Cooperative scanning scheduling method based on severe convection moving direction and radar layout

Abstract

The invention relates to a cooperative scanning scheduling method based on a severe convection moving direction and radar layout, and belongs to the field of radar detection, and the method comprises the steps: collecting radar data, forming puzzle data, and obtaining a severe convection center moving direction; the distances between all the schedulable radars and the severe convection target are calculated, the orientations of all the schedulable radars relative to the severe convection target are calculated, and the included angles between all the schedulable radars and the operation orientations of the severe convection target are calculated; selecting the optimal vertical analysis radar, calculating the sending direction of the severe convection target relative to the final vertical analysis radar, scheduling two roundabout scheduling of the radars to execute the vertical analysis task according to all the selected optimal vertical analysis radars if the same radars are selected, otherwise, scheduling the radars to execute the vertical analysis task all the time, and the next radar scheduling period is finished. According to the invention, a plurality of severe convection targets can be observed and tracked continuously in the severe convection weather process, and the internal structure and strength change of the severe convection weather system can be obtained.

Description

Technical Field

[0001] The present invention relates to the field of meteorological detection, and particularly to a collaborative scanning scheduling method based on the moving direction of severe convection and radar layout. Background Art

[0002] In the field of meteorological monitoring and early warning, severe convective weather has always been the focus of meteorologists and meteorological service agencies due to its strong suddenness, wide influence range, and great destructive power. Traditional weather radar systems, such as S-band and C-band radars, although able to detect the existence of severe convective weather to a certain extent, often have observation blind spots in complex terrain or areas with sparse radar networks, restricting the monitoring and early warning capabilities of hazardous weather in the low-altitude area.

[0003] Meteorological radar plays an irreplaceable and important role in severe weather monitoring and early warning, and plays a key role in reducing the loss of personnel and property caused by meteorological disasters. However, at present, the collection of radar echo data related to disastrous weather is mostly based on the observation data of existing operational radars, and the scanning strategy is single; at the same time, weather radar is restricted by factors such as the earth's curvature, electromagnetic wave refraction, terrain, and observation mode, and there are observation blind spots in the observation of near-surface weather processes, restricting the monitoring and early warning capabilities of hazardous weather in the low-altitude area. Especially in complex terrain or areas with sparse radar networks, observation blind spots are more common. Conducting collaborative observations of multiple weather radars, through different scanning strategies, and obtaining high-resolution data on the vertical structure of precipitation systems using a limited-scale observation network is particularly important for analyzing the formation mechanism of disaster-type weather. The main purpose is to identify and track severe convective weather processes that are prone to causing natural disasters, and obtain the high spatio-temporal resolution meteorological structure on the vertical section of severe convective weather, that is, to invert the particle phase state on the vertical section of severe convective weather, so as to better analyze the information of this weather process.

[0004] In recent years, with the accelerated promotion of meteorological modernization construction, due to the single scanning strategy of existing operational radars, X-band radars can be freely controlled for scanning and collaborative control, and the collaborative observation of S-band and C-band radars with X-band weather radars has become an important means. By collaboratively controlling and scheduling the X-band radar for vertical profiling scanning (RHI) to detect the vertical profile of severe convective targets, it is particularly important to obtain high-resolution data on the vertical structure of precipitation systems using a limited-scale observation network for analyzing the formation mechanism of disaster-type weather. However, during the collaborative observation process, because severe convective weather targets move fast and change fast, and it takes a certain amount of time for weather radar to complete the detection of the entire airspace, resulting in a change in the position of the strong center of severe convective weather during the time interval from detection to recognition to decision-making and then to scheduling. How to reasonably schedule the radar for collaborative scanning according to the moving direction of severe convective weather and the radar layout to obtain the high spatio-temporal resolution meteorological structure on the vertical section of severe convective weather has become an urgent problem to be solved. Summary of the Invention

[0005] The object of the present invention is to overcome the shortcomings of the prior art, and provides a collaborative scanning scheduling method based on the moving direction of severe convection and radar layout, which solves the deficiencies existing in the prior art.

[0006] The object of the present invention is achieved by the following technical solutions: A collaborative scanning scheduling method based on the moving direction of severe convection and radar layout, the method comprising:

[0007] S1. After collecting radar data to form mosaic data, determine whether a severe convection target is recognized. If a severe convection target is recognized, obtain the moving direction of the severe convection center;

[0008] S2. Calculate the distances between all schedulable radars and the severe convection target, calculate the azimuths of all schedulable radars relative to the severe convection target, and calculate the angles between the running azimuths of all schedulable radars and the severe convection target;

[0009] S3. Select the optimal vertical profiling radar, and calculate the azimuth of the severe convection target relative to the last vertical profiling radar. According to all the selected optimal vertical profiling radars, if the same radar is selected, schedule the radar to perform the vertical profiling task in two rounds of rotation, otherwise schedule the radar to continuously perform the vertical profiling task until the next radar scheduling cycle.

[0010] The specific content of S1 includes the following:

[0011] Collect data of S-band and X-band networked radars through the central server, check the integrity and format of the data, and then perform data preprocessing;

[0012] Perform coordinate transformation on different radar data, use the nearest neighbor interpolation method for interpolation with inconsistent resolutions, and use the weighting method to fuse the data in the overlapping areas;

[0013] Determine whether a severe convection target is recognized. If a severe convection target is recognized, obtain the background wind field direction at the height corresponding to the wind profiler radar data closest to the severe convection center to represent the movement method of the severe convection center. If no severe convection target is recognized, obtain the data again.

[0014] The calculation of the distances between all schedulable radars and the severe convection target includes the following content:

[0015] Let the longitude and latitude of point A of the radar position be (LonA, LatA), and let the longitude and latitude of point B of the active weather target be (LonB, LatB);

[0016] Taking A as the reference point, according to the formula and Obtain \(E_d\) and \(E_c\) at point A respectively, where \(E_a\) is the equatorial radius, \(E_b\) is the polar radius, \(E_d\) is the radius of the latitude circle at the latitude where point A is located, and \(E_c\) is the radius of the sphere with the continuously changing corrected latitude;

[0017] Obtain the distances in the longitude and latitude directions of point B relative to point A, which are respectively and , and then obtain the distance of point B relative to point A as ;

[0018] Calculate the distances \(D\) between all schedulable radars and severe convective targets respectively i , where \(i = 1\cdots n\), and \(n\) is the total number of schedulable radars.

[0019] The calculation of the azimuth of all schedulable radars relative to the severe convective target includes the following content:

[0020] Let the longitude and latitude of point A, the radar position, be \((LonA, LatA)\), and let the longitude and latitude of point B, the active weather target, be \((LonB, LatB)\);

[0021] Taking A as the reference point, according to the formulas and Obtain \(E_d\) and \(E_c\) at point A respectively, where \(E_a\) is the equatorial radius, \(E_b\) is the polar radius, \(E_d\) is the radius of the latitude circle at the latitude where point A is located, and \(E_c\) is the radius of the sphere with the continuously changing corrected latitude;

[0022] Obtain the distances in the longitude and latitude directions of point B relative to point A, which are respectively and , and then obtain the azimuth of point B relative to point A as ;

[0023] Judge the azimuth of point B relative to point A according to the sign of \(dx\). If \(dx\) is positive, the azimuth of point B relative to point A is \(90^{\circ}\); if \(dx\) is negative, the azimuth of point B relative to point A is \(270^{\circ}\);

[0024] Judge according to the longitude and latitude differences between the two points to obtain the corrected , and finally obtain the azimuth of the severe convective target relative to all schedulable radars , where \(i = 1\cdots n\), and \(n\) is the total number of schedulable radars. Among them, represents the longitude difference between point B and point A, represents the latitude difference between point B and point A.

[0025] The calculation of the included angle between the running azimuths of all schedulable radars and the severe convective target includes the following content:

[0026] According to the target running azimuth \(mAz\) and the azimuths of all schedulable radars relative to the severe convective target , obtain the included angle between the running azimuths of all schedulable radars and severe convective targets 。

[0027] The said selection of the optimal vertical profiling radar includes the following:

[0028] Select the radars within the effective observation distance of the target according to the effective observation distance of the X-band;

[0029] According to the included angle between the radar within the effective observation distance and the running direction of the target , i = 1…n, where n is the total number of schedulable radars, calculate the absolute value of the included angle between the radar within the effective observation distance and the running direction of the target ;

[0030] Arrange the absolute values of the included angles between the radars within the effective observation distance and the running direction of the target in ascending order, and take the radar with the minimum angle as the optimal observation radar.

[0031] The said calculation of the azimuth of the severe convective target relative to the last vertical profiling radar includes the following:

[0032] Let the longitude and latitude of point A where the radar is located be (LonA, LatA), and let the longitude and latitude of point B of the active weather target be (LonB, LatB);

[0033] Taking A as the reference point, according to the formulas and respectively obtain Ed and Ec at point A, where Ea is the equatorial radius, Eb is the polar radius, Ed is the radius of the latitude circle at the latitude where point A is located, and Ec is the radius of the sphere with the corrected latitude changing;

[0034] Obtain the distances in the longitude and latitude directions of point B relative to point A as and , and then obtain the azimuth of point B relative to point A as ;

[0035] Judge the azimuth of point B relative to point A according to the positive or negative of dx. If dx is positive, the azimuth of point B relative to point A is 90°, and if dx is negative, the azimuth of point B relative to point A is 270°;

[0036] Judge according to the longitude and latitude differences between the two points to obtain the corrected , which is the azimuth of the severe convective target relative to the optimal vertical profiling radar 。

[0037] The said method also includes:

[0038] When performing the vertical profiling task, set the start elevation angle of the vertical profiling scan mode to 0.5°, the end elevation angle to 70°, and the azimuth to the azimuth az of the target relative to the optimal vertical profiling radar. Send a scan command to the executing radar until the optimal radar is reselected in the next cycle.

[0039] The present invention has the following advantages: A cooperative scanning scheduling method based on the moving direction of severe convection and radar layout. By the moving direction of the precipitation system and the radar layout, vertical profiling scans (RHI) are performed by selecting radars along the moving direction of the weather system, which can better enable the internal structure of the weather system obtained by the vertical profiling scans (RHI). It can continuously track multiple severe convection targets during the observation of severe convection weather processes and obtain the internal structure and intensity changes of the severe convection weather system. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is a schematic diagram of the effect;

[0041] Figure 2 is a schematic flow diagram of the present invention;

[0042] Figure 3 is a schematic diagram of the interpolation method;

[0043] Figure 4 is a schematic diagram of the effect of clustering severe convection echo points. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and illustrated herein can be arranged and designed in various different configurations. Therefore, the detailed description of the embodiments of the present application provided below with reference to the accompanying drawings is not intended to limit the protection scope of the claimed present application, but only represents the selected embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative efforts belong to the protection scope of the present application. The present invention will be further described below with reference to the accompanying drawings.

[0045] The present invention specifically relates to a cooperative scanning scheduling method based on the moving direction of severe convection and radar layout. By the moving direction of the precipitation system and the radar layout, vertical profiling scans (RHI) are performed by selecting radars along the moving direction of the weather system, which can better enable the internal structure of the weather system obtained by the vertical profiling scans (RHI). During the observation of severe convection weather processes, multiple severe convection targets are continuously tracked to obtain the internal structure and intensity changes of the severe convection weather system.

[0046] Such asFigure 1 As shown, through the moving direction of the precipitation system and the radar layout, a vertical profiling scan (RHI) of the radar selected along the moving direction of the weather system can better obtain the internal structure of the weather system by the vertical profiling scan (RHI).

[0047] Such as Figure 2 shown, it specifically includes the following contents:

[0048] 1. Collect radar data to form mosaic data:

[0049] (1) Collect data of S-band and X-band networked radars through the central server;

[0050] (2) Check the integrity and data format of weather radar data;

[0051] (3) Preprocess and quality control the data, including removing noise and interference, etc., to ensure the accuracy and reliability of the data;

[0052] (4) Perform coordinate transformation on different radar data, interpolate the inconsistent resolutions using the nearest neighbor interpolation method, and fuse the data in the overlapping area using the weighting method.

[0053] Furthermore, the S-band and X-band radar network mosaic data fusion technology includes two steps: coordinate transformation and difference processing.

[0054] A1. Inverse calculate the spherical coordinates (radar polar coordinates) from the Cartesian coordinates (three-dimensional grid);

[0055] According to the mosaic grid point size (algorithm input parameter) and the mosaic range, a three-dimensional grid coordinate system can be constructed. Each grid point is described by longitude, latitude, and altitude. Let the coordinates of any grid cell in the three-dimensional grid be ( , , ), where is the latitude, is the longitude, is the altitude. The coordinates of the point where the radar antenna is located are ( , , ), where is the latitude, is the longitude, is the altitude. Using the radar beam propagation and great circle geometry theory, the polar coordinate position (r, a, e) of the grid cell relative to the radar point can be determined, where r is the slant range, a is the azimuth angle, and e is the elevation angle. It can be obtained from the spherical triangle formula:

[0056] ,

[0057] Among them, where R is the radius of the earth and s is the great circle distance, and its expression is:

[0058] ,

[0059] Let C = sin a, then there is:

[0060] ,

[0061] Among them, the expression of the elevation angle e is:

[0062] ,

[0063] Among them, R m = 4 / 3R is the equivalent earth radius, and R is the radius of the earth.

[0064] The expression of the slant range r is:

[0065] .

[0066] A2. 8-point interpolation method;

[0067] As Figure 3 shown, the value of the current radar falling on the 3D grid point is obtained by using the 8-point interpolation method.

[0068] The polar coordinate position (r, a, e) of a certain grid point relative to the radar point falls within , , , , , , , the cone enclosed, then the analysis value of this grid point can be obtained by bilinear interpolation of the observed values of these 8 points.

[0069] ,

[0070] Among them, w a1 and w a2 are the azimuth interpolation weights:

[0071] ,

[0072] w r1 and w r2 are the slant range interpolation weights:

[0073] ,

[0074] ,

[0075] we1 、w e2 is the elevation interpolation weight:

[0076] ,

[0077] A3. Puzzle method;

[0078] In the puzzle area, when a three-dimensional grid cell has multiple radar data, the exponential weight function method is used to obtain the reflectivity value of the current cell.

[0079] ,

[0080] where f is the composite reflectivity value of the three-dimensional cell, f j is the analysis value of the j-th radar falling in the current cell, w j is the weight of the analysis value f j , and N rad is the total number of radars with analysis values at the current grid cell.

[0081] The exponential weight function is:

[0082] ,

[0083] where R1 is an appropriate length ratio and r1 is the distance from the grid point to the radar center. Through historical experience accumulation and comparative analysis of the puzzle effect, for S-band radar, R = 100 km, and for X-band radar, R = 50 km, which can effectively improve the structural discontinuity caused by differences in radar observation time and sampling volume, and ensure the integrity and smoothness of the echo structure in the stratiform cloud area.

[0084] 2. Severe convective target recognition:

[0085] Severe convective weather has characteristics such as small spatio-temporal scale, rapid development, intense intensity, large destructiveness, and easy disaster-causing. Identifying severe convective targets through puzzle data includes information such as boundaries, centers, and areas.

[0086] (1) Arbitrarily select a strong center point as the starting point. If this point meets the following principles:

[0087] ,

[0088] where Z represents the composite reflectivity, represents the coordinate point corresponding composite reflectivity, max(.) is the maximum operation, represents the Euclidean distance between two points, The threshold represents the radius searched near the strong center point, which is set to 6 in the present invention.

[0089] (2) Generate a set that contains only the starting points .

[0090] Traverse the remaining severe convective echo points. If a certain point meets the following conditions, it will be classified into until no point meets the conditions.

[0091] ,

[0092] where dist(.) represents calculating the minimum Euclidean distance between point p and all points in the set in.

[0093] (3) Remove the points that have been classified into the set from the total samples.

[0094] (4) Select a new severe center starting point again and repeat steps (1)-(4) until all severe center points are processed.

[0095] (5) If the total number of points in a certain set is less than 40, then consider this set as noise points and remove it.

[0096] From the above steps, it can be seen that this clustering algorithm mainly takes the spatial distance as the core observation point and clusters according to the spatial density distribution characteristics of the convective points. The effect of clustering the severe convective echo points is as follows Figure 4 shown. It can be seen that whether it is a convective cell ( Figure 4 the two cases on the upper side), or a more complex multi-cell structure ( Figure 4 the two cases on the lower side), the clustering algorithm can accurately locate the severe convective echo area.

[0097] After the clustering algorithm, the possible severe convective areas in the radar echo have been identified. After further extracting parameters such as the area, maximum reflectivity, average reflectivity, vertically integrated liquid water content, and echo top height of each area.

[0098] 3. Obtain the moving direction of the severe convective center: According to the severe convective center information, find the corresponding nearest wind profiler radar data, obtain the background wind field direction at the corresponding height, and use it to represent the moving direction of the severe convective center, which can better reflect the change of the severe convective center position.

[0099] 4. Calculate the distances between all schedulable radars and the severe convective targets:

[0100] Let the longitude and latitude of point A of the radar position be (LonA, LatA), and let the longitude and latitude of point B of the active weather target be (LonB, LatB);

[0101] Taking point A as the reference point, according to the formula and the latitude circle radius Ed and the spherical radius Ec at point A are obtained respectively, where Ea is the equatorial radius, Eb is the polar radius, Ed is the latitude circle radius of the latitude where point A is located, and Ec is the spherical radius with the continuously changing corrected latitude;

[0102] The distances in the longitude and latitude directions of point B relative to point A are obtained as and respectively, and then the distance of point B relative to point A is .

[0103] Calculate the distances D between all schedulable radars and the target i (i = 1…n), where n is the total number of schedulable radars.

[0104] 5. Calculate the azimuths of all schedulable radars relative to the target:

[0105] Let the longitude and latitude of radar position point A be (LonA, LatA), and the longitude and latitude of the active weather target point B be (LonB, LatB);

[0106] Taking point A as the reference point, according to the formula and the latitude circle radius Ed and the spherical radius Ec at point A are obtained respectively, where Ea is the equatorial radius, Eb is the polar radius, Ed is the latitude circle radius of the latitude where point A is located, and Ec is the spherical radius with the continuously changing corrected latitude;

[0107] The distances in the longitude and latitude directions of point B relative to point A are obtained as and respectively, and then the azimuth of point B relative to point A is ;

[0108] Since the azimuth output here needs to be the azimuth angle relative to the due north, the az output by the formula needs to be judged and converted. First, if dy is 0, it means that the two points are on the same latitude circle, and the calculation of will not be performed. According to the positive or negative of dx, judge the azimuth of point B relative to point A. If dx is positive, the azimuth of point B relative to point A is 90°, and if dx is negative, the azimuth of point B relative to point A is 270°;

[0109] Judge according to the longitude and latitude differences between the two points to obtain the corrected , and finally obtain the azimuths of the target relative to all schedulable radars , i = 1…n, where n is the total number of schedulable radars. Among them, represents the longitude difference between point B and point A, represents the latitude difference between point B and point A.

[0110] 6. Calculate the included angles between all schedulable radars and the running azimuth of severe convective targets:

[0111] Based on the target running azimuth mAz and the azimuths of all schedulable radars relative to the target (i = 1…n), where n is the total number of schedulable radars. Calculate the included angles between all schedulable radars and the target running azimuth .

[0112] 7. Select the optimal vertical profiling radar:

[0113] The effective observation distance of the X - band radar for collaborative vertical profiling of targets is 10 km - 60 km. Filter out the radars within the effective observation distance of the target according to the effective observation distance, that is, Distance > 10 and Distance < 60, where Distance is the effective observation distance.

[0114] Then, according to the included angles (i = 1…n) between the radars within the effective observation distance and the target running direction, calculate the absolute values of the included angles between the radars within the effective observation distance and the target running direction .

[0115] Arrange the absolute values of the included angles between the radars within the effective observation distance and the target running direction in ascending order, and take the radar with the minimum angle as the optimal observation radar.

[0116] 8. Calculate the azimuth of the severe convective target relative to the optimal vertical profiling radar:

[0117] Let the longitude and latitude of point A (the radar position) be (LonA, LatA), and the longitude and latitude of point B (the active weather target) be (LonB, LatB);

[0118] Taking A as the reference point, according to the formulas and respectively obtain Ed and Ec at point A, where Ea is the equatorial radius, Eb is the polar radius, Ed is the radius of the latitude circle at the latitude of point A, and Ec is the radius of the sphere with the continuously changing corrected latitude;

[0119] The distances in the longitude and latitude directions of point B relative to point A are obtained as and respectively, and then the azimuth of point B relative to point A is ;

[0120] Judge the azimuth of point B relative to point A according to the sign of dx. If dx is positive, the azimuth of point B relative to point A is 90°, and if dx is negative, the azimuth of point B relative to point A is 270°;

[0121] Judgment is made based on the difference in longitude and latitude between two points to obtain the corrected , which is the azimuth of the target relative to the optimal vertical profiling radar .

[0122] 9. Radar scheduling scan strategy:

[0123] According to all the selected optimal vertical profiling radars, if the same radar is selected, the radar is scheduled to perform the vertical profiling task in two round-robin schedules, otherwise the radar keeps performing the vertical profiling task until the next radar scheduling cycle.

[0124] 10. Scheduling the radar to execute tasks:

[0125] When performing the vertical profiling task, set the start elevation angle of the RHI scan mode to 0.5°, the end elevation angle to 70°, and the azimuth to the azimuth az of the target relative to the optimal vertical profiling radar, which can better observe the vertical structure of weather targets. Send the scan command to the executing radar until the optimal radar is reselected in the next cycle.

[0126] The above are only the preferred embodiments of the present invention. It should be understood that the present invention is not limited to the form disclosed herein, should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications and improvements, and can be changed within the scope of the concept described herein through the above teachings or the technology or knowledge in related fields. And any changes and variations made by those skilled in the art without departing from the spirit and scope of the present invention shall fall within the protection scope of the appended claims of the present invention.

Claims

1. A collaborative scanning scheduling method based on strong convection moving direction and radar layout, characterized by: The method comprises: S1. After collecting radar data to form jigsaw data, determine whether a strong convective target is identified. If a strong convective target is identified, obtain the movement direction of the strong convective center; S2. Calculate the distances between all scalable radars and the strong convective target, calculate the azimuths of all scalable radars relative to the strong convective target, and calculate the angles between all scalable radars and the operating azimuths of the strong convective target; S3. Select the optimal vertical profiling radar and calculate the azimuth of the strong convective target relative to the last vertical profiling radar. According to all the selected optimal vertical profiling radars, if the same radar is selected, two radars are scheduled to perform the vertical profiling task in rotation. Otherwise, the radar is scheduled to perform the vertical profiling task until the next radar scheduling cycle.

2. The method for collaborative scanning scheduling based on strong convection moving direction and radar layout according to claim 1 is characterized in that: The S1 specifically includes the following contents: Collect data from S-band and X-band networked radars through the central server, and perform data preprocessing after checking the integrity and format of the data; The coordinates of different radar data are transformed, the nearest neighbor interpolation method is used to interpolate the inconsistent resolutions, and the weight method is used to fuse the overlapping area data; Determine whether a strong convective target is identified. If a strong convective target is identified, obtain the wind profile radar data closest to the strong convective center and the background wind field direction at the corresponding height to represent the movement method of the strong convective center. If no strong convective target is identified, re-acquire the data.

3. The method for collaborative scanning scheduling based on strong convection moving direction and radar layout according to claim 1 is characterized in that: The calculation of the distances between all dispatchable radars and severe convective targets includes the following: Assume the longitude and latitude of radar location point A is (LonA, LatA), and the longitude and latitude of active weather target point B is (LonB, LatB); Take A as the reference point and follow the formula and We obtain point A’s Ed and Ec respectively, where Ea is the equatorial radius, Eb is the polar radius, Ed is the radius of the latitude circle at the latitude of point A, and Ec is the radius of the sphere that corrects the changing latitude; The distances of point B relative to point A in longitude and latitude are and , and then the distance between point B and point A is ; Calculate the distance D between all dispatchable radars and severe convection targets respectively i , i=1…n, n is the total number of dispatchable radars.

4. The method for collaborative scanning scheduling based on strong convection moving direction and radar layout according to claim 1 is characterized in that: The calculation of the relative positions of all schedulable radars to the severe convective target includes the following contents: Assume the longitude and latitude of radar location point A is (LonA, LatA), and the longitude and latitude of active weather target point B is (LonB, LatB); Take A as the reference point and follow the formula and We obtain point A’s Ed and Ec respectively, where Ea is the equatorial radius, Eb is the polar radius, Ed is the radius of the latitude circle at the latitude of point A, and Ec is the radius of the sphere that corrects the changing latitude; The distances of point B relative to point A in longitude and latitude are and , and then the position of point B relative to point A is ; Determine the direction of point B relative to point A based on the sign of dx. If dx is positive, the direction of point B relative to point A is 90°. If dx is negative, the direction of point B relative to point A is 270°. According to the difference between the longitude and latitude of the two points, the corrected Finally, the position of the severe convective target relative to all schedulable radars is obtained. , i=1…n, n is the total number of schedulable radars, where, It represents the longitude difference between point B and point A. Indicates the latitude difference between point B and point A.

5. The method for collaborative scanning scheduling based on strong convection moving direction and radar layout according to claim 4 is characterized in that: The calculation of the angles between all schedulable radars and the operating azimuths of the severe convective target includes the following contents: According to the operating position mAz of the severe convective target and the position of all dispatchable radars relative to the severe convective target , get the angle between all the adjustable radars and the operating direction of the severe convective target .

6. The method for collaborative scanning scheduling based on strong convection moving direction and radar layout according to claim 1, characterized in that: The selection of the optimal vertical profile radar includes the following contents: According to the X-band effective observation range, select the radar whose target is within the effective observation range; According to the angle between the radar and the target's running direction within the effective observation range radar , i=1…n, n is the total number of dispatchable radars, calculate the absolute value of the angle between the radar within the effective observation range and the target running direction ; The absolute value of the angle between the radar and the target's running direction within the effective observation range Arrange them in ascending order and take the radar with the minimum angle as the optimal observation radar.

7. The method for collaborative scanning scheduling based on strong convection moving direction and radar layout according to claim 1 is characterized in that: The calculation of the azimuth of the severe convective target relative to the last vertical analysis radar includes the following contents: Assume the longitude and latitude of radar location point A is (LonA, LatA), and the longitude and latitude of active weather target point B is (LonB, LatB); Take A as the reference point and follow the formula and We obtain point A’s Ed and Ec respectively, where Ea is the equatorial radius, Eb is the polar radius, Ed is the radius of the latitude circle at the latitude of point A, and Ec is the radius of the sphere that corrects the changing latitude; The distances of point B relative to point A in longitude and latitude are and , and then the position of point B relative to point A is ; Determine the direction of point B relative to point A based on the sign of dx. If dx is positive, the direction of point B relative to point A is 90°. If dx is negative, the direction of point B relative to point A is 270°. According to the difference between the longitude and latitude of the two points, the corrected , which is the target's position relative to the optimal vertical profiling radar .

8. A collaborative scanning scheduling method based on strong convection moving direction and radar layout according to any one of claims 1 to 7, characterized in that: The method further comprises: When executing the vertical profiling task, set the vertical profiling scanning mode start elevation angle to 0.5°, end elevation angle to 70°, and azimuth to the target relative to the optimal vertical profiling radar azimuth az, and send a scanning command to the executing radar until the optimal radar is reselected in the next cycle.

Images