Articles | Volume 25, issue 6
https://doi.org/10.5194/nhess-25-2081-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-25-2081-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development of a wind-based storm surge model for the German Bight
Federal Maritime and Hydrographic Agency (BSH), Hamburg, Germany
Institute of Oceanography, University of Hamburg, Hamburg, Germany
Andreas Boesch
Federal Maritime and Hydrographic Agency (BSH), Hamburg, Germany
Johanna Baehr
Institute of Oceanography, University of Hamburg, Hamburg, Germany
Tim Kruschke
Federal Maritime and Hydrographic Agency (BSH), Hamburg, Germany
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EGUsphere, https://doi.org/10.5194/egusphere-2025-2653, https://doi.org/10.5194/egusphere-2025-2653, 2025
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This study uses a high-resolution global climate model to simulate future climate, focusing on the Arctic and North Atlantic. The model captures observed sea ice loss and Atlantic circulation trends, projecting a nearly ice-free Arctic by 2040. It introduces a new method to quantify deep water formation, revealing how different ocean regions contribute to the weakening of overturning circulation in a warming climate.
Julianna Carvalho-Oliveira, Giorgia Di Capua, Leonard F. Borchert, Reik V. Donner, and Johanna Baehr
Weather Clim. Dynam., 5, 1561–1578, https://doi.org/10.5194/wcd-5-1561-2024, https://doi.org/10.5194/wcd-5-1561-2024, 2024
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We demonstrate with a causal analysis that an important recurrent summer atmospheric pattern, the so-called East Atlantic teleconnection, was influenced by the extratropical North Atlantic in spring during the second half of the 20th century. This causal link is, however, not well represented by our evaluated seasonal climate prediction system. We show that simulations able to reproduce this link show improved surface climate prediction credibility over those that do not.
Anja Lindenthal, Claudia Hinrichs, Simon Jandt-Scheelke, Tim Kruschke, Priidik Lagemaa, Eefke M. van der Lee, Ilja Maljutenko, Helen E. Morrison, Tabea R. Panteleit, and Urmas Raudsepp
State Planet, 4-osr8, 16, https://doi.org/10.5194/sp-4-osr8-16-2024, https://doi.org/10.5194/sp-4-osr8-16-2024, 2024
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Daniel Krieger, Sebastian Brune, Johanna Baehr, and Ralf Weisse
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Previous studies found that climate models can predict storm activity in the German Bight well for averages of 5–10 years but struggle in predicting the next winter season. Here, we improve winter storm activity predictions by linking them to physical phenomena that occur before the winter. We guess the winter storm activity from these phenomena and discard model solutions that stray too far from the guess. The remaining solutions then show much higher prediction skill for storm activity.
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Yiyu Zheng, Maria Rugenstein, Patrick Pieper, Goratz Beobide-Arsuaga, and Johanna Baehr
Earth Syst. Dynam., 13, 1611–1623, https://doi.org/10.5194/esd-13-1611-2022, https://doi.org/10.5194/esd-13-1611-2022, 2022
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Tim Rohrschneider, Johanna Baehr, Veit Lüschow, Dian Putrasahan, and Jochem Marotzke
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Annika Drews, Wenjuan Huo, Katja Matthes, Kunihiko Kodera, and Tim Kruschke
Atmos. Chem. Phys., 22, 7893–7904, https://doi.org/10.5194/acp-22-7893-2022, https://doi.org/10.5194/acp-22-7893-2022, 2022
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Solar irradiance varies with a period of approximately 11 years. Using a unique large chemistry–climate model dataset, we investigate the solar surface signal in the North Atlantic and European region and find that it changes over time, depending on the strength of the solar cycle. For the first time, we estimate the potential predictability associated with including realistic solar forcing in a model. These results may improve seasonal to decadal predictions of European climate.
Marcel Meyer, Iuliia Polkova, Kameswar Rao Modali, Laura Schaffer, Johanna Baehr, Stephan Olbrich, and Marc Rautenhaus
Weather Clim. Dynam., 2, 867–891, https://doi.org/10.5194/wcd-2-867-2021, https://doi.org/10.5194/wcd-2-867-2021, 2021
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Novel techniques from computer science are used to study extreme weather events. Inspired by the interactive 3-D visual analysis of the recently released ERA5 reanalysis data, we improve commonly used metrics for measuring polar winter storms and outbreaks of cold air. The software (Met.3D) that we have extended and applied as part of this study is freely available and can be used generically for 3-D visualization of a broad variety of atmospheric processes in weather and climate data.
Julianna Carvalho-Oliveira, Leonard Friedrich Borchert, Aurélie Duchez, Mikhail Dobrynin, and Johanna Baehr
Weather Clim. Dynam., 2, 739–757, https://doi.org/10.5194/wcd-2-739-2021, https://doi.org/10.5194/wcd-2-739-2021, 2021
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Klaus Wyser, Torben Koenigk, Uwe Fladrich, Ramon Fuentes-Franco, Mehdi Pasha Karami, and Tim Kruschke
Geosci. Model Dev., 14, 4781–4796, https://doi.org/10.5194/gmd-14-4781-2021, https://doi.org/10.5194/gmd-14-4781-2021, 2021
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Tian Tian, Shuting Yang, Mehdi Pasha Karami, François Massonnet, Tim Kruschke, and Torben Koenigk
Geosci. Model Dev., 14, 4283–4305, https://doi.org/10.5194/gmd-14-4283-2021, https://doi.org/10.5194/gmd-14-4283-2021, 2021
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Sabine Haase, Jaika Fricke, Tim Kruschke, Sebastian Wahl, and Katja Matthes
Atmos. Chem. Phys., 20, 14043–14061, https://doi.org/10.5194/acp-20-14043-2020, https://doi.org/10.5194/acp-20-14043-2020, 2020
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Ozone depletion over Antarctica was shown to influence the tropospheric jet in the Southern Hemisphere. We investigate the atmospheric response to ozone depletion comparing climate model ensembles with interactive and prescribed ozone fields. We show that allowing feedbacks between ozone chemistry and model physics as well as including asymmetries in ozone leads to a strengthened ozone depletion signature in the stratosphere but does not significantly affect the tropospheric jet position.
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Short summary
We developed a simple and effective model to predict storm surges in the German Bight, using wind data and a multiple linear regression approach. Trained on historical data from 1959 to 2022, our storm surge model demonstrates high predictive skill and performs as well as more complex models, despite its simplicity. It can predict both moderate and extreme storm surges, making it a valuable tool for future climate change studies.
We developed a simple and effective model to predict storm surges in the German Bight, using...
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