Estimation of tropical cyclone wind hazards in coastal regions of China

Abstract

Abstract. Coastal regions of China feature high population densities as well as wind-sensitive structures and are therefore vulnerable to tropical cyclones (TCs) with approximately six to eight landfalls annually. This study predicts TC wind hazard curves in terms of design wind speed versus return periods for major coastal cities of China to facilitate TC-wind-resistant design and disaster mitigation as well as insurance-related risk assessment. The 10 min wind information provided by the Japan Meteorological Agency (JMA) from 1977 to 2015 is employed to rebuild TC wind field parameters (radius of maximum winds Rmax,s and shape parameter of radial pressure profile Bs) at surface level using a height-resolving boundary layer model. These parameters will be documented to develop an improved JMA dataset. The probabilistic behaviors of historical tracks and wind field parameters at the first time step within a 500 km radius subregion centered at a site of interest are examined to determine preferable probability distribution models before stochastically generating correlated genesis parameters utilizing the Cholesky decomposition method. Recursive models are applied for translation speed, Rmax,s and Bs during the TC track and wind field simulations. Site-specific TC wind hazards are studied using 10 000-year Monte Carlo simulations and compared with code suggestions as well as other studies. The resulting estimated wind speeds for northern cities (Ningbo and Wenzhou) under a TC climate are higher than code recommendations, while those for southern cities (Zhanjiang and Haikou) are lower. Other cities show a satisfactory agreement with code provisions at the height of 10 m. Some potential reasons for these findings are discussed to emphasize the importance of independently developing hazard curves of TC winds.

Rapid Damage Prediction and Risk Assessment for Tropical Cyclones at a Fine Grid in Guangdong Province, South China

“…It remains rare to encounter in many previous studies the application of wind field models that determine MWS for damage prediction or risk assessment of possible TC disasters. The parametric wind field model can quickly convert the point wind speed data into a spreading grid using the key parameters of TC records, so that the potential damage caused by the wind could be rapidly estimated for TC emergency responses (Fang et al 2020).…”

Observed Surface Wind Field Structure of Severe Tropical Cyclones and Associated Precipitation

“…With an increase in higher resolution data, such as Multiplatform Tropical Cyclone Surface Wind Analysis (MTCSWA) and buoy observations, new statistical models have advanced. For example, there are now symmetric wind field models [18], an inflow angle asymmetry model (TCIAA model) [19], a decomposed TC boundary layer model [20,21], and a height-resolving, linear analytical model of the boundary layer [22]. These newly developed models provide a relatively accurate description of the entire surface wind field of a TC.…”

Quantitative Risk Assessment of Population Affected by Tropical Cyclones Through Joint Consideration of Extreme Precipitation and Strong Wind—A Case Study of Hainan Province

“…Historical records of different variables are incorporated into tropical cyclone risk model studies to make meaningful estimations of tropical cyclone risk. For example, wind speed is one of the most critical factors that affect the losses caused by tropical cyclones (Darling, 1991;Fang et al, 2020;Georgiou et al, 1983;Sajjad & Chan, 2019;Watson & Johnson, 2004). Heavy rain, which can cause floods, is another essential factor of tropical cyclone hazard; e.g., the casualty and economic losses caused by Hurricane Katrina' were mainly due to heavy rainfall (Kates et al, 2006).…”