Articles | Volume 26, issue 11
https://doi.org/10.5194/nhess-26-5815-2026
© Author(s) 2026. 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-26-5815-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Nov 2026
Research article |
| 13 Nov 2026
| 13 Nov 2026
Evaluating the performance of a numerical weather prediction model for precipitation and temperature in Luxembourg and the Greater Region: insights from WRF and WRFDA 3D-VAR
Geodesy and Geospatial Engineering, Department of Engineering, Faculty of Science, Technology and Medicine, University of Luxembourg, 2 Avenue de l'Université, 4365 Esch-sur-Alzette, Luxembourg
Felicia Norma Rebecca Teferle
Geodesy and Geospatial Engineering, Department of Engineering, Faculty of Science, Technology and Medicine, University of Luxembourg, 2 Avenue de l'Université, 4365 Esch-sur-Alzette, Luxembourg
Addisu Hunegnaw
Geodesy and Geospatial Engineering, Department of Engineering, Faculty of Science, Technology and Medicine, University of Luxembourg, 2 Avenue de l'Université, 4365 Esch-sur-Alzette, Luxembourg
Rohith Muraleedharan Thundathil
Section 1.1 Space Geodetic Techniques, GFZ Helmholtz Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
Jens Wickert
Section 1.1 Space Geodetic Techniques, GFZ Helmholtz Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
Florian Zus
Section 1.1 Space Geodetic Techniques, GFZ Helmholtz Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
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Short summary
We tested whether assimilating conventional weather observations and Global Navigation Satellite System (GNSS) satellite delay data improves Weather Research and Forecasting (WRF) forecasts of rain and temperature over Luxembourg and the Greater Region in the month around the July 2021 floods. How the model’s background errors are represented mattered more than which observations were used. With an error model derived from the study month, GNSS data improved forecasts of light and moderate rain, while no setup was clearly best for temperature.
We tested whether assimilating conventional weather observations and Global Navigation Satellite...
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