A boundary layer height inversion method based on LEOSPHERE100S lidar

Abstract

The present invention relates to the field of atmospheric detection technology, and discloses a boundary layer height inversion method based on a LEOSPHERE 100S laser radar. The method comprises: in DBS mode, using a laser radar and completing a directional scan every 4 seconds according to a set azimuth and elevation angle, and obtaining the radial wind speed corresponding to the azimuth angle; collecting laser radar observation data for 24 hours a day, calculating the signal-to-noise ratio of each laser radar observation data, and retaining only radial wind speeds with a signal-to-noise ratio CNR ≥ 22dB; collecting data within every 50-meter range in the vertical scan, constructing a vertical wind speed time series, and calculating the second-order partial derivative of the vertical wind speed for 30 minutes; determining the second-order partial derivative threshold and determining the daytime boundary layer height by using a potential temperature profile method of a tethered sounding; determining the nighttime boundary layer height by the maximum value of the horizontal wind speed shear in the vertical direction; and fusing the daytime boundary layer height and the nighttime boundary layer height to obtain a comprehensive all-day boundary layer height. The present invention can more accurately determine the boundary layer height throughout the day.

Description

Technical Field

[0001] The present invention relates to the field of atmospheric detection technology, and in particular to a boundary layer height inversion method based on LEOSPHERE100S laser radar. Background Art

[0002] Among traditional methods for measuring the atmospheric boundary layer, meteorological tower observations and tethered balloon detection are two common approaches. The meteorological tower method involves constructing a high tower on the ground and installing various meteorological instruments on it. These instruments measure the average temperature and wind speed profiles of the atmosphere's vertical structure, thereby calculating the height of the atmospheric boundary layer. However, this method has certain limitations. The high cost and technical difficulty of constructing taller detection towers prevent comprehensive measurement of the entire atmospheric boundary layer. On the other hand, the tethered balloon method, which involves tethering a balloon at a certain altitude and using the balloon's onboard instruments, can somewhat mitigate the shortcomings of the meteorological tower method, but it also has its drawbacks. The tethered balloon method cannot conduct long-term observations because the balloon's tethering system may malfunction over extended periods of use, and the balloon's stability and safety cannot be guaranteed. Consequently, it cannot accurately determine the boundary layer height throughout the day or night.

[0003] Therefore, it is necessary to design a boundary layer height inversion method based on LEOSPHERE100S lidar to solve the problems existing in current technology. Summary of the Invention

[0004] In view of this, the present invention proposes a boundary layer height inversion method based on LEOSPHERE100S lidar, aiming to more accurately determine the boundary layer height throughout the day and at night.

[0005] The present invention proposes a boundary layer height inversion method based on LEOSPHERE100S laser radar, comprising the following steps:

[0006] S100: In DBS mode, a laser radar is used to complete a directional scan every 4 seconds according to the set azimuth and elevation angles, and the radial wind speed corresponding to the azimuth angle is obtained;

[0007] S200: Collecting 24-hour laser radar observation data, calculating the signal-to-noise ratio of each laser radar observation data, and retaining only radial wind speeds with a signal-to-noise ratio CNR ≥ -22 dB;

[0008] S300: Collects data within every 50 meters of the vertical scan, constructs a vertical wind speed time series, and calculates the second-order partial derivative of the vertical wind speed for 30 minutes;

[0009] S400: Determine a second-order partial derivative threshold using a potential temperature profile method using a tethered sounding, and determine the daytime boundary layer height based on the second-order partial derivative threshold; determine the nighttime boundary layer height based on the maximum horizontal wind speed shear in the vertical direction; wherein nighttime is from 21:30 p.m. to 8:00 a.m. the next day;

[0010] S500: Fusing the daytime boundary layer height and the nighttime boundary layer height to obtain a comprehensive all-day boundary layer height.

[0011] Furthermore, when a laser radar is used to complete a directional scan every 4 seconds according to a set azimuth and elevation angle, and the radial wind speed corresponding to the azimuth angle is obtained, the method includes:

[0012] The azimuth angles include a first azimuth angle of 0°, a second azimuth angle of 90°, a third azimuth angle of 180°, and a fourth azimuth angle of 270°;

[0013] The elevation angle is 75°;

[0014] The radial velocity includes a first radial velocity corresponding to the first azimuth angle, a second radial velocity corresponding to the second azimuth angle, a third radial velocity corresponding to the third azimuth angle, and a fourth radial velocity corresponding to the fourth azimuth angle.

[0015] Furthermore, when a laser radar is used to complete a directional scan every 4 seconds according to a set azimuth and elevation angle, and a radial wind speed corresponding to the azimuth angle is obtained, the method further includes:

[0016] Calculating horizontal wind speed and horizontal wind direction according to the radial wind speed;

[0017] The radial wind speed is obtained by the following formula:

[0018]

[0019] Wherein, u represents the first component of radial wind speed; Vr1 represents the first radial velocity; Vr2 represents the second radial velocity; Vr3 represents the third radial velocity; Vr4 represents the fourth radial velocity; θ represents the elevation angle; v represents the second component of radial wind speed;

[0020] As mentioned above, the horizontal wind speed and horizontal wind direction are obtained by the following formula:

[0021]

[0022]

[0023] Wherein, Vh represents the horizontal wind speed; az i represents the horizontal wind direction.

[0024] Furthermore, only radial wind speeds with a signal-to-noise ratio (CNR) ≥ -22dB are retained, including:

[0025] The signal-to-noise ratio is obtained by the following formula:

[0026]

[0027] Where CNR represents the signal-to-noise ratio, S represents the average signal power, and N represents the average noise power.

[0028] Furthermore, when only radial wind speeds with a signal-to-noise ratio (CNR) ≥ -22dB are retained, the following are also included:

[0029] According to the Laida criterion, radial wind speeds exceeding the interval (μ-3σ, μ+3σ) within a 4-min period were eliminated for each height, where μ is the mean value and σ = 1.4826MAD;

[0030] MAD is obtained by the following formula:

[0031] MAD=median(|Vri-median(Vr)|);

[0032] Wherein, Vri represents the i-th radial wind speed; Vr represents the radial wind speed.

[0033] Furthermore, vertical wind speed data for 30 minutes is collected, and the second-order partial derivative of vertical wind speed is calculated based on the vertical wind speed data;

[0034]

[0035] Where f represents the vertical wind speed variance; w represents the vertical wind speed; and z represents the height.

[0036] Furthermore, the second-order derivative threshold of the vertical wind speed is 0.15.

[0037] Furthermore, when determining the nighttime boundary layer height by the maximum horizontal wind speed shear in the vertical direction, it includes:

[0038] The nighttime boundary layer height is defined as the point where the vertical shear of the horizontal wind reaches a maximum;

[0039] The horizontal wind vertical shear is obtained by the following equation:

[0040]

[0041] Where ΔVh represents the horizontal wind speed difference between two heights; Δz represents the height difference; u t Indicates the upper horizontal wind speed; u b Indicates the horizontal wind speed in the lower layer; z t Indicates the upper layer height; z b Indicates the height of the lower layer; v t Indicates the upper horizontal wind speed; vb Indicates the horizontal wind speed in the lower layer.

[0042] Compared with the prior art, the beneficial effect of the present invention is that: in the DBS mode, the present invention can ensure that the laser radar covers a sufficiently wide area by setting appropriate azimuth and elevation angles, thereby obtaining more comprehensive wind speed information. The screening standard of the signal-to-noise ratio CNR of -22dB is based on experimental and theoretical analysis. It can effectively eliminate data with large noise interference and ensure data quality. When calculating the horizontal wind speed and wind direction, the formula used takes into account the two components of the radial wind speed, u and v, which helps to more accurately reflect the actual situation of the wind. The threshold of the second-order partial derivative of the vertical wind speed is determined by the tethered sounding potential temperature profile method, thereby determining the boundary layer height, making the vertical wind speed second-order partial derivative method more accurate. Combined with the horizontal wind speed shear maximum value method, the boundary layer height of the whole day can be more accurately determined independently without relying on tethered sounding data, thereby providing more accurate data support for meteorological research and environmental monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0044] Figure 1 Flowchart of the boundary layer height inversion method based on LEOSPHERE100S lidar provided in an embodiment of the present invention;

[0045] Figure 2 The second-order partial derivative of vertical wind speed based on the LEOSPHERE100S lidar boundary layer height inversion method provided in an embodiment of the present invention;

[0046] Figure 3 The potential temperature profile and the second-order deviator profile of the vertical wind speed based on the LEOSPHERE100S lidar boundary layer height inversion method provided in the embodiment of the present invention;

[0047] Figure 4 A schematic diagram of the daytime boundary layer height based on the LEOSPHERE100S lidar boundary layer height inversion method provided in an embodiment of the present invention;

[0048] Figure 5 A schematic diagram of the nighttime boundary layer height based on the LEOSPHERE100S lidar boundary layer height inversion method provided in an embodiment of the present invention;

[0049] Figure 6A schematic diagram of the comprehensive all-day boundary layer height based on the LEOSPHERE100S lidar boundary layer height inversion method provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0050] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, unless there is a conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0051] See Figure 1 As shown, in some embodiments of the present application, this embodiment provides a boundary layer height inversion method based on LEOSPHERE100S laser radar, including the following steps:

[0052] S100: In DBS mode, a laser radar is used to complete a directional scan every 4 seconds according to the set azimuth and elevation angles, and the radial wind speed corresponding to the azimuth angle is obtained;

[0053] S200: Collecting 24-hour laser radar observation data, calculating the signal-to-noise ratio of each laser radar observation data, and retaining only radial wind speeds with a signal-to-noise ratio CNR ≥ -22 dB;

[0054] S300: Collects data within every 50 meters of the vertical scan, constructs a vertical wind speed time series, and calculates the second-order partial derivative of the vertical wind speed for 30 minutes;

[0055] S400: Determine a second-order partial derivative threshold using a potential temperature profile method using a tethered sounding, and determine the daytime boundary layer height based on the second-order partial derivative threshold; determine the nighttime boundary layer height based on the maximum horizontal wind speed shear in the vertical direction; wherein nighttime is from 21:30 p.m. to 8:00 a.m. the next day;

[0056] S500: Fusing the daytime boundary layer height and the nighttime boundary layer height to obtain a comprehensive all-day boundary layer height.

[0057] It can be seen that DBS mode is an effective data acquisition and processing method, which can improve the accuracy of boundary layer height inversion. In DBS mode, the scanning speed of the lidar and the frequency of data acquisition are crucial for obtaining high-quality radial wind speed data. By setting appropriate azimuth and elevation angles, it can be ensured that the lidar covers a sufficiently wide area, thereby obtaining more comprehensive wind speed information. The screening standard of -22dB for the signal-to-noise ratio (CNR) is based on experimental and theoretical analysis. It can effectively eliminate data with large noise interference and ensure data quality. When calculating horizontal wind speed and wind direction, the formula used takes into account the two components of the radial wind speed, u and v, which helps to more accurately reflect the actual wind conditions. The calculation of the vertical wind speed variance provides an important reference for determining the boundary layer height. The threshold of the second-order partial derivative of vertical wind speed is determined by the tethered sounding potential temperature profile method, thereby determining the boundary layer height, making the second-order partial derivative of vertical wind speed more accurate. Combined with the maximum horizontal wind speed shear method, the boundary layer height of the whole day can be determined more accurately and independently without relying on tethered sounding data, thereby providing more accurate data support for meteorological research and environmental monitoring.

[0058] Specifically, when a laser radar is used to complete a directional scan every 4 seconds according to a set azimuth and elevation angle, and the radial wind speed corresponding to the azimuth angle is obtained, the following steps are included:

[0059] The azimuth angles include a first azimuth angle of 0°, a second azimuth angle of 90°, a third azimuth angle of 180°, and a fourth azimuth angle of 270°;

[0060] The elevation angle is 75°;

[0061] The radial velocity includes a first radial velocity corresponding to the first azimuth angle, a second radial velocity corresponding to the second azimuth angle, a third radial velocity corresponding to the third azimuth angle, and a fourth radial velocity corresponding to the fourth azimuth angle.

[0062] It can be seen that in DBS mode, the lidar's scanning speed and data acquisition frequency are crucial for obtaining high-quality radial wind speed data. By setting appropriate azimuth and elevation angles, the lidar can ensure that it covers a sufficiently wide area, thereby obtaining more comprehensive wind speed information.

[0063] Specifically, when a laser radar is used to complete a directional scan every 4 seconds according to a set azimuth and elevation angle, and the radial wind speed corresponding to the azimuth angle is obtained, the method further includes:

[0064] Calculating horizontal wind speed and horizontal wind direction according to the radial wind speed;

[0065] The radial wind speed is obtained by the following formula:

[0066]

[0067] Wherein, u represents the first component of radial wind speed; Vr1 represents the first radial velocity; Vr2 represents the second radial velocity; Vr3 represents the third radial velocity; Vr4 represents the fourth radial velocity; θ represents the elevation angle; v represents the second component of radial wind speed;

[0068] As mentioned above, the horizontal wind speed and horizontal wind direction are obtained by the following formula:

[0069]

[0070]

[0071] Wherein, Vh represents the horizontal wind speed; az i represents the horizontal wind direction.

[0072] It can be seen that the horizontal wind speed and direction calculated using the above formula can more accurately describe the actual wind field conditions. The calculation of horizontal wind speed takes into account the two components of radial wind speed, u and v, while the calculation of horizontal wind direction is based on the ratio of these two components, using the inverse tangent function to obtain the wind direction angle. This processing method not only improves data accuracy but also provides a solid foundation for subsequent boundary layer height inversion.

[0073] Specifically, only radial wind speeds with a signal-to-noise ratio (CNR) ≥ -22dB are retained, including:

[0074] The signal-to-noise ratio is obtained by the following formula:

[0075]

[0076] Where CNR represents the signal-to-noise ratio, S represents the average signal power, and N represents the average noise power.

[0077] It's understandable that average signal power is calculated by averaging the signals collected by the lidar, while average noise power is calculated by averaging the background noise. The signal-to-noise ratio formula reflects the relative strength of the signal to the noise, helping us select high-quality data. In practice, the signal-to-noise ratio threshold is set at -22dB, meaning that data will only be retained for subsequent analysis if the signal strength is at least 22dB higher than the noise intensity.

[0078] Specifically, when only radial wind speeds with a signal-to-noise ratio (CNR) ≥ -22dB are retained, the following are also included:

[0079] According to the Laida criterion, radial wind speeds exceeding the interval (μ-3σ, μ+3σ) within a 4-min period were eliminated for each height, where μ is the mean value and σ = 1.4826MAD;

[0080] MAD is obtained by the following formula:

[0081] MAD=median(|Vri-median(Vr)|);

[0082] Wherein, Vri represents the i-th radial wind speed; Vr represents the radial wind speed.

[0083] It can be understood that MAD, or median absolute deviation, is a robust statistic used to measure the degree of discreteness of data distribution. By calculating the MAD value of the radial wind speed at each altitude layer, outliers can be identified and eliminated, thereby further improving data quality. The Laida criterion is a commonly used outlier detection method, which determines the range of outliers based on the mean and standard deviation of the data. In this method, by setting a threshold of 3 times the MAD, radial wind speed data that exceeds the range of (μ-3σ, μ+3σ) within 4 minutes can be effectively identified and eliminated. Such processing not only ensures the accuracy of the data, but also helps to reduce errors caused by outliers, providing a guarantee for the accurate inversion of boundary layer height. Through the above steps, more accurate boundary layer height data can be obtained, providing strong data support for meteorological research and environmental monitoring.

[0084] Furthermore, vertical wind speed data for 30 minutes is collected, and the second-order partial derivative of vertical wind speed is calculated based on the vertical wind speed data;

[0085]

[0086] Where f represents the vertical wind speed variance; w represents the vertical wind speed; and z represents the height.

[0087] Specifically, the second-order deviator threshold of the vertical wind speed is 0.15.

[0088] It is understandable that the calculation formula for the second-order partial derivative of vertical wind speed can reflect the degree of change in wind speed in the vertical direction. By calculating the second-order partial derivative of vertical wind speed within 30 minutes, the statistics of wind speed changes within a time period can be obtained, which is of great significance for determining the height of the boundary layer. The larger the second-order partial derivative of vertical wind speed, the more drastic the change in wind speed in the vertical direction, which is usually related to turbulent activity within the boundary layer. Therefore, by analyzing the second-order partial derivative of vertical wind speed, it can assist in determining the dynamic characteristics of the boundary layer and provide important reference information for the inversion of boundary layer height.

[0089] See Figure 4As shown, the second-order vertical wind speed threshold is a key parameter in determining the height of the stable boundary layer. It helps distinguish turbulent activity within the boundary layer from motion in the upper atmosphere. When the second-order partial derivative of the vertical wind speed is less than 0.15, the atmospheric stratification is considered stable. This method can accurately determine the height of the daytime boundary layer, providing important data for weather forecasting and environmental monitoring.

[0090] Specifically, when determining the nighttime boundary layer height by the maximum horizontal wind shear in the vertical direction, it includes:

[0091] The nighttime boundary layer height is defined as the point where the vertical shear of the horizontal wind reaches a maximum;

[0092] The horizontal wind vertical shear is obtained by the following equation:

[0093]

[0094] Where ΔVh represents the horizontal wind speed difference between two heights; Δz represents the height difference; u t Indicates the upper horizontal wind speed; u b Indicates the horizontal wind speed in the lower layer; z t Indicates the upper layer height; z b Indicates the height of the lower layer; v t Indicates the upper horizontal wind speed; v b Indicates the horizontal wind speed in the lower layer.

[0095] See Figure 5 As shown, in this embodiment, when the daytime boundary layer height is determined by calculating the second-order partial derivative of the vertical wind speed, the stable boundary layer at night and early morning often fails, so the maximum horizontal wind speed shear in the vertical direction is used to determine the nighttime boundary layer height.

[0096] It is understandable that the maximum horizontal wind speed shear usually occurs near the top of the boundary layer. This is because the wind speed inside the boundary layer changes with increasing altitude, and at the top of the boundary layer, the rate of change of wind speed is the largest. By calculating the horizontal wind speed difference between different altitude layers and finding the point with the largest rate of change, the height of the nighttime boundary layer can be determined more accurately. This method is particularly suitable for nighttime and early morning hours because the top of the boundary layer is usually more stable at this time, and the formation of a ground-based inversion layer makes the wind speed changes in the vertical direction more significant. In this way, more accurate boundary layer height data can be provided for meteorological forecasting and environmental monitoring, which helps to improve the accuracy of weather forecasts and the efficiency of environmental monitoring.

[0097] See Figure 6 As shown, in this embodiment, the daytime boundary layer height and the nighttime boundary layer height are fused to obtain a comprehensive all-day boundary layer height, so that the inversion result of the all-day boundary layer height is more comprehensive and accurate.

[0098] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or a combination of software and hardware embodiments. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0099] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0100] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0101] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0102] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A boundary layer height inversion method based on LEOSPHERE100S lidar, characterized in that: include: In DBS mode, a laser radar is used to complete a directional scan every 4 seconds according to the set azimuth and elevation angles, and the radial wind speed corresponding to the azimuth angle is obtained; Collect lidar observation data for 24 hours a day, calculate the signal-to-noise ratio of each lidar observation data, and only retain radial wind speeds with a signal-to-noise ratio (CNR) ≥ -22dB; Collect data within every 50 meters of the vertical scan, construct a vertical wind speed time series, and calculate the second-order partial derivative of the vertical wind speed for 30 minutes; The second-order partial derivative threshold is determined by the potential temperature profile method of the tethered sounding, and the daytime boundary layer height is determined based on the second-order partial derivative threshold; the nighttime boundary layer height is determined by the maximum horizontal wind speed shear in the vertical direction; wherein the nighttime is from 21:30 pm to 8:00 am the next day; The daytime boundary layer height and the nighttime boundary layer height are fused to obtain a comprehensive all-day boundary layer height.

2. The boundary layer height inversion method based on LEOSPHERE100S laser radar according to claim 1 is characterized in that: When using a laser radar and completing a directional scan every 4 seconds according to the set azimuth and elevation angles, and obtaining the radial wind speed corresponding to the azimuth angle, it includes: The azimuth angles include a first azimuth angle of 0°, a second azimuth angle of 90°, a third azimuth angle of 180°, and a fourth azimuth angle of 270°; The elevation angle is 75°; The radial wind speed includes a first radial speed corresponding to the first azimuth angle, a second radial speed corresponding to the second azimuth angle, a third radial speed corresponding to the third azimuth angle, and a fourth radial speed corresponding to the fourth azimuth angle.

3. The boundary layer height inversion method based on LEOSPHERE100S laser radar according to claim 2 is characterized in that: When a laser radar is used to complete a directional scan every 4 seconds according to a set azimuth and elevation angle, and obtain the radial wind speed corresponding to the azimuth angle, the method further includes: Calculating horizontal wind speed and horizontal wind direction according to the radial wind speed; The radial wind speed is obtained by the following formula: ； ； in, represents the first component of radial wind speed; represents the first radial velocity; represents the second radial velocity; represents the third radial velocity; represents the fourth radial velocity; Indicates the elevation angle; represents the second component of radial wind speed; As mentioned above, the horizontal wind speed and horizontal wind direction are obtained by the following formula: ； ； in, Indicates horizontal wind speed; Indicates horizontal wind direction.

4. The boundary layer height inversion method based on LEOSPHERE100S laser radar according to claim 1 is characterized in that: When only radial wind speeds with a signal-to-noise ratio (CNR) ≥ -22dB are retained, these include: The signal-to-noise ratio is obtained by the following formula: ； in, represents the signal-to-noise ratio; represents the average signal power; represents the average noise power.

5. The boundary layer height inversion method based on LEOSPHERE100S laser radar according to claim 4 is characterized in that: When only radial wind speeds with a signal-to-noise ratio (CNR) ≥ -22dB are retained, the following are also included: According to the Laida criterion, radial wind speeds exceeding the interval (µ-3σ, µ+3σ) within a 4-min period were eliminated for each height, where µ is the mean value and σ = 1.4826MAD; MAD is obtained by the following formula: ； in, i represents the i-th radial wind speed; Indicates radial wind speed.

6. The boundary layer height inversion method based on LEOSPHERE100S laser radar according to claim 1 is characterized in that: When calculating the 30-minute second-order partial derivative of vertical wind speed, include: Collecting 30 minutes of vertical wind speed data, and calculating the second-order partial derivative of the vertical wind speed based on the vertical wind speed data; ； in, represents the vertical wind speed variance; Indicates vertical wind speed; Indicates altitude.

7. The boundary layer height inversion method based on LEOSPHERE100S laser radar according to claim 1 is characterized in that: The second-order deflection threshold of the vertical wind speed is 0.

15.

8. The boundary layer height inversion method based on LEOSPHERE100S laser radar according to claim 1 is characterized in that: When determining the nighttime boundary layer height by the maximum horizontal wind shear in the vertical direction, it includes: The nighttime boundary layer height is defined as the point where the vertical shear of the horizontal wind reaches a maximum; The horizontal wind vertical shear is obtained by the following equation: ； in, Indicates the horizontal wind speed difference between two heights; Indicates height difference; Indicates the upper horizontal wind speed; Indicates the horizontal wind speed at the lower layer; Indicates the upper level height; Indicates the height of the lower layer; Indicates the upper horizontal wind speed; Indicates the horizontal wind speed in the lower layer.

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