Meteorological dynamic prediction multi-scale smooth transition method, device and equipment

Abstract

The invention relates to the technical field of meteorological prediction, and discloses a meteorological dynamic prediction multi-scale smooth transition method, device and equipment, and the method comprises the steps: building a focusing grid topological structure according to the regional focusing mode power frame characteristics for a target region; applying the dynamic equation and the physical process parameterization matched with the dynamic equation to the focusing grid topological structure to obtain a power framework parameter and a physical process parameter corresponding to each grid in the focusing grid topological structure; and performing focusing smooth nesting processing on the power frame parameters and the physical process parameters of each grid to obtain forecast values of meteorological elements under different resolutions. By implementing the method, large-scale coarse-resolution signals can be transmitted to high-resolution and small-scale high-fidelity under the focusing variable grid condition, the boundary effect is reduced while the temporal-spatial resolution of meteorological elements in a target area is improved, the maximum fidelity of prediction signals is realized, the prediction time efficiency is prolonged, and the prediction precision is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of meteorological forecasting, and in particular to a multi-scale smooth transition method, device and equipment for meteorological dynamics forecasting. Background Art

[0002] With the development of new energy, the problem of grid connection difficulty has gradually emerged. Since new energy power generation is intermittent and unstable, it has a huge impact on the power grid after grid connection. Therefore, the prediction and regulation of new energy power generation is an important condition for the stable operation and effective absorption of wind power grid connection. New energy power generation mainly includes photovoltaic power generation, wind power generation, etc. The power generation is mainly affected by environmental factors. Therefore, in order to realize the prediction and regulation of new energy power generation, it is necessary to predict the weather first.

[0003] The existing regional meteorological model forecasting scheme is the WRF model, which is a commercial regional high-resolution model: WRF, the full name is Weather Research and Forecast Model, that is, the weather research and forecast model. WRF has two frameworks to choose from, NMM and ARW. It can be used as a global model for weather forecasting, or as a regional model for numerical simulation of weather processes. WRF adopts a non-hydrostatic equilibrium framework, with terrain-following coordinates in the horizontal direction and eta coordinates in the vertical direction. Non-hydrostatic equilibrium and eta coordinates in the vertical direction can meet most mesoscale weather research. In recent years, WRF has also begun to be used as a regional climate model. Due to its eta coordinate characteristics and a large number of physical parameterization schemes, WRF has stronger compatibility. WRF can perform weather forecasts in the global mode, including ideal experiments, single column models, ideal squall lines to ideal typhoons. WRF also contains a separate atmospheric chemistry module for aerosol simulation and forecasting. WRF's built-in assimilation system WRFDA has a full set of assimilation algorithms such as three-dimensional variational, four-dimensional variational and ensemble Kalman filtering.

[0004] The traditional WRF model workflow uses a three-layer nesting scheme, setting up multiple layers of grids with different resolutions in the WRF preprocessing system WPS and calculating the meteorological forecast results of the layer grids. Since the connection between the inner and outer layers of the model adopts a one-way step-by-step nesting scheme, it is easy to cause unstable connection of model signals under different resolution conditions of the inner and outer layers of the model, which amplifies the prediction error. Summary of the invention

[0005] In view of this, an embodiment of the present invention provides a multi-scale smooth transition method, device and equipment for meteorological dynamic forecasting to solve the problem of unstable connection between different resolutions in existing nested solutions.

[0006] In the first aspect, an embodiment of the present invention provides a multi-scale smooth transition method for meteorological dynamic forecasting, including: for the target area, establishing a focused grid topology structure according to the dynamic framework characteristics of the regional focusing mode; applying the dynamic equation and the physical process parameterization matching it to the focused grid topology structure to obtain the dynamic framework parameters and physical process parameters corresponding to each grid in the focused grid topology structure; performing focused smooth nesting processing on the dynamic framework parameters and physical process parameters of each grid to obtain forecast values ​​of meteorological elements at different resolutions.

[0007] The multi-scale smooth transition method for meteorological dynamic forecasting provided by the embodiment of the present invention establishes a focused grid topology structure for the target area. The focused grid topology structure is established by adopting the regional focusing mode of the finite volume cubic spherical grid. The dynamic framework and physical process parameterization are applied to the focused grid topology structure. The dynamic framework parameters and physical process parameters of each grid can be smoothly nested to obtain the forecast values ​​of meteorological elements at different levels of grids and different time scales, and the high-fidelity transmission of large-scale coarse-resolution signals to high-resolution small-scale signals under the condition of focused variable grids can be realized. While improving the spatiotemporal resolution of meteorological elements in the target area, the boundary effect is reduced, the maximum fidelity of the prediction signal is achieved, the prediction time is extended, and the prediction accuracy is improved.

[0008] In an optional embodiment, a focusing grid topology structure is established according to the regional focusing mode dynamic framework characteristics, including: obtaining a cubic spherical uniform grid topology structure of the target area and an original resolution of the target area; determining a core area of ​​the target area and a target resolution of the core area, wherein the target resolution is less than the original resolution; calculating conversion parameters according to the original resolution and the target resolution; and formatting each grid in the cubic spherical uniform grid topology structure according to the conversion parameters to obtain a focusing grid topology structure of the target area, wherein the resolution of each grid in the focusing grid topology structure decreases successively along a target direction, and the target direction is a direction from a boundary of the target area to a boundary of the core area.

[0009] In an optional embodiment, conversion parameters are calculated based on the original resolution and the target resolution, including: determining the pull-up coefficient of the focus transformation based on the original resolution and the target resolution; calculating the focus conversion coefficient based on the pull-up coefficient; calculating the focus-to-grid transformation angle of each grid based on the focus conversion coefficient and the spherical angle of each grid in the cube spherical uniform grid topology structure before transformation.

[0010] In an optional implementation, the dynamic framework parameters and physical process parameters of each grid are focused, smoothly nested, and forecast values ​​of meteorological elements at different resolutions are obtained, including: integrating the dynamic framework parameters on a time scale to obtain updated dynamic framework parameters; updating the physical process parameters according to the updated dynamic framework parameters to obtain updated physical process parameters; and obtaining forecast values ​​of meteorological elements at different time scales for grids of different resolutions based on the updated dynamic framework parameters and physical process parameters of grids at different levels.

[0011] In an optional embodiment, the dynamic framework grid parameters of two adjacent grid layers satisfy the element mass and flux conservation formulas during the integration process.

[0012] In a second aspect, an embodiment of the present invention provides a multi-scale smooth transition device for meteorological dynamics forecasting, comprising:

[0013] The topological structure construction module is used to establish a focused grid topological structure for the target area according to the dynamic framework characteristics of the regional focusing mode; the mapping module is used to apply the dynamic equations and the matching physical process parameters to the focused grid topological structure to obtain the dynamic framework parameters and physical process parameters corresponding to each grid in the focused grid topological structure; the smoothing nesting module is used to perform focused and smoothing nesting processing on the dynamic framework parameters and physical process parameters of each grid to obtain the forecast values ​​of meteorological elements at different resolutions.

[0014] In an optional embodiment, the topology structure construction module includes: a spherical uniform grid acquisition submodule, which is used to acquire the cubic spherical uniform grid topology structure of the target area and the original resolution of the target area; a parameter determination submodule, which is used to determine the core area of ​​the target area and the target resolution of the core area, and the target resolution is less than the original resolution; a conversion parameter calculation submodule, which is used to calculate the conversion parameters according to the original resolution and the target resolution; a grid conversion submodule, which is used to convert the format of each grid in the cubic spherical uniform grid topology structure according to the conversion parameters to obtain a focused grid topology structure of the target area, in which the resolution of each grid decreases successively along the target direction, and the target direction is the direction from the boundary of the target area to the boundary of the core area.

[0015] In a third aspect, an embodiment of the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the multi-scale smooth transition method for meteorological dynamic forecasting of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0016] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the multi-scale smooth transition method for meteorological dynamic forecasting of the above-mentioned first aspect or any corresponding embodiment thereof.

[0017] In a fifth aspect, an embodiment of the present invention provides a computer program product, comprising computer instructions, which are used to enable a computer to execute the multi-scale smooth transition method for meteorological dynamic forecasting of the above-mentioned first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 is a schematic flow chart of a multi-scale smooth transition method for meteorological dynamics prediction according to some embodiments of the present invention;

[0020] Figure 2 It is a schematic diagram of several forms of finite volume cubic sphere grid;

[0021] Figure 3 is a structural block diagram of a multi-scale smooth transition device for meteorological dynamics prediction according to an embodiment of the present invention;

[0022] Figure 4 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0024] The traditional WRF model workflow is to use a three-layer nested scheme to set up multiple layers of grids with different resolutions in the WRF preprocessing system WPS. For example, the outer layer resolution is 25km, the second layer resolution is 12km, and the innermost layer resolution is 3km. The grid coverage range is the target area and some surrounding areas. For example, the grid range is: 36-43°N, 113.3-120.1°E. Set namelist.input in ARW, the integration step is 30s, and the mainstream physical parameter scheme combination suitable for the target area is selected. The specific parameter setting scheme is determined by actual experiments. Generate WRF boundary field and initial field, use MPI parallel computing method to forecast the weather conditions in the next few days, and output the forecast results in sequence every preset time. After the forecast is completed, the post-processing uses python for data extraction, conversion, processing and visualization services, and the forecast results will be released on time at a fixed time. In the above method, when parallel computing is used, 3 nodes and 72 cores can be set to perform the forecast task to forecast the weather conditions for the next 10 days and output the forecast results every 15 minutes. The main forecast elements are: 2m temperature (T2m), 2m relative humidity (Rh2m), total radiation irradiance, direct radiation irradiance, scattered radiation irradiance, and wind speed and direction at different heights of 10m, 30m, 50m, 70m, 90m, 100m, 110m, 120m, 130m, 140m and 150m. In the above scheme, the grid is discontinuous from coarse to fine. The coarse grid data will enter the fine grid as it is transmitted, and the interpolation process is step-like, which will lead to lateral boundary effects and amplify the model forecast error.

[0025] According to an embodiment of the present invention, an embodiment of a multi-scale smooth transition method for meteorological dynamic forecasting is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0026] In this embodiment, a multi-scale smooth transition method for meteorological dynamics prediction is provided. Figure 1 is a flow chart of a multi-scale smooth transition method for meteorological dynamics prediction according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0027] Step S101: for a target area, a focusing grid topology structure is established according to the regional focusing mode dynamic framework characteristics.

[0028] In an embodiment of the present invention, the focusing grid topology is a form of a finite volume cubic sphere grid.

[0029] The finite volume cubic spherical grid is a grid structure that divides and approximates the earth's surface based on a cube. It maps the earth's surface onto a cube, and then further divides the six faces of the cube into smaller grid units, thereby achieving a discretized representation of the earth's surface. In this way, complex earth surface problems are converted into numerical calculations and simulations on a regular cubic grid. The focusing grid topology structure established in the embodiment of the present invention is based on the same Figure 2 The corresponding mode in the lower right corner is established.

[0030] Step S102 : applying the dynamic equation and the physical process parameterization matched therewith to the focused grid topology structure, and obtaining the dynamic framework parameters and physical process parameters corresponding to each grid in the focused grid topology structure.

[0031] In an optional embodiment, the dynamic equations in the dynamic framework include basic equations describing atmospheric motion, such as momentum equations, continuity equations, etc.

[0032] Physical process parameterization is used to characterize some physical processes that cannot be directly described by the dynamical framework, such as radiation processes, water vapor phase change processes, etc.

[0033] The dynamic framework adopted in the embodiment of the present invention is a model dynamic framework based on a finite volume cubic spherical grid. Compared with the traditional WRF model, this dynamic framework divides the world into 6 surfaces according to geographic information coordinates. Each surface is calculated in parallel separately, and calculus information is exchanged between surfaces through an information transmission layer.

[0034] Since the finite volume method is a numerical method developed based on physical conservation laws, it can strictly guarantee the conservation properties of the numerical solution. In addition, the construction process of the model dynamics framework based on the finite volume cubic spherical grid is based on clear physical concepts, has good scalability, can achieve high precision, and can guarantee strict numerical conservation. Compared with the discontinuous Galerkin and spectral element methods, it better balances the requirements of numerical models in terms of computational accuracy, robustness, algorithm simplicity and computational efficiency, and has high practical value. At the same time, the hexahedral segmentation parallel calculation is adopted to increase the parallel efficiency and scalability of the model dynamics framework, and achieve the optimal computational efficiency under the same calculation line. Furthermore, the relatively clear calculation formula, topological structure and grid conservation of the model dynamics framework based on the finite volume cubic spherical grid facilitate various forms of grid nesting. The nesting forms include single grid nesting, multi-grid nesting, multiple grid nesting, regional focusing, regional focusing combined with nesting, etc.

[0035] Step S103, performing nested smoothing processing on the dynamic framework parameters and physical process parameters of each grid to obtain forecast values ​​of meteorological elements at different resolutions.

[0036] The multi-scale smooth transition method for meteorological dynamic forecasting provided by the embodiment of the present invention establishes a focused grid topology structure for the target area. The focused grid topology structure is established by adopting the regional focusing mode of the finite volume cubic spherical grid. The dynamic framework and physical process parameterization are applied to the focused grid topology structure. The dynamic framework parameters and physical process parameters of each grid can be smoothly nested to obtain the forecast values ​​of meteorological elements at different resolutions, and the high-fidelity transmission of large-scale coarse-resolution signals to high-resolution small-scale signals under the condition of focused variable grids can be realized. While improving the spatiotemporal resolution of meteorological elements in the target area, the boundary effect is reduced, the maximum fidelity of the prediction signal is achieved, the prediction time is extended, and the prediction accuracy is improved.

[0037] In an optional embodiment, the above step S101 specifically includes:

[0038] Step a1, obtaining the cube spherical uniform grid topology structure of the target area and the original resolution of the target area.

[0039] In the cube sphere uniform grid topology, the target area is divided into multiple grids of the same size.

[0040] Step a2, determining a core area of ​​the target area and a target resolution of the core area, wherein the target resolution is smaller than the original resolution.

[0041] The core area is the area to be studied, and the resolution of the core area can be set according to actual needs. For example, the original resolution of the target area is 25km globally. When it is necessary to obtain refined data of the core area, the core area is focused 8 times to make the resolution of the core area reach 3.25km.

[0042] Step a3, calculating conversion parameters according to the original resolution and the target resolution.

[0043] In the embodiment of the present invention, it is necessary to perform Schmidt transformation on the cube spherical uniform grid topology structure to obtain the focused grid topology structure. When performing the Schmidt transformation, it is necessary to calculate the transformation parameters first.

[0044] Step a4, converting the formats of the grids in the cube spherical uniform grid topology structure according to the conversion parameters to obtain a focused grid topology structure of the target area. In the focused grid topology structure, the resolution of each grid decreases successively along the target direction, and the target direction is the direction from the boundary of the target area to the boundary of the core area.

[0045] In an optional embodiment, the above step a3 specifically includes the following steps:

[0046] Step a31, determining the upscaling coefficient of the focus transformation according to the original resolution and the target resolution.

[0047] In an optional embodiment, the range of the stretching factor is determined by the actual stretching resolution requirement. The grid ratio can be a multiple of 2. For example, for a basic uniform grid with a resolution of 100 kilometers, if the stretching ratio is 2, the focus center resolution is 50 kilometers, and if the stretching ratio is 4, the focus center resolution is 25 kilometers. That is, the stretching factor is determined based on the quotient of the original resolution and the target resolution.

[0048] Step a32, calculating the focus conversion coefficient according to the pull-up coefficient:

[0049]

[0050] Where c is the pull-up coefficient.

[0051] Step a33, calculating the focus transformation angle of each grid according to the focus transformation coefficient and the spherical angle of each grid before transformation in the cubic spherical uniform grid topology structure:

[0052]

[0053] in, is the focus grid transformation angle, D is the focus conversion coefficient, and θ is the spherical angle before transformation.

[0054] In an optional embodiment, the above step S103 specifically includes:

[0055] Step b1, integrating the power frame parameters on a time scale to obtain updated power frame parameters.

[0056] Step b2, updating the physical process parameters according to the updated power framework parameters to obtain updated physical process parameters.

[0057] Step b3, according to the dynamic framework parameters and physical process parameters of the grids at different levels after each update, the forecast values ​​of the meteorological elements of the grids at different levels at different time scales are obtained.

[0058] In the embodiment of the present invention, the model is divided into a dynamic framework and a physical process parameterization, and the integration process is a dynamic process that cooperates with each other. The dynamic framework usually contains basic equations that describe atmospheric motion, such as momentum equations, continuity equations, etc. When integrating the dynamic framework, it is equivalent to calculating the changes of these physical quantities (such as speed, density, etc.) at the next moment according to the time step and the current physical quantities.

[0059] At the same time, the physical process parameterization module handles some physical processes that cannot be directly described by the dynamical framework, such as radiation processes, water vapor phase change processes, etc. The physical process parameters are updated while the dynamical framework is integrated, because the changes in physical quantities during the dynamical framework integration process will affect the physical quantities involved in these physical process parameterization processes, and vice versa. For example, the movement of the atmosphere (dynamical framework description) will change the distribution of water vapor, and the water vapor phase change (physical process parameterization) will affect the movement state of the atmosphere.

[0060] After each dynamic framework integration and physical process parameterization update, the dynamic framework integration is performed backwards, just like a chain, one link after another. This process is repeated continuously, so that the physical quantity evolves gradually and continuously on the basis of the uniform grid space as time goes on, thereby simulating the dynamic changes of physical processes such as meteorology in the grid area.

[0061] In an optional embodiment, the dynamic framework grid parameters of two adjacent layers of grids satisfy the element mass and flux conservation formulas during the integration process.

[0062] In the process of model integration, assuming that the model integration step is Δt, the focused nested grid is considered to be divided into n sub-times in time. In each sub-time, the time step of the focused nested grid is Δt / n. Inside the focused nested grid, the coarse and fine grids are considered to be focused bidirectionally nested. In order to ensure the organic connection between the inner and outer layers of the grid, the information transfer smoothing function is used to ensure the quality of meteorological elements and the flux conservation formula of the inner and outer grids during the integration process:

[0063]

[0064] In which, it is assumed that the model integration variable is V (which can be variables such as temperature, pressure, humidity, wind, etc.), N is the specific k_split value, k_split is the specific number of divisions of the model time step, which determines the division coefficient on the time trend, n is the specific time integration step, f t is the smoothing supplement coefficient, V t is the outer layer transmission variable, which is then smoothly transmitted through the inner and outer layers to obtain the inner layer flux V t / n .

[0065] In the present embodiment, a kind of meteorological dynamic forecast multi-scale smooth transition device is also provided, and this device is used to realize the above-mentioned embodiment and preferred implementation mode, and what has been described is not repeated here. As used below, the term "module" can realize the combination of software and / or hardware of predetermined function. Although the device described in the following embodiments is preferably realized with software, the realization of hardware, or the combination of software and hardware is also possible and conceived.

[0066] This embodiment provides a multi-scale smooth transition device for meteorological dynamics prediction, such as Figure 3 As shown, including:

[0067] The topology building module 201 is used to establish a focus grid topology structure for the target area according to the regional focus mode power framework characteristics. For details, please refer to the description in the above embodiment, which will not be repeated here.

[0068] The mapping module 202 is used to apply the dynamic equation and the physical process parameterization matched therewith to the focused grid topology structure to obtain the dynamic framework parameters and physical process parameters corresponding to each grid in the focused grid topology structure. For details, please refer to the description in the above embodiment and will not be repeated here.

[0069] The smooth nesting module 203 is used to perform focused smooth nesting processing on the dynamic framework parameters and physical process parameters of each grid to obtain the forecast values ​​of meteorological elements at different resolutions. For details, please refer to the description in the above embodiment, which will not be repeated here.

[0070] In an optional embodiment, the topology building module 201 includes:

[0071] The spherical uniform grid acquisition submodule is used to obtain the cubic spherical uniform grid topological structure of the target area and the original resolution of the target area.

[0072] The parameter determination submodule is used to determine the core area of ​​the target area and the target resolution of the core area, and the target resolution is smaller than the original resolution. For details, please refer to the description in the above embodiment, which will not be repeated here.

[0073] The conversion parameter calculation submodule is used to calculate the conversion parameters according to the original resolution and the target resolution. For details, please refer to the description in the above embodiment, which will not be repeated here.

[0074] The grid conversion submodule is used to convert the format of each grid in the cube spherical uniform grid topology structure according to the conversion parameters to obtain a focused grid topology structure of the target area. In the focused grid topology structure, the resolution of each grid decreases in sequence along the target direction, and the target direction is the direction from the boundary of the target area to the boundary of the core area. For details, please refer to the description in the above embodiment, which will not be repeated here.

[0075] The multi-scale smooth transition device for meteorological dynamic forecasting in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0076] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0077] The embodiment of the present invention also provides a computer device having the above Figure 3 The multi-scale smooth transition device for meteorological dynamic forecasting is shown.

[0078] See also Figure 4 , Figure 4 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 4 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 4 A processor 10 is taken as an example.

[0079] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0080] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0081] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created by the use of a computer device based on the presentation of a small program landing page, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0082] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0083] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0084] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0085] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0086] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A multi-scale smooth transition method for meteorological dynamics forecasting, characterized in that: The method comprises: For the target area, a focusing grid topology is established according to the characteristics of the regional focusing mode dynamic framework; Applying the dynamic equation and the physical process parameterization matched therewith to the focusing grid topology structure to obtain the dynamic framework parameters and physical process parameters corresponding to each grid in the focusing grid topology structure; The dynamic framework parameters and physical process parameters of each grid are subjected to focused smoothing and nesting processing to obtain the forecast values ​​of meteorological elements at different resolutions.

2. The method according to claim 1, characterized in that The method of establishing a focusing grid topology structure according to the regional focusing mode dynamic framework characteristics includes: Acquire a cube spherical uniform grid topology structure of the target area and an original resolution of the target area; Determining a core area of ​​the target area and a target resolution of the core area, wherein the target resolution is less than the original resolution; Calculating conversion parameters according to the original resolution and the target resolution; The format of each grid in the cube spherical uniform grid topology structure is converted according to the conversion parameters to obtain a focused grid topology structure of the target area. In the focused grid topology structure, the resolution of each grid decreases successively along the target direction, and the target direction is the direction from the boundary of the target area to the boundary of the core area.

3. The method according to claim 2, characterized in that The calculating the conversion parameter according to the original resolution and the target resolution comprises: Determine a pull-up coefficient of a focus transformation according to the original resolution and the target resolution; Calculate the focus conversion coefficient according to the pull-up coefficient; The focusing grid transformation angle of each grid is calculated according to the focusing transformation coefficient and the spherical angle of each grid before transformation in the cube spherical uniform grid topology structure.

4. The method according to claim 1, characterized in that: The dynamic framework parameters and physical process parameters of each grid are subjected to focused smoothing and nesting processing to obtain forecast values ​​of meteorological elements at different resolutions, including: Integrating the power frame parameters on a time scale to obtain updated power frame parameters; Updating the physical process parameters according to the updated power framework parameters to obtain updated physical process parameters; According to the dynamic framework parameters and physical process parameters of grids at different levels after each update, the forecast values ​​of meteorological elements at different time scales for grids with different resolutions are obtained.

5. The method according to claim 4, characterized in that The dynamic frame grid parameters of two adjacent grid layers satisfy the element mass and flux conservation formulas during the integration process.

6. A multi-scale smooth transition device for meteorological dynamics forecasting, characterized in that: The device comprises: A topology building module is used to establish a focusing grid topology structure for a target area according to the characteristics of the regional focusing mode dynamic framework; A mapping module, used for applying the dynamic equation and the physical process parameterization matched therewith to the focusing grid topology structure, and obtaining the dynamic framework parameters and the physical process parameters corresponding to each grid in the focusing grid topology structure; The smooth nesting module is used to perform focused smooth nesting processing on the dynamic framework parameters and physical process parameters of each grid to obtain the forecast values ​​of meteorological elements at different resolutions.

7. The device according to claim 6, characterized in that The topology building module includes: A spherical uniform grid acquisition submodule is used to acquire a cubic spherical uniform grid topological structure of the target area and an original resolution of the target area; A parameter determination submodule, used to determine a core area of ​​the target area and a target resolution of the core area, wherein the target resolution is smaller than the original resolution; A conversion parameter calculation submodule, used to calculate conversion parameters according to the original resolution and the target resolution; The grid conversion submodule is used to convert the format of each grid in the cube spherical uniform grid topology structure according to the conversion parameters to obtain a focused grid topology structure of the target area. In the focused grid topology structure, the resolution of each grid decreases successively along the target direction, and the target direction is the direction from the boundary of the target area to the boundary of the core area.

8. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 5 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 5.

10. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the method according to any one of claims 1 to 5.

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