Method and system for hail prevention operation based on convective cell hazard index and hail discrimination

Abstract

The application discloses a hail prevention operation method and system based on a convection cell hazard index and hail identification, and relates to the technical field of weather monitoring and artificial weather modification command operation. The method is based on multi-source observation such as weather radar and sounding, establishes a strong convection cell hazard model and a hail identification model, identifies the type of each strong convection cell in the hail identification model by combining two segment score thresholds, and determines the development stage corresponding to the strong convection cell. According to the identification type and stage of the strong convection cell, a segmented operation strategy is constructed, a task allocation mechanism for multiple convection cells and multiple operation points is established, and an element method for calculating cannonball launching parameters is established. The application provides a precise operation process for hail prevention command, reduces human intervention in hail prevention operation, and improves the efficiency and accuracy of decision execution.

Description

Technical Field

[0001] This invention relates to the field of meteorological monitoring and weather modification command and control technology, and in particular to a hail suppression operation method and system based on convective cell hazard index and hail identification. Background Technology

[0002] Artificial hail suppression is a complex and delicate task, with hail identification and suppression being the two key aspects. The principle of artificial hail suppression mainly involves using artillery, rockets, and other tools to deliver silver iodide as artificial ice nuclei into appropriate parts of the hail cloud, forming artificial hail embryos. These artificial hail embryos compete with naturally occurring hail embryos for the limited supercooled water in the cloud, thereby inhibiting the formation of larger hailstones. Artificial hail suppression operations, primarily using artillery and rockets, are an important measure to mitigate the impact of hail disasters.

[0003] Hail identification is fundamental to hail prevention. Hail is characterized by its suddenness, instantaneousness, and locality, making it a key focus and challenge in short-term nowcasting and early warning. The life cycle of a hail cloud includes three stages: formation and development, mature hailfall, and dissipation. Hail occurs in environments below 0 degrees Celsius or lower. Ice crystals mainly grow in ambient temperatures between -7°C and -20°C, forming hail embryos. Large hailstones may form in areas where the altitude corresponding to the -20°C isotherm exceeds the altitude corresponding to the radar reflectivity factor of 45 dBZ. Currently, there is considerable theoretical research on identifying large hailstones, such as the presence of high-hanging strong and weak echo zones on the vertical structure of single-polarization radar, strong hail indexes exceeding 80%, and differential reflectivity values ​​and low correlation coefficients corresponding to strong reflectivity factors close to 0 in dual-polarization radar. However, the observation of heavy precipitation before strong hailstones hit the ground and the formation of small hailstones from weak hailstone clouds both affect crop growth and fruit quality. Therefore, methods for identifying small hailstones are also crucial for hail prevention.

[0004] Field trials of hail suppression revealed that the rapid development of hail clouds from ordinary convective cells necessitates swift decision-making by operational teams when facing rapidly developing multi-cell storms. This involves determining whether and how hail suppression operations should be conducted. Currently, in terms of operational conditions, artificial hail suppression decision-making and command systems primarily utilize historical meteorological data and weather radar technology. Through analysis of radar characteristic parameters, particularly statistical analysis of echo cloud area and intensity, automatic tracking and analysis of hail clouds are achieved, providing a scientific basis for hail suppression operations. For example, Chinese patent application CN202111339839.4 provides a method for directing artificial hail suppression operations based on dual-polarization weather radar, including: S1, data entry and preprocessing, wherein horizontal polarization reflectivity factor, differential reflectivity factor, differential propagation phase shift, cross-correlation coefficient of zero hysteresis of horizontal and vertical polarization echo power, and ambient temperature are selected as judgment parameters, and the above parameter data detected by polarization radar are entered in real time, and the preprocessing of all parameters is performed by attenuation correction using polarization parameters; S2, data quality control; S3, identification of water condensate phase state using fuzzy logic element method, wherein hail is identified by fuzzy logic method, and the echo characteristics of hail in the early stage of hail, such as graupel particles formed before hail formation, are detected before hail formation; S4, strategy judgment, giving the best time for artificial hail suppression operations according to the judgment strategy, and combining the shot point information to convert it into accurate information that can be used for artificial weather modification operations; S5, production and release of hail suppression operation information. The aforementioned scheme utilizes dual-polarization weather radar information, combined with the microphysical characteristics of hail formation in hail clouds, to determine the timing and location of early-stage hail suppression operations. It also provides intelligent real-time audio-visual alerts to avoid delays and improve the efficiency of hail suppression command. However, this scheme relies primarily on polarization radar data for hail identification, which cannot determine the development and changes of hail clouds. Its ability to detect and identify rapidly evolving, strong convective hail weather processes is far from sufficient, hindering high-precision hail suppression operations. Hail clouds develop and change rapidly, and the opportunity for hail suppression is fleeting. The effectiveness of hail suppression depends heavily on accurate timing and conditions; ensuring the orderly and efficient implementation of hail suppression measures is both crucial and challenging for hail suppression operations.

[0005] On the other hand, existing technologies provide some solutions for refined observation of severe convective targets. For example, Chinese patent ZL201910641616.X discloses a networked X-band weather radar cooperative adaptive control method, which can better achieve rapid tracking and early warning of severe convective weather. Based on this solution, Chinese patent application CN202310834165.8 also discloses a networked X-band radar cooperative observation method for severe convective cells. When a severe convective region is detected, it can perform severe convective cell segmentation based on the severe convective region. If multiple severe convective cells are obtained, the hazard level of each severe convective cell is determined according to its corresponding target characteristic quantity. Based on the hazard level of each severe convective cell, the distance between the centroid of each severe convective cell and the X-band radar in the radar network framework, and the vertical expansion of each severe convective cell, corresponding scanning tasks are assigned to each X-band radar in the radar network framework. The scanning tasks include volume scanning tasks and vertical scanning tasks. Building upon the aforementioned approach, Chinese patent ZL202410446117.6 discloses a multi-band radar adaptive cooperative observation method for convective processes. This method focuses on hail and short-duration heavy precipitation, and studies an intelligent cooperative tracking algorithm for highly hazardous single-cell targets in strong convection. Specifically, it introduces a comprehensive disaster-causing index to evaluate the hazard of strong convective cells, and after ranking storm cells by strength based on key areas and the comprehensive disaster-causing index, uniformly allocates radar observation task priorities. Furthermore, it introduces storm cell prediction, configuring different scanning strategies for predicted hail and precipitation. This approach can accurately identify and segment each strong convective cell in the context of rapidly developing multi-cell storms, extract hazardous weather characteristic parameters based on the strong convective cells, and calculate the comprehensive disaster-causing index (or hazard index) for each strong convective cell. Then, based on hail weather forecast judgment conditions and the comprehensive disaster-causing index score, it predicts the weather type (whether hail will form) of the strong convective cell.

[0006] Based on the requirements of precise hail suppression operations, this invention further improves the above-mentioned convective cell hazard index scoring and hail identification technology, and proposes a hail suppression operation scheme based on convective cell hazard index and hail identification. Summary of the Invention

[0007] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a hail suppression operation method and system based on the convective cell hazard index and hail identification. This invention is based on a strong convective cell hazard model and a hail identification model. In the hail identification model, two score thresholds are combined to identify the type of each strong convective cell and determine the corresponding stage. Based on the identified type and stage of the strong convective cell, a segmented operation strategy is constructed, realizing task allocation for multiple convective cells and multiple operation points. This invention provides a precise operation process for hail suppression command, reducing human intervention in hail suppression operations and improving the efficiency and accuracy of decision-making execution.

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] A hail suppression operation method based on convective cell hazard index and hail identification includes the following steps:

[0010] After segmenting all strong convective cells within the observation area, the hazard index RSIK of each strong convective cell is calculated; and, after determining the corresponding hazard model information of strong convective cells based on the local hail occurrence conditions, the hazard index scores corresponding to hail identification indicators and hail pre-landing indicators are determined based on the strong convective cell hazard model.

[0011] Hail identification is performed on severe convective cells using a hail identification model. The hail identification model is configured to: determine two score thresholds for hail identification based on the hazard index scores corresponding to the aforementioned two indicators; and, based on the segmentation information of the severe convective cell and the hazard index RSIK, combined with the two score thresholds and the temperature profile of the radiosonde, identify the type of each severe convective cell and determine the stage corresponding to the severe convective cell.

[0012] Based on the identification type and corresponding stage of the severe convective cells, hail suppression strategies are configured for each severe convective cell to form a segmented hail suppression strategy.

[0013] Furthermore, the hazard index scores corresponding to the hail identification index and the hail pre-landing index are related to the weighting coefficients w1, w2, and w3 of the network reflectivity, network vertical liquid water content (VIL), and network hail index (POSH). After obtaining the local hail occurrence condition ratio data, the ratio of the aforementioned weighting coefficients w1, w2, and w3 is determined according to the local hail occurrence condition ratio. Different ratios correspond to different strong convective cell hazard model information.

[0014] After determining the ratio, the hazard model information of the strong convective cells corresponding to the ratio is obtained. Then, the hazard index score corresponding to each index is obtained according to the set hail identification index and hail pre-landing index. The hazard index score corresponding to the hail identification index is set as the first score threshold, and the hazard index score corresponding to the hail pre-landing index is set as the second score threshold.

[0015] Furthermore, before calculating the hazard index RSIK of a strongly convective cell, the following steps are also included:

[0016] Obtain the segmentation information of convective cells, and obtain the area S of the high threshold boundary segmentation of strong convective cells based on the set high reflectivity threshold;

[0017] Determine whether the area S exceeds a preset area threshold. If the area S is less than or equal to the area threshold, it is determined that the RSIK score of the strong convection cell is zero. If the area S exceeds the area threshold, it is determined that the convection cell is generated and the RSIK score of the strong convection cell is zero. Calculate the RSIK value of the strong convection cell.

[0018] Furthermore, the steps for calculating the RSIK value of a strongly convective cell are as follows:

[0019] Based on the maximum network reflectivity of strong convective cells, the vertical liquid water content of the network, and the strong hail index, a normalized model is established by combining the statistical analysis results of the storm spatial distribution and parameter characteristics of local convection.

[0020] Let the hazard index of the Kth strong convective cell be RSIK. K RSIK K The normalization calculation formula is as follows:

[0021]

[0022] Where K is a natural number greater than or equal to 1;

[0023] Z K Represents the network reflectivity of the Kth strong convective cell, max(Z K () represents the maximum reflectivity of the Kth strongly convective cell;

[0024] VIL K This represents the liquid water content of the Kth strongly convective monomer, max(VIL). K ) represents the maximum vertical liquid water content of the Kth strongly convective cell;

[0025] POSH represents the network hail index of this strong convective cell. The value range of POSH is greater than or equal to 0 and less than or equal to 1, i.e., [0, 1]. Specifically, after segmenting each strong convective cell, the maximum height and reflectivity of each strong convective cell are identified, and the POSH is obtained by combining the temperature profile of the radiosonde.

[0026] ref(Z K ) and ref(VIL K ) represent the local reference values ​​of the network reflectivity and vertical liquid water content of the region where the Kth strong convective cell is located;

[0027] w i This represents the weighting coefficients, i = 1, 2, 3, w1 + w2 + w3 = 1.

[0028] Furthermore, the strong convective cell is configured to include five types: no-risk type, ordinary precipitation HR type, heavy precipitation HR type, suspected hail HI type, and hail HI type, which correspond to the RSIK no score stage, convective cell development stage, possible development into hail cloud stage, hail cloud development stage, and hail cloud development and landing stage, respectively.

[0029] Furthermore, the hail identification model is configured to identify the type of each strong convective cell through the following steps:

[0030] For strong convective cells with no RSIK score, the cell is determined to be of no risk type.

[0031] For strong convective cells with hazard index scores, a secondary screening is performed based on two determined score thresholds S1 and S2, as follows:

[0032] The severity index (RSIK) of a severe convective cell is compared with the fractional thresholds S1 and S2. If the RSIK does not reach the first fractional threshold S1 (RSIK < S1), it is identified as ordinary precipitation (HR type). If the RSIK reaches the second fractional threshold S2 (RSIK ≥ S2), it is identified as hail (HI type). If the RSIK reaches the first fractional threshold S1 but not the second fractional threshold S2 (S1 ≤ RSIK < S2), it enters the third screening stage, as follows:

[0033] Determine whether the height of the high reflectivity threshold of a strong convective cell exceeds the height corresponding to -20° radiosonde; if the height of the high reflectivity threshold does not exceed the height corresponding to -20° radiosonde, it is identified as heavy precipitation (HR type); if the height of the high reflectivity threshold exceeds the height corresponding to -20° radiosonde, it is identified as suspected hail (HI type).

[0034] Furthermore, based on the identified type and corresponding stage of the severe convective cells, the steps for configuring hail suppression strategies for each severe convective cell include:

[0035] For strong convective cells with RSIK scores, obtain the following parameters for each strong convective cell: RSIK score of the convective cell hazard index, latitude and longitude of the core location of the convective cell, identification type of the convective cell, maximum height of the high reflectivity threshold of the convective cell, and range of the convective cell.

[0036] Locate hail suppression operation points within a preset radius of the core location of each severe convective cell; rank the operation points in order of proximity to the core location of the convective cell to form a list of operation points.

[0037] Based on the type and stage of the severe convective cell, hail suppression operation points and operation parameters are matched within the range of the severe convective cell. Among them, the distance between the two points and the azimuth angle θ of the hail suppression operation point towards the cell core are calculated by using the latitude and longitude of the core point of the severe convective cell and the latitude and longitude of the matched hail suppression operation point; and the elevation angle of the operation point is calculated based on the distance between the two points and the maximum height of the high reflectivity threshold, thus forming the operation parameters of the hail suppression operation.

[0038] Furthermore, the steps for determining the hail suppression operation points and parameters within the matching range of a strong convective cell are as follows:

[0039] For strong convection units identified as HR, trigger single-point operations;

[0040] For severe convective cells of the ordinary precipitation type, the first operational strategy is adopted as follows: Initiate weather modification operations, match the nearest operational point, calculate the azimuth angle of the anti-aircraft gun at the operational point based on the latitude and longitude of the severe convective cell core and the latitude and longitude of the operational point, calculate the elevation angle of the weather modification operational point based on the height and range of the high reflectivity threshold, and then carry out single-point operations; continuously monitor the development of the convective cell, and dynamically adjust the operational parameters based on the updated observation data and forecast results until the RSIK score is zero;

[0041] For severe convective cells with heavy precipitation, the second operational strategy is adopted as follows: Initiate weather modification operations, match the nearest operational point, calculate the azimuth of the anti-aircraft gun at the operational point based on the latitude and longitude of the severe convective cell's core and the operational point's latitude and longitude, and calculate the elevation angle of the weather modification operational point based on the height and range of the high reflectivity threshold; after the operation is completed, recalculate the hazard index RSIK of the severe convective cell, compare the new hazard index RSIK with the score threshold S1, if RSIK > S1, it is determined that the number of shells needs to be increased, and the secondary anti-aircraft gun operation parameters are configured, and single-point operations continue to be performed until RSIK < S1 after the operation, that is, when it is identified as ordinary precipitation HR, the operation strategy corresponding to ordinary precipitation is implemented until RSIK has no score;

[0042] For strong convection cells identified as HI, trigger multi-point joint operations;

[0043] For severe convective cells suspected of being hail-type, a third operational strategy is adopted, as follows: Initiate weather modification operations, matching at least two operational points. Calculate the azimuth of anti-aircraft artillery firing at each operational point based on the core latitude and longitude of the severe convective cell and the latitude and longitude of each operational point. Calculate the elevation angle of the operational points based on the height and range of the high reflectivity threshold. After this operation is completed, re-identify the type of the severe convective cell. If it is identified as precipitation (HR) type, adjust to single-point operation, executing the corresponding operational strategy based on whether it is ordinary or heavy precipitation. Otherwise, it is determined that the number of shells needs to be increased, and secondary anti-aircraft artillery operation parameters need to be configured. Continue multi-point operation until it is identified as precipitation (HR) type; and so on, until RSIK scores are zero.

[0044] For severe convective cells of the hail type, corresponding to the mature stage of hail cloud development, the fourth operational strategy is implemented as follows: Initiate weather modification operations, match all operational points, calculate the azimuth angle for firing anti-aircraft guns at each operational point based on the core latitude and longitude of the severe convective cell and the latitude and longitude of each operational point, and calculate the elevation angle of the weather modification operational point based on the height and range of the high reflectivity threshold; after this operation is completed, recalculate the hazard index RSIK of the severe convective cell, compare the new hazard index RSIK with the score thresholds S1 and S2, when RSIK ≥ S2, it is determined that the number of shells needs to be increased, and the secondary anti-aircraft gun operation parameters are configured, and the joint operation strategy for all points continues to be implemented until S1 ≤ RSIK < S2 after the operation, and the third operational strategy is implemented; and so on, until RSIK has no score.

[0045] Furthermore, the steps for calculating the elevation angle β of the multitude operation point and the azimuth angle θ of the anti-aircraft gun launched from the operation point are as follows:

[0046] Based on the latitude and longitude coordinates (λ1, φ1) of the core of the strong convective cell and the latitude and longitude coordinates (λ2, φ2) of the work site, the spherical distance d between the two points is calculated using the formula d = R·c, where,

[0047]

[0048] φ1 and φ2 are the latitudes of the two points, in radians;

[0049] λ1 and λ2 are the longitudes of the two points, in radians;

[0050] Δφ is the difference in latitude between two points: Δφ = φ2 - φ1;

[0051] Δλ is the difference in longitude between two points: Δλ = λ2 - λ1;

[0052] R is the radius of the Earth, usually taken as 6371 kilometers;

[0053] Based on the aforementioned spherical distance d, calculate the elevation angle β of the shadow manipulation point. The formula is β = tan -1 (H / d),

[0054] Where d is the spherical distance between the two points, and H is the maximum height of the high threshold of reflectivity of the convective cell;

[0055] The formula for calculating the azimuth angle θ is as follows:

[0056]

[0057] Furthermore, it also includes the network data fusion step and the flow unit segmentation step;

[0058] In the network data fusion step, data from multiple weather radars covering the observation area are collected, and after quality control and coordinate transformation, network fusion products are obtained.

[0059] In the convective cell segmentation step, based on the aforementioned network fusion product and the network reflectivity, a dual threshold method is used to identify and segment all strong convective cells within the observation area to obtain one or more strong convective cells.

[0060] When calculating the hazard index of a severe convective cell, the hazardous weather characteristic parameters of each severe convective cell are first extracted, and the hazard index of each severe convective cell is calculated based on the extracted hazardous weather characteristic parameters. The characteristic parameters related to the comprehensive disaster index include single / multi-layer network reflectivity, network vertical liquid water content (VIL), and network hail index (POSH).

[0061] Furthermore, it also includes a hail suppression effectiveness assessment step, including: after hail suppression operations, using the severe convective cell hazard model and hail identification model to identify hail on the severe convective cells after the operations in order to assess the effectiveness of the hail suppression operations;

[0062] And / or, after the hail suppression operation is completed, the meteorological data before and after the hail suppression operation are compared with the actual disaster information to assess the effectiveness of the hail suppression operation, and the hail suppression operation strategy is optimized based on the feedback assessment results.

[0063] The present invention also provides a hail suppression system, including a hail detection module and a hail suppression module;

[0064] The hail identification module is used to: segment all strong convective cells within the observation area and calculate the hazard index (RSIK) for each strong convective cell; determine the corresponding hazard model information for strong convective cells based on the local hail occurrence conditions, and determine the hazard index scores corresponding to hail identification indicators and pre-landing hail indicators based on the strong convective cell hazard model; identify strong convective cells using a hail identification model, which is configured to: determine two score thresholds for hail identification based on the hazard index scores corresponding to the aforementioned two indicators; and identify the type of each strong convective cell and determine the stage corresponding to the strong convective cell based on the segmentation information and hazard index (RSIK) of the strong convective cells, combined with the two score thresholds and the temperature profile of the radiosonde.

[0065] The hail suppression module is used to: receive the identification results from the hail identification module, and configure hail suppression operation strategies for each strong convective cell according to the identification type and corresponding stage of the strong convective cell to form a segmented hail suppression operation strategy.

[0066] Compared with existing technologies, this invention, by employing the above technical solutions, has the following advantages and positive effects: Based on a severe convective cell hazard model and a hail identification model, the hail identification model combines two score thresholds to identify the type of each severe convective cell and determine its corresponding stage. A segmented operation strategy is constructed based on the identified type and stage of the severe convective cell, enabling task allocation for multiple convective cells and multiple operation points. This invention provides a precise operation process for hail suppression command, reducing human intervention in hail suppression operations and improving the efficiency and accuracy of decision execution. Thus, in the face of rapidly developing multi-cell storms, the solution provided by this invention allows the operation team to quickly make hail suppression operation decisions.

[0067] Furthermore, based on the development of convective cells and combined with the latest observation data and forecast results, operational plans can be dynamically adjusted—for example, whether to add additional operations, such as increasing the number of hail suppression shells fired, or whether multiple operation points need to be coordinated. This ensures that hail suppression operations can adapt to weather changes in a timely manner.

[0068] Furthermore, after the hail suppression operation is completed, the effectiveness of the operation can be evaluated, and the hail suppression strategy can be optimized based on the evaluation results, thereby improving the accuracy and scientific nature of future decision-making. Attached Figure Description

[0069] Figure 1 A flowchart illustrating the hail suppression operation method based on convective cell hazard index and hail identification provided in this embodiment of the invention.

[0070] Figure 2The five identification types and stage diagrams formed by three screenings are provided for embodiments of the present invention.

[0071] Figure 3 This is a flowchart illustrating how a hail suppression strategy is configured for each severe convective cell based on its identification type and corresponding stage, as provided in an embodiment of the present invention.

[0072] Figure 4 This is a schematic diagram illustrating the calculation of the elevation angle β of the shadowing operation point, provided in an embodiment of the present invention. Detailed Implementation

[0073] The hail suppression method and system based on convective cell hazard index and hail identification disclosed in this invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that the technical features or combinations of technical features described in the following embodiments should not be considered isolated; they can be combined to achieve better technical effects. In the accompanying drawings of the following embodiments, the same reference numerals in each drawing represent the same features or components, which can be applied to different embodiments. Therefore, once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0074] It should be noted that the structures, proportions, sizes, etc., illustrated in the accompanying drawings are merely for illustrative purposes and to aid those skilled in the art in understanding and reading the invention. They are not intended to limit the conditions under which the invention can be implemented. Any modifications to the structure, changes in proportions, or adjustments to size, provided they do not affect the effectiveness or purpose of the invention, should fall within the scope of the technical content disclosed in the invention. The scope of the preferred embodiments of the present invention includes other implementations, wherein functions may be performed not in the order stated or discussed, including substantially simultaneously or in reverse order, depending on the functions involved. This should be understood by those skilled in the art to which the embodiments of the present invention pertain.

[0075] Techniques, methods, and apparatus known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and apparatus should be considered part of the specification. In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0076] Example

[0077] Based on the requirements of precise hail suppression operations, this invention further improves the convective cell hazard index scoring technology and hail identification technology disclosed in Chinese Patent ZL202410446117.6, and proposes this hail suppression operation scheme. This invention establishes a segmented hail suppression operation strategy based on models and thresholds, realizing task allocation for multiple convective cells and multiple operation points.

[0078] Specifically, this embodiment provides a hail suppression method based on convective cell hazard index and hail identification, including the following steps: First, after segmenting the strong convective cells within the observation area, the hazard index (RSIK) of each strong convective cell is calculated; then, after determining the corresponding strong convective cell hazard model information according to the local hail occurrence conditions, the hazard index scores corresponding to hail identification indicators and pre-landing hail indicators are determined based on the strong convective cell hazard model. Then, hail identification is performed on the strong convective cells using a hail identification model, which is configured to: determine two score thresholds for hail identification based on the hazard index scores corresponding to the aforementioned two indicators; and, based on the segmentation information of the strong convective cells and the hazard index (RSIK), combined with the two score thresholds and the temperature profile of the radiosonde, the type of each strong convective cell is identified, and the stage corresponding to that strong convective cell is determined. Subsequently, based on the identification type and corresponding stage of the severe convective cells, hail suppression operation strategies are configured for each severe convective cell; among them, different operation strategies are corresponding to severe convective cells at different stages to form a segmented hail suppression operation strategy.

[0079] This embodiment analyzes hail occurrence using two indicators: hail identification indicators and hail pre-landing indicators.

[0080] The hazard index scores corresponding to the hail identification indicators and pre-landing hail indicators are related to the weighting coefficients w1, w2, and w3 of three factors: network reflectivity, network vertical liquid water content (VIL), and network hail index (POSH). In practice, local hail occurrence condition data can be obtained first, and then the weighting ratios of the aforementioned weighting coefficients w1, w2, and w3 can be determined based on these local hail occurrence condition data. Different ratios correspond to different hazard model information for strong convective cells.

[0081] After determining the weighting coefficients w1, w2, and w3 of the three elements and obtaining the strong convective cell hazard model information corresponding to this ratio, the hazard index scores corresponding to the hail identification index and the hail-before-landing index can be obtained from the aforementioned hazard model information based on the set hail identification index and the hail-before-landing index. Then, the hazard index score corresponding to the hail identification index is set as the first score threshold, and the hazard index score corresponding to the hail-before-landing index is set as the second score threshold. In this way, two score thresholds for hail identification are determined.

[0082] In this embodiment, the severe convective cell hazard model is used to analyze the parameter conditions for hail occurrence. It is pre-constructed based on hail growth theory and analysis of hail weather radar echo characteristics. The severe convective cell hazard model records the fractional changes of the severe convective cell hazard index under different ratios (the ratio of weighting coefficients w1, w2, and w3).

[0083] Different mix ratios correspond to different hazard sub-models for severe convective weather. These sub-models record the changes in hazard index scores as the network hail index (POSH), reflectivity intensity, and vertical liquid water content change according to the set network hail index, reflectivity intensity, and vertical liquid water content, all within the specified mix ratio. Based on the weighting coefficients w1, w2, and w3, the corresponding hazard sub-model can be determined within the severe convective weather hazard model. Then, based on this sub-model, the hazard index scores corresponding to the hail identification index and pre-landing hail indicators for that mix ratio can be obtained.

[0084] The hail identification indicators and pre-landing hail indicators can be set by system defaults or customized by the user according to local conditions. It should be noted that, based on hail growth theory and analysis of hail weather radar echo characteristics, the high value area of ​​vertical liquid water content (VIL) is one of the indicators for judging hail potential. When the VIL of vertical liquid water content increases sharply in the preceding and following volume scans, the probability of hail is relatively high. Therefore, the proportional threshold of vertical liquid water content (VIL) is usually higher than the other two factors.

[0085] As a typical example, the following describes how to determine two score thresholds for hail identification in conjunction with specific implementation methods.

[0086] Taking a certain observation area as an example, assuming that the weighting coefficients w1, w2, and w3 of the three factors—network reflectivity, network vertical liquid water content (VIL), and network hail index (POSH)—are determined to be 40%, 50%, and 10% respectively, based on the local hail occurrence conditions, the corresponding strong convective cell hazard model information (hazard sub-model) is shown in the table below:

[0087]

[0088] It can be seen that the reflectivity of the network changes by approximately 0.03 for every 5 dBZ, and the VIL changes by approximately 5 kg / m². 2 The change is approximately 0.05 (the increase in each element varies depending on the proportion configuration); POSH ≥ 50% is assumed as the strong hail warning threshold. Strong convective cell reflectivity > 50 dBZ and VIL ≥ 20 kg / m³ are also considered. 2When set as a hail identification index, the corresponding severe convective cell hazard index is 55 points; a severe convective cell reflectance ≥ 55 dBZ and VIL ≥ 30 kg / m³ are also considered. 2 When set as the pre-landing hail indicator, the corresponding severe convective cell hazard index is 64 points. Then, the hazard index score of 55 corresponding to the hail identification indicator is set as the first score threshold S1, and the hazard index score of 64 corresponding to the pre-landing hail indicator is set as the second score threshold S2, i.e., S1 = 55, S2 = 64. Thus, two score thresholds for hail identification are determined when the ratios of w1, w2, and w3 are 40%, 50%, and 10%, respectively.

[0089] For example, taking another observation area as an example, if the weighting coefficients w1, w2, and w3 of three factors—network reflectivity, network vertical liquid water content (VIL), and network hail index (POSH)—are determined to be 30%, 50%, and 20% respectively, based on the local hail occurrence conditions, the corresponding strong convective cell hazard model information (hazard sub-model) is shown in the table below:

[0090]

[0091] It can be seen that the reflectivity of the network changes by approximately 0.02 for every 5 dBZ, and the VIL changes by approximately 5 kg / m². 2 The change is approximately 0.04 (the increase in each element varies depending on the proportion configuration); POSH ≥ 50% is assumed as the strong hail warning threshold. Strong convective cell reflectivity > 50 dBZ and VIL ≥ 20 kg / m³ are also considered. 2 When set as a hail identification index, the corresponding severe convective cell hazard index is 52 points; a severe convective cell reflectance ≥ 55 dBZ and VIL ≥ 30 kg / m³ are also considered. 2 When set as the pre-landing hail indicator, the corresponding severe convective cell hazard index is 61 points. Then, the hazard index score of 52 corresponding to the hail identification indicator is set as the first score threshold S1, and the hazard index score of 61 corresponding to the pre-landing hail indicator is set as the second score threshold S2, i.e., S1 = 52, S2 = 61. Thus, two score thresholds for hail identification are determined when the ratios of w1, w2, and w3 are 40%, 50%, and 10%, respectively.

[0092] Preferably, in this embodiment, based on the aforementioned two score thresholds S1 and S2 that may form hail, three screenings are performed to form five results, and a five-segment hail prevention operation strategy is constructed based on the five results.

[0093] The following is combined Figures 1 to 4 The document details the process of establishing a segmented hail suppression strategy based on models and thresholds, and allocating tasks to multiple convective units and multiple operation points.

[0094] To accurately grasp the timing of the occurrence and development of severe convective cells and the possibility of hail, focusing on precipitation and hail, based on networked weather radar and radiosonde temperature profile data, a five-stage decision-making basis is established through networked weather radar data quality control and fusion, convective cell segmentation, hazard index calculation, hail identification and classification. Combined with the distance of the operation point, operation point matching and operation parameters are formed to support hail prevention operation decision-making and assessment.

[0095] For details, see Figure 1 As shown, the hail suppression operation method includes the following steps:

[0096] S100 is used for data collection, quality control, and coordinate transformation from multiple weather radars.

[0097] S200, network reflectivity and strong convection cell segmentation, calculate network vertical liquid water content and network hail index.

[0098] S300 calculates the hazard index of severe convective cells and identifies hail in severe convective cells.

[0099] S400 refers to the five operational parameters for hazard index zoning and precipitation / hail formation.

[0100] S500 matches the location of strong convective cells and hail suppression operation points based on the identification type and stage.

[0101] S600, configure the work point parameters and the number of operations. The work parameters for each operation include the azimuth and elevation angles of the work point.

[0102] Step S100 primarily involves data fusion. It collects data from multiple weather radars covering the observation area, performs quality control and coordinate transformation, and then obtains a networked fusion product. Preferably, it collects temperature profile data from S-band weather radars covering the area and radiosonde radars covering the area. The weather radars undergo major quality control methods such as ground clutter filtering, radial interference filtering, and point clutter processing. Through the volume scanning mode analysis and coordinate transformation of the networked S-band weather radars, radar reflectivity data is projected onto a three-dimensional grid field. Combined with networked radar coverage analysis, a maximum value method or a weighted function method is used. That is, the maximum value among multiple radar estimates covering the same grid cell is assigned to the grid cell R. max The distance between a grid cell and the radar location is assigned to cell R using an exponential weighting function. cappi .

[0103] Step S200 is mainly used for convective cell segmentation. Based on the network fusion product obtained in the previous step, it identifies and segments all strong convective cells within the observation area based on the network reflectivity to obtain one or more strong convective cells. Specifically, a dual-threshold method is preferably used to identify and segment all strong convective cells within the observation area, as follows: Based on a pre-set high reflectivity threshold—for example, 45 dBZ—when the 45 dBZ area of ​​a strong convective cell does not exceed a preset area threshold—for example, 16 km²... 2 If the conditions are met, no segmentation is performed; otherwise, convective cell segmentation is performed. For cells that meet the segmentation conditions, based on pre-set high reflectance thresholds (e.g., 45 dBZ) and low reflectance thresholds (e.g., 35 dBZ), the high threshold is used to detect the core of the strong convective cell, and the low threshold is used as the boundary reflectance detection threshold to determine the boundary of the strong convective cell. The high threshold is decreased according to a preset reflectance step size, and then an expansion search is performed using the corresponding reflectance contour lines until the cell boundary corresponding to the low threshold is reached, thus obtaining the boundary range of each strong convective cell.

[0104] When calculating the hazard index (RSIK) of severe convective cells, it is necessary to first extract hazardous weather characteristic parameters for each severe convective cell, and then calculate the hazard index for each cell based on these extracted parameters. The characteristic parameters related to the comprehensive hazard index include single / multi-layer network reflectivity, network vertical liquid water content (VIL), and network hail index (POSH). Specifically, through a network fusion algorithm, parameters such as network reflectivity and height, network vertical liquid water content (VIL) and density, and network hail index (POSH) can be obtained.

[0105] Among them, the liquid water content (VIL) is derived from the vertical scale of the liquid water mixing ratio based on the gridded reflectance data and then vertically accumulated, which has a good warning effect for the early detection of local severe convection.

[0106] In the VIL algorithm for vertical liquid water content measurement, a reflectance factor less than 55 dBZ reflects liquid water content. However, a reflectance factor exceeding 55 dBZ to 70 dBZ, indicating a high reflectance factor, could correspond to either liquid or solid water. The presence of solid water introduces measurement inaccuracies. Therefore, the POSH (Polymerized Hail Index) is introduced, replacing the VIL algorithm's relationship between reflectance factor and solid water (hail) with the POSH's relationship between reflectance factor and liquid water. POSH reflects the hazard potential of hail kinetic energy and is closely related to potential ground-falling hail. In practice, after segmenting strong convective cells based on network reflectance, the height and maximum value of each cell can be identified. Combined with the temperature profile from radiosonde data, a network hail probability is formed, corresponding to the POSH. The network hail probability is rounded and output at preset intervals—e.g., 10%. The primary objective of this algorithm is to measure the probability of hail with a size greater than 20 mm. Based on experience, when the POH value is relatively high, the hail index tends to significantly overestimate severe convection (i.e., there are more false alarms). However, even if hail does not occur, thunderstorms and other severe convective weather often do occur.

[0107] The network reflectivity reflects the storm intensity, while the network vertical liquid water content and strong hail probability reflect the effects of liquid water and solid water, respectively, playing different roles. Specific implementations of steps S100 and S200 can be found in the relevant content disclosed in patent ZL202410446117.6, and will not be repeated here.

[0108] In step S300, the hazard index of a strong convective cell is first calculated, and then hail identification is performed on the strong convective cell.

[0109] Specifically, for each strong convective cell, the steps to calculate the RSIK value of that strong convective cell can be as follows: Based on the maximum network reflectivity, network vertical liquid water content, and strong hail index of the strong convective cell, a normalized model is established by combining the statistical analysis results of the storm spatial distribution and parameter characteristics of local convection.

[0110] Let the hazard index of the Kth strong convective cell be RSIK. K RSIK K The normalization calculation formula is as follows:

[0111]

[0112] Where K is a natural number greater than or equal to 1.

[0113] Z K Represents the network reflectivity of the Kth strong convective cell, max(Z K ) represents the maximum reflectivity of the Kth strongly convective cell.

[0114] VIL K This represents the liquid water content of the Kth strongly convective monomer, max(VIL). K ) represents the maximum vertical liquid water content of the Kth strongly convective cell.

[0115] POSH represents the network hail index of this strong convective cell. The value range of POSH is greater than or equal to 0 and less than or equal to 1, i.e., [0, 1]. Specifically, after segmenting each strong convective cell, the maximum height and reflectivity of each strong convective cell are identified, and the POSH is obtained by combining the temperature profile of the radiosonde.

[0116] ref(Z K ) and ref(VIL K The values ​​represent the local reference values ​​for the network reflectance and vertical liquid content of the region where the Kth strong convective cell is located. These values ​​can be specifically set based on statistical analysis of the spatial distribution and parameter characteristics of local convective storms. For example, the network reflectance range could be 0-70 dBZ, and the vertical liquid content range could be 0-55 kg / m³. 2 .

[0117] w i This represents the weighting coefficients, i = 1, 2, 3, w1 + w2 + w3 = 1.

[0118] In this embodiment, before calculating the hazard index RSIK of a strong convective cell, the following steps may be included: obtaining convective cell segmentation information; obtaining the area S of the 45 dBZ boundary segmentation of the strong convective cell based on a set high reflectivity threshold—for example, 45 dBZ; and determining whether the area S exceeds a preset area threshold—for example, 16 km². 2 When the area S is less than or equal to the area threshold, it is determined that the RSIK score of the strong convective cell is zero (or RSIK = 0). When the area S exceeds the area threshold, it is determined that a convective cell is generated and the RSIK score of the strong convective cell is obtained. The RSIK value of the strong convective cell is then calculated.

[0119] After obtaining the RSIK value of a severe convective cell, hail can be identified in the severe convective cell using a hail identification model.

[0120] In this embodiment, the strong convective cell is configured to include five types: no-risk type, ordinary precipitation HR type, heavy precipitation HR type, suspected hail HI type, and hail HI type, which correspond to the RSIK no score stage, convective cell development stage, possible development into hail cloud stage, hail cloud development stage, and hail cloud development and landing stage, respectively.

[0121] The hail identification model is configured to: identify the type of each strong convective cell based on the segmentation information and hazard index RSIK, combined with two fractional thresholds and the temperature profile of radiosonde, and determine the stage corresponding to the strong convective cell.

[0122] Specifically, the hail identification model is configured to identify the type of each strong convective cell through the following steps.

[0123] First, an initial screening is conducted by determining whether the hazard index RSIK has a score; see [link to relevant documentation]. Figure 2 As shown.

[0124] For a strong convective cell with no RSIK score, the cell is determined to be of the no-risk type, corresponding to the stage with no RSIK score.

[0125] For strong convective cells with hazard index scores, a second screening is required based on the two determined score thresholds S1 and S2.

[0126] The second screening process is as follows: compare the hazard index RSIK of the severe convective cell with the fractional thresholds S1 and S2. When the hazard index RSIK of the severe convective cell does not reach the first fractional threshold S1, i.e., RSIK < S1, it is identified as ordinary precipitation (HR) type, corresponding to the development stage of the convective cell. When the hazard index RSIK of the severe convective cell reaches the second fractional threshold S2, i.e., RSIK ≥ S2, it is identified as hail (HI) type, corresponding to the mature stage of hail cloud development and landing. When the hazard index RSIK of the severe convective cell reaches the first fractional threshold S1 but does not reach the second fractional threshold S2, i.e., S1 ≤ RSIK < S2, it proceeds to the third screening.

[0127] The third screening process is as follows: First, determine if the high reflectivity threshold height of the strong convective cell—for example, 45 dBZ—exceeds the altitude corresponding to -20° radiosonde. If the 45 dBZ height does not exceed the altitude corresponding to -20° radiosonde, it is identified as a strong precipitation (HR) type, corresponding to a possible hail cloud stage. If the 45 dBZ height exceeds the altitude corresponding to -20° radiosonde, it is identified as a suspected hail (HI) type, corresponding to a hail cloud development stage.

[0128] Then, based on the identification type and corresponding stage of the severe convective cells, hail prevention strategies are configured for each severe convective cell. The specific steps are as follows.

[0129] First, for strong convective cells with RSIK scores, obtain the following parameters for each strong convective cell: the convective cell hazard index RSIK score, the latitude and longitude of the maximum RSIK value within the cell, the identification type of the convective cell, the maximum height of the high reflectivity threshold (e.g., 45 dBZ) of the convective cell, and the cell range.

[0130] Then, hail suppression operation points are located within a preset radius (e.g., 10-15 km) of the core location of each strong convective cell (the location of the maximum RSIK value within the cell); the hail suppression operation points are then sorted in order of proximity to the core location of the convective cell hazard index.

[0131] Finally, based on the type and stage of the severe convective cell, hail suppression operation points and parameters are matched within the range of the severe convective cell. Specifically, the distance between the two points and the azimuth angle θ of the operation point towards the cell core are calculated using the latitude and longitude of the cell's core and the matched weather modification operation points; and the elevation angle of the operation points is calculated based on the distance between the two points and the maximum height of the high reflectivity threshold, thus forming the operational parameters for weather modification.

[0132] The following is combined Figure 3 As shown, taking a high reflectivity threshold of 45dBZ as an example, the steps for hail suppression operation points and operation parameters within the matching range of strong convective cells of different types and stages are described in detail.

[0133] For strong convection units identified as HR, trigger single-point operations.

[0134] For severe convective cells of the ordinary precipitation type, the first operational strategy is adopted as follows: Initiate weather modification operations, match the nearest operational point, calculate the azimuth of the anti-aircraft gun at the operational point based on the latitude and longitude of the severe convective cell's core and the operational point, calculate the elevation angle of the operational point based on the 45 dBZ altitude and range, and then conduct single-point operations; continuously monitor the development of the convective cell, and dynamically adjust the operational parameters based on updated observation data and forecast results until the RSIK score is zero. The effective range of the anti-aircraft gun varies depending on the type of anti-aircraft gun; for example, the range of a high-frequency anti-aircraft gun can be 10 km.

[0135] For severe convective cells with heavy precipitation, the second operational strategy is adopted as follows: Initiate weather modification operations, match the nearest operational point, calculate the azimuth of the anti-aircraft gun at the operational point based on the latitude and longitude of the severe convective cell's core and the operational point, and calculate the elevation angle of the weather modification operational point based on the 45 dBZ altitude and range; after the operation is completed, recalculate the hazard index RSIK of the severe convective cell, compare the new hazard index RSIK with the score threshold S1, if RSIK > S1, it is determined that the number of shells needs to be increased, and the secondary anti-aircraft gun operation parameters are configured, and single-point operations continue to be performed until RSIK < S1 after the operation, that is, when it is identified as ordinary precipitation HR, the operation strategy corresponding to ordinary precipitation is implemented until RSIK has no score.

[0136] For strong convection cells identified as HI, trigger multi-point joint operations.

[0137] For severe convective cells suspected of being hail-type, a third operational strategy is adopted, as follows: Initiate weather modification operations, matching at least two operational points. Calculate the azimuth of anti-aircraft guns fired at each operational point based on the core latitude and longitude of the severe convective cell and the latitude and longitude of each operational point. Calculate the elevation angle of the operational points based on the 45dBZ altitude and range. After this operation is completed, re-identify the type of the severe convective cell. If it is identified as a precipitation HR type, adjust to single-point operation, executing the corresponding operational strategy based on whether it is ordinary or heavy precipitation. Otherwise, it is determined that the number of shells needs to be increased, and secondary anti-aircraft gun operation parameters need to be configured. Continue multi-point operation until it is identified as a precipitation HR type, then adjust to single-point operation. This process continues until no RSIK score is obtained.

[0138] For severe convective cells of the hail type, corresponding to the mature stage of hail cloud development, the fourth operational strategy is implemented as follows: Initiate weather modification operations, match all operational points, calculate the azimuth of anti-aircraft artillery firing at each operational point based on the core latitude and longitude of the severe convective cell and the latitude and longitude of each operational point, and calculate the elevation angle of the operational points based on the 45 dBZ altitude and range; after this operation is completed, recalculate the hazard index RSIK of the severe convective cell, compare the new hazard index RSIK with the score thresholds S1 and S2. When RSIK ≥ S2, it is determined that the number of shells needs to be increased, and secondary anti-aircraft artillery operation parameters are configured. Continue to implement the joint operation strategy for all points until S1 ≤ RSIK < S2 after the operation, then implement the third operational strategy; and so on, until RSIK has no score, then participate in... Figure 3 The process is shown below.

[0139] In this embodiment, the steps for calculating the elevation angle β of the manned operation point and the azimuth angle θ of the anti-aircraft gun launched from the operation point are as follows.

[0140] First, the spherical distance d between the two points is calculated based on the latitude and longitude coordinates (λ1, φ1) of the core of the strong convective cell and the latitude and longitude coordinates (λ2, φ2) of the work point.

[0141] Specifically, the Haversine formula is used to calculate the shortest distance between two points on Earth (assuming the Earth is an ideal sphere), known as the great circle distance. It is a commonly used method in navigation and aviation to estimate the distance between two geographic coordinates (longitude and latitude). The algorithm's calculation principle is based on spherical trigonometry.

[0142] The Haversine formula is as follows:

[0143] d = R·c;

[0144]

[0145] In the formula, φ1 and φ2 are the latitudes of the two points, in radians.

[0146] λ1 and λ2 are the longitudes of the two points, in radians.

[0147] Δφ is the difference in latitude between two points: Δφ = φ2 - φ1.

[0148] Δλ is the difference in longitude between two points: Δλ = λ2 - λ1.

[0149] R is the radius of the Earth, usually taken as 6371 kilometers.

[0150] Then, based on the aforementioned spherical distance d, the elevation angle β of the shadow manipulation point is calculated using the following formula:

[0151] β=tan -1 (H / d).

[0152] Where d is the spherical distance between the two points, and H is the maximum height of the convective cell at 45 dBZ. (See [link]) Figure 4 As shown.

[0153] At the same time, the azimuth angle θ is calculated using the following formula:

[0154]

[0155] The above scheme is based on five segments of results derived from the severe convective hazard index and hail identification. It calculates the distance and azimuth of the man-made weather modification operation point towards the cell core by using the latitude and longitude of the cell core and the matching latitude and longitude of the man-made weather modification operation point. Based on the distance between the two points and the maximum altitude of 45 dBZ, it calculates the elevation angle, forming the azimuth angle, elevation angle and other operational parameters of the man-made weather modification operation. This provides accurate parameters for rapid response and automatic command of man-made weather modification operations, meets the urgent requirements of artificial weather modification operations, and provides a scientific basis for hail prevention operations.

[0156] In another embodiment of this example, a hail suppression effectiveness assessment step is also included, comprising: after hail suppression operations, using the severe convective cell hazard model and hail identification model to identify hail on the severe convective cells after the operations in order to assess the effectiveness of the hail suppression operations.

[0157] Furthermore, after the hail suppression operation is completed, the meteorological data before and after the operation are compared with the actual disaster information to assess the effectiveness of the hail suppression operation, and the hail suppression operation strategy is optimized based on the feedback assessment results.

[0158] The solution provided by this invention includes hail identification, hail prevention, and hail assessment technologies. During hail identification, the main task is to monitor and assess the risk of impending convective cells using multi-source observation data, thereby determining whether to initiate hail prevention operations. This stage relies on the analysis of real-time meteorological data and the application of risk assessment models, identifying potential severe convective weather systems through multi-source observation and application, including weather radar, radiosonde, and satellite remote sensing. Based on established hail identification criteria, when the identification results indicate a significant need for hail prevention, the system can issue an early warning, initiate preparatory work for hail prevention operations, and promptly notify relevant departments and personnel.

[0159] During hail suppression, responses are based on hail identification results, shifting towards specific operational strategies and resource allocation to address real-time weather changes. At this time, continuous monitoring of convective cell development, combined with the latest observational data and forecasts, allows for the assessment of hail suppression effectiveness and dynamic adjustments to operational plans. For example, if the severity of a convective cell is detected to be increasing, decisions can be made regarding whether to add additional operations (i.e., increase the number of hail suppression shells fired) or whether multiple operation sites need to coordinate operations. This provides flexibility and speed of response in hail suppression, ensuring that hail suppression operations can adapt promptly to weather changes.

[0160] After the operation is completed, a hail suppression assessment can be conducted. The main task is to comprehensively evaluate and summarize the hail suppression effect, thereby optimizing future hail suppression strategies. At this stage, the effectiveness of the hail suppression measures is assessed by comparing meteorological data before and after the operation with the actual damage situation. The assessment results will be fed back to various models in the system to optimize assessment and operational strategies, improving the accuracy and scientific rigor of future decisions.

[0161] Another embodiment of the present invention provides a hail suppression system, including a hail detection module and a hail suppression module.

[0162] The hail identification module is used to: segment all strong convective cells within the observation area and calculate the hazard index (RSIK) of each strong convective cell using a strong convective cell hazard model; and identify strong convective cells for hail using a hail identification model. The hail identification model is configured to: determine two score thresholds for hail identification based on the hazard index scores corresponding to hail identification indicators and pre-landing hail indicators; and identify the type of each strong convective cell and the corresponding stage based on the segmentation information and hazard index (RSIK) of the strong convective cells, combined with the two score thresholds and the temperature profile of the radiosonde.

[0163] The hail suppression module is used to: receive the identification results from the hail identification module, and configure hail suppression operation strategies for each strong convective cell according to the identification type and corresponding stage; wherein, strong convective cells at different stages correspond to different operation strategies to form a segmented hail suppression operation strategy.

[0164] Furthermore, it may also include a hail suppression effectiveness assessment module. On the one hand, after hail suppression operations, the severe convective cell hazard model and hail identification model can be used to identify hail in the severe convective cells after the operations, thereby assessing the effectiveness of the hail suppression operations. On the other hand, after the hail suppression operations are completed, meteorological data before and after the operations can be compared with actual disaster information to assess the effectiveness of the hail suppression operations, and the hail suppression strategy can be optimized based on the feedback assessment results.

[0165] Other technical features are described in the preceding embodiments and will not be repeated here.

[0166] In the above description, the disclosure of this invention is not intended to limit itself to these aspects. Rather, within the scope of the objectives of this disclosure, components can be selectively and operationally combined in any number. Furthermore, terms such as “comprising,” “encompassing,” and “having” should be interpreted by default as inclusive or open-ended, rather than exclusive or closed, unless explicitly defined as such. All technical, scientific, or other terms are to be understood by those skilled in the art, unless defined as such. Public terms found in dictionaries should not be interpreted in the context of the relevant technical documents in an overly idealistic or impractical manner, unless explicitly defined as such in this disclosure. Any modifications or alterations made by those skilled in the art based on the foregoing disclosure are within the scope of the claims.

Claims

1. A hail suppression operation method based on a convective cell hazard index and hail discrimination, characterized by The method comprises the steps of: calculating a hazard index RSIK of each strong convective cell after the strong convective cell in the observation area is segmented; and determining corresponding strong convective cell hazard model information according to local hail occurrence condition matching, and determining the hazard index scores of hail identification indexes and hail landing before indexes based on the strong convective cell hazard model; The hail identification model is configured to: determine two segment score thresholds for hail identification according to the hazard index scores of the two indexes; and identify the type of each strong convective cell and determine the corresponding stage of the strong convective cell according to the segmentation information and the hazard index RSIK of the strong convective cell, in combination with the two segment score thresholds and the temperature profile of the sounding. According to the identified type and corresponding stage of the strong convective cell, a hail suppression operation strategy is configured for each strong convective cell to form a segmented hail suppression operation strategy.

2. The method of claim 1, wherein, The hazard index scores of the hail identification indexes and the hail landing before indexes are related to the matching of the weight coefficients w1, w2, and w3 of the network reflectivity, the network vertical liquid water content VIL, and the network hail index POSH. After obtaining the local hail occurrence condition matching data, the proportions of the weight coefficients w1, w2, and w3 are determined according to the local hail occurrence condition matching. Different matching corresponds to different strong convective cell hazard model information. After determining the matching, obtaining the strong convective cell hazard model information corresponding to the matching, and obtaining the hazard index scores corresponding to each index according to the set hail identification indexes and hail landing before indexes, the hazard index score corresponding to the hail identification index is set as the first score threshold, and the hazard index score corresponding to the hail landing before index is set as the second score threshold.

3. The method according to claim 1 or 2, characterized in that, Before calculating the hazard index RSIK of the strong convective cell, the method further comprises the steps of: Obtaining the segmentation information of the convective cell, and obtaining the high threshold boundary segmentation area S of the strong convective cell according to the set high reflectivity threshold; Determining whether the area S exceeds a preset area threshold. When the area S is less than or equal to the area threshold, it is determined that the RSIK of the strong convective cell has no score. When the area S exceeds the area threshold, it is determined that the convective cell generates, and the RSIK of the strong convective cell has a score. The RSIK value of the strong convective cell is calculated.

4. The method of claim 3, wherein, The steps of calculating the RSIK value of the strong convective cell are as follows: A normalization model is established based on the network reflectivity maximum value, network vertical liquid water content, and strong hail index of the strong convective cell, in combination with the statistical analysis results of the storm spatial distribution and parameter characteristics of local convection. Let the hazard index of the Kth strong convective cell be RSIK K , and the normalized calculation formula of RSIK K is as follows: K is a natural number greater than or equal to 1; Z K ZKrepresents the reflectivity of the Kth strong convective cell, max(Z K ) represents the maximum reflectivity of the Kth strong convective cell; VIL K represents the liquid water content of the Kth strong convective cell, max(VIL K ) represents the maximum vertical liquid water content of the Kth strong convective cell; POSH represents the network hail index of the strong convective cell, and the value range of POSH is greater than or equal to 0 and less than or equal to 1, i.e. [0, 1]. After each strong convective cell is segmented, the height and reflectivity maximum value of each strong convective cell are identified, and the POSH is obtained in combination with the temperature profile of the sounding. ref(Z K ) and ref(VIL K ) represent the local reference values of reflectivity and vertical liquid water content of the Kth strong convective cell, respectively; w i represent weight coefficients, i = 1, 2, 3, wi + w2+ w3= 1.

5. The method of claim 3, wherein: The strong convective cell is configured to include five types, respectively, a risk-free type, a general precipitation HR type, a heavy precipitation HR type, a suspected hail HI type, and a hail HI type, respectively corresponding to an RSIK non-score stage, a convective cell development stage, a possible development into a hail cloud stage, a hail cloud development stage, and a hail cloud development mature landing stage.

6. The method of claim 5, wherein, The hail identification model is configured to identify the type of each strong convective cell by the following steps: For a strong convective cell with a hazard index RSIK without a score, it is determined that the cell belongs to the risk-free type; For a strong convective cell with a hazard index with a score, secondary screening is performed according to the determined two score thresholds S1 and S2, as follows: Compare the hazard index RSIK of the strong convective cell with the size of the score threshold S1 and S2, when the hazard index RSIK of the strong convective cell does not reach the first score threshold S1, i.e. RSIK < S1, it is identified as a general precipitation HR type; when the hazard index RSIK of the strong convective cell reaches the second score threshold S2, i.e. RSIK ≥ S2, it is identified as a hail HI type; when the hazard index RSIK of the strong convective cell reaches the first score threshold S1 but does not reach the second score threshold S2, i.e. S1 ≤ RSIK < S2, it enters the third screening, as follows: Determine whether the height of the reflectivity high threshold of the strong convective cell exceeds the sounding-20° corresponding height; when the reflectivity high threshold height does not exceed the sounding-20° corresponding height, it is identified as a heavy precipitation HR type; when the reflectivity high threshold height exceeds the sounding-20° corresponding height, it is identified as a suspected hail HI type.

7. The method of claim 6, wherein, According to the identification type and the corresponding stage of the strong convective cell, the steps for configuring the hail suppression operation strategy for each strong convective cell include: For a strong convective cell with a hazard index RSIK with a score, the following parameters of each strong convective cell are obtained: the convective cell hazard index RSIK score, the longitude and latitude of the convective cell core position, the identification type of the convective cell, the maximum height of the convective cell reflectivity high threshold, and the convective cell range; Find the hail suppression operation point within a predetermined radius range of the core position of each strong convective cell; according to the distance between the hail suppression operation point and the core position of the convective cell, the operation points are sequentially sorted in order from near to far to form an operation point list; Based on the type and stage to which the strong convective cell belongs, the hail suppression operation points and operation parameters within the range of the strong convective cell are matched; wherein the distance between the two points and the azimuth angle θ of the shadow hail suppression operation point towards the cell core are calculated through the longitude and latitude of the strong convective cell core point and the longitude and latitude of the matched shadow hail suppression operation point; and the shadow operation parameter is formed according to the distance between the two points and the maximum height of the reflectivity high threshold.

8. The method of claim 7, wherein, The steps for matching the hail suppression operation points and operation parameters within the range of the strong convective cell are as follows: For a strong convective cell identified as HR, trigger single-point operation; For the strong convective cell of ordinary precipitation type, the first operation strategy is adopted, as follows: start the human shadow operation, match one nearest operation point, calculate the azimuth of the operation point launching the high-velocity gun according to the longitude and latitude of the strong convective cell core and the longitude and latitude of the operation point, calculate the elevation angle of the human shadow operation point according to the height and range of the high reflectivity threshold, and then perform single-point operation; continuously monitor the development of the convective cell, dynamically adjust the operation parameters combined with the updated observation data and prediction results, until the RSIK score is zero; For the strong convective cell of strong precipitation type, the second operation strategy is adopted, as follows: start the human shadow operation, match one nearest operation point, calculate the azimuth of the operation point launching the high-velocity gun according to the longitude and latitude of the strong convective cell core and the longitude and latitude of the operation point, calculate the elevation angle of the human shadow operation point; after this operation is completed, recalculate the hazard index RSIK of the strong convective cell, compare the new hazard index RSIK with the score threshold S1, when RSIK > S1, it is determined that the number of gun shells needs to be increased, and the second high-velocity gun operation parameters are configured, and the single-point operation is continued to be performed, until RSIK < S1 after the operation, that is, when it is determined to be ordinary precipitation HR, the operation strategy corresponding to ordinary precipitation is executed, until the RSIK score is zero; For the strong convective cell identified as HI, trigger multi-point joint operation; For the strong convective cell of suspected hail type, the third operation strategy is adopted, as follows: start the human shadow operation, match at least two operation points, calculate the azimuth of each operation point launching the high-velocity gun according to the longitude and latitude of the strong convective cell core and the longitude and latitude of each operation point, calculate the elevation angle of the human shadow operation point; after this operation is completed, re-identify the type of the strong convective cell, when it is identified as precipitation HR type, adjust to single-point operation, and execute the corresponding operation strategy according to whether it is ordinary precipitation or strong precipitation; otherwise, it is determined that the number of gun shells needs to be increased, and the second high-velocity gun operation parameters are configured, and multi-point operation is continued to be performed, until it is identified as precipitation HR type; and so on, until the RSIK score is zero; For the strong convective cell of hail type, the fourth operation strategy is executed corresponding to the mature stage of hail cloud development, as follows: start the human shadow operation, match all operation points, calculate the azimuth of each operation point launching the high-velocity gun according to the longitude and latitude of the strong convective cell core and the longitude and latitude of each operation point, calculate the elevation angle of the human shadow operation point; after this operation is completed, recalculate the hazard index RSIK of the strong convective cell, compare the new hazard index RSIK with the score thresholds S1 and S2, when RSIK ≥ S2, it is determined that the number of gun shells needs to be increased, and the second high-velocity gun operation parameters are configured, and the all-point joint operation strategy is continued to be executed, until S1 ≤ RSIK < S2 after the operation, the third operation strategy is executed; and so on, until the RSIK score is zero.

9. The method of claim 7, wherein, The steps of calculating the elevation angle β of the human shadow operation point and the azimuth θ of the operation point launching the high-velocity gun are as follows: According to the longitude and latitude coordinates (λ1, φ1) of the strong convective cell core and the longitude and latitude coordinates (λ2, φ2) of the operation point, the spherical distance d between the two points is calculated, and the calculation formula is d = R c, wherein, φ1, φ2 are the latitudes of the two points, in radians; λ1, λ2 are the longitudes of the two points, in radians; Δφ is the latitude difference between the two points: Δφ = φ2 - φ1; Δλ is the longitude difference between the two points: Δλ = λ2 - λ1; R is the radius of the earth, usually taken as 6371 kilometers; According to the aforementioned spherical distance d, the elevation angle β of the shadow operation point is calculated, and the calculation formula is β = tan -1 (H / d), wherein, d is the spherical distance between the two points, and H is the maximum height of the convective cell reflectivity high threshold; The azimuth angle θ is calculated, and the calculation formula is 10. The method of claim 1, wherein, It also includes a network data fusion step and a convective cell segmentation step; In the network data fusion step, after collecting the data of multiple weather radars covering the observation area, performing quality control and coordinate conversion, the network fusion product is obtained; In the convective cell segmentation step, according to the aforementioned network fusion product, based on the network reflectivity, a double threshold method is used to identify and segment all strong convective cells in the observation area to obtain one or more strong convective cells; In calculating the hazard index of the strong convective cell, the disaster weather characteristic parameters of each strong convective cell are extracted first, and the hazard index of each strong convective cell is calculated according to the extracted disaster weather characteristic parameters; the characteristic parameters related to the comprehensive disaster index include single / multi-layer network reflectivity, network vertical liquid water content VIL, and network hail index POSH.

11. The method of claim 1, wherein, It also includes a hail prevention effect evaluation step, which includes: after the hail prevention operation, the strong convective cell after the operation is identified for hail by the strong convective cell hazard model and the hail identification model to evaluate the effectiveness of the hail prevention operation; And / or, after the hail prevention operation is completed, the weather data before and after the hail prevention operation is compared with the actual disaster information to evaluate the effectiveness of the hail prevention operation, and the hail prevention operation strategy is optimized according to the feedback evaluation result.

12. A hail mitigation system for a human shadow, characterized by It includes a hail identification module and a hail prevention module; The hail identification module is used to: after segmenting all strong convective cells in the observation area, calculate the hazard index RSIK of each strong convective cell; and after determining the corresponding strong convective cell hazard model information according to the local hail occurrence condition ratio, determine the hazard index scores corresponding to the hail identification index and the hail landing before index based on the strong convective cell hazard model; identify hail for the strong convective cell by the hail identification model, which is configured to: determine two segment score thresholds for hail identification according to the hazard index scores corresponding to the two indexes; and identify the type of each strong convective cell according to the segmentation information and the hazard index RSIK of the strong convective cell, combined with the two segment score thresholds and the temperature profile of the sounding, and determine the corresponding stage of the strong convective cell; The hail prevention module is used to: receive the identification result of the hail identification module, configure a hail prevention operation strategy for each strong convective cell according to the identification type and the corresponding stage of the strong convective cell to form a segmented hail prevention operation strategy.

Images