Abstract

Abstract. Parametric wind profiles are commonly applied in a number of engineering applications for the generation of tropical cyclone (TC) wind and pressure fields. Nevertheless, existing formulations for computing wind fields often lack the required accuracy when the TC geometry is not known. This may affect the accuracy of the computed impacts generated by these winds. In this paper, empirical stochastic relationships are derived to describe two important parameters affecting the TC geometry: radius of maximum winds (RMW) and the radius of gale-force winds (ΔAR35). These relationships are formulated using best-track data (BTD) for all seven ocean basins (Atlantic; S, NW, and NE Pacific; and N, SW, and SE Indian oceans). This makes it possible to (a) estimate RMW and ΔAR35 when these properties are not known and (b) generate improved parametric wind fields for all oceanic basins. Validation results show how the proposed relationships allow the TC geometry to be represented with higher accuracy than when using relationships available from literature. Outer wind speeds can be reproduced well by the commonly used Holland wind profile when calibrated using information either from best-track data or from the proposed relationships. The scripts to compute the TC geometry and the outer wind speed are freely available via the following URL: https://bit.ly/2k9py1J (last access: October 2019).

Highlights

  • Tropical cyclones (TCs) are among the most destructive natural hazards worldwide

  • The analysis has shown how the proposed relationships in combination with the H10 wind profile result in the lowest root-mean-square deviation (RMSD) and smallest bias for the outer winds, compared to other existing relationships

  • The new relationships include a stochastic description for both the radius of maximum winds (RMW) and the radius of gale-force winds ( average radius of 35 kn (AR35))

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Summary

Introduction

Tropical cyclones (TCs) are among the most destructive natural hazards worldwide. TCs can cause hazardous weather conditions including extreme rainfall and wind speeds, leading to coastal hazards, such as extreme storm surge levels and wave conditions. In the United States (US) alone, the mean annual damage due to TCs was estimated by Willoughby (2012) as USD 11.0 billion (year 2015). TCs result in immense social costs in terms of destruction and mortality. Between 1960 and 2004 more than half a million inhabitants of Bangladesh died as a consequence of TCs, primarily due to storm surges (Shultz et al, 2005). TCs can have devastating effects on nature, geomorphology, agriculture and freshwater supply. Due to the extensive costs in lives, property and other damage, the ability to effectively model these storms is essential

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