CN116563091A - Terrain data generation method, device, medium and electronic equipment - Google Patents
Terrain data generation method, device, medium and electronic equipment Download PDFInfo
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/05—Geographic models
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Abstract
The application provides a topographic data generation method, a topographic data generation device, a topographic data generation medium and an electronic device. The topographic data generating method comprises the following steps: acquiring longitude and latitude coordinates and a global uniform grid of a region to be predicted; generating a variable grid according to the longitude and latitude coordinates and the global uniform grid, wherein the resolution of a variable grid core area is better than the resolution of the core area in the global uniform grid, and the resolution of a variable grid non-core area is worse than the resolution of the non-core area in the global uniform grid; and carrying out regional interpolation on the global topographic data based on the interpolation weight coefficient of the variable grid so as to obtain the variable grid topographic data, wherein the density of the variable grid topographic data is matched with the structure of the variable grid. The topographic data generation method can improve the generation efficiency of topographic data, reduce the calculation cost and improve the calculation timeliness.
Description
Technical Field
The application belongs to the field of weather, relates to a topographic data generation method, and in particular relates to a topographic data generation method, a topographic data generation device, a topographic data generation medium and electronic equipment.
Background
The numerical weather forecast is to solve the atmospheric motion equation set by a numerical method under certain initial conditions and boundary conditions, so that the atmospheric state at the future moment is predicted by the atmospheric state at the known initial moment. By means of numerical weather forecast, the current weather service can achieve seamless weather forecast, comprising: short time (within hours), short time (1 day-3 days), medium time (4 days-9 days), and extension period (10 days-30 days).
The accurate numerical weather forecast depends on the topographic data matched with the grid structure, two solutions of a global numerical forecast mode and a regional numerical forecast mode exist at present, the global high-resolution meteorological numerical mode based on the two solutions has high calculation cost, the calculation timeliness of generating the topographic data matched with the global high-resolution grid is low, the calculation process highly depends on the calculation and storage performance of an ultra-calculation platform, and therefore the topographic data generation method of the global high-resolution meteorological numerical mode has the problems of high calculation cost and low calculation timeliness.
Disclosure of Invention
The purpose of the application is to provide a topographic data generation method, a topographic data generation device, a topographic data generation medium and an electronic device, which are used for solving the problems of high calculation cost and low calculation timeliness existing in the existing topographic data generation method in a global high-resolution meteorological numerical mode.
In a first aspect, the present application provides a terrain data generating method applied to a high-resolution grid-change weather prediction system, the terrain data generating method including: acquiring longitude and latitude coordinates and a global uniform grid of a region to be predicted; generating a variable grid according to the longitude and latitude coordinates and the global uniform grid, wherein the resolution of a variable grid core area is larger than the resolution of the core area in the global uniform grid, and the resolution of a variable grid non-core area is smaller than the resolution of the non-core area in the global uniform grid; and carrying out regional interpolation on the global topographic data based on the interpolation weight coefficient of the variable grid so as to obtain the variable grid topographic data, wherein the density of the variable grid topographic data is matched with the structure of the variable grid.
According to the terrain data generation method, the resolution of the core area is improved, the resolution of the non-core area is reduced, high-precision terrain data can be generated in the variable grid core area, coarse-resolution terrain data can be generated in the non-core area, and therefore excessive calculation force input in the non-core area in the process of generating the terrain data is avoided. The topographic data generation method can improve the generation efficiency of topographic data, reduce the calculation cost and improve the calculation timeliness.
In one embodiment of the present application, the grid points of the global uniform grid are projected in a polar direction by a schmitt transformation,
the method comprises the steps of obtaining a plane grid point of the variable grid, wherein the center grid point of the plane grid point is an earth pole, and the grid points of the global uniform grid are converged towards the center grid point of the plane grid point after projection; and carrying out rigid rotation on the plane lattice points to obtain the variable grids, wherein the coordinates of the central lattice points of the plane lattice points after the rigid rotation are longitude and latitude coordinates. The variable grid can be obtained quickly by obtaining the plane grid points of the variable grid and carrying out rigid body rotation on the plane grid points to obtain the variable grid, so that the efficiency of generating the topographic data is improved.
In an embodiment of the present application, the latitude before the schmitt transformation of the lattice points of the global uniform grid is a first latitude, and the latitude after the schmitt transformation of the lattice points of the global uniform grid is a second latitude, where the second latitude is represented by the following formula:wherein θ is the first latitude, +.>And for the second latitude, S is a tensile latitude conversion factor of the variable grid.
In an embodiment of the present application, the tensile latitude conversion factor of the variable grid is represented by the following formula:where x is the focusing stretch factor.
In an embodiment of the present application, a method for implementing area interpolation on topographic data includes: performing regional interpolation processing on the topographic data based on the interpolation weight coefficient to acquire topographic data to be processed; and carrying out smoothing treatment on the topographic data to be treated so as to obtain the variable grid topographic data.
In an embodiment of the present application, the method for implementing smoothing processing on the terrain data to be processed includes: performing smoothing processing on the terrain data to be processed based on a smoothing algorithm to obtain the variable grid terrain data, wherein the smoothing algorithm comprises any one or more of the following algorithms: spatial 9-point smoothing, adjacent point slope smoothing, and region conservation smoothing.
In a second aspect, the present application provides a weather prediction method comprising: and weather prediction is carried out on the area to be predicted based on the variable grid topographic data, wherein the variable grid topographic data is obtained by adopting the topographic data generating method according to any one of the first aspects of the application.
In a third aspect, the present application provides a terrain data generating device, which is applied to a weather prediction system, and a uniform grid acquisition module, configured to acquire longitude and latitude coordinates and a global uniform grid of a region to be predicted; the variable grid acquisition module is used for generating a variable grid according to the longitude and latitude coordinates and the global uniform grid, the resolution of the variable grid core area is larger than the resolution of the core area in the global uniform grid, and the resolution of the variable grid non-core area is smaller than the resolution of the non-core area in the global uniform grid; the terrain data acquisition module is used for carrying out regional interpolation on global terrain data based on the interpolation weight coefficient of the variable grid so as to acquire the variable grid terrain data, and the density of the variable grid terrain data is matched with the variable grid structure.
In a fourth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a terrain data generating method according to any of the first aspects of the present application.
In a fifth aspect, the present application provides an electronic device, including: a memory storing a computer program; and the processor is in communication connection with the memory and executes the topographic data generating method according to any one of the first aspect of the application when the computer program is called.
As described above, the topographic data generating method, device, medium and electronic equipment have the following beneficial effects:
first, according to the terrain data generation method, high-precision terrain data can be generated in the variable-grid core area and coarse-resolution terrain data can be generated in the non-core area by improving the resolution of the core area and reducing the resolution of the non-core area, so that excessive calculation effort is prevented from being input in the non-core area in the process of generating the terrain data. The topographic data generation method can improve the generation efficiency of topographic data, reduce the calculation cost and improve the calculation timeliness.
Secondly, according to the terrain data generation method, the variable grid can be quickly obtained by obtaining the plane grid points of the variable grid and carrying out rigid body rotation on the plane grid points to obtain the variable grid, so that the terrain data generation efficiency is improved.
Drawings
FIG. 1 is a schematic diagram of a weather prediction system according to an embodiment of the present application.
Fig. 2 is a flowchart of a terrain data generating method according to an embodiment of the present application.
Fig. 3 is a flowchart of an implementation method for generating a variable grid according to the longitude and latitude coordinates and the global uniform grid according to an embodiment of the present application.
Fig. 4 is a flowchart of an implementation method for performing area interpolation on terrain data according to an embodiment of the present application.
Fig. 5 is a schematic structural diagram of a topographic data generating device according to an embodiment of the present application.
Description of element reference numerals
10. Weather prediction system
110. Memory device
120. Processor and method for controlling the same
1210. Global wind-light seamless prediction module
12110. Grid-variable power nuclear unit
12120. Ocean mixed layer unit
12130. Land unit
12140. Physical process parameterization unit
1220. Post-processing module
130. Display device
500. Topographic data generating device
510. Uniform grid acquisition module
520. Variable grid acquisition module
530. Topographic data acquisition module
S11-S13 step
S21-S22 step
S31-S32 step
Detailed Description
Other advantages and effects of the present application will become apparent to those skilled in the art from the present disclosure, when the following description of the embodiments is taken in conjunction with the accompanying drawings. The present application may be embodied or carried out in other specific embodiments, and the details of the present application may be modified or changed from various points of view and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict.
It should be noted that, the illustrations provided in the following embodiments merely illustrate the basic concepts of the application by way of illustration, and only the components related to the application are shown in the drawings and are not drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complex.
The following describes the technical solutions in the embodiments of the present application in detail with reference to the drawings in the embodiments of the present application.
As shown in FIG. 1, embodiments of the present application provide a weather forecast system 10, the weather forecast system 10 comprising: the device comprises a memory 110, a processor 120 and a display 130, wherein the processor 120 is used for processing data of a global wind-solar seamless prediction module 1210 and a post-processing module 1220, and the global wind-solar seamless prediction module 1210 comprises: the variable grid power core unit 12110, the ocean hybrid layer unit 12120, the land surface unit 12130 and the physical process parameterization unit 12140 perform data exchange among the units through any coupler, and the post-processing module 1220 is used for generating and publishing a prediction result of the global wind-solar seamless prediction module 1210.
Alternatively, the power core in the variable grid power core unit 12110 may be FV3 (Finite-Volume cube-Sphere Dynamical Core), where FV3 power core is an expandable and flexible power core that is capable of hydrostatic and non-hydrostatic atmospheric simulation. The variable mesh in the variable mesh power core unit 12110 is a variable mesh generated from a global uniform mesh, and the resolution of the variable mesh core region is better than the resolution of the core region in the global uniform mesh. The ocean hybrid layer unit 12120 includes information such as ocean data, and the land unit 12130 includes information such as terrain data.
Optionally, the prediction result of the global wind-solar seamless prediction module 1210 is 6 grid-variable cube spheres, and the post-processing module 1220 maps the 6 grid-variable cube spheres to the longitude and latitude grids with equal intervals in the world according to a preset interpolation coefficient file, so as to facilitate taking. The post-processing module 1220 may draw and issue the prediction result through drawing software, for example, the output of the post-processing module 1220 may be a chinese summer precipitation prediction drawing. The weather prediction system 10 can effectively perform weather prediction, and has good prediction results for the structures of rainfall in the middle summer, storm in the river and the storm in the south and double typhoons and large wind areas.
As shown in fig. 2, the present embodiment provides a topographic data generating method, which may be implemented by a processor of a computer device, the topographic data generating method including:
s11, longitude and latitude coordinates and a global uniform grid of the region to be predicted are obtained.
Optionally, when weather prediction is performed on a Chongqing, the longitude and latitude coordinates of the region to be predicted may be, for example, longitude and latitude coordinates (106E, 29N) of the Chongqing, and the global uniform grid may be a global uniform grid in WRF (Weather Research and Forecast Model, weather forecast mode).
And S12, generating a variable grid according to the longitude and latitude coordinates and the global uniform grid, wherein the resolution of a variable grid core area is larger than the resolution of the core area in the global uniform grid, and the resolution of a variable grid non-core area is smaller than the resolution of the non-core area in the global uniform grid.
Optionally, the variable grid is a global variable grid generated based on the global uniform grid, and the variable grid refers to grids with different sizes in different regions of the world, such as using a plurality of small grids in a core region with important attention, and using a large grid in a non-core region with no important attention. When the longitude and latitude coordinates are those of Chongqing, the grid-changing core area may be an adjacent area with Chongqing as a center point, for example, a related area in Hunan province near Chongqing may be in the grid-changing core area, for example, a related area in America may be a non-core area with the longitude and latitude coordinates of Chongqing.
Optionally, the resolution of the variable grid core area is positively correlated with the lattice point density of the variable grid core area, and the resolution of the variable grid core area is better than the resolution of the core area in the global uniform grid, that is, the lattice point density of the variable grid core area is greater than the lattice point density of the core area in the global uniform grid. Wherein, the grid points of the variable grid can be grid intersection points among the variable grids.
And S13, carrying out regional interpolation on the terrain data based on the interpolation weight coefficient of the variable grid so as to obtain the variable grid terrain data, wherein the density of the variable grid terrain data is matched with the variable grid structure.
Optionally, the matching of the density of the variable grid topographic data with the variable grid structure means that the greater the density of the variable grid topographic data in the area with high density of the variable grid points is, the higher the precision of the topographic data in the area is, and the smaller the density of the variable grid topographic data in the area with low density of the variable grid points is, the lower the precision of the topographic data in the area is.
Optionally, the method for obtaining the interpolation weight coefficient includes: and acquiring the interpolation weight coefficient according to the focusing ratio of the longitude and latitude coordinates and the variable grid. The focus ratio of the longitude and latitude coordinates is positively correlated with the resolution of the variable grid core region, e.g., when the focus ratio of the longitude and latitude coordinates is 8, the resolution of the variable grid core region is 8 times the resolution of the core region in the global uniform grid.
Alternatively, the variegated mesh may be provided with a plurality of core regions, such as a first core region and a second core region, each of which has a resolution that is better than the resolution of the first core region and the second core region in the global uniform mesh. In addition, the resolution of the first core region and the second core region may also be different, for example, when the variable grid is generated at the global uniform grid with a horizontal resolution of 100 km, the horizontal resolution of the first core region may be 12.5 km, the horizontal resolution of the second core region may be between 12.5 km and 100 km, and the resolution of the non-core region is greater than 100 km.
Optionally, the variable grid includes a core area and a non-core area, the core area has a corresponding first weight coefficient, the non-core area has a corresponding second weight coefficient, and the implementation method for performing area interpolation on the terrain data includes: interpolating the core region based on the first weight coefficient; and interpolating the non-core area based on the second weight coefficient.
Alternatively, when interpolating different grids based on the terrain data, for example, global uniform grid terrain data and variable grid terrain data can be obtained, the global uniform grid terrain data matching the grid structure of the global uniform grid, and the variable grid terrain data matching the grid structure of the variable grid.
As can be seen from the above description, the terrain data generating method according to the present embodiment is applied to a high-resolution grid-change weather prediction system, and includes: acquiring longitude and latitude coordinates and a global uniform grid of a region to be predicted; generating a variable grid according to the longitude and latitude coordinates and the global uniform grid, wherein the resolution of a variable grid core area is larger than the resolution of the core area in the global uniform grid, and the resolution of a variable grid non-core area is smaller than the resolution of the non-core area in the global uniform grid; and carrying out regional interpolation on the global topographic data based on the interpolation weight coefficient of the variable grid so as to obtain the variable grid topographic data, wherein the density of the variable grid topographic data is matched with the structure of the variable grid.
According to the terrain data generation method, the resolution of the core area is improved, the resolution of the non-core area is reduced, high-precision terrain data can be generated in the variable grid core area, coarse-resolution terrain data can be generated in the non-core area, and therefore excessive calculation force input in the non-core area in the process of generating the terrain data is avoided. The topographic data generation method can improve the generation efficiency of topographic data, reduce the calculation cost and improve the calculation timeliness.
As shown in fig. 3, the implementation method for generating the variable grid according to the longitude and latitude coordinates and the global uniform grid includes:
s21, carrying out polar projection on grid points of the global uniform grid through Schmidt transformation to obtain plane grid points of the variable grid, wherein the center grid point of the plane grid points is an earth pole, and the grid points of the global uniform grid are converged towards the center grid points of the plane grid points after projection.
Optionally, the implementation method for performing polar projection on the grid points of the global uniform grid through schmitt transformation comprises the following steps: setting a south pole as a focusing center point; and according to the focusing center point, performing polar projection on grid points of the global uniform grid through Schmidt transformation to obtain plane grid points of the variable grid. When a pole is taken as a focusing center point, the grid points of the global uniform grid are projected in a circular plane by taking the pole as the center point, the grid points of the global uniform grid are converged near the focusing center point, and the pole can be a south pole.
Optionally, the latitude before the schmitt transformation of the lattice points of the global uniform grid is a first latitude, and the latitude after the schmitt transformation of the lattice points of the global uniform grid is a second latitude, where the second latitude can be represented by the following formula:
wherein θ is the first latitude, +.>And for the second latitude, S is a tensile latitude conversion factor of the variable grid. The tensile dimension conversion factor of the variable mesh may be an amount of change representing a density of lattice points of the variable mesh core region relative to a density of lattice points of the core region in the global uniform mesh. According to the conversion formula of the second latitude and the first latitude, the lattice points of the global uniform grid can increase the lattice point density near the given longitude and latitude coordinates after transformation, and the lattice point density is sparse at the far end of the given longitude and latitude.
Alternatively, the tensile latitude conversion factor of the variable mesh may be represented by the following formula:
where x is the focusing stretch factor. The focusing stretching coefficient may be a focusing ratio of the region to be predicted, for example, the focusing stretching coefficient may be 8 when focusing is 8 times of Chongqing.
And S22, carrying out rigid rotation on the plane lattice points to obtain the variable grids, wherein the coordinates of the center lattice points of the plane lattice points after rigid rotation transformation are longitude and latitude coordinates.
Optionally, the center lattice point of the plane lattice point is the pole, and when focusing is performed on a Chongqing, the coordinates of the center lattice point of the plane lattice point after rigid transformation are the coordinates of the Chongqing, wherein the coordinates of the Chongqing can be represented by longitude and latitude, and in addition, the related content of the rigid rotation method is not described in detail in this embodiment.
Alternatively, the implementation method of performing rigid rotation on the plane lattice points may be that the plane lattice points are processed by a rigid rotation method to obtain the variable lattice. The related content of the rigid body rotation method is not described in detail in this embodiment.
As can be seen from the above description, the implementation method for generating the variable grid according to the longitude and latitude coordinates and the global uniform grid according to the present embodiment includes: performing polar projection on grid points of the global uniform grid through Schmitt transformation to obtain plane grid points of the variable grid, wherein the center grid point of the plane grid points is an earth pole, and the grid points of the global uniform grid are converged towards the center grid point of the plane grid points after projection; and carrying out rigid rotation on the plane lattice points to obtain the variable grids, wherein the coordinates of the central lattice points of the plane lattice points after the rigid rotation are longitude and latitude coordinates. The variable grid can be obtained quickly by obtaining the plane grid points of the variable grid and carrying out rigid body rotation on the plane grid points to obtain the variable grid, so that the efficiency of generating the topographic data is improved.
As shown in fig. 4, the implementation method for performing region interpolation on the topographic data includes:
and S31, carrying out regional interpolation processing on the topographic data based on the interpolation weight coefficient so as to acquire topographic data to be processed.
Optionally, the generating method of the interpolation weight coefficient is already referred to in S13, which is not described in detail in this embodiment. The interpolation weight coefficients may be stored in a netcdf4 (Network Common Data Form, network generic data format) format file for ease of recall.
S32, performing smoothing processing on the terrain data to be processed to obtain the grid-variable terrain data.
Optionally, the terrain data may include: GMTED (Global Multi-resolution Terrain Elevation Data, global land-wide elevation data set) at 30 minutes of spatial resolution, land cover data at 30 minutes of spatial resolution, and antarctic topographic data at 30 minutes of spatial resolution, the topographic data having a data format of binary data.
Optionally, the implementation method for smoothing the terrain data to be processed includes: smoothing the terrain data to be processed based on a smoothing algorithm to obtain the variable grid terrain data, wherein the smoothing algorithm comprises any one or more of the following combinations: spatial 9-point smoothing, adjacent point slope smoothing, and region conservation smoothing. And carrying out smoothing treatment on the topographic data to be treated based on a smoothing algorithm, so that the stability of numerical integration can be improved, and topographic data matched with the variable grid structure can be obtained.
In an embodiment of the present application, the present application provides the weather prediction method, including: and weather prediction is carried out on the region to be predicted based on the variable grid topographic data, wherein the variable grid topographic data is obtained by adopting the topographic data generating method shown in fig. 2.
The protection scope of the terrain data generating method according to the embodiment of the present application is not limited to the execution sequence of the steps listed in the embodiment, and all the schemes implemented by adding or removing steps and replacing steps according to the prior art made by the principles of the present application are included in the protection scope of the present application.
As shown in fig. 5, the present embodiment provides a terrain data generating apparatus 500 applied to a weather prediction system, the terrain data generating apparatus 500 including:
the uniform grid acquisition module 510 is configured to acquire latitude and longitude coordinates of a region to be predicted and a global uniform grid.
And a variable grid acquisition module 520, configured to generate a variable grid according to the longitude and latitude coordinates and the global uniform grid, where a resolution of the variable grid core area is greater than a resolution of the core area in the global uniform grid, and a resolution of the variable grid non-core area is less than a resolution of the non-core area in the global uniform grid.
The terrain data obtaining module 530 is configured to perform area interpolation on the terrain data based on the interpolation weight coefficient of the variable grid, so as to obtain variable grid terrain data, where the density of the variable grid terrain data is matched with the structure of the variable grid.
In the topographic data generating device 500 provided in this embodiment, the uniform grid obtaining module 510, the variable grid obtaining module 520 and the topographic data obtaining module 530 are in one-to-one correspondence with steps S11 to S13 of the topographic data generating method shown in fig. 2, and will not be described in detail here.
As can be seen from the above description, the terrain data generating device 500 according to the present embodiment can generate high-precision terrain data in the variable-grid core region and generate coarse-resolution terrain data in the non-core region by improving the resolution of the core region and reducing the resolution of the non-core region, so as to avoid excessive calculation effort in the non-core region during the generation of the terrain data. The topographic data generating device can improve the generating efficiency of topographic data, reduce the calculating cost and improve the calculating timeliness.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus or method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of modules/units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple modules or units may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or modules or units, which may be in electrical, mechanical or other forms.
The modules/units illustrated as separate components may or may not be physically separate, and components shown as modules/units may or may not be physical modules, i.e., may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules/units may be selected according to actual needs to achieve the purposes of the embodiments of the present application. For example, functional modules/units in various embodiments of the present application may be integrated into one processing module, or each module/unit may exist alone physically, or two or more modules/units may be integrated into one module/unit.
Those of ordinary skill would further appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The embodiment provides an electronic device, which comprises a memory, wherein a computer program is stored in the memory; and the processor is in communication connection with the memory and executes the topographic data generating method shown in fig. 2 when the computer program is called. And a display communicatively coupled to the processor and the memory for displaying an interactive interface of an associated GUI (Graphical User Interface ) of the terrain data generating method.
Embodiments of the present application also provide a computer-readable storage medium. Those of ordinary skill in the art will appreciate that all or part of the steps in the method implementing the above embodiments may be implemented by a program to instruct a processor, where the program may be stored in a computer readable storage medium, where the storage medium is a non-transitory (non-transitory) medium, such as a random access memory, a read only memory, a flash memory, a hard disk, a solid state disk, a magnetic tape (magnetic tape), a floppy disk (floppy disk), an optical disk (optical disk), and any combination thereof. The storage media may be any available media that can be accessed by a computer or a data storage device such as a server, data center, or the like that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a digital video disc (digital video disc, DVD)), or a semiconductor medium (e.g., a Solid State Disk (SSD)), or the like.
Embodiments of the present application may also provide a computer program product comprising one or more computer instructions. When the computer instructions are loaded and executed on a computing device, the processes or functions described in accordance with the embodiments of the present application are produced in whole or in part. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website, computer, or data center to another website, computer, or data center by a wired (e.g., coaxial cable, fiber optic, digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.).
The computer program product is executed by a computer, which performs the method according to the preceding method embodiment. The computer program product may be a software installation package, which may be downloaded and executed on a computer in case the aforementioned method is required.
The descriptions of the processes or structures corresponding to the drawings have emphasis, and the descriptions of other processes or structures may be referred to for the parts of a certain process or structure that are not described in detail.
The foregoing embodiments are merely illustrative of the principles of the present application and their effectiveness, and are not intended to limit the application. Modifications and variations may be made to the above-described embodiments by those of ordinary skill in the art without departing from the spirit and scope of the present application. Accordingly, it is intended that all equivalent modifications and variations which may be accomplished by persons skilled in the art without departing from the spirit and technical spirit of the disclosure be covered by the claims of this application.
Claims (10)
1. A terrain data generation method, applied to a weather prediction system, the terrain data generation method comprising:
acquiring longitude and latitude coordinates and a global uniform grid of a region to be predicted;
generating a variable grid according to the longitude and latitude coordinates and the global uniform grid, wherein the resolution of a variable grid core area is larger than the resolution of the core area in the global uniform grid, and the resolution of a variable grid non-core area is smaller than the resolution of the non-core area in the global uniform grid;
and carrying out regional interpolation on the global topographic data based on the interpolation weight coefficient of the variable grid so as to obtain the variable grid topographic data, wherein the density of the variable grid topographic data is matched with the structure of the variable grid.
2. The terrain data generating method of claim 1, wherein the implementation method for generating a variable grid from the longitude and latitude coordinates and the global uniform grid comprises:
performing polar projection on grid points of the global uniform grid through Schmitt transformation to obtain plane grid points of the variable grid, wherein the center grid point of the plane grid points is an earth pole, and the grid points of the global uniform grid are converged towards the center grid point of the plane grid points after projection;
and carrying out rigid rotation on the plane lattice points to obtain the variable grids, wherein the coordinates of the central lattice points of the plane lattice points after the rigid rotation are longitude and latitude coordinates.
3. The terrain data generating method according to claim 2, wherein the latitude before the lattice point schmitt transformation of the global uniform grid is a first latitude, and the latitude after the lattice point schmitt transformation of the global uniform grid is a second latitude, the second latitude being represented by:
where θ is the first latitude and where,and for the second latitude, S is a tensile latitude conversion factor of the variable grid.
4. A terrain data generating method according to claim 3, characterized in that the tension latitude conversion factor of the variable grid is expressed by:
where x is the focusing stretch factor.
5. The terrain data generating method of claim 1, wherein the implementation method of performing area interpolation on the terrain data to obtain the variable grid terrain data comprises:
performing regional interpolation processing on the topographic data based on the interpolation weight coefficient to acquire topographic data to be processed;
and carrying out smoothing treatment on the topographic data to be treated so as to obtain the variable grid topographic data.
6. The topographic data generating method according to claim 5, characterized in that the implementation method of smoothing the topographic data to be processed includes: performing smoothing processing on the terrain data to be processed based on a smoothing algorithm to obtain the variable grid terrain data, wherein the smoothing algorithm comprises any one or more of the following algorithms: spatial 9-point smoothing, adjacent point slope smoothing, and region conservation smoothing.
7. A weather prediction method, the weather prediction method comprising:
weather prediction is performed on a region to be predicted based on variable grid terrain data acquired using the terrain data generation method according to any one of claims 1 to 6.
8. A terrain data generating apparatus, applied to a weather prediction system, comprising:
the uniform grid acquisition module is used for acquiring longitude and latitude coordinates of the region to be predicted and the global uniform grid;
the variable grid acquisition module is used for generating a variable grid according to the longitude and latitude coordinates and the global uniform grid, the resolution of the variable grid core area is larger than the resolution of the core area in the global uniform grid, and the resolution of the variable grid non-core area is smaller than the resolution of the non-core area in the global uniform grid;
the terrain data acquisition module is used for carrying out regional interpolation on global terrain data based on the interpolation weight coefficient of the variable grid so as to acquire the variable grid terrain data, and the density of the variable grid terrain data is matched with the variable grid structure.
9. A computer readable storage medium having stored thereon a computer program, which when executed by a processor implements the terrain data generating method according to any of claims 1-6.
10. An electronic device, the electronic device comprising:
a memory storing a computer program;
a processor communicatively coupled to said memory for executing the terrain data generating method of any of claims 1-6 when said computer program is invoked;
and the display is in communication connection with the processor and the memory and is used for displaying a related GUI interactive interface of the topographic data generating method.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102077698A (en) * | 2008-06-30 | 2011-05-25 | 新日铁化学株式会社 | Flexible circuit board and method for producing same and bend structure of flexible circuit board |
| JP2013246779A (en) * | 2012-05-29 | 2013-12-09 | For-A Co Ltd | Unified optimal calculation method and program for two-dimensional or three-dimensional geometric transformation |
| CN105336003A (en) * | 2015-09-28 | 2016-02-17 | 中国人民解放军空军航空大学 | Three-dimensional terrain model real-time smooth drawing method with combination of GPU technology |
| US20170351793A1 (en) * | 2016-06-01 | 2017-12-07 | Disney Enterprises, Inc. | Algebraic multigrid method for cloth simulation |
| CN108038249A (en) * | 2017-12-28 | 2018-05-15 | 北京星球时空科技有限公司 | A kind of one diagram data storage organization method in whole world and call method |
| CN111401634A (en) * | 2020-03-13 | 2020-07-10 | 成都信息工程大学 | Processing method, system and storage medium for acquiring climate information |
| US10930072B1 (en) * | 2019-11-11 | 2021-02-23 | Bentley Systems, Incorporated | Multi-resolution mesh real-time contouring |
| CN112731565A (en) * | 2021-03-17 | 2021-04-30 | 北京墨迹风云科技股份有限公司 | Weather forecast data processing method and device based on multi-level grid map |
| CN114492252A (en) * | 2022-04-18 | 2022-05-13 | 中国人民解放军国防科技大学 | Coordinate tree space mapping method for overlapped grid contribution unit search |
-
2022
- 2022-12-27 CN CN202211683921.3A patent/CN116563091B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102077698A (en) * | 2008-06-30 | 2011-05-25 | 新日铁化学株式会社 | Flexible circuit board and method for producing same and bend structure of flexible circuit board |
| JP2013246779A (en) * | 2012-05-29 | 2013-12-09 | For-A Co Ltd | Unified optimal calculation method and program for two-dimensional or three-dimensional geometric transformation |
| CN105336003A (en) * | 2015-09-28 | 2016-02-17 | 中国人民解放军空军航空大学 | Three-dimensional terrain model real-time smooth drawing method with combination of GPU technology |
| US20170351793A1 (en) * | 2016-06-01 | 2017-12-07 | Disney Enterprises, Inc. | Algebraic multigrid method for cloth simulation |
| CN108038249A (en) * | 2017-12-28 | 2018-05-15 | 北京星球时空科技有限公司 | A kind of one diagram data storage organization method in whole world and call method |
| US10930072B1 (en) * | 2019-11-11 | 2021-02-23 | Bentley Systems, Incorporated | Multi-resolution mesh real-time contouring |
| CN111401634A (en) * | 2020-03-13 | 2020-07-10 | 成都信息工程大学 | Processing method, system and storage medium for acquiring climate information |
| CN112731565A (en) * | 2021-03-17 | 2021-04-30 | 北京墨迹风云科技股份有限公司 | Weather forecast data processing method and device based on multi-level grid map |
| CN114492252A (en) * | 2022-04-18 | 2022-05-13 | 中国人民解放军国防科技大学 | Coordinate tree space mapping method for overlapped grid contribution unit search |
Non-Patent Citations (11)
| Title |
|---|
| 冯树常，彭爱和: "一个在球面半规则网格上的求解Helmholtz方程的多重网格法", 气象科技, no. 02 * |
| 刘卓，曾庆存: "非常定自适应网格模式在台风路径数值预报中的应用", 大气科学, no. 03 * |
| 康来;吴玲达;宋汉辰;杨冰;: "基于投影网格的全球多分辨率地形绘制", 计算机工程, no. 08 * |
| 张光, 张克实, 冯露: "硬化模型对多晶变形织构预测的影响", 机械科学与技术, no. 08 * |
| 张汉武;王海波;张萍萍;: "基于横向地球坐标系的极区惯导机械编排研究", 舰船电子工程, no. 08 * |
| 彭新东;李兴良;: "多尺度大气数值预报的技术进展", 应用气象学报, no. 02 * |
| 徐国强, 胡欣, 张迎新, 李晓燕: "河北省变网格数值预报系统设计和试验", 气象, no. 12 * |
| 杨名生, 史奇: "交互有限元网格自动生成算法", 计算力学学报, no. 01 * |
| 沈桐立, 丁一汇, 覃丹宇, 徐国强: "有限区域模式的非均匀网格应用研究", 南京气象学院学报, no. 01 * |
| 解杨敏;郭煜坤;邹怀武;史航;: "曲率分析的变分辨率数字高程模型建模算法", 国防科技大学学报, no. 06 * |
| 钱滔滔, 郭肖容, 廖洞贤: "一个有限区变网格模式的设计", 大气科学, no. 06 * |
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