Abstract
Tropical cyclones (TCs) cause catastrophic loss in many coastal areas of the world. TC wind hazard maps can play an important role in disaster management. A good representation of local factors reflecting the effects of spatially heterogeneous terrain and land cover is critical to evaluation of TC wind hazard. Very few studies, however, provide global wind hazard assessment results that consider detailed local effects. In this study, the wind fields of historical TCs were simulated with parametric models in which the planetary boundary layer models explicitly integrate local effects at 1 km resolution. The topographic effects for eight wind directions were quantified over four types of terrain (ground, escarpment, ridge, and valley), and the surface roughness lengths were estimated from a global land cover map. The missing TC parameters in the best track datasets were reconstructed with local regression models. Finally, an example of a wind hazard map in the form of wind speeds under a 100-year return period and corresponding uncertainties was created based on a statistical analysis of reconstructed historical wind fields over seven of the world’s ocean basins.
Highlights
Tropical cyclones (TCs) cause casualties and enormous economic losses in the coastal areas of the world (GuhaSapir et al 2013)
The development of TC wind hazard maps is of great importance to disaster mitigation, especially for less developed and disaster-prone areas
Most TC wind hazard maps were created for developed areas, and few maps have been developed with detailed consideration of local effects at the global scale
Summary
Tropical cyclones (TCs) cause casualties and enormous economic losses in the coastal areas of the world (GuhaSapir et al 2013). Wind is one of the major hazards of TCs, which brings direct property damage and determines the intensity of other secondary hazards, such as storm surge and waves. Tropical cyclonic wind hazard is often quantified by the statistical distribution of storm intensity and frequency and is delineated in the form of a wind speed map of the return period (Fang and Lin 2013). The frequency of wind speeds is usually analyzed with methods like the extreme value theory (EVT), which is based on historical ground meteorological observations (Elsner et al 2008). Ground observations might be insufficient and modeling of historical or stochastic simulated TCs based on the Monte-Carlo method (Russell 1969; Huang et al 2001) is needed. Methods using basin-wide stochastic simulations of full TC tracks have been developed (Vickery et al 2000; Emanuel et al 2006)
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
