# Study of the Algorithm for Wind Shear Detection with Lidar Based on Shear Intensity Factor
## 4 Conclusions and Discussion  
This paper improved the ramp length extension and contraction strategy of the conventional single ramp wind shear detection algorithm based on the change of wind shear intensity factor. It then tested the effectiveness of the improved algorithm by constructing the numerical simulation wind field. We then compared the wind shear detection results of the improved algorithm with the traditional single ramp and double ramp detection algorithms. Our conclusions are as follows:  
1. The conventional single ramp wind shear detection algorithm (WSDHP) can accurately locate the maximum wind shear. However, when the real optimal ramp length is long enough (generally longer than twice the distance of adjacent data point locations), the algorithm cannot accurately calculate the maximum wind shear value and the real wind shear intensity is easily underestimated.
2. The double ramp detection algorithm is more sensitive to weak wind shear and can accurately detect it. However, it is also easy to release wrong wind shear detection results and cause an interference of wind shear warnings.
3. The improved single ramp wind shear detection algorithm (WSDSF) can more accurately calculate the location and intensity of the maximum wind shear and provide accurate early warnings of the location and intensity of wind shear.  
Overall, the improved wind shear detection algorithm has obvious advantages over the other two algorithms. However, the three wind shear detection algorithms have unique characteristics. In the factual wind shear warning service, we must combine the results of the three algorithms for our final results. In this way, we can not only verify the accuracy of the detection results based on the three algorithms, but also accurately detect the wind shear with various intensities. It is really not enough to test the effectiveness of the improved algorithm only based on numerical simulations, so further factual wind shear detection experiments are necessary in a follow-up study.  
**Author Contributions**: Visualization, Y.S.; experimentation, S.Z.; writing--original draft preparation; S.Z. and Y.S.; writing--review and editing, Y.S. All authors have read and agreed to the published version of the manuscript.  
**Funding**: This research received no external funding.  
**Data Availability Statement**: Data is contained within the article.  
**Conflicts of Interest**: The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multicolumn{1}{c}{\multirow{2}{*}{Wind Fields}} & \multirow{2}{*}{\begin{tabular}{c} **Algorithms** \\ **WSDSF** \\ \end{tabular} } & \multirow{2}{*}{\
\begin{tabular}{c} **WSDHP** \\ **Detection Algorithm** \\ \end{tabular} } & \multicolumn{1}{c}{
\begin{tabular}{c} **Double Ramp** \\ **Detection Algorithm** \\ \end{tabular} } \\ \hline \multirow{4}{*}{Frontal wind field} & Mild & 7 & 1 & 0 \\  & Moderate & 0 & 0 & 1 \\  & Strong & 0 & 0 & 0 \\  & Severe & 0 & 0 & 0 \\  & Mild & 0 & 0 & 0 \\  & Moderate & 0 & 3 & 2 \\  & Strong & 2 & 0 & 2 \\  & Severe & 18 & 2 & 4 \\  & Mild & 0 & 0 & 0 \\  & Moderate & 1 & 0 & 0 \\  & Strong & 13 & 1 & 0 \\  & Severe & 6 & 1 & 3 \\  & Mild & 20 & 9 & 1 \\  & Moderate & 0 & 0 & 9 \\  & Strong & 0 & 0 & 2 \\  & Severe & 0 & 0 & 0 \\ \hline \hline \end{tabular}
\end{table}
Table 2: The number of wind shear alerts of different levels under different wind fields.