Articles | Volume 21, issue 3
https://doi.org/10.5194/nhess-21-861-2021
© Author(s) 2021. 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-21-861-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Mar 2021
Research article |
| 05 Mar 2021
| 05 Mar 2021
Simulating synthetic tropical cyclone tracks for statistically reliable wind and pressure estimations
Kees Nederhoff
CORRESPONDING AUTHOR
Deltares USA, 8601 Georgia Ave, Silver Spring, MD 20910, USA
Jasper Hoek
Deltares, Boussinesqweg 1, Delft, 2629 HV, the Netherlands
Delft University of Technology, Stevinweg 1, 2628 CN Delft, the
Netherlands
Tim Leijnse
Deltares, Boussinesqweg 1, Delft, 2629 HV, the Netherlands
Maarten van Ormondt
Deltares, Boussinesqweg 1, Delft, 2629 HV, the Netherlands
Sofia Caires
Deltares, Boussinesqweg 1, Delft, 2629 HV, the Netherlands
Alessio Giardino
Deltares, Boussinesqweg 1, Delft, 2629 HV, the Netherlands
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Arctic coastlines are eroding rapidly as the climate warms, with some stretches retreating several metres per year and threatening homes in Alaska. We built Arctic-XBeach, an open-source model linking the thawing of frozen ground to wave-driven coastal change. By updating the coast only during storms, it runs fast enough for multi-year projections. Tested at Barter Island, Alaska, it reproduced ground temperatures and shoreline retreat, offering a tool for Arctic coastal planning.
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Deriving reliable estimates of design conditions resulting from tropical cyclones is a challenge of high relevance to coastal engineering. Here, having few historical observations is overcome by using the Tropical Cyclone Wind Statistical Estimation Tool (TCWiSE) to create thousands of synthetic realizations, representative of 1000 years of tropical cyclone activity for the Bay of Bengal. The use of synthetic tracks is shown to provide more reliable wind speed, storm surge and wave estimates.
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Arctic coastlines are eroding rapidly as the climate warms, with some stretches retreating several metres per year and threatening homes in Alaska. We built Arctic-XBeach, an open-source model linking the thawing of frozen ground to wave-driven coastal change. By updating the coast only during storms, it runs fast enough for multi-year projections. Tested at Barter Island, Alaska, it reproduced ground temperatures and shoreline retreat, offering a tool for Arctic coastal planning.
Doris M. Vertegaal, Bart J. J. M. van den Hurk, Anaïs Couasnon, Natalia Aleksandrova, Tycho Bovenschen, Fernaldi Gradiyanto, Tim W. B. Leijnse, Henrique M. D. Goulart, and Sanne Muis
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Kees Nederhoff, Maarten van Ormondt, Jay Veeramony, Ap van Dongeren, José Antonio Álvarez Antolínez, Tim Leijnse, and Dano Roelvink
Geosci. Model Dev., 17, 1789–1811, https://doi.org/10.5194/gmd-17-1789-2024, https://doi.org/10.5194/gmd-17-1789-2024, 2024
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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.
Dirk Eilander, Anaïs Couasnon, Tim Leijnse, Hiroaki Ikeuchi, Dai Yamazaki, Sanne Muis, Job Dullaart, Arjen Haag, Hessel C. Winsemius, and Philip J. Ward
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In coastal deltas, flooding can occur from interactions between coastal, riverine, and pluvial drivers, so-called compound flooding. Global models however ignore these interactions. We present a framework for automated and reproducible compound flood modeling anywhere globally and validate it for two historical events in Mozambique with good results. The analysis reveals differences in compound flood dynamics between both events related to the magnitude of and time lag between drivers.
Panagiotis Athanasiou, Ap van Dongeren, Alessio Giardino, Michalis Vousdoukas, Jose A. A. Antolinez, and Roshanka Ranasinghe
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Sandy dunes protect the hinterland from coastal flooding during storms. Thus, models that can efficiently predict dune erosion are critical for coastal zone management and early warning systems. Here we develop such a model for the Dutch coast based on machine learning techniques, allowing for dune erosion estimations in a matter of seconds relative to available computationally expensive models. Validation of the model against benchmark data and observations shows good agreement.
Mariana C. A. Clare, Tim W. B. Leijnse, Robert T. McCall, Ferdinand L. M. Diermanse, Colin J. Cotter, and Matthew D. Piggott
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Assessing uncertainty is computationally expensive because it requires multiple runs of expensive models. We take the novel approach of assessing uncertainty from coastal flooding using a multilevel multifidelity (MLMF) method which combines the efficiency of less accurate models with the accuracy of more expensive models at different resolutions. This significantly reduces the computational cost but maintains accuracy, making previously unfeasible real-world studies possible.
Tim Willem Bart Leijnse, Alessio Giardino, Kees Nederhoff, and Sofia Caires
Nat. Hazards Earth Syst. Sci., 22, 1863–1891, https://doi.org/10.5194/nhess-22-1863-2022, https://doi.org/10.5194/nhess-22-1863-2022, 2022
Short summary
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Deriving reliable estimates of design conditions resulting from tropical cyclones is a challenge of high relevance to coastal engineering. Here, having few historical observations is overcome by using the Tropical Cyclone Wind Statistical Estimation Tool (TCWiSE) to create thousands of synthetic realizations, representative of 1000 years of tropical cyclone activity for the Bay of Bengal. The use of synthetic tracks is shown to provide more reliable wind speed, storm surge and wave estimates.
Kees Nederhoff, Li Erikson, Anita Engelstad, Peter Bieniek, and Jeremy Kasper
The Cryosphere, 16, 1609–1629, https://doi.org/10.5194/tc-16-1609-2022, https://doi.org/10.5194/tc-16-1609-2022, 2022
Short summary
Short summary
Diminishing sea ice is impacting waves across the Arctic region. Recent work shows the effect of the sea ice on offshore waves; however, effects within the nearshore are less known. This study characterizes the wave climate in the central Beaufort Sea coast of Alaska. We show that the reduction of sea ice correlates strongly with increases in the average and extreme waves. However, found trends deviate from offshore, since part of the increase in energy is dissipated before reaching the shore.
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Short summary
The design of coastal protection affected by tropical cyclones is often based solely on the analysis of historical tropical cyclones (TCs). The simulation of numerous synthetic TC tracks based on historical data can overcome this limitation. In this paper, a new method for the generation of synthetic TC tracks is proposed, called the Tropical Cyclone Wind Statistical Estimation Tool (TCWiSE). TCWiSE can simulate thousands of tracks and wind fields in any oceanic basin based on any data source.
The design of coastal protection affected by tropical cyclones is often based solely on the...
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