Articles | Volume 21, issue 3
https://doi.org/10.5194/nhess-21-861-2021
https://doi.org/10.5194/nhess-21-861-2021
Research article
 | 
05 Mar 2021
Research article |  | 05 Mar 2021

Simulating synthetic tropical cyclone tracks for statistically reliable wind and pressure estimations

Kees Nederhoff, Jasper Hoek, Tim Leijnse, Maarten van Ormondt, Sofia Caires, and Alessio Giardino

Related authors

Accounting for uncertainties in forecasting tropical-cyclone-induced compound flooding
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
Short summary
Generating reliable estimates of tropical-cyclone-induced coastal hazards along the Bay of Bengal for current and future climates using synthetic tracks
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
The effect of changing sea ice on wave climate trends along Alaska's central Beaufort Sea coast
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
Estimates of tropical cyclone geometry parameters based on best-track data
Kees Nederhoff, Alessio Giardino, Maarten van Ormondt, and Deepak Vatvani
Nat. Hazards Earth Syst. Sci., 19, 2359–2370, https://doi.org/10.5194/nhess-19-2359-2019,https://doi.org/10.5194/nhess-19-2359-2019, 2019
Short summary

Related subject area

Atmospheric, Meteorological and Climatological Hazards
Application of the teaching–learning-based optimization algorithm to an analytical model of thunderstorm outflows to analyze the variability of the downburst kinematic and geometric parameters
Andi Xhelaj and Massimiliano Burlando
Nat. Hazards Earth Syst. Sci., 24, 1657–1679, https://doi.org/10.5194/nhess-24-1657-2024,https://doi.org/10.5194/nhess-24-1657-2024, 2024
Short summary
Projections and uncertainties of winter windstorm damage in Europe in a changing climate
Luca G. Severino, Chahan M. Kropf, Hilla Afargan-Gerstman, Christopher Fairless, Andries Jan de Vries, Daniela I. V. Domeisen, and David N. Bresch
Nat. Hazards Earth Syst. Sci., 24, 1555–1578, https://doi.org/10.5194/nhess-24-1555-2024,https://doi.org/10.5194/nhess-24-1555-2024, 2024
Short summary
Improving seasonal predictions of German Bight storm activity
Daniel Krieger, Sebastian Brune, Johanna Baehr, and Ralf Weisse
Nat. Hazards Earth Syst. Sci., 24, 1539–1554, https://doi.org/10.5194/nhess-24-1539-2024,https://doi.org/10.5194/nhess-24-1539-2024, 2024
Short summary
A satellite view of the exceptionally warm summer of 2022 over Europe
João P. A. Martins, Sara Caetano, Carlos Pereira, Emanuel Dutra, and Rita M. Cardoso
Nat. Hazards Earth Syst. Sci., 24, 1501–1520, https://doi.org/10.5194/nhess-24-1501-2024,https://doi.org/10.5194/nhess-24-1501-2024, 2024
Short summary
Demographic yearbooks as a source of weather-related fatalities: the Czech Republic, 1919–2022
Rudolf Brázdil, Kateřina Chromá, and Pavel Zahradníček
Nat. Hazards Earth Syst. Sci., 24, 1437–1457, https://doi.org/10.5194/nhess-24-1437-2024,https://doi.org/10.5194/nhess-24-1437-2024, 2024
Short summary

Cited articles

Arthur, W. C.: A statistical-parametric model of tropical cyclones for hazard assessment, Nat. Hazards Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/nhess-2019-192, in review, 2019. 
Bader, D. J.: Including stochastic rainfall distributions in a probabilistic modelling approach for compound flooding due to tropical cyclones, Delft University of Technology, available at: http://resolver.tudelft.nl/uuid:57b9e495-0c90-4cf5-ab22-e169fb908ac1 (last access: 1 March 2018), 2019. 
Bloemendaal, N., Haigh, I. D., de Moel, H., Muis, S., Haarsma, R. J., and Aerts, J. C. J. H.: Generation of a global synthetic tropical cyclone hazard dataset using STORM, Sci. Data, 7, 1–19, https://doi.org/10.1038/s41597-020-0381-2, 2020. 
Brzeźniak, Z. and Zastawniak, T.: Basic Stochastic Processes, Springer, London., 2000. 
Caires, S.: A Comparative Simulation Study of the Annual Maxima and the Peaks-Over-Threshold Methods, J. Offshore Mech. Arct., 138, 051601, https://doi.org/10.1115/1.4033563, 2016. 
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.
Altmetrics
Final-revised paper
Preprint