Articles | Volume 20, issue 2
https://doi.org/10.5194/nhess-20-567-2020
https://doi.org/10.5194/nhess-20-567-2020
Research article
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25 Feb 2020
Research article | Highlight paper |  | 25 Feb 2020

Modelling global tropical cyclone wind footprints

James M. Done, Ming Ge, Greg J. Holland, Ioana Dima-West, Samuel Phibbs, Geoffrey R. Saville, and Yuqing Wang

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Cited articles

Arthur, W. C.: A statistical-parametric model of tropical cyclones for hazard assessment, Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2019-192, in review, 2019. 
Arthur, W. C., Schofield, A., Cechet, R. P., and Sanabria, L. A.: Return period cyclonic wind hazard in the Australian region, in: 28th AMS Conference on Hurricanes and Tropical Meteorology, Orlando, Florida, USA, 28 April–2 May 2008, 12B.5, 2008. 
Blackadar, A. K.: The vertical distribution of wind and turbulent exchange in a neutral atmosphere, J. Geophys. Res., 67, 3095–3102, https://doi.org/10.1029/JZ067i008p03095, 1962. 
Chavas, D. R., Reed, K. A., and Knaff, J. A.: Physical understanding of the tropical cyclone wind-pressure relationship, Nat. Commun., 8, 1360, https://doi.org/10.1038/s41467-017-01546-9, 2017. 
Cobb, A. and Done, J. M.: The Use of Global Climate Models for Tropical Cyclone Risk Assessment, in: Hurricanes and Climate Change, edited by: Collins, J., Walsh, K., Springer, Cham, https://doi.org/10.1007/978-3-319-47594-3_7, 2017. 
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Assessing tropical cyclone (TC) wind risk is challenging due to a lack of historical TC wind data. This paper presents a novel approach to simulating landfalling TC winds anywhere on Earth. It captures local features such as high winds over coastal hills and lulls over rough terrain. A dataset of over 700 global historical wind footprints has been generated to provide new views of historical events. This dataset can be used to advance our understanding of overland TC wind risk.
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