Articles | Volume 17, issue 4
https://doi.org/10.5194/gmd-17-1789-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-1789-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
29 Feb 2024
Model description paper |
| 29 Feb 2024
| 29 Feb 2024
Accounting for uncertainties in forecasting tropical-cyclone-induced compound flooding
Kees Nederhoff
CORRESPONDING AUTHOR
Deltares USA, 8601 Georgia Ave, Silver Spring, MD 20910, USA
Department of Coastal and Urban Risk & Resilience, CURR, UNESCO-IHE Institute for Water Education, P.O. BOX 3015, 2601 DA Delft, the Netherlands
Department of Hydraulic Engineering, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, the Netherlands
Maarten van Ormondt
Deltares USA, 8601 Georgia Ave, Silver Spring, MD 20910, USA
Jay Veeramony
Naval Research Lab, Stennis Space Center, MS 39529, USA
Ap van Dongeren
Department of Coastal and Urban Risk & Resilience, CURR, UNESCO-IHE Institute for Water Education, P.O. BOX 3015, 2601 DA Delft, the Netherlands
Marine and Coastal Management, Deltares, Boussinesqweg 1, Delft, 2629 HV, the Netherlands
José Antonio Álvarez Antolínez
Department of Hydraulic Engineering, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, the Netherlands
Tim Leijnse
Marine and Coastal Management, Deltares, Boussinesqweg 1, Delft, 2629 HV, the Netherlands
Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, De Boelelaan 1111, 1081 HV Amsterdam, the Netherlands
Dano Roelvink
Department of Coastal and Urban Risk & Resilience, CURR, UNESCO-IHE Institute for Water Education, P.O. BOX 3015, 2601 DA Delft, the Netherlands
Marine and Coastal Management, Deltares, Boussinesqweg 1, Delft, 2629 HV, the Netherlands
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Cited
11 citations as recorded by crossref.
- Probabilistic storm surge and flood-inundation modeling of the Texas gulf coast using super-fast INundation of CoastS (SFINCS) W. Lee et al. 10.1016/j.coastaleng.2025.104721
- From decades to years: Rising seas and cyclones amplify Bangladesh’s storm-tide hazards in a warming climate J. Qiu et al. 10.1016/j.oneear.2025.101273
- Understanding mariners’ tsunami information needs and decision-making contexts: A post-event case study of the 2022 Tonga eruption and tsunami S. Harrison et al. 10.1016/j.isci.2025.111801
- A composite index framework for compound flood risk assessment J. Del-Rosal-Salido et al. 10.1038/s43247-025-02331-z
- Leveraging Coupled Hydrodynamic with Data-Driven GeoAI Models for Advancing Systemic Compound Flood Risk Evaluation in Coastal Urban Areas T. Atmaja et al. 10.1007/s11831-025-10394-6
- Estimating nearshore infragravity wave conditions at large spatial scales T. Leijnse et al. 10.3389/fmars.2024.1355095
- Evaluating impact-based forecasting models for tropical cyclone anticipatory action S. Sedhain et al. 10.1016/j.ijdrr.2025.105782
- Exploring coastal climate adaptation through storylines: Insights from cyclone Idai in Beira, Mozambique H. Goulart et al. 10.1016/j.crsus.2024.100270
- The importance of waves in large-scale coastal compound flooding: A case study of Hurricane Florence (2018) T. Leijnse et al. 10.1016/j.coastaleng.2025.104726
- Disentangling atmospheric, hydrological, and coupling uncertainties in compound flood modeling within a coupled Earth system model D. Feng et al. 10.5194/nhess-25-3619-2025
- Review article: The growth in compound weather and climate event research in the decade since SREX L. Brett et al. 10.5194/nhess-25-2591-2025
11 citations as recorded by crossref.
- Probabilistic storm surge and flood-inundation modeling of the Texas gulf coast using super-fast INundation of CoastS (SFINCS) W. Lee et al. 10.1016/j.coastaleng.2025.104721
- From decades to years: Rising seas and cyclones amplify Bangladesh’s storm-tide hazards in a warming climate J. Qiu et al. 10.1016/j.oneear.2025.101273
- Understanding mariners’ tsunami information needs and decision-making contexts: A post-event case study of the 2022 Tonga eruption and tsunami S. Harrison et al. 10.1016/j.isci.2025.111801
- A composite index framework for compound flood risk assessment J. Del-Rosal-Salido et al. 10.1038/s43247-025-02331-z
- Leveraging Coupled Hydrodynamic with Data-Driven GeoAI Models for Advancing Systemic Compound Flood Risk Evaluation in Coastal Urban Areas T. Atmaja et al. 10.1007/s11831-025-10394-6
- Estimating nearshore infragravity wave conditions at large spatial scales T. Leijnse et al. 10.3389/fmars.2024.1355095
- Evaluating impact-based forecasting models for tropical cyclone anticipatory action S. Sedhain et al. 10.1016/j.ijdrr.2025.105782
- Exploring coastal climate adaptation through storylines: Insights from cyclone Idai in Beira, Mozambique H. Goulart et al. 10.1016/j.crsus.2024.100270
- The importance of waves in large-scale coastal compound flooding: A case study of Hurricane Florence (2018) T. Leijnse et al. 10.1016/j.coastaleng.2025.104726
- Disentangling atmospheric, hydrological, and coupling uncertainties in compound flood modeling within a coupled Earth system model D. Feng et al. 10.5194/nhess-25-3619-2025
- Review article: The growth in compound weather and climate event research in the decade since SREX L. Brett et al. 10.5194/nhess-25-2591-2025
Latest update: 07 Oct 2025
Short summary
Forecasting tropical cyclones and their flooding impact is challenging. Our research introduces the Tropical Cyclone Forecasting Framework (TC-FF), enhancing cyclone predictions despite uncertainties. TC-FF generates global wind and flood scenarios, valuable even in data-limited regions. Applied to cases like Cyclone Idai, it showcases potential in bettering disaster preparation, marking progress in handling cyclone threats.
Forecasting tropical cyclones and their flooding impact is challenging. Our research...
