Method and System for Determining Sensitive Areas of Low-Altitude Economic Route Flow Fields Based on Ensemble Simulation

Abstract

The present invention discloses a method and system for determining sensitive areas of low-altitude economic airway flow fields based on ensemble simulation, belonging to the technical field of airway setting. The present invention uses global atmospheric reanalysis datasets to obtain the meteorological initial conditions and boundary conditions of the target area, drives the WRF numerical model system to perform ensemble simulation on the meteorological field of the target area, obtains the hourly ensemble simulation dataset, and further determines the hourly airway meteorological variables of the low-altitude wind field in the target area, thereby constructing an airway flow field sensitivity model to obtain the airway flow field sensitivity. On this basis, the spatial distribution of sensitivity of the low-altitude airway in the target area is determined, and finally, the sensitive areas of the low-altitude economic airway flow field in the target area are determined according to the sensitivity threshold. The present invention can reasonably plan the low-altitude airspace airway in the target area, reasonably set the UAV takeoff and landing areas, avoid the areas with frequent meteorological disasters that have obvious impacts on the low-altitude economy, and reduce the meteorological disaster risks of the airway.

Description

Technical Field

[0001] The present invention relates to a method and system for determining a sensitive area of a low-altitude economic airway flow field based on ensemble simulation, belonging to the technical field of airway setting. Background Art

[0002] Data assimilation technology is one of the most effective technologies for improving the model prediction level. However, in existing assimilation studies, observational data is often directly assimilated into the model without discrimination and screening, which not only reduces the computational efficiency but also affects the assimilation level. Considering objective conditions such as high field observation costs and insufficient density of observation stations, targeted observation, one of the new observation methods proposed in the 1990s, has developed rapidly in the past 20 years. The specific idea of the targeted observation method is that, in order to better predict an event that will occur in the target area (i.e., the verification area) at a future time t2 (i.e., the verification time), a certain number of additional observations are deployed in the key area (i.e., the sensitive area) at a future time t1 (i.e., the target time, t1 < t2). The additional observational data in the key area will theoretically play a great role in reducing the prediction error of the target area. These additional observations will be assimilated by the data assimilation system to provide more reliable initial conditions. By effectively utilizing the correlation between observational data and forecast variables, targeted observation can save computational resources and data resources while effectively improving the model prediction effect. In the field of atmospheric related research, the targeted observation method has been applied to meteorological forecasts in different categories and scales such as haze events, tropical cyclone development, winter storms, and El Niño events, and its effectiveness has been fully verified. Applying the targeted observation method to 5 cases of Atlantic cyclone development and identifying the forecast sensitive area using the singular vector with the largest energy at the final moment in the verification area can reduce the overall root mean square error of the verification area by 13%. By assimilating targeted dropwindsondes and satellite wind data, the short-term prediction ability of winter storm landfall in the western Pacific of North America is improved, effectively solving the problem that the sparse observations in the North Pacific Basin affect the prediction effect. In the Winter Storm Reconnaissance (WSR00) project in winter 2000, by adaptively releasing dropwindsondes at target locations in the northeastern Pacific, the prediction accuracy of storms formed downstream of the target area is improved, which also promotes the further improvement of synoptic-scale wave forecasts.

[0003] In order to avoid areas with frequent meteorological disasters that have an obvious impact on the low-altitude economy and reduce the meteorological disaster risk of airways, how to reasonably plan the low-altitude airspace airways in the target area and reasonably set the takeoff and landing areas for unmanned aerial vehicles has become the key. Summary of the Invention

[0004] Objective of the Invention: To avoid meteorologically disaster-prone areas that significantly affect the low-altitude economy, reduce the meteorological disaster risk of air routes, and reasonably plan the low-altitude airspace routes and set up UAV takeoff and landing areas in the target area. The present invention provides a method for determining the sensitive area of the low-altitude economic air route flow field based on ensemble simulation.

[0005] Technical Solution: To achieve the above objective, the technical solution adopted by the present invention is as follows:

[0006] A method for determining the sensitive area of the low-altitude economic air route flow field based on ensemble simulation, comprising the following steps:

[0007] Obtain the meteorological initial conditions and boundary condition data of the target area.

[0008] According to the obtained initial conditions and boundary condition data of the target area, use the WRF numerical model system to perform ensemble simulation on the meteorological field of the target area to obtain an hourly meteorological field ensemble simulation data set.

[0009] Determine the hourly air route meteorological variables of the low-altitude wind field in the target area through the meteorological field ensemble simulation data set.

[0010] Use the obtained hourly air route meteorological variables of the low-altitude wind field in the target area to construct an air route flow field sensitivity model, and then calculate the air route flow field sensitivity.

[0011] Determine the spatial distribution of the air route flow field sensitivity in the low-altitude air routes of the target area through the air route flow field sensitivity.

[0012] Determine the sensitive area of the low-altitude economic air route flow field in the target area according to the spatial distribution of the sensitivity and the sensitivity threshold.

[0013] Preferably, the air route flow field sensitivity model is:

[0014] ;

[0015] Wherein, is the air route flow field sensitivity, is the simulation time period, is the number of samples of the ensemble simulation, is the wind speed of the th sample in the target area at time, is the average wind speed in the target area at time, is the wind speed of the th sample at time, is the average wind speed at time, is the wind speed of the The air temperature of a sample is the average air temperature at a moment is the relative humidity of the th sample at a moment is the average humidity at a moment

[0016] Preferably, the meteorological element included in the meteorological field ensemble simulation data set includes wind speed, air temperature, relative humidity and air pressure

[0017] Preferably, the resolution of the WRF numerical model system is 0.1 - 2KM

[0018] Preferably, the sensitivity threshold is 0.15 - 0.3

[0019] Another object of the present invention is to provide a system for determining the sensitive area of the low - altitude economic airway flow field based on ensemble simulation. Using the method for determining the sensitive area of the low - altitude economic airway flow field based on ensemble simulation, it includes an acquisition unit, a WRF numerical model system, an hourly wind speed determination unit, an airway flow field sensitivity model unit, a sensitivity distribution unit, and a low - altitude economic airway flow field sensitive area division unit, where:

[0020] The acquisition unit is used to obtain the meteorological initial conditions and boundary condition data of the target area

[0021] The WRF numerical model system is used to perform ensemble simulation on the meteorological field of the target area according to the obtained initial conditions and boundary condition data of the target area, and obtain an hourly meteorological field ensemble simulation data set

[0022] The hourly wind speed determination unit is used to determine the hourly airway meteorological variables of the low - altitude wind field in the target area through the meteorological field ensemble simulation data set

[0023] The airway flow field sensitivity model unit obtains the airway flow field sensitivity by using the airway flow field sensitivity model according to the hourly airway meteorological variables of the low - altitude wind field in the target area

[0024] The sensitivity distribution unit is used to determine the sensitivity spatial distribution of the airway flow field sensitivity in the low - altitude airway of the target area through the airway flow field sensitivity

[0025] The low - altitude economic airway flow field sensitive area division unit is used to determine the low - altitude economic airway flow field sensitive area of the target area according to the sensitivity spatial distribution and the sensitivity threshold

[0026] Another object of the present invention is to provide an electronic device, comprising: at least one processor, at least one memory, and a communication interface. The processor, the memory, and the communication interface communicate with each other. The memory stores program instructions executable by the processor, and the processor invokes the program instructions to execute the method for determining the sensitive area of the low-altitude economic airway flow field based on ensemble simulation.

[0027] Another object of the present invention is to provide a non-transitory computer-readable storage medium storing computer instructions that cause a computer to execute the method for determining the sensitive area of the low-altitude economic airway flow field based on ensemble simulation.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] In the present invention, by using the WRF numerical model system to perform ensemble simulation on the meteorological field of the target area according to the obtained meteorological initial conditions and boundary condition data of the target area, an hourly meteorological field ensemble simulation data set is obtained, and then the hourly airway meteorological variables of the low-altitude wind field in the target area are determined. Then, an airway flow field sensitivity model is constructed by using the obtained hourly airway meteorological variables of the low-altitude wind field in the target area, and the airway flow field sensitivity is calculated. On this basis, the spatial distribution of the airway flow field sensitivity in the low-altitude airway of the target area is determined. Finally, the sensitive area of the low-altitude economic airway flow field in the target area is determined according to the sensitivity threshold. Therefore, it can reasonably plan the low-altitude airspace airway in the target area, reasonably set the takeoff and landing areas of unmanned aerial vehicles, avoid the areas with frequent meteorological disasters that have an obvious impact on the low-altitude economy, and reduce the meteorological disaster risk of the airway. Description of the Drawings

[0030] Figure 1 It is a flowchart of the method for determining the sensitive area of the low-altitude economic airway flow field based on ensemble simulation.

[0031] Figure 2 It is the spatial distribution of the sensitivity of the airway flow field at a height of 10 m during the winter northerly wind.

[0032] Figure 3 It is the spatial distribution of the sensitivity of the airway flow field at a height of 300 m during the winter northerly wind.

[0033] Figure 4 It is the spatial distribution of the sensitivity of the airway flow field at a height of 600 m during the winter northerly wind.

[0034] Figure 5 It is the spatial distribution of the sensitivity of the airway flow field at a height of 10 m during the summer southeasterly wind.

[0035] Figure 6 It is the spatial distribution of the sensitivity of the airway flow field at a height of 300 m during the summer southeasterly wind.

[0036] Figure 7 It is the sensitivity spatial distribution of the airway flow field at a height of 600m when the southeast wind blows in summer. Specific implementation manners

[0037] The present invention will be further clarified below in conjunction with the accompanying drawings and specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and not to limit the scope of the present invention. After reading the present invention, those skilled in the art's various equivalent modifications of the present invention all fall within the scope defined by the appended claims of this application.

[0038] Embodiment 1

[0039] This embodiment provides a method for determining a sensitive area of a low-altitude economic airway flow field based on ensemble simulation, as Figure 1 shown, including the following steps:

[0040] Step S1, obtaining meteorological initial conditions and boundary condition data of a target area. In another embodiment, the meteorological initial conditions and boundary conditions of the target area are obtained by using a global atmospheric reanalysis dataset.

[0041] Step S2, using the WRF numerical model system to perform ensemble simulation on the meteorological field of the target area according to the obtained meteorological initial conditions and boundary condition data of the target area, and obtaining an hourly meteorological field ensemble simulation dataset. The meteorological elements included in the meteorological field ensemble simulation dataset are wind speed (wind direction), air temperature, relative humidity, air pressure, etc.

[0042] In this embodiment, the version of the WRF numerical model system used is WRF V4.5.2. WRF (full name: Weather Research and Forecasting model, Chinese for Meteorological Research and Forecasting Model) is a numerical model system coupled with atmospheric dynamics jointly developed by the National Oceanic and Atmospheric Administration (NOAA), Pacific Northwest National Laboratory (PNNL), and National Center for Atmospheric Research (NCAR) of the United States. The resolution of the adopted WRF numerical model system is 0.1 - 2KM.

[0043] During the process of using the WRF numerical model system to perform ensemble simulation on the low-altitude wind field of the target area, three-layer nesting simulation is adopted. The three-layer nesting are the first-layer nesting d01 of the model, the second-layer nesting d02 of the model, and the third-layer nesting d03 of the model. Among them, when performing the simulation of the first-layer nesting d01 of the model, both the initial conditions and boundary conditions of the meteorological field adopt the global atmospheric reanalysis dataset, and the global atmospheric reanalysis dataset is interpolated into the target area by using the interpolation method and then simulated; when performing the simulation of the second-layer nesting d02 and the third-layer nesting d03 of the model, the boundary conditions come from the simulation of the previous level.

[0044] The ensemble simulation is carried out for the third-level nested d03 of the model. By adding random perturbations to the initial field, initial field ensemble samples are obtained. To ensure that the ensemble sensitivity of the forecast variables is within a certain range, random perturbations are also added to the boundary conditions to obtain corresponding boundary condition ensemble samples, and then an ensemble simulation is performed to obtain an hourly meteorological field ensemble simulation dataset for the target area.

[0045] Step S3: Determine the hourly route meteorological variables of the low-altitude wind field in the target area through the meteorological field ensemble simulation dataset. The hourly route meteorological variables of the low-altitude wind field in the target area extracted from the meteorological field ensemble simulation dataset include wind speed (wind direction), air temperature, and relative humidity.

[0046] Step S4: Use the obtained hourly route meteorological variables of the low-altitude wind field in the target area to construct a route flow field sensitivity model, and then obtain the route flow field sensitivity.

[0047] The route flow field sensitivity model is as follows:

[0048] ;

[0049] Where is the route flow field sensitivity, is the simulation time period, is the number of samples in the ensemble simulation, is the wind speed of the th sample in the target area at time, is the average wind speed in the target area at time, is the wind speed of the th sample at time, is the air temperature of the th sample at time, is the average air temperature at time, is the relative humidity of the th sample at time,

[0050] In this embodiment, a sensitivity model of the airway flow field is constructed based on wind speed, air temperature, and relative humidity. Furthermore, the obtained sensitivity of the airway flow field has high accuracy. The influence of the initial velocity field within the model area on the predicted airway flow field at a certain moment or period of the entire target can be quantified through the sensitivity of the airway flow field. According to its relative magnitude and distribution, the sensitive area affecting the airway flow field of this time can be determined. Its division is more reliable, avoiding meteorologically disaster-prone areas that have an obvious impact on the low-altitude economy and reducing the meteorological disaster risk of the airway.

[0051] Step S5: Determine the spatial distribution of the sensitivity of the airway flow field in the low-altitude airway of the target area through the sensitivity of the airway flow field. In another embodiment, in the WRF numerical model system, the target area is simulated and distributed according to the sensitivity of the airway flow field to determine the spatial distribution of the sensitivity of the low-altitude airway in the target area.

[0052] Step S6: Determine the sensitive area of the low-altitude economic airway flow field in the target area according to the spatial distribution of sensitivity and the sensitivity threshold, that is, the area greater than the sensitivity threshold in the spatial distribution of sensitivity is used as the sensitive area of the low-altitude economic airway flow field in the target area. In this embodiment, in the WRF numerical model system, the sensitive area of the low-altitude economic airway flow field in the target area is determined through the contour line of the sensitivity threshold and the value of the spatial distribution of sensitivity. In this embodiment, the sensitivity threshold adopted is 0.2. In another embodiment, the sensitivity threshold adopted is 0.15. In another embodiment, the sensitivity threshold adopted is 0.3.

[0053] Embodiment 2

[0054] This embodiment provides a system for determining the sensitive area of the low-altitude economic airway flow field based on ensemble simulation, adopting the method for determining the sensitive area of the low-altitude economic airway flow field based on ensemble simulation, including an acquisition unit, a WRF numerical model system, an hourly wind speed determination unit, an airway flow field sensitivity model unit, a sensitivity distribution unit, and a low-altitude economic airway flow field sensitive area division unit, where:

[0055] The acquisition unit is used to obtain the meteorological initial conditions and boundary condition data of the target area.

[0056] The WRF numerical model system is used to perform ensemble simulation of the meteorological field of the target area according to the obtained meteorological initial conditions and boundary condition data of the target area by using the WRF numerical model system to obtain an hourly meteorological field ensemble simulation data set. The resolution of the adopted WRF numerical model system is 0.1 - 2 KM.

[0057] The hourly wind speed determination unit is used to determine the hourly airway meteorological variables of the low-altitude wind field in the target area through the meteorological field ensemble simulation data set.

[0058] The route flow field sensitivity model unit obtains the route flow field sensitivity according to the hourly route meteorological variables of the low-altitude wind field in the target area by using the route flow field sensitivity model.

[0059] The route flow field sensitivity model is as follows:

[0060] ;

[0061] Wherein, is the route flow field sensitivity, is the simulation time period, is the number of samples in the ensemble simulation, is the wind speed of the th sample in the target area at time is the average wind speed in the target area at time is the wind speed of the th sample at time is the average wind speed at time is the air temperature of the th sample at time is the average air temperature at time is the relative humidity of the th sample at time is the average humidity at time

[0062] The sensitivity distribution unit is used to determine the spatial distribution of the route flow field sensitivity in the low-altitude route of the target area through the route flow field sensitivity.

[0063] The low-altitude economic route flow field sensitive area division unit is used to determine the low-altitude economic route flow field sensitive area of the target area according to the spatial distribution of sensitivity and the sensitivity threshold. In the WRF numerical model system, the low-altitude economic route flow field sensitive area of the target area is determined by the contour line of the sensitivity threshold and the value of the spatial distribution of sensitivity. In this embodiment, the sensitivity threshold adopted is 0.2. In another embodiment, the sensitivity threshold adopted is 0.15. In another embodiment, the sensitivity threshold adopted is 0.3.

[0064] Embodiment 3

[0065] This embodiment provides an electronic device, including: at least one processor, at least one memory, and a communication interface. The processor, the memory, and the communication interface communicate with each other. The memory stores program instructions executable by the processor, and the processor invokes the program instructions to execute the method for determining the sensitive area of the low-altitude economic airway flow field based on ensemble simulation.

[0066] In another embodiment, a non-transitory computer-readable storage medium is provided. The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions cause the computer to execute the method for determining the sensitive area of the low-altitude economic airway flow field based on ensemble simulation.

[0067] Embodiment 4

[0068] This embodiment provides for determining the sensitive area of the low-altitude economic airway flow field in a specified target area by using the method for determining the sensitive area of the low-altitude economic airway flow field based on ensemble simulation in Embodiment 1, including the following steps:

[0069] Step S1: By using the global atmospheric reanalysis dataset, obtain the meteorological initial conditions and boundary condition data of the specified target area, and interpolate the global atmospheric reanalysis dataset to obtain the meteorological initial conditions and boundary condition data of the specified target area.

[0070] Step S2: According to the obtained meteorological initial conditions and boundary condition data of the specified target area, use the WRF numerical model system to perform ensemble simulation on the meteorological field of the specified target area to obtain an hourly meteorological field ensemble simulation dataset. The meteorological elements included in the meteorological field ensemble simulation dataset are wind speed, wind direction, air temperature, relative humidity, air pressure, etc. The resolution of the WRF numerical model system used is 1KM.

[0071] In this embodiment, the parameterization schemes adopted by the WRF numerical model system are as follows: the Lin parameterization scheme (Chinese: Lin microphysical process parameterization scheme) is used for the microphysical process, the RRTMG scheme (full name: Rapid Radiative Transfer Model for Global Climate Model, Chinese: Rapid Radiative Transfer Model for Global Climate Model) is used for both the long-wave radiation and short-wave radiation processes, the NOAH (full name: National Center for Environmental Prediction, Oregon State University, Air Force, and Hydrologic Research Lab, Chinese: Oregon State University National Environmental Prediction Center, Air Force and Hydrologic Research Laboratory) LSM (full name: land surface model, Chinese: land surface model) scheme is used for the land surface process, and the Grell scheme (Chinese: Grell cumulus convection parameterization scheme) is used for the cumulus convection parameterization process. The YSU scheme (Chinese: Yonsei University first-order non-local boundary layer parameterization scheme) is used for the boundary layer process.

[0072] The model adopts the Lambert map projection method, with the model center located in the specified target area. The simulation area consists of three one-way nested domains, namely the d01 - d03 areas. The horizontal resolutions from the outside to the inside are 9 km, 3 km, and 1 km respectively, and the corresponding grid numbers are 267×267, 184×184, and 250×250 respectively. The simulation period for the study is from January 22 to 24, 2023.

[0073] When simulating the first layer d01 of the model, both the initial conditions and boundary conditions of the meteorological field adopt the global meteorological reanalysis dataset FNL provided by the National Center for Atmospheric Research in the United States. The global meteorological reanalysis data is interpolated into the simulation area using an interpolation program and then simulated. For the second layer d02 and the third layer d03 of the model, the boundary conditions come from the simulation of the previous layer, and the initial conditions come from the FNL dataset.

[0074] The ensemble simulation is carried out for the third layer d03 of the model. We obtain an ensemble sample of the initial field with 50 members by adding random perturbations to the initial field. To ensure that the ensemble sensitivity of the forecast variables is within a certain range, we also add random perturbations to the boundary conditions to obtain the corresponding 50 boundary conditions.

[0075] Step S3, determine the hourly en-route meteorological variables of the low-altitude wind field in the specified target area through the meteorological field ensemble simulation dataset.

[0076] Step S4: Use the hourly route meteorological variables of the obtained specified target area low-altitude wind field to construct a route flow field sensitivity model, and then obtain the route flow field sensitivity.

[0077] The route flow field sensitivity model is as follows:

[0078] ;

[0079] Where, is the route flow field sensitivity, is the simulation time period, is the number of samples for ensemble simulation, is the wind speed of the th sample in the target area at time is the average wind speed in the target area at time is the wind speed of the th sample at time is the average wind speed at time is the temperature of the th sample at time is the average temperature at time is the relative humidity of the th sample at time is the average humidity at time

[0080] Through the route flow field sensitivity, the influence of the initial velocity field in the model area on the predicted route flow field in a certain moment or time period of the entire specified target area can be quantified, and the sensitive area affecting the route flow field can be determined according to its relative magnitude and distribution.

[0081] Step S5: Determine the sensitivity spatial distribution of the route flow field sensitivity in the low-altitude route of the specified target area, and perform simulation distribution on the specified target area in the WRF numerical model system according to the route flow field sensitivity to determine the sensitivity spatial distribution of the low-altitude route of the specified target area.

[0082] The specified target area is a typical monsoon area, with northerly winds prevailing in winter and southeasterly winds prevailing in summer. In this embodiment, the simulation forecasts of the wind fields in two time periods, January 22 - 25, 2023 (representing winter, northerly wind) and July 25 - 30, 2023 (representing summer, southeasterly wind), are selected for research.

[0083] As Figures 2 - 7As shown, they are the sensitivity spatial distributions of the route flow fields at 10 m, 300 m, and 600 m heights in the specified target area during the winter northerly wind and the summer southeasterly wind, respectively. It can be seen from the figure that the sensitivity of the route flow field changes with the change of the wind field direction. In winter, when the incoming flow is the northerly wind, the sensitivity spatial distributions of the route flow fields at the three altitude levels in the specified target area are very consistent, all showing a trend of being higher in the north and lower in the south. However, the sensitivity of the route flow field at 300 m height is the largest, followed by that at 600 m height, and the smallest at the near ground. In summer, since the incoming flow direction changes to the southeasterly wind, the sensitivity of the route flow field shows a decreasing trend from the southeast to the northwest. Also, the sensitivity of the route flow field at 300 m height is the largest, followed by that at 600 m height, and the smallest at the near ground. Overall, the sensitivity of the route flow field in winter is greater than that in summer.

[0084] Step S6: Determine the sensitive area of the low-altitude economic route flow field in the specified target area according to the sensitivity spatial distribution and the sensitivity threshold. In the WRF numerical model system, the sensitive area of the low-altitude economic route flow field in the specified target area is determined by the contour line of the sensitivity threshold and the value of the sensitivity spatial distribution. In this embodiment, the sensitivity threshold adopted is 0.2.

[0085] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A method for determining the flow field sensitive area of ​​a low-altitude economic route based on ensemble simulation, characterized in that: The following steps are involved: Obtain meteorological initial conditions and boundary conditions data of the target area; Based on the acquired initial condition and boundary condition data of the target area, the meteorological field of the target area is simulated by using the WRF numerical model system to obtain an hourly meteorological field ensemble simulation data set. The hourly route meteorological variables of low-altitude wind field in the target area are determined through the meteorological field ensemble simulation data set; The route flow field sensitivity model is constructed by using the hourly route meteorological variables of the low-altitude wind field in the target area, and then the route flow field sensitivity is obtained; The route flow field sensitivity model is: ; in, is the route flow field sensitivity, is the simulation time period, is the number of samples simulated for the set, for Moment The wind speed of samples in the target area, for The average wind speed in the target area at any given moment, for Moment The wind speed of the samples, for The average wind speed at the time, for Moment The temperature of the samples, for Average temperature at the time, for Moment The relative humidity of the samples, for Average humidity at all times; Determine the spatial distribution of the sensitivity of the airway flow field in the low-altitude airway of the target area through the airway flow field sensitivity; The sensitive area of ​​low-altitude economic route flow field in the target area is determined according to the sensitivity spatial distribution and sensitivity threshold.

2. The method for determining the flow field sensitive area of ​​a low-altitude economic route based on ensemble simulation according to claim 1 is characterized by: In the process of ensemble simulation of the low-altitude wind field in the target area using the WRF numerical model system, a three-layer nested simulation is adopted. The three layers of nesting are model first layer nesting d01, model second layer nesting d02, and model third layer nesting d03. Among them, when simulating the model first layer nesting d01, the initial conditions and boundary conditions of the meteorological field are all based on the global atmospheric reanalysis dataset. The data in the global meteorological reanalysis dataset are interpolated to the target area using the interpolation method for simulation; when simulating the model second layer nesting d02 and the model third layer nesting d03, the boundary conditions come from the simulation of the previous level.

3. The method for determining the flow field sensitive area of ​​a low-altitude economic route based on ensemble simulation according to claim 2 is characterized in that: In the process of ensemble simulation of the low-altitude wind field in the target area using the WRF numerical model system, the ensemble simulation is carried out on the third nested layer d03 of the model. The initial condition ensemble samples are obtained by adding random perturbations to the initial conditions, and random perturbations are added to the boundary conditions to obtain the corresponding boundary condition ensemble samples.

4. The method for determining the flow field sensitive area of ​​a low-altitude economic route based on ensemble simulation according to claim 3 is characterized by: The meteorological elements included in the meteorological field set simulation data set are wind speed, temperature, relative humidity and air pressure.

5. The method for determining the flow field sensitive area of ​​a low-altitude economic route based on ensemble simulation according to claim 4 is characterized by: The resolution of the WRF numerical model system is 0.1-2KM.

6. The method for determining the flow field sensitive area of ​​a low-altitude economic route based on ensemble simulation according to claim 5 is characterized by: The sensitivity threshold is 0.15-0.

3.

7. A system for determining the flow field sensitive area of ​​low-altitude economic routes based on ensemble simulation, characterized in that: The method for determining the flow field sensitive area of ​​a low-altitude economic route based on ensemble simulation as described in claim 1 comprises a collection unit, a WRF numerical model system, an hourly wind speed determination unit, a route flow field sensitivity model unit, a sensitivity distribution unit, and a low-altitude economic route flow field sensitive area division unit, wherein: The acquisition unit is used to obtain meteorological initial conditions and boundary condition data of the target area; The WRF numerical model system is used to perform ensemble simulation on the meteorological field of the target area according to the acquired initial condition and boundary condition data of the target area, and obtain an hourly ensemble simulation data set of the meteorological field; The hourly wind speed determination unit is used to determine the hourly route meteorological variables of the low-altitude wind field in the target area through the meteorological field set simulation data set; The route flow field sensitivity model unit obtains the route flow field sensitivity by using the route flow field sensitivity model according to the hourly route meteorological variables of the low-altitude wind field in the target area; The sensitivity distribution unit is used to determine the sensitivity spatial distribution of the route flow field sensitivity in the low-altitude route of the target area through the route flow field sensitivity; The low-altitude economic route flow field sensitive area division unit is used to determine the low-altitude economic route flow field sensitive area of ​​the target area according to the sensitivity spatial distribution and the sensitivity threshold.

8. An electronic device, characterized in that: include: at least one processor, at least one memory, and a communication interface; The processor, memory and communication interface communicate with each other; The memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the method for determining the flow field sensitive area of ​​a low-altitude economic route based on ensemble simulation as described in any one of claims 1-6.

9. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions enable the computer to execute the method for determining the flow field sensitive area of ​​a low-altitude economic route based on ensemble simulation as described in any one of claims 1 to 6.

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