Method and system for generating meteorological field of air quality model

Abstract

The application belongs to the technical field of air quality numerical prediction, and relates to an air quality model meteorological field generation method and system, the method comprising: 1) dividing a large area into multiple sub-areas, and determining an optimal parameterization scheme combination thereof; 2) setting a buffer area between adjacent sub-areas, and determining an optimal parameterization scheme combination thereof; 3) obtaining a first meteorological field of an inner layer nested area of each sub-area and each buffer area; 4) fitting east-west to obtain a second meteorological field of the inner layer nested area of each sub-area; 5) fitting south-north to obtain a final meteorological field of the inner layer nested area of each sub-area; 6) obtaining a meteorological field of the large area; and 7) obtaining a meteorological field of each nested area of a target area under an air quality model. According to the characteristics of the required meteorological field of the air quality model, the multi-area simulation result coupling technology is used, the prediction accuracy of the meteorological model is improved, and the prediction effect of the air quality model is further improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of air quality numerical prediction, and relates to a meteorological field generation method and system, in particular to an air quality model meteorological field generation method and system. BACKGROUND

[0002] With the development of numerical models, the numerical model method has become an important method in the prediction of pollutant concentration. In actual business prediction, the third generation air quality model is mainly used to construct an air quality prediction system. The mainstream third generation air quality model at present mainly includes a multiscale air quality model MODEL-3 / CAMQ (Community Multiscale Air Quality Modeling System), an atmospheric chemical transport model CAMx (Community Atmosphere Model), a WRF-CHEM model and a nested grid air quality prediction system (NAQPMS). The third generation air quality model contains a complex and perfect gas phase chemical and photochemical mechanism, and has good simulation and prediction ability for the temporal and spatial distribution of pollutants.

[0003] However, no matter which third generation air quality model is used to construct an air quality prediction system, a complete air quality prediction system mainly includes three parts of an emission source processing system (providing emission source input), a meteorological model (providing meteorological fields such as temperature, pressure, humidity and wind) and an air quality model (simulating the temporal and spatial distribution of pollutants). As can be seen, the meteorological field is an important input item of the air quality prediction system, and has a greater influence on the prediction accuracy of the air quality prediction system. Therefore, the prediction accuracy of the meteorological model has a greater influence on the prediction accuracy of the air quality.

[0004] In weather forecast, how to use weather model to get the most local actual weather field has been an important research topic, and each weather forecast department will organize special forces to carry out the localization of weather model. The parameter adjustment of weather model has been an important direction in the localization. Weather model contains a large number of physical parameterization schemes, which are mainly based on mathematical modeling to express various physical processes in the atmosphere, such as WRF weather model contains more than 10 kinds of parameterization schemes, such as cumulus convection parameterization scheme, boundary layer parameterization scheme, microphysical parameterization scheme, land surface process parameterization scheme, etc. Each type of parameterization scheme has multiple schemes to choose from, such as more than 10 boundary layer schemes can be selected, such as MYJ boundary layer parameterization scheme, MRF boundary layer parameterization scheme, ACM2 boundary layer parameterization scheme, QNSE boundary layer parameterization scheme, MYNN boundary layer parameterization scheme, etc. It is necessary to select the most suitable local parameterization scheme from various physical parameterization schemes according to the actual situation of the local area, that is, to select one from each type of boundary layer scheme, one from each type of cumulus convection parameterization scheme, and one from each type of other scheme. The optimal parameterization scheme combination is formed to make the weather model have the best prediction effect on the local area.

[0005] The existing localization of weather model has great practical significance for weather forecast, but there are some differences between the meteorological field required by the air quality model and the meteorological field required by the meteorological department in weather forecast. If the meteorological model of a certain area is adjusted and has good prediction effect on the local area, it can be applied to the local actual weather forecast system. However, the meteorological field required by the air quality model is generally a larger area. This is mainly because the impact of pollutant transport is large. For example, generally in the city scale, the local contribution of particulate matter is about 30%, and the transport contribution is about 70%; the local contribution of ozone is about 20%, and the transport contribution is about 80%. If the simulation prediction area is small, it is difficult to accurately consider the transport contribution of the surrounding area, and the simulation error of pollutant concentration is generally large.

[0006] This necessitates selecting a parameterization scheme combination applicable to a larger area during the parameter tuning process. However, it's difficult to find a parameterization scheme combination suitable for all areas, which is a significant factor contributing to low forecast accuracy. For example, a parameterization scheme combination might perform well in forecasting the meteorological field of region A, but poorly in forecasting the meteorological field of another neighboring region B, even though region B contributes significantly to the transmission of data from region A. The poor forecast performance of the meteorological field in region B, when used to drive an air quality model, will result in a larger forecast error for pollutant concentrations in region B. This larger forecast error in region B will then lead to a larger transmission error to region A, resulting in a larger forecast error for pollutant concentrations in region A. Therefore, even for air quality forecasting systems targeting region A, the accuracy of meteorological field forecasts in surrounding areas must be considered.

[0007] Existing technologies for improving the accuracy of meteorological field forecasts mainly employ methods such as data assimilation, ensemble forecasting, and improved parameterization schemes. Data assimilation primarily involves assimilating monitoring data to the initial field to improve its accuracy, thereby enhancing the accuracy of meteorological forecasts. Ensemble forecasting addresses the inherent errors in the initial field and various parameterization schemes by constructing multiple initial value ensembles based on the initial field, and building ensembles of physical processes based on different parameterization schemes of the same type. Each ensemble member drives a meteorological model, yielding a series of forecast results, which are then averaged using an ensemble mean. Improved parameterization schemes refine the physical representation of the parameterization schemes to more closely approximate actual atmospheric physical processes, thus making them applicable to larger regions. These technologies have all improved the accuracy of meteorological field forecasts to some extent, thereby enhancing the accuracy of air quality forecasts. However, these technologies still cannot solve the problem of cross-regional differences in air quality forecasting.

[0008] Chinese invention patent application No. 202211577968.1 discloses a method for determining weather forecast values ​​across multiple climate zones. This method primarily divides the target simulation area into multiple sub-regions according to the projection zone. Then, it interpolates the minimum-resolution nested simulation forecast values ​​of each sub-region onto latitude and longitude to generate weather forecast values ​​for each latitude and longitude of the target area. Because simulations are performed separately for two sub-regions, there will be differences in the simulation results for overlapping latitudes and longitudes between the two sub-regions. This method employs a weighted average to address these differences. However, this method is mainly used in the field of weather forecasting, where only a small relative error in the meteorological forecast values ​​at each latitude and longitude is required; abnormal discontinuities in the meteorological field do not need to be considered. For example, suppose the actual wind in the overlapping area and surrounding areas is westerly (270 degrees, 2 m / s) at a certain time. The wind forecast for the first sub-region (sub-region 1) is north-west (280 degrees, 2 m / s), and the wind forecast for the second sub-region (sub-region 2) is south-west (260 degrees, 2 m / s). If we follow weather forecasting requirements, both sub-regions show good forecast accuracy. If the overlapping area is weighted and averaged, the forecast error for the overlapping area is even smaller. However, the wind change from sub-region 1 to the overlapping area and then to sub-region 2 is northwesterly to westerly and then to southwesterly (forming a wind shear, which is an abnormal discontinuity). Although the polluted air mass generally still spreads from west to east, a weak convergence field forms at the boundary, causing pollutants to linger there. Therefore, this meteorological field is not suitable for air quality model simulation.

[0009] Meanwhile, the meteorological field used for weather forecasting only needs to stitch together the results from the inner nested regions of the meteorological model. The simulation results from the outer nested regions only provide initial and boundary values ​​to the inner nested regions and are not used for specific analysis. Therefore, the method in Chinese invention patent application number 202211577968.1 does not require processing of the outer nested regions. However, when driving an air quality model, not only the meteorological background field of the inner nested regions but also the meteorological field of the outer nested regions are needed. The meteorological fields of each nested region drive the air quality model of that region. The simulation results of the air quality model in the outer nested regions provide initial and boundary conditions to the inner nested regions. If the prediction error of the outer nested regions for a certain region in the air quality model is large, it will affect the prediction results of the inner nested regions. If the meteorological field of the outer nested region is stitched together using the method in the above-mentioned patent application, it will not only cause discontinuity of the meteorological field at the boundary region, but also cause a mismatch between the meteorological fields of the outer nested region and the inner nested region, since the inner nested region and the outer nested region are stitched together separately. (In the original simulation results of the meteorological model, the outer nested region and the inner nested region have direct feedback to each other and there will be no mismatch.)

[0010] Therefore, the technology disclosed in Chinese invention patent application No. 202211577968.1 is insufficient to meet the requirement of simultaneously achieving good simulation and prediction results for each sub-region within a large area when forecasting regional meteorological fields, thus failing to meet the needs of air quality model forecasting. Moreover, simple splicing not only causes discontinuities in the meteorological field at the splicing points but also results in mismatches in the meteorological fields between nested regions.

[0011] Therefore, in view of the shortcomings of the existing technology, there is an urgent need for a new method and system for generating meteorological fields for air quality models, so as to improve the accuracy of meteorological field prediction in various regions and thus improve the prediction effect of air quality models. Summary of the Invention

[0012] To address the shortcomings of existing technologies, this invention proposes a method and system for generating meteorological fields for air quality models. Based on fully considering the characteristics of the meteorological fields required for air quality models, a buffer zone is set up to simulate and predict in different regions. The meteorological fields generated in each region are fitted to obtain the meteorological field of a large region to drive the air quality model, thereby improving the accuracy of air quality model forecasts.

[0013] To achieve the above objectives, the present invention provides the following technical solution:

[0014] A method for generating meteorological fields for air quality models, characterized by comprising the following steps:

[0015] 1) Divide the large area into multiple sub-regions and determine the optimal combination of parameterization schemes for each sub-region based on the simulation results of meteorological field data from many years of history;

[0016] 2) Set up buffer zones between two adjacent sub-regions, and determine the optimal combination of parameterization schemes for each buffer zone based on the simulation results of meteorological field data from many years of history;

[0017] 3) Use the optimal parameterization scheme combination of each sub-region and each buffer region to predict future weather, and obtain the first meteorological field of the inner nested region of each sub-region and each buffer region;

[0018] 4) By combining the first meteorological field of the inner nested region of the buffer zone between the east-west sub-regions and the first meteorological field of the inner nested region of each sub-region, east-west fitting is performed to obtain the second meteorological field of the inner nested region of each sub-region.

[0019] 5) By combining the first meteorological field of the inner nested region of the buffer zone between the north-south sub-regions and the second meteorological field of the inner nested region of each sub-region, a north-south fitting is performed to obtain the final meteorological field of the inner nested region of each sub-region.

[0020] 6) The final meteorological fields of the inner nested regions of each sub-region are spliced ​​together to obtain the meteorological field of the large region;

[0021] 7) The large region is truncated according to the geographical range of each nested region of the target region under the air quality model, and the meteorological field of each nested region of the target region under the air quality model is obtained based on the meteorological field of the truncated large region.

[0022] Preferably, step 1) of determining the optimal parameterization scheme combination for each sub-region based on the simulation results of meteorological field data from many years of history specifically includes:

[0023] 11) Based on a certain sub-region, simulate the meteorological field of the sub-region over many years using different combinations of parameterization schemes, use monitoring data to verify the simulation effect, and select the optimal combination of parameterization schemes for the sub-region.

[0024] 12) Simulate the historical meteorological fields of each adjacent sub-region of this sub-region using different combinations of parameterization schemes, verify the simulation effect using monitoring data, screen out the better combinations of parameterization schemes for each adjacent sub-region of this sub-region, and determine the optimal combinations of parameterization schemes for each adjacent sub-region of this sub-region by referring to the optimal combinations of parameterization schemes for this sub-region, with the principle of minimizing the adjustment relative to the optimal combinations of parameterization schemes for this sub-region.

[0025] 13) Simulate the historical meteorological fields of other adjacent sub-regions of each adjacent sub-region using different combinations of parameterization schemes. Use monitoring data to verify the simulation effect, screen out the better combinations of parameterization schemes of other adjacent sub-regions of each adjacent sub-region of this sub-region, and refer to the optimal combinations of parameterization schemes of each adjacent sub-region of this sub-region. The optimal combinations of parameterization schemes of other adjacent sub-regions of each adjacent sub-region of this sub-region are determined with the principle of minimizing the adjustment relative to the optimal combinations of parameterization schemes of each adjacent sub-region of this sub-region.

[0026] Preferably, step 2) of determining the optimal parameterization scheme combination for each buffer zone based on the simulation effect of meteorological field data over many years specifically includes: simulating the meteorological field of the buffer zone over many years using different parameterization scheme combinations, verifying the simulation effect using monitoring data, selecting the better parameterization scheme combination for the buffer zone, and referring to the optimal parameterization scheme combination of two adjacent sub-regions of the buffer zone, with the principle of minimizing the adjustment relative to the optimal parameterization scheme combination of the two adjacent sub-regions of the buffer zone, to determine the optimal parameterization scheme combination for the buffer zone.

[0027] Preferably, step 4) specifically includes:

[0028] 41) Divide the buffer zone between the sub-regions in the east-west direction into a central region and two edge regions, wherein the first meteorological field of the inner nested region of the buffer zone is used as the second meteorological field of the inner nested region of the central region.

[0029] 42) The fitting result of the first meteorological field of the inner nested region of the buffer region and the first meteorological field of the inner nested region of the sub-region that overlaps with the edge region is taken as the second meteorological field of the inner nested region of the edge region.

[0030] 43) The first meteorological field of the inner nested region of each sub-region is used as the second meteorological field of the inner nested region of the part of each sub-region that does not overlap with the buffer region;

[0031] 44) Integrate the second meteorological field of the inner nested region of the central region, the second meteorological field of the inner nested region of the edge region, and the second meteorological field of the inner nested region of each sub-region that does not overlap with the buffer region to obtain the second meteorological field of the inner nested region of each sub-region.

[0032] Preferably, in step 42), the fitting results of the first meteorological field of the inner nested region of the buffer region and the first meteorological field of the inner nested region of the sub-region that overlaps with the edge region are specifically as follows:

[0033]

[0034] In the formula, Let n be the meteorological field of the i-th grid (starting from the center) in a certain row of grids in the east-west direction of the inner nested region of the edge region, where n is the total number of grids in that row of grids in the east-west direction of the inner nested region of the edge region. The meteorological field of the corresponding grid in the inner nested region of the buffer region. The meteorological field of the corresponding grid of the inner nested region of the sub-region that overlaps with the edge region.

[0035] Preferably, step 7) specifically includes:

[0036] 71) Based on the geographical range of the inner nested region of the target area under the air quality model, the large area is extracted, and the meteorological field of the extracted large area is used as the meteorological field of the inner nested region of the target area under the air quality model.

[0037] 72) Based on the geographical range of other nested regions of the target area under the air quality model, the large area is extracted, and based on the meteorological field of the extracted large area, the meteorological field of other nested regions of the target area under the air quality model is processed to obtain the meteorological field of other nested regions of the target area under the air quality model.

[0038] Preferably, step 72) of processing the meteorological field of the target area into other nested areas under the air quality model based on the captured meteorological field of the large area specifically includes:

[0039] 721) The meridional wind in the meteorological field of each grid in the other nested regions is obtained by weighted averaging the meridional wind in the meteorological field of the westernmost column of grids in the large region contained by each grid in the other nested regions;

[0040] 722) The zonal wind in the meteorological field of each grid in the other nested regions is obtained by weighted averaging of the zonal wind in the meteorological field of the northernmost column of grids in the large region contained by each grid in the other nested regions;

[0041] 723) The prediction results of the remaining meteorological elements in the meteorological field of each grid in the other nested regions are obtained by weighted averaging the prediction results of the corresponding meteorological elements in the meteorological field of all grids in the large region contained by each grid in the other nested regions.

[0042] Furthermore, the present invention also provides an air quality model meteorological field generation system, characterized in that it comprises:

[0043] The sub-region optimal parameterization scheme combination determination module is used to divide a large region into multiple sub-regions and determine the optimal parameterization scheme combination for each sub-region based on the simulation effect of meteorological field data from many years of history.

[0044] The module for determining the optimal parameterization scheme combination for buffer zones is used to set up buffer zones between two adjacent sub-regions and determine the optimal parameterization scheme combination for each buffer zone based on the simulation effect of meteorological field data from many years of history.

[0045] The first meteorological field determination module is used to predict future weather using the optimal parameterization scheme combination of each sub-region and each buffer region, and to obtain the first meteorological field of the inner nested region of each sub-region and each buffer region.

[0046] The east-west fitting module is used to combine the first meteorological field of the inner nested region of the buffer zone between the east-west sub-regions and the first meteorological field of the inner nested region of each sub-region to perform east-west fitting, so as to obtain the second meteorological field of the inner nested region of each sub-region.

[0047] The north-south fitting module is used to combine the first meteorological field of the inner nested region of the buffer zone between the north-south sub-regions and the second meteorological field of the inner nested region of each sub-region to perform north-south fitting, so as to obtain the final meteorological field of the inner nested region of each sub-region.

[0048] A large-area meteorological field determination module is used to stitch together the meteorological fields of the inner nested regions of each sub-region to obtain the meteorological field of the large region;

[0049] The nested region meteorological field determination module is used to extract the large region according to the geographical range of each nested region of the target region under the air quality mode, and obtain the meteorological field of each nested region of the target region under the air quality mode based on the meteorological field of the extracted large region.

[0050] Furthermore, the present invention also provides an air quality model meteorological field generation device, characterized in that it comprises:

[0051] One or more processors;

[0052] Memory, used to store one or more programs;

[0053] When the one or more programs are executed by the one or more processors, the one or more processors implement the air quality model meteorological field generation method as described above.

[0054] Finally, the present invention also provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when the program is executed by a processor, it implements the steps of the air quality model meteorological field generation method as described above.

[0055] Compared with the prior art, the air quality model meteorological field generation method and system of the present invention have one or more of the following beneficial technical effects:

[0056] 1. This invention improves the accuracy of simulation prediction for each sub-region by using different combinations of parameterization schemes for different sub-regions.

[0057] 2. This invention reduces the impact of abnormal discontinuities in meteorological fields in adjacent sub-regions caused by different combinations of parameterization schemes on air quality model simulation by setting buffer areas and performing east-west and north-south fitting.

[0058] 3. This invention obtains the meteorological field of the outer nested region by processing the meteorological field of the inner nested region, thus solving the problem of mismatch between the meteorological fields of the inner and outer nested regions.

[0059] 4. The present invention ultimately yields a meteorological field for driving air quality models, thereby improving the accuracy of air quality model predictions. Attached Figure Description

[0060] Figure 1 This is a flowchart of the air quality model meteorological field generation method of the present invention.

[0061] Figure 2 A schematic diagram of the large-area division of the present invention is shown.

[0062] Figure 3 A schematic diagram of nested sub-regions of the present invention is shown.

[0063] Figure 4 A schematic diagram of the buffer area configuration of the present invention is shown.

[0064] Figure 5 A schematic diagram of the east-west fitting of the present invention is shown.

[0065] Figure 6 A schematic diagram of the meridional winds of each grid in the outer nested region of the present invention is shown.

[0066] Figure 7 A schematic diagram of the zonal winds for each grid in the outer nested region of the present invention is shown.

[0067] Figure 8 A schematic diagram is shown illustrating the prediction results of other meteorological elements for each grid in the outer nested region determined by the present invention.

[0068] Figure 9 This is a schematic diagram of the air quality model meteorological field generation system of the present invention.

[0069] in, Figures 6-8 In the image, the left side shows a grid diagram of a large area, and the right side shows a grid diagram of the outer nested area of ​​the air quality model. One grid in the outer nested area includes nine grids within the large area. Detailed Implementation

[0070] Before detailing any embodiment of the invention, it should be understood that the invention, in its application, is not limited to the details of the construction and arrangement of the components set forth in the following description or illustrated in the following figures. The invention can have other embodiments and can be practiced or carried out in various ways. Furthermore, it should be understood that the wording and terminology used herein are for descriptive purposes and should not be considered limiting. The use of “comprising” or “having” and variations thereof is intended to cover the items set forth below and their equivalents, as well as any additional items. Unless otherwise specified or limited, the terms “installation,” “connection,” “support,” and “linkage,” and variations thereof are used broadly and cover both direct and indirect installation, connection, support, and linking. Moreover, “connection” and “linkage” are not limited to physical or mechanical connections or links.

[0071] Furthermore, firstly, in the disclosure of this invention, the terms "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the above terms should not be construed as limiting this invention. Secondly, the term "a" should be understood as "at least one" or "one or more," that is, in one embodiment, the number of an element can be one, while in another embodiment, the number of the element can be multiple. The term "a" should not be construed as a limitation on the quantity.

[0072] To address the shortcomings of existing technologies, this invention provides a method and system for generating meteorological fields for air quality models. Based on a thorough consideration of the characteristics of the meteorological fields required for air quality models, it sets up sub-regions and buffer zones between them. Simulation and prediction are performed regionally based on combinations of parameterized schemes; that is, each sub-region uses different combinations of parameterized schemes for prediction. Considering that the atmosphere is fluid, and based on the principle of meteorological field continuity, the meteorological fields generated in each sub-region are subjected to secondary fitting. A high-resolution meteorological field for a large area is obtained by stitching these fields together. This high-resolution meteorological background field is then combined with the simulated area of ​​the air quality model to obtain the meteorological background fields for each nested layer used to drive the air quality model, thereby improving the accuracy of air quality model forecasts.

[0073] Figure 1 A flowchart of the air quality model meteorological field generation method of the present invention is shown. Figure 1 As shown, the air quality model meteorological field generation method of the present invention includes the following steps:

[0074] I. Determine the optimal combination of parameterization schemes for the sub-region.

[0075] The large region is divided into multiple sub-regions, and the optimal combination of parameterization schemes for each sub-region is determined based on the simulation results of meteorological field data from many years of history.

[0076] In this invention, the specific implementation is illustrated by dividing a large area (e.g., a certain large region) into four sub-regions, with each sub-region implementing a double nesting (an outer nested region, which is gridded with a grid size of 9km, i.e., a square grid with a side length of 9km, also known as a 9km resolution grid; and an inner nested region, which is also gridded with a grid size of 3km, i.e., a square grid with a side length of 3km, also known as a 3km resolution grid; thus, one grid of the outer nested region includes nine grids of the inner nested region). In practical applications, multiple sub-regions (8 or 16) and multiple nesting (e.g., triple nesting, where the outer nested region has a grid size of 27km, the middle nested region has a grid size of 9km, and the inner nested region has a grid size of 3km) can be set according to actual needs, with the specific processing method being the same as for four sub-regions and double nesting.

[0077] For ease of expression, such as Figure 2 As shown, this invention divides the large region into four sub-regions (northeast, northwest, southeast, and southwest, denoted as NE, NW, SE, and SW, respectively). Meanwhile, as... Figure 3 As shown, each sub-region includes an inner nested region and an outer nested region. Furthermore, during setup, it is ensured that the innermost nested regions of each sub-region are tightly connected and do not overlap (e.g., ...). Figure 2 The outer nested regions can overlap. Because the outer nested regions in this invention only provide initial values ​​and boundary values ​​to the inner nested regions, and do not subsequently process the data in the outer nested regions, this is for ease of demonstration. Figure 2 The outer nested area has been hidden, and only the inner nested area is displayed.

[0078] In this invention, determining the optimal parameterization scheme combination for each sub-region based on the simulation results of meteorological field data from many years of history specifically includes:

[0079] 1. Based on a certain sub-region, different combinations of parameterization schemes are used to simulate the meteorological field of the sub-region over many years. The simulation effect is verified using monitoring data, and the optimal combination of parameterization schemes for the sub-region is selected.

[0080] For example, based on the Northeast sub-region, different combinations of parameterization schemes can be used to simulate the historical meteorological field of the Northeast sub-region over three years using WRF or other meteorological models. The simulation results can be verified using monitoring data, and the optimal combination of parameterization schemes for the Northeast sub-region can be selected.

[0081] When using the WRF meteorological model, the optimal parameterization scheme combination includes more than 10 types of parameterization schemes, such as cumulus convection parameterization scheme, boundary layer parameterization scheme, microphysical parameterization scheme, and land surface process parameterization scheme. Each parameterization scheme includes the optimal parameterization scheme adopted.

[0082] 2. Simulate the historical meteorological fields of adjacent sub-regions of this sub-region using different combinations of parameterization schemes. Validate the simulation results using monitoring data, select the optimal parameterization scheme combinations for each adjacent sub-region, and, referencing the optimal parameterization scheme combination for this sub-region, determine the optimal parameterization scheme combination for each adjacent sub-region based on the principle of minimizing adjustments relative to the optimal parameterization scheme combination for this sub-region. This approach ensures that the differences in the optimal parameterization scheme combinations among sub-regions are small, thereby reducing abnormal discontinuities in the meteorological fields of adjacent sub-regions.

[0083] For example, using WRF or other meteorological models with different combinations of parameterization schemes, the historical meteorological fields of adjacent sub-regions of the Northeast sub-region, namely the Northwest and Southeast sub-regions, can be simulated over three years. The simulation results can be verified using monitoring data, and the optimal combination of parameterization schemes for the Northwest and Southeast sub-regions can be selected.

[0084] Simultaneously, referencing the optimal parameterization scheme combination for the Northeast sub-region, and aiming to minimize adjustments relative to the optimal parameterization scheme combination for the Northeast sub-region, the optimal parameterization scheme combinations for the Northwest and Southeast sub-regions are determined. For example, if the boundary layer parameterization scheme for the Northeast sub-region is the MYJ boundary layer parameterization scheme, and among the relatively optimal boundary layer parameterization schemes selected for the Northwest sub-region, the MYJ boundary layer parameterization scheme and the MRF boundary layer parameterization scheme have comparable effects, then the final boundary layer parameterization scheme for the Northwest sub-region should be the MYJ boundary layer parameterization scheme, in order to maintain consistency with the boundary layer parameterization scheme for the Northeast sub-region as much as possible.

[0085] 3. Simulate the historical meteorological fields of other adjacent sub-regions of each adjacent sub-region using different parameterization scheme combinations. Use monitoring data to verify the simulation effect, screen out the better parameterization scheme combinations of other adjacent sub-regions of each adjacent sub-region of this sub-region, and refer to the optimal parameterization scheme combinations of each adjacent sub-region of this sub-region. The principle is to minimize the adjustment relative to the optimal parameterization scheme combinations of each adjacent sub-region of this sub-region, and then determine the optimal parameterization scheme combinations of other adjacent sub-regions of each adjacent sub-region of this sub-region.

[0086] For example, using WRF or other meteorological models, different combinations of parameterization schemes can be used to simulate the historical meteorological field of the adjacent sub-regions of the Northwest and Southeast sub-regions, excluding the Northeast sub-region, namely the Southwest sub-region, for three years. The simulation effect can be verified using monitoring data, and the optimal combination of parameterization schemes for the Southwest sub-region can be selected.

[0087] Simultaneously, referencing the optimal parameterization scheme combinations for the Northwest and Southeast sub-regions, the optimal parameterization scheme combination for the Southwest sub-region is determined based on the principle of minimizing adjustments relative to the optimal parameterization scheme combinations for the Northwest and Southeast sub-regions. For example, if the boundary layer parameterization scheme for the Northwest and Southeast sub-regions is the MYJ boundary layer parameterization scheme, and among the boundary layer parameterization schemes selected for the Southwest sub-region, the MYJ boundary layer parameterization scheme and the ACM2 boundary layer parameterization scheme have comparable effects, then the final boundary layer parameterization scheme for the Southwest sub-region should be the MYJ boundary layer parameterization scheme, in order to maintain consistency with the boundary layer parameterization schemes for the Northwest and Southeast sub-regions as much as possible.

[0088] II. Determine the optimal combination of parameterization schemes for the buffer region.

[0089] A buffer zone is established between two adjacent sub-regions, and the optimal parameterization scheme combination for each buffer zone is determined based on the simulation results of historical meteorological field data over many years. Specifically, different parameterization scheme combinations are used to simulate the historical meteorological field of the buffer zone over many years. The simulation results are verified using monitoring data, and a better parameterization scheme combination for the buffer zone is selected. The optimal parameterization scheme combination for the buffer zone is determined by referring to the optimal parameterization scheme combination of the two adjacent sub-regions where the buffer zone is set, with the principle of minimizing the adjustment relative to the optimal parameterization scheme combination of the two adjacent sub-regions.

[0090] In an example of the present invention, it specifically includes:

[0091] 1. For example Figure 4 As shown, a buffer region 1 (also set as a double nested region) is set between the northeast and northwest sub-regions, denoted as HC1. The inner nested region of buffer region 1 needs to completely overlap with the mesh of the inner nested regions of the northeast and northwest sub-regions (e.g., ...). Figure 4 Because the outer nested region of this invention only provides initial values ​​and boundary values ​​to the inner nested region, and does not subsequently process the data of the outer nested region, this is for ease of demonstration. Figure 4 The outer nested region was hidden, and only the inner nested region was displayed. The historical meteorological field of buffer zone 1 for the past three years was simulated using different combinations of parameterization schemes from WRF or other meteorological models. Monitoring data was used to verify the simulation results, and the optimal parameterization scheme combination for buffer zone 1 was selected. Simultaneously, referencing the optimal parameterization scheme combinations for the northeastern and northwestern sub-regions, the optimal parameterization scheme combination for buffer zone 1 was determined based on the principle of minimizing adjustments relative to the optimal parameterization scheme combinations for the northeastern and northwestern sub-regions.

[0092] 2. Similarly, buffer region 2 is set between the southeast and southwest sub-regions, buffer region 3 is set between the northeast and southeast sub-regions, and buffer region 4 is set between the southwest and northwest sub-regions (buffer regions 2, 3, and 4 are also nested). It can be seen that buffer region 1 and buffer region 2 are buffer regions between sub-regions divided in the east-west direction, and buffer region 3 and buffer region 4 are buffer regions between sub-regions divided in the north-south direction. Following step 1 above, the optimal parameterization scheme combination of buffer region 2, buffer region 3, and buffer region 4 is selected.

[0093] In this invention, the purpose of setting a buffer zone is to establish a transition zone between two connected sub-regions, allowing meteorological elements to evolve slowly and avoiding abnormal discontinuities in the meteorological field at the boundary between two adjacent sub-regions. For example, if the northeastern and northwestern sub-regions are directly spliced ​​together, and the two sub-regions use different parameterization schemes, there will be abnormal discontinuities in the meteorological field at the boundary. These abnormal discontinuities may form a false convergence zone at the boundary, and using this meteorological field to drive an air quality model will increase the simulation error.

[0094] III. Determine the primary meteorological field.

[0095] With the optimal parameterization scheme combination for each sub-region and each buffer region, the future weather can be predicted using the optimal parameterization scheme combination for each sub-region and each buffer region, and the first meteorological field of each sub-region and each buffer region can be obtained.

[0096] Because each sub-region and each buffer region is nested multiple times (double nesting in the example of this invention), by predicting future weather, both the first meteorological field of the inner nested region of each sub-region and each buffer region and the first meteorological field of the outer nested region of each sub-region and each buffer region can be obtained. However, in subsequent processing, this invention only uses the first meteorological field of the inner nested region of each sub-region and each buffer region.

[0097] IV. East-West Fitting.

[0098] By combining the first meteorological field of the inner nested region of the buffer zone between the east-west divided sub-regions and the first meteorological field of the inner nested region of each sub-region, an east-west fitting is performed to obtain the second meteorological field of the inner nested region of each sub-region. The specific implementation steps are as follows:

[0099] 1. The buffer zone between the east-west oriented sub-regions is divided into a central region and two edge regions. The central region and edge regions are also doubly nested. Specifically, the first meteorological field of the inner nested region of the buffer zone is used as the second meteorological field of the inner nested region of the central region.

[0100] For example, such as Figure 5As shown, buffer zone 1 is divided into a central zone C and two edge zones D and E. The central zone C and the edge zones D and E are also double-nested. The width of the central zone D and the two edge zones D and E can each occupy one-third of the width of buffer zone 1. The first meteorological field of the inner nested region of buffer zone 1 is used as the second meteorological field of the inner nested region of region C in the middle of buffer zone 1.

[0101] 2. The fitting result of the first meteorological field of the inner nested region of the buffer region and the first meteorological field of the inner nested region of the sub-region that overlaps with the edge region is taken as the second meteorological field of the inner nested region of the edge region.

[0102] For example, such as Figure 5 As shown, the areas outside region C in the middle of buffer zone 1, namely region D which overlaps with the northeast sub-region and region E which overlaps with the northwest sub-region, need to be fitted to solve the problem of abnormal discontinuity in the east-west direction of the meteorological field in adjacent regions and improve the accuracy of the meteorological field.

[0103] For each grid within the inner nested region of region D, there are two predicted meteorological elements (i.e., the meteorological field): the predicted meteorological elements of the inner nested region of the northeast sub-region and the predicted meteorological elements of the inner nested region of buffer region 1. When fitting region D, to ensure the continuity of the meteorological field, the predicted meteorological elements (temperature, air pressure, humidity, radial wind, zonal wind, etc., more than 100 other meteorological elements) of the inner nested region of buffer region 1 should have a higher weight when fitting the grids of region D closer to the inner nested region of region C. Similarly, the predicted meteorological elements of the inner nested region of the northeast sub-region should have a higher weight when fitting the grids of region D closer to the inner nested region of region B. From region C to region B, the weight of the predicted meteorological elements of the inner nested region of buffer region 1 gradually decreases, while the weight of the predicted meteorological elements of the inner nested region of the northeast sub-region gradually increases. The fitting formula is as follows:

[0104]

[0105] In the formula, This represents the prediction result of meteorological elements for the i-th grid (starting from the center area) in a certain row of grids along the east-west direction within the inner nested region of the edge region D, where n is the total number of grids in that row along the east-west direction within the inner nested region of the edge region D. The prediction results of meteorological elements for the corresponding grid of the inner nested region of the buffer zone. The prediction results of meteorological elements for the inner nested region of the sub-region that overlaps with the edge region are given by i, which is 1, 2, 3...n from C to B.

[0106] By using the above fitting formula to fit all the grids in a row of grids in the east-west direction of the inner nested region of the edge area, the prediction results of meteorological elements for all grids in that row can be obtained.

[0107] As can be seen from the formula, the first grid of the inner nested region on the left side of region D, close to region C, uses the prediction results of meteorological elements from the inner nested region of buffer region 1. The first grid of the inner nested region on the right side, close to region B, uses the prediction results of meteorological elements from the inner nested region of the northeast sub-region. The weight of the prediction results of meteorological elements from the inner nested region of buffer region C to region B gradually decreases, while the weight of the prediction results of meteorological elements from the inner nested region of the northeast sub-region gradually increases.

[0108] By fitting all the grids in each row of the east-west direction of the inner nested region of the edge region using the above fitting formula, the predicted meteorological elements of the inner nested region of the edge region can be obtained.

[0109] Using the same method, the forecast results of meteorological elements in the inner nested region of region E can be obtained.

[0110] 3. The first meteorological field of the inner nested region of each sub-region is used as the second meteorological field of the inner nested region of the part of each sub-region that does not overlap with the buffer region.

[0111] For example, outside of buffer zone 1, the meteorological element forecasts for region B in the northeast sub-region and region A in the northwest sub-region are used from the inner nested regions of their respective sub-regions.

[0112] 4. Integrate the second meteorological field of the inner nested region of the central region, the second meteorological field of the inner nested region of the edge region, and the second meteorological field of the inner nested region of each sub-region that does not overlap with the buffer region to obtain the second meteorological field of the inner nested region of each sub-region.

[0113] That is, the meteorological element prediction results of the inner nested regions of region C, region D, region E, region A, and region B obtained in steps 2-3 are integrated to obtain the meteorological element prediction results of the inner nested regions of the new northeast and northwest sub-regions, namely, the second meteorological field.

[0114] Similarly, by fitting the buffer zone 2 between the southwest and southeast sub-regions using the methods described in steps 1-4 above, we can obtain the prediction results of meteorological elements in the inner nested regions of the new southwest and southeast sub-regions, i.e., the second meteorological field.

[0115] However, the second meteorological field is only an east-west fit of the inner nested regions of the buffer zones between the northeast and northwest sub-regions and the buffer zones between the southeast and southwest sub-regions. The prediction results of meteorological elements in the north-south direction of the inner nested regions of the northeast and southeast sub-regions and the northwest and southwest sub-regions may still differ greatly, which will cause discontinuity in the meteorological field. Therefore, north-south fitting is required.

[0116] V. North-South Fitting.

[0117] By combining the first meteorological field of the inner nested region of the buffer zone between the north-south sub-regions and the second meteorological field of the inner nested region of each sub-region, a north-south fitting is performed to obtain the final meteorological field of the inner nested region of each sub-region, that is, the prediction result of the meteorological elements of the inner nested region of each sub-region.

[0118] In this invention, similar to the east-west fitting method, north-south fitting is performed based on the second meteorological field of the inner nested region of buffer area 4 and the northwest and southwest sub-regions, and north-south fitting is performed based on the second meteorological field of the inner nested region of buffer area 3 and the northeast and southeast sub-regions, so as to obtain the final meteorological field of the inner nested region of each sub-region, that is, the prediction results of meteorological elements in the inner nested region of each sub-region.

[0119] VI. Determine the meteorological field of the large area.

[0120] After obtaining the final meteorological field of the inner nested region of each sub-region, the meteorological fields of the inner nested region of each sub-region are spliced ​​together to obtain the meteorological field of the large region.

[0121] In this invention, since the previous processing was based on the inner nested region, it can be seen that the meteorological field of this large area is only the meteorological field of the inner nested region, that is, the meteorological field of the 3-kilometer resolution grid.

[0122] VII. Determine the meteorological field for each nested region.

[0123] When conducting air quality model simulations, the first step is to determine the area to be simulated, i.e., the target area in the air quality model. For example, if an air quality model simulation is conducted for a specific location, the target area is the geographical area within a certain distance of that location.

[0124] Meanwhile, air quality model simulations are generally multi-layered, such as double-layered. In this case, the outer nested region (e.g., a specific location) is larger with a larger grid, for example, a 9km grid, but with lower resolution. The inner nested region (e.g., a specific area within that location) is smaller than the outer nested region, and its grid is smaller than the outer nested region's grid, for example, a 3km grid, but with higher resolution. Of course, triple-layered or other heavily nested regions are also possible. In a triple-layered simulation, the outer nested region has a 27km grid, the middle nested region has a 9km grid, and the inner nested region has a 3km grid.

[0125] Through the processing described in steps one through six above, this invention can obtain a meteorological field with a 3km resolution grid for a large area (e.g., a specific region). Thus, when performing air quality model simulations, the target area in the air quality model (e.g., a specific location in Hebei Province or a specific city within the aforementioned region) can directly obtain its own 3km resolution grid meteorological field based on the meteorological field of the larger region, eliminating the need for each target area to obtain its own 3km resolution grid meteorological field through steps one through six separately, thereby saving significant costs.

[0126] In this invention, when performing air quality model simulation, the large area can be truncated according to the geographical range of each nested region of the target area under the air quality model, and the meteorological fields of each nested region of the target area under the air quality model can be obtained based on the meteorological field of the truncated large area, which specifically includes:

[0127] 1. Based on the geographical range of the inner nested region of the target area under the air quality model, the large area is directly extracted, and the meteorological field of the extracted large area is used as the meteorological field of the inner nested region of the target area under the air quality model.

[0128] For example, based on the size of the inner nested region of the target area in the air quality model, a section is directly cut off on the large area, and the meteorological field of each grid in the cut-off large area (i.e., each 3km resolution grid of the large area) is used as the meteorological field of each grid (which is also a 3km resolution grid) in the inner nested region of the target area in the air quality model.

[0129] 2. Based on other nested regions of the air quality model, for example, the geographical range of the outer nested region is cut off from the large region, and the meteorological field of each grid in the large region contained by each grid of the other nested regions is processed to obtain the meteorological field of each grid of the other nested regions of the air quality model.

[0130] For example, in this invention, the grid of the outer nested region of the target area in the air quality model is a 9km resolution grid, and the grid of the large area is a 3km resolution grid. Therefore, one grid of the outer nested region of the target area in the air quality model includes 9 grids in the large area. By processing the meteorological field of the 9 grids in the large area, the meteorological field of the grid of the outer nested region of the target area in the air quality model can be obtained.

[0131] In this invention, the process of obtaining the meteorological field of each grid in the other nested regions of the target area under the air quality model, based on the meteorological field of each grid within the large region contained in each of the other nested regions, specifically includes:

[0132] 1) The meridional wind in the meteorological field of each grid in the other nested regions is obtained by weighted averaging the meridional wind in the meteorological field of the westernmost column of grids in the large region contained by each grid in the other nested regions.

[0133] For example, such as Figure 6 As shown, the meridional wind u in a grid 1 of the outer nested region is determined by the westernmost column of nine grids within the large area encompassed by grid 1 of the outer nested region, that is, Figure 6 The weighted average of the meridional winds of grid 1, grid 2, and grid 3 within the large region is obtained.

[0134] 2) The zonal wind in the meteorological field of each grid in the other nested regions is obtained by weighted averaging the zonal wind in the meteorological field of the northernmost grid in the large region contained by each grid in the nested gas layer region.

[0135] For example, such as Figure 7 As shown, the zonal wind v in grid 1 of the outer nested region is determined by the westernmost column of the nine grids within the large area encompassed by grid 1 of the outer nested region. Figure 7 The weighted average of the zonal winds of grid 1, grid 2, and grid 3 within the large region is obtained.

[0136] 3) The prediction results of the remaining meteorological elements in the meteorological field of each grid in the other nested regions are obtained by weighted averaging the prediction results of the corresponding meteorological elements in the meteorological field of all grids in the large region contained by each grid in the outer nested region.

[0137] For example, such as Figure 8 As shown, the prediction results of meteorological elements other than meridional wind u and zonal wind v in grid 1 of the outer nested region are derived from the nine grids within the large area contained in grid 1 of the outer nested region, that is,Figure 8 The weighted average of the prediction results of the corresponding meteorological elements in grid 1, grid 2, grid 3, ..., grid 9 within the large area is obtained.

[0138] In general meteorological model simulations, the outer nested region (using a 9km resolution grid) is larger than the inner nested region (using a 3km resolution grid), providing initial and boundary values ​​to the inner nested region. Simultaneously, the inner nested region provides feedback to the outer nested region, ensuring that meteorological elements in the overlapping areas of the two nested regions match. However, this invention, when obtaining the prediction results of meteorological elements from the inner nested region's grid, reduces the impact of discontinuities in the meteorological field between adjacent sub-regions by setting a buffer and performing secondary fitting. This results in a deviation between the predicted meteorological elements of the overlapping area's grid and the original meteorological element prediction results. If a similar method is used to process and stitch together the outer nested region to obtain the prediction results of its meteorological elements, then the predicted meteorological elements of each grid in the overlapping or adjacent areas of the two sub-regions in the outer nested region will also deviate from the original meteorological elements. This leads to a mismatch between the predicted meteorological elements of the 9km resolution grid and the 3km resolution grid in the overlapping areas of the inner and outer nested regions, thus preventing the direct processing of the outer nested region. Therefore, the prediction results of meteorological elements in the inner and outer nested regions of this invention are all based on the prediction results of meteorological elements in the 3km resolution grid (i.e., the 3km resolution grid in the large area of ​​the meteorological model obtained in step six), and can be arbitrarily extracted according to the needs of air quality model simulation.

[0139] Figure 9 A schematic diagram of the air quality model meteorological field generation system of the present invention is shown. Figure 9 As shown, the air quality model meteorological field generation system of the present invention includes:

[0140] 1. Module for determining the optimal parameterization scheme combination for sub-regions.

[0141] The sub-region optimal parameterization scheme combination determination module is used to divide a large area into multiple sub-regions and determine the optimal parameterization scheme combination for each sub-region based on the simulation effect of meteorological field data from many years of history.

[0142] 2. Module for determining the optimal parameterization scheme combination for the buffer region.

[0143] The module for determining the optimal parameterization scheme combination of the buffer zone is used to set up a buffer zone between two adjacent sub-regions and determine the optimal parameterization scheme combination of each buffer zone based on the simulation effect of meteorological field data from many years of history.

[0144] 3. First meteorological field determination module.

[0145] The first meteorological field determination module is used to predict future weather by combining the optimal parameterization schemes of each sub-region and each buffer region, and to obtain the first meteorological field of the inner nested region of each sub-region and each buffer region.

[0146] 4. East-West Fitting Module.

[0147] The east-west fitting module is used to combine the first meteorological field of the inner nested region of the buffer zone between the east-west sub-regions and the first meteorological field of the inner nested region of each sub-region to perform east-west fitting, so as to obtain the second meteorological field of the inner nested region of each sub-region.

[0148] 5. North-South Fitting Module.

[0149] The north-south fitting module is used to combine the first meteorological field of the inner nested region of the buffer zone between the north-south sub-regions and the second meteorological field of the inner nested region of each sub-region to perform north-south fitting, so as to obtain the final meteorological field of the inner nested region of each sub-region.

[0150] 6. Module for determining the meteorological field in a large area.

[0151] The large-area meteorological field determination module is used to stitch together the meteorological fields of the inner nested regions of each sub-region to obtain the meteorological field of the large region.

[0152] 7. Meteorological field determination module for each nested region.

[0153] The nested region meteorological field determination module is used to extract the large region according to the geographical range of each nested region of the target region under the air quality mode, and obtain the meteorological field of each nested region of the target region under the air quality mode based on the meteorological field of the extracted large region.

[0154] Furthermore, the present invention also provides an air quality model meteorological field generation device, comprising: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the air quality model meteorological field generation method as described above.

[0155] Finally, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the air quality model meteorological field generation method as described above.

[0156] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit the scope of protection of the present invention. Those skilled in the art can modify or make equivalent substitutions to the technical solutions of the present invention based on the concept of the present invention, without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. A method for generating meteorological fields for air quality models, characterized in that, Includes the following steps: 1) Divide the large area into multiple sub-regions and determine the optimal combination of parameterization schemes for each sub-region based on the simulation results of meteorological field data from many years of history; 2) Set up buffer zones between two adjacent sub-regions, and determine the optimal combination of parameterization schemes for each buffer zone based on the simulation results of meteorological field data from many years of history; 3) Use the optimal parameterization scheme combination of each sub-region and each buffer region to predict future weather, and obtain the first meteorological field of the inner nested region of each sub-region and each buffer region; 4) By combining the first meteorological field of the inner nested region of the buffer zone between the east-west divided sub-regions and the first meteorological field of the inner nested region of each sub-region, an east-west fitting is performed to obtain the second meteorological field of the inner nested region of each sub-region. Specifically, this includes: 41) Dividing the buffer zone between the east-west divided sub-regions into a central region and two edge regions, wherein the first meteorological field of the inner nested region of the buffer zone is used as the second meteorological field of the inner nested region of the central region; 42) Using the fitting result of the first meteorological field of the inner nested region of the buffer zone and the first meteorological field of the inner nested region of the sub-region that overlaps with the edge region as the second meteorological field of the inner nested region of the edge region; 43) Using the first meteorological field of the inner nested region of each sub-region as the second meteorological field of the inner nested region of the part of each sub-region that does not overlap with the buffer zone; 44) Integrating the second meteorological field of the inner nested region of the central region, the second meteorological field of the inner nested region of the edge region, and the second meteorological field of the inner nested region of the part of each sub-region that does not overlap with the buffer zone, the second meteorological field of the inner nested region of each sub-region is obtained. 5) Similar to the east-west fitting method, the first meteorological field of the inner nested region of the buffer zone between the north-south sub-regions and the second meteorological field of the inner nested region of each sub-region are combined to perform north-south fitting, so as to obtain the final meteorological field of the inner nested region of each sub-region. 6) The final meteorological fields of the inner nested regions of each sub-region are spliced ​​together to obtain the meteorological field of the large region; 7) The large region is truncated according to the geographical range of each nested region of the target region under the air quality model, and the meteorological field of each nested region of the target region under the air quality model is obtained based on the meteorological field of the truncated large region.

2. The method for generating meteorological fields for air quality models according to claim 1, characterized in that, Step 1) involves determining the optimal parameterization scheme combination for each sub-region based on the simulation results of meteorological field data from many years of history. This specifically includes: 11) Based on a certain sub-region, simulate the meteorological field of the sub-region over many years using different combinations of parameterization schemes, use monitoring data to verify the simulation effect, and select the optimal combination of parameterization schemes for the sub-region. 12) Simulate the historical meteorological fields of each adjacent sub-region of this sub-region using different combinations of parameterization schemes, verify the simulation effect using monitoring data, screen out the better combinations of parameterization schemes for each adjacent sub-region of this sub-region, and determine the optimal combinations of parameterization schemes for each adjacent sub-region of this sub-region by referring to the optimal combinations of parameterization schemes for this sub-region, with the principle of minimizing the adjustment relative to the optimal combinations of parameterization schemes for this sub-region. 13) Simulate the historical meteorological fields of other adjacent sub-regions of each adjacent sub-region using different combinations of parameterization schemes. Use monitoring data to verify the simulation effect, screen out the better combinations of parameterization schemes of other adjacent sub-regions of each adjacent sub-region of this sub-region, and refer to the optimal combinations of parameterization schemes of each adjacent sub-region of this sub-region. The optimal combinations of parameterization schemes of other adjacent sub-regions of each adjacent sub-region of this sub-region are determined with the principle of minimizing the adjustment relative to the optimal combinations of parameterization schemes of each adjacent sub-region of this sub-region.

3. The method for generating meteorological fields for air quality models according to claim 1, characterized in that, Step 2) of determining the optimal parameterization scheme combination for each buffer zone based on the simulation effect of meteorological field data over many years specifically includes: simulating the meteorological field of the buffer zone over many years using different parameterization scheme combinations, verifying the simulation effect using monitoring data, selecting the better parameterization scheme combination for the buffer zone, and referring to the optimal parameterization scheme combination of the two adjacent sub-regions of the buffer zone, with the principle of minimizing the adjustment relative to the optimal parameterization scheme combination of the two adjacent sub-regions of the buffer zone, to determine the optimal parameterization scheme combination for the buffer zone.

4. The method for generating meteorological fields for air quality models according to claim 1, characterized in that, In step 42), the fitting results of the first meteorological field of the inner nested region of the buffer region and the first meteorological field of the inner nested region of the sub-region that overlaps with the edge region are specifically as follows: In the formula, Let n be the meteorological field of the i-th grid (starting from the center) in a certain row of grids in the east-west direction of the inner nested region of the edge region, where n is the total number of grids in that row of grids in the east-west direction of the inner nested region of the edge region. The meteorological field of the corresponding grid in the inner nested region of the buffer region. The meteorological field of the corresponding grid of the inner nested region of the sub-region that overlaps with the edge region.

5. The method for generating meteorological fields for air quality models according to claim 1, characterized in that, Step 7) specifically includes: 71) Based on the geographical range of the inner nested region of the target area under the air quality model, the large area is extracted, and the meteorological field of the extracted large area is used as the meteorological field of the inner nested region of the target area under the air quality model. 72) Based on the geographical range of other nested regions of the target area under the air quality model, the large area is extracted, and based on the meteorological field of the extracted large area, the meteorological field of other nested regions of the target area under the air quality model is processed to obtain the meteorological field of other nested regions of the target area under the air quality model.

6. The method for generating meteorological fields for air quality models according to claim 5, characterized in that, Step 72) involves processing the meteorological field of the large area captured to obtain the meteorological field of other nested regions of the target area under the air quality model. This specifically includes: 721) The meridional wind in the meteorological field of each grid in the other nested regions is obtained by weighted averaging the meridional wind in the meteorological field of the westernmost column of grids in the large region contained by each grid in the other nested regions; 722) The zonal wind in the meteorological field of each grid in the other nested regions is obtained by weighted averaging of the zonal wind in the meteorological field of the northernmost column of grids in the large region contained by each grid in the other nested regions; 723) The prediction results of the remaining meteorological elements in the meteorological field of each grid in the other nested regions are obtained by weighted averaging the prediction results of the corresponding meteorological elements in the meteorological field of all grids in the large region contained by each grid in the other nested regions.

7. An air quality model meteorological field generation system, characterized in that, include: The sub-region optimal parameterization scheme combination determination module is used to divide a large region into multiple sub-regions and determine the optimal parameterization scheme combination for each sub-region based on the simulation effect of meteorological field data from many years of history. The module for determining the optimal parameterization scheme combination for buffer zones is used to set up buffer zones between two adjacent sub-regions and determine the optimal parameterization scheme combination for each buffer zone based on the simulation effect of meteorological field data from many years of history. The first meteorological field determination module is used to predict future weather using the optimal parameterization scheme combination of each sub-region and each buffer region, and to obtain the first meteorological field of the inner nested region of each sub-region and each buffer region. An east-west fitting module is used to combine the first meteorological field of the inner nested region of the buffer zone between the east-west divided sub-regions and the first meteorological field of the inner nested region of each sub-region to perform east-west fitting, thereby obtaining the second meteorological field of the inner nested region of each sub-region. Specifically, it includes: 1) dividing the buffer zone between the east-west divided sub-regions into a central region and two edge regions, wherein the first meteorological field of the inner nested region of the buffer zone is used as the second meteorological field of the inner nested region of the central region; 2) combining the first meteorological field of the inner nested region of the buffer zone with the first meteorological field of the edge region... 3) The fitting result of the first meteorological field of the inner nested region of the sub-region with overlapping parts is used as the second meteorological field of the inner nested region of the edge region; 4) The first meteorological field of the inner nested region of each sub-region is used as the second meteorological field of the inner nested region of the part of each sub-region that does not overlap with the buffer region; 5) The second meteorological field of the inner nested region of the center region, the second meteorological field of the inner nested region of the edge region and the second meteorological field of the inner nested region of the part of each sub-region that does not overlap with the buffer region are integrated to obtain the second meteorological field of the inner nested region of each sub-region; The north-south fitting module uses the same method as the east-west fitting module. It combines the first meteorological field of the inner nested region of the buffer zone between the sub-regions divided in the north-south direction with the second meteorological field of the inner nested region of each sub-region to perform north-south fitting, and obtains the final meteorological field of the inner nested region of each sub-region. A large-area meteorological field determination module is used to stitch together the meteorological fields in the inner nested areas of each sub-region to obtain the meteorological field of the large region; The nested region meteorological field determination module is used to extract the large region according to the geographical range of each nested region of the target region under the air quality mode, and obtain the meteorological field of each nested region of the target region under the air quality mode based on the meteorological field of the extracted large region.

8. An air quality model meteorological field generation device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the air quality model meteorological field generation method as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the air quality model meteorological field generation method as described in any one of claims 1-6.

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