A thunderstorm identification method based on dual-polarization radar

Abstract

The application discloses a thunderstorm identification method based on dual-polarization radar, and relates to the technical field of thunderstorm identification.The method comprises the following steps: obtaining a thunderstorm reflection threshold based on the reflectivity of a first number of thunderstorms; obtaining a thunderstorm coordinate point based on the thunderstorm reflection threshold, real-time coordinates and real-time reflectivity; obtaining a single thunderstorm point based on the thunderstorm coordinate point; constructing real-time thunderstorm parameters and a fitting midpoint based on the single thunderstorm point; obtaining a pre-warning thunderstorm threshold based on a second number of thunderstorms that need to be pre-warned; judging whether the thunderstorm is a thunderstorm that needs to be pre-warned based on the pre-warning thunderstorm threshold and real-time thunderstorm parameters; and obtaining a thunderstorm horizontal moving direction based on the fitting midpoint.The application is used to solve the problem that the existing thunderstorm identification technology cannot set a suitable reflectivity threshold, simple pre-warning judgment and simple thunderstorm moving direction acquisition, resulting in that the thunderstorm identification result is not fast and accurate enough.

Description

Technical Field

[0001] This invention relates to the field of thunderstorm identification technology, specifically a thunderstorm identification method based on dual-polarization radar. Background Technology

[0002] Thunderstorms are a typical example of severe convective weather, often accompanied by short-duration heavy rainfall, hail, thunderstorm winds, and even tornadoes, posing a serious threat to people's lives and property, aviation safety, agricultural production, and socio-economic activities; therefore, accurate and timely monitoring and early warning of thunderstorms are necessary.

[0003] Existing thunderstorm identification technologies based on dual-polarization radar rely on the acquired reflectivity factor and a fixed reflectivity factor threshold to determine whether a thunderstorm is occurring. However, setting a fixed reflectivity factor threshold fails to provide a more accurate threshold by incorporating historical thunderstorm data. For example, patent application CN110346800A discloses a thunderstorm identification method based on dual-polarization weather radar volume scan data, which sets a reflectivity factor threshold of 40 dBZ. This method also fails to obtain a more accurate reflectivity factor threshold by incorporating historical thunderstorm data. Furthermore, it does not acquire information on the thunderstorm's hazards and direction of movement, resulting in insufficient precision in the identification results. Due to the variability and irregularity of thunderstorms, determining their hazards and direction of movement is difficult, thus requiring a simpler method. Existing thunderstorm identification technologies lack suitable reflectivity thresholds, simple early warning judgments, and simple information on thunderstorm movement direction acquisition, leading to problems with both speed and accuracy in thunderstorm identification. Summary of the Invention

[0004] This invention aims to at least partially solve one of the technical problems in the prior art. It obtains a thunderstorm reflection threshold based on the reflectivity of a first number of thunderstorms; obtains thunderstorm coordinate points based on the thunderstorm reflection threshold, real-time coordinates, and real-time reflectivity; obtains individual thunderstorm points based on the thunderstorm coordinate points; constructs real-time thunderstorm parameters and a fitted midpoint based on the individual thunderstorm points; obtains a warning thunderstorm threshold based on a second number of thunderstorms requiring warning; determines whether a thunderstorm requires warning based on the warning thunderstorm threshold and real-time thunderstorm parameters; and obtains the horizontal movement direction of the thunderstorm based on the fitted midpoint. This addresses the problem that existing thunderstorm identification technologies fail to set appropriate reflectivity thresholds, provide simple warning judgments, and obtain simple thunderstorm movement directions, resulting in slow and inaccurate thunderstorm identification results.

[0005] To achieve the above objectives, this application provides a thunderstorm identification method based on dual-polarization radar, comprising the following steps:

[0006] The reflectivity and corresponding coordinates of the target area are obtained based on the dual-polarization radar and are marked as real-time reflectivity and real-time coordinates, respectively.

[0007] The thunderstorm reflection threshold is obtained based on the reflectivity of a first number of thunderstorms;

[0008] Thunderstorm coordinates are obtained based on thunderstorm reflection threshold, real-time coordinates, and real-time reflectivity.

[0009] Obtain individual thunderstorm points based on thunderstorm coordinates;

[0010] Constructing real-time thunderstorm parameters and fitting midpoints based on individual thunderstorm points;

[0011] The threshold for warning thunderstorms is obtained based on the second number of thunderstorms that require warning;

[0012] Whether a thunderstorm requires warning is determined based on the early warning thunderstorm threshold and real-time thunderstorm parameters, and the horizontal movement direction of the thunderstorm is obtained based on the fitted midpoint.

[0013] Furthermore, obtaining the thunderstorm reflection threshold based on the reflectivity of a first number of thunderstorms includes the following sub-steps:

[0014] The reflectivity of the first number of thunderstorms is marked as the historical thunderstorm reflectivity;

[0015] Obtain the range of historical thunderstorm reflectivity; divide the range of historical thunderstorm reflectivity into a third number of equally spaced intervals, and mark them as reflectivity segmentation intervals;

[0016] Obtain the frequency of historical thunderstorm reflectance within each reflectance segmentation interval and mark it as the reflectance segmentation frequency;

[0017] The reflectance frequency threshold is calculated as follows: A1 = b1 × (C1 ÷ D1); where A1 is the reflectance frequency threshold, b1 is the reflectance frequency ratio, C1 is the sum of all reflectance segment frequencies, and D1 is the third quantity.

[0018] Reflectance segmentation frequencies that are less than the reflectance frequency threshold are marked as reflectance anomaly frequencies.

[0019] Furthermore, obtaining the thunderstorm reflection threshold based on the reflectivity of a first number of thunderstorms also includes the following sub-steps:

[0020] Obtain the minimum value of each reflectance segmentation interval and mark it as the first reflectance value;

[0021] Sort the reflectivity segmentation frequencies from left to right according to the corresponding first reflectivity value, from smallest to largest.

[0022] If the leftmost reflectance division frequency is an abnormal reflectance frequency, then delete this abnormal reflectance frequency until the leftmost reflectance division frequency is no longer an abnormal reflectance frequency; then obtain the first reflectance value corresponding to the leftmost reflectance division frequency and mark it as the thunderstorm reflection threshold.

[0023] Furthermore, obtaining the thunderstorm coordinates based on the thunderstorm reflection threshold, real-time coordinates, and real-time reflectivity includes the following sub-steps:

[0024] The real-time reflectivity that is greater than or equal to the thunderstorm reflectivity threshold is marked as the real-time thunderstorm reflectivity; the real-time coordinates corresponding to the real-time thunderstorm reflectivity are obtained and marked as thunderstorm coordinate points.

[0025] Furthermore, obtaining individual thunderstorm points based on thunderstorm coordinates includes the following sub-steps:

[0026] Establish a three-dimensional coordinate system, labeled as the thunderstorm location coordinate system; ensure that all thunderstorm coordinate points are within the thunderstorm location coordinate system.

[0027] Obtain any thunderstorm coordinates and mark it as the starting thunderstorm point; mark a sphere with a diameter of the first length as the reference sphere; establish a reference sphere centered on the starting thunderstorm point and mark it as the starting sphere;

[0028] Determine if the starting sphere contains newly appeared thunderstorm coordinates. If not, obtain a new thunderstorm coordinate as the starting thunderstorm point. If it does contain thunderstorm coordinates, mark the newly appeared thunderstorm coordinates within the starting sphere as the search thunderstorm point.

[0029] Establish a reference sphere centered on the searched thunderstorm point and mark it as the search sphere; establish a new reference sphere with the new thunderstorm coordinates within the search sphere, and repeat the process of establishing a new reference sphere with the new thunderstorm coordinates within the new reference sphere until the new reference sphere does not contain any new thunderstorm coordinates; obtain the thunderstorm coordinates within all the established reference spheres and mark them as individual thunderstorm points.

[0030] Furthermore, constructing real-time thunderstorm parameters and fitting midpoints based on individual thunderstorm points includes the following sub-steps:

[0031] The plane formed by the X-axis and Y-axis in the thunderstorm location coordinate system is marked as the projection plane. All individual thunderstorm points are projected onto the projection plane to obtain thunderstorm projection points.

[0032] Mark the line parallel to the X-axis as the first parallel line; draw a fourth number of first parallel lines with an interval of the second distance to divide the thunderstorm location coordinate system into multiple regions, and mark them as the divided regions;

[0033] Obtain the minimum and maximum x-coordinates of the thunderstorm projection points within each divided region, and mark them as projection boundary points.

[0034] Furthermore, constructing real-time thunderstorm parameters and fitting midpoints based on individual thunderstorm points also includes the following sub-steps:

[0035] The contour fitting equation is set as: (F1-e1) 2 ÷e2+(F2-e3) 2÷e4=1; where F1 and F2 are the x-coordinate and y-coordinate values, respectively, and e1, e2, e3, and e4 are the parameters of the contour fitting equation;

[0036] The graphic obtained by fitting all the projected boundary points with the contour fitting equation is marked as the projected contour.

[0037] Obtain the area of ​​the projected contour and mark it as the real-time thunderstorm parameter; obtain the center of the projected contour and mark it as the fitting midpoint.

[0038] Furthermore, obtaining the warning thunderstorm threshold based on the second number of thunderstorms requiring warning includes the following sub-steps:

[0039] Get real-time thunderstorm parameters by taking any coordinate point in a thunderstorm that requires warning as the thunderstorm coordinate point and marking it as historical thunderstorm parameters; get historical thunderstorm parameters for all thunderstorms that require warning.

[0040] Obtain the range of historical thunderstorm parameters; divide the range of historical thunderstorm parameters into five equal intervals, and mark them as parameter segmentation intervals;

[0041] Obtain the frequency of historical thunderstorm parameters within each parameter segmentation interval and mark it as the parameter segmentation frequency;

[0042] The parameter frequency threshold is calculated as: A2 = b2 × (C2 ÷ D2); where A2 is the parameter frequency threshold, b2 is the parameter frequency ratio, C2 is the sum of the frequencies of all parameter segments, and D2 is the fifth quantity.

[0043] Parameter segmentation frequencies that are less than the parameter frequency threshold are marked as parameter abnormal frequencies.

[0044] Furthermore, obtaining the warning thunderstorm threshold based on the second number of thunderstorms requiring warning also includes the following sub-steps:

[0045] Get the minimum value of each parameter's segmentation interval and mark it as the first parameter value;

[0046] Sort the parameter segmentation frequencies from left to right according to the corresponding first parameter value, from smallest to largest.

[0047] If the leftmost parameter segmentation frequency is a parameter abnormality frequency, then delete this parameter abnormality frequency until the leftmost parameter segmentation frequency is no longer a parameter abnormality frequency; then obtain the first parameter value corresponding to the leftmost parameter segmentation frequency and mark it as the warning thunderstorm threshold.

[0048] Furthermore, determining whether a thunderstorm requires warning based on the early warning threshold and real-time thunderstorm parameters, and obtaining the horizontal movement direction of the thunderstorm based on the fitted midpoint, includes the following sub-steps:

[0049] If the real-time thunderstorm parameters are greater than the warning thunderstorm threshold, the thunderstorm area is identified as a thunderstorm requiring warning; the fitted midpoint obtained before the first time is obtained and marked as the midpoint of the previous time; the direction from the midpoint of the previous time to the fitted midpoint is regarded as the horizontal movement direction of the thunderstorm.

[0050] The beneficial effects of this invention are as follows: This invention obtains a thunderstorm reflection threshold based on the reflectivity of a first number of thunderstorms; obtains thunderstorm coordinate points based on the thunderstorm reflection threshold, real-time coordinates, and real-time reflectivity; obtains individual thunderstorm points based on the thunderstorm coordinate points; constructs real-time thunderstorm parameters and a fitted midpoint based on the individual thunderstorm points; obtains a warning thunderstorm threshold based on a second number of thunderstorms requiring warning; determines whether a thunderstorm requires warning based on the warning thunderstorm threshold and real-time thunderstorm parameters; and obtains the horizontal movement direction of the thunderstorm based on the fitted midpoint. The advantage lies in the fact that setting an appropriate reflectivity threshold, simple warning judgment, and simple acquisition of the thunderstorm movement direction enable rapid and accurate thunderstorm identification results.

[0051] This invention constructs real-time thunderstorm parameters and fitted midpoints based on individual thunderstorm points. Its advantage lies in the fact that simple thunderstorm early warning judgments and simple thunderstorm movement direction acquisition can be performed based on real-time thunderstorm parameters and fitted midpoints, making thunderstorm identification results fast and accurate. Attached Figure Description

[0052] Figure 1 This is a flowchart illustrating the steps of the method of the present invention;

[0053] Figure 2 This is a schematic diagram of the thunderstorm projection point according to the present invention;

[0054] Figure 3 This is a schematic diagram of the first parallel line and the divided region of the present invention;

[0055] Figure 4 This is a schematic diagram of the projection boundary points of the present invention;

[0056] Figure 5 This is a schematic diagram of the contour fitting equation of the present invention. Detailed Implementation

[0057] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0058] Example 1, please refer to Figure 1 As shown, this application provides a thunderstorm identification method based on dual-polarization radar, including the following steps:

[0059] Step S1: Obtain the reflectivity and corresponding coordinate points of the target area based on dual-polarization radar, and mark them as real-time reflectivity and real-time coordinates, respectively; real-time reflectivity is the reflectivity factor, real-time coordinates and the coordinate points that generate the corresponding reflectivity factor; in this article, the reflectivity factor is referred to as reflectivity.

[0060] Step S2: Obtain the thunderstorm reflection threshold based on the reflectivity of a first number of thunderstorms; Step S2 includes the following sub-steps:

[0061] Step S201: Mark the reflectivity of the first number of thunderstorms as historical thunderstorm reflectivity; the distribution range of the first number of historical thunderstorm reflectivity, therefore the first number should not be set too small, for example, the first number is 200;

[0062] Step S202: Obtain the range of historical thunderstorm reflectivity; divide the range of historical thunderstorm reflectivity into a third number of equally spaced intervals, and mark them as reflectivity segmentation intervals; divide into a third number of reflectivity segmentation intervals in order to observe the distribution of historical thunderstorm reflectivity, so the third number should not be set too small, for example, the third number is 10;

[0063] Step S203: Obtain the frequency of historical thunderstorm reflectivity within each reflectivity segmentation interval, and mark it as the reflectivity segmentation frequency;

[0064] Step S204: Calculate the reflectivity frequency threshold as: A1 = b1 × (C1 ÷ D1); where A1 is the reflectivity frequency threshold, b1 is the reflectivity frequency ratio, C1 is the sum of all reflectivity segment frequencies, and D1 is the third quantity; the reflectivity frequency threshold is set to filter out smaller reflectivity segment frequencies, so b1 is set relatively small, for example, b1 is 0.1; b1 can be changed according to the size of C1 and D1;

[0065] The reflectance segmentation frequency that is less than the reflectance frequency threshold is marked as the reflectance anomaly frequency;

[0066] Step S205: Obtain the minimum value of each reflectance segmentation interval and mark it as the first reflectance value;

[0067] Sort the reflectivity segmentation frequencies from left to right according to the corresponding first reflectivity value, from smallest to largest.

[0068] Step S206: If the leftmost reflectance division frequency is an abnormal reflectance frequency, delete this abnormal reflectance frequency until the leftmost reflectance division frequency is no longer an abnormal reflectance frequency; then obtain the first reflectance value corresponding to the leftmost reflectance division frequency and mark it as the thunderstorm reflectance threshold; the thunderstorm reflectance threshold is used to exclude small historical thunderstorm reflectance, that is, to exclude abnormally small data, and thus obtain the accurate range of historical thunderstorm reflectance, which is convenient for subsequent judgment on whether the real-time reflectance is thunderstorm reflectance;

[0069] In practical applications, the historical thunderstorm reflectance range is obtained from 35 dBZ to 75 dBZ. This range is divided into 10 reflectance intervals: 35 to 39, 39 to 43, ..., 71 to 75. The corresponding reflectance interval frequencies are 1, 6, ..., 2. The sum of all reflectance interval frequencies is 200. The reflectance frequency threshold is calculated as: A1 = 0.1 × (200 ÷ 10) = 2. Reflectance interval frequencies less than the threshold of 2 are marked as abnormal reflectance frequencies. After deleting abnormal reflectance frequencies, the reflectance interval frequencies are sorted as 6, ..., 2. The first reflectance value corresponding to the leftmost reflectance interval frequency 6 is 39 dBZ, therefore the thunderstorm reflectance threshold is 39 dBZ.

[0070] Step S3: Obtain the thunderstorm coordinates based on the thunderstorm reflection threshold, real-time coordinates, and real-time reflectivity; Step S3 includes the following sub-steps:

[0071] Step S301: Mark the real-time reflectivity that is greater than or equal to the thunderstorm reflection threshold as the real-time thunderstorm reflectivity; obtain the real-time coordinates corresponding to the real-time thunderstorm reflectivity and mark them as thunderstorm coordinate points; since the reflectivity factor is a measure of the echo power received by the radar antenna after the electromagnetic waves emitted by the weather radar are scattered by precipitation particles in the atmosphere; therefore, the greater the rain, the greater the real-time thunderstorm reflectivity, and when it reaches a certain level, it is called a thunderstorm; therefore, the real-time reflectivity that is greater than the thunderstorm reflection threshold is identified as the reflectivity of a thunderstorm;

[0072] In practical applications, real-time reflectance greater than or equal to 39 dBZ is labeled as real-time thunderstorm reflectance.

[0073] Step S4: Obtain individual thunderstorm points based on thunderstorm coordinates; Step S4 includes the following sub-steps:

[0074] Step S401: Establish a three-dimensional coordinate system and label it as the thunderstorm location coordinate system; ensure that all thunderstorm coordinate points are within the thunderstorm location coordinate system;

[0075] Step S402: Obtain any thunderstorm coordinate point and mark it as the starting thunderstorm point; mark a sphere with a diameter of the first length as a reference sphere; establish a reference sphere centered on the starting thunderstorm point and mark it as the starting sphere; the first length is set based on the continuity of the thunderstorm range, for example, the first length is 0.15km; establishing a reference sphere facilitates the search of the overall thunderstorm volume range and the elimination of individual interfering data, such as aircraft, etc.

[0076] Step S403: Determine whether the starting sphere contains newly appearing thunderstorm coordinates. If not, obtain new thunderstorm coordinates as the starting thunderstorm point. If it does contain thunderstorm coordinates, mark the newly appearing thunderstorm coordinates in the starting sphere as the search thunderstorm point. Eliminate interfering independent thunderstorm coordinates to obtain the accurate thunderstorm area.

[0077] Step S404: Establish a reference sphere centered on the searched thunderstorm point and mark it as the search sphere; establish a new reference sphere with new thunderstorm coordinates within the search sphere, and repeat the process of establishing a new reference sphere with new thunderstorm coordinates within the new reference sphere until the new reference sphere does not contain any new thunderstorm coordinates; obtain the thunderstorm coordinates within all the established reference spheres and mark them as individual thunderstorm points; this method can obtain a continuous thunderstorm region, and an individual thunderstorm point is a coordinate point within a thunderstorm region.

[0078] Step S5: Construct real-time thunderstorm parameters and fitted midpoints based on individual thunderstorm points; Step S5 includes the following sub-steps:

[0079] Step S501: Mark the plane formed by the X-axis and Y-axis in the thunderstorm location coordinate system as the projection plane, and project all individual thunderstorm points onto the projection plane to obtain thunderstorm projection points.

[0080] For practical applications, please refer to Figure 2 As shown, the projection points of the thunderstorm are drawn.

[0081] Step S502: Mark the straight line parallel to the X-axis as the first parallel line; draw a fourth number of first parallel lines with an interval of the second distance to divide the thunderstorm location coordinate system into multiple regions, and mark them as divided regions; the division of regions is to obtain the region formed by the thunderstorm projection points, so the division of regions should divide the entire region formed by the thunderstorm projection points. Therefore, the fourth number should not be set too small, and the second distance should not be set too large. For example, the fourth number is 31 and the second distance is 0.15km.

[0082] For practical applications, please refer to Figure 3 As shown, the first parallel line and the divided region are drawn.

[0083] Step S503: Obtain the minimum and maximum abscissa of the thunderstorm projection points within each divided region and mark them as projection boundary points; obtain the projection boundary points by dividing the region, and the projection boundary points are the thunderstorm projection points at the boundaries of the regions formed by the obtained thunderstorm projection points; this facilitates the analysis of the size and direction of the thunderstorm projection.

[0084] For practical applications, please refer to Figure 4 As shown, the obtained projection boundary points.

[0085] Step S504, set the contour fitting equation as: (F1-e1) 2 ÷e2+(F2-e3) 2 ÷e4=1; where F1 and F2 are the x-coordinate and y-coordinate values, respectively, and e1, e2, e3, and e4 are the parameters of the contour fitting equation; the contour fitting equation is an ellipse equation, since the projection of each thunderstorm on the plane is approximately a circle or ellipse, so the projection boundary points are fitted by the contour fitting equation.

[0086] Step S505: Fit all the projection boundary points with the contour fitting equation to obtain the graphic, and mark it as the projection contour.

[0087] For practical applications, please refer to Figure 5 As shown, the obtained projection contour.

[0088] Step S506: Obtain the area of ​​the projected contour and mark it as the real-time thunderstorm parameter; obtain the center of the projected contour and mark it as the fitting midpoint; the projected contour is elliptical, so the real-time thunderstorm parameter and the fitting midpoint can be obtained; the regular projected contour makes it easier to analyze thunderstorms.

[0089] For practical applications, please refer to Figure 5 As shown, the area of ​​the obtained projected profile is 24.2 km². 2 The fitted midpoint is (5.9, 5.7).

[0090] Step S6: Obtain the warning thunderstorm threshold based on the second number of thunderstorms requiring warning; Step S6 includes the following sub-steps:

[0091] Step S601: Obtain real-time thunderstorm parameters by taking any coordinate point in a thunderstorm that requires warning as the thunderstorm coordinate point, and mark it as historical thunderstorm parameters; obtain historical thunderstorm parameters for all thunderstorms that require warning; thunderstorms that require warning are those with a large area, where the larger the projected outline area, the more historical thunderstorm parameters are obtained, and then it is determined whether the thunderstorm requires warning; the distribution range of historical thunderstorm parameters is obtained from the second number of historical thunderstorm parameters, so the larger the second number, the better, for example, the second number is 1000;

[0092] Step S602: Obtain the range of historical thunderstorm parameters; divide the range of historical thunderstorm parameters into five equal intervals, and mark them as parameter segmentation intervals; the fifth number of parameter segmentation intervals is for observing the distribution of historical thunderstorm parameters, so the fifth number should not be set too small, for example, the fifth number is 50;

[0093] Step S603: Obtain the frequency of historical thunderstorm parameters within each parameter segmentation interval and mark it as the parameter segmentation frequency;

[0094] Step S604, calculate the parameter frequency threshold as: A2 = b2 × (C2 ÷ D2); where A2 is the parameter frequency threshold, b2 is the parameter frequency ratio, C2 is the sum of the frequencies of all parameter segments, and D2 is the fifth quantity; the parameter frequency threshold is set to filter out parameters with excessively small segment frequencies, so b2 is set relatively small, for example, b2 is 0.1;

[0095] Step S605: Mark the parameter segmentation frequency that is less than the parameter frequency threshold as the parameter abnormal frequency.

[0096] Step S606: Obtain the minimum value of each parameter segmentation interval and mark it as the first parameter value;

[0097] Step S607: Sort the parameter segmentation frequencies from left to right according to the corresponding first parameter values ​​from smallest to largest;

[0098] Step S608: If the leftmost parameter segmentation frequency is an abnormal parameter frequency, delete this abnormal parameter frequency until the leftmost parameter segmentation frequency is no longer an abnormal parameter frequency; then obtain the first parameter value corresponding to the leftmost parameter segmentation frequency and mark it as the warning thunderstorm threshold; the warning thunderstorm threshold is used to filter out smaller abnormal parameter frequencies, that is, to exclude abnormally small data, and thus obtain the accurate range of historical thunderstorm parameters; this facilitates subsequent judgment on whether a thunderstorm warning is needed;

[0099] In practical applications, the range for obtaining historical thunderstorm parameters is 6km. 2 up to 206km 2 The range of 6 to 206 is divided into five parameter segmentation intervals: 6 to 10, 10 to 14, ..., 202 to 206; the parameter segmentation frequencies are 1, 4, ..., 6 respectively; the sum of all parameter segmentation frequencies, C2, is 1000; the parameter frequency threshold is calculated as: A2 = 0.1 × (1000 ÷ 50) = 2; parameter segmentation frequencies less than 2 are marked as abnormal parameter frequencies; after deleting these abnormal parameter frequencies, the parameter segmentation frequencies are sorted as: 4, ..., 6; the first parameter value corresponding to the leftmost parameter segmentation frequency is 10, therefore the warning thunderstorm threshold is 10km. 2 .

[0100] Step S7: Determine whether a thunderstorm requires warning based on the warning thunderstorm threshold and real-time thunderstorm parameters, and obtain the horizontal movement direction of the thunderstorm based on the fitted midpoint; Step S1 includes the following sub-steps:

[0101] Step S701: If the real-time thunderstorm parameters are greater than the warning thunderstorm threshold, the thunderstorm area is identified as a thunderstorm requiring warning; obtain the fitted midpoint obtained before the first time and mark it as the midpoint of the previous time; take the direction from the midpoint of the previous time to the fitted midpoint as the horizontal movement direction of the thunderstorm; if the real-time thunderstorm parameters are greater than the warning thunderstorm threshold, it means that the projected area of ​​the thunderstorm is large, that is, the thunderstorm is large and exceeds the warning requirement; since the horizontal movement direction of the thunderstorm is the east-west-north-south direction, the horizontal movement direction of the thunderstorm can be predicted quickly and briefly.

[0102] In practical applications, if the real-time thunderstorm parameter is 24.2km... 2 10km above the warning thunderstorm threshold 2 If a thunderstorm area is identified as a thunderstorm requiring warning, the real-time thunderstorm parameters can be further divided into ranges, with each range representing the warning level for the thunderstorm.

[0103] Example 2: This application also provides an electronic device, which may include: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus. The memory stores computer-readable instructions, and the processor can call the instructions in the memory. When the computer-readable instructions are executed by the processor, the steps of a thunderstorm identification method based on dual-polarization radar are performed to achieve the following functions: obtaining the reflectivity and corresponding coordinate points of the target area based on dual-polarization radar, and marking them as real-time reflectivity and real-time coordinates, respectively; obtaining a thunderstorm reflection threshold based on the reflectivity of a first number of thunderstorms; obtaining thunderstorm coordinate points based on the thunderstorm reflection threshold, real-time coordinates, and real-time reflectivity; obtaining individual thunderstorm points based on the thunderstorm coordinate points; constructing real-time thunderstorm parameters and a fitted midpoint based on the individual thunderstorm points; obtaining a warning thunderstorm threshold based on a second number of thunderstorms requiring warning; determining whether a thunderstorm requires warning based on the warning thunderstorm threshold and real-time thunderstorm parameters; and obtaining the horizontal movement direction of the thunderstorm based on the fitted midpoint.

[0104] Furthermore, the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, and can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0105] Example 3: This application also provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute a thunderstorm identification method based on dual-polarization radar provided by the above methods. The method includes: acquiring the reflectivity and corresponding coordinate points of a target area based on dual-polarization radar, and marking them as real-time reflectivity and real-time coordinates, respectively; acquiring a thunderstorm reflection threshold based on the reflectivity of a first number of thunderstorms; acquiring thunderstorm coordinate points based on the thunderstorm reflection threshold, real-time coordinates, and real-time reflectivity; acquiring individual thunderstorm points based on the thunderstorm coordinate points; constructing real-time thunderstorm parameters and a fitting midpoint based on the individual thunderstorm points; acquiring a warning thunderstorm threshold based on a second number of thunderstorms requiring warning; determining whether a thunderstorm requires warning based on the warning thunderstorm threshold and real-time thunderstorm parameters; and acquiring the horizontal movement direction of the thunderstorm based on the fitting midpoint.

[0106] Example 4: This application also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it performs the steps of the above-described thunderstorm identification method based on dual-polarization radar to achieve the following functions: acquiring the reflectivity and corresponding coordinate points of the target area based on dual-polarization radar, and marking them as real-time reflectivity and real-time coordinates, respectively; acquiring a thunderstorm reflection threshold based on the reflectivity of a first number of thunderstorms; acquiring thunderstorm coordinate points based on the thunderstorm reflection threshold, real-time coordinates, and real-time reflectivity; acquiring individual thunderstorm points based on the thunderstorm coordinate points; constructing real-time thunderstorm parameters and a fitted midpoint based on the individual thunderstorm points; acquiring a warning thunderstorm threshold based on a second number of thunderstorms requiring warning; determining whether a thunderstorm requires warning based on the warning thunderstorm threshold and real-time thunderstorm parameters; and acquiring the horizontal movement direction of the thunderstorm based on the fitted midpoint.

[0107] Based on the above description of the embodiments, the embodiments of the present invention can be provided as methods, systems, or computer program products. Based on this understanding, the above technical solutions, in essence or in terms of their contribution to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or certain parts of the embodiments.

[0108] In the embodiments provided in this application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces. The indirect coupling or communication connection between systems, modules, and units may be electrical, mechanical, or other forms.

[0109] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A thunderstorm identification method based on dual-polarization radar, characterized in that, Includes the following steps: The reflectivity and corresponding coordinates of the target area are obtained based on the dual-polarization radar and are marked as real-time reflectivity and real-time coordinates, respectively. The thunderstorm reflection threshold is obtained based on the reflectivity of a first number of thunderstorms; Thunderstorm coordinates are obtained based on thunderstorm reflection threshold, real-time coordinates, and real-time reflectivity. Obtain individual thunderstorm points based on thunderstorm coordinates; Constructing real-time thunderstorm parameters and fitting midpoints based on individual thunderstorm points; The threshold for warning thunderstorms is obtained based on the second number of thunderstorms that require warning; Whether a thunderstorm requires warning is determined based on the warning thunderstorm threshold and real-time thunderstorm parameters, and the horizontal movement direction of the thunderstorm is obtained based on the fitted midpoint. Obtaining the thunderstorm reflection threshold based on the reflectivity of a first number of thunderstorms includes the following sub-steps: The reflectivity of the first number of thunderstorms is marked as the historical thunderstorm reflectivity; Obtain the range of historical thunderstorm reflectivity; divide the range of historical thunderstorm reflectivity into a third number of equally spaced intervals, and mark them as reflectivity segmentation intervals; Obtain the frequency of historical thunderstorm reflectance within each reflectance segmentation interval and mark it as the reflectance segmentation frequency; The reflectance frequency threshold is calculated as follows: A1 = b1 × (C1 ÷ D1); where A1 is the reflectance frequency threshold, b1 is the reflectance frequency ratio, C1 is the sum of all reflectance segment frequencies, and D1 is the third quantity. The reflectance segmentation frequency that is less than the reflectance frequency threshold is marked as the reflectance anomaly frequency; Obtain the minimum value of each reflectance segmentation interval and mark it as the first reflectance value; Sort the reflectivity segmentation frequencies from left to right according to the corresponding first reflectivity value, from smallest to largest. If the leftmost reflectance segment frequency is an abnormal reflectance frequency, then delete this abnormal reflectance frequency until the leftmost reflectance segment frequency is no longer an abnormal reflectance frequency; then obtain the first reflectance value corresponding to the leftmost reflectance segment frequency and mark it as the thunderstorm reflection threshold.

2. The thunderstorm identification method based on dual-polarization radar according to claim 1, characterized in that, Obtaining thunderstorm coordinates based on thunderstorm reflection threshold, real-time coordinates, and real-time reflectivity includes the following sub-steps: The real-time reflectivity that is greater than or equal to the thunderstorm reflectivity threshold is marked as the real-time thunderstorm reflectivity; the real-time coordinates corresponding to the real-time thunderstorm reflectivity are obtained and marked as thunderstorm coordinate points.

3. The thunderstorm identification method based on dual-polarization radar according to claim 2, characterized in that, Obtaining a single thunderstorm location based on thunderstorm coordinates includes the following sub-steps: Establish a three-dimensional coordinate system, labeled as the thunderstorm location coordinate system; ensure that all thunderstorm coordinate points are within the thunderstorm location coordinate system. Obtain any thunderstorm coordinates and mark it as the starting thunderstorm point; mark a sphere with a diameter of the first length as the reference sphere; establish a reference sphere centered on the starting thunderstorm point and mark it as the starting sphere; Determine if the starting sphere contains newly appeared thunderstorm coordinates. If not, obtain a new thunderstorm coordinate as the starting thunderstorm point. If it does contain thunderstorm coordinates, mark the newly appeared thunderstorm coordinates within the starting sphere as the search thunderstorm point. Establish a reference sphere centered on the searched thunderstorm point and mark it as the search sphere; establish a new reference sphere with the new thunderstorm coordinates within the search sphere, and repeat the process of establishing a new reference sphere with the new thunderstorm coordinates within the new reference sphere until the new reference sphere does not contain any new thunderstorm coordinates; obtain the thunderstorm coordinates within all the established reference spheres and mark them as individual thunderstorm points.

4. The thunderstorm identification method based on dual-polarization radar according to claim 3, characterized in that, Constructing real-time thunderstorm parameters and fitting midpoints based on individual thunderstorm points includes the following sub-steps: The plane formed by the X-axis and Y-axis in the thunderstorm location coordinate system is marked as the projection plane. All individual thunderstorm points are projected onto the projection plane to obtain thunderstorm projection points. The line parallel to the X-axis is marked as the first parallel line; Draw a fourth number of first parallel lines with an interval of the second distance to divide the thunderstorm location coordinate system into multiple regions, and mark them as the divided regions; Obtain the minimum and maximum x-coordinates of the thunderstorm projection points within each divided region, and mark them as projection boundary points.

5. A thunderstorm identification method based on dual-polarization radar according to claim 4, characterized in that, Constructing real-time thunderstorm parameters and fitting midpoints based on individual thunderstorm points also includes the following sub-steps: The contour fitting equation is set as: (F1-e1) 2 ÷e2+(F2-e3) 2 ÷e4=1; where F1 and F2 are the x-coordinate and y-coordinate values, respectively, and e1, e2, e3, and e4 are the parameters of the contour fitting equation; The graphic obtained by fitting all the projected boundary points with the contour fitting equation is marked as the projected contour. Obtain the area of ​​the projected contour and mark it as the real-time thunderstorm parameter; obtain the center of the projected contour and mark it as the fitting midpoint.

6. A thunderstorm identification method based on dual-polarization radar according to claim 5, characterized in that, Obtaining the warning thunderstorm threshold based on the second number of thunderstorms requiring warning includes the following sub-steps: Get real-time thunderstorm parameters by taking any coordinate point in a thunderstorm that requires warning as the thunderstorm coordinate point and marking it as historical thunderstorm parameters; get historical thunderstorm parameters for all thunderstorms that require warning. Obtain the range of historical thunderstorm parameters; divide the range of historical thunderstorm parameters into five equal intervals, and mark them as parameter segmentation intervals; Obtain the frequency of historical thunderstorm parameters within each parameter segmentation interval and mark it as the parameter segmentation frequency; The parameter frequency threshold is calculated as: A2 = b2 × (C2 ÷ D2); where A2 is the parameter frequency threshold, b2 is the parameter frequency ratio, C2 is the sum of the frequencies of all parameter segments, and D2 is the fifth quantity. Parameter segmentation frequencies that are less than the parameter frequency threshold are marked as parameter abnormal frequencies.

7. A thunderstorm identification method based on dual-polarization radar according to claim 6, characterized in that, The process of obtaining the warning thunderstorm threshold based on the second number of thunderstorms requiring warning also includes the following sub-steps: Get the minimum value of each parameter's segmentation interval and mark it as the first parameter value; Sort the parameter segmentation frequencies from left to right according to the corresponding first parameter value, from smallest to largest. If the leftmost parameter segmentation frequency is a parameter abnormality frequency, then delete this parameter abnormality frequency until the leftmost parameter segmentation frequency is no longer a parameter abnormality frequency; then obtain the first parameter value corresponding to the leftmost parameter segmentation frequency and mark it as the warning thunderstorm threshold.

8. A thunderstorm identification method based on dual-polarization radar according to claim 7, characterized in that, Determining whether a thunderstorm requires warning based on the early warning threshold and real-time thunderstorm parameters, and obtaining the horizontal movement direction of the thunderstorm based on the fitted midpoint, includes the following sub-steps: If the real-time thunderstorm parameters are greater than the warning thunderstorm threshold, the thunderstorm area is identified as a thunderstorm requiring warning; the fitted midpoint obtained before the first time is obtained and marked as the midpoint of the previous time; the direction from the midpoint of the previous time to the fitted midpoint is regarded as the horizontal movement direction of the thunderstorm.

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