Low-altitude economic airway flow field sensitive area determination method and system based on set simulation

Abstract

The invention discloses a low-altitude economic airway flow field sensitive area determination method and system based on set simulation, and belongs to the technical field of airway setting. The meteorological initial conditions and boundary conditions of the target area are obtained by using the global atmosphere reanalysis data set, the WRF numerical mode system is driven to perform set simulation on the meteorological field of the target area, the hourly set simulation data set is obtained, and then the hourly airway meteorological variables of the low-altitude wind field of the target area are determined. And constructing an air route flow field sensitivity model to obtain the air route flow field sensitivity, determining the sensitivity spatial distribution of the low-altitude air route in the target area on this basis, and finally determining the low-altitude economic air route flow field sensitive area of the target area according to a sensitivity threshold. According to the invention, the low-altitude airspace route of the target area can be reasonably planned, the take-off and landing area of the unmanned aerial vehicle is reasonably set, meteorological disaster-prone areas having obvious influence on low-altitude economy are avoided, and the meteorological disaster risk of the route is reduced.

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 level of model prediction. 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 method of targeted observation 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 method of targeted observation to 5 cases of Atlantic cyclone development and identifying the forecast sensitive area using the singular vector with the maximum 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 dropsonde and satellite wind data, the short-term prediction ability of the winter storm landing in the western Pacific of North America has been improved, effectively solving the problem that the sparse observation in the North Pacific Basin affects the prediction effect. In the Winter Storm Reconnaissance (WSR00) project in 2000, by adaptively releasing dropsondes at target locations in the northeastern Pacific, the prediction accuracy of storms formed downstream of the target area has been improved, which has also promoted the further improvement of weather-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] Purpose of the invention: In order to avoid areas prone to meteorological disasters that have a significant impact on the low-altitude economy, reduce the risk of meteorological disasters on routes, rationally plan low-altitude airspace routes in target areas, and reasonably set up drone take-off and landing areas, the present invention provides a method for determining flow field sensitive areas of low-altitude economic routes based on ensemble simulation.

[0005] Technical solution: To achieve the above purpose, the technical solution adopted by the present invention is:

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

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

[0008] According to the acquired initial and boundary condition data of the target area, the meteorological field of the target area is simulated ensemble using the WRF numerical model system to obtain an hourly meteorological field ensemble simulation data set.

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

[0010] The en-route flow field sensitivity model is constructed using the hourly en-route meteorological variables of the low-altitude wind field in the target area, and then the en-route flow field sensitivity is calculated.

[0011] The sensitivity of the route flow field is used to determine the spatial distribution of the sensitivity of the route flow field in the low-altitude routes in the target area.

[0012] 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.

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

[0014] ;

[0015] 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 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.

[0016] Preferably, the meteorological elements included in the meteorological field set simulation data set include wind speed, temperature, relative humidity and air pressure.

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

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

[0019] Another object of the present invention is to provide a system for determining a flow field sensitive area of ​​a low-altitude economic route based on ensemble simulation, which adopts the method for determining a flow field sensitive area of ​​a low-altitude economic route based on ensemble simulation, including 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:

[0020] The acquisition unit is used to obtain 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 acquired initial condition and boundary condition data of the target area, and obtain an hourly ensemble simulation data set of the meteorological field.

[0022] 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 a meteorological field set simulation data set.

[0023] 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.

[0024] 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.

[0025] 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.

[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, 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 ​​the low-altitude economic route based on ensemble simulation.

[0027] Another object of the present invention is to provide a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions enable the computer to execute the method for determining the flow field sensitive area of ​​the low-altitude economic route based on ensemble simulation.

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

[0029] The present invention uses the WRF numerical model system to perform ensemble simulation on the meteorological field of the target area according to the acquired meteorological initial conditions and boundary conditions data of the target area, obtains an hourly image field ensemble simulation data set, and then determines the hourly route meteorological variables of the low-altitude wind field in the target area. Then, the route flow field sensitivity model is constructed using the obtained hourly route meteorological variables of the low-altitude wind field in the target area, and the route flow field sensitivity is calculated. On this basis, the sensitivity spatial distribution of the route flow field sensitivity in the low-altitude route of the target area is determined, and finally, the low-altitude economic route flow field sensitive area of ​​the target area is determined according to the sensitivity threshold. Therefore, it can reasonably plan the low-altitude airspace routes of the target area, reasonably set the drone take-off and landing areas, avoid the meteorological disaster-prone areas with obvious impact on the low-altitude economy, and reduce the meteorological disaster risks of the routes. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a flow chart of the method for determining the flow field sensitive area of ​​low-altitude economic routes based on ensemble simulation.

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

[0032] Figure 3 This is the spatial distribution of the sensitivity of the airway flow field at an altitude of 300m during north wind in winter.

[0033] Figure 4 This is the spatial distribution of the sensitivity of the airway flow field at an altitude of 600m during north wind in winter.

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

[0035] Figure 6 This is the spatial distribution of the sensitivity of the airway flow field at an altitude of 300m during southeast winds in summer.

[0036] Figure 7 This is the spatial distribution of the sensitivity of the airway flow field at an altitude of 600m during southeast winds in summer. DETAILED DESCRIPTION

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

[0038] Example 1

[0039] This embodiment provides a method for determining the flow field sensitive area of ​​a low-altitude economic route based on ensemble simulation. Figure 1 As shown, the following steps are included:

[0040] Step S1, obtaining meteorological initial conditions and boundary conditions data of the 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, based on the acquired meteorological initial conditions and boundary conditions data of the target area, the meteorological field of the target area is collectively simulated using the WRF numerical model system to obtain an hourly meteorological field collective simulation data set, wherein the meteorological elements included in the meteorological field collective simulation data set include wind speed (wind direction), temperature, relative humidity and air pressure.

[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 developed by the National Oceanic and Atmospheric Administration (NOAA), the Pacific Northwest National Laboratory (PNNL), and the National Center for Atmospheric Research (NCAR). The resolution of the WRF numerical model system used is 0.1-2KM.

[0043] In the process of ensemble simulation of the low-altitude wind field in the target area using the WRF numerical model system, three-layer nesting is used for simulation. 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 global atmospheric reanalysis dataset is interpolated to the target area using the interpolation method and then simulated; 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.

[0044] The ensemble simulation is carried out on the third nested layer d03 of the model. The initial field ensemble sample is obtained by adding random perturbations to the initial field. In order 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 boundary condition ensemble samples. After ensemble simulation, the hourly meteorological field ensemble simulation data set of the target area is obtained.

[0045] Step S3, determining the hourly route meteorological variables of the low-altitude wind field in the target area through the meteorological field set simulation data set, and the hourly route meteorological variables of the low-altitude wind field in the target area extracted from the meteorological field set simulation data set include wind speed (wind direction), temperature, and relative humidity.

[0046] Step S4, constructing an en-route flow field sensitivity model using the obtained hourly en-route meteorological variables of the low-altitude wind field in the target area, and then obtaining the en-route flow field sensitivity.

[0047] The route flow field sensitivity model is:

[0048] ;

[0049] 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 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.

[0050] This embodiment constructs an airway flow field sensitivity model through wind speed, air temperature, and relative humidity, and the obtained airway flow field sensitivity has high accuracy. The airway flow field sensitivity can be used to quantify the impact of the initial velocity field in the model area on the predicted airway flow field of the entire target at a certain moment or time period, and the sensitive area affecting the airway flow field is determined according to its relative size and distribution. The division is more reliable, avoiding areas prone to meteorological disasters that have a significant impact on the low-altitude economy, and reducing the risk of meteorological disasters on the route.

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

[0052] Step S6, determining the low-altitude economic route flow field sensitive area of ​​the target area according to the sensitivity spatial distribution and the sensitivity threshold, that is, taking the area greater than the sensitivity threshold in the sensitivity spatial distribution as the low-altitude economic route flow field sensitive area of ​​the target area. In this embodiment, in the WRF numerical model system, the low-altitude economic route flow field sensitive area of ​​the target area is determined by the contour lines of the sensitivity threshold and the numerical value of the sensitivity spatial distribution. In this embodiment, the sensitivity threshold used is 0.2, in another embodiment, the sensitivity threshold used is 0.15, and in another embodiment, the sensitivity threshold used is 0.3.

[0053] Example 2

[0054] This embodiment provides a system for determining a flow field sensitive area of ​​a low-altitude economic route based on ensemble simulation, and adopts the method for determining a flow field sensitive area of ​​a low-altitude economic route based on ensemble simulation, including 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:

[0055] The acquisition unit is used to obtain 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 acquired meteorological initial conditions and boundary conditions data of the target area, and obtain an hourly ensemble simulation data set of the meteorological field. The resolution of the adopted WRF numerical model system is 0.1-2KM.

[0057] 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 a meteorological field set simulation data set.

[0058] 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.

[0059] The route flow field sensitivity model is:

[0060] ;

[0061] 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 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.

[0062] 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.

[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 sensitivity spatial distribution 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 lines of the sensitivity threshold and the numerical value of the sensitivity spatial distribution. In this embodiment, the sensitivity threshold used is 0.2, in another embodiment, the sensitivity threshold used is 0.15, and in another embodiment, the sensitivity threshold used is 0.3.

[0064] Example 3

[0065] This embodiment provides an electronic device, including: 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 ​​the low-altitude economic route based on ensemble simulation.

[0066] In another embodiment, a non-transitory computer-readable storage medium is provided, wherein the non-transitory computer-readable storage medium stores computer instructions, wherein 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.

[0067] Example 4

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

[0069] Step S1, obtaining meteorological initial conditions and boundary condition data of a designated target area by using a global atmospheric reanalysis dataset, and interpolating the global atmospheric reanalysis dataset to obtain meteorological initial conditions and boundary condition data of the designated target area.

[0070] Step S2, based on the acquired meteorological initial conditions and boundary conditions data of the designated target area, the meteorological field of the designated target area is collectively simulated using the WRF numerical model system to obtain an hourly meteorological field collective simulation data set, wherein the meteorological elements included in the meteorological field collective simulation data set include wind speed, wind direction, temperature, relative humidity and air pressure, etc. The resolution of the adopted WRF numerical model system is 1KM.

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

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

[0073] When simulating the first layer d01 of the model, the initial and boundary conditions of the meteorological field are based on the global meteorological reanalysis data set FNL provided by the National Center for Atmospheric Research in the United States. The global meteorological reanalysis data are interpolated to the simulation area using an interpolation program for simulation. 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 data set.

[0074] The ensemble simulation is carried out on the third layer d03 of the model. We obtain an ensemble sample of 50 initial fields by adding random perturbations to the initial fields. In order to ensure that the ensemble sensitivity of the predicted variables is within a certain range, we also add random perturbations to the boundary conditions and obtain the corresponding 50 boundary conditions.

[0075] Step S3, determining the hourly route meteorological variables of the low-altitude wind field in the designated target area through the meteorological field set simulation data set.

[0076] Step S4, constructing an en-route flow field sensitivity model using the obtained hourly en-route meteorological variables of the low-altitude wind field in the designated target area, and then obtaining the en-route flow field sensitivity.

[0077] The route flow field sensitivity model is:

[0078] ;

[0079] 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 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.

[0080] The sensitivity of the route flow field can be used to quantify the impact of the initial velocity field in the model area on the predicted route flow field in the entire specified target area at a certain moment or time period, and the sensitive area affecting the route flow field can be determined based on its relative size and distribution.

[0081] Step S5, determining the spatial distribution of the sensitivity of the route flow field in the low-altitude route of the designated target area through the route flow field sensitivity, simulating the distribution of the designated target area according to the route flow field sensitivity in the WRF numerical model system, and determining the spatial distribution of the sensitivity of the low-altitude route of the designated target area.

[0082] The designated target area is a typical monsoon area, with prevailing northerly winds in winter and southeasterly winds in summer. This embodiment selects the simulated forecast of the wind field in two time periods, January 22-25, 2023 (representing winter, northerly wind) and July 25-30, 2023 (representing summer, southeasterly wind) for research.

[0083] like Figure 2-7As shown in the figure, the sensitivity spatial distribution of the airway flow field in the designated target area at 10m, 300m and 600m altitudes when there is north wind in winter and southeast wind in summer, respectively. It can be seen from the figure that the sensitivity of the airway flow field changes with the change of the wind field direction. In winter, when the incoming flow is north wind, the spatial distribution of the sensitivity of the airway flow field at the three altitude layers of the designated target area is very consistent, showing a trend of high in the north and low in the south, but the airway flow field sensitivity at an altitude of 300m is the largest, followed by that at an altitude of 600m, and the smallest near the ground. In summer, since the incoming flow direction changes to southeast wind, the sensitivity of the airway flow field shows a decreasing trend from southeast to northwest, and the airway flow field sensitivity at an altitude of 300m is the largest, followed by that at an altitude of 600m, and the smallest near the ground. Overall, the sensitivity of the airway flow field in winter is greater than that in summer.

[0084] Step S6, determining the low-altitude economic airway flow field sensitive area of ​​the designated target area according to the sensitivity spatial distribution and the sensitivity threshold. In the WRF numerical model system, the low-altitude economic airway flow field sensitive area of ​​the designated target area is determined by the contour lines of the sensitivity threshold and the value of the sensitivity spatial distribution. In this embodiment, the sensitivity threshold used is 0.2.

[0085] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection 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; 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 in that: 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 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.

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, 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.

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: 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 field ensemble sample is obtained by adding random perturbations to the initial field, and random perturbations are added to the boundary conditions to obtain the corresponding boundary condition ensemble samples.

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 meteorological elements included in the meteorological field set simulation data set are wind speed, temperature, relative humidity and air pressure.

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 resolution of the WRF numerical model system is 0.1-2KM.

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

3.

8. 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.

9. 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 1-7.

10. 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 7.

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