Wind Profile and Spectra in Typhoon-Prone Regions in South China

Li, Lixiao; Kareem, Ahsan; Xiao, Yiqing; Song, Lili; Peng, Qin

doi:10.1061/9780784412626.081

Cited by 4 publications

(7 citation statements)

References 1 publication

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“…As upper level disturbances descend downwards, sudden changes in the wind speed and direction along the radial axis of the storm are experienced at the ground level. The downward transport of convective elements and horizontal momentum in higher level by downdraughts and boundary layer rolls also magnifies the wind speed and the variance of fluctuations in the surface (Powell et al, 1991Bradbury et al, 1994;Wurman and Winslow, 1998;Sparks and Huang, 2001;Vickery and Skerlj, 2005;Li et al, 2012aLi et al, , 2014. In light of the dominant features that are different from the extratropical storms, there is a need for better understanding of the turbulent wind characteristics and the flow structure in tropical cyclones.…”

Section: Introductionmentioning

confidence: 98%

A comparative study of field measurements of the turbulence characteristics of typhoon and hurricane winds

Kareem

Xiao

et al. 2015

Journal of Wind Engineering and Industrial Aerodynamics

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Section: Introductionmentioning

confidence: 98%

A comparative study of field measurements of the turbulence characteristics of typhoon and hurricane winds

Kareem

Xiao

et al. 2015

Journal of Wind Engineering and Industrial Aerodynamics

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“…Moreover, it is reasonable to assume that the wind strength, indicated by the mean wind speed at 10 m, impacts the shape of the typhoon boundary layer mean wind profile. Consequently, the mean wind speed at 10 m (U 10 ) interpolated from the resulting mean wind profiles derived from post-processing the WRF simulation results is checked and the resulting mean wind profiles are binned according to U 10 with a step size of 4 m·s −1 (12)(13)(14)(15)(16) When normalizing by the simulated wind speed at lowest elevation of 4 m, the resulting mean wind profiles belonging to each bin can be compared to the calculations made according to the power-law and log-law model. For the parameter α in the power-law model, the value of 0.11 as suggested by DNV for extreme condition is adopted.…”

Section: Typhoon Conditionmentioning

confidence: 99%

“…In summary, the estimates of wind speeds and wave heights under both normal and extreme conditions are necessary for the design of a floating wind turbine, and hence have become a common topic in previous studies [13]. Also focusing on the estimates of wind and wave fields, the present study introduces two models to calculate the vertical variation of wind speeds and the wave spectra under both the normal and extreme conditions.…”

Section: Introductionmentioning

confidence: 99%

Wind Profiles and Wave Spectra for Potential Wind Farms in South China Sea. Part I: Wind Speed Profile Model

et al. 2017

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Abstract:With the setting of wind energy harvesting moving from coastal waters to deep waters, the South China Sea has been deemed to offer great potential for the construction of floating wind farms thanks to the abundance of wind energy resources. An engineering model describing the wind profiles and wave spectra specific to the South China Sea conditions, which is the precondition for offshore wind farm construction, has, however, not yet been proposed. In the present study, a series of numerical simulations have been conducted using the Weather Forecast and Research model. Through analyzing the wind and wave information extracted from the numerical simulation results, engineering models to calculate vertical profiles of wind speeds and wave spectra have been postulated. While the present paper focuses on the wind profile model, a companion paper articulates the wave spectrum model. For wind profiles under typhoon conditions, the power-law and log-law models have been found applicable under the condition that the Hellmann exponent α or the friction velocity u * are modified to vary with the wind strength. For wind profiles under non-typhoon conditions, the log-law model is revised to take into consideration the influence of the atmospheric stability.

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“…Normally, the observations by Global Position System (GPS) dropsonde and Doppler radar show that the variation of mean wind speed with height follows the logarithmic law in the lower part of tropical cyclone boundary layer [21][22][23][24][25]. Thus, the logarithmic law can be used to describe lower boundary layer and the outer-vortex regions of a tropical cyclone:…”

Section: Logarithmic Law Wind Profilementioning

confidence: 99%

“…As expected, Equation 9gives a maximum turbulence ratio [σ u /u * ] max of approximately 2.85 for various roughness lengths. However, field measurements show that turbulence ratios in tropical cyclones are usually greater than the values in extratropical storms [12,24,40], making the selection of [σ u /u * ] max = 2.85 inapplicable to tropical cyclones. On the other hand, a height-independent relation between turbulence ratio σ u /u * and underlying surface roughness length z 0 was proposed by Li et al [13] based on the analysis of field measurements in typhoons.…”

Section: Turbulence Intensitymentioning

confidence: 99%

An Analytical Framework for the Investigation of Tropical Cyclone Wind Characteristics over Different Measurement Conditions

Zhou

Wang

et al. 2019

Applied Sciences

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Wind characteristics (e.g., mean wind speed, gust factor, turbulence intensity and integral scale, etc.) are quite scattered in different measurement conditions, especially during typhoon and/or hurricane processes, which results in the structural engineer ambiguously determining the wind parameters in wind-resistant design of buildings and structures in cyclone-prone regions. In tropical cyclones (including typhoons and hurricanes), the inconsistent wind characteristics may be in part ascribed to the complex flow structure with the coexistence of both mechanical and convective turbulence in the boundary layer of tropical cyclones. Another significant contribution to the scattered wind characteristics is due to various measurement conditions (e.g., terrain exposure and height) and data processing schemes (e.g., averaging time). The removal of the inconsistency in the field-measurement system may offer a more rational comparison of measured wind data from various observation platforms, and hence facilitates a better identification scheme of the wind characteristics to guide the urban planning design and wind-resistant design of buildings and structures. In this study, an analytical framework was firstly proposed to eliminate the potential observation-related effects in wind characteristics and then the wind characteristics of seven field measured tropical cyclones (four typhoons and three hurricanes) were comparatively investigated. Specifically, field measurements of wind characteristics were converted to a standard reference station with a roughness length of 0.03 m, observation duration of 10 min for mean wind and averaging time of 3 s for gusty wind at a 10 m height. The differences of the measured wind characteristics between the typhoons and hurricanes were highlighted. The standardized turbulent wind characteristics under the analytical framework for typhoons and hurricanes were compared with the corresponding recommendations in standard of American Society of Civil Engineers (ASCE 7-10) and Architectural Institute of Japan Recommendations for Loads on Buildings (AIJ-RLB-2004).

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Wind Profile and Spectra in Typhoon-Prone Regions in South China

Cited by 4 publications

References 1 publication

A comparative study of field measurements of the turbulence characteristics of typhoon and hurricane winds

A comparative study of field measurements of the turbulence characteristics of typhoon and hurricane winds

Wind Profiles and Wave Spectra for Potential Wind Farms in South China Sea. Part I: Wind Speed Profile Model

An Analytical Framework for the Investigation of Tropical Cyclone Wind Characteristics over Different Measurement Conditions

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