Prediction of typhoon wind by Level 2.5 closure model

Yoshida, M.; Yamamoto, Masahito; Takagi, Kenji; Ohkuma, Takeshi

doi:10.1016/j.jweia.2008.02.016

Cited by 8 publications

(3 citation statements)

References 15 publications

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“…The power law is the most popular pattern for describing the vertical distribution of wind speed in the wind resistance codes and standards of many countries, including China (Tamura et al, 2007;Yoshida et al, 2008;Ge et al, 2010). The formula is…”

Section: Variation Of the Power Law Exponent During Typhoon Processesmentioning

confidence: 99%

Characteristics of wind profiles in the landfalling typhoon boundary layer

Song

Chen²,

Wang

et al. 2016

Journal of Wind Engineering and Industrial Aerodynamics

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Section: Variation Of the Power Law Exponent During Typhoon Processesmentioning

confidence: 99%

Characteristics of wind profiles in the landfalling typhoon boundary layer

Song

Chen²,

Wang

et al. 2016

Journal of Wind Engineering and Industrial Aerodynamics

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“…e power-law model is the most popular pattern to describe the vertical distribution of wind speed in the wind resistance codes and standards of many countries, due to its simple form [28,29]. e power exponent α is an important parameter reflecting the variation in the mean wind speed with height.…”

Section: E Effect Of Mean Wind Speed On Power Exponentmentioning

confidence: 99%

Comparative Study of the Near-Surface Typhoon Wind Profile Fitting between Offshore and Onshore Areas

Wang

Guo

Wang

2021

Mathematical Problems in Engineering

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The study of typhoon wind profiles, especially offshore typhoon wind profiles, has been constrained by the scarcity of observational data. In this study, the Doppler wind lidar was used to observe the offshore wind profiles during Super Typhoon Mangkhut and onshore wind profiles during Super Typhoon Lekima. Four wind profile models, including the power law, logarithmic law, Deaves–Harris (D-H), and Gryning, were selected in the height range of 0–300 m to fit the wind profile. The variations in the power exponent with the mean wind speed and roughness length were also analyzed. The results showed that the wind profiles fitted by the four models were generally in good agreement with the observed wind profiles with correlation coefficients greater than 0.98 and root mean square deviations less than 0.5 m s−1. For the offshore case, the fitting degree of all wind profile models improved with increasing mean wind speed. Specifically, the D-H model had the highest fitting degree when the horizontal mean wind speed at 40 m was in the range of 8–25 m s−1, while the log-law model had the highest fitting degree when the wind speed exceeded 30 m s−1. For the onshore case, the fitting degree of the four wind profile models deteriorated with increasing mean wind speed, and the log-law model had the highest fitting degree in all wind speed intervals from 8 to 30 m s−1. For both offshore and onshore cases, the power exponent was less affected by mean wind speed and increased with increasing roughness length, and the logarithmic empirical model proposed in this study could well characterize the relationship between the power exponent and roughness length.

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“…For example, Yasui et al [16] and Xiao et al [17] presented refinements of the Monte Carlo method, focusing on improvements to the statistical distribution functions describing typhoon characteristics that were used in the simulation. In addition, Yoshida et al [18] proposed a model for predicting the wind speed and the direction of typhoon winds, according to the Monte Carlo method.…”

Section: Introductionmentioning

confidence: 99%

Regional Forecasting of Wind Speeds during Typhoon Landfall in Taiwan: A Case Study of Westward-Moving Typhoons

et al. 2018

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Abstract:Taiwan is located on a route where typhoons often strike. Each year, the strong winds accompanying typhoons are a substantial threat and cause significant damage. However, because the terrains of high mountains in Taiwan vary greatly, when a typhoon passes the Central Mountain Range (CMR), the wind speed of typhoons becomes difficult to predict. This research had two primary objectives: (1) to develop data-driven techniques and a powerful artificial neural network (ANN) model to predict the highly complex nonlinear wind systems in western Taiwan; and, (2) to investigate the accuracy of wind speed predictions at various locations and for various durations in western Taiwan when the track of westward typhoons is affected by the complex geographical shelters and disturbances of the CMR. This study developed a typhoon wind speed prediction model that evaluated various typhoon tracks (covering Type 2, Type 3, and Type 4 tracks, as defined by the Central Weather Bureau), and evaluated the prediction accuracy at Hsinchu, Wuqi, and Kaohsiung Stations in western Taiwan. Back propagation neural networks (BPNNs) were employed to establish wind speed prediction models, and a linear regression model was adopted as the benchmark to evaluate the strengths and weaknesses of the BPNNs. The results were as follows: (1) The BPNNs generally had favorable performance in predicting wind speeds and their performances were superior to linear regressions; (2) when absolute errors were adopted to evaluate the prediction performances, the predictions at Hsinchu Station were the most accurate, whereas those at Wuqi Station were the least accurate; however, when relative errors were adopted, the predictions at Hsinchu Station were again the most accurate, whereas those at Kaohsiung were the least accurate; and, (3) regarding the relative error rates for the maximum wind speed of Types 2, 3, and 4 typhoons, Wuqi, Kaohsiung, and Wuqi had the most accurate performance, respectively; as for maximum wind time error (ET M ) for Types 2, 3, and 4 typhoons, Kaohsiung, Wuqi, and Wuqi correspondingly performed the most favorably.

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Prediction of typhoon wind by Level 2.5 closure model

Cited by 8 publications

References 15 publications

Characteristics of wind profiles in the landfalling typhoon boundary layer

Characteristics of wind profiles in the landfalling typhoon boundary layer

Comparative Study of the Near-Surface Typhoon Wind Profile Fitting between Offshore and Onshore Areas

Regional Forecasting of Wind Speeds during Typhoon Landfall in Taiwan: A Case Study of Westward-Moving Typhoons

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