predictable per winter month with a seasonal prediction system. We also demonstrate in ERA-Interim that weather regime clusters can be directly identified via the jet stream’s position by using k-mean clustering with monthly data. Moreover our results show that the MPI-ESM reforecast ensemble represents the spatial and temporary variability of these clusters. We analyse whether predictive skill can be improved if the number of clusters represented within the reforecast ensemble at a given time is reduced. Specifically, we test whether the incorporation of the location of the jet stream into the prediction analysis improves the prediction skill of sea level pressure and Z500 in the North Atlantic area.

How to cite: Hellmich, L., Rautenhaus, M., Athanasiadis, P., Dobrynin, M., Düsterhus, A., Ruggieri, P., and Baehr, J.: The Northern Hemisphere Winter Polar Jet Stream and its Connection to the Seasonal Prediction Skill of Weather Regimes over Europe, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8669, https://doi.org/10.5194/egusphere-egu2020-8669, 2020.

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