Method and device for evaluating artificial hail prevention effect, terminal equipment and storage medium

Abstract

The application discloses a kind of artificial hail prevention effect evaluation method, device, terminal equipment and storage medium, the method comprises: based on operation information matching radar data, to divide target cloud block;Search similar cloud block in unit time before and after operation, and the radar combined reflectivity of similar cloud block is calculated, to filter out target cloud block before and after operation;Based on the target cloud block before and after operation, calculate the change rate of radar parameter on unit time sequence before and after operation, to obtain the cloud system generation and disappearance development index of target cloud block before and after operation;The cloud system generation and disappearance development index of target cloud block before and after operation is compared, to judge whether operation result is effective, judging standard is: when the cloud system generation and disappearance development index of target cloud block before operation>the cloud system generation and disappearance development index of target cloud block after operation, operation result is effective, otherwise operation result is invalid.This evaluation method is simple and efficient, can exclude the interference of cloud system natural development to operation.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of artificial hail prevention, and particularly relates to an artificial hail prevention effect evaluation method and device, a terminal device and a storage medium. BACKGROUND

[0002] Hail, as a short-time severe weather process, often causes serious impact on agriculture, construction, power, transportation and even life and property, so artificial hail prevention has attracted widespread attention.

[0003] Artificial hail prevention is a disaster prevention means by seeding catalyst (such as silver iodide) into hail cloud to inhibit hail growth or make it melt into raindrops in advance, and its effect evaluation needs to solve the core problems of high randomness of natural process and difficulty in separating operation interference. The existing hail prevention effect evaluation technical solutions are mainly divided into mathematical model method and comparative cloud analysis method: the mathematical model method is based on the change of radar parameters before and after operation for formula calculation, which is simple to operate and the result is intuitive, but it ignores natural evolution and the parameters are easily disturbed by environment; the comparative cloud analysis method is based on the parameter difference between target cloud and non-operation comparative cloud for analysis, which has clear physical mechanism and can trace the process, but it is difficult to select comparative cloud and the operation is complex. In addition, there are problems such as lack of direct observation of catalyst diffusion efficiency, low matching precision of seeding area and hail inhibition area, dependence of ground hail data on farmer reporting and high omission rate, and no distinction between high cannon / rocket operation differences. Therefore, there is still a lack of scientific method for efficient and accurate evaluation of hail prevention operation effect. SUMMARY

[0004] The purpose of the present application is to provide an artificial hail prevention effect evaluation method, device, terminal device and storage medium, which aims to overcome the shortcomings of the prior art. The present application uses high-precision radar data and the inversion ability of polarized parameter microphysical indicators, and combines computer-related algorithms to deduce the target cloud before and after operation. On the basis of conventional radar parameter indicators, the multi-dimensional macro-micro parameter indicators of hail cloud represented by polarimetric radar are specially added. Then the change rate of these radar parameters in time series before and after operation is calculated to obtain the cloud system generation and development index of the target cloud before and after operation. Finally, the cloud system generation and development indexes of the target cloud before and after operation are compared in numerical size, so as to efficiently and accurately evaluate the effect of hail prevention operation.

[0005] To solve the above problems, the first aspect of the present application provides a method for evaluating the effect of artificial hail prevention, which comprises the following steps: step S1, dividing target cloud blocks based on operation information matching radar data; step S2, retrieving similar cloud blocks in unit time before and after operation, and calculating radar combined reflectivity of the similar cloud blocks to screen out target cloud blocks before and after operation and obtain radar parameter data of the target cloud blocks before and after operation; step S3, calculating the change rate of radar parameters on the unit time sequence before and after operation based on the target cloud blocks before and after operation to obtain cloud system generation and dissipation development indexes of the target cloud blocks before and after operation; and step S4, comparing the cloud system generation and dissipation development indexes of the target cloud blocks before and after operation to determine whether the operation result is effective, and the determination standard is that when the cloud system generation and dissipation development index of the target cloud block before operation is greater than that of the target cloud block after operation, the operation result is effective, otherwise the operation result is ineffective.

[0006] Further, the step S1 comprises the following steps: step S11, matching the closest radar data based on operation time; step S12, marking radar data reference points with the longitude and latitude of the operation site; step S13, dividing target cloud blocks of 10x10 km to 30x30 km in size from the radar data reference points as the starting point, extending 5-15 km to the left and right, and along the operation azimuth direction; and step S14, determining the reference position of the target cloud blocks based on the divided target cloud blocks.

[0007] Further, the step S2 comprises the following steps: step S21, determining target cloud block reference points according to the reference position of the target cloud blocks; step S22, retrieving similar cloud blocks in unit time before and after operation based on the target cloud block reference points, and the minimum value of the unit time is in the range of 3-6 minutes; step S23, performing a set of parallel calculations on the radar combined reflectivity of each similar cloud block by using a computer vision algorithm for multi-target tracking, a linear algorithm for measuring the linear relationship between continuous variables, and an image quality evaluation index for evaluating the difference or similarity between signals; step S24, performing summation operation on each set of parallel calculation results; step S25, comparing the results of the summation operation to screen out the summation maximum value before operation and the summation maximum value after operation; step S26, determining the radar combined reflectivity corresponding to the maximum value as the matching echo, i.e., determining the matching echo as the derived echo of the target cloud block, thereby quickly excluding similar cloud blocks and screening out the target cloud blocks before and after operation.

[0008] Further, the step S3 comprises: a step S31 of dividing the unit time before and after the operation into a plurality of equal time periods according to a unified standard; a step S32 of calculating the change rate of each single radar parameter in each equal time period before and after the operation; a step S33 of dividing the unit time before and after the operation into a main time period and an auxiliary time period which are continuous in time based on the plurality of equal time periods before and after the operation; a step S34 of performing summation calculation or average calculation on the change rate of each equal time period of the single radar parameter in the main time period and the auxiliary time period before and after the operation, so as to obtain the change rate of the single radar parameter in the main time period and the auxiliary time period before and after the operation, i.e., the cloud system generation and disappearance development index of the single radar parameter before and after the operation; and a step S35 of performing weighted summation calculation on the cloud system generation and disappearance development indexes of the plurality of radar parameters before and after the operation based on the cloud system generation and disappearance development index of the single radar parameter before and after the operation, so as to obtain the cloud system generation and disappearance development index of the target cloud block before and after the operation.

[0009] Further, the radar parameters comprise: target cloud block spatial maximum echo intensity, strong echo top height, strong echo proportion, echo centroid, hail particle distribution maximum height, hail particle proportion, graupel particle distribution maximum height, graupel particle proportion, radar estimated rainfall, and strong echo vertical dispersion, which are parameter indexes for characterizing cloud microphysical processes and can accurately describe the generation and disappearance state of the cloud system after calculation, and exclude the interference of natural development of the cloud system on the operation.

[0010] According to another aspect of the present application, the present application also provides an artificial hail prevention effect evaluation device, which comprises: a target cloud block space-time matching module for matching radar data according to operation information and dividing a target cloud block; a target cloud block tracking module for searching similar cloud blocks in the unit time before and after the operation, calculating the radar combined reflectivity of the similar cloud blocks, and screening the target cloud blocks before and after the operation; a parameter change rate calculation module for calculating the change rate of the radar parameters in the unit time sequence before and after the operation based on the target cloud blocks before and after the operation, and obtaining the cloud system generation and disappearance development index of the target cloud blocks before and after the operation; and a comprehensive effect evaluation module for comparing the cloud system generation and disappearance development indexes of the target cloud blocks before and after the operation, judging whether the operation result is effective or not, and the judgment standard being that the operation result is effective when the cloud system generation and disappearance development index of the target cloud block before the operation is greater than the cloud system generation and disappearance development index of the target cloud block after the operation, otherwise the operation result is ineffective.

[0011] Further, the target cloud block space-time matching module is specifically configured to: match the closest radar data based on the operation time; mark the radar data reference point by using the longitude and latitude of the operation site; divide the target cloud block of 10x10 km to 30x30 km from the radar data reference point to the left and right by 5-15 km along the operation azimuth direction; and determine the reference position of the target cloud block based on the divided target cloud block.

[0012] Further, the target cloud block tracking module is specifically configured to: determine the target cloud block reference point according to the target cloud block reference position; search for similar cloud blocks in a unit time before and after the operation based on the target cloud block reference point, wherein the minimum value of the unit time is in the range of 3-6 minutes; perform a set of parallel calculations on the radar combined reflectivity of each similar cloud block by using a computer vision algorithm for multi-target tracking, a linear algorithm for measuring the linear relationship between continuous variables, and an image quality evaluation index for evaluating the difference or similarity between signals; perform summation operation on each set of parallel calculation results; compare the results of the summation operation to filter out the summation maximum value before the operation and the summation maximum value after the operation; determine the radar combined reflectivity corresponding to the maximum value as the derived echo of the target cloud block, so as to filter out the target cloud block before the operation and the target cloud block after the operation.

[0013] Further, the parameter change rate calculation module is specifically configured to: uniformly divide the unit time before and after the operation into a plurality of equal time periods; calculate the change rate of each equal time period of a single radar parameter before and after the operation; uniformly divide the unit time before and after the operation into a time-continuous main time period and an auxiliary time period based on the plurality of equal time periods before and after the operation; perform summation calculation or average calculation on the change rate of each equal time period of the single radar parameter in the main time period and the auxiliary time period before and after the operation to obtain the change rate of the single radar parameter in the main time period and the auxiliary time period before and after the operation; perform weighted summation calculation on the change rate of the single radar parameter in the main time period and the auxiliary time period before and after the operation to obtain the change rate of the single radar parameter in the total time period before and after the operation, that is, the cloud system generation and dissipation development index of the single radar parameter before and after the operation; and perform weighted summation calculation on the cloud system generation and dissipation development indexes of the plurality of radar parameters before and after the operation based on the cloud system generation and dissipation development index of the single radar parameter before and after the operation to obtain the cloud system generation and dissipation development index of the target cloud block before and after the operation.

[0014] According to another aspect of the present application, the present application also provides a terminal device comprising a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor implements the steps of the artificial hail prevention effect evaluation method described above when executing the program.

[0015] According to still another aspect of the present application, the present application also provides a storage medium storing a program, which, when executed by a processor, implements the steps of the artificial hail prevention effect evaluation method described above.

[0016] The artificial hail prevention effect evaluation method provided by the present application is to match a target cloud block according to operation information, then search for similar cloud blocks before and after operation in a unit time, quickly exclude similar cloud blocks by calculating radar combined reflectivity of the similar cloud blocks, screen out target cloud blocks before and after operation, and obtain radar parameter data of the target cloud blocks before and after operation; based on the radar parameter data of the target cloud blocks before and after operation, calculate the change rate of radar parameters on the unit time sequence before and after operation to obtain cloud system generation and disappearance development indexes of the target cloud blocks before and after operation; compare the cloud system generation and disappearance development indexes of the target cloud blocks before and after operation to determine whether the operation result is effective, and the specific determination standard is: when the cloud system generation and disappearance development index of the target cloud block before operation is greater than that of the target cloud block after operation, the operation result is effective; when the cloud system generation and disappearance development index of the target cloud block before operation is less than or equal to that of the target cloud block after operation, the operation result is ineffective. This method can efficiently and simply complete the evaluation of artificial hail prevention effect according to the deduced cloud system change.

[0017] The above technical solutions of the present application have the following beneficial technical effects:

[0018] The present application establishes multi-dimensional macro-micro parameter indexes based on the cloud microphysical process of hail cloud represented by polarization radar in addition to conventional radar parameter indexes (such as reflectivity), such as target cloud block space maximum echo intensity, strong echo top height, strong echo proportion, hail particle distribution maximum height, hail particle proportion, graupel particle proportion, and radar estimated rainfall, and accurately describes the generation and disappearance state of cloud system through scientific calculation, thereby excluding the interference of natural development of cloud system on operation.

[0019] The present application is based on the existing meteorological business radar system, utilizes high-precision, high-spatiotemporal resolution, and high-reliability radar data and polarization parameter microphysical index inversion capability, simultaneously establishes the trajectory of high-altitude gun or rocket according to the parameters provided by different manufacturers, accurately locates the diffusion position of catalyst during each operation, and thus locks the operation range, which not only solves the operation difference problem of high-altitude gun and rocket, but also solves the problem of low matching accuracy of sowing area and hail suppression area.

[0020] Particularly, in the technical scheme of the present application, only radar data in a unit time before and after the operation is extracted for full-chain analysis and calculation, wherein the minimum value of the unit time is 6 minutes; the technical scheme of the present application does not need to find a contrast area of a target cloud block, all indexes are data-based, quantitative analysis can be performed, and the technical scheme of the present application can be implemented in full automation, the overall operation can be completed within a few minutes, and has high scientificity and timeliness. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 is a flow chart of a method for evaluating the effect of artificial hail prevention in the embodiment of the present application;

[0022] Figure 2 is Figure 1 is a flow chart of a specific implementation of step S1 in the embodiment;

[0023] Figure 3 is Figure 1 is a flow chart of a specific implementation of step S2 in the embodiment;

[0024] Figure 4 is Figure 1 is a flow chart of a specific implementation of step S3 in the embodiment;

[0025] Figure 5 is a schematic diagram of the first-order derivative of the maximum echo intensity of the target cloud block in the main time period and the auxiliary time period within 1 hour after (or before) the operation in the specific embodiment of the present application;

[0026] Figure 6 is a schematic diagram of a judgment standard for the effect of artificial hail prevention in the embodiment of the present application;

[0027] Figure 7 is a flow chart of a device for evaluating the effect of artificial hail prevention in the embodiment of the present application. DETAILED DESCRIPTION

[0028] To make the objectives, technical solutions and advantages of the present application clearer, further detailed description will be made to the present application with reference to the specific embodiments and the accompanying drawings. It should be understood that these descriptions are only exemplary and are not intended to limit the scope of the present application. In addition, in the following description, the description of the known structures and technologies is omitted to avoid unnecessary confusion of the concept of the present application.

[0029] Figure 1 is a flow chart of a method for evaluating the effect of artificial hail prevention in the embodiment of the present application, and the specific implementation process of the present application will be described below with reference to Figures 2 to 6 , in some embodiments, the method comprises steps S1 to S4:

[0030] Step S1, matching radar data based on job information to divide target cloud blocks;

[0031] Step S2, searching for similar cloud blocks in unit time before and after the job, and calculating radar combined reflectivity of the similar cloud blocks to filter out target cloud blocks before and after the job and obtain radar parameter data of the target cloud blocks before and after the job;

[0032] Step S3, calculating the change rate of radar parameters on the unit time sequence before and after the job based on the target cloud blocks before and after the job to obtain cloud system generation and dissipation development indexes of the target cloud blocks before and after the job;

[0033] Step S4, comparing the cloud system generation and dissipation development indexes of the target cloud blocks before and after the job to determine whether the job result is effective, and the judgment standard is that when the cloud system generation and dissipation development index of the target cloud block before the job is greater than that of the target cloud block after the job, the job result is effective, otherwise the job result is ineffective.

[0034] In some embodiments of the step S1, the job information includes job time, job location (for example, job site longitude and latitude) and performance parameters of the hail catalyst device (for example, performance parameters of the high-speed gun or the rocket), radar data is matched according to the job time and the job site longitude and latitude, a trajectory simulation is established according to the device parameters, the diffusion position of the catalyst is accurately positioned, the job influence echo is locked, and therefore the matching accuracy of the sowing area and the hail suppression area is greatly improved.

[0035] Referring to Figure 2 , Figure 2 is Figure 1 a flow chart of one specific embodiment of step S1. In some embodiments, the step S1 specifically includes steps S11 to S14.

[0036] In step S11, the closest radar data is matched based on the job time.

[0037] In step S12, the radar data reference point is marked by using the job site longitude and latitude.

[0038] In step S13, the radar data reference point is taken as the starting point, and 10x10km to 30x30km target cloud blocks are divided in the direction of the job azimuth angle by extending 5-15km to the left and right.

[0039] In step S14, the reference position of the divided target cloud block is determined.

[0040] In one embodiment, the operational azimuth angle is 0°, and a 10x10 km target cloud block frame is automatically generated with the radar data reference point as the midpoint, extending 5 km to the left and right, and 10 km to the north, and the frame contains echoes and target cloud blocks.

[0041] In another embodiment, the operational azimuth angle is 135°, and a 20x20 km target cloud block frame is automatically generated with the radar data reference point as the starting point, extending 10 km to the left and right, and 10 km to the southeast, and the frame contains echoes and target cloud blocks.

[0042] Referring to Figure 3 , Figure 3 is Figure 1 a flowchart of one embodiment of step S2. In some embodiments, step S2 specifically includes steps S21 to S26.

[0043] In step S21, a target cloud block reference point is determined according to a target cloud block reference position.

[0044] In step S22, similar cloud blocks in a unit time before and after the operation are retrieved based on the target cloud block reference point, and the minimum value range of the unit time is 3-6 minutes, which is related to the radar observation mode.

[0045] In step S23, a set of parallel calculations of radar composite reflectivity of each similar cloud block is performed using computer vision algorithms for multi-target tracking, linear algorithms for measuring linear relationships between continuous variables, and image quality evaluation indicators for evaluating differences or similarities between signals, and parallel calculations of multiple algorithms can reduce misjudgment, especially when there are large-scale similar cloud blocks, and the target cloud block before the operation and the target cloud block after the operation can be more accurately tracked.

[0046] In step S24, the results of each set of parallel calculations are summed.

[0047] In step S25, the results of the summation operation are compared to screen out the maximum summation before the operation and the maximum summation after the operation.

[0048] In step S26, the radar composite reflectivity corresponding to the maximum value is determined as the matching echo, i.e., the matching echo is determined as the derived echo of the target cloud block, and this step reduces misjudgment through parallel calculations of multiple methods, especially when there are large-scale similar echoes, and the derived echo of the target cloud block can be more accurately tracked, thereby quickly excluding similar cloud blocks and screening out the target cloud block before the operation and the target cloud block after the operation.

[0049] In some embodiments, based on the target cloud cluster reference point, similar cloud clusters within hours before and after the operation are retrieved on radar, while stepping selection of radar range resolution, and the optional resolutions are 75m resolution, 150m resolution and 250m resolution, which can effectively solve the special cases of cloud cluster echo development in place or very slow movement.

[0050] In some embodiments, the computer vision algorithm includes cosine similarity and centroid tracking, the linear algorithm includes Pearson correlation coefficient, and the image quality evaluation index includes mean square error, peak signal-to-noise ratio and structural similarity. During the calculation process, a set of parallel calculations of radar combined reflectivity of each similar cloud cluster are performed based on cosine similarity, centroid tracking and Pearson correlation coefficient, and combined with mean square error and / or peak signal-to-noise ratio and / or structural similarity.

[0051] In a specific embodiment, cosine similarity, centroid tracking, Pearson correlation coefficient and mean square error are calculated for the radar combined reflectivity of each similar cloud cluster retrieved on radar within 1 hour before and after the operation, which is a set of parallel calculations.

[0052] In another specific embodiment, cosine similarity, centroid tracking, Pearson correlation coefficient, mean square error and peak signal-to-noise ratio are calculated for the radar combined reflectivity of each similar cloud cluster retrieved on radar within 1 hour before and after the operation, which is a set of parallel calculations.

[0053] In yet another specific embodiment, cosine similarity, centroid tracking, Pearson correlation coefficient, mean square error, peak signal-to-noise ratio and structural similarity are calculated for the radar combined reflectivity of each similar cloud cluster retrieved on radar within 1 hour before and after the operation, which is a set of parallel calculations.

[0054] In a specific embodiment, after calculating cosine similarity, centroid tracking, Pearson correlation coefficient, mean square error and peak signal-to-noise ratio for the radar combined reflectivity of a single similar cloud cluster retrieved on radar within 1 hour before and after the operation, the sum of the set of calculation results is calculated.

[0055] In a specific embodiment, based on the parallel calculations of cosine similarity, centroid tracking, Pearson correlation coefficient, mean square error, peak signal-to-noise ratio and structural similarity for the radar combined reflectivity of each similar cloud cluster retrieved on radar within 1 hour before and after the operation, and the sum calculation of each set of calculation results, numerical comparison is made according to the operation time, and the sum maximum before the operation and the sum maximum after the operation are respectively selected.

[0056] Referring toFigure 4 , Figure 4 is Figure 1 a flow chart of one specific implementation of step S3. In some embodiments, the step S3 specifically comprises steps S31 to S35.

[0057] In step S31, the unit time before and after the operation is uniformly divided into multiple equal time periods.

[0058] In step S32, the change rate of the single radar parameter in each equal time period before and after the operation is calculated.

[0059] In step S33, based on the multiple equal time periods before and after the operation, the unit time before and after the operation is uniformly divided into time-continuous main time periods and auxiliary time periods.

[0060] In step S34, the change rates of the single radar parameter in each equal time period before and after the operation are summed or averaged to obtain the change rates of the single radar parameter in the main time periods and auxiliary time periods before and after the operation; the change rates of the single radar parameter in the main time periods and auxiliary time periods before and after the operation are weighted and summed to obtain the change rate of the single radar parameter in the total time period before and after the operation, which is the cloud system development index of the single radar parameter before and after the operation.

[0061] In step S35, based on the cloud system development index of the single radar parameter before and after the operation, the cloud system development indexes of multiple radar parameters before and after the operation are weighted and summed to obtain the cloud system development index of the target cloud block before and after the operation.

[0062] In one specific embodiment, taking 1 hour before and after the operation as an example, the unit time is 1 hour, 6 minutes is taken as the division standard, 1 hour is divided into 10 time periods, and the time periods are sequentially labeled, i.e., 1 hour before the operation is divided into 10 equal time periods with labels, and 1 hour after the operation is divided into 10 equal time periods with labels.

[0063] In some embodiments, the calculation of the change rate of the single radar parameter in each equal time period before and after the operation specifically refers to the calculation of the first derivative of the single radar parameter in each equal time period before and after the operation within the unit time, the first derivative is denoted by K, and each equal time period is distinguished by different ordinal numbers t, so that the first derivative of a certain parameter in a certain equal time period before the operation is denoted by K 前参数 (t), and the first derivative of a certain parameter in a certain equal time period after the operation is denoted by K 后参数(t) represents. In addition, the radar parameters include multi-dimensional parameters of the polarized radar, which include: target cloud block space maximum echo intensity (Z-Max, ZM for short), strong echo top height (Z-Top, ZT for short), strong echo ratio (Z-Ratio, ZR for short), echo centroid (Centroid-Height, CH for short), hail particle distribution maximum height (Hail-Top, HT for short), hail particle ratio (Hail-Ratio, HR for short), graupel particle distribution maximum height (Graupel-Top, GT for short), graupel particle ratio (Graupel-Ratio, GR for short), radar estimated rainfall (Rainfall Estimation, RE for short), and strong echo vertical dispersion (Z-Dispersion, ZD for short). These parameter indexes representing cloud microphysical processes can accurately describe the birth and death state of the cloud system after calculation, and exclude the interference of natural development of the cloud system on the operation. Taking the radar parameter ZM as an example, the first derivative of ZM in a certain equal period before the operation is K 前ZM (t) represents, and the first derivative of ZM in a certain equal period after the operation is K 后ZM (t) represents.

[0064] In a specific embodiment, taking 1 hour before and after the operation as an example, 1 hour is divided into 10 time periods with 6 minutes as the division standard, and the time periods are sequentially marked with labels 1, 2, 3, 4, 5, 6, 7, 8, 9 and 10, that is, 1 hour before the operation is divided into 10 equal time periods with labels, and 1 hour after the operation is divided into 10 equal time periods with labels. Taking the radar parameter ZM as an example, the first derivative of the radar parameter ZM in each equal period of 1 hour before and after the operation can be obtained, and the specific equal time periods before the operation can be represented as: K 前ZM (1), K 前ZM (2), K 前ZM (3), K 前ZM (4), K 前ZM (5), K 前ZM (6), K 前ZM (7), K 前ZM (8), K 前ZM (9), and K 前ZM (10); and the specific equal time periods after the operation can be represented as: K 后ZM (1), K 后ZM (2), K 后ZM (3), K 后ZM (4), K 后ZM (5), K 后ZM (6), K 后ZM (7), K 后ZM (8), K 后ZM (9), and K后ZM (10).

[0065] In some embodiments, based on the plurality of equal time periods before and after the work, the unit time before and after the work is divided into two time-continuous time periods before and after the work according to the same division standard, one is the main time period, and the other is the auxiliary time period, that is, the plurality of equal time periods before the work can be the main time period or the auxiliary time period, and the plurality of equal time periods after the work can also be the main time period or the auxiliary time period.

[0066] In a specific embodiment, taking 1 hour after the work (or 1 hour before the work) as an example, referring to FIG. 1, Figure 5 , Figure 5 FIG. 1 is a schematic diagram of the first derivative of the maximum echo intensity of the target cloud block space in the main time period and the auxiliary time period within 1 hour after the work (or 1 hour before the work) in the specific embodiments of the present application. Taking 6 minutes as a time period, 1 hour is divided into 10 time periods, and the time periods are sequentially labeled, that is, 1 hour after the work (or 1 hour before the work) is divided into 10 equal time periods with labels. Based on the plurality of equal time periods before and after the work, 1 hour after the work (or 1 hour before the work) is divided into 3 time-continuous time periods and 7 time-continuous time periods, wherein the first 3 time-continuous time periods are the main time period and the last 7 time-continuous time periods are the auxiliary time period. The specific situation after the work is that the main time period after the work is the first 3 time periods of 1 hour after the work (that is, the first 18 minutes of 1 hour after the work), the main time period after the work is represented by “18”, and the auxiliary time period after the work is the last 7 time periods of 1 hour after the work (that is, the last 42 minutes of 1 hour after the work), the auxiliary time period after the work is represented by “42”; the specific situation before the work is that the main time period before the work is the first 3 time periods of 1 hour before the work (that is, the first 18 minutes of 1 hour before the work), the main time period before the work is represented by “18”, and the auxiliary time period before the work is the last 7 time periods of 1 hour before the work (that is, the last 42 minutes of 1 hour before the work), the auxiliary time period before the work is represented by “42”.

[0067] In some embodiments, the first derivatives of each equal time period of the main time period and the auxiliary time period of the unit time before and after the work of the single radar parameter are respectively summed and calculated to obtain the first derivatives of the main time period and the auxiliary time period of the single radar parameter before and after the work, and then the first derivatives of the main time period and the auxiliary time period of the single radar parameter before and after the work are weighted and summed to obtain the first derivative of the total time period of the single radar parameter before and after the work, that is, the cloud system generation and development index of the single radar parameter before and after the work. The first derivative of the main time period is represented by K 主时段 , the first derivative of the auxiliary time period is represented by K 辅时段 , and the first derivative of the total time period is represented by K 总时段 , K 总时段 , that is, the cloud system generation and development index of the single radar parameter, and the specific calculation formula is as follows:

[0068]

[0069] Wherein, a, b are weight coefficients, t represents the time period number, n represents the time period number of main time period, N represents the total number of time periods, in addition, in order to avoid confusion of each parameter, the first derivative can be distinguished according to the operation time, operation time period and parameter name, for example, the first derivative of each parameter before operation can be expressed as: K 前主时段（参数） , K 前辅时段（参数） and K 前总时段（参数） ; the first derivative of each parameter after operation can be expressed as: K 后主时段（参数） , K 后辅时段（参数） and K 后总时段（参数） . Taking the target cloud block space maximum echo intensity (ZM) as an example, the first derivative before and after operation can be expressed as: K 前主时段（ZM） , K 前辅时段（ZM） , K 前总时段（ZM） , K 后主时段（ZM） , K 后辅时段（ZM） and K 后总时段（ZM） .

[0070] In a specific embodiment, the first derivative of the radar parameter ZM in the main time period, auxiliary time period and total time period per unit time is calculated, taking 1 hour as the unit time (i.e. 1 hour before and after operation) as an example, referring to Figure 5 , Figure 5 is a schematic diagram of the first derivative of the target cloud block space maximum echo intensity in the main time period and auxiliary time period within 1 hour after operation (or before operation) in the specific embodiment of the present application. Taking 6 minutes as a time period, 1 hour is divided into 10 time periods, the main time period after operation is the first 3 time periods of 1 hour after operation (i.e. the first 18 minutes of 1 hour after operation), the main time period after operation is represented by “18 after”, the auxiliary time period after operation is the last 7 time periods of 1 hour after operation (i.e. the last 42 minutes of 1 hour after operation), the auxiliary time period after operation is represented by “42 after”, the main time period before operation is the first 3 time periods of 1 hour before operation (i.e. the first 18 minutes of 1 hour before operation), the main time period before operation is represented by “18 before”, the auxiliary time period before operation is the last 7 time periods of 1 hour before operation (i.e. the last 42 minutes of 1 hour before operation), the auxiliary time period before operation is represented by “42 before”, the first derivative of the main time period and the first derivative of the auxiliary time period before and after operation are calculated by summation, the total time period before and after operation is calculated by weighted summation, therefore, the specific calculation expression is as follows:

[0071] 1. The expression after operation is as follows:

[0072]

[0073] 2. The expression before operation is as follows:

[0074]

[0075] wherein a, b are weight coefficients, t represents the time period number, the main time period includes 3 consecutive time periods, the auxiliary time period includes 7 consecutive time periods, the total number of time periods is 10, the cloud system generation and dissipation development indexes of the maximum echo intensity (ZM) of the target cloud block space before and after the operation are K 后总时段（ZM） and K 前总时段（ZM） .

[0076] In some embodiments, the first-order derivatives of each equal time period of a single radar parameter in the main time period and the auxiliary time period per unit time before and after the operation are respectively averaged to obtain the first-order derivatives of the single radar parameter in the main time period and the auxiliary time period before and after the operation, and then the first-order derivatives of the single radar parameter in the main time period and the auxiliary time period before and after the operation are weighted and summed to obtain the first-order derivative of the single radar parameter in the total time period before and after the operation, i.e. the cloud system generation and dissipation development index of the single radar parameter. The first-order derivative of the main time period is represented by K 主时段 , the first-order derivative of the auxiliary time period is represented by K 辅时段 , and the first-order derivative of the total time period is represented by K 总时段 , K 总时段 , i.e. the cloud system generation and dissipation development index of the single radar parameter. The specific calculation formula is as follows:

[0077]

[0078] wherein a, b are weight coefficients, t represents the time period number, n represents the number of time periods of the main time period, N represents the total number of time periods, in addition, to avoid confusion of each parameter, the first-order derivative can be distinguished according to the operation time, operation time period and parameter name, for example, the first-order derivative before operation of each parameter can be represented as: K 前主时段（参数） , K 前辅时段（参数） and K 前总时段（参数） ; the first-order derivative after operation of each parameter can be represented as: K 后主时段（参数） , K 后辅时段（参数） and K 后总时段（参数） . Taking the maximum echo intensity (ZM) of the target cloud block space as an example, the first-order derivatives before and after operation can be represented as: K 前主时段（ZM） , K 前辅时段（ZM） , K 前总时段（ZM） , K 后主时段（ZM） , K 后辅时段（ZM） and K 后总时段（ZM） .

[0079] In a specific embodiment, the first-order derivatives of the radar parameter ZM in the main time period, the auxiliary time period and the total time period per unit time are calculated, taking 1 hour as the unit time (i.e. 1 hour before and after operation) as an example, referring to Figure 5 , Figure 5is a schematic diagram of the first-order derivative of the maximum echo intensity of the target cloud block space in the main period and the auxiliary period within 1 hour after the operation (or before the operation) in the specific embodiments of the present application. 1 hour is divided into 10 periods with 6 minutes as a period, the main period after the operation is the first 3 periods of 1 hour after the operation (i.e. the first 18 minutes of 1 hour after the operation), the main period after the operation is represented by “after 18”, the auxiliary period after the operation is the last 7 periods of 1 hour after the operation (i.e. the last 42 minutes of 1 hour after the operation), the auxiliary period after the operation is represented by “after 42”, the main period before the operation is the first 3 periods of 1 hour before the operation (i.e. the first 18 minutes of 1 hour before the operation), the main period before the operation is represented by “before 18”, the auxiliary period before the operation is the last 7 periods of 1 hour before the operation (i.e. the last 42 minutes of 1 hour before the operation), the auxiliary period before the operation is represented by “before 42”, the first-order derivative of the main period and the first-order derivative of the auxiliary period before and after the operation are calculated by averaging, and the total period before and after the operation is calculated by weighted summation, therefore, the specific calculation expression is as follows:

[0080] 1. The expression after the operation is as follows:

[0081]

[0082] 2. The expression before the operation is as follows:

[0083]

[0084] Wherein, a, b are weight coefficients, t represents the period number, the main period includes 3 consecutive periods, the auxiliary period includes 7 consecutive periods, the total number of periods is 10, and the cloud system generation and dissipation development index of the target cloud block space maximum echo intensity (ZM) before and after the operation is K 后总时段（ZM） and K 前总时段（ZM） .

[0085] In some embodiments, the cloud system generation and dissipation development index of the multiple radar parameters is calculated by weighted summation based on the cloud system generation and dissipation development index of the single radar parameter, i.e. the first-order derivative of the multiple radar parameters in the total period before and after the operation is calculated by weighted summation, to obtain the cloud system generation and dissipation development index of the target cloud block before and after the operation, the cloud system generation and dissipation development index of the target cloud block before the operation is represented by K 前 , and the cloud system generation and dissipation development index of the target cloud block after the operation is represented by K 后 , and the calculation formula is as follows:

[0086]

[0087] Wherein, a, b, c, d, e, f, g, h, i, j… are weight coefficients, K1, K2, K3, K4, K5, K6, K7, K8, K9, K10 …is the cloud system generation and dissipation development index of each radar parameter before and after the operation.

[0088] In a specific embodiment, the first-order derivatives of the multi-dimensional parameters of the polarization radar in the total period before and after the operation are weighted and summed to obtain the cloud system generation and dissipation development index of the target cloud block before and after the operation, the cloud system generation and dissipation development index of the target cloud block before the operation is represented by K 前 , and the cloud system generation and dissipation development index of the target cloud block after the operation is represented by K 后 , the specific calculation formula is as follows:

[0089]

[0090] wherein a, b, c, d, e, f, g, h, i, j… are weight coefficients.

[0091] In the above embodiments and specific embodiments, the cloud system generation and dissipation development index K 前总时段 of the single radar parameter before the operation, the cloud system generation and dissipation development index K 后总时段 of the single radar parameter after the operation, the cloud system generation and dissipation development index K 前 of the target cloud block before the operation, and the cloud system generation and dissipation development index K 后 of the target cloud block after the operation are all calculated by weighted summation, in the above calculation formulas, in order to prevent individual index values from being too large or too small, the parameter data needs to be processed and each index needs to be assigned a weight, such as the weight coefficients a, b, c… in the above formulas. At the same time, the index values represent the change trend of each index, and the values are positive and negative, so the values of the cloud system generation and dissipation development index K 前 and K 后 of the target cloud block before and after the operation are also positive and negative (positive represents rising, and negative represents falling). The specific processing method and process are as follows:

[0092] 1. Outlier processing (preprocessing)

[0093] Winsorization, replacing the extreme values of each index with the quantile threshold.

[0094] (1) Quantile positioning boundary

[0095] Each index is calculated separately, and the quantile threshold is:

[0096] Lower limit value: L=Q1-k×IQR

[0097] Upper limit value: U=Q3+k×IQR

[0098] Q1: 25% quantile (lower quartile), Q3: 75% quantile (upper quartile)

[0099] IQR = Q3 - Q1 (interquartile range), k: scaling factor (usually 1.5~3);

[0100] (2) Replace the values beyond the boundary with the boundary values.

[0101] 2. Standardization of direction preservation

[0102] Robust Scaling

[0103] Use median and interquartile range (IQR) to retain positive and negative:

[0104] Indicator' = (Indicator - median(Indicator)) / IQR(Indicator), where median represents the median value.

[0105] 3. Contribution cut-off

[0106] Set the upper and lower limits of contribution: ensure that the contribution of a single indicator does not exceed ±3 (adjustable).

[0107] 4. Weight assignment and weighted sum

[0108] Weight design principles:

[0109] The weights wi are all positive numbers (0~1), and ∑wi=1.

[0110] where wi represents the weight coefficient, and the weight coefficient of each indicator in the present application is objectively assigned to each indicator using the entropy weight method (Entropy Weight Method).

[0111] (1) Since there are positive and negative indicators, it is necessary to shift each indicator, and the shift value = |minimum value of indicator| + 0.0001, to avoid the appearance of 0 values;

[0112] (2) Calculate the proportion matrix: calculate the sample proportion (normalized) for each indicator:

[0113] Assuming there are 10 indicators; where i represents different times, j represents different parameters, and P ij represents the sample proportion;

[0114] (3) Calculate the information entropy of each indicator

[0115] ; where x ij represents the multi-dimensional parameters of different polarization radars;

[0116] (4) Calculate the information utility value

[0117] ;

[0118] (5) Calculate weight

[0119] .

[0120] Refer to Figure 6 , Figure 6 is a schematic diagram of a kind of artificial hail prevention effect judgment standard in the embodiment of the application, in some embodiments of the step S4, the cloud system life and death development index K of the target cloud block before operation 前 And the cloud system life and death development index K of the target cloud block after operation 后 It is compared to judge whether the operation result is effective, and the judgment standard is: when K 前 >K 后 , the operation result is effective; when K 前 ≤K 后 , the operation result is invalid.

[0121] Refer to Figure 7 , Figure 7is a flow chart of an artificial hail prevention effect evaluation device in an embodiment of the present application, in some embodiments, the artificial hail prevention effect evaluation device comprises: a target cloud block space-time matching module, a target cloud block tracking module, a parameter change rate calculation module, and a comprehensive effect evaluation module. The target cloud block space-time matching module is specifically configured to: match the closest radar data based on the operation time; mark the radar data reference point with the longitude and latitude of the operation site; divide a target cloud block of 10x10 km to 30x30 km along the direction of the operation azimuth angle from the radar data reference point as the starting point, extending 5-15 km to the left and right; and determine the reference position of the target cloud block based on the divided target cloud block. The target cloud block tracking module is specifically configured to: determine the target cloud block reference point according to the target cloud block reference position; search for similar cloud blocks in a unit time before and after the operation based on the target cloud block reference point, and the minimum value of the unit time is in the range of 3-6 minutes; perform a set of parallel calculations on the radar combined reflectivity of each similar cloud block by using a computer vision algorithm for multi-target tracking, a linear algorithm for measuring the linear relationship between continuous variables, and an image quality evaluation index for evaluating the difference or similarity between signals; perform summation operation on each set of parallel calculation results; compare the results of the summation operation to filter out the summation maximum value before the operation and the summation maximum value after the operation; determine the radar combined reflectivity corresponding to the maximum value as the derived echo of the target cloud block, thereby filtering out the target cloud block before the operation and the target cloud block after the operation. The parameter change rate calculation module is specifically configured to: uniformly divide the unit time before and after the operation into a plurality of equal time periods; calculate the change rate of each single radar parameter in the equal time periods before and after the operation; uniformly divide the unit time before and after the operation into a time-continuous main time period and an auxiliary time period based on the plurality of equal time periods before and after the operation; perform summation calculation or average calculation on the change rate of each single radar parameter in the equal time periods in the main time period and the auxiliary time period before and after the operation to obtain the change rate of each single radar parameter in the main time period and the auxiliary time period before and after the operation; perform weighted summation calculation on the change rate of each single radar parameter in the main time period and the auxiliary time period before and after the operation to obtain the change rate of each single radar parameter in the total time period before and after the operation, i.e., the cloud system generation and dissipation development index of each single radar parameter before and after the operation; and perform weighted summation calculation on the cloud system generation and dissipation development indexes of the plurality of radar parameters before and after the operation based on the cloud system generation and dissipation development indexes of each single radar parameter before and after the operation to obtain the cloud system generation and dissipation development index of the target cloud block before and after the operation. The comprehensive effect evaluation module is configured to: compare the cloud system generation and dissipation development indexes of the target cloud block before and after the operation to determine whether the operation result is effective, and the determination standard is that the operation result is effective when the cloud system generation and dissipation development index of the target cloud block before the operation is greater than the cloud system generation and dissipation development index of the target cloud block after the operation, otherwise the operation result is ineffective.

[0122] For the principles, specific implementations, and beneficial effects of the device, please refer to the foregoing and Figures 1 to 7The description of the artificial hail prevention effect evaluation method is shown, and will not be repeated here.

[0123] The application further provides a terminal device, comprising a memory, a processor and a program stored in the memory and executable on the processor, and the processor implements the method described above and the method described below when executing the program. Figures 1 to 7 The steps of the artificial hail prevention effect evaluation method are shown. The terminal device can include, but is not limited to, a mobile phone, a computer, a tablet computer and other terminals, and can also be a server, a cloud platform and the like.

[0124] Specifically, in the embodiment of the application, the processor can be a central processing unit (CPU), and the processor can also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0125] It should also be understood that the memory in the embodiments of the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM) or a flash memory, etc. The volatile memory can be a random access memory (RAM) or the like, which is used as an external cache. By way of example but not limitation, many forms of random access memory (RAM) are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct rambus RAM (DR RAM), etc.

[0126] The present application also provides a storage medium storing a program for executing the artificial hail prevention effect evaluation method described above. The program is executed by a processor to perform the steps of the artificial hail prevention effect evaluation method described above and Figures 1 to 7 The steps of the artificial hail prevention effect evaluation method shown. The storage medium can include a non-volatile or non-transitory memory, and can also include an optical disk, a mechanical hard disk, a solid state disk, etc.

[0127] It should be understood that the term "and / or" in this document is merely used to describe associated objects, for example, A and / or B indicates that there can be three relationships, specifically, A alone, A and B together, and B alone; for another example, A and / or B and / or C indicates that there can be eight relationships, specifically, A alone, B alone, C alone, A and B together, A and C together, B and C together, A and B and C together, and A and B and C do not exist together. In addition, the character " / " in this document represents an "or" relationship between the associated objects.

[0128] "Multiple" appearing in the embodiments of the present application means two or more.

[0129] It should be noted that the serial numbers of the steps in the embodiments do not represent the limitation of the execution order of the steps.

[0130] It should be understood that the above specific embodiments of the present application are only used for illustrative or explanatory purposes of the principles of the present application, and do not constitute a limitation of the present application. Therefore, any modification, equivalent replacement, improvement, etc. made without departing from the spirit and scope of the present application shall be included in the protection scope of the present application. In addition, the claims of the present application are intended to cover all changes and modifications falling within the scope and boundary of the appended claims, or the equivalent forms of such scope and boundary.

Claims

1. A method for evaluating the effectiveness of artificial hail suppression, characterized by, The method comprises the following steps: Step S1, matching radar data based on operation information to divide target cloud blocks; Step S2, searching for similar cloud blocks in unit time before and after operation, and calculating radar combined reflectivity of the similar cloud blocks to screen out target cloud blocks before and after operation; Step S3, calculating the change rate of radar parameters in unit time before and after operation based on the target cloud blocks before and after operation to obtain cloud system generation and dissipation development indexes of the target cloud blocks before and after operation; Step S4, comparing the cloud system generation and dissipation development indexes of the target cloud blocks before and after operation to determine whether the operation result is effective, and the judgment standard is that when the cloud system generation and dissipation development index of the target cloud block before operation is greater than that of the target cloud block after operation, the operation result is effective, otherwise the operation result is ineffective; The step S2 comprises: Step S21, determining a target cloud block reference point according to a target cloud block reference position; Step S22, searching for similar cloud blocks in unit time before and after operation based on the target cloud block reference point, and the minimum value of the unit time is 3-6 minutes; Step S23, performing a set of parallel calculations on the radar combined reflectivity of each similar cloud block by using a computer vision algorithm for multi-target tracking, a linear algorithm for measuring linear relationship between continuous variables, and an image quality evaluation index for evaluating differences or similarities between signals; Step S24, performing summation operation on each set of parallel calculation results; Step S25, comparing the results of the summation operation to screen out summation maximum values before and after operation; Step S26, determining radar combined reflectivity corresponding to the maximum values as derived echoes of the target cloud blocks, thereby screening out the target cloud blocks before and after operation.

2. The artificial hail suppression effect evaluation method according to claim 1, wherein The step S1 comprises: Step S11, matching the closest radar data based on operation time; Step S12, marking a radar data reference point by using the longitude and latitude of the operation site; Step S13, dividing a target cloud block of 10x10 km to 30x30 km in size from the radar data reference point as a starting point, extending 5-15 km to the left and right, and along the operation azimuth direction; Step S14, determining the reference position of the divided target cloud block.

3. The artificial hail suppression effect evaluation method according to claim 1, wherein The step S3 comprises: Step S31, uniformly dividing unit time before and after operation into multiple equal time periods; Step S32, calculating the change rate of each single radar parameter in the equal time periods before and after operation; Step S33, uniformly dividing unit time before and after operation into time-continuous main time periods and auxiliary time periods based on the multiple equal time periods before and after operation; Step S34, performing summation calculation or average calculation on the change rate of each single radar parameter in the equal time periods in the main time periods and the auxiliary time periods before and after operation to obtain the change rate of each single radar parameter in the main time periods and the auxiliary time periods before and after operation, and performing weighted summation calculation on the change rate of each single radar parameter in the main time periods and the auxiliary time periods before and after operation to obtain the change rate of each single radar parameter in the total time periods before and after operation, i.e., the cloud system generation and dissipation development index of each single radar parameter before and after operation. In step S35, the cloud system generation and disappearance development indexes of the target cloud blocks before and after the operation are calculated by weighted summation of the cloud system generation and disappearance development indexes of the multiple radar parameters before and after the operation.

4. The artificial hail suppression effect evaluation method according to any one of claims 1 to 3, wherein, The radar parameters include: target cloud block spatial maximum echo intensity, strong echo top height, strong echo proportion, echo centroid, hail particle distribution maximum height, hail particle proportion, graupel particle distribution maximum height, graupel particle proportion, radar estimated rainfall, and strong echo vertical dispersion.

5. An artificial hail suppression effect evaluation device characterized by comprising: The method comprises: a target cloud block space-time matching module that matches radar data according to operation information and divides target cloud blocks; a target cloud block tracking module that searches for similar cloud blocks in unit time before and after the operation, calculates radar combined reflectivity of the similar cloud blocks, and filters out target cloud blocks before and after the operation; a parameter change rate calculation module that calculates the change rate of radar parameters in unit time sequence before and after the operation based on the target cloud blocks before and after the operation, and obtains cloud system generation and disappearance development indexes of the target cloud blocks before and after the operation; a comprehensive effect evaluation module that compares the cloud system generation and disappearance development indexes of the target cloud blocks before and after the operation, and judges whether the operation result is effective, with the judgment standard being: when the cloud system generation and disappearance development index of the target cloud block before the operation is greater than that of the target cloud block after the operation, the operation result is effective, otherwise the operation result is ineffective. The target cloud block tracking module is specifically configured to: determine a target cloud block reference point according to a target cloud block reference position; search for similar cloud blocks in unit time before and after the operation based on the target cloud block reference point, with the minimum value of the unit time being in the range of 3-6 minutes; perform a set of parallel calculations on radar combined reflectivity of each similar cloud block by using a computer vision algorithm for multi-target tracking, a linear algorithm for measuring linear relationship between continuous variables, and an image quality evaluation index for evaluating differences or similarities between signals; perform summation operation on each set of parallel calculation results; compare the results of the summation operation to filter out summation maximum values before and after the operation; determine radar combined reflectivity corresponding to the maximum values as derived echoes of the target cloud block, thereby filtering out the target cloud block before the operation and the target cloud block after the operation.

6. The artificial hail suppression effect evaluation device according to claim 5, wherein The target cloud block space-time matching module is specifically configured to: match the closest radar data based on operation time; label radar data reference points with operation site latitude and longitude; divide target cloud blocks of 10x10 km to 30x30 km along the operation azimuth direction from the radar data reference points as starting points, extending 5-15 km to the left and right; determine reference positions of the divided target cloud blocks.

7. The artificial hail suppression effect evaluation device according to claim 5, wherein The parameter change rate calculation module is specifically configured to: divide unit time before and after the operation into multiple equal time periods according to a unified standard; calculate the change rate of a single radar parameter in each equal time period before and after the operation; unify unit time before and after the operation into a main time period and an auxiliary time period in time sequence based on the multiple equal time periods before and after the operation. The change rates of the single radar parameter in each equal time period of the main time period and the auxiliary time period before and after the operation are summed or averaged to obtain the change rates of the single radar parameter in the main time period and the auxiliary time period before and after the operation; the change rates of the single radar parameter in the main time period and the auxiliary time period before and after the operation are weighted and summed to obtain the change rate of the single radar parameter in the total time period before and after the operation, that is, the cloud system generation and disappearance development index of the single radar parameter before and after the operation; Based on the cloud system generation and disappearance development index of the single radar parameter before and after the operation, the cloud system generation and disappearance development indexes of multiple radar parameters before and after the operation are weighted and summed to obtain the cloud system generation and disappearance development index of the target cloud block before and after the operation.

8. A terminal device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that, The processor implements the steps of the artificial hail prevention effect evaluation method in any one of claims 1 to 4 when executing the program.

9. A storage medium, characterized by The storage medium stores a program, and the program is executed by the processor to implement the steps of the artificial hail prevention effect evaluation method in any one of claims 1 to 4.

Images