Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 19, issue 16
Articles | Volume 19, issue 16
https://doi.org/10.5194/gmd-19-7705-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-7705-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 16
Development and technical paper
 | 
20 Aug 2026
Development and technical paper |  | 20 Aug 2026

Advancing the capabilities for efficient hurricane-centric simulations with the atmospheric model ICON

Fabian Senf and Roxana Cremer

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Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M., and Reinhardt, T.: Operational Convective-Scale Numerical Weather Prediction with the COSMO Model: Description and Sensitivities, Mon. Weather Rev., 139, 3887–3905, https://doi.org/10.1175/mwr-d-10-05013.1, 2011. a
Bechtold, P., Köhler, M., Jung, T., Doblas-Reyes, F., Leutbecher, M., Rodwell, M. J., Vitart, F., and Balsamo, G.: Advances in simulating atmospheric variability with the ECMWF model: From synoptic to decadal time-scales, Q. J. Roy. Meteor. Soc., 134, 1337–1351, https://doi.org/10.1002/qj.289, 2008. a
Bender, M. A. and Ginis, I.: Real-Case Simulations of Hurricane–Ocean Interaction Using A High-Resolution Coupled Model: Effects on Hurricane Intensity, Mon. Weather Rev., 128, 917–946, https://doi.org/10.1175/1520-0493(2000)128<0917:RCSOHO>2.0.CO;2, 2000. a
Davis, C., Wang, W., Chen, S. S., Chen, Y., Corbosiero, K., DeMaria, M., Dudhia, J., Holland, G., Klemp, J., Michalakes, J., Reeves, H., Rotunno, R., Snyder, C., and Xiao, Q.: Prediction of Landfalling Hurricanes with the Advanced Hurricane WRF Model, Mon. Weather Rev., 136, 1990–2005, https://doi.org/10.1175/2007MWR2085.1, 2008. a
Davis, C., Wang, W., Cavallo, S., Done, J., Dudhia, J., Fredrick, S., Michalakes, J., Caldwell, G., Engel, T., and Torn, R.: High-Resolution Hurricane Forecasts, Comput. Sci. Eng., 13, 22–30, https://doi.org/10.1109/MCSE.2010.74, 2011. a
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Computer models for hurricane prediction are increasingly detailed but require large computing resources. We developed a flexible approach that follows hurricanes, applying high-resolution simulations only where needed. This method reduces computing costs by up to an order of magnitude compared to conventional limited-area domains, while achieving resolutions down to 300 m. The approach enables more efficient hurricane research and improved understanding of tropical dynamics.
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