Articles | Volume 16, issue 2
https://doi.org/10.5194/amt-16-295-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-16-295-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Assessing and mitigating the radar–radar interference in the German C-band weather radar network
Observatorium Hohenpeißenberg, Forschung und Entwicklung, Deutscher Wetterdienst, Albin-Schwaiger-Weg 10, 82383 Hohenpeißenberg, Germany
Cornelius Hald
Observatorium Hohenpeißenberg, Forschung und Entwicklung, Deutscher Wetterdienst, Albin-Schwaiger-Weg 10, 82383 Hohenpeißenberg, Germany
Maximilian Schaper
Observatorium Hohenpeißenberg, Forschung und Entwicklung, Deutscher Wetterdienst, Albin-Schwaiger-Weg 10, 82383 Hohenpeißenberg, Germany
Bertram Lange
Technische Infrastruktur und Betrieb, Deutscher Wetterdienst, Frahmredder 95, 22393 Hamburg, Germany
Benjamin Rohrdantz
Technische Infrastruktur und Betrieb, Deutscher Wetterdienst, Frahmredder 95, 22393 Hamburg, Germany
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EGUsphere, https://doi.org/10.5194/egusphere-2025-4679, https://doi.org/10.5194/egusphere-2025-4679, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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This study presents the new vertically pointing birdbath scan of the German C-band radar network, which provides high-resolution profiles of precipitating clouds above all DWD weather radars since the spring of 2021. Our AI-based postprocessing method for filtering and analyzing the recorded radar data offers a unique quantitative view into a wide range of precipitation events from snowfall over stratiform rain to intense frontal showers and will be used to complement DWD's operational services.
Maximilian Schaper, Michael Frech, David Michaelis, Cornelius Hald, and Benjamin Rohrdantz
Atmos. Meas. Tech., 15, 6625–6642, https://doi.org/10.5194/amt-15-6625-2022, https://doi.org/10.5194/amt-15-6625-2022, 2022
Short summary
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C-band weather radar data are commonly compromised by radio frequency interference (RFI) from external sources. It is not possible to separate a superimposed interference signal from the radar data. Therefore, the best course of action is to shut down RFI sources as quickly as possible. An automated RFI detection algorithm has been developed. Since its implementation, persistent RFI sources are eliminated much more quickly, while the number of short-lived RFI sources keeps steadily increasing.
Silke Trömel, Clemens Simmer, Ulrich Blahak, Armin Blanke, Sabine Doktorowski, Florian Ewald, Michael Frech, Mathias Gergely, Martin Hagen, Tijana Janjic, Heike Kalesse-Los, Stefan Kneifel, Christoph Knote, Jana Mendrok, Manuel Moser, Gregor Köcher, Kai Mühlbauer, Alexander Myagkov, Velibor Pejcic, Patric Seifert, Prabhakar Shrestha, Audrey Teisseire, Leonie von Terzi, Eleni Tetoni, Teresa Vogl, Christiane Voigt, Yuefei Zeng, Tobias Zinner, and Johannes Quaas
Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021, https://doi.org/10.5194/acp-21-17291-2021, 2021
Short summary
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Short summary
Weather radar data are the backbone of a lot of meteorological products. In order to obtain a better low-level coverage with radar data, additional systems have to be included. The frequency range in which radars are allowed to operate is limited. A potential radar-to-radar interference has to be avoided. The paper derives guidelines on how additional radars can be included into a C-band weather radar network and how interferences can be avoided.
Weather radar data are the backbone of a lot of meteorological products. In order to obtain a...