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.

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ABSTRACT:Forest disturbance induced by tropical cyclone often has significant and profound effects on the structure and function of forest ecosystem. Detection and analysis of post-disaster forest disturbance based on remote sensing technology has been widely applied. At present, it is necessary to conduct further quantitative analysis of the magnitude of forest disturbance with the intensity of typhoon. In this study, taking the case of super typhoon Rammasun (201409), we analysed the sensitivity of four common used remote sensing indices and explored the relationship between remote sensing index and corresponding wind speeds based on pre-and post-Landsat-8 OLI (Operational Land Imager) images and a parameterized wind field model. The results proved that NBR is the most sensitive index for the detection of forest disturbance induced by Typhoon Rammasun and the variation of NBR has a significant linear dependence relation with the simulated 3-second gust wind speed.

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