Air-ground fusion thunderstorm weather influence intensity quantitative evaluation method

Abstract

According to the air-ground fusion thunderstorm weather influence intensity quantitative evaluation method provided by the invention, an ATMAP meteorological algorithm is adopted for an airport scene thunderstorm weather index, and the ground thunderstorm weather intensity is graded by analyzing an METAR message, so that the ground thunderstorm weather intensity is quantified. According to the air thunderstorm intensity index, a specific direction convective weather airspace blocking probability model is used, terminal area meteorological radar data is used as data, the probability that the traffic flow is blocked in all directions in thunderstorm weather is obtained, and the air thunderstorm weather intensity is quantified. And finally, respectively carrying out data normalization processing and arithmetic averaging on the ground thunderstorm intensity and the air thunderstorm intensity to obtain a thunderstorm influence intensity index. The index can reflect the overall influence of thunderstorm weather on airport operation in real time, and provides a scientific basis for airport operation management.

Description

Technical Field

[0001] The present invention belongs to the technical field of air-ground integration, and in particular relates to a method for quantitatively evaluating the influence intensity of thunderstorm weather in air-ground integration. Background Art

[0002] As the hub of the air transportation network, the safety and efficiency of airport operations have been increasingly emphasized. It can be seen from the Civil Aviation Industry Development Statistical Bulletin from 2019 to 2023 that among the reasons for the abnormal flights of airlines, the proportion of weather is 46.49%, 57.31%, 59.56%, 67.14%, and 60.42% respectively. Among them, thunderstorm weather has a non-negligible impact on airport flight operations due to its characteristics such as many associated weather conditions, large impact of thunderstorm clouds on airspace operations, and difficulty in quantifying intensity. Thunderstorm weather not only causes flight delays and cancellations, but may even lead to safety accidents, bringing great challenges to airport operations. The impact of airport operations on different thunderstorm processes varies greatly. Therefore, quantifying the influence intensity of thunderstorm weather has become an urgent problem in the current aviation industry.

[0003] Thunderstorm processes are often accompanied by ground weather phenomena such as heavy precipitation and thunderstorm gales, and such weather can be far from the main body of the thunderstorm. For example, the gust front can reach more than 20 km away; the thunderstorm also has a certain influence area in the air, and the range of its main body strictly prohibits aircraft from entering, which will affect the operation of aircraft in the airspace. At the same time, the non-linear characteristics of the thunderstorm itself, the complex relationship between meteorological elements, and the complexity of thunderstorm disasters have greatly increased the difficulty of quantitatively representing the thunderstorm influence. To quantify the impact of weather on air traffic, scholars have proposed various weather intensity assessment methods from multiple perspectives such as air routes, airspace, and airports. There are many research results on the impact of weather on air traffic. The existing technologies mainly rely on the analysis of a single data source, such as METAR messages or air radar data. Although these methods can reflect the characteristics of thunderstorm weather to a certain extent, they have obvious limitations. First, the analysis of a single data source cannot comprehensively reflect the overall impact of thunderstorm weather on airport operations. Second, most of the existing methods are qualitative analyses, lacking quantitative indicators for the influence intensity of thunderstorms, and it is difficult to accurately measure the degree of interference of thunderstorm weather on airport operations. In addition, most of the existing assessment methods are static analyses and cannot reflect the dynamic changes of thunderstorm weather in real time, making it difficult to meet the dynamic decision-making needs of airports under complex meteorological conditions. Summary of the Invention

[0004] In view of this, the present invention aims to overcome the deficiencies of the above problems in the prior art, and proposes a method for quantitatively evaluating the impact intensity of thunderstorm weather in the integration of air and ground. By combining the ground thunderstorm weather index (based on the ATMAP algorithm) and the air thunderstorm intensity index (based on the specific direction convective weather airspace blocking probability model), it makes up for the deficiency of the existing method that only relies on a single data source, realizes the integrated air-ground evaluation of the impact of thunderstorm weather, develops an evaluation index that can quantify the impact intensity of thunderstorm weather, integrates the thunderstorm intensity data on the ground and in the air into the thunderstorm impact intensity index through data normalization processing and arithmetic mean, improves the accuracy and scientific nature of the evaluation, and realizes the dynamic monitoring and real-time evaluation of the impact intensity of thunderstorm weather based on real-time METAR messages and radar meteorological data, providing real-time and accurate decision-making support for airport operation management.

[0005] To achieve the above object, the technical solution of the present invention is realized as follows:

[0006] The first aspect of the present invention provides a method for quantitatively evaluating the impact intensity of thunderstorm weather in the integration of air and ground, including the following steps:

[0007] Step 1: Use the ATMAP meteorological algorithm to parse the airport METAR message, extract key meteorological elements, and perform quantitative assignment according to their severity to obtain the ground thunderstorm weather index;

[0008] Step 2: Utilize the terminal area meteorological radar data, combine the specific direction convective weather airspace blocking probability model, and quantify the air thunderstorm intensity through grid processing and reflectivity threshold analysis to obtain the air thunderstorm intensity index;

[0009] Step 3: Normalize the thunderstorm intensity data on the ground and in the air, and calculate their arithmetic mean to obtain the thunderstorm impact intensity index.

[0010] Further, the specific content of Step 1 includes:

[0011] Step (101): Select the hourly data of all METAR messages of the airport during the thunderstorm occurrence process;

[0012] Step (102): Extract visibility, cloud height, wind speed, precipitation, freezing, and hazardous weather information;

[0013] Step (103): Analyze the extracted key information according to the ATMAP algorithm, and assign values to the severity of 5 types of meteorological elements including low cloud and low visibility, wind speed, precipitation, freezing, and hazardous weather respectively.

[0014] Further, the specific content of Step (103) includes:

[0015] Classify the impact levels of different levels of meteorological elements using severity codes to identify different levels of meteorological conditions;

[0016] Introduce coefficients to score the severity of each type of meteorological element;

[0017] Finally, sum up the scores of 5 types of meteorological elements to obtain the weather score at that moment;

[0018] δ t =V t +W t +P t +F t +D t (1)

[0019] Where V t is the visibility coefficient, W t is the wind speed coefficient, P t is the precipitation coefficient, F t is the freezing condition coefficient, D t is the hazardous weather coefficient, and δ t is the ATMAP weather score at time t.

[0020] Furthermore, the specific steps of step 2 include:

[0021] Step (201): Obtain the airport radar echo data and perform threshold processing on the radar reflectivity;

[0022] Step (202): Use the geographical location of the airport as the center point, and starting from 0° with magnetic north as the reference, draw a scanning line every 15°;

[0023] Step (203): Perform grid processing on the scanning lines and combine the gridded areas with the filtered radar meteorological echo map;

[0024] Step (204): Scan all the grids covering the terminal area airspace, scan the number of grids with reflectivity within the set value range, and evaluate the airspace blockage probability based on this;

[0025] Step (205): Assume that there are n effective scanning lines in the designated airspace range, divide the grid with m unit length, and the airspace blockage probability of each grid is φ ij , then the blockage probability ε t of the terminal area airspace at time t is:

[0026]

[0027] The size of m is related to the size of the divided grid. The larger the ε t value, the stronger the impact of the weather on the airspace at that moment.

[0028] Further, in step 3, the formula (3) min-max normalization method is used to map the data to the range of 0-1. The constructed thunderstorm impact intensity index is the average value of the normalized ATMAP score and the blocking probability.

[0029]

[0030] The second aspect of the present invention provides a ground-air integrated thunderstorm weather impact intensity quantification and evaluation device, including:

[0031] A first data processing unit, configured to parse the airport METAR message using the ATMAP meteorological algorithm, extract key meteorological elements, and perform quantitative assignment according to their severity to obtain a ground thunderstorm weather index;

[0032] A second data processing unit, configured to utilize terminal area meteorological radar data, combine with a specific direction convective weather airspace blocking probability model, and through grid processing and reflectivity threshold analysis, quantify the intensity of in-air thunderstorms to obtain an in-air thunderstorm intensity index;

[0033] A third data processing unit, configured to normalize the ground and in-air thunderstorm intensity data and calculate their arithmetic mean to obtain a thunderstorm impact intensity index.

[0034] The third aspect of the present invention provides an electronic device, including a processor and a memory communicatively connected to the processor and used for storing executable instructions of the processor. The processor is configured to execute the above-mentioned ground-air integrated thunderstorm weather impact intensity quantification and evaluation method.

[0035] The fourth aspect of the present invention provides a computer-readable storage medium, storing a computer program, and when the computer program is executed by a processor, it implements the above-mentioned ground-air integrated thunderstorm weather impact intensity quantification and evaluation method.

[0036] Compared with the prior art, the ground-air integrated thunderstorm weather impact intensity quantification and evaluation method of the present invention has the following advantages:

[0037] In the evaluation of ground thunderstorm weather intensity, the present invention applies the ATMAP meteorological algorithm. This algorithm objectively and comprehensively measures the intensity of ground thunderstorm weather by analyzing key meteorological information in the METAR message, such as low clouds, low visibility, wind speed, precipitation, icing, and hazardous weather. At the same time, in order to further improve the accuracy of the evaluation, coefficients are introduced to score the severity of each type of meteorological element, thereby realizing the fine quantification of ground thunderstorm weather intensity.

[0038] In the evaluation of in-air thunderstorm intensity, this patent uses a specific-direction convective weather airspace blockage probability model to perform fitting analysis on the radar meteorological echo map and the terminal control plane range, enabling accurate assessment of the degree of airspace affected by weather, thereby quantifying the intensity of in-air thunderstorm weather. In the specific implementation process, this invention also realizes the accurate calculation of airspace blockage probability through steps such as data processing, determination of scan lines and scan reference lines, grid division, and determination of airspace blockage probability.

[0039] This invention combines the ground thunderstorm weather index (based on the ATMAP algorithm) and the in-air thunderstorm intensity index (based on the specific-direction convective weather airspace blockage probability model), performs data normalization processing and arithmetic averaging on the ground thunderstorm intensity and in-air thunderstorm intensity, and constructs a thunderstorm impact intensity index. This method can not only quantify the intensity of ground thunderstorm weather but also evaluate the probability of air traffic flow being blocked in each direction, thus comprehensively reflecting the overall impact of thunderstorm weather on airport operations. This method not only breaks through the limitation of traditional thunderstorm weather impact assessment that only relies on a single ground or in-air data source, realizes the organic integration of ground and air data, but also provides new technical means and solutions for aviation safety management, helping to improve the safety of airport flight operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The drawings constituting a part of this invention are used to provide a further understanding of this invention. The schematic embodiments of this invention and their descriptions are used to explain this invention and do not constitute an improper limitation to this invention. In the drawings:

[0041] Figure 1 is a schematic flow chart of a method for quantifying the impact intensity of thunderstorm weather with ground-air integration according to this invention;

[0042] Figure 2 is a schematic diagram for quantifying the intensity of ground thunderstorm weather in the embodiment of this invention;

[0043] Figure 3 is the radar echo map in the embodiment of this invention;

[0044] Figure 4 is the filtered radar echo map in the embodiment of this invention;

[0045] Figure 5 is a schematic diagram of the scan reference line in the embodiment of this invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0046] It should be noted that, without conflict, the embodiments in this invention and the features in the embodiments can be combined with each other.

[0047] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "center", "longitudinal", "transverse", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention. In addition, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first", "second", etc. may explicitly or implicitly include one or more of such features. In the description of the present invention, unless otherwise specified, the meaning of "a plurality of" is two or more.

[0048] In the description of the present invention, it should be noted that unless otherwise clearly specified and limited, the terms "installation", "connection", and "coupling" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood through specific circumstances.

[0049] The present invention will be described in detail below with reference to the drawings and in conjunction with embodiments.

[0050] Embodiment 1:

[0051] As Figure 1 shown, the present invention provides a method for quantitatively evaluating the impact intensity of thunderstorm weather in the integration of air and ground, including the following steps:

[0052] Step 1: Use the ATMAP meteorological algorithm to parse the airport METAR message, extract key meteorological elements, and perform quantitative assignment according to their severity to obtain the ground thunderstorm weather index;

[0053] Step 2: Utilize the terminal area meteorological radar data, combine with the specific direction convective weather airspace blockage probability model, and through grid processing and reflectivity threshold analysis, quantify the intensity of the airborne thunderstorm to obtain the airborne thunderstorm intensity index;

[0054] Step 3: Normalize the thunderstorm intensity data on the ground and in the air, and calculate their arithmetic mean to obtain the thunderstorm impact intensity index.

[0055] In step 1 of the present invention, the ATMAP weather algorithm is used to objectively and comprehensively measure the ground weather intensity as Figure 2As shown in the figure, specifically including:

[0056] (1) Select the hourly data of all METAR messages at the airport during the thunderstorm occurrence process, which usually includes wind information, visibility, runway visual range, weather phenomena, cloud layer, temperature / dew point, etc.

[0057] (2) Extract the date, airport code, visibility cloud height, wind speed, precipitation, freezing, and hazardous weather information to prepare for subsequent data processing and calculation.

[0058] (3) Analyze the extracted key information according to the ATMAP algorithm, and assign values to the severity levels of 5 types of meteorological elements, namely low cloud and low visibility, wind speed, precipitation, freezing, and hazardous weather. First, use the severity code to classify the influence levels of different levels of meteorological elements to identify different levels of meteorological conditions. Second, since the severity code cannot describe the non-linear change of meteorological phenomena, a coefficient is introduced to score the severity of each type of meteorological element; finally, sum up the scores of the 5 types of meteorological elements to obtain the weather score at this moment.

[0059] δ t =V t +W t +P t +F t +D t (1)

[0060] Among them, V t is the visibility coefficient, W t is the wind speed coefficient, P t is the precipitation coefficient, F t is the freezing condition coefficient, D t is the hazardous weather coefficient, δ t is the ATMAP weather score at time t, as shown in Table 1.

[0061] Table 1

[0062]

[0063] In step 2 of the present invention, the radar meteorological echo map is fitted and analyzed with the terminal control plane range, and the specific direction convective weather airspace blockage probability model is used to accurately evaluate the degree of influence of the airspace by the weather, so as to quantify the intensity of in-air thunderstorm weather. Specifically including:

[0064] (1) Data processing

[0065] Taking the airport as the geometric center, restricting the range of longitude and latitude. Using the 10-minute data of the combined radar reflectivity factor at the airport as the data source.

[0066] To simplify radar data, threshold processing is performed on the reflectivity. Values of reflectivity less than 18 dBZ are set to 0 dBZ; values greater than or equal to 18 dBZ and less than 41 dBZ are set to 18 dBZ; values greater than or equal to 41 dBZ are set to 41 dBZ, thereby obtaining a filtered radar echo map. The area shown by the red dashed line is the planar range of the terminal area airspace, the area shown by the black dashed line is the sector, and the red dots are waypoints, as Figure 3 、 4 shown.

[0067] (2) Determination of scan lines and scan reference lines

[0068] Taking the geographical location of the airport as the center point, with magnetic north as the reference, starting from 0°, a scan line is made every 15°. The area shown by the dashed line is the planar range of the terminal area airspace. There are a total of 12 scan reference lines (the scan lines in opposite directions are regarded as the same reference line. For example, the 0° and 180° scan lines are the same scan reference line).

[0069] (3) Grid division

[0070] On the basis of determining the scan lines and scan reference lines, grid processing is carried out. The grid division is carried out at 0.1°. 1.5° can completely cover the entire terminal area airspace. Therefore, a total of 24×15 small grids are divided, and the grid area is combined with the filtered radar meteorological echo map to analyze the weather intensity within the grid. The scan reference lines are as Figure 5 shown.

[0071] (4) Judgment of airspace blockage probability

[0072] Whether an aircraft is blocked by weather in the airspace depends on the highest weather intensity situation within the grid. Scan all the grids covering the terminal area airspace, respectively scan out the number of grids with the highest reflectivity of 18 dBZ or 41 dBZ, and use this to evaluate the airspace blockage probability.

[0073] If the highest weather intensity value λ within the grid is less than the critical value ξ1, that is, λ<ξ1, φ i =0, the aircraft will not be blocked; if λ is greater than or equal to the critical value ξ1 and less than ξ2, that is, ξ1≤λ<ξ2, φ i =0.5, the aircraft has a 50% probability of being blocked; if λ is greater than or equal to the critical value ξ2, that is, λ≥ξ2, φ i =1, the aircraft will be blocked, where ξ1 corresponds to the reflectivity of 18 dBZ and ξ2 corresponds to the reflectivity of 41 dBZ. Among them, the airspace blockage probability φ i is defined as shown in Table 2.

[0074] Table 2

[0075]

[0076] (5) Calculation of airspace blockage probability

[0077] Assume that there are n effective scan lines in the defined airspace range, and the grid is divided with a unit length of m. The airspace blockage probability of each grid is φ ij , then the blockage probability ε of the terminal area airspace at time t t is as follows:

[0078]

[0079] The size of m is related to the size of the defined grid. The larger the ε t value is, the stronger the influence of weather on the airspace at this moment.

[0080] In step 3 of the present invention, in order to scale the obtained ground thunderstorm intensity and airborne thunderstorm intensity values to the same interval and improve the accuracy, the formula (3) min-max normalization method is used to map the data to between 0 and 1. The constructed thunderstorm influence intensity index is the average value of the normalized ATMAP score and the blockage probability, as shown in formula (4).

[0081] The thunderstorm intensity index combining ground and air evaluates the intensity of thunderstorms by comprehensively considering ground and airborne data, which is more comprehensive and accurate than the method that simply relies on airport weather scores or airborne blockage probabilities, and can also more accurately evaluate the resilience of airport flight operations under the influence of thunderstorms.

[0082]

[0083] Among them, x i is the data to be normalized, x min is the minimum value in the data, x max is the maximum value in the data, is the ATMAP score after normalization at time t, is the blockage probability after normalization at time t, ω t is the thunderstorm influence intensity index at time t.

[0084] Embodiment 2:

[0085] The present invention provides a device for quantitatively evaluating the influence intensity of thunderstorm weather in the integration of air and ground, including:

[0086] The first data processing unit is used to use the ATMAP meteorological algorithm to score the ground thunderstorm weather intensity by analyzing the METAR message and quantify the ground thunderstorm weather intensity;

[0087] A second data processing unit, which is used to apply a specific-direction convective weather airspace blockage probability model, take the terminal area meteorological radar data as materials, obtain the probabilities of traffic flow being blocked in each direction under thunderstorm weather, and quantify the intensity of in-air thunderstorm weather;

[0088] A third data processing unit, which is used to perform data normalization processing and arithmetic averaging on the ground thunderstorm intensity and the in-air thunderstorm intensity respectively to obtain a thunderstorm impact intensity index.

[0089] Embodiment 3:

[0090] The present invention provides an electronic device, including a processor and a memory communicatively connected to the processor and used to store executable instructions of the processor, where the processor is used to execute the above-mentioned method for quantifying and evaluating the impact intensity of thunderstorm weather with air-ground integration.

[0091] Embodiment 4

[0092] The present invention provides a computer-readable storage medium storing a computer program, where when the computer program is executed by a processor, it implements the above-mentioned method for quantifying and evaluating the impact intensity of thunderstorm weather with air-ground integration.

[0093] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for quantitatively evaluating the impact intensity of thunderstorm weather by integrating air and ground, characterized in that: The steps include: Step 1: Use the ATMAP meteorological algorithm to parse the airport METAR message, extract key meteorological elements, and quantify and assign values ​​according to their severity to obtain the ground thunderstorm weather index; Step 2: Using the terminal area weather radar data, combined with the blocking probability model of convective weather airspace in a specific direction, the intensity of the air thunderstorm is quantified through grid processing and reflectivity threshold analysis to obtain the air thunderstorm intensity index; Step 3: Normalize the ground and air thunderstorm intensity data and calculate their arithmetic mean to obtain the thunderstorm impact intensity index.

2. The method for quantitatively evaluating the impact intensity of thunderstorm weather by integrating air and ground according to claim 1 is characterized in that: The step 1 specifically includes: Step (101): selecting hourly data of all METAR messages of the airport during the thunderstorm; Step (102): extracting visibility, cloud height, wind speed, precipitation, freezing and dangerous weather information; Step (103): Analyze the extracted key information according to the ATMAP algorithm, and assign values ​​to the severity of five meteorological elements: low cloud and low visibility, wind speed, precipitation, freezing and dangerous weather.

3. The method for quantitatively evaluating the impact intensity of thunderstorm weather by integrating air and ground according to claim 2 is characterized in that: The step (103) specifically includes: Severity codes are used to classify the impact of different levels of meteorological elements and to identify different levels of meteorological conditions; Introduce coefficients to score the severity of each type of meteorological element; Summarize the scores of the five meteorological elements to get the weather score at that moment; δ t =V t +W t +P t +F t +D t (1) Where V t is the visibility coefficient, W t is the wind speed coefficient, P t is the precipitation coefficient, F t is the freezing condition coefficient, D t is the dangerous weather coefficient, δ t is the ATMAP weather score at time t.

4. The method for quantitatively evaluating the impact intensity of thunderstorm weather by integrating air and ground according to claim 1 is characterized in that: The step 2 specifically includes: Step (201): acquiring airport radar echo data and performing threshold processing on radar reflectivity; Step (202): Taking the geographical location of the airport as the center point and magnetic north as the reference, starting from 0°, a scanning line is made every 15°; Step (203): gridding the scan lines and combining the gridded area with the filtered radar weather echo map; Step (204): Scan all grids covering the airspace of the terminal area, scan out the number of grids whose reflectivity is within the set value range, and use this to evaluate the airspace blocking probability; Step (205): Assume that the designated airspace has n valid scan lines, and is divided into grids with m unit lengths. The airspace blocking probability of each grid is φ ij , then the blocking probability ε of the terminal area airspace at time t t for: The size of m is related to the size of the grid. t The larger the value is, the more the airspace is affected by the weather at that moment.

5. The method for quantitatively evaluating the impact intensity of thunderstorm weather by integrating air and ground according to claim 1 is characterized in that: In step 3, the data is mapped to a value between 0 and 1 using the maximum value normalization method of formula (3). The constructed thunderstorm impact intensity index is the average value of the normalized ATMAP score and the blocking probability.

6. An air-ground integrated thunderstorm weather impact intensity quantitative assessment device, characterized in that: include: The first data processing unit is used to parse the airport METAR message using the ATMAP meteorological algorithm, extract key meteorological elements, and quantify and assign values ​​according to their severity to obtain a ground thunderstorm weather index; The second data processing unit is used to quantify the intensity of air thunderstorms by using the terminal area meteorological radar data, combined with the blocking probability model of convective weather airspace in a specific direction, through grid processing and reflectivity threshold analysis, to obtain an air thunderstorm intensity index; The third data processing unit is used to normalize the thunderstorm intensity data on the ground and in the air, and calculate the arithmetic mean thereof to obtain the thunderstorm impact intensity index.

7. An electronic device, comprising a processor and a memory connected to the processor for storing instructions executable by the processor, characterized in that: The processor is used to execute the air-ground integrated thunderstorm weather impact intensity quantitative assessment method described in any one of claims 1-5 above.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for quantitatively evaluating the intensity of thunderstorm weather impact by integrating air and ground as described in any one of claims 1 to 5 is implemented.

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