A method for simulating atmospheric pollution diffusion and migration with high temporal and spatial resolution

Abstract

The present invention is to solve the technical problem that when the FLEXPART model is used in the numerical study of the existing atmospheric pollutant diffusion law, the spatial resolution of the mesoscale meteorological model WRF used to drive FLEXPART to simulate the pollutant diffusion is low, and FLEXPART cannot be driven to simulate the pollutant diffusion at the block scale. A high spatiotemporal resolution atmospheric pollution diffusion migration simulation method is provided. On the basis of the mesoscale three-dimensional meteorological simulation, the present invention first adopts a downscaling meteorological diagnostic model to perform a dynamic downscaling diagnostic simulation, and spatially downscales the meteorological field data with a spatial resolution of 3-5km obtained by the mesoscale meteorological model to a spatial resolution of 100 meters. Subsequently, a self-programming coupling interface program is used to convert the block-scale three-dimensional meteorological field data into a data format readable by the FLEXPART model, and the block-scale meteorological field data is used to drive the FLEXPART model to perform the numerical calculation of the next step of the atmospheric pollutant diffusion process, thereby realizing a high spatiotemporal resolution simulation of pollutant diffusion at the block scale.

Description

Technical Field

[0001] The present invention relates to the field of air pollution monitoring technology, in particular to numerical simulation of air pollution diffusion and migration at small and medium scales, and more particularly to a method for simulating air pollution diffusion and migration with high temporal and spatial resolution. Background Art

[0002] Due to the large-scale emission of air pollutants and their precursors, many cities often suffer from serious air pollution problems. Especially in recent years, PM 2.5 The concentration rose sharply, and there were several outbreaks of severe PM 2.5 Pollution incident. PM 2.5 The main sources of ozone pollution include coal burning, motor vehicle emissions, biomass burning, etc., which not only affect visibility, but also enter the human respiratory system or other organs, endangering human health. In addition to particulate matter pollution, urban gas pollution such as ozone pollution is also becoming more serious. Since the 1990s, the ozone concentration in many urban agglomerations has risen very rapidly. The average ozone concentration in some areas has reached 179-208μg / m 3 It can be seen that air pollution has become a major environmental issue, with significant impacts on human health and climate change.

[0003] Numerical models for studying the diffusion of atmospheric pollutants can generally be divided into three categories: Gaussian diffusion models, Eulerian diffusion models, and Lagrangian particle diffusion models. The Gaussian diffusion model was the earliest developed and is a relatively mature empirical model (e.g., "Application of the Gaussian Model in Simulating Multi-Point Source Atmospheric Diffusion in Small and Medium-sized Cities," a master's thesis from Harbin Normal University, 2020; and "Study of a GIS System for Gas Leak Diffusion under Variable Wind Fields," a master's thesis from Chongqing University, 2018). The Gaussian model is a classic and convenient analytical model, but it is a steady-state model with a relatively simple consideration of meteorological and topographic (underlying surface) factors. Therefore, it is difficult to apply to numerical simulations under complex unsteady conditions. The Euler diffusion model discretizes the computational domain into three-dimensional space and simultaneously solves conservation equations for different discrete grids to obtain the component characteristics of pollutants within each grid. Popular computational models include the WRF-CMAQ mesoscale model ("Study on Air Pollution Characteristics in Shenyang Based on the WRF-CMAQ Model," Shenyang Aerospace University Master's Thesis, 2020) and the CFD model ("Atmospheric Pollution Simulation Based on the Multiphase Particle Mesh Method," Science, Technology and Engineering, Vol. 20, No. 14, 2020). The advantage of the Euler diffusion model is that it can parameterize certain complex physical processes and perform refined modeling. However, the Euler model is generally computationally expensive and has certain limitations in its numerical convergence, making it unsuitable for rapid evaluation. The core of the Lagrangian particle model is to track the spatiotemporal changes in particle physical behavior. Representative models include the HYSPLIT model ("Research on Atmospheric CO2 Transport Based on the HYSPLIT Model", Master's thesis of China University of Geosciences (Beijing), 2014) and the FLEXPART model ("Preliminary Study on the Applicability of the FLEXPART Model in Beijing", Journal of Environmental Sciences, August 2010, Vol. 30, No. 8).

[0004] The FLEXPART model, a well-established and easily portable Lagrangian particle diffusion model, lies between simple trajectory calculations and atmospheric chemistry models in terms of complexity. Compared to the Eulerian diffusion model, the FLEXPART model offers advantages such as high spatiotemporal resolution, short computation time, and backward trajectory tracking. Furthermore, the FLEXPART model incorporates turbulence and small- and medium-scale convection processes, enabling it to accurately simulate tracer diffusion, deposition, and attenuation.

[0005] However, the current FLEXPART model still has shortcomings in simulating atmospheric pollutant dispersion processes at the block scale (calculation area is approximately 10×10 km, spatial resolution is 100 meters). One of the main reasons is that the spatial resolution of the mesoscale meteorological model WRF used to drive FLEXPART pollutant dispersion simulation is generally only on the order of 3-5 km, which is not enough to drive FLEXPART to simulate pollutant dispersion at the block scale. Therefore, it is of great significance to study how to use the FLEXPART model to capture the spatiotemporal distribution characteristics of atmospheric pollutant dispersion at the block scale with high temporal and spatial resolution, thereby conducting in-depth analysis of atmospheric pollution diffusion and deposition processes. Summary of the Invention

[0006] The purpose of the present invention is to solve the technical problem that when the FLEXPART model is used in the existing numerical research on the diffusion law of atmospheric pollutants, the mesoscale meteorological model WRF used to drive FLEXPART for pollutant diffusion simulation has low spatial resolution and cannot drive FLEXPART to simulate pollutant diffusion at the block scale. The present invention provides a high temporal and spatial resolution atmospheric pollution diffusion and migration simulation method.

[0007] The concept of the present invention is to first perform dynamic downscaling diagnostic simulations using a downscaling meteorological diagnostic model based on a mesoscale 3D meteorological simulation. The hourly meteorological field data with a spatial resolution of 3-5 km obtained by the mesoscale meteorological model is spatially downscaled to a spatial resolution of 100 meters. Subsequently, a coupling interface program is used to convert the block-scale 3D meteorological field data into a data format readable by the FLEXPART model. This block-scale meteorological field data is then used to drive the FLEXPART model to perform numerical calculations of the atmospheric pollutant diffusion process, thereby achieving high spatiotemporal resolution (spatial resolution of 100 meters, temporal resolution of minutes) simulations of pollutant diffusion at the block scale.

[0008] In order to achieve the above-mentioned purpose of the invention and realize the above-mentioned concept, the technical solution adopted by the present invention is:

[0009] A high temporal and spatial resolution atmospheric pollution diffusion and migration simulation method is characterized in that it includes the following steps:

[0010] Step 1: Using a mesoscale meteorological model, simulate the mesoscale meteorological field of the proposed study area at set time intervals during the proposed study period to obtain three-dimensional meteorological field data within the mesoscale range including the proposed study area during the proposed study period;

[0011] The three-dimensional meteorological field data includes temperature, air pressure, humidity, wind speed, wind direction and precipitation;

[0012] Step 2: Based on the three-dimensional meteorological field data within the mesoscale range obtained in step 1, a downscaling meteorological diagnostic model is used to perform dynamic downscaling diagnostic simulation in the proposed study area to obtain refined three-dimensional meteorological field data;

[0013] Step 3: Keeping the time interval and spatial resolution unchanged, use the coupling interface program to compare and map the refined three-dimensional meteorological field data obtained in step 2 with the meteorological field variables required for the FLEXPART model operation;

[0014] Step 4: Set the pollution source parameters in the parameter script of the FLEXPART model;

[0015] The source item parameters include output file path, three-dimensional meteorological data path, calculation domain start and end time, time parameters, grid parameters, emission species parameters, pollutant release location, pollutant release time, and pollutant release intensity;

[0016] Step 5: Combine the mapping results of step 3 and the source parameters set in step 4 to drive the FLEXPART model to simulate the migration and diffusion of atmospheric pollutants and obtain the concentration distribution and deposition information at different times.

[0017] Furthermore, in step 3, the coupling interface program is used to compare and map the refined three-dimensional meteorological field data obtained in step 2 with the meteorological field variables required for the operation of the FLEXPART model, specifically:

[0018] 3.1. Use the CALMET2NETCDF program to convert the result file of the refined three-dimensional meteorological field data obtained in step 2 into three NETCDF format files: CALGRID2D, CALMET2D, and CALMET3D. Among them, CALGRID2D is the grid information file, CALMET2D is the ground meteorological field data, and CALMET3D is the three-dimensional meteorological field data.

[0019] 3.2. Use the coupling interface program to map the meteorological field variables in the three files CALGRID2D, CALMET2D, and CALMET3D with the meteorological field variables required for the FLEXPART model operation.

[0020] Furthermore, in step 3.2, the variable mapping relationship between the meteorological field variables in the three files CALGRID2D, CALMET2D, and CALMET3D and the meteorological field variables required for the FLEXPART mode operation is specifically as follows:

[0021] Variable latitude: XLAT in FLEXPART mode corresponds to lat in CALGRID2D;

[0022] Variable longitude: XLONG in FLEXPART mode corresponds to lon in CALGRID2D;

[0023] Variable base potential: PHB=0 in FLEXPART mode corresponds to 0 in CALMET3D;

[0024] Variable perturbation potential: PH in FLEXPART mode corresponds to global attributes: VGLVLS in CALMET3D and ELEV in CALGRID2D;

[0025] Variable base pressure: PB=0 in FLEXPART mode corresponds to 0 in CALMET3D;

[0026] Variable wind speed component U: U in FLEXPART mode corresponds to U in CALMET3D;

[0027] Variable wind speed component V: V in FLEXPART mode corresponds to V in CALMET3D;

[0028] Variable wind speed component W: W in FLEXPART mode corresponds to W in CALMET3D;

[0029] Variable temperature T: T in FLEXPART mode corresponds to T in CALMET3D; variable 10m wind speed component U10: U10 in FLEXPART mode corresponds to U interpolation in CALMET3D, and 2m and 10m altitude layers are set when setting CALMET;

[0030] Variable 10m wind speed component V10: V10 in FLEXPART mode corresponds to V interpolation in CALMET3D, and the 2m and 10m altitude layers are set when setting CALMET;

[0031] Variable 2m air temperature: T2 in FLEXPART mode corresponds to T interpolation in CALMET3D, and the 2m and 10m altitude layers are set when setting CALMET;

[0032] Variable 2m specific humidity: Q2 in FLEXPART mode corresponds to IRH in CALMET2D: relative humidity (%) calculated and obtained; set the 2m and 10m altitude layers when setting CALMET;

[0033] Variable surface pressure: PSFC in FLEXPART mode corresponds to RHO in CALMET2D: air density p = RHO × Rd × Tv;

[0034] Variable large-scale precipitation: RAINNC in the FLEXPART model corresponds to RMM in CALMET2D;

[0035] Variable land use type: LU_INDEX in FLEXPART mode corresponds to ILANDU in CALGRID2D;

[0036] Variable friction speed: UST in FLEXPART mode corresponds to USTAR in CALMET2D;

[0037] Variable boundary layer height: PBLH in FLEXPART mode corresponds to ZI in CALMET2D;

[0038] Variable shortwave radiation: SWDOWN in FLEXPART mode corresponds to QSW in CALMET2D.

[0039] Furthermore, in step five, during the migration and diffusion simulation, a turbulence parameterization method is used to estimate the turbulent mixing effect and the boundary layer height in the convective boundary layer; and a convective parameterization method based on three-dimensional turbulent kinetic energy is used to calculate the small and medium-scale convective processes.

[0040] Furthermore, in step 1, the meteorological field simulation of the mesoscale model adopts a three-layer nesting method, and the innermost layer needs to cover the proposed study area, wherein the spatial resolution of the innermost layer is 3 km.

[0041] Furthermore, in step 2, the block scale of the refined three-dimensional meteorological field data is 10km×10km, the spatial horizontal grid resolution is 100m, and the vertical direction is divided into more than ten layers.

[0042] Furthermore, in step 1, the set time interval is 1 hour.

[0043] Furthermore, in step five, the spatial resolution of the migration and diffusion simulation results obtained by the FLEXPART model is 100m, the vertical maximum resolution is 20m, and the time resolution reaches the minute level.

[0044] Compared with the prior art, the present invention has the following beneficial technical effects:

[0045] 1. The high-temporal-spatial resolution atmospheric pollution diffusion and migration simulation method provided by the present invention is based on the downscaling coupling technology. Based on the meteorological data of the mesoscale three-dimensional meteorological simulation, the method adopts a downscaling meteorological diagnostic model to perform dynamic downscaling diagnostic simulation to obtain the three-dimensional meteorological field distribution parameters at the block scale, and realizes the spatial downscaling of the meteorological field data of the mesoscale meteorological model with an hourly spatial resolution of 3-5 km to a spatial resolution of 100 meters.

[0046] 2. The high-temporal-resolution atmospheric pollution diffusion and migration simulation method provided by the present invention utilizes a self-programming coupling interface to couple the downscaled three-dimensional meteorological model and the FLEXPART model to achieve high-temporal-resolution numerical simulation of atmospheric pollutant diffusion at the block scale. It has the characteristics of high temporal-spatial resolution. In the simulation of physical problems at the block scale, the temporal resolution can reach the order of minutes, the spatial horizontal resolution can reach the order of hundreds of meters, and the spatial vertical resolution can reach 20 meters.

[0047] 3. In the numerical simulation process of the diffusion and migration of pollutants, the present invention takes into account the model turbulence and small and medium-scale convection, and adopts the turbulence parameterization method to estimate the turbulent mixing effect and boundary layer height in the convective boundary layer. It takes into account both the inclination of the turbulence in the vertical velocity and the vertical gradient of the air density, making the factors of turbulence in the simulation of atmospheric pollution diffusion and migration more complete, and can better calculate the mixing state in the convective boundary layer; the convection parameterization method based on three-dimensional turbulent kinetic energy is used to calculate the small and medium-scale convection process, which can more accurately capture the atmospheric diffusion process of pollutants.

[0048] 4. The method of the present invention consumes little computing resources and takes little computation time. Given the availability of downscaled three-dimensional meteorological field data, the entire diffusion migration calculation process can be completed within 5 minutes on a single machine, making it suitable for rapid assessment of accident consequences. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 This is a flow chart of the method for simulating atmospheric pollution diffusion and migration with high temporal and spatial resolution according to the present invention;

[0050] Figure 2 : The wind field distribution with a resolution of 100 m × 100 m obtained by the downscaling model in the embodiment of the present invention; (a) is the surface wind vector diagram of the calculated area at the time of pollutant release; (b) is the surface wind vector diagram of the calculated area 1 hour after the pollutant release; (c) is the surface wind vector diagram of the calculated area 2 hours after the pollutant release; (d) is the surface wind vector diagram of the calculated area 3 hours after the pollutant release; (e) is the surface wind vector diagram of the calculated area 4 hours after the pollutant release; and (f) is the surface wind vector diagram of the calculated area 5 hours after the pollutant release.

[0051] Figure 3 The meteorological file is read into FLEXPART after conversion using the coupling interface in the embodiment of the present invention;

[0052] Figure 4The following are cloud maps of pollutant concentration distribution at different times at the block scale output by the FLEXPART model in an embodiment of the present invention; (a) is a cloud map of the surface concentration distribution of the area calculated at the moment of pollutant release; (b) is a cloud map of the surface concentration distribution of the area calculated 1 hour after the pollutant release; (c) is a cloud map of the surface concentration distribution of the area calculated 2 hours after the pollutant release; (d) is a cloud map of the surface concentration distribution of the area calculated 3 hours after the pollutant release; (e) is a cloud map of the surface concentration distribution of the area calculated 4 hours after the pollutant release; and (f) is a cloud map of the surface concentration distribution of the area calculated 5 hours after the pollutant release.

[0053] Figure 5 The following are the distribution cloud maps of pollutant deposition at different times at the block scale output by the FLEXPART model in an embodiment of the present invention; (a) is the surface deposition distribution cloud map of the calculated area at the moment of pollutant release; (b) is the surface deposition distribution cloud map of the calculated area 1 hour after the pollutant release; (c) is the surface deposition distribution cloud map of the calculated area 2 hours after the pollutant release; (d) is the surface deposition distribution cloud map of the calculated area 3 hours after the pollutant release; (e) is the surface deposition distribution cloud map of the calculated area 4 hours after the pollutant release; and (f) is the surface deposition distribution cloud map of the calculated area 5 hours after the pollutant release. DETAILED DESCRIPTION

[0054] To make the objects, advantages, and features of the present invention more apparent, the following describes in further detail a method for simulating atmospheric pollution diffusion and migration with high temporal and spatial resolution, in conjunction with the accompanying drawings and specific examples. Those skilled in the art should understand that these embodiments are merely intended to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0055] like Figure 1 As shown, the high temporal and spatial resolution atmospheric pollution diffusion and migration simulation method provided in this embodiment specifically includes five steps:

[0056] Step 1: Use a mesoscale meteorological model to simulate the mesoscale meteorological field of the proposed study area during the proposed study period, and obtain three-dimensional meteorological field data within the mesoscale range including the proposed study area during the proposed study period;

[0057] In this embodiment, the meteorological field simulation of the mesoscale model adopts a three-layer nesting method, the innermost layer has a spatial resolution of 3 km, and the spatial resolutions are 27 km, 9 km and 3 km respectively. The innermost layer needs to cover the proposed study area.

[0058] The selection of physical parameterization schemes in the mesoscale model is shown in Table 1.

[0059] Table 1 WRF model physical process settings

[0060]

[0061] The hourly three-dimensional meteorological field data within the mesoscale range include temperature, air pressure, humidity, wind speed, wind direction, and precipitation.

[0062] Step 2: Using the downscaling meteorological diagnostic model, the meteorological data output by the mesoscale meteorological model are spatially simulated using dynamic downscaling diagnostic simulations.

[0063] In the downscaling meteorological diagnosis mode, the meteorological field output by the mesoscale meteorological model is set as the preliminary meteorological field. The calculation domain (block scale) needs to cover the emission sources of atmospheric pollutants. The calculation domain range is 10km×10km, the horizontal grid resolution is 100m, and the vertical direction is divided into more than ten layers. The final output is a refined wind field with a spatial horizontal resolution of about 100m per hour, such as Figure 2 As shown in Figure 2, the surface wind vector diagrams of the area were calculated from 0 to 5 hours after the pollutant release. (a) to (f) are the surface wind vector diagrams at the moment of pollutant release and every hour after the release, respectively.

[0064] The core parameter settings of the downscaling meteorological diagnostic model are shown in Table 2.

[0065] Table 2 List of core parameter settings for downscaling meteorological diagnostic model

[0066]

[0067] Step 3: Use the CALMET2NETCDF program to convert the downscaling meteorological diagnostic model output file into three NETCDF format files: CALGRID2D, CALMET2D, and CALMET3D. CALGRID2D is the grid information file, CALMET2D is the ground meteorological field data, and CALMET3D is the three-dimensional meteorological field data.

[0068] Furthermore, the self-written model coupling interface program module is used to compare and map the meteorological field variables in the three files CALGRID2D, CALMET2D, and CALMET3D with the meteorological field variables required for the operation of the FLEXPART model, that is, to convert the downscaled meteorological field information output by the CALMET model into the input files required by the FLEXPART model (such as Figure 3 As shown), to drive FLEXPART to simulate pollution diffusion and migration.

[0069] The coupling process requires variable mapping between the meteorological field output by the CALMET model and the meteorological field required by the FLEXPART model. The variable mapping relationship between the two models is shown in Table 3:

[0070] Table 3 Mapping relationship between variables required for FLEXPART mode operation and variables in CALMET results

[0071]

[0072]

[0073] Step 4: Set the calculation parameters in the flexwrf.input file. Specific settings include the output file path, CALMET meteorological data path, calculation domain start and end times, time-related parameter settings, grid-related parameter settings, emission species-related parameter settings, and pollutant release information (release location, release time, release intensity, etc.).

[0074] Step 5: Use the FLEXPART mode to read the downscaled meteorological field in the converted format, and perform numerical simulation of the diffusion and migration of pollutants based on the defined source parameter information.

[0075] In the numerical simulation of the diffusion and migration of pollutants, the turbulence parameterization method is used to estimate the turbulent mixing effect and boundary layer height in the convective boundary layer. This method takes into account both the inclination of turbulence in the vertical velocity and the vertical gradient of air density. Therefore, this method considers the turbulence factors more completely and can better calculate the mixing state in the convective boundary layer. In terms of convection, the convection parameterization method based on three-dimensional turbulent kinetic energy is used to calculate small and medium-scale convective processes, so it can more accurately capture the atmospheric diffusion process of pollutants.

[0076] This step requires setting the LDIRECT parameter in the FLEXPART model parameter file flexwrf.input to 1 to control the FLEXPART simulation of the tracer diffusing from the source area to the surrounding area.

[0077] The variables output by FLEXPART simulation are: concentration (CONC, pollutant concentration, unit: ng·m -3 ,ng=10 -9 g)(e.g. Figure 4 DRYDEP: cumulative total dry deposition. Unit: pg·m -2 ,ng=10 -12 g)(e.g. Figure 5 shown).

[0078] Figure 4 The surface concentration distribution cloud maps of the region are calculated from 0 to 5 hours after the pollutant release. (a) to (f) are the surface concentration distribution cloud maps of the region calculated at the moment of pollutant release and every hour after the release, respectively.

[0079] Figure 5 The surface deposition distribution cloud maps of the region are calculated from 0 to 5 hours after the pollutant release. (a) to (f) are the surface deposition distribution cloud maps of the region calculated at the moment of pollutant release and every hour after the release, respectively.

[0080] Post-processing and mapping of the results reveals patterns in the diffusion and deposition of pollutants emitted from the source. The computational domain and spatial resolution of the FLEXPART model are the same as those of the CALMET model: a 10 km × 10 km domain with a horizontal spatial resolution of 100 m and a temporal resolution of minutes.

[0081] The present invention can overcome the problem of low spatiotemporal resolution in existing atmospheric pollution diffusion models, thereby enabling the FLEXPART model to accurately simulate and capture the diffusion, transmission, and deposition processes of atmospheric pollutants in environments such as industrial parks and urban blocks, based on the dynamic downscaling of the simulation results of the mesoscale meteorological model.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the present invention.

Claims

1. A high temporal and spatial resolution atmospheric pollution diffusion and migration simulation method, characterized in that: The following steps are involved: Step 1: Using a mesoscale meteorological model, simulate the mesoscale meteorological field of the proposed study area at set time intervals during the proposed study period to obtain three-dimensional meteorological field data within the mesoscale range including the proposed study area during the proposed study period; The three-dimensional meteorological field data includes temperature, air pressure, humidity, wind speed, wind direction and precipitation; Step 2: Based on the three-dimensional meteorological field data within the mesoscale range obtained in step 1, a downscaling meteorological diagnostic model is used to perform dynamic downscaling diagnostic simulation in the proposed study area to obtain refined three-dimensional meteorological field data; Step 3: Keeping the time interval and spatial resolution unchanged, use the coupling interface program to compare and map the refined three-dimensional meteorological field data obtained in step 2 with the meteorological field variables required for the FLEXPART model operation; Step 4: Set the pollution source parameters in the parameter script of the FLEXPART model; The source item parameters include output file path, three-dimensional meteorological data path, calculation domain start and end time, time parameters, grid parameters, emission species parameters, pollutant release location, pollutant release time and pollutant release intensity; Step 5: Combine the mapping results of step 3 and the source parameters set in step 4 to drive the FLEXPART model to simulate the migration and diffusion of atmospheric pollutants and obtain the concentration distribution and deposition information at different times.

2. The high temporal and spatial resolution atmospheric pollution diffusion and migration simulation method according to claim 1, characterized in that: In step 3, the coupling interface program is used to compare and map the refined three-dimensional meteorological field data obtained in step 2 with the meteorological field variables required for the FLEXPART model operation, specifically: 3.

1. Use the CALMET2NETCDF program to convert the result file of the refined three-dimensional meteorological field data obtained in step 2 into three NETCDF format files: CALGRID2D, CALMET2D, and CALMET3D. Among them, CALGRID2D is the grid information file, CALMET2D is the ground meteorological field data, and CALMET3D is the three-dimensional meteorological field data. 3.

2. Use the coupling interface program to map the meteorological field variables in the three files CALGRID2D, CALMET2D, and CALMET3D with the meteorological field variables required for the FLEXPART model operation.

3. The high temporal and spatial resolution atmospheric pollution diffusion and migration simulation method according to claim 2, characterized in that: In step 3.2, the variable mapping relationship between the meteorological field variables in the three files CALGRID2D, CALMET2D, and CALMET3D and the meteorological field variables required for the FLEXPART mode operation is specifically as follows: Variable latitude: XLAT in FLEXPART mode corresponds to lat in CALGRID2D; Variable longitude: XLONG in FLEXPART mode corresponds to lon in CALGRID2D; Variable base potential: PHB=0 in FLEXPART mode corresponds to 0 in CALMET3D; Variable perturbation potential: PH in FLEXPART mode corresponds to global attributes: VGLVLS in CALMET3D and ELEV in CALGRID2D; Variable base pressure: PB=0 in FLEXPART mode corresponds to 0 in CALMET3D; Variable wind speed component U: U in FLEXPART mode corresponds to U in CALMET3D; Variable wind speed component V: V in FLEXPART mode corresponds to V in CALMET3D; Variable wind speed component W: W in FLEXPART mode corresponds to W in CALMET3D; Variable temperature T: T in FLEXPART mode corresponds to T in CALMET3D; variable 10m wind speed component U10: U10 in FLEXPART mode corresponds to U interpolation in CALMET3D, and 2m and 10m altitude layers are set when setting CALMET; Variable 10m wind speed component V10: V10 in FLEXPART mode corresponds to V interpolation in CALMET3D, and the 2m and 10m altitude layers are set when setting CALMET; Variable 2m temperature: T2 in FLEXPART mode corresponds to T interpolation in CALMET3D, When setting CALMET, set the 2m and 10m altitude layers; Variable 2m specific humidity: Q2 in FLEXPART mode corresponds to IRH in CALMET2D: relative humidity percentage calculation; set the 2m and 10m altitude layers when setting CALMET; Variable surface pressure: PSFC in FLEXPART mode corresponds to RHO in CALMET2D: air density, obtained by calculating p = RHO × Rd × Tv; Variable large-scale precipitation: RAINNC in the FLEXPART model corresponds to RMM in CALMET2D; Variable land use type: LU_INDEX in FLEXPART mode corresponds to ILANDU in CALGRID2D; Variable friction speed: UST in FLEXPART mode corresponds to USTAR in CALMET2D; Variable boundary layer height: PBLH in FLEXPART mode corresponds to ZI in CALMET2D; Variable shortwave radiation: SWDOWN in FLEXPART mode corresponds to QSW in CALMET2D.

4. The high temporal and spatial resolution atmospheric pollution diffusion and migration simulation method according to claim 3, characterized in that: In step five, during the migration and diffusion simulation, a turbulence parameterization method is used to estimate the turbulent mixing effect and the boundary layer height in the convective boundary layer; a convective parameterization method based on three-dimensional turbulent kinetic energy is used to calculate the small and medium-scale convective processes.

5. The high temporal and spatial resolution atmospheric pollution diffusion and migration simulation method according to claim 4, characterized in that: In step 1, the meteorological field simulation of the mesoscale meteorological model adopts a three-layer nesting method, and the innermost layer needs to cover the proposed study area, wherein the spatial resolution of the innermost layer is 3 km.

6. The high temporal and spatial resolution atmospheric pollution diffusion and migration simulation method according to claim 5, characterized in that: In step 2, the block scale of the refined three-dimensional meteorological field data is 10 km × 10 km, the spatial horizontal grid resolution is 100 m, and the vertical direction is divided into more than ten layers.

7. The high temporal and spatial resolution atmospheric pollution diffusion and migration simulation method according to claim 6, characterized in that: In step 1, the set time interval is 1 hour.

8. The high temporal and spatial resolution atmospheric pollution diffusion and migration simulation method according to any one of claims 1 to 7, characterized in that: In step 5, the spatial resolution of the migration and diffusion simulation results obtained by the FLEXPART model is 100m, the highest vertical resolution is 20m, and the temporal resolution reaches the minute level.

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