Lidar boundary layer height inversion method based on LEOSPHERE100S

Abstract

The invention relates to the technical field of atmospheric exploration, and discloses a boundary layer height inversion method based on an LEOSPHERE100S laser radar, and the method comprises the steps: completing one-time direction scanning every four seconds through employing the laser radar according to a set azimuth angle and a set elevation angle in a DBS mode, and obtaining the radial wind speed corresponding to the azimuth angle; the method comprises the following steps: collecting laser radar observation data of 24 hours in the whole day, calculating the signal-to-noise ratio of each piece of laser radar observation data, and only reserving a radial wind speed with the signal-to-noise ratio CNR greater than or equal to-22dB; collecting data in a range of every 50 meters in vertical scanning, constructing a vertical wind speed time sequence, and calculating a second-order partial derivative of the vertical wind speed in 30 minutes; determining a second-order partial derivative threshold value and determining the height of a boundary layer in the daytime through a position temperature profile method of mooring sounding; determining the height of a night boundary layer through the maximum value of horizontal wind speed shear in the vertical direction; and fusing the daytime boundary layer height and the night boundary layer height to obtain a comprehensive all-day boundary layer height. According to the invention, the all-day boundary layer height can be determined more accurately.

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 the traditional methods for detecting the atmospheric boundary layer, the meteorological tower observation method and the tethered balloon detection method are two common means. The meteorological tower observation method measures the average temperature profile and average wind speed profile of the vertical structure of the atmosphere by building a high tower on the ground and installing various meteorological instruments on the tower, thereby calculating the height of the atmospheric boundary layer. However, this method has certain limitations, because the cost and technical difficulty of building a higher detection tower are high, resulting in the inability to fully detect the height of the entire atmospheric boundary layer. On the other hand, the tethered balloon detection method tethers the balloon to a certain height and uses the instruments carried by the balloon for detection. Although this method can make up for the shortcomings of the meteorological tower observation method to a certain extent, it also has defects. The tethered balloon detection method cannot perform long-term series observations because the balloon's tethering system may fail during long-term use, and the stability and safety of the balloon are difficult to guarantee. Therefore, it is impossible to accurately determine the boundary layer height throughout the day and 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 laser radar observation data for 24 hours a day, calculating the signal-to-noise ratio of each laser radar observation data, and only retaining radial wind speeds with a signal-to-noise ratio CNR ≥ -22 dB;

[0008] S300: Collect data within every 50 meters in 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;

[0009] S400: determining a second-order partial derivative threshold by a potential temperature profile method of a moored sounding, and determining a daytime boundary layer height according to the second-order partial derivative threshold; determining a nighttime boundary layer height by a maximum value of horizontal wind speed shear in a vertical direction; wherein the nighttime is from 21:30 p.m. to 8 a.m. the next day;

[0010] S500: The daytime boundary layer height and the nighttime boundary layer height are merged 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 a radial wind speed corresponding to the azimuth angle is obtained, it 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 a third azimuth angle, and a fourth radial velocity corresponding to a fourth azimuth angle.

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

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

[0017] Wherein, 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 horizontal wind speed; az i represents 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] Among them, CNR represents signal-to-noise ratio; S represents average signal power; and N represents 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 are 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] Among them, Vri represents the i-th radial wind speed; Vr represents the radial wind speed.

[0033] Further, vertical wind speed data for 30 minutes is collected, and the second-order partial derivative of the 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, by setting appropriate azimuth and elevation angles, the present invention can ensure that the laser radar covers a sufficiently wide area, 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, which 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 throughout the 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 of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0044] Figure 1 A flow chart of a boundary layer height inversion method based on LEOSPHERE100S laser radar provided in an embodiment of the present invention;

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

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

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

[0049] Figure 6A schematic diagram of a comprehensive all-day boundary layer height inversion method based on the LEOSPHERE100S laser radar 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 described herein. On the contrary, these embodiments are provided in order 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, in the absence of conflict, the embodiments of the present invention and the features described 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 combination with the embodiments.

[0051] See also 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, comprising 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 laser radar observation data for 24 hours a day, calculating the signal-to-noise ratio of each laser radar observation data, and only retaining radial wind speeds with a signal-to-noise ratio CNR ≥ -22 dB;

[0054] S300: Collect data within every 50 meters in 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;

[0055] S400: determining a second-order partial derivative threshold by a potential temperature profile method of a moored sounding, and determining a daytime boundary layer height according to the second-order partial derivative threshold; determining a nighttime boundary layer height by a maximum value of horizontal wind speed shear in a vertical direction; wherein the nighttime is from 21:30 p.m. to 8 a.m. the next day;

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

[0057] It can be seen that the DBS mode is an effective data collection 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 collection are crucial to 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 to obtain more comprehensive wind speed information. The screening standard of the signal-to-noise ratio CNR -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 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 the set azimuth and elevation angle, and the radial wind speed corresponding to the azimuth angle is obtained, it includes:

[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 a third azimuth angle, and a fourth radial velocity corresponding to a fourth azimuth angle.

[0062] It can be seen that in DBS mode, the scanning speed of the lidar and the frequency of data collection are crucial to obtaining high-quality radial wind speed data. By setting the appropriate azimuth and elevation angles, it can be ensured that the lidar 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 the set azimuth and elevation angle, and the radial wind speed corresponding to the azimuth angle is obtained, it also includes:

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

[0065] Wherein, 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 horizontal wind speed; az i represents horizontal wind direction.

[0072] It can be seen that the horizontal wind speed and wind direction calculated by the above formula can more accurately describe the actual situation of the wind field. The calculation of the horizontal wind speed takes into account the two components of the radial wind speed, u and v, while the calculation of the horizontal wind direction is based on the ratio of these two components, and the angle of the wind direction is obtained by the inverse tangent function. This processing method not only improves the accuracy of the data, but also provides a solid foundation for the 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] Among them, CNR represents signal-to-noise ratio; S represents average signal power; and N represents average noise power.

[0077] It can be understood that the average signal power is obtained by averaging the signals collected by the lidar, while the average noise power is obtained by averaging the background noise. The calculation formula of the signal-to-noise ratio can reflect the strength of the signal relative to the noise, thus helping us to filter out high-quality data. In practical applications, the threshold of the signal-to-noise ratio is set to -22dB, which means that only when the signal strength is at least 22dB higher than the noise strength, the data will be retained for subsequent analysis.

[0078] Specifically, when only the radial wind speed with a signal-to-noise ratio CNR ≥ -22dB is retained, it also includes:

[0079] According to the Laida criterion, radial wind speeds exceeding the interval (μ-3σ, μ+3σ) within a 4-min period are 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] Among them, 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 the errors caused by outliers, providing a guarantee for the accurate inversion of the 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] Further, vertical wind speed data for 30 minutes is collected, and the second-order partial derivative of the 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 derivative threshold of the vertical wind speed is 0.15.

[0088] It can be understood that the calculation formula of the second-order partial derivative of vertical wind speed can reflect the degree of change of 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 change 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 of wind speed in the vertical direction, which is usually related to turbulent activity in the boundary layer. Therefore, by analyzing the second-order partial derivative of vertical wind speed, it can assist in judging the dynamic characteristics of the boundary layer and provide important reference information for the inversion of the boundary layer height.

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

[0090] Specifically, when determining the nighttime boundary layer height by the maximum horizontal wind speed 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 also Figure 5 As shown, in this embodiment, when the daytime boundary layer height is determined by calculating the second-order partial derivative method of the vertical wind speed, the stable boundary layer at night and early morning often fails, so the maximum value of the horizontal wind speed shear in the vertical direction determines 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 height, 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 change 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 forecasting and the efficiency of environmental monitoring.

[0097] See also 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 adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0099] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to 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 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 generate 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 capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A 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 operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified 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 rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant 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 within the scope of protection of the claims of the present invention.

Claims

1. A boundary layer height inversion method based on LEOSPHERE100S laser radar, 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 laser radar observation data for 24 hours a day, calculate the signal-to-noise ratio of each laser radar observation data, and only retain radial wind speeds with a signal-to-noise ratio CNR ≥ -22dB; Collect data within every 50 meters in 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 moored sounding, and the daytime boundary layer height is determined according to the second-order partial derivative threshold; the nighttime boundary layer height is determined by the maximum value of the horizontal wind speed shear in the vertical direction; wherein the nighttime is from 21:30 pm to 8 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 a laser radar is used to complete a directional scan every 4 seconds according to the set azimuth and elevation angle, and the radial wind speed corresponding to the azimuth angle is obtained, 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 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 a third azimuth angle, and a fourth radial velocity corresponding to a 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 the set azimuth and elevation angle, and the radial wind speed corresponding to the azimuth angle is obtained, it also includes: Calculate the horizontal wind speed and horizontal wind direction according to the radial wind speed; Wherein, the radial wind speed is obtained by the following formula: 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; As mentioned above, the horizontal wind speed and horizontal wind direction are obtained by the following formula: Wherein, Vh represents horizontal wind speed; azi represents 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, including: The signal-to-noise ratio is obtained by the following formula: Among them, CNR represents signal-to-noise ratio; S represents average signal power; and N represents 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 are eliminated for each height, where μ is the mean value and σ = 1.4826MAD; MAD is obtained by the following formula: MAD=median(|Vri-median(Vr)|); Among them, Vri represents the i-th radial wind speed; Vr represents the 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 second-order partial derivative of vertical wind speed for 30 minutes, 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; Where f represents the vertical wind speed variance; w represents the vertical wind speed; and z represents the height.

7. The boundary layer height inversion method based on LEOSPHERE100S laser radar according to claim 1 is characterized in that: The second-order deviator 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 speed 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: 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.

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