4-9 September 2022, Bonn, Germany
EMS Annual Meeting Abstracts
Vol. 19, EMS2022-717, 2022
EMS Annual Meeting 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Tryout of Kassandra: A Prototype of a Customizable, Probabilistic Warning and Information System

Heiko Niebuhr, Renate Hagedorn, Kathrin Feige, and Matthias Jerg
Heiko Niebuhr et al.
  • Deutscher Wetterdienst, Offenbach, Germany

To meet the individual needs requested by many expert users of DWD products, the idea of a new customizable branch for our future warning system was born. Based on the prospects of a fully automatic warning system, the possibility of individual warning information could be realized by giving users the option to configure their own parameters and settings for warnings and reports. To investigate and test such a system both internally and together with our users, and also to determine the meteorological and technical requirements and challenges, a prototype named Kassandra (acronym for "configurable automated weather warning information based on individual user profiles and requirements" (translated from German)) has been developed at DWD during the last years.

By using a configurable web portal, Kassandra gives users the ability to create and manage their own profiles, which consist of warning location, period, weather element and criteria and also probabilistic or time-based thresholds. Using the wide range of available EPS models at DWD, the user configurations are periodically analyzed. Warnings or reports are generated and sent to the users by mail or messenger (PUSH) in case of transgression. The system also gives users the possibility for PULL requests at any time by using the Kassandra web portal or web API. Especially the web API enables users to include individual warning information into their own automated processes.

During this poster session the opportunity to try out Kassandra is given. More information about the Kassandra system and its concepts are shown as an oral presentation in another session.

How to cite: Niebuhr, H., Hagedorn, R., Feige, K., and Jerg, M.: Tryout of Kassandra: A Prototype of a Customizable, Probabilistic Warning and Information System, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-717, https://doi.org/10.5194/ems2022-717, 2022.

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