Comparison of tropical cyclone wind field models and their influence on estimated wind hazard

被引:15
|
作者
Gu, J. Y. [1 ]
Sheng, C. [1 ]
Hong, H. P. [1 ]
机构
[1] Univ Western Ontario, Dept Civil & Environm Engn, 1151 Richmond St, London, ON N6A 5B9, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
tropical cyclone; wind field; wind hazard; adjustment factor; simulation; BOUNDARY-LAYER JETS; HURRICANE; SIMULATION; PRESSURE; PROFILES; DYNAMICS; REGIONS; CORE; RISK;
D O I
10.12989/was.2020.31.4.321
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Engineering type tropical cyclone (TC) wind field models are used to estimate TC wind hazard. Some of the models are well-calibrated using observation data, while others are not extensively compared and verified. They are all proxies to the real TC wind fields. The computational effort for their use differs. In the present study, a comparison of the predicted wind fields is presented by considering three commonly used models: the gradient wind field model, slab-resolving model, and a linear height-resolving model. These models essentially predict the horizontal wind speed at a different height. The gradient wind field model and linear height-resolving model are simple to use while the nonlinear slab-resolving model is more compute-intensive. A set of factors is estimated and recommended such that the estimated TC wind hazard by using these models becomes more consistent. The use of the models, including the developed set of factors, for estimating TC wind hazard over-water and overland is presented by considering the historical tracks for a few sites. It is shown that the annual maximum TC wind speed can be adequately modelled by the generalized extreme value distribution.
引用
收藏
页码:321 / 334
页数:14
相关论文
共 50 条
  • [21] Mapping the Wind Hazard of Global Tropical Cyclones with Parametric Wind Field Models by Considering the Effects of Local Factors
    Chenyan Tan
    Weihua Fang
    International Journal of Disaster Risk Science, 2018, 9 : 86 - 99
  • [22] Assessment of wind hazard at wind turbine sites based on CFD simulation under tropical cyclone conditions
    Li, Yuhui
    Tang, Shengming
    Zhang, Xiaodong
    Yu, Hui
    Zhu, Rong
    Zhou, Limin
    SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2025, 73
  • [23] Tropical cyclone wind hazard assessment for Donghaitang wind farm (Zhejiang Province, China): Case study
    Li, Yuhui
    Tang, Shengming
    Li, Yongping
    Zhu, Rong
    Yu, Hui
    FRONTIERS IN EARTH SCIENCE, 2023, 10
  • [24] Mapping the Wind Hazard of Global Tropical Cyclones with Parametric Wind Field Models by Considering the Effects of Local Factors
    Tan, Chenyan
    Fang, Weihua
    INTERNATIONAL JOURNAL OF DISASTER RISK SCIENCE, 2018, 9 (01) : 86 - 99
  • [25] Modelling global tropical cyclone wind footprints
    Done, James M.
    Ge, Ming
    Holland, Greg
    Dima-West, Ioana
    Phibbs, Samuel
    Saville, Geoffrey R.
    Wang, Yuqing
    NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2020, 20 (02) : 567 - 580
  • [26] Estimation of Tropical Cyclone Wind Hazard for Darwin: Comparison with Two Other Locations and the Australian Wind-Loading Code
    Cook, Garry D.
    Nicholls, Michael J.
    JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY, 2009, 48 (11) : 2331 - 2340
  • [27] Tropical cyclone wind field forcing for surge models: critical issues and sensitivities
    V. J. Cardone
    A. T. Cox
    Natural Hazards, 2009, 51 : 29 - 47
  • [28] Modeling tropical cyclone boundary layer: Height-resolving pressure and wind fields
    Snaiki, Reda
    Wu, Teng
    JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 2017, 170 : 18 - 27
  • [29] Machine-learning-based tropical cyclone wind field model incorporating multiple meteorological parameters
    Wei, Miaomiao
    Fang, Genshen
    Nikitas, Nikolaos
    Ge, Yaojun
    JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS, 2024, 255
  • [30] Investigation of Tropical Cyclone Wind Models With Application to Storm Tide Simulations
    Wangl, Shuai
    Lin, Ning
    Gori, Avantika
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2022, 127 (17)