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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/nhess-2019-207
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2019-207
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 02 Jul 2019

Submitted as: research article | 02 Jul 2019

Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Modelling Global Tropical Cyclone Wind Footprints

James M. Done1,2, Ming Ge1, Greg J. Holland1,2, Ioana Dima-West3, Samuel Phibbs3, Geoffrey R. Saville3, and Yuqing Wang4 James M. Done et al.
  • 1National Center for Atmospheric Research, 3090 Center Green Drive, Boulder CO 80301, US
  • 2Willis Research Network, 51 Lime St, London, EC3M 7DQ, UK
  • 3Willis Towers Watson, 51 Lime St, London, EC3M 7DQ, UK
  • 4International Pacific Research Center and Department of Atmospheric Sciences, School of Ocean and Earth Science and Technology, University of Hawaii at Manoa, HI 96822, US

Abstract. A novel approach to modelling the surface wind field of landfalling tropical cyclones (TCs) is presented. The modelling system simulates the evolution of the low-level wind fields of landfalling TCs, accounting for terrain effects. A two-step process models the gradient-level wind field using a parametric wind field model fitted to TC track data, then brings the winds down to the surface using a full numerical boundary layer model. The physical wind response to variable surface drag and terrain height produces substantial local modifications to the smooth wind field provided by the parametric wind profile model. For a set of U.S. historical landfalling TCs the simulated footprints compare favourably with surface station observations. The model is applicable from single event simulation to the generation of global catalogues. One application demonstrated here is the creation of a dataset of 714 global historical TC overland wind footprints. A preliminary analysis of this dataset shows regional variability in the inland wind speed decay rates and evidence of a strong influence of regional orography. This dataset can be used to advance our understanding of overland wind risk in regions of complex terrain and support wind risk assessments in regions of sparse historical data.

James M. Done et al.
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James M. Done et al.
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Short summary
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 seven hundred 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.
Assessing Tropical Cyclone (TC) wind risk is challenging due to a lack of historical TC wind...
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