Arch-shaped echo associated convection early warning method

Abstract

The invention discloses a bow-shaped echo associated convection early warning method. The method comprises the following steps: receiving multi-dimensional weather forecast data input; calculating vertical shear rate data grid by grid by using a central difference method; analyzing the vertical shear rate data of each horizontal grid point, and detecting a vertical shear layer conforming to a condition by adopting a sliding window method; carrying out thermal parameter coupling and verification on the screened shear rate sequence; optimal window selection is carried out aiming at a plurality of shear rate sequences which possibly appear in each grid and meet conditions, and the sequence with the maximum product is selected as final output; and drawing the flow trigger intensity of the finally output shear sequence on a forecast reflectivity image in a scattered point manner. The method is realized based on mathematical module construction and method of theoretical innovation; a shear rate distribution normality test is introduced to eliminate an abnormal disturbance layer; the convection trigger potential is quantified in a physical quantity product form; and automatic layered feature identification of the three-dimensional meteorological field is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of meteorological data reprocessing, and particularly relates to an arcuate echo associated convective warning method. Background Art

[0002] An arcuate echo is a typical severe convective weather system, named after its arcuate structure presented in the radar reflectivity image. An arcuate echo can trigger extreme strong winds and may be accompanied by short-term heavy precipitation, hail, or even tornadoes. Therefore, it has attracted much attention in severe convective warning and forecasting. Sometimes, quasi-linear convective systems will newly occur upstream or downstream of the arcuate echo. Such systems are not far from the arcuate echo parent storm and are closely related, and are often referred to as arcuate echo associated convection (hereinafter simply referred to as associated convection). The occurrence and development mechanism of this kind of associated convection is complex, and the forecasting accuracy is extremely low (about 20%); and it often brings harmful weather such as hail and thunderstorm strong winds.

[0003] The mechanism of associated convection is complex. Foreign scholars believe that its occurrence and development are related to low-level convergence, that is, as Figure 1 shown in (a) below, the triggering of the associated convection upstream of the arcuate echo benefits from the convergence of the mesoscale convective vortex of the arcuate echo parent body itself and the environmental low-level jet upstream; while the triggering of the downstream associated convection is mainly caused by the convergence of the environmental front and the low-level jet downstream, as Figure 1 shown in (b) below. However, due to the significant differences in the domestic climate environment characteristics from those abroad, the occurrence and development mechanism of domestic associated convection has regional characteristics. Domestic scholars' research shows that the occurrence and development of the arcuate echo associated convection in China are closely related to the rapid change of the vertical shear in the middle and lower layers. For example, based on the case study of the associated convection upstream of the Anhui arcuate echo on June 5, 2016, it is considered that the vertical shear generated by the stacking of the low-level jet and the mesoscale convective vortex of the arcuate echo itself at different heights (i.e., the rapid change area of the vertical shear, hereinafter simply referred to as the change area) is an important reason for the occurrence and triggering of the associated convection; further research based on the case of the associated convection downstream of the Bohai Bay arcuate echo on July 25, 2022 found that under the modulation of the downstream wind field by the anticyclonic vortex formed by the upper-level outflow of the arcuate echo parent storm, the vertical shear changes rapidly, and then a negative pressure disturbance is generated, which has an important impact on the occurrence and development of the downstream associated convection. Based on multi-sample simulations, the research further found that the change area widely exists in the associated convection and has a certain guiding significance for the occurrence and development of the associated convection; the formation of the change area is related to the interaction of various multi-scale elements at different heights, such as: the interaction between the large-scale northwest airflow behind the upper-level trough and the low-level southwest airflow; the interaction of the non-uniform flow fields of the Northeast cold vortex at different heights, etc.

[0004] Although breakthroughs have been made in related research, indicating that the occurrence and development mechanism of the associated convective system in China has significant regional characteristics, its triggering and evolution are mainly controlled by the rapid change of the vertical wind shear in the middle and lower layers, while the contribution of the surface convergence field is relatively limited. However, the innovative theoretical system has not been mathematically realized. The current numerical forecast analysis products cannot characterize the key factor of the rapid change of the vertical wind shear that affects the occurrence and development of the associated convection, and lack a specialized diagnostic module for the precursor signals of such associated convection triggering, resulting in the absence of precursor signals and the inability to provide an effective warning lead time for forecasters. These technical bottlenecks directly lead to a low forecast accuracy of the associated convective system, seriously restricting the warning ability of severe convective weather. Summary of the Invention

[0005] The present invention aims to solve at least one of the technical problems existing in the related art to some extent.

[0006] An object of the present invention is to provide an arcuate echo associated convection warning method based on an innovative theoretical system through a mathematical model, generate relevant potential forecast products, and give a warning forecast for the triggering of the associated convection.

[0007] To achieve the above object, on the one hand, the present invention provides an arcuate echo associated convection warning method, including the following steps:

[0008] S100. Receive the input of multi-dimensional meteorological forecast data;

[0009] S200. Use the central difference method to calculate the vertical shear rate of the radial wind, the vertical shear rate of the zonal wind, the cumulative convective instability energy, and the free lifting height grid by grid;

[0010] S300. Analyze the vertical shear rate data of each horizontal grid point, and use the sliding window method to detect the vertical shear layer that meets the conditions;

[0011] S400. Perform thermal parameter coupling and verification on the selected shear rate sequence, and the thermal parameters include the cumulative convective instability energy and the top height of the shear rate sequence;

[0012] S500. For multiple shear rate sequences that may appear in each grid, perform optimal window selection, eliminate the intervals completely included by other shear sequences, and select the sequence with the largest product as the final output;

[0013] S600. Plot the convective triggering intensity of the final output shear sequence as scatter points on the forecast reflectivity image to form an associated convection warning forecast product.

[0014] A further preferred technical solution of the present invention is that the multi-dimensional meteorological forecast data in step S100 are multi-dimensional elements of the mesoscale model forecast field of the meteorological department, including at least three-dimensional radial wind, zonal wind, temperature, humidity, air pressure, convective instability energy, and two-dimensional free lifting height.

[0015] Preferably, in step S200, the vertical shear rate of the radial wind is used to represent the second-order derivative matrix of the radial wind speed in the vertical direction, and the calculation formula is:

[0016]

[0017] The vertical shear rate of the zonal wind represents the second-order derivative matrix of the zonal wind speed in the vertical direction, and the calculation formula is:

[0018]

[0019] The cumulative convective instability energy is a physical quantity matrix reflecting the instability of the atmospheric layer structure, expressed as ; The free lifting height is used to characterize the two-dimensional field of the convective triggering critical height, expressed as ;

[0020] Among them, is the partial derivative symbol, is the wind speed of the radial wind, is the wind speed of the zonal wind, represents the cumulative convective instability energy of the height layer, is the free lifting height, represents the vertical shear rate of the radial wind, represents the vertical shear rate of the zonal wind, is the zonal grid, is the radial grid, is the height layer.

[0021] Preferably, in step S300, the vertical shear rate data of each horizontal grid point are analyzed, and the sliding window method is used to detect the vertical shear layer that meets the conditions, specifically including:

[0022] S310. Grid by grid (y, x), starting from height layer i and expanding the window upward. The sliding window is represented as [i, j], where i starts from the bottom layer to the top layer, and j ≥ i;

[0023] S320. Inside the window, calculate the average shear rate of the radial wind , and the average shear rate of the zonal wind ;

[0024] S330. When the window thickness reaches the minimum threshold m, verify the validity of the shear rate sequence inside the window.

[0025] Preferably, in step S330, the validation of the shear rate sequence within the window includes:

[0026] S331. Conduct a normal distribution test on the shear rate sequence within the window area. The calculation formula is:

[0027]

[0028]

[0029] The passing condition is or ;

[0030] represents the Shapiro-Wilk normality test; and are respectively the Shapiro-Wilk normality test statistic and the significance probability value of the radial wind within the window; and are respectively the Shapiro-Wilk normality test statistic and the significance probability value of the zonal wind within the window; is the significance level;

[0031] S332. Validate the average shear rate of the shear rate sequence within the window area. The passing condition is , where n is the minimum value of the average shear rate of the shear rate sequence;

[0032] S333. Validate the thickness of the shear rate sequence within the window area. The passing condition is , where Z is the vertical height of the terrain.

[0033] Preferably, the thermal parameter coupling and validation of the selected shear rate sequence in step S400 specifically include:

[0034] S410. Validate the accumulated unstable energy of the selected shear rate sequence. The passing condition is , where represents the convective unstable energy at the height level, is the minimum value of the accumulated convective unstable energy;

[0035] S420. Validate the height of the layer top of the selected shear rate sequence. The passing condition is .

[0036] Preferably, for the multiple eligible shear rate sequences that may appear in each grid in step S500, the optimal window is selected, the intervals completely included by other shear sequences are excluded, and the sequence with the largest product is selected as the final output; specifically including:

[0037] S510. Remove the intervals that are completely included by other shear sequences from all valid window sets, expressed as: from the set R, where,

[0038]

[0039] wherein, is the height index of any sequence other than the target sequence in the set R, and are its bottom and top height indices respectively;

[0040] S520. Select the sequence with the maximum product of the average shear rate and the cumulative convective instability energy from the remaining candidate sequences as the final output, expressed as:

[0041]

[0042]

[0043] wherein, is the convective triggering intensity value of the optimal shear rate sequence, is the height index corresponding to the convective triggering intensity value of the optimal shear rate sequence.

[0044] Preferably, step S600 plots the convective triggering intensity of the finally output shear sequence as scatter points on the forecast reflectivity image to form an associated convective warning forecast product; specifically including:

[0045] S610. Output the elements of the associated convective warning forecast product, including the vertical index range of all valid shear rate sequences at each grid point, the average shear rate value of the corresponding shear rate sequence, the cumulative instability energy value of each shear rate sequence, the vertical index of the optimal shear rate sequence, and the convective triggering intensity value of the optimal shear rate sequence; wherein, the vertical index range of all valid shear rate sequences at each grid point is expressed as ; the convective triggering intensity value of the optimal shear rate sequence is expressed as ;

[0046] S620. When there is an index of a valid shear rate sequence at a grid point, it indicates that there is a possibility of associated convective triggering at this grid point; the convective triggering intensity value of the shear sequence indicates the quality of the associated convective triggering condition at this grid.

[0047] S630. Plot the convective triggering intensity of the shear sequence as scatter points on the forecast reflectivity image as the precursor signal of the associated convective warning.

[0048] On the other hand, the present invention provides a non-transitory computer-readable storage medium storing computer instructions that cause a computer to execute the above-mentioned bow echo associated convection warning method.

[0049] On yet another aspect, the present invention provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete communication with each other through the communication bus. The processor calls the logic instructions in the memory to execute the above-mentioned bow echo associated convection warning method.

[0050] On still another aspect, the present invention provides a computer program product. The computer program product includes a computer program stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer executes the above-mentioned bow echo associated convection warning method.

[0051] Beneficial effects: The bow echo associated convection warning method of the present invention is based on an independently constructed theoretical framework for associated convection triggering. By establishing a mathematical model describing the sudden change characteristics of mid-low layer vertical wind shear, it realizes the quantitative characterization of the dynamic process; through theoretical tests and verifications of multiple sample cases, the critical thresholds of dynamic and thermodynamic parameters are determined; through comprehensive judgment of dynamic and thermodynamic conditions, a comprehensive judgment model of thermal-dynamic coupled convection potential is innovatively established to generate warning and forecast products. This product has a good forecasting effect on the occurrence and development of associated convection.

[0052] The product generated by the present invention has a good forecasting effect on the target convection. After improvement, it can be used in business applications, realizing the leap from scratch in the forecasting of bow echo associated convection, and further improving the accuracy of related convection warning and forecasting. The present invention is based on the construction and implementation of a mathematical module with theoretical innovation; the introduction of the normality test of the shear rate distribution excludes abnormal disturbance layers; the convection triggering potential is quantified in the form of a physical quantity product; the automatic recognition of the layered characteristics of the three-dimensional meteorological field is realized. Description of the Drawings

[0053] Figure 1 It is a conceptual model for the occurrence and development mechanism of foreign bow echo associated convection;

[0054] Figure 1 In (a), it is the associated convection upstream of the bow echo; Figure 1 In (b), it is the associated convection downstream of the bow echo;

[0055] Figure 2 It is a flowchart of the bow echo associated convection warning method of the present invention;

[0056] Figure 3 It is the forecasting effect diagram for the case of the associated convection upstream of the bow echo in Embodiment 1;

[0057] Figure 3 In (a), it is the distribution of the radar composite reflectivity and the associated convective potential in the model forecast field at 19:00. Figure 3 In (b), it is the distribution of the radar composite reflectivity and the associated convective potential in the model forecast field at 20:00. Figure 3 In (c), it is the distribution of the radar composite reflectivity and the associated convective potential in the model forecast field at 21:00. Figure 3 In (d), it is the distribution of the radar composite reflectivity and the associated convective potential in the model forecast field at 22:00;

[0058] Figure 4 It is the forecast effect diagram for the case of the associated convection downstream of the bow echo in Example 1;

[0059] Figure 4 In (a), it is the distribution of the radar composite reflectivity and the associated convective potential in the model forecast field at 03:00. Figure 4 In (b), it is the distribution of the radar composite reflectivity and the associated convective potential in the model forecast field at 03:30. Figure 4 In (c), it is the distribution of the radar composite reflectivity and the associated convective potential in the model forecast field at 04:00. Figure 4 In (d), it is the distribution of the radar composite reflectivity and the associated convective potential in the model forecast field at 04:30. Detailed implementation manner

[0060] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention, and they should not be construed as limiting the present invention. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts fall within the scope of protection of the present invention. In the description of the present invention, it should be understood that the terms used are only for the purpose of description and cannot be construed as indicating or implying relative importance.

[0061] The following is combined with Figures 1 - 4 to describe the method for warning of the associated convection of the bow echo provided by the present invention.

[0062] Example 1: This example provides a method for warning of the associated convection of the bow echo, including the following steps:

[0063] S100. Receive the input of multi-dimensional meteorological forecast data.

[0064] In this embodiment, the input data is multi-dimensional elements of the mesoscale model forecast field of the meteorological department (e.g., the PWRFS forecast data of the meteorological department of Jiangsu Province), including three-dimensional radial wind, zonal wind, temperature, humidity, air pressure, convective instability energy; two-dimensional free lifting height, etc. Taking the zonal wind U as an example, the data structure is expressed as U[z,y,x], where z is the height layer, y is the radial grid, and x is the zonal grid.

[0065] S200. Using the central difference method, calculate the vertical shear rate of the radial wind, the vertical shear rate of the zonal wind, the cumulative convective instability energy, and the free lifting height grid by grid.

[0066] The vertical shear rate of the radial wind represents the second-order derivative matrix of the radial wind speed in the vertical direction, with the dimension of [height layer, longitude, latitude]. The calculation formula is:

[0067]

[0068] The vertical shear rate of the zonal wind represents the second-order derivative matrix of the zonal wind speed in the vertical direction. The calculation formula is:

[0069]

[0070] The cumulative convective instability energy is a physical quantity matrix reflecting the instability of the atmosphere structure, expressed as ; The free lifting height is a two-dimensional field used to characterize the critical height of convective triggering, expressed as ;

[0071] Among them, is the partial derivative symbol, is the wind speed of the radial wind, is the wind speed of the zonal wind, represents the cumulative convective instability energy of the height layer, is the free lifting height, represents the vertical shear rate of the radial wind, represents the vertical shear rate of the zonal wind, is the zonal grid, is the radial grid, is the height layer.

[0072] S300. Analyze the vertical shear rate data of each horizontal grid point, and use the sliding window method to detect the vertical shear layer that meets the conditions.

[0073] Specifically, it includes:

[0074] S310. Grid by grid (y,x), starting from the height layer i, expand the window upward. The sliding window is expressed as [i,j], where i starts from the bottom layer to the top layer, and j≥i;

[0075] S320. Calculate the average radial wind shear rate within the window. , and the average zonal wind shear rate ;

[0076] S330. When the window thickness reaches the minimum threshold m, verify the validity of the shear rate sequence within the window, including:

[0077] S331. Conduct a normal distribution test on the shear rate sequence within the window area. The calculation formula is:

[0078]

[0079]

[0080] The passing condition is or ;

[0081] denotes the Shapiro-Wilk normality test, and are respectively the Shapiro-Wilk normality test statistic and the significance probability value of the radial wind within the window; and are respectively the Shapiro-Wilk normality test statistic and the significance probability value of the zonal wind within the window; is the significance level;

[0082] S332. Verify the average shear rate of the shear rate sequence within the window area. The passing condition is , where n is the minimum value of the average shear rate of the shear rate sequence. In this embodiment, n is 2.e -5 m -1 s -2 ;

[0083] S333. Verify the thickness of the shear rate sequence within the window area. The passing condition is , where Z is the vertical terrain height. In this embodiment, m is 2000 meters.

[0084] In addition, a nested list structure matching the spatial dimension of the input data needs to be created in this step to store output results such as the shear layer index range and trigger intensity value of each grid point.

[0085] S400. Conduct thermal parameter coupling and verification on the selected shear rate sequence.

[0086] The thermal conditions include: energy condition - the accumulated convective instability energy ≥ the preset threshold; height condition - the top height of the shear rate sequence exceeds the free convection height. Therefore, this step specifically includes:

[0087] S410. Verify the accumulated unstable energy of the screened shear rate sequence. The passing condition is , where represents the convective unstable energy at the height level, is the minimum value of the accumulated convective unstable energy;

[0088] S420. Verify the top height of the screened shear rate sequence. The passing condition is .

[0089] S500. For multiple eligible shear rate sequences that may appear in each grid, perform optimal window selection, remove the intervals completely included by other shear sequences, and select the sequence with the largest product as the final output. Specifically, it includes:

[0090] S510. Remove the intervals completely included by other shear sequences from all valid window sets , which is expressed as:

[0091]

[0092] where, is the height index of any other sequence except the target sequence in set R, and are its bottom and top height indices respectively;

[0093] S520. Select the sequence with the largest product of the average shear rate and the accumulated convective unstable energy from the remaining candidate sequences as the final output, which is expressed as:

[0094]

[0095]

[0096] where, is the convective triggering intensity value of the optimal shear rate sequence, is the height index corresponding to the convective triggering intensity value of the optimal shear rate sequence.

[0097] S600. Plot the convective triggering intensity of the finally output shear sequence as scatter points on the forecast reflectivity image to form an associated convective warning and forecast product. Specifically, it includes:

[0098] S610. Output the associated convective warning and forecasting product elements, including the vertical index range of all effective shear rate sequences at each grid point, the average shear rate value of the corresponding shear rate sequence, the cumulative instability energy value of each shear rate sequence, the vertical index of the optimal shear rate sequence, and the convective triggering intensity value of the optimal shear rate sequence; among them, the vertical index range of all effective shear rate sequences at each grid point is expressed as ; the convective triggering intensity value of the optimal shear rate sequence is expressed as ;

[0099] S620. When there is an index of an effective shear rate sequence at a grid point, it indicates that the grid point has the possibility of associated convective triggering; the convective triggering intensity value of the shear sequence indicates the quality of the associated convective triggering conditions of the grid

[0100] S630. Plot the convective triggering intensity of the shear sequence as scatter points on the forecast reflectivity image as the precursor signal of the associated convective warning

[0101] In this embodiment, two cases of the associated convection upstream of the bow echo on June 5, 2016 and the associated convection downstream of the bow echo on June 13, 2018 are used to verify the effectiveness of the bow echo associated convection warning method of the present invention. Among them, the filled color is the forecast composite reflectivity, and the gray-scale scatter points are the associated convective potential forecast products

[0102] The case of the associated convection upstream of the bow echo on June 5, 2016 shows that from 19:00 to 20:00, as shown in Figure 3 (a) in Figure 3 and Figure 3 (b) in Figure 3 , the scattered convection at the rear of the bow echo has an obvious dissipation trend, while the potential forecast product represented by the scatter distribution shows an increasing trend. From 21:00 to 22:00, as shown in (c) in

[0103] Figure 4 (a) in Figure 4 and Figure 4 (c) in Figure 4As shown in Figure (d), two linear convections are successively triggered downstream of the system, and the triggering positions are basically the same as the potential forecast positions. It can be seen that this early warning method has good early warning and forecasting effects on the triggering of the convections associated with the bow echo downstream.

[0104] Embodiment 2: This embodiment provides a non-transitory computer-readable storage medium, on which computer instructions are stored, and the computer instructions cause the computer to execute the method for warning the convections associated with the bow echo. The method includes the following steps:

[0105] S100. Receive the input of multi-dimensional meteorological forecast data;

[0106] S200. Use the central difference method to calculate the vertical shear rate of the radial wind, the vertical shear rate of the zonal wind, the accumulated convective instability energy, and the free lifting height grid by grid;

[0107] S300. Analyze the vertical shear rate data of each horizontal grid point, and use the sliding window method to detect the vertical shear layer that meets the conditions;

[0108] S400. Perform thermal parameter coupling and verification on the selected shear rate sequence. The thermal parameters include the accumulated convective instability energy and the top height of the shear rate sequence;

[0109] S500. For multiple eligible shear rate sequences that may appear in each grid, perform optimal window selection, remove the intervals completely included by other shear sequences, and select the sequence with the largest product as the final output;

[0110] S600. Plot the convective triggering intensity of the final output shear sequence as scatter points on the forecast reflectivity image to form a warning and forecast product for the associated convections.

[0111] Embodiment 3: This embodiment provides an electronic device, which may include: a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete mutual communication through the communication bus. The processor can call the logical instructions in the memory to execute the method for warning the convections associated with the bow echo. The method includes the following steps:

[0112] S100. Receive the input of multi-dimensional meteorological forecast data;

[0113] S200. Use the central difference method to calculate the vertical shear rate of the radial wind, the vertical shear rate of the zonal wind, the accumulated convective instability energy, and the free lifting height grid by grid;

[0114] S300. Analyze the vertical shear rate data of each horizontal grid point, and use the sliding window method to detect the vertical shear layers that meet the conditions;

[0115] S400. Perform thermal parameter coupling and verification on the selected shear rate sequences, where the thermal parameters include the accumulated convective instability energy and the height of the top layer of the shear rate sequence;

[0116] S500. For multiple shear rate sequences that may appear in each grid, perform optimal window selection, eliminate the intervals completely included by other shear sequences, and select the sequence with the largest product as the final output;

[0117] S600. Plot the convective triggering intensity of the finally output shear sequence as scatter points on the forecast reflectivity image to form an associated convective warning and forecast product.

[0118] In addition, when the logical instructions in the above-mentioned memory are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0119] Embodiment 4: What this embodiment provides is a computer program product. The computer program product includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the method for warning associated convection of bow echo, and this method includes the following steps:

[0120] S100. Receive the input of multi-dimensional meteorological forecast data;

[0121] S200. Use the central difference method to calculate the vertical shear rate of the radial wind, the vertical shear rate of the zonal wind, the accumulated convective instability energy, and the free lifting height grid by grid;

[0122] S300. Analyze the vertical shear rate data of each horizontal grid point, and use the sliding window method to detect the vertical shear layers that meet the conditions;

[0123] S400. Perform thermal parameter coupling and verification on the selected shear rate sequences. The thermal parameters include the accumulated convective instability energy and the top height of the shear rate sequence.

[0124] S500. For multiple eligible shear rate sequences that may occur in each grid, perform optimal window selection, eliminate the intervals completely included by other shear sequences, and select the sequence with the largest product as the final output.

[0125] S600. Plot the convective triggering intensity of the finally output shear sequence as scatter points on the forecast reflectivity image to form an associated convective warning and forecast product.

[0126] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative labor.

[0127] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0128] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An early warning method for convections associated with bow echoes, characterized in that, It includes the following steps: S100. Receive the input of multi-dimensional meteorological forecast data; S200. Use the central difference method to calculate the vertical shear rate of radial wind, the vertical shear rate of zonal wind, the cumulative convective instability energy, and the free lifting height grid by grid; S300. Analyze the vertical shear rate data of each horizontal grid point, and use the sliding window method to detect the vertical shear layer that meets the conditions; S400. Perform thermal parameter coupling and verification on the selected shear rate sequence, where the thermal parameters include the cumulative convective instability energy and the top height of the shear rate sequence; S500. For multiple eligible shear rate sequences that may appear in each grid, perform optimal window selection, eliminate the intervals completely included by other shear sequences, and select the sequence with the largest product as the final output; S600. Plot the convective trigger intensity of the final output shear sequence as scatter points on the forecast reflectivity image to form an associated convective warning forecast product.

2. The bow echo associated convection warning method according to claim 1, wherein The multi-dimensional meteorological forecast data described in step S100 are multi-dimensional elements of the mesoscale model forecast field of the meteorological department, including at least three-dimensional radial wind, zonal wind, temperature, humidity, air pressure, convective instability energy, and two-dimensional free lifting height.

3. The bow echo associated convection warning method according to claim 1, wherein In step S200, the vertical shear rate of radial wind represents the second-order derivative matrix of the radial wind speed in the vertical direction, and the calculation formula is: ； The vertical shear rate of zonal wind represents the second-order derivative matrix of the zonal wind speed in the vertical direction, and the calculation formula is: ； The accumulated convective instability energy is a physical quantity matrix reflecting the instability of the atmospheric layer structure, expressed as ; The free lifting height is a two-dimensional field used to characterize the critical height of convective triggering, expressed as ; Among them, is the partial derivative symbol, is the wind speed of the radial wind, is the wind speed of the zonal wind, represents the accumulated convective instability energy of the height layer, is the free lifting height, represents the vertical shear rate of the radial wind, represents the vertical shear rate of the zonal wind, is the zonal grid, is the radial grid, is the height layer.

4. The bow echo associated convection warning method according to claim 3, wherein The analysis of the vertical shear rate data of each horizontal grid point described in step S300, and the use of the sliding window method to detect the vertical shear layer that meets the conditions specifically includes: S310. Grid by grid (y, x), start expanding the window upward from height layer i, and the sliding window is represented as [i, j], where i starts from the bottom layer to the top layer, and j ≥ i; S320. Calculate the average radial wind shear rate within the window , and the average zonal wind shear rate ; S330. When the window thickness reaches the minimum threshold m, perform validity verification on the shear rate sequence within the window.

5. The bow echo associated convective warning method according to claim 4, wherein The validity verification of the shear rate sequence within the window in step S330 includes: S331. Perform a normal distribution test on the shear rate sequence within the window area, and the calculation formula is: ； ； By the condition that or ; Indicates the Shapiro-Wilk normality test; and are respectively the Shapiro-Wilk normality test statistic and the significance probability value of the radial wind within the window; and are respectively the Shapiro-Wilk normality test statistic and the significance probability value of the zonal wind within the window; is the significance level; S332. Verify the average shear rate of the shear rate sequence in the window area. The passing condition is , where n is the minimum value of the average shear rate of the shear rate sequence; S333. Verify the thickness of the shear rate sequence in the window area, and the passing condition is , where Z is the vertical terrain height.

6. The bow echo associated convection warning method according to claim 4, characterized in that, The thermal parameter coupling and verification of the selected shear rate sequence described in step S400 specifically includes: S410. Verify the accumulated unstable energy of the screened shear rate sequence. The passing condition is , where represents the convective unstable energy of the height level, is the minimum value of the accumulated convective unstable energy; S420. Verify the top height of the selected shear rate sequence layer. The passing condition is .

7. The bow echo associated convective warning method according to claim 4, wherein The optimal window selection for multiple eligible shear rate sequences that may appear in each grid described in step S500, eliminating the intervals completely included by other shear sequences, and selecting the sequence with the largest product as the final output; specifically includes: S510. Remove intervals that are completely contained by other shear sequences from all valid window sets, expressed as: ​ ； Among them, is the height index of any sequence other than the target sequence in the set R, and are its bottom and top height indexes respectively; S520. Select the sequence with the largest product of the average shear rate and the cumulative convective instability energy from the remaining candidate sequences as the final output, which is expressed as: ； ； Among them, is the convective triggering intensity value of the optimal shear rate sequence, is the height index corresponding to the convective triggering intensity value of the optimal shear rate sequence.

8. The bow echo associated convection warning method according to claim 7, characterized in that Step S600 plots the convective trigger intensity of the final output shear sequence as scatter points on the forecast reflectivity image to form an associated convective warning forecast product; specifically includes: S610. Output the associated convective early warning and forecasting product elements, including the vertical index range of all valid shear rate sequences at each grid point, the average shear rate value of the corresponding shear rate sequence, the cumulative unstable energy value of each shear rate sequence, the vertical index of the optimal shear rate sequence, and the convective triggering intensity value of the optimal shear rate sequence; among them, the vertical index range of all valid shear rate sequences at each grid point is expressed as ; the convective triggering intensity value of the optimal shear rate sequence is expressed as ; S620. When there is an index of a valid shear rate sequence at the grid point, it indicates that there is a possibility of associated convective trigger at this grid point; the convective trigger intensity value of the shear sequence indicates the quality of the associated convective trigger condition at this grid; S630. Plot the convective trigger intensity of the shear sequence as scatter points on the forecast reflectivity image as the precursor signal of the associated convective warning.

9. A non-transitory computer-readable storage medium, characterized in that, It stores computer instructions that cause a computer to execute the bow echo associated convective warning method described in any one of claims 1-8.

10. An electronic device, characterized in that, Including: A processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete mutual communication through the communication bus. The processor calls the logical instructions in the memory to execute the bow echo associated convective warning method described in any one of claims 1-8.

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