EGU21-5727, updated on 07 Feb 2023
EGU General Assembly 2021
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Work towards the near real-time attribution of extreme weather and climate events at the German weather service (Deutscher Wetterdienst)

Jordis Tradowsky1,2, Philip Lorenz1, Frank Kreienkamp1, and Amalie Skålevåg1
Jordis Tradowsky et al.
  • 1Deutscher Wetterdienst, Regionales Klimabüro Potsdam, Stahnsdorf, Germany (
  • 2Bodeker Scientific, New Zealand

The interest in statements about the impact of climate change on a specific extreme weather or climate event is largest in the immediate aftermath of an event. The wider public and other stakeholder would like to know, ideally within days after an event occurred, if and how anthropogenic climate change has altered the frequency and severity of such an extreme event. While the scientific area of event attribution has developed quickly within the last decade, providing attribution statements shortly after the event is still a challenge.

To satisfy the public’s need for information, several groups are currently working towards a near real-time attribution system. As part of module B1.2 of the German ClimXtreme project, we are working on a prototype for a semi-automated attribution system to analyse extreme events affecting Germany. Initially, the focus is on heat waves, droughts, and extreme precipitation events, which have large impacts in Germany.

This attribution system will implement existing methodologies for the probabilistic event attribution and extend them, where required. Collaborations with international colleagues facilitate an ongoing exchange with the growing community specialising in extreme event attribution. A close collaboration with project partners within ClimXtreme will enable us to implement new methodologies from other modules of the ClimXtreme project.

In this presentation, we will give an overview of the scientific and technical approach, as well as the different methodologies that will be part of the prototype attribution system. We will also compare the methodologies and discuss their different benefits.

How to cite: Tradowsky, J., Lorenz, P., Kreienkamp, F., and Skålevåg, A.: Work towards the near real-time attribution of extreme weather and climate events at the German weather service (Deutscher Wetterdienst), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5727,, 2021.


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