Method and device for evaluating meteorological safety risk of rescue airplane in low-altitude flight

Abstract

The present application relates to a method and device for evaluating the meteorological safety risk of a rescue aircraft in low-altitude flight, which considers the actual meteorological conditions of the sea area near the Guangdong-Hong Kong-Macao Greater Bay Area, relies on the three-dimensional observation network in the region, focuses on wind (shear) and visibility as key meteorological elements, pays attention to severe convective weather, typhoon and other weather, designs meteorological condition evaluation factors, designs a low-altitude flight index that comprehensively reflects meteorological conditions and can serve different aircraft models, forms an AFI calculation method, and finally calculates AFI using the forecast data of the high-resolution regional mesoscale numerical model CMA_GD_3km in South China, which is applied to the low-altitude flight meteorological evaluation and prediction process to ensure the safety of rescue aircraft search and rescue flights. The present application realizes the evaluation of the meteorological safety risk of a rescue aircraft in low-altitude flight, fully considers severe convective weather, typhoon weather and precipitation weather during low-altitude flight, and conducts targeted safety risk evaluation of rescue flights of different rescue aircrafts under adverse weather conditions.

Description

Technical Field

[0001] This invention relates to the field of general aviation meteorological safety technology, and in particular to a method and device for assessing meteorological safety risks of rescue aircraft during low-altitude flight. Background Technology

[0002] Flight activities in low-altitude airspace are easily affected by terrain and weather conditions. Weather phenomena such as low visibility, low clouds, rain, thunderstorms, hail, and low-altitude wind shear can all affect the normality and safety of low-altitude flights.

[0003] Rescue flights, including disaster relief and rescue operations, mostly take place at low altitudes, making low-altitude flight one of the most common scenarios for general aviation low-altitude flight activities. Existing methods for assessing the meteorological safety risks of general aviation aircraft during low-altitude flight can be categorized as follows: one type assesses specific aspects of meteorological safety risks during low-altitude flight, primarily focusing on collision risks or drone crash risks, lacking a comprehensive assessment of meteorological safety risks during flight; another type uses civilian meteorological information for meteorological safety risk assessment, but the accuracy, frequency, and precision of civilian meteorological intelligence are insufficient to meet the needs of meteorological safety risk assessment in the complex and rapidly changing weather conditions of low-altitude flight; and a third type assesses the meteorological safety risks of general aviation aircraft under normal flight conditions, but lacks a comprehensive assessment of the meteorological safety risks of rescue aircraft under adverse weather conditions.

[0004] The assessment methods for meteorological safety risks in low-altitude flights have the following main defects: (1) The accuracy and frequency of the meteorological information used are not high, and the focus is mainly on the actual situation and forecast of short-term weather over a large area, which is difficult to meet the needs of low-altitude flights for high-precision weather conditions and weather forecasts; (2) The focus is mainly on the meteorological safety risks at the take-off and landing points, as well as limited meteorological elements and weather phenomena, and insufficient consideration is given to the comprehensive meteorological safety risks and various severe weather conditions during low-altitude flights; (3) The focus of the assessment is on the meteorological safety risks under normal flight conditions, and there is a lack of assessment of the meteorological safety risks of rescue flights under severe weather conditions. Summary of the Invention

[0005] The purpose of this invention is to at least address one of the shortcomings of the prior art and to provide a method and apparatus for assessing the meteorological safety risks of rescue aircraft during low-altitude flight.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] Specifically, a method for assessing meteorological safety risks of rescue aircraft flying at low altitudes is proposed, including the following:

[0008] Historical data of the target area is obtained, and influencing factors are extracted from the historical data through regression analysis. Effective weight coefficients of wind shear under typhoon weather and severe convective weather backgrounds are calculated, as well as effective weight coefficients of visibility at various levels under rainy and rainless conditions are calculated.

[0009] The wind shear prediction equation is established based on the effective weighting coefficient of the wind shear, and the visibility prediction equation is established based on the effective weighting coefficient of each level of visibility.

[0010] Using forecast data from the mesoscale numerical model CMA_GD_3km, wind shear is calculated by selecting the wind shear prediction equation, thereby correcting the forecast of upper-level wind speed.

[0011] Visibility forecasts are calculated using the forecast data from the mesoscale numerical model CMA_GD_3km, and the visibility forecast equation is selected to make the visibility forecast correction.

[0012] The Low-Altitude Flight Index (AFI) is defined based on the aforementioned influencing factors, and the AFI is combined with preset meteorological elements to obtain a discrimination standard.

[0013] The calculation results are obtained by calculating the wind shear, the upper-level wind speed (corrected forecast), and the visibility (corrected forecast). The low-altitude flight index is then calculated and the results are compared with the discrimination criteria to complete the meteorological safety risk assessment for low-altitude flight.

[0014] Furthermore, specifically, the established wind shear prediction equations include,

[0015] (1) Lower-level wind shear: ranging from the ground to 800 meters

[0016] Typhoon landfall affects eastern Guangdong coast

[0017] (1.1)

[0018] Typhoon landfall affects central Guangdong coast

[0019] (1.2)

[0020] Typhoon landfall affects western Guangdong coast

[0021] (1.3)

[0022] When severe convective weather affects

[0023] (1.4)

[0024] (2) Upper-level wind shear: ranging from 800 meters to 1500 meters

[0025] Typhoon landfall affects eastern Guangdong coast

[0026] (1.5)

[0027] Typhoon landfall affects central Guangdong coast

[0028] (1.6)

[0029] Typhoon landfall affects western Guangdong coast

[0030] (1.7)

[0031] When severe convective weather affects

[0032] (1.8);

[0033] Where x represents the wind speed at 10m above the ground, and y represents the wind shear.

[0034] Furthermore, specifically, the established visibility forecasting equations include,

[0035] (1) When there is no rain

[0036] Level 1: T < 23℃, V < 6m / s, T-Td: 1.5~2℃

[0037] (1.9)

[0038] Level 2: T < 23℃, V < 6m / s, T-Td: 1~1.5℃

[0039] (1.10)

[0040] Level 3: T < 23℃, V < 6m / s, T-Td: 0.7~1℃

[0041] (1.11)

[0042] Level 4: T < 23℃, V < 6m / s, T-Td: 0~0.7℃

[0043] (1.12)

[0044] (2) When it rains

[0045] Level 1: T < 23℃, V: 3~6m / s, T-Td: 1.5~2℃

[0046] (1.13)

[0047] Level 2: T < 23℃, V: 2.5~3m / s, T-Td: 1~1.5℃

[0048] (1.14)

[0049] Level 3: T < 23℃, V: 2~2.5m / s, T-Td: 0.7~1℃

[0050] (1.15)

[0051] Level 4: T < 23℃, V: 0~2m / s, T-Td: 0~0.7℃

[0052] (1.16);

[0053] Where VIS is visibility, T is ground temperature, V is ground wind speed at 10m, which has the same meaning as x in formula (1.1), and Td is ground dew point temperature.

[0054] Furthermore, specifically, using forecast data from the mesoscale numerical model CMA_GD_3km, the wind shear prediction equation is selected to calculate wind shear, thereby correcting upper-level wind speed forecasts, including...

[0055] Based on the mesoscale numerical model CMA_GD_3km, determine whether there is a typhoon landfall or severe convective weather impact during the forecast period. If there is no impact, the wind speed and wind shear will use the initial data.

[0056] If the forecast period is affected by severe convective weather, use equations (1.4) and (1.8) to calculate the lower-level wind shear and upper-level wind shear; if the forecast period is affected by typhoon landfall, use the corresponding equations (1.1-1.3) and (1.5-1.7) to calculate the lower-level wind shear and upper-level wind shear, depending on whether the typhoon lands on the eastern, central, or western coast of Guangdong.

[0057] C3: By calculating the lower and upper-level wind shear, and using the upper-level wind speeds at 800m and 1500m using the 10m surface wind speed correction model, the forecast correction for upper-level wind speeds is achieved; the calculation relationship between the lower and upper-level wind shear and the corresponding wind speeds is as follows:

[0058] (1.17)

[0059] (1.18);

[0060] Among them WS 10m-800m The wind shear between two layers at heights of 10m and 800m, i.e., the lower-level wind shear, WS800m-1500m V represents the wind shear between two layers at altitudes of 800m and 1500m, i.e., the upper-level wind shear. 10m V 800m V 1500m These represent wind speeds at altitudes of 10m, 800m, and 1500m, respectively.

[0061] Furthermore, specifically, determining whether a typhoon will make landfall or cause severe convective weather during the forecast period includes,

[0062] Determine if the echo reflectance is greater than 50 dBZ during the forecast period. If it is, it indicates that a typhoon is making landfall or that the area is affected by severe convective weather.

[0063] Furthermore, specifically, using forecast data from the mesoscale numerical model CMA_GD_3km, a visibility forecast equation is selected to calculate visibility, thereby performing visibility forecast corrections, including:

[0064] Based on the mesoscale numerical model CMA_GD_3km, determine whether the initial visibility field needs correction. If no correction is needed, the initial data is used for visibility.

[0065] If correction is needed, determine whether there will be rain during the forecast period. If there is no rain, use equation (1.9-1.12) to calculate the corrected visibility. If there is rain, use equation (1.13-1.16) to calculate the corrected visibility.

[0066] This invention also proposes a device for assessing the meteorological safety risks of rescue aircraft during low-altitude flight, comprising the following:

[0067] The data acquisition module is used to acquire historical data of the target area, extract influencing factors from the historical data through regression analysis, calculate the effective weight coefficient of wind shear under typhoon weather and severe convective weather background, and calculate the effective weight coefficient of visibility at all levels when there is rain and when there is no rain.

[0068] The forecast equation establishment module is used to establish the wind shear forecast equation based on the effective weighting coefficient of wind shear, and to establish the visibility forecast equation based on the effective weighting coefficient of visibility at each level.

[0069] The first forecast correction module is used to calculate wind shear by selecting the wind shear prediction equation using forecast data from the mesoscale numerical model CMA_GD_3km, thereby correcting the forecast of upper-level wind speed.

[0070] The second forecast correction module is used to calculate visibility using the forecast data of the mesoscale numerical model CMA_GD_3km, select the visibility forecast equation, and then perform visibility forecast correction.

[0071] The discrimination criterion definition module is used to define the Low-Altitude Flight Index (AFI) based on the influencing factors, and to classify and combine the AFI with preset meteorological elements to obtain the discrimination criteria.

[0072] The safety risk assessment module is used to calculate the low-altitude flight index based on the calculated wind shear, the forecasted and corrected upper-altitude wind speed, and the forecasted and corrected visibility. The calculation results are then compared with the discrimination criteria to complete the low-altitude flight meteorological safety risk assessment.

[0073] The beneficial effects of this invention are as follows:

[0074] This invention proposes a method and device for assessing meteorological safety risks of rescue aircraft during low-altitude flight. It utilizes forecast data from the CMA_GD_3km high-resolution regional medium-scale numerical model in South China, fully considering severe convective weather, typhoon weather, and precipitation during low-altitude flight, and conducts targeted safety risk assessments for different rescue aircraft operating under adverse weather conditions. The main advantages are:

[0075] 1) Regression analysis was used to analyze surface wind speed, upper-level wind speed and wind shear under typhoon and severe convective weather in historical data, and visibility under precipitation conditions was analyzed. Effective weighting coefficients were obtained and forecast equations for wind shear and visibility were established. The method comprehensively considers the meteorological safety risks of rescue flights.

[0076] 2) By using the high-precision regional mesoscale numerical model CMA_GD_3km and correcting the upper-level wind speed and visibility using the forecast equations, the accuracy and stability of the forecast assessment are improved.

[0077] 3) The Low-Altitude Flight Index (AFI) was defined, making meteorological safety risk assessment more direct and operational. The introduction of the AFI index also provides an important reference for the meteorological safety risk assessment of low-altitude flights of general aviation aircraft other than rescue aircraft. Attached Figure Description

[0078] The above and other features of this disclosure will become more apparent from the detailed description of the embodiments illustrated in conjunction with the accompanying drawings. In the accompanying drawings, the same reference numerals denote the same or similar elements. Obviously, the drawings described below are merely some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained from these drawings without any creative effort. In the drawings:

[0079] Figure 1 The flowchart shown is a process for correcting the forecast of upper-level wind speed in this invention.

[0080] Figure 2 The diagram shows a flowchart of visibility forecast correction in this invention. Detailed Implementation

[0081] The following will provide a clear and complete description of the concept, specific structure, and technical effects of the present invention in conjunction with embodiments and accompanying drawings, so as to fully understand the purpose, solution, and effects of the present invention. It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The same reference numerals used throughout the accompanying drawings indicate the same or similar parts.

[0082] Reference Figure 1 as well as Figure 2 Example 1: This invention proposes a method for assessing the meteorological safety risks of rescue aircraft during low-altitude flight, including the following:

[0083] Historical data of the target area is obtained, and influencing factors are extracted from the historical data through regression analysis. Effective weight coefficients of wind shear under typhoon weather and severe convective weather backgrounds are calculated, as well as effective weight coefficients of visibility at various levels under rainy and rainless conditions are calculated.

[0084] Specifically in this step,

[0085] Historical data mainly includes surface meteorological observation data and upper-air meteorological sounding data from 2013 to 2019, relevant data on typhoons that affected or made landfall in Guangdong from 2013 to 2019, data on severe convective weather processes that affected Guangdong from 2013 to 2019, and data on low visibility processes in Guangdong from December to April of the following year from 2015 to 2019.

[0086] The process of analyzing and determining the influencing factors and weights of wind shear using regression analysis is as follows:

[0087] (1) Analyze the perennial variation characteristics of the low-altitude wind field in the region using historical data. Using surface meteorological observation data and upper-air meteorological sounding data from 2013 to 2019, statistically analyze the low-altitude wind field over the land and sea of ​​Guangdong from 2013 to 2019 to obtain the perennial variation characteristics of the low-altitude wind field.

[0088] (2) Analyze the characteristics of low-altitude wind field changes under the influence of typhoon and severe convective weather from 2013 to 2019, and distinguish different weather types. Assume that the influencing factors are mainly composed of the wind speed at 10m above the ground (i.e., the ground wind speed), including the first power. , square ,index Logarithm Equal factors, and then ground wind speed Wind shear is the independent variable. Using [variable name] as the dependent variable, a regression fit is performed. The final results are obtained for each factor. , , , The weight coefficients of each factor were determined, and a reliability test was performed on the weight coefficients of each factor. Factors whose weight coefficients passed the 95% reliability test were retained, while factors that failed the test were excluded.

[0089] (3) Regress and fit the factors whose weight coefficients have passed the test again, and perform the reliability test again. Keep the factors whose weight coefficients have passed the test and exclude the factors whose weight coefficients have not passed the test. Repeat the above process until all the weight coefficients of the factors obtained from the regression fitting have passed the reliability test. At this time, each factor is the final determined influencing factor, and their weight coefficients are the effective weight coefficients. For example, when severe convective weather has an impact, the square of the final determined influencing factor is... Sum of Indices The weighting coefficients all passed the 95% reliability test, and their weighting coefficients are the effective weighting coefficients of wind shear.

[0090] The process of analyzing and determining the influencing factors and weights of visibility using regression analysis is as follows:

[0091] (1) Analyze the annual variation characteristics of visibility in the region using historical data. Using surface meteorological observation data from 2013 to 2019 (including meteorological elements such as visibility, surface temperature, surface wind speed, and surface temperature-dew point difference), statistically analyze the relationship between visibility y and surface temperature T, surface wind speed V, and surface temperature-dew point difference T-Td from 2013 to 2019 to obtain the annual variation characteristics of visibility.

[0092] (2) Analyze the visibility variation characteristics under low visibility events from 2013 to 2019, distinguish between rainless and rainy conditions, and differentiate visibility levels. Assume that the influencing factors are mainly composed of functions of surface temperature T, surface wind speed V, and surface temperature-dew point difference T-Td, including the first power. , square ,index Logarithm Factors such as visibility Using T as the dependent variable, perform multiple regression fitting. This ultimately yields the factors for T, V, and T-Td. , , , The weight coefficients of each factor were determined, and a reliability test was performed on the weight coefficients of each factor. Factors whose weight coefficients passed the 95% reliability test were retained, while factors that failed the test were excluded.

[0093] (3) Regression fitting is performed again for each factor whose weight coefficients have passed the test, and reliability test is performed again. Factors whose weight coefficients have passed the test are retained, and factors whose weight coefficients have not passed the test are excluded. The above process is repeated until all the weight coefficients of each factor obtained by regression fitting have passed the reliability test. At this time, each factor is the final determined influencing factor, and their weight coefficients are the effective weight coefficients of visibility.

[0094] The wind shear prediction equation is established based on the effective weighting coefficient of the wind shear, and the visibility prediction equation is established based on the effective weighting coefficient of each level of visibility.

[0095] Using forecast data from the mesoscale numerical model CMA_GD_3km, wind shear is calculated based on the selected wind shear prediction equation, thereby correcting upper-level wind speed forecasts. The specific procedure is as follows: Figure 1 ;

[0096] Visibility forecasts are calculated using the forecast data from the mesoscale numerical model CMA_GD_3km, and the visibility forecast equation is selected to make the visibility forecast correction.

[0097] The Low-Altitude Flight Index (AFI) is defined based on the aforementioned influencing factors, and the AFI is combined with preset meteorological elements to obtain a discrimination standard.

[0098] Specifically, a Low Altitude Flight Index (AFI) is defined by utilizing factors such as surface wind, upper-level wind, wind shear, and visibility, supplemented by considerations of weather conditions such as typhoons, severe convection, and precipitation, to comprehensively reflect whether meteorological conditions are suitable for low-altitude flight and operations of rescue aircraft. The classification and explanation of the Low Altitude Flight Index (AFI) are shown in Table 2.

[0099] Table 2: Classification and Explanation of the Airspace Flight Index (AFI)

[0100]

[0101] For two types of rescue aircraft (S-67D rescue helicopters and rotary-wing UAVs), classification ranges for meteorological elements such as ground wind, upper-level wind, wind shear, and visibility were designed and combined with the AFI index. The AFI classifications and corresponding meteorological element classification combinations for the two types of rescue aircraft are shown in Tables 3 and 4.

[0102] Table 3: AFI Classification and Corresponding Meteorological Element Classification Ranges for S-76D Rescue Helicopters

[0103]

[0104] Note: 1. Visibility >= 10,000 meters, AFI is 0; 2. Wind speed >= 24.4 m / s, or wind shear >= 15 m / s, AFI is 100.

[0105] Table 4: AFI Classification of Rotary-Wing UAVs and Corresponding Meteorological Element Classification Ranges

[0106]

[0107] Note: 1. Visibility >= 10,000 meters, AFI is 0; 2. Wind speed >= 17.1 m / s, or wind shear >= 12 m / s, AFI is 100.

[0108] The calculation results are obtained by calculating the wind shear, the upper-level wind speed (corrected forecast), and the visibility (corrected forecast). The low-altitude flight index is then calculated and the results are compared with the discrimination criteria to complete the meteorological safety risk assessment for low-altitude flight.

[0109] Specifically,

[0110] The corrected surface wind (10m), upper-level wind (800m), upper-level wind (1500m), lower-level wind shear, upper-level wind shear, and visibility meteorological elements are used to obtain the AFI classification of each meteorological element according to the rescue aircraft type reference Table 3 or Table 4.

[0111] The AFI classifications of each meteorological element are compared, and the highest classification is taken as the final AFI index.

[0112] Substitute the final AFI index into Table 2 to complete the meteorological safety risk assessment for low-altitude flight of the rescue aircraft.

[0113] The evaluation method of this invention utilizes the AFI index, which can reflect whether rescue aircraft are suitable for low-altitude flight and operation under different flight weather conditions, and provides an assessment of the meteorological safety risks for low-altitude flight of rescue aircraft.

[0114] In a preferred embodiment of the present invention, specifically, the established wind shear prediction equation includes,

[0115] (1) Lower-level wind shear: ranging from the ground to 800 meters

[0116] Typhoon landfall affects eastern Guangdong coast

[0117] (1.1)

[0118] Typhoon landfall affects central Guangdong coast

[0119] (1.2)

[0120] Typhoon landfall affects western Guangdong coast

[0121] (1.3)

[0122] When severe convective weather affects

[0123] (1.4)

[0124] (2) Upper-level wind shear: ranging from 800 meters to 1500 meters

[0125] Typhoon landfall affects eastern Guangdong coast

[0126] (1.5)

[0127] Typhoon landfall affects central Guangdong coast

[0128] (1.6)

[0129] Typhoon landfall affects western Guangdong coast

[0130] (1.7)

[0131] When severe convective weather affects

[0132] (1.8);

[0133] Where x represents the wind speed at 10m above the ground, and y represents the wind shear.

[0134] Furthermore, specifically, the established visibility forecasting equations include,

[0135] (1) When there is no rain

[0136] Level 1: T < 23℃, V < 6m / s, T-Td: 1.5~2℃

[0137] (1.9)

[0138] Level 2: T < 23℃, V < 6m / s, T-Td: 1~1.5℃

[0139] (1.10)

[0140] Level 3: T < 23℃, V < 6m / s, T-Td: 0.7~1℃

[0141] (1.11)

[0142] Level 4: T < 23℃, V < 6m / s, T-Td: 0~0.7℃

[0143] (1.12)

[0144] (2) When it rains

[0145] Level 1: T < 23℃, V: 3~6m / s, T-Td: 1.5~2℃

[0146] (1.13)

[0147] Level 2: T < 23℃, V: 2.5~3m / s, T-Td: 1~1.5℃

[0148] (1.14)

[0149] Level 3: T < 23℃, V: 2~2.5m / s, T-Td: 0.7~1℃

[0150] (1.15)

[0151] Level 4: T < 23℃, V: 0~2m / s, T-Td: 0~0.7℃

[0152] (1.16);

[0153] Where VIS is visibility, T is ground temperature, V is ground wind speed at 10m, which has the same meaning as x in formula (1.1), and Td is ground dew point temperature.

[0154] In a preferred embodiment of the present invention, specifically, wind shear is calculated using forecast data from the mesoscale numerical model CMA_GD_3km, by selecting a wind shear forecast equation, thereby correcting the forecast of upper-level wind speeds, including...

[0155] Based on the mesoscale numerical model CMA_GD_3km, determine whether there is a typhoon landfall or severe convective weather impact during the forecast period. If there is no impact, the wind speed and wind shear will use the initial data.

[0156] If the forecast period is affected by severe convective weather, use equations (1.4) and (1.8) to calculate the lower-level wind shear and upper-level wind shear; if the forecast period is affected by typhoon landfall, use the corresponding equations (1.1-1.3) and (1.5-1.7) to calculate the lower-level wind shear and upper-level wind shear, depending on whether the typhoon lands on the eastern, central, or western coast of Guangdong.

[0157] C3: By calculating the lower and upper-level wind shear, and using the upper-level wind speeds at 800m and 1500m using the 10m surface wind speed correction model, the forecast correction for upper-level wind speeds is achieved; the calculation relationship between the lower and upper-level wind shear and the corresponding wind speeds is as follows:

[0158] (1.17)

[0159] (1.18);

[0160] Among them WS 10m-800m The wind shear between two layers at heights of 10m and 800m, i.e., the lower-level wind shear, WS 800m-1500m V represents the wind shear between two layers at altitudes of 800m and 1500m, i.e., the upper-level wind shear. 10m V 800m V 1500m These represent wind speeds at altitudes of 10m, 800m, and 1500m, respectively.

[0161] In a preferred embodiment of the present invention, specifically, determining whether there is a typhoon making landfall or severe convective weather impact during the forecast period includes:

[0162] Determine if the echo reflectance is greater than 50 dBZ during the forecast period. If it is, it indicates that a typhoon is making landfall or that the area is affected by severe convective weather.

[0163] In a preferred embodiment of the present invention, specifically, visibility is calculated using forecast data from the mesoscale numerical model CMA_GD_3km, by selecting a visibility forecast equation, thereby performing visibility forecast correction, including:

[0164] Based on the mesoscale numerical model CMA_GD_3km, determine whether the initial visibility field needs correction. If no correction is needed, the initial data is used for visibility.

[0165] If correction is needed, determine whether there will be rain during the forecast period. If there is no rain, use equation (1.9-1.12) to calculate the corrected visibility. If there is rain, use equation (1.13-1.16) to calculate the corrected visibility.

[0166] Specifically, in the application of this invention, an assessment of the meteorological safety risks of rescue aircraft flying at low altitudes was conducted from March 12 to 14, 2020.

[0167] From March 12th to 13th, as the influence of cold air weakened, water vapor rapidly increased in South China, leading to a rise in atmospheric saturation. Light fog or mist appeared in most parts of South China and coastal areas, with some areas experiencing light rain, resulting in mixed rain and fog weather. In Guangdong Province, visibility at many observation stations was below 2000m or even less than 500m.

[0168] Step A: Using historical data, extract influencing factors through regression analysis, calculate the effective weight coefficient of wind shear under typhoon and severe convective weather conditions, and calculate the effective weight coefficient of visibility at various levels under rainy and dry weather conditions.

[0169] Step B: Establish the prediction equations for wind shear and visibility (1.1 to 1.16) based on the effective weighting coefficients obtained in Step A.

[0170] Step C: Using the surface 10m wind forecast data from the mesoscale numerical model CMA_GD_3km, the wind shear forecast equation is selected to calculate the wind shear, thereby correcting the upper-level wind speed forecast.

[0171] Step D: Using visibility forecast data from the mesoscale numerical model CMA_GD_3km, select the visibility forecast equation to calculate visibility, thereby correcting the visibility forecast.

[0172] Step E1: Using factors such as surface wind, upper-level wind, wind shear, and visibility, and taking into account severe convection and precipitation weather from March 12th to 14th, define a Low-Altitude Flight Index (AFI) to comprehensively reflect whether meteorological conditions are suitable for low-altitude flight and operations of rescue aircraft. The classification and explanation of the Low-Altitude Flight Index (AFI) are shown in Table 2.

[0173] Step E2: For the two types of rescue aircraft (S-67D rescue helicopters and rotary-wing UAVs), design the classification ranges for meteorological elements such as ground wind, upper-level wind, wind shear, and visibility, and combine them with the AFI index. The AFI classifications and corresponding meteorological element classification combinations for the two types of rescue aircraft are shown in Tables 3 and 4.

[0174] Step F involves calculating and classifying the low-altitude flight index using meteorological factors such as the calculated wind shear, corrected wind speed, and calculated visibility, thus completing the low-altitude flight meteorological safety risk assessment. At dawn on the 13th, the AFI for rescue helicopters was between 50 and 60, placing them at Level 3 (moderate impact, relatively difficult flight). In other areas, some AFIs reached Level 2, indicating mild impact and moderate flight difficulty. The AFI for rotary-wing drones exceeded 60, placing them at Level 4 (severe impact). Because drones are remotely controlled by rescue personnel, their actual field of vision is narrower, making them more difficult to control under the same visibility conditions. At this point, the AFI reached Level 4, indicating that low visibility weather severely interfered with flight, posing a high risk.

[0175] To give a specific example, starting in the afternoon of March 13, another cold air mass moved southward and affected South China. This time, precipitation occurred near the front of the cold air mass, and the wind force increased. It can be seen that the radar echo forecast is quite consistent with the actual situation in terms of range, structure, and intensity, and can basically reflect the location and amount of precipitation. The corresponding AFI of rescue helicopters is between 30 and 80, spanning levels 2 to 4, showing a certain gradient range. This indicates that the difficulty of flying in the precipitation area also varies from general to severe. It reflects that the meteorological safety risks of low-altitude flight are affected by factors such as precipitation, visibility, and wind, and the risks range from general to very high levels.

[0176] This invention also proposes a device for assessing the meteorological safety risks of rescue aircraft during low-altitude flight, comprising the following:

[0177] The data acquisition module is used to acquire historical data of the target area, extract influencing factors from the historical data through regression analysis, calculate the effective weight coefficient of wind shear under typhoon weather and severe convective weather background, and calculate the effective weight coefficient of visibility at all levels when there is rain and when there is no rain.

[0178] The forecast equation establishment module is used to establish the wind shear forecast equation based on the effective weighting coefficient of wind shear, and to establish the visibility forecast equation based on the effective weighting coefficient of visibility at each level.

[0179] The first forecast correction module is used to calculate wind shear by selecting the wind shear prediction equation using forecast data from the mesoscale numerical model CMA_GD_3km, thereby correcting the forecast of upper-level wind speed.

[0180] The second forecast correction module is used to calculate visibility using the forecast data of the mesoscale numerical model CMA_GD_3km, select the visibility forecast equation, and then perform visibility forecast correction.

[0181] The discrimination criterion definition module is used to define the Low-Altitude Flight Index (AFI) based on the influencing factors, and to classify and combine the AFI with preset meteorological elements to obtain the discrimination criteria.

[0182] The safety risk assessment module is used to calculate the low-altitude flight index based on the calculated wind shear, the forecasted and corrected upper-altitude wind speed, and the forecasted and corrected visibility. The calculation results are then compared with the discrimination criteria to complete the low-altitude flight meteorological safety risk assessment.

[0183] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0184] If the integrated module is implemented as a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or system capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0185] Although the description of the invention has been quite detailed and particularly of several described embodiments, it is not intended to limit it to any of these details or embodiments or any particular embodiment, but should be considered as providing a broad possible interpretation of the claims by referring to the appended claims and taking into account the prior art, thereby effectively covering the intended scope of the invention. Furthermore, the invention has been described above with respect to embodiments foreseeable by the inventors in order to provide a useful description, and non-substantial modifications to the invention that have not yet been foreseen may still represent equivalent modifications.

[0186] The above description is merely a preferred embodiment of the present invention. The present invention is not limited to the above-described embodiments. Any embodiment that achieves the technical effects of the present invention using the same means should fall within the protection scope of the present invention. Within the protection scope of the present invention, various modifications and variations can be made to the technical solutions and / or implementation methods.

Claims

1. A method for assessing meteorological safety risks of rescue aircraft during low-altitude flight, characterized in that, Including the following: Historical data of the target area is obtained, and influencing factors are extracted from the historical data through regression analysis. Effective weight coefficients of wind shear under typhoon and severe convective weather backgrounds are calculated, as well as effective weight coefficients of visibility at various levels under rainy and dry weather conditions are calculated. The wind shear prediction equation is established based on the effective weighting coefficient of the wind shear, and the visibility prediction equation is established based on the effective weighting coefficient of each level of visibility. Using forecast data from the mesoscale numerical model CMA_GD_3km, wind shear is calculated by selecting the wind shear prediction equation, thereby correcting the forecast of upper-level wind speed. Visibility forecasts are calculated using the forecast data from the mesoscale numerical model CMA_GD_3km, and the visibility forecast equation is selected to make the visibility forecast correction. The Low-Altitude Flight Index (AFI) is defined based on the aforementioned influencing factors, and the AFI is combined with preset meteorological elements to obtain a discrimination standard. The calculation results are obtained by calculating the wind shear, the upper-level wind speed of the forecast correction, and the visibility of the forecast correction. The low-altitude flight index is calculated by comparing the calculation results with the discrimination criteria to complete the low-altitude flight meteorological safety risk assessment. The aforementioned meteorological safety risk assessment method for rescue aircraft flying at low altitudes is characterized by, specifically, the established wind shear prediction equation, including, (1) Lower-level wind shear: The range is from the ground to 800 meters. The typhoon's landfall will affect the eastern coastal areas of Guangdong. （1.1）； Typhoon landfall affects central Guangdong coast （1.2） Typhoon landfall affects western Guangdong coast （1.3） When severe convective weather affects （1.4） (2) Upper-level wind shear: ranging from 800 meters to 1500 meters Typhoon landfall affects eastern Guangdong coast （1.5） Typhoon landfall affects central Guangdong coast （1.6） Typhoon landfall affects western Guangdong coast （1.7） When severe convective weather affects （1.8）； Where x represents the wind speed at 10m above the ground, and y represents the wind shear; Specifically, using forecast data from the mesoscale numerical model CMA_GD_3km, wind shear is calculated using the selected wind shear prediction equation, thereby correcting upper-level wind speed forecasts, including... Based on the mesoscale numerical model CMA_GD_3km, determine whether there is a typhoon landfall or severe convective weather impact during the forecast period. If there is no impact, the wind speed and wind shear will use the initial data. If the forecast period is affected by severe convective weather, use equations (1.4) and (1.8) to calculate the lower-level wind shear and upper-level wind shear; if the forecast period is affected by typhoon landfall, use the corresponding equations (1.1-1.3) and (1.5-1.7) to calculate the lower-level wind shear and upper-level wind shear, depending on whether the typhoon lands on the eastern, central, or western coast of Guangdong. By calculating the lower and upper-level wind shear, and using the upper-level wind speeds at 800m and 1500m using a ground-based 10m wind speed correction model, the forecast correction for upper-level wind speeds is achieved. The calculation relationship between the lower and upper-level wind shear and the corresponding wind speeds is as follows: （1.17） （1.18）； Among them WS 10m-800m The wind shear between two layers at heights of 10m and 800m, i.e., the lower-level wind shear, WS 800m-1500m V represents the wind shear between two layers at altitudes of 800m and 1500m, i.e., the upper-level wind shear. 10m V 800m V 1500m These represent wind speeds at altitudes of 10m, 800m, and 1500m, respectively.

2. The meteorological safety risk assessment method for rescue aircraft during low-altitude flight according to claim 1, characterized in that, Specifically, the established visibility forecasting equations include: (1) When there is no rain Level 1: T < 23℃, V < 6m / s, T-Td: 1.5~2℃ （1.9） Level 2: T < 23℃, V < 6m / s, T-Td: 1~1.5℃ （1.10） Level 3: T < 23℃, V < 6m / s, T-Td: 0.7~1℃ （1.11） Level 4: T < 23℃, V < 6m / s, T-Td: 0~0.7℃ （1.12） (2) When it rains Level 1: T < 23℃, V: 3~6m / s, T-Td: 1.5~2℃ （1.13） Level 2: T < 23℃, V: 2.5~3m / s, T-Td: 1~1.5℃ （1.14） Level 3: T < 23℃, V: 2~2.5m / s, T-Td: 0.7~1℃ （1.15） Level 4: T < 23℃, V: 0~2m / s, T-Td: 0~0.7℃ （1.16）； Where VIS is visibility, T is ground temperature, V is ground wind speed at 10m, and Td is ground dew point temperature.

3. The meteorological safety risk assessment method for rescue aircraft during low-altitude flight according to claim 1, characterized in that, Specifically, using forecast data from the mesoscale numerical model CMA_GD_3km, a visibility forecast equation is selected to calculate visibility, thereby performing visibility forecast corrections, including: Based on the mesoscale numerical model CMA_GD_3km, determine whether the initial visibility field needs correction. If no correction is needed, the initial data is used for visibility. If correction is needed, determine whether there will be rain during the forecast period. If there is no rain, use equation (1.9-1.12) to calculate the corrected visibility. If there is rain, use equation (1.13-1.16) to calculate the corrected visibility.

4. The meteorological safety risk assessment method for rescue aircraft during low-altitude flight according to claim 1, characterized in that, Specifically, determining whether a typhoon will make landfall or cause severe convective weather during the forecast period includes: Determine if the echo reflectance is greater than 50 dBZ during the forecast period. If it is, it indicates that a typhoon is making landfall or that the area is affected by severe convective weather.

5. A device for assessing meteorological safety risks of rescue aircraft during low-altitude flight, characterized in that, The apparatus comprises the steps of the method described in any one of claims 1-4. the following: The data acquisition module is used to acquire historical data of the target area, extract influencing factors from the historical data through regression analysis, calculate the effective weight coefficient of wind shear under typhoon weather and severe convective weather background, and calculate the effective weight coefficient of visibility at all levels when there is rain and when there is no rain. The forecast equation establishment module is used to establish the wind shear forecast equation based on the effective weighting coefficient of wind shear, and to establish the visibility forecast equation based on the effective weighting coefficient of visibility at each level. The first forecast correction module is used to calculate wind shear by selecting the wind shear prediction equation using forecast data from the mesoscale numerical model CMA_GD_3km, thereby correcting the forecast of upper-level wind speed. The second forecast correction module is used to calculate visibility using the forecast data of the mesoscale numerical model CMA_GD_3km, select the visibility forecast equation, and then perform visibility forecast correction. The discrimination criterion definition module is used to define the Low-Altitude Flight Index (AFI) based on the influencing factors, and to classify and combine the AFI with preset meteorological elements to obtain the discrimination criteria. The safety risk assessment module is used to calculate the low-altitude flight index based on the calculated wind shear, the forecasted and corrected upper-altitude wind speed, and the forecasted and corrected visibility. The calculation results are then compared with the discrimination criteria to complete the low-altitude flight meteorological safety risk assessment.

Images