# Analysis of the Near-Ground Wind Field Characteristics during Typhoon Soulik
## 5 Conclusions  
Based on 10 min wind field data at heights of 15, 27, 53, 67, and 82 m in China's coastal areas, wind field characteristics such as Typhoon Soulik's wind speed profile, turbulence intensity, gust factor, peak factor, and turbulence integral scale were analyzed. The following significant conclusions were made:  
(1) When the mean wind velocity exceeded 12 m/s, Typhoon Soulik's average wind speed variation trend with height aligned with both the power law and the logarithmic law. However, the Deaves-Harris model showed significant differences.  
(2) The gust components in \(u\), \(v\), and \(w\) orientations fitted in the form of \(G_{i}=a\big{(}\frac{z}{10}\big{)}^{\beta}\) approximately coincided with the changes in measured gust factors with height. Furthermore, the measured data were utilized to examine the correlation between gust factor and turbulence intensity, and these findings were then compared to previous study outcomes. The results were found to be consistent with [PERSON]'s empirical formula.  
(3) The integral scale of turbulence in \(u\), \(v\), and \(w\) orientations was positively correlated with both the average wind velocity and height. The integral scales of turbulence in all directions at heights of 15, 53, and 82 m had ratios of 1:0.68:0.11, 1:0.67:0.27, and 1:0.67:0.30, respectively.  
(4) A power spectrum analysis was performed on the fluctuating wind velocity near the ground during Typhoon Soulik. The results revealed that the von Karman spectrum effectively depicted the power spectrum of wind velocity. Also, the modified Kaimal cross-spectrum model showed excellent concordance with the observed cross-spectrum in all ranges of frequencies.  
Conceptualization, X.W.; writing--original draft preparation, Z.Y.; supervision, Y.G.; writing--review and editing, Y.L. All authors have read and agreed to the published version of the manuscript.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Height (m)** & \(a\) & \(b\) & \(c\) & **Kaimal** \\ \hline
15 & 2.4 & 65.4 & 1.29 & \(\frac{-nC_{\text{sw}}(n)}{\sigma_{s}^{2}}=\frac{2.4f}{(1+65.4f)^{128}}\) \\
53 & 5.1 & 45.9 & 1.62 & \(\frac{-nC_{\text{sw}}(n)}{\sigma_{s}^{2}}=\frac{5.1f}{(1+45.9f)^{128}}\) \\
82 & 3.1 & 44.3 & 1.61 & \(\frac{-nC_{\text{sw}}(n)}{\sigma_{s}^{2}}=\frac{3.1f}{(1+44.3f)^{137}}\) \\ \hline \hline \end{tabular}
\end{table}
Table 7: Fitting parameters and mathematical expressions.  
Figure 18: Power spectra at different heights: (**a**) 15 m, (**b**) 53 m, and (**c**) 82 m.  
**Funding:** This paper was partially supported by the Natural Science Foundation of Chongqing (Grant No.: CSTB2022 NSCQ-MSX1655) and the State Key Laboratory of Structural Dynamics of Bridge Engineering and Key Laboratory of Bridge Structure Seismic Technology for Transportation Industry Open Fund (Grant No.: 202205).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** All data generated or analyzed during this study are included in this article. All data included in this study are available upon request by contact with the corresponding author.  
**Conflicts of Interest:** The authors declare no conflicts of interest.