A meteorological early warning method and computer device for control operation

Abstract

The present invention relates to the field of meteorological warning, and specifically to a meteorological warning method and computer device for control operation, which greatly improves the accuracy of meteorological warning. The method includes: according to the control operation requirements, screening out routes, navigation points and terminal areas, and pre-processing the routes, navigation points and terminal areas; reading the hourly echo reflectivity forecast data DBZ with a set time forecast validity; using a statistical algorithm to perform quality control on DBZ, correcting the control area, and standardizing the corrected DBZ to form new data; processing the new data, and performing graded warnings on route weather, graded warnings on navigation point weather, and graded warnings on terminal area coverage. The present invention is suitable for meteorological warnings for control operation.

Description

Technical Field

[0001] The present invention relates to the field of meteorological warning, and in particular to a meteorological warning method and a computer device for controlling operation. Background Art

[0002] In recent years, the main factor causing flight delays is still the severe convective weather in summer, among which thunderstorms, heavy rainfall, strong winds and other weather have the greatest impact. At present, the response level of large-scale flight delays is divided into three levels: yellow, orange and red. When the operation support capability decreases by more than 25%, a yellow warning is issued; when the operation support capability decreases by more than 50%, an orange warning is issued; when the operation support capability decreases by more than 75%, a red warning is issued. According to the warning, the control department will reduce flights in advance, with 25% of flights reduced for the yellow level, 50% of flights reduced for the orange level, and 75% of flights reduced for the red level. The level of warning issued for large-scale flight delays still depends on the subjective judgment of the traffic department. The judgment of the traffic department is mainly based on the MDRS (Massive Delay Response System, large-scale flight delay response mechanism) probability warning product issued by the meteorological department.

[0003] At present, the meteorological department's MDRS probability warning product still relies on subjective grading, which is divided into three levels: less than 30%, 30-40%, and greater than 70%. This probability grading has no objective basis. It only indicates the probability of weather occurrence, and does not reflect the weather intensity, let alone the corresponding warning level of large-scale flight delays. This probability warning product relies on the forecaster's confidence index and subjective judgment of weather intensity. Since the grading is not evaluated based on the impact of traffic release and aircraft detours under severe convective weather, it is difficult for traffic departments and control departments to directly use MDRS probability warning products to determine the response level of large-scale flight delays. They still need to issue response levels based on work experience, which greatly affects the accuracy of meteorological warnings. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a weather warning method for control operations, which greatly improves the accuracy of weather warnings and can provide an accurate basis for control and traffic departments to respond to large-scale flight delays.

[0005] The present invention adopts the following technical solutions to achieve the above-mentioned purpose. In a first aspect, the present invention provides a meteorological early warning method for control operation, comprising:

[0006] S1. According to the control operation requirements, the routes, navigation points and terminal areas are screened out, and the routes, navigation points and terminal areas are pre-processed to form a text file with longitude and latitude positions;

[0007] S2, reading the hourly echo reflectivity forecast data of the set time forecast validity;

[0008] S3. Use statistical algorithms to perform quality control on the echo reflectivity forecast data, revise the control area, and standardize the revised echo reflectivity forecast data to form new data;

[0009] S4. Based on the new data, calculate the average value a of the new data of the route segment and the maximum value b of the new data of the route segment, and construct the first variable c, where c=k×a×b, k is the expected incremental ratio of the flow of the route segment. Combined with the first threshold of c that has an impact on the control operation when the historical control operation data statistics are combined, an hourly route weather graded warning is issued according to the first threshold.

[0010] Furthermore, the default value of k is 1. If the planned flight flow is reduced by more than 25% due to non-weather reasons, k is assigned a value of 0.7. If the planned flight flow increases by more than 20% due to other reasons, k is assigned a value of 1.3. The classification judgment method of route warnings that affect control operations is: if c is greater than or equal to 0.21, it is the first warning value; c is greater than or equal to 0.15 and less than 0.21, it is the second warning value; the rest is the third warning value, the impact of the first warning value is greater than the impact of the second warning value, and the impact of the second warning value is greater than the impact of the third warning value.

[0011] Furthermore, step S4 further includes:

[0012] Based on the new data, the average value m of the new data within the set distance range of each navigation point and the maximum value n of the new data within the range are calculated to construct the second variable y, where y=h×m×n, h is the expected traffic increase ratio of the navigation point, and the second threshold of y when the historical control operation data statistics have an impact on the operation is combined, and the navigation point weather graded warning is issued according to the second threshold.

[0013] The default value of h is 1. If the planned flight flow is reduced by more than 20% due to non-weather reasons, h is assigned a value of 0.7. If the planned flight flow increases by more than 15% due to other reasons, h is assigned a value of 1.3. The navigation point warning classification judgment method that affects the control operation is:

[0014] If y is greater than or equal to 0.25, it is the first warning value; if y is greater than or equal to 0.13 and less than 0.25, it is the second warning value; if y is less than 0.13, it is the third warning value. The impact of the first warning value is greater than that of the second warning value, and the impact of the second warning value is greater than that of the third warning value.

[0015] Furthermore, step S4 further includes:

[0016] Based on the new data, the ray method is used to calculate the area percentage w of each terminal area where the new data is greater than the set value, and the third variable f is constructed, where f=d×w, d is the expected increase ratio of the traffic in each terminal area. The third threshold of f is used when the historical control operation data statistics have an impact on the operation, and the terminal area coverage rate is graded and warned according to the third threshold.

[0017] The default value of d is 1. If the planned flight flow is reduced by more than 30% due to non-weather reasons, d is assigned a value of 0.7. If the planned flight flow increases by more than 25% due to other reasons, d is assigned a value of 1.3. The terminal area coverage rate warning classification judgment method that affects the control operation is as follows:

[0018] If f is greater than or equal to 20%, it is the first warning value; if f is greater than or equal to 5% and less than 20%, it is the second warning value; if f is less than 5%, it is the third warning value. The impact of the first warning value is greater than that of the second warning value, and the impact of the second warning value is greater than that of the third warning value.

[0019] Furthermore, step S2 specifically includes:

[0020] The hourly echo reflectivity forecast data of the SWC numerical model with a set time forecast validity is read through the MeteoInfoLab script, the echo reflectivity forecast data is converted and stored in netcdf format data, and then python is used to read the echo reflectivity forecast data in netcdf format.

[0021] Furthermore, step S3 specifically includes:

[0022] Evaluation and statistics are carried out according to different sectors of control, and the historical average error between the echo reflectivity value of SWC and the actual radar echo reflectivity is calculated. The echo reflectivity forecast data is corrected according to the historical average error, and the corrected echo reflectivity forecast data is standardized to form new data.

[0023] In a second aspect, the present invention provides a computer device, including a memory, wherein the memory stores program instructions, and when the program instructions are executed, the above-mentioned meteorological warning method for control operation is executed.

[0024] The beneficial effects of the present invention are:

[0025] The present invention selects routes, navigation points and terminal areas according to control operation requirements, pre-processes the routes, navigation points and terminal areas to form a text file with longitude and latitude positions, reads hourly echo reflectivity forecast data of a SWC numerical model with a set time forecast validity, uses a statistical algorithm to perform quality control on the echo reflectivity forecast data, corrects the control area, and standardizes the corrected echo reflectivity forecast data to form new data, and performs graded warnings on routes, navigation points and terminal areas that have an impact on control operations according to the new data, thereby greatly improving the accuracy of meteorological warnings and providing an accurate basis for control and traffic departments to respond to large-scale flight delays. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 The present invention provides a flow chart of a meteorological warning method for controlling operation. DETAILED DESCRIPTION

[0027] To make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0028] The present invention provides a meteorological early warning method for control operation, such as Figure 1 As shown, including:

[0029] S1. According to the control operation requirements, select the main routes, important navigation points and terminal areas; pre-process the routes, navigation points and terminal areas to form a text file with longitude and latitude positions. The pre-processing includes: segmenting the routes and zoning the terminal areas.

[0030] Specifically, route segments, terminal area divisions and important navigation points are formed through communication and research with control users. Each route is divided into several sections, each of which starts at an important navigation point; the terminal area is divided into several sub-areas based on the sector range of the terminal control user.

[0031] S2. Read the hourly echo reflectivity forecast data DBZ (Decibels of equivalent reflectivity) of the SWC numerical model with a forecast period of 36 hours.

[0032] Specifically, the format of the SWC numerical forecast model data is grib2 format, and the data volume is large. Directly using python to read the grib2 data takes a long time to calculate, which is inefficient. The present invention chooses to use the MeteoInfoLab script to read the DBZ variables of the SWC numerical model, and stores its variables separately as netcdf format data, and then uses python to read the DBZ data in netcdf format for related calculations, which greatly improves the calculation speed.

[0033] The SWC numerical forecast model refers to the Southwest Regional Numerical Forecast Model System (SouthWest Center-WRF ADASReal-time Modeling System, referred to as SWC-WARMS).

[0034] S3. Use statistical algorithms to perform quality control on DBZ, correct abnormally high values ​​in the controlled area, and standardize the corrected DBZ to form new data X.

[0035] Specifically, the error between the SWC echo reflectivity and the actual radar echo reflectivity is evaluated and calculated according to different sectors of control, and DBZ correction is performed based on the historical average error. According to statistical calculations, the error between the predicted DBZ and the actual DBZ in the southwest region is 8-12DBZ. The corrected DBZ is standardized using the formula (DBZ-DBZmin) / (DBZmax-DBZ) to form new data X.

[0036] S4. Based on the new data X, calculate the average value a of the new data X of the route segment and the maximum value b of the new data X of the route segment, and construct a variable c, where c=k*a*b, k is the expected incremental ratio of the flow of the route segment; combine the historical operation data statistics to determine the threshold of c when it has an impact on the operation, and issue a graded route weather warning based on the statistical threshold.

[0037] Specifically, k defaults to an estimated increase ratio of 1 for the route traffic. If the planned flight traffic decreases by more than 25% due to non-weather reasons, k is assigned a value of 0.7; if the flight volume increases by more than 20% due to important holidays or other reasons, k is assigned a value of 1.3; the route warning grading judgment method that affects the control operation is: c is greater than or equal to 0.21, the warning is assigned a value of R; c is greater than or equal to 0.15 and less than 0.21, the warning is assigned a value of Y; in other cases, the warning is assigned a value of G.

[0038] According to the new data X, the average value m of the new data X within 20KM range of each important navigation point and the maximum value n of the area are calculated, and the variable y is constructed, where y=h*m*n, h is the expected traffic increment ratio of the navigation point; the threshold of y when it affects the operation is combined with the historical operation data statistics, and the navigation point weather graded warning is carried out according to the statistical threshold.

[0039] Specifically, h defaults to the expected increase ratio of the navigation point traffic as 1. If the planned flight traffic decreases by more than 20% due to non-weather reasons, h is assigned a value of 0.7; if the flight volume increases by more than 15% due to important holidays or other reasons, h is assigned a value of 1.3; the warning classification judgment method for navigation points that affect control operations is: if y is greater than or equal to 0.25, the warning value is R, if y is greater than or equal to 0.13 and less than 0.25, the warning value is Y, and if y is less than 0.13, the warning value is G.

[0040] According to the new data X, the ray method is used to calculate the area percentage w of each terminal area where the new data X is greater than 0.43, and the variable f is constructed, where f=d*w, d is the expected incremental ratio of the flow of each terminal area. The threshold of f when it affects the operation is combined with the historical operation data statistics, and the terminal area coverage rate is graded and warned according to the statistical threshold.

[0041] Specifically, d defaults to the expected increase ratio of the navigation point traffic as 1. If the planned flight traffic decreases by 30% (inclusive) or more due to non-weather reasons on that day, d is assigned a value of 0.7; if the flight volume increases by 25% (inclusive) or more due to important holidays or other reasons, d is assigned a value of 1.3; the terminal area coverage rate warning grading judgment method that affects the control operation is: if f is greater than or equal to 20%, the warning value is R; if f is greater than or equal to 5% and less than 20%, the warning value is Y; if f is less than 5%, the warning value is G.

[0042] Specifically, according to the length of the impact time, the specific method for calculating and generating the route weather warning, navigation point weather warning and terminal area echo coverage warning products with a forecast time of 36 hours is as follows: in the hourly route, navigation point and terminal area coverage graded warnings, if the warning value is R or Y for more than 4 consecutive hours, or more than 8 hours intermittently, it is classified as a red warning, which is regarded as a strong impact, and the corresponding warning level is red when Python draws the product; if the warning value is R or Y for 2-4 hours continuously, or 4-8 hours intermittently, it is classified as a yellow warning, which is regarded as a general impact, and the corresponding warning level is yellow when Python draws the product; in other cases, the warning value is G, which is classified as a green warning, which is regarded as no impact or a small impact, and the corresponding warning level is green when Python draws the product.

[0043] The above is only a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the form disclosed herein, and should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be modified within the scope of the concept described herein through the above teachings or the technology or knowledge of the relevant field. The changes and modifications made by those skilled in the art shall not deviate from the spirit and scope of the present invention, and shall be within the scope of protection of the claims attached to the present invention.

Claims

1. A meteorological early warning method for control operation, characterized in that: include: S1. Screen out routes, navigation points and terminal areas according to control operation requirements; S2, reading the hourly echo reflectivity forecast data of the set time forecast validity; S3. Use statistical algorithms to perform quality control on the echo reflectivity forecast data, revise the control area, and standardize the revised echo reflectivity forecast data to form new data; S4. Calculate the average value a of the new data of the route segment and the maximum value b of the new data of the route segment based on the new data, and construct a first variable c, where c=k×a×b, k is the expected incremental ratio of the flow of the route segment, and then combine the first threshold value of c when the historical control operation data statistics have an impact on the control operation, and make a graded warning of route weather based on the first threshold value; According to the new data, the average value m of the new data within the set distance range of each navigation point and the maximum value n of the new data within the range are calculated to construct the second variable y, where y=h×m×n, h is the expected flow increment ratio of the navigation point, and then the second threshold of y when the historical control operation data statistics have an impact on the operation is combined, and the navigation point weather graded warning is carried out according to the second threshold; Based on the new data, the ray method is used to calculate the area percentage w of each terminal area where the new data is greater than the set value, and the third variable f is constructed, where f=d×w, d is the expected increase ratio of the traffic in each terminal area. The third threshold of f is used when the historical control operation data statistics have an impact on the operation, and the terminal area coverage rate is graded and warned according to the third threshold.

2. The meteorological early warning method for control operation according to claim 1, characterized in that: The default value of h is 1. If the planned flight flow is reduced by more than 20% due to non-weather reasons, h is assigned a value of 0.

7. If the planned flight flow increases by more than 15% due to other reasons, h is assigned a value of 1.

3. The navigation point warning classification judgment method that affects the control operation is: If y is greater than or equal to 0.25, it is the first warning value; if y is greater than or equal to 0.13 and less than 0.25, it is the second warning value; if y is less than 0.13, it is the third warning value. The impact of the first warning value is greater than that of the second warning value, and the impact of the second warning value is greater than that of the third warning value.

3. The meteorological early warning method for control operation according to claim 1, characterized in that: The default value of d is 1. If the planned flight flow is reduced by more than 30% due to non-weather reasons, d is assigned a value of 0.

7. If the planned flight flow increases by more than 25% due to other reasons, d is assigned a value of 1.

3. The terminal area coverage rate warning classification judgment method that affects the control operation is as follows: If f is greater than or equal to 20%, it is the first warning value; if f is greater than or equal to 5% and less than 20%, it is the second warning value; if f is less than 5%, it is the third warning value. The impact of the first warning value is greater than that of the second warning value, and the impact of the second warning value is greater than that of the third warning value.

4. The meteorological early warning method for control operation according to claim 1, characterized in that: Step S2 specifically includes: The hourly echo reflectivity forecast data of the SWC numerical model with a set time forecast validity is read through the MeteoInfoLab script, the echo reflectivity forecast data is converted and stored in netcdf format data, and then python is used to read the echo reflectivity forecast data in netcdf format.

5. The meteorological early warning method for control operation according to claim 1, characterized in that: Step S3 specifically includes: Evaluation and statistics are carried out according to different sectors of control, and the historical average error between the echo reflectivity value of SWC and the actual radar echo reflectivity is calculated. The echo reflectivity forecast data is corrected according to the historical average error, and the corrected echo reflectivity forecast data is standardized to form new data.

6. The weather warning method for control operation according to claim 1, characterized in that: The default value of k is 1. If the planned flight flow is reduced by more than 25% due to non-weather reasons, k is assigned a value of 0.

7. If the planned flight flow increases by more than 20% due to other reasons, k is assigned a value of 1.

3. The classification judgment method for route warnings that affect control operations is: if c is greater than or equal to 0.21, it is the first warning value; if c is greater than or equal to 0.15 and less than 0.21, it is the second warning value; in other cases, it is the third warning value. The impact of the first warning value is greater than that of the second warning value, and the impact of the second warning value is greater than that of the third warning value.

7. A computer device comprising a memory, wherein the memory stores program instructions, characterized in that: When the program instructions are executed, the meteorological warning method for control operation as described in any one of claims 1 to 6 is executed.

Images