Three-dimensional wind field inversion method in thunderstorm cloud strong echo region based on single Doppler weather radar

Abstract

The invention relates to the technical field of three-dimensional wind field inversion, in particular to a three-dimensional wind field inversion method in a thunderstorm cloud strong echo region based on a single Doppler weather radar, which comprises the following steps of: 1, carrying out lattice processing on a radar reflectivity factor to obtain a radar reflectivity factor; the reflectivity factor is converted from a polar coordinate system to a Cartesian rectangular coordinate system through interpolation; 2, performing same-layer continuous moment strong echo graph similarity recognition through an image similarity recognition technology; 3, calculating the horizontal movement speed of the thunderstorm cloud at different heights; and 4, comparing the observation result of the radial speed of the radar with the horizontal movement speed of the thunderstorm, and calculating the rising or sinking airflow speed. According to the method, the grid data of the single Doppler weather radar and the observation data of the radial speed of the radar can be utilized to accurately describe the three-dimensional wind field of the strong echo region in the thunderstorm cloud.

Description

Technical Field

[0001] The invention relates to the technical field of three-dimensional wind field inversion, and in particular to a three-dimensional wind field inversion method in a strong echo area of ​​a thunderstorm cloud based on a single Doppler weather radar. Background Art

[0002] The existing wind field inversion technologies for weather radars include single Doppler radar, dual Doppler radar, and triple Doppler radar algorithms. The single Doppler radar wind field inversion algorithm inverts the radial velocity data at multiple heights and can use some assumptions to infer the wind field. The most commonly used inversion method is to use VAD (Velocity-Azimuth Display) technology, which derives the horizontal wind field by observing the radial velocity changes in different azimuths; the wind field inversion algorithms for single Doppler radars also include VAP and VVP algorithms. The inversion method VAP (Velocity-Azimuth-Plane) technology constructs the wind field by acquiring the radial velocity data of the Doppler radar at different azimuths and different heights; the inversion method VVP (Velocity-Vortex-Plane) technology uses the analysis volume composed of radial, tangential, and vertical directions in three-dimensional space to invert the wind field. Dual Doppler technology can calculate the two components of the horizontal wind field (generally the wind speed in the east-west direction and the north-south direction) by differentially processing the radial velocity measured by two radars. This method can provide a more accurate wind field structure. The triple Doppler radar wind field inversion algorithm can more accurately calculate the three-dimensional wind field (including vertical wind speed) through the radial velocity data obtained by three radars.

[0003] Single Doppler radar, dual Doppler radar and triple Doppler wind field inversion technology are widely used in meteorological monitoring and research, but their inversion effects are affected by the following aspects. Single Doppler radar inversion technology is directly processed under spherical coordinates, relying on the assumption that the wind field is uniform. Although dual Doppler radar improves the accuracy of wind field inversion, it still faces the limitation of radar layout. In order to obtain reasonable wind field information, the relative position of the two radar sites must be appropriate. If the distance between the radars is too far or the direction is not appropriate, the flow field information may be lost or the inversion may be inaccurate. Although triple Doppler radar technology provides more comprehensive three-dimensional wind field information, it is unlikely that three radars can simultaneously conduct complete observations of thunderstorm clouds. The overlapping parts of the scanning areas of the three radars are limited, so it can only be used for scientific research and identification of wind field structures within the local range of thunderstorms.

[0004] For thunderstorm clouds, the wind field may vary greatly. Based on this situation, this technology proposes to grid the radar data in spherical coordinates and place them in Cartesian coordinates to identify the movement of echoes, realize the image recognition of the horizontal velocity of thunderstorm clouds, and then combine the meridional velocity observation to realize the determination of the vertical airflow of radar clouds. In this way, it is more scientific and reasonable to directly combine the movement characteristics of the radar itself and the meridional velocity to invert the three-dimensional wind field structure of the thunderstorm. Summary of the invention

[0005] The present invention provides a three-dimensional wind field inversion method for the strong echo area of ​​thunderstorm cloud based on single Doppler weather radar, which can use the grid data of single Doppler weather radar and the observation data of radar radial velocity to accurately describe the three-dimensional wind field in the strong echo area of ​​thunderstorm cloud.

[0006] According to the present invention, a three-dimensional wind field inversion method in a thunderstorm cloud strong echo area based on a single Doppler weather radar comprises the following steps:

[0007] Step 1: Grid the radar reflectivity factor and transform the reflectivity factor from the polar coordinate system to the Cartesian rectangular coordinate system by interpolation;

[0008] Step 2: Using image similarity recognition technology to perform similarity recognition of strong echo patterns at consecutive moments in the same layer;

[0009] Step 3, calculating the horizontal moving speed of the thunderstorm cloud at different heights;

[0010] Step 4: Compare the radar radial velocity observations with the horizontal speed of the thunderstorm to calculate the rising or sinking air velocity.

[0011] Preferably, in step 2, the image at the first moment T0 and the image at the second moment T1 are compared and identified by similar image recognition technology, specifically including:

[0012] 2.1) Image preprocessing, including denoising and grayscale transformation;

[0013] 2.2) Convert the image into a binary image by thresholding;

[0014] 2.3) Identify the boundaries of image grid points through edge detection;

[0015] 2.4) Detect the grid point positions in the image through template matching or deep learning methods;

[0016] 2.5) Find the coordinates of the grid points through the feature point detection algorithm.

[0017] As a preference, if the strong echo range at the first moment T0 becomes larger or smaller than the strong echo range at the second moment T1, the smaller strong echo area shall prevail; when the strong echo area at the first moment T0 is smaller than the strong echo area at the second moment T1, the strong echo area at the first moment T0 is prevailed for wind field inversion; when the strong echo area at the first moment T0 is larger than the strong echo area at the second moment T1, the strong echo area at the second moment T1 is prevailed for wind field inversion, that is, only the overlapping area of ​​the two is considered; if the strong echo area at the second moment T1 becomes larger, only the area consistent with the smaller strong echo area is considered; at the third moment T2, if the strong echo area becomes smaller, the small strong echo area is mainly used to compare the strong echo areas of the three moments.

[0018] Preferably, in step 3, the horizontal grid points of two similar horizontal reflectivity factor graphs are determined to correspond, and the distance S1 between the two similar points is calculated from the corresponding positions of the two similar points, so that the average speed of translation can be calculated according to the time ΔT required for the radar to complete a volume scanning observation. According to the comparison between T1 and T2, the distance S2 between two similar points and the average speed of translation are obtained. Specifically:

[0019] To determine the speed of the first three consecutive moments, first determine the initial speed V0 at time T0, then calculate the credible speed V1 of the corresponding point according to the kinematic formula, as shown in formulas (1)-(3), where δ is a small positive speed value; after calculating the first V1, assign V1 to V0, and perform the speed determination for the next three consecutive moments. The difference is that V0 needs to be determined before being assigned a value. Then the calculation formulas that follow are (4)-(8). The azimuth angle θ of the horizontal moving speed is calculated by the grid coordinates (X1, Y1) and (X2, Y2) corresponding to two consecutive moments through formula (9). Through the above calculation, the calculation of the horizontal speed at different moments at the same height is realized. By applying this method to the calculation of each height layer, the calculation of the horizontal moving speed at different heights of the entire thunderstorm cloud is completed.

[0020] If a thunderstorm moves at a uniform speed, So,

[0021] Thunderstorms accelerate, if So,

[0022] Thunderstorm deceleration motion, if It can be seen that

[0023] If a thunderstorm moves at a uniform speed, So,

[0024] Thunderstorms accelerate, if So,

[0025] Thunderstorms accelerate, if So,

[0026] Thunderstorm deceleration motion, if It can be seen that

[0027] Thunderstorms accelerate, if So,

[0028] tanθ=(X2-X1) / (Y2-Y1) (9).

[0029] Preferably, in step 4, specifically: by comparing the velocity value of the storage point with the translation velocity of the nearest grid point, the rising or sinking airflow velocity of the grid point can be calculated.

[0030] As a preferred method, when calculating the rising or sinking airflow velocity, the radial storage point velocity V r The corresponding angle and elevation angle are α and β respectively, and the angle between the horizontal velocity direction and the radial velocity of the grid point approaching or overlapping is γ. According to the trigonometric relationship between the two, the radial projection velocity V3 of the horizontal velocity of the grid point is calculated. According to the relationship between the directions and magnitudes of the two, the vertical velocity V of the grid point is determined. t , according to V t Greater than zero means far away from the radar, V t Less than zero indicates proximity to the radar, which can be used to determine whether the vertical airflow characteristics of the grid point are rising or sinking. The specific formulas are shown in (10)-(18):

[0031] γ=α-(π / 2-θ) (10)

[0032] cosγ=V2 / V1 (11)

[0033] cosβ=V2 / V3 (12)

[0034] In the first and fourth quadrants, if |V3|>V r , γ<=π / 2, then V t =(V r -V3) / cos(π / 2-β) (13)

[0035] In the first, fourth quadrant, if |V3| <V r , γ<=π / 2, then V t =(V r-V3) / cos(π / 2-β) (14)

[0036] In the first and fourth quadrants, if |V3|=V r , γ<=π / 2, then V t =(V r -V3) / cos(π / 2-β) (15)

[0037] In the second and third quadrants, if |V3|>V r ,γ>π / 2, then V t =(V r -V3) / cos(π / 2-β) (16)

[0038] In the second, third quadrant, if |V3| <V r ,γ>π / 2, then V t =(V r -V3) / cos(π / 2-β) (17)

[0039] In the second and third quadrants, if |V3|=V r ,γ>π / 2, then V t =(V r -V3) / cos(π / 2-β) (18).

[0040] The beneficial effects of the present invention are as follows:

[0041] 1) Further improve the accuracy of wind field inversion algorithm.

[0042] In the previous wind field inversion algorithm, only the original radar data was processed, and the original radar data was not gridded, so the specific structure of the wind in the cloud could not be known. To address this problem, the present invention designs a wind field inversion algorithm based on radar data gridding. This method can judge the moving speed of the cloud from point to point, which improves people's understanding of the wind field structure in the cloud.

[0043] 2) It can give the horizontal and vertical speeds of clouds at different altitudes.

[0044] By comparing the echo intensity images at each moment, the horizontal movement direction and speed of the cloud can be obtained. By processing multiple heights, the horizontal movement speed at each height can be accurately known. Through the size of the radial velocity and the size of the horizontal movement speed projected onto the radial velocity direction, the vertical structural movement direction of the point can be determined.

[0045] The present invention utilizes the gridded data of single Doppler weather radar and the observation data of radar radial velocity to accurately characterize the three-dimensional wind field in the strong echo area of ​​thunderstorm clouds. In addition to being able to accurately determine the average horizontal moving speed of thunderstorms, the present invention can also calculate the rising or sinking air flow speed in the strong echo area of ​​thunderstorm clouds, which is an important quantitative reference for analyzing and determining the development trend and characteristic evolution of thunderstorm clouds. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a flow chart of a method for inverting a three-dimensional wind field in a strong echo area of ​​a thunderstorm cloud based on a single Doppler weather radar in an embodiment;

[0047] Figure 2 It is a multi-layer height structure diagram at three moments in the embodiment;

[0048] Figure 3 The echo graphs of n layers at three moments in the embodiment;

[0049] Figure 4 Schematic diagram of the corresponding relationship between radar radial velocity observation and gridded translational velocity field in the embodiment;

[0050] Figure 5 Schematic diagram of radial velocity in the embodiment. DETAILED DESCRIPTION

[0051] In order to further understand the content of the present invention, the present invention is described in detail in conjunction with the accompanying drawings and embodiments. It should be understood that the embodiments are only for explaining the present invention and are not intended to limit it.

[0052] Example

[0053] like Figure 1 As shown, this embodiment provides a method for inverting the three-dimensional wind field in the strong echo area of ​​thunderstorm clouds based on a single Doppler weather radar, which includes the following steps:

[0054] Step 1: Grid the radar reflectivity factor and transform the reflectivity factor from the polar coordinate system to the Cartesian rectangular coordinate system through interpolation.

[0055] A scientific and reasonable four-point or eight-point interpolation method is used to transform the reflectivity factor of the Doppler weather radar from polar coordinates to Cartesian coordinates to prepare data for the next step of calculation.

[0056] Step 2: Use image similarity recognition technology to perform similarity recognition of strong echo patterns at consecutive moments in the same layer.

[0057] Assuming that the time required for the radar to complete a volume scan observation is ΔT, since the observation mode of each volume scan is consistent, the time difference between the reflectivity factors at different heights at two consecutive observation times is also ΔT. For operational Doppler weather radars, ΔT is usually not too large, generally a few minutes (the time can be accurate to seconds), so the thunderstorm will not change much, then the distribution characteristics of the reflectivity factor at the same height at two consecutive times have certain similarities, especially the strong echo area with a reflectivity factor greater than 30dBZ, that is, the strong echo area of ​​the thunderstorm will not change much in a short time, and the weak echo area is not suitable for the wind field inversion technology due to its large changes. Figure 2 The radar reflectivity factor images at different heights at three consecutive observation moments of a thunderstorm process are schematically given. The horizontal velocity will be calculated in combination with the gridded reflectivity factors at three consecutive moments.

[0058] Combination Figure 2 , taking the reflectivity factor of the nth layer as an example to illustrate the situation, the image at the first moment T0 and the image at the second moment T1 are compared and identified by similar image recognition technology, specifically including:

[0059] 2.1) Image preprocessing, including denoising and grayscale transformation;

[0060] 2.2) Convert the image into a binary image by thresholding (such as Otsu method, simple threshold method, etc.); for example, select an echo intensity, and set the echo intensity above this to white, and set the echo intensity below this to black;

[0061] 2.3) Identify the boundaries of image grid points through edge detection;

[0062] 2.4) Detect the grid point positions in the image through template matching or deep learning methods;

[0063] 2.5) Find the coordinates of the grid points through the feature point detection algorithm.

[0064] If the strong echo range at the first moment T0 becomes larger or smaller than the strong echo range at the second moment T1, the smaller strong echo area will be taken as the standard; when the strong echo area at the first moment T0 is smaller than the strong echo area at the second moment T1, the strong echo area at the first moment T0 is taken as the standard for wind field inversion; when the strong echo area at the first moment T0 is larger than the strong echo area at the second moment T1, the strong echo area at the second moment T1 is taken as the standard for wind field inversion, that is, only the overlapping area of ​​the two is considered; if the strong echo area at the second moment T1 becomes larger, only the area consistent with the small strong echo area is considered; at the third moment T2, if the strong echo area becomes smaller, the small strong echo area is taken as the main area to compare the strong echo areas at the three moments.

[0065] like Figure 3 As shown, the data are plotted for comparison (such as Figure 2 ), since there are grid points in the radar echo map, the echo map at each moment has corresponding grid points. Therefore, in the specific implementation, the size of the radar image recognition can be adjusted according to the size of the radar echo map. The rule is: the radar echo map with the smallest range in the radar echo map at three moments is used as the range to ensure that the echo map at each moment has the same grid points. According to the image recognition technology, the same grid points are found, and the distance between the grid points can be used to obtain the moving distance at a moment, and then a horizontal moving speed can be obtained.

[0066] Step 3: Calculate the horizontal moving speed of the thunderstorm cloud at different heights.

[0067] In step 3, after completing the similarity recognition of the strong echo patterns at the same layer at consecutive moments, the horizontal grid points of the two similar horizontal reflectivity factor patterns are determined to correspond, and the distance S1 between the two similar points is calculated from the corresponding positions of the two similar points, so that the average speed V1 of the translation can be calculated according to the time ΔT required for the radar to complete a volume scanning observation, and the distance S2 between the two similar points and the average speed of translation can be obtained by comparing the time T1 and T2.

[0068] — Degree V2; specifically:

[0069] To determine the speed of the first three consecutive moments, first determine the initial speed V0 at time T0, then calculate the credible speed V1 of the corresponding point according to the kinematic formula, as shown in formulas (1)-(3), where δ is a small positive speed value; after calculating the first V1, assign V1 to V0, and perform the speed determination for the next three consecutive moments. The difference is that V0 needs to be determined before being assigned a value. Then the calculation formulas that follow are (4)-(8). The azimuth angle θ of the horizontal moving speed is calculated by the grid coordinates (X1, Y1) and (X2, Y2) corresponding to two consecutive moments through formula (9). Through the above calculation, the calculation of the horizontal speed at different moments at the same height is realized. By applying this method to the calculation of each height layer, the calculation of the horizontal moving speed at different heights of the entire thunderstorm cloud is completed.

[0070] If a thunderstorm moves at a uniform speed, So,

[0071] Thunderstorms accelerate, if So,

[0072] Thunderstorm deceleration motion, if It can be seen that

[0073] If a thunderstorm moves at a uniform speed, So,

[0074] Thunderstorms accelerate, if So,

[0075] Thunderstorms accelerate, if So,

[0076] Thunderstorm deceleration motion, if It can be seen that

[0077] Thunderstorms accelerate, if So,

[0078] tanθ=(X2-X1) / (Y2-Y1) (9).

[0079] Step 4: Compare the radar radial velocity observations with the horizontal speed of the thunderstorm to calculate the rising or sinking air velocity.

[0080] Since the velocity values ​​of radial points cannot be interpolated (no actual physical meaning), the velocity value of the point is compared with the translation velocity of the nearest grid point, and the velocity value of the point is compared with the translation velocity of the nearest grid point to calculate the velocity of the rising or sinking airflow at the grid point. In other words, not every grid point can be used to calculate the motion state of the vertical airflow of the thunderstorm cloud. Only those grid points that are close to or coincident with the radar radial velocity points can calculate the velocity of the rising or sinking airflow, such as Figure 4 shown.

[0081] When calculating the velocity of rising or sinking airflow, assume that the radial storage point velocity V r The corresponding angle and elevation angle are α and β respectively, and the angle between the horizontal velocity direction approaching or re-crossing the qualified point and the radial velocity is γ, as shown in Figure 5 As shown; according to the trigonometric relationship between the two, the projection speed V3 of the horizontal speed of the grid point in the radial direction is calculated, and according to the relationship between the directions and magnitudes of the two, the vertical speed V of the grid point is determined. t , according to V t Greater than zero means far away from the radar, V t Less than zero indicates proximity to the radar, which can be used to determine whether the vertical airflow characteristics of the grid point are rising or sinking. The specific formulas are shown in (10)-(18):

[0082] γ=α-(π / 2-θ) (10)

[0083] cosγ=V2 / V1 (11)

[0084] cosβ=V2 / V3 (12)

[0085] In the first and fourth quadrants, if |V3|>V r , γ<=π / 2, then V t =(V r -V3) / cos(π / 2-β) (13)

[0086] In the first, fourth quadrant, if |V3| <V r , γ<=π / 2, then V t =(V r -V3) / cos(π / 2-β) (14)

[0087] In the first and fourth quadrants, if |V3|=V r , γ<=π / 2, then V t =(V r -V3) / cos(π / 2-β) (15)

[0088] In the second and third quadrants, if |V3|>V r ,γ>π / 2, then V t =(V r -V3) / cos(π / 2-β) (16)

[0089] In the second, third quadrant, if |V3| <V r ,γ>π / 2, then V t =(V r -V3) / cos(π / 2-β) (17)

[0090] In the second and third quadrants, if |V3|=V r ,γ>π / 2, then V t =(V r -V3) / cos(π / 2-β) (18).

[0091] The above derivation formula is only the derivation of one case. There are also other directions and size relationships between the two in other cases, and the same can be deduced from this case.

[0092] When using Doppler weather radar data to invert the wind field of a thunderstorm, in addition to judging the speed of the overall horizontal movement of the thunderstorm, more attention is paid to the accurate judgment of the rising or sinking airflow in the thunderstorm cloud. Since the volume scanning observation of the radar is completed under rotating spherical coordinates, that is, when a 360° scan is performed at the same non-zero elevation angle, the observations at different points of the radar reflect the information at different positions and heights of the thunderstorm cloud. Therefore, directly using spherical coordinate data for wind field inversion must inevitably set some idealized assumptions, which makes the wind field inversion results in the thunderstorm cloud differ greatly from the actual ones. In view of this, this embodiment proposes a new thunderstorm three-dimensional wind field inversion method to avoid idealized assumptions about the wind field as much as possible. The core of this technology is to grid the radar reflectivity factor, and transform the reflectivity factor from the polar coordinate system to the Cartesian rectangular coordinate system through scientific interpolation. Through image similarity recognition technology, in order to accurately determine the horizontal moving speed of the strong echo area at two consecutive observation times at a certain height, it is necessary to combine the echo at the third moment to determine the overall movement characteristics of the thunderstorm (uniform speed, acceleration or deceleration), so as to calculate the horizontal moving speed at the second moment. In this way, the calculation of the horizontal moving speed at each height is completed, so as to achieve accurate calculation of the horizontal moving speed of the thunderstorm cloud at different heights from top to bottom. On this basis, combined with the direct observation results of the radial velocity at different radar storage points, by judging the corresponding relationship between the horizontal moving speed and the radial velocity, the scientific calculation of the rising / sinking airflow in the strong echo area of ​​the thunderstorm cloud can be achieved, thereby realizing the inversion of the three-dimensional wind field in the strong echo area of ​​the thunderstorm cloud.

[0093] The present invention and its embodiments are described schematically above, and the description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. Therefore, if a person skilled in the art is inspired by it and designs a structural method and an embodiment similar to the technical solution without creativity without departing from the purpose of the invention, they shall all fall within the protection scope of the present invention.

Claims

1. A three-dimensional wind field inversion method in a thunderstorm cloud strong echo area based on a single Doppler weather radar, characterized in that: The following steps are involved: Step 1: Grid the radar reflectivity factor and transform the reflectivity factor from the polar coordinate system to the Cartesian rectangular coordinate system by interpolation; Step 2: Using image similarity recognition technology to perform similarity recognition of strong echo patterns at consecutive moments in the same layer; Step 3, calculating the horizontal moving speed of the thunderstorm cloud at different heights; Step 4: Compare the radar radial velocity observations with the horizontal speed of the thunderstorm to calculate the rising or sinking air velocity.

2. The three-dimensional wind field inversion method based on single Doppler weather radar in the strong echo area of ​​thunderstorm clouds according to claim 1 is characterized by: In step 2, the image at the first moment T0 and the image at the second moment T1 are compared and identified by similar image recognition technology, specifically including: 2.1) Image preprocessing, including denoising and grayscale transformation; 2.2) Convert the image into a binary image by thresholding; 2.3) Identify the boundaries of image grid points through edge detection; 2.4) Detect the grid point positions in the image through template matching or deep learning methods; 2.5) Find the coordinates of the grid points through the feature point detection algorithm.

3. The three-dimensional wind field inversion method based on single Doppler weather radar in the strong echo area of ​​thunderstorm clouds according to claim 2 is characterized by: If the strong echo range at the first moment T0 becomes larger or smaller than the strong echo range at the second moment T1, the smaller strong echo area will be taken as the standard; when the strong echo area at the first moment T0 is smaller than the strong echo area at the second moment T1, the strong echo area at the first moment T0 is taken as the standard for wind field inversion; when the strong echo area at the first moment T0 is larger than the strong echo area at the second moment T1, the strong echo area at the second moment T1 is taken as the standard for wind field inversion, that is, only the overlapping area of ​​the two is considered; if the strong echo area at the second moment T1 becomes larger, only the area consistent with the small strong echo area is considered; at the third moment T2, if the strong echo area becomes smaller, the small strong echo area is taken as the main area to compare the strong echo areas at the three moments.

4. The three-dimensional wind field inversion method based on single Doppler weather radar in the strong echo area of ​​thunderstorm clouds according to claim 3 is characterized by: In step 3, the horizontal grid points of two similar horizontal reflectivity factor graphs are determined to correspond, and the distance S1 between the two similar points is calculated from the corresponding positions of the two similar points, so that the average speed of translation can be calculated according to the time ΔT required for the radar to complete a volume scanning observation. According to the comparison between T1 and T2, the distance S2 between two similar points and the average speed of translation are obtained. Specifically: To determine the speed of the first three consecutive moments, first determine the initial speed V0 at time T0, then calculate the credible speed V1 of the corresponding point according to the kinematic formula, as shown in formulas (1)-(3), where δ is a small positive speed value; after calculating the first V1, assign V1 to V0, and perform the speed determination for the next three consecutive moments. The difference is that V0 needs to be determined before being assigned a value. Then the calculation formulas that follow are (4)-(8). The azimuth angle θ of the horizontal moving speed is calculated by the grid coordinates (X1, Y1) and (X2, Y2) corresponding to two consecutive moments through formula (9). Through the above calculation, the calculation of the horizontal speed at different moments at the same height is realized. By applying this method to the calculation of each height layer, the calculation of the horizontal moving speed at different heights of the entire thunderstorm cloud is completed. If a thunderstorm moves at a uniform speed, So, Thunderstorms accelerate, if So, Thunderstorm deceleration motion, if It can be seen that If a thunderstorm moves at a uniform speed, So, Thunderstorms accelerate, if Then, V0=V1, Thunderstorms accelerate, if So, Thunderstorm deceleration motion, if It can be seen that V0 = V1, Thunderstorms accelerate, if So, tanθ=(X2-X1) / (Y2-Y1) (9).

5. The three-dimensional wind field inversion method based on single Doppler weather radar in the strong echo area of ​​thunderstorm clouds according to claim 4 is characterized by: In step 4, specifically: by comparing the velocity value of the storage point with the translation velocity of the nearest grid point, the rising or sinking airflow velocity of the grid point can be calculated.

6. The three-dimensional wind field inversion method based on single Doppler weather radar in the strong echo area of ​​thunderstorm clouds according to claim 5 is characterized by: When calculating the velocity of rising or sinking airflow, assume that the radial storage point velocity V r The corresponding angle and elevation angle are α and β respectively, and the angle between the horizontal velocity direction and the radial velocity of the grid point approaching or overlapping is γ. According to the trigonometric relationship between the two, the radial projection velocity V3 of the horizontal velocity of the grid point is calculated. According to the relationship between the directions and magnitudes of the two, the vertical velocity V of the grid point is determined. t , according to V t Greater than zero means far away from the radar, V t Less than zero indicates proximity to the radar, which can be used to determine whether the vertical airflow characteristics of the grid point are rising or sinking. The specific formulas are shown in (10)-(18): γ=α-(π / 2-θ) (10) cosγ=V2 / V1 (11) cosβ=V2 / V3 (12) In the first and fourth quadrants, if |V3|>V r , γ<=π / 2, then V t =(V r -V3) / cos(π / 2-β)(13) In the first, fourth quadrant, if |V3| <V r , γ<=π / 2, then V t =(V r -V3) / cos(π / 2-β)(14) In the first and fourth quadrants, if |V3|=V r , γ<=π / 2, then V t =(V r -V3) / cos(π / 2-β)(15) In the second and third quadrants, if |V3|>V r ,γ>π / 2, then V t =(V r -V3) / cos(π / 2-β)(16) In the second, third quadrant, if |V3| <V r ,γ>π / 2, then V t =(V r -V3) / cos(π / 2-β)(17) In the second and third quadrants, if |V3|=V r ,γ>π / 2, then V t =(V r -V3) / cos(π / 2-β)(18).

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