EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Detection and tracking of atmospheric blocks: a Lagrangian flow network approach

Noémie Ehstand1, Reik Donner2,3, Cristóbal López1, and Emilio Hernández-García1
Noémie Ehstand et al.
  • 1Institute for Cross-Disciplinary Physics and Complex Systems (IFISC), CSIC-UIB, Palma de Mallorca, Spain (
  • 2Department of Water, Environment, Construction & Safety, Magdeburg–Stendal University of Applied Sciences, Magdeburg, Germany
  • 3Research Department I - Earth System Science, Potsdam Institute for Climate Impact Research (PIK), Potsdam, Germany

In the past decades, boreal summers have been characterized by a number extreme weather events such as heat waves, droughts and heavy rainfall periods with significant social, economic and environmental impacts. One of the most outstanding examples occurred in the summer of 2010 when an anomalously strong heatwave persisted over Eastern Europe for several weeks while extreme rainfalls struck Pakistan, leading to the country’s worst floods in record history. Both events were related to the presence of an anomalously persistent atmospheric blocking situation - that is a large-scale, nearly stationary, atmospheric pressure pattern - over Eastern Europe.

The high impact of blocking events has motivated numerous studies. However, there is not yet a comprehensive theory explaining their onset, maintenance and decay and their prediction remains a challenge.

In this work, we employ a Lagrangian dynamics based, complex network description of the atmospheric transport to study the connectivity patterns associated with atmospheric blocking events. The network is constructed by associating nodes to regions of the atmosphere and establishing links based on the flux of material between these nodes during a given time interval, as described in Ser-Giacomi et al. [1]. One can then use the tools and metrics developed in the context of graph theory to explore the atmospheric flow properties. In particular, we demonstrate the ability of measures such as the network degree, entropy and harmonic closeness centrality to trace the spatio-temporal characteristics of atmospheric blocking events.

[1] E. Ser-Giacomi, V. Rossi, C. López, E. Hernández-García, Chaos 25(3), 036404 (2015)


This research was conducted as part of the CAFE Innovative Training Network (Climate Advanced Forecasting of sub-seasonal Extremes, which has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 813844.

How to cite: Ehstand, N., Donner, R., López, C., and Hernández-García, E.: Detection and tracking of atmospheric blocks: a Lagrangian flow network approach, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1527,, 2021.


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