Articles | Volume 18, issue 3
https://doi.org/10.5194/os-18-881-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-18-881-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data-assimilation-based parameter estimation of bathymetry and bottom friction coefficient to improve coastal accuracy in a global tide model
Delft Institute of Applied Mathematics, Delft University of Technology, Delft, the Netherlands
Martin Verlaan
Delft Institute of Applied Mathematics, Delft University of Technology, Delft, the Netherlands
Deltares, Delft, the Netherlands
Jelmer Veenstra
Deltares, Delft, the Netherlands
Hai Xiang Lin
Delft Institute of Applied Mathematics, Delft University of Technology, Delft, the Netherlands
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Cited
16 citations as recorded by crossref.
- Stochastic coastal flood risk modelling for the east coast of Africa I. Benito et al. https://doi.org/10.1038/s44304-024-00010-1
- Sensitivity of global storm surge modelling to sea surface drag F. Özkan et al. https://doi.org/10.1007/s10236-025-01713-3
- Automatic calibration and simultaneous estimation of bottom friction and open boundary conditions in a tidal model A. Sebastian et al. https://doi.org/10.1016/j.apor.2026.105145
- An empirical formula of bottom friction coefficient with a dependence on the current speed for the tidal models Y. Dong et al. https://doi.org/10.3389/fmars.2023.1206024
- A global unstructured, coupled, high-resolution hindcast of waves and storm surge L. Mentaschi et al. https://doi.org/10.3389/fmars.2023.1233679
- Global Projections of Storm Surges Using High‐Resolution CMIP6 Climate Models S. Muis et al. https://doi.org/10.1029/2023EF003479
- Investigation of tidal evolution in the Bohai Sea using the combination of satellite altimeter records and numerical models H. Pan et al. https://doi.org/10.1016/j.ecss.2022.108140
- Sequential model identification with reversible jump ensemble data assimilation method Y. Huan & H. Lin https://doi.org/10.1007/s11222-024-10499-1
- Uncovering unprecedented storm surges in European and Mediterranean coastlines I. Benito et al. https://doi.org/10.1088/1748-9326/ae2529
- High-Resolution Modeling of Storm Surge Response to Typhoon Doksuri (2023) in Fujian, China: Impacts of Wind Field Fusion, Parameter Sensitivity, and Sea-Level Rise Z. Xiao & Y. Lu https://doi.org/10.3390/jmse14010005
- Climate and impact attribution of compound flooding induced by tropical cyclone Idai in Mozambique D. Vertegaal et al. https://doi.org/10.5194/nhess-26-1417-2026
- A multiscale modelling framework of coastal flooding events for global to local flood hazard assessments I. Benito et al. https://doi.org/10.5194/nhess-25-2287-2025
- Study of the tidal dynamics in the Southwestern Atlantic Continental Shelf based on data assimilation M. Dinápoli & C. Simionato https://doi.org/10.1016/j.ocemod.2024.102332
- Assessing storm surge model performance: what error indicators can measure the model's skill? R. Campos-Caba et al. https://doi.org/10.5194/os-20-1513-2024
- Altimetry-derived tide model for improved tide and water level forecasting along the European continental shelf M. Hart-Davis et al. https://doi.org/10.1007/s10236-023-01560-0
- Positive Storm Surges in the Río de la Plata Estuary: forcings, long-term variability, trends and linkage with Southwestern Atlantic Continental Shelf dynamics G. Alonso et al. https://doi.org/10.1007/s11069-024-06402-w
16 citations as recorded by crossref.
- Stochastic coastal flood risk modelling for the east coast of Africa I. Benito et al. https://doi.org/10.1038/s44304-024-00010-1
- Sensitivity of global storm surge modelling to sea surface drag F. Özkan et al. https://doi.org/10.1007/s10236-025-01713-3
- Automatic calibration and simultaneous estimation of bottom friction and open boundary conditions in a tidal model A. Sebastian et al. https://doi.org/10.1016/j.apor.2026.105145
- An empirical formula of bottom friction coefficient with a dependence on the current speed for the tidal models Y. Dong et al. https://doi.org/10.3389/fmars.2023.1206024
- A global unstructured, coupled, high-resolution hindcast of waves and storm surge L. Mentaschi et al. https://doi.org/10.3389/fmars.2023.1233679
- Global Projections of Storm Surges Using High‐Resolution CMIP6 Climate Models S. Muis et al. https://doi.org/10.1029/2023EF003479
- Investigation of tidal evolution in the Bohai Sea using the combination of satellite altimeter records and numerical models H. Pan et al. https://doi.org/10.1016/j.ecss.2022.108140
- Sequential model identification with reversible jump ensemble data assimilation method Y. Huan & H. Lin https://doi.org/10.1007/s11222-024-10499-1
- Uncovering unprecedented storm surges in European and Mediterranean coastlines I. Benito et al. https://doi.org/10.1088/1748-9326/ae2529
- High-Resolution Modeling of Storm Surge Response to Typhoon Doksuri (2023) in Fujian, China: Impacts of Wind Field Fusion, Parameter Sensitivity, and Sea-Level Rise Z. Xiao & Y. Lu https://doi.org/10.3390/jmse14010005
- Climate and impact attribution of compound flooding induced by tropical cyclone Idai in Mozambique D. Vertegaal et al. https://doi.org/10.5194/nhess-26-1417-2026
- A multiscale modelling framework of coastal flooding events for global to local flood hazard assessments I. Benito et al. https://doi.org/10.5194/nhess-25-2287-2025
- Study of the tidal dynamics in the Southwestern Atlantic Continental Shelf based on data assimilation M. Dinápoli & C. Simionato https://doi.org/10.1016/j.ocemod.2024.102332
- Assessing storm surge model performance: what error indicators can measure the model's skill? R. Campos-Caba et al. https://doi.org/10.5194/os-20-1513-2024
- Altimetry-derived tide model for improved tide and water level forecasting along the European continental shelf M. Hart-Davis et al. https://doi.org/10.1007/s10236-023-01560-0
- Positive Storm Surges in the Río de la Plata Estuary: forcings, long-term variability, trends and linkage with Southwestern Atlantic Continental Shelf dynamics G. Alonso et al. https://doi.org/10.1007/s11069-024-06402-w
Saved (final revised paper)
Latest update: 03 Sep 2026
Short summary
The accuracy of the Global Tide and Surge Model is significantly affected by some parameters. We correct the bathymetry and bottom friction coefficient with mathematical methods to improve model accuracy. The lack of tide gauge data in many coastal areas affects the correction process. We propose using observations from altimetry tidal products like FES2014 that have higher accuracy than our model to offset the data lack. Model accuracy is greatly improved, especially in the European shelf.
The accuracy of the Global Tide and Surge Model is significantly affected by some parameters. We...