Weather forecast information generation method and device, equipment, medium and product

Abstract

The invention provides a weather forecast information generation method and device, equipment, a medium and a product. The method comprises the steps that when target weather forecast information is generated based on demand information, a target production line path available for the target weather forecast information can be determined in a unified directory according to the demand information, so that target weather data is acquired according to the target production line path, and the target weather forecast information is generated according to the target weather data. Production line paths corresponding to multiple target meteorological elements under multiple production dates are automatically collected in the unified directory, each target meteorological element corresponds to multiple production line paths, the multiple production line paths correspond to different time scales and spatial scales, and the target meteorological elements are meteorological elements required by the target meteorological forecast information. Therefore, the target meteorological data can be obtained based on the unified catalog when various requirements of the meteorological forecast information for different time scales, different meteorological elements and the like are met, and the flexibility of generating the meteorological forecast information is improved.

Description

Technical Field

[0001] The present application relates to the field of meteorological technology, and in particular to a method, device, equipment, medium and product for generating meteorological forecast information. Background Art

[0002] Due to the different physical properties of different meteorological elements and their different impacts on forecast accuracy, the meteorological data corresponding to each meteorological element can be produced through different numerical models and processing methods, so that the meteorological data of each meteorological element can be obtained on independent production lines.

[0003] In related technologies, the generation system of weather forecast information usually relies on a single numerical model, which makes the system less flexible in generating weather forecast information when dealing with meteorological data generated by multi-source numerical models. Summary of the Invention

[0004] The present application provides a method, device, equipment, medium and product for generating weather forecast information, which are used to solve the problem of poor flexibility in generating weather forecast information in related technologies.

[0005] In a first aspect, the present application provides a method for generating weather forecast information, comprising:

[0006] Obtaining target weather forecast information requirement information, wherein the requirement information includes a target forecast date, a target time scale, and a target spatial scale;

[0007] Determining, based on the demand information, whether a target production line path available for generating the target weather forecast information exists in a unified catalog, the unified catalog including production line paths corresponding to multiple target weather elements under multiple production dates, each target weather element corresponding to multiple production line paths, the multiple production line paths corresponding to different time scales and / or spatial scales, the target weather elements being the weather elements required for the target weather forecast information;

[0008] If so, target meteorological data is acquired according to the target production line path, and the target meteorological forecast information is generated according to the target meteorological data.

[0009] In this embodiment, when generating target weather forecast information based on demand information, the target production line paths available for the target weather forecast information can be determined from a unified directory based on the demand information, thereby acquiring target weather data based on the target production line paths and generating target weather forecast information based on the target weather data. The unified directory automatically aggregates production line paths corresponding to multiple target weather elements under multiple production dates, with each target weather element corresponding to multiple production line paths. The multiple production line paths correspond to different time and spatial scales, and the target weather elements are the weather elements required for the target weather forecast information. This allows target weather data to be acquired based on the unified directory when addressing various demands for weather forecast information, such as those for different time scales and different weather elements, thereby enhancing the flexibility of weather forecast information generation.

[0010] In a possible implementation, determining, based on the demand information, whether there is a target production line path in the unified directory that is available for generating the target weather forecast information includes:

[0011] determining, based on the target forecast date, whether a production line path for the target meteorological element under the multiple production dates includes a production line path for the first production date, the first production date being the date closest to the target forecast date;

[0012] If so, based on the target time scale and the target spatial scale, determine whether there is a production line path corresponding to the target time scale and the target spatial scale in the production line path of the first production date as the target production line path.

[0013] In this embodiment, a target forecast date is used to determine whether a production line path for a first production date exists among the production line paths for target meteorological elements for multiple production dates. The first production date is the date closest to the target forecast date. If so, based on the target time scale and target spatial scale, a determination can be made as to whether a production line path corresponding to the target time scale and target spatial scale exists among the production line paths for the first production date, thereby determining the target production line path. The target production line path can then be used to obtain the target meteorological data required for producing the target meteorological product.

[0014] In a possible implementation, the demand information further includes target meteorological elements and user preferences; and the method further includes:

[0015] Obtain meteorological data of various meteorological elements on the current production date. The meteorological data of each meteorological element includes meteorological data at multiple time scales and multiple spatial scales.

[0016] Storing meteorological data of the plurality of meteorological elements and generating an actual storage path of the meteorological data of each meteorological element;

[0017] Determining meteorological data of the target meteorological element from the meteorological data of the multiple meteorological elements, and determining target meteorological data corresponding to the target spatial scale and the target time scale from the meteorological data of the target meteorological element;

[0018] According to the actual storage path of the target meteorological data, a soft link is created for the target meteorological data in the unified directory to generate a production line path corresponding to the target meteorological element under the current production date.

[0019] In this embodiment, by storing the meteorological data of multiple meteorological elements produced on each production date, and then soft-linking the meteorological data of the target meteorological element to a unified directory, it is convenient to directly find the target meteorological data in the unified directory when generating target forecast information, thereby improving the flexibility of producing target meteorological forecast information.

[0020] In a possible implementation, the method further includes:

[0021] At preset time intervals, monitoring operations are performed on production line paths corresponding to multiple target meteorological elements under multiple production dates in the unified catalog to obtain monitoring results, wherein the monitoring operations include: determining whether meteorological data under each production line path is readable and whether the size occupied by the meteorological data under each production line path is accurate;

[0022] If the monitoring result indicates that any production line path has an abnormality, the unified directory is updated.

[0023] In this embodiment, the production line paths of target meteorological elements under the unified directory can be monitored in real time to avoid interruption of target meteorological product production due to unavailability of target meteorological data.

[0024] In one possible implementation, there are multiple target meteorological variables, and the target meteorological data includes candidate meteorological data corresponding to each target meteorological variable. For any target meteorological variable, there are multiple groups of candidate meteorological data for the target meteorological variable, and each group of candidate meteorological data has a different data source. The demand information also includes user preferences, and the user preferences include the source of the target data and / or sensitivity to error.

[0025] According to the actual storage path of the target meteorological data, a soft link is created for the target meteorological data in the unified directory to generate a production line path corresponding to the target meteorological element under the current production date, including:

[0026] For any target meteorological variable, based on the user preference, the first meteorological data is determined from multiple groups of candidate meteorological data of the target meteorological variable; and based on the actual storage path of the first meteorological data, a soft link is created for the first meteorological data under the unified directory to generate the production line path corresponding to the first meteorological data under the current production date.

[0027] In this embodiment, based on user preferences, a group of candidate meteorological data that meets the user's requirements can be selected from multiple groups of candidate meteorological data and a soft link can be created in a unified directory to improve the accuracy of meteorological product production.

[0028] In a possible implementation, the user preference includes sensitivity to errors, and determining the first meteorological data from multiple sets of candidate meteorological data according to the user preference includes:

[0029] Determining that the data source of each set of candidate meteorological data is historical meteorological data within a first preset time period;

[0030] Acquiring historical meteorological forecast information generated by the historical meteorological data, wherein the historical meteorological forecast information indicates a plurality of forecast data, and the first preset time period is a time period before the current production date;

[0031] Acquiring a variety of live data within the first preset time period;

[0032] Determining a comparison index based on the plurality of forecast data and the plurality of actual data, the comparison index comprising one or more of a root mean square error, a correlation coefficient, and a mean deviation;

[0033] According to the comparison index of each set of candidate meteorological data, priority values ​​of data sources of multiple sets of candidate meteorological data are obtained;

[0034] The first meteorological data is determined from the multiple groups of candidate meteorological data according to the priority values ​​of the data sources of the multiple groups of candidate meteorological data.

[0035] In this embodiment, if the user preference includes sensitivity to errors, a set of candidate meteorological data that meets the user's requirements can be found by calculating a comparison index, thereby improving the accuracy of meteorological product production.

[0036] In a second aspect, the present application provides a device for generating weather forecast information, comprising:

[0037] An acquisition module is used to acquire demand information of target weather forecast information, wherein the demand information includes a target forecast date, a target time scale, and a target spatial scale;

[0038] a determination module, configured to determine, based on the demand information, whether a target production line path available for generating the target weather forecast information exists in a unified catalog, the unified catalog including production line paths corresponding to multiple target weather elements under multiple production dates, each target weather element corresponding to multiple production line paths, the multiple production line paths corresponding to different time scales and / or spatial scales, the target weather elements being the weather elements required for the target weather forecast information;

[0039] A generation module is used to obtain target meteorological data according to the target production line path if there is a target production line path available for generating the target meteorological forecast information in the unified directory, and generate the target meteorological forecast information according to the target meteorological data.

[0040] In a possible implementation, the determination module is specifically configured to:

[0041] determining, based on the target forecast date, whether a production line path for the target meteorological element under the multiple production dates includes a production line path for the first production date, the first production date being the date closest to the target forecast date;

[0042] If so, based on the target time scale and the target spatial scale, determine whether there is a production line path corresponding to the target time scale and the target spatial scale in the production line path of the first production date as the target production line path.

[0043] In a possible implementation, the demand information further includes target meteorological elements and user preferences; the device further includes a processing module, the processing module being configured to:

[0044] Obtain meteorological data of various meteorological elements on the current production date. The meteorological data of each meteorological element includes meteorological data at multiple time scales and multiple spatial scales.

[0045] Storing meteorological data of the plurality of meteorological elements and generating an actual storage path of the meteorological data of each meteorological element;

[0046] Determining meteorological data of the target meteorological element from the meteorological data of the multiple meteorological elements, and determining target meteorological data corresponding to the target spatial scale and the target time scale from the meteorological data of the target meteorological element;

[0047] According to the actual storage path of the target meteorological data, a soft link is created for the target meteorological data in the unified directory to generate a production line path corresponding to the target meteorological element under the current production date.

[0048] In a possible implementation, the processing module is further configured to:

[0049] At preset time intervals, monitoring operations are performed on production line paths corresponding to multiple target meteorological elements under multiple production dates in the unified catalog to obtain monitoring results, wherein the monitoring operations include: determining whether meteorological data under each production line path is readable and whether the size occupied by the meteorological data under each production line path is accurate;

[0050] If the monitoring result indicates that any production line path has an abnormality, the unified directory is updated.

[0051] In one possible implementation, there are multiple target meteorological variables, and the target meteorological data includes candidate meteorological data corresponding to each target meteorological variable. For any target meteorological variable, there are multiple groups of candidate meteorological data for the target meteorological variable, and each group of candidate meteorological data has a different data source. The demand information also includes user preferences, and the user preferences include the source of the target data and / or sensitivity to error.

[0052] The processing module is specifically used to:

[0053] For any target meteorological variable, based on the user preference, the first meteorological data is determined from multiple groups of candidate meteorological data of the target meteorological variable; and based on the actual storage path of the first meteorological data, a soft link is created for the first meteorological data under the unified directory to generate the production line path corresponding to the first meteorological data under the current production date.

[0054] In a possible implementation, the user preference includes sensitivity to errors, and the processing module is specifically configured to:

[0055] Determining that the data source of each set of candidate meteorological data is historical meteorological data within a first preset time period;

[0056] Acquiring historical meteorological forecast information generated by the historical meteorological data, wherein the historical meteorological forecast information indicates a plurality of forecast data, and the first preset time period is a time period before the current production date;

[0057] Acquiring a variety of live data within the first preset time period;

[0058] Determining a comparison index based on the plurality of forecast data and the plurality of actual data, the comparison index comprising one or more of a root mean square error, a correlation coefficient, and a mean deviation;

[0059] According to the comparison index of each set of candidate meteorological data, priority values ​​of data sources of multiple sets of candidate meteorological data are obtained;

[0060] The first meteorological data is determined from the multiple groups of candidate meteorological data according to the priority values ​​of the data sources of the multiple groups of candidate meteorological data.

[0061] In a third aspect, the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0062] The memory stores computer-executable instructions;

[0063] The processor executes the computer-executable instructions stored in the memory to implement the method according to the first aspect.

[0064] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a computer, they are used to implement the method described in the first aspect.

[0065] The computer-readable storage medium provided in the embodiment of the present application can execute the technical solutions in the above method embodiments, and its beneficial effects are similar and will not be repeated here.

[0066] In a fifth aspect, the present application provides a computer program product, comprising a computer program, which, when executed by a computer, is used to implement the method described in the first aspect.

[0067] The computer program product provided in the embodiment of the present application can execute the technical solutions in the above method embodiments, and its beneficial effects are similar, which will not be described in detail here.

[0068] The method, device, equipment, medium and product for generating weather forecast information provided by the present application can, when generating target weather forecast information based on demand information, determine the target production line path available for the target weather forecast information in a unified directory according to the required information, thereby obtaining target weather data according to the target production line path, and generating target weather forecast information according to the target weather data. Among them, the unified directory automatically collects production line paths corresponding to multiple target weather elements under multiple production dates, each target weather element corresponds to multiple production line paths, and the multiple production line paths correspond to different time scales and spatial scales, and the target weather element is the weather element required for the target weather forecast information, so that when responding to multiple demands for weather forecast information for different time scales, different weather elements, etc., the target weather data can be obtained based on the unified directory, thereby improving the flexibility of weather forecast information generation. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0070] Figure 1 A schematic diagram of a flow chart of a method for generating weather forecast information provided in an embodiment of the present application;

[0071] Figure 2 A flowchart of another method for generating weather forecast information provided in an embodiment of the present application;

[0072] Figure 3 A flowchart of another method for generating weather forecast information provided in an embodiment of the present application;

[0073] Figure 4 This is a schematic diagram of the structure of a device for generating weather forecast information provided by an embodiment of the present application;

[0074] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0075] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0076] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0077] Due to the different physical properties of different meteorological elements and their different impacts on forecast accuracy, the meteorological data of each meteorological element can be produced through different numerical models, so that the meteorological data of each meteorological element can be obtained on independent production lines.

[0078] To meet diverse needs, weather forecast production requires integrating meteorological data from multiple numerical models. However, in related technologies, weather forecast generation systems typically rely on a single numerical model. This makes it difficult for production systems to integrate meteorological data from multiple numerical models, resulting in limited flexibility when producing forecasts.

[0079] Furthermore, weather forecast information can have a short-term (e.g., 1-3 days), medium-term (e.g., 3-10 days), extended (e.g., 10-30 days), or long-term (e.g., more than 30 days) timescale. Weather forecast information at different timescales also has different requirements for the source of weather data and how it is processed. Consequently, the production lines for weather data required for weather forecast information corresponding to each timescale are relatively independent. Weather forecast information at different timescales often uses weather data generated by different numerical models. Current weather forecast information generation systems are unable to switch between weather data required for weather forecast information at different timescales. This results in manual configuration required when generating weather forecast information across timescales, increasing operational complexity and the time required to generate weather forecast information.

[0080] Furthermore, the rigidity of current weather forecast generation systems is primarily reflected in complex production processes, which complicates data extraction during forecast production. Data processing methods for different meteorological elements and timescales vary. While weather forecast generation systems are capable of processing these data separately, in practice, complex data rules and widely distributed data sources when acquiring meteorological data from different numerical models make data extraction difficult and rule management complex, hindering the efficient production of subsequent forecast information.

[0081] Moreover, in related technologies, after weather forecast information is generated, its distribution can be achieved through platforms such as the File Transfer Protocol (FTP), but there is a lack of effective monitoring of the distribution process. For example, it is impossible to monitor the integrity of the distributed data in real time, nor is it possible to determine whether the distribution process is successful in a timely manner. In addition, the efficiency and timeliness of distribution cannot be effectively monitored and recorded, making it difficult to track and analyze the distribution status when problems arise. More importantly, when distribution fails, the existing generation system cannot automatically restart the distribution, resulting in the need for manual intervention for troubleshooting and retransmission. This not only reduces distribution efficiency, but also easily causes delays, failing to meet the needs of efficient and accurate data transmission.

[0082] Therefore, the present application provides a method for generating weather forecast information. When generating target weather forecast information based on demand information, the target production line path available for the target weather forecast information can be determined in a unified directory according to the demand information, thereby obtaining target weather data according to the target production line path and generating target weather forecast information according to the target weather data. Among them, the unified directory automatically collects production line paths corresponding to multiple target weather elements under multiple production dates, each target weather element corresponds to multiple production line paths, and the multiple production line paths correspond to different time scales and spatial scales. The target weather element is the weather element required for the target weather forecast information. When responding to various demands for weather forecast information for different time scales, different weather elements, etc., the target weather data can be obtained based on the unified directory, thereby improving the flexibility of weather forecast information generation.

[0083] In an embodiment of the present application, weather forecast information may also be referred to as a meteorological product. Meteorological forecast information may be, for example, a weather forecast report, a climate simulation report, and a disaster warning report. Taking the weather forecast report as an example, the weather forecast report may include a single-point weather forecast report or a grid weather forecast report. A single-point weather forecast report refers to a weather forecast report for a specific coordinate point, such as a weather forecast report at 30 degrees north latitude and 110 degrees east longitude. A grid weather forecast report refers to a weather forecast report for a certain range, such as a weather forecast report within the range of 30-40 degrees north latitude and 110-120 degrees east longitude.

[0084] It can be understood that the above-mentioned weather forecast information can be in the form of a data product or a non-data product (such as a picture), and this application does not impose any restrictions on this.

[0085] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0086] Figure 1 The present invention provides a flow chart of a method for generating weather forecast information. The method can be executed by a weather forecast information generating device, which can be implemented by a computer program; it can also be implemented by a medium storing relevant computer programs, such as a USB flash drive and / or a CD, or it can also be implemented by a physical device integrated or installed with relevant computer programs, such as a chip or electronic device. The electronic device can be a server, a server cluster, a terminal device such as a computer, etc. The following description takes the server as an example. Figure 1 As shown, the method may include the following steps:

[0087] S101. Obtaining target weather forecast information requirement information, where the requirement information includes a target forecast date, a target time scale, and a target spatial scale.

[0088] In one possible implementation, the user can express the key information of the target weather forecast information in natural language, such as "I need the weather forecast for a certain area in the next 5 days, with a spatial scale of 0.1 degrees". The server can identify the key information through a large language model and obtain the required information.

[0089] The target time scale refers to the forecast time range of the target weather forecast information. The target time scale can be short-term (e.g., 1-3 days), medium-term (e.g., 3-10 days), extended (e.g., 10-30 days), or long-term (e.g., more than 30 days). Based on the key information "next 3 days," the target time scale can be determined to be medium-term.

[0090] The target forecast date refers to the forecast date of the target weather forecast information. Based on the above key information "next 3 days", the target forecast date can be determined according to the date on which the user inputs the key information.

[0091] The target spatial scale can be understood as grid accuracy. It divides the forecast area into a grid of longitude and latitude, with each grid representing a basic forecast unit. The smaller the grid (i.e., higher the resolution), the better the target forecast system's ability to capture local weather phenomena. Typically, the target spatial scale can be 0.1° or 0.01°, where 0.1° indicates that each grid cell spans 0.1 degrees in both latitude and longitude, and 0.01° indicates that each grid cell spans 0.01 degrees in both latitude and longitude. Since each degree of latitude corresponds to approximately 111 kilometers (at mid-latitudes), a 0.1° grid size covers an area of ​​approximately 11.1 km × 11.1 km, and a 0.01° grid size covers an area of ​​approximately 1.11 km × 1.11 km. The target spatial scale allows users to indicate the accuracy of the meteorological data required to produce the target forecast (the smaller the target spatial scale, the higher the meteorological data accuracy).

[0092] S102: Determine, based on the demand information, whether there is a target production line path in the unified directory that is available for generating target weather forecast information.

[0093] The server can determine whether there is a target production line path available for generating target weather forecast information in the unified directory based on the demand information. If there is a target production line path available for generating target weather forecast information in the unified directory, S103 is executed.

[0094] The unified catalog includes production line paths corresponding to multiple target meteorological elements across multiple production dates. Each target meteorological element corresponds to multiple production line paths, each corresponding to different temporal and / or spatial scales. The target meteorological elements are the meteorological elements required for the target meteorological forecast information. In other words, the unified path aggregates production line paths corresponding to multiple target meteorological elements across multiple production dates, facilitating direct access to the corresponding meteorological data when generating the target meteorological forecast information.

[0095] It should be noted that, taking any production line path a as an example, the production line path 1 corresponds to the time scale 1 and the spatial scale 1, and the meteorological data indicated by the production line path a is used to generate the meteorological forecast information corresponding to the time scale 1 and the spatial scale 1. That is to say, when generating the meteorological forecast information corresponding to the time scale 1 and the spatial scale 1, it can be generated based on the meteorological data indicated by the production line path a.

[0096] For example, and for ease of understanding, the unified directory can refer to Table 1.

[0097] As can be seen from Table 1, for any target meteorological element, there can be multiple production line paths at the same time scale and spatial scale. It can be understood that the meteorological data indicated by each production line path can come from different data sources. The data source can be, for example, a numerical model, such as the Weather Research and Forecasting Model (WRF), or other meteorological models, such as a meteorological model that generates meteorological data on a spherical cube grid (for example, it can divide the world into six regions, effectively solving the theoretical bottleneck of the convergence of the North and South Poles, and through a more uniform grid distribution, it can maximize the super computing power of modern large-scale parallel computing supercomputers).

[0098] It is understood that the unified directory is in a state of real-time updating. For example, the server can monitor the production line paths corresponding to multiple target meteorological elements under multiple production dates in the unified directory at preset time intervals to determine whether each production line path is available. For example, when a new production line path appears in the target meteorological element "temperature", it is necessary to add the production line path in the unified directory; for example, when production line path 1 in the target meteorological element "temperature" is unavailable (for example, the meteorological data corresponding to production line path 1 is damaged), it is necessary to delete production line path 1 from the unified directory.

[0099] Table 1

[0100]

[0101] S103: Acquire target meteorological data according to the target production line path, and generate target meteorological forecast information according to the target meteorological data.

[0102] After determining the target production line path, the server can trigger the target weather forecast information production process, that is, the server can obtain target weather data according to the target production line path, and generate target weather forecast information based on the target weather data.

[0103] In one possible implementation, after the server generates the target weather forecast information, it can obtain the user's File Transfer Protocol (FTP) account and password information according to the user corresponding to the target weather forecast information, and automatically distribute the target weather forecast information through the FTP server based on the account and password information.

[0104] For example, the server can obtain information such as the FTP account and password corresponding to the target weather forecast information through a distribution configuration file. The distribution configuration file includes information such as the FTP account and password of multiple users. The server can automatically publish the target weather forecast information to the user based on the FTP account and password of the user corresponding to the target weather forecast information. This system realizes the automatic distribution of target weather forecast information through the FTP server, reducing the reliance on manual operations. Compared with the lack of monitoring and low efficiency of the distribution process in the prior art, the present application can monitor the integrity of the distribution of target weather forecast information and the success rate of the distribution process in real time, ensuring that the target weather forecast information is delivered to the user end in a timely and accurate manner. This improvement improves overall work efficiency, ensures the accuracy of data transmission, and meets the needs of efficient and accurate data transmission.

[0105] In this embodiment, when generating target weather forecast information based on demand information, the target production line paths available for the target weather forecast information can be determined from a unified directory based on the demand information, thereby acquiring target weather data based on the target production line paths and generating target weather forecast information based on the target weather data. The unified directory automatically aggregates production line paths corresponding to multiple target weather elements under multiple production dates, with each target weather element corresponding to multiple production line paths. The multiple production line paths correspond to different time and spatial scales, and the target weather elements are the weather elements required for the target weather forecast information. This allows target weather data to be acquired based on the unified directory when addressing various demands for weather forecast information, such as those for different time scales and different weather elements, thereby enhancing the flexibility of weather forecast information generation.

[0106] In one possible implementation, when the target weather forecast information is generated, the production line paths in the unified directory are also in a real-time updating state (for example, when there may be an abnormality in the meteorological data corresponding to the production line path, the production line path is in an updating state). The server can determine whether there is a target production line path required for the target weather forecast information in the generated paths collected in the unified directory.

[0107] Next, it is described how the server determines whether there is a target production line path available for generating target weather forecast information in the unified directory.

[0108] The server determines, based on the target forecast date, whether there is a production line path for the first production date among the production line paths of the target meteorological elements under multiple production dates, where the first production date is the date closest to the target forecast date.

[0109] It can be understood that the target forecast date is a date that has not yet occurred, that is, a future date, and multiple production dates are historical dates. The first production date is the date closest to the target forecast date. Using the meteorological data of the production line path on the date closest to the target forecast date can improve the accuracy of the target meteorological forecast information.

[0110] In one possible implementation, the first production date may be a specific date. For example, the target forecast date is January 15 to January 20. For example, the date closest to January 15 among multiple production dates is January 1, then the first production date is January 1.

[0111] In a possible implementation, the first production date may be a time range. Taking the above example, the first production date may be, for example, January 1 to January 3.

[0112] It should be noted that the above examples are based on months and days. The production date can also be specified to the time, such as 22:21 on January 1, to obtain more detailed meteorological data. This application does not impose any restrictions on this.

[0113] If the production line path of the target meteorological elements under multiple production dates does not include the production line path for the first production date, for example, a prompt message can be output to prompt the user that the production line path for the first production date does not exist and whether the first production date needs to be changed. If an instruction to change the first production date is received, the first production date can be determined within a preset time range before the target forecast date.

[0114] If there is a production line path for the first production date among the production line paths of the target meteorological elements under multiple production dates, the server can determine whether there is a production line path corresponding to the target time scale and target spatial scale in the production line path of the first production date as the target production line path based on the target time scale and target spatial scale.

[0115] Taking Table 1 as an example, if the target time scale is short-term, the target spatial scale is scale 1, the first production date is date 1, and the target meteorological variables are temperature and humidity, the production line paths for the first production date include path 1, path 2, path 3, path 4, path 5, path 6, etc. The server can determine, based on the target time scale and target spatial scale, that the target production line path includes path 1 corresponding to "temperature" and path 4 corresponding to "humidity" among these production line paths.

[0116] In this embodiment, a target forecast date is used to determine whether a production line path for a first production date exists among the production line paths for target meteorological elements for multiple production dates. The first production date is the date closest to the target forecast date. If so, based on the target time scale and target spatial scale, a determination can be made as to whether a production line path corresponding to the target time scale and target spatial scale exists among the production line paths for the first production date, thereby determining the target production line path. The target production line path can then be used to obtain the target meteorological data required for producing the target meteorological product.

[0117] Next, the production line paths corresponding to various target meteorological elements under multiple production dates are explained in a unified path.

[0118] Figure 2 This is a flow chart of another method for generating weather forecast information provided in an embodiment of the present application. This method can be executed by a device for generating weather forecast information, which can be implemented by a computer program; it can also be implemented by a medium storing relevant computer programs, such as a USB flash drive and / or a CD, or it can also be implemented by a physical device integrated or installed with relevant computer programs, such as a chip or electronic device. The electronic device can be a server, a server cluster, a terminal device such as a computer, etc. The following description will take a server as an example. Figure 2 As shown, the method may include the following steps:

[0119] S201. Obtain meteorological data of multiple meteorological elements on the current production date, where the meteorological data of each meteorological element includes meteorological data at multiple time scales and multiple spatial scales.

[0120] For any time scale and spatial scale, the meteorological data at that time scale and spatial scale may include multiple meteorological data. For example, in Table 2, the meteorological element "temperature" has meteorological data 1 and meteorological data 2 at the time scale "short-term" and spatial scale "scale 1". The data sources of meteorological data 1 and meteorological data 2 are different. For example, meteorological data 1 is generated by WRF, and meteorological data 2 is generated by other meteorological models.

[0121] S202: Meteorological data of various meteorological elements are stored, and an actual storage path of the meteorological data of each meteorological element is generated.

[0122] For example, the meteorological data of various meteorological elements and their actual storage paths are shown in Table 2.

[0123] Table 2

[0124]

[0125] It can be understood that meteorological data 1 to meteorological data 12 represent multiple groups of meteorological data. Taking temperature as an example, each group of meteorological data includes temperature values ​​of different pressure layers (or altitude layers), and the temperature index of each pressure layer (or altitude layer) may include temperature values ​​of multiple latitude and longitude grids in multiple forecast areas (that is, each latitude and longitude grid corresponds to a temperature index), wherein the size of each latitude and longitude grid is related to scale 1 (for example, if scale 1 is 0.1°, then the latitude and longitude grid size covers an area of ​​approximately 11.1 km × 11.1 km).

[0126] S203: Determine meteorological data of a target meteorological element from the meteorological data of the multiple meteorological elements, and determine target meteorological data corresponding to a target spatial scale and a target time scale from the meteorological data of the target meteorological element.

[0127] The server can determine the target meteorological element's meteorological data from the meteorological data of multiple meteorological elements based on the target meteorological forecast information requirements. For example, if the target meteorological elements include temperature and humidity, the target spatial scale is scale 1, and the target temporal scale is short-term, the server can determine the target meteorological data corresponding to "scale 1 and short-term" from the temperature meteorological data, and determine the target meteorological data corresponding to "scale 1 and short-term" from the humidity meteorological data. Taking Table 2 as an example, the target meteorological data includes meteorological data 1, meteorological data 2, and meteorological data 5.

[0128] That is to say, if there are multiple target meteorological variables, then the target meteorological data includes candidate meteorological data corresponding to each target meteorological variable. Taking the above example, the target meteorological data includes candidate meteorological data corresponding to temperature (i.e., meteorological data 1 and meteorological data 2) and candidate meteorological data corresponding to humidity (i.e., meteorological data 5).

[0129] S204: Create a soft link for the target meteorological data in a unified directory according to the actual storage path of the target meteorological data, so as to generate a production line path corresponding to the target meteorological element under the current production date.

[0130] The server can establish a soft link for the target meteorological data in a unified directory according to the actual storage path of the target meteorological data, so as to generate a production line path corresponding to the target meteorological element under the current production date.

[0131] Since there can be multiple target meteorological variables, the target meteorological data includes candidate meteorological data corresponding to each target meteorological variable, and each target meteorological variable can correspond to multiple groups of candidate meteorological data, and each group of candidate meteorological data has a different data source.

[0132] It can be understood that after creating a soft link to the target meteorological data under the unified directory, the production line path of the target meteorological data under the unified directory can point to the actual storage path of the target meteorological data. When accessing the production line path, the actual storage path is actually accessed. Deleting the production line path under the unified directory will not affect the original target meteorological data. Deleting the original target meteorological data will cause the production line path under the unified directory to become invalid.

[0133] Exemplarily, the server may use a command to create a soft link to establish the soft link.

[0134] exist Figure 2 In the corresponding embodiment, by storing meteorological data for multiple meteorological elements produced on each production date and then soft-linking the meteorological data for the target meteorological element to a unified directory, it is convenient to directly find the target meteorological data in the unified directory when generating target forecast information. This provides a unified interface for subsequent meteorological forecast information production, reduces the complexity of meteorological forecast information production, and improves the flexibility of meteorological forecast information production. Compared with the existing single data source management method, this application significantly improves overall production efficiency.

[0135] In one possible implementation, the server can establish soft links to all candidate meteorological data in the target meteorological data under a unified directory. In this case, for the target meteorological variable for which there are multiple sets of candidate meteorological data, when generating the target meteorological forecast information, any set of candidate meteorological data can be determined from the multiple sets of candidate meteorological data to generate the target meteorological forecast information.

[0136] In one possible implementation, the server may monitor the production line path of the target meteorological elements under the unified directory to avoid interruption of target meteorological product production due to unavailability of target meteorological data.

[0137] Specifically, the server can monitor production line paths corresponding to various target meteorological factors for multiple production dates in the unified directory at preset intervals, obtaining monitoring results. The monitoring operations include determining whether the meteorological data for each production line path is readable and whether the size occupied by the meteorological data for each production line path is accurate. If the monitoring results indicate that any production line path is abnormal, the unified directory is updated.

[0138] For example, if there is an abnormality in any production line path, the server can delete the production line path under the unified directory; or re-acquire the meteorological data under the production line path. After obtaining the meteorological data, it is determined that the meteorological data is readable and the size of the storage space occupied by the meteorological data is accurate, and then a soft link to the meteorological data can be established under the unified directory.

[0139] In a possible implementation, for a target meteorological variable with multiple sets of candidate meteorological data, the server may determine a set of candidate meteorological data that meets the user's requirements in the following manner:

[0140] The demand information corresponding to the target meteorological forecast information also includes user preferences, which include the source of target data and / or sensitivity to errors, etc. For any target meteorological variable, the first meteorological data is determined from multiple groups of candidate meteorological data of the target meteorological variable based on the user preferences; and based on the actual storage path of the first meteorological data, a soft link is created for the first meteorological data in a unified directory to generate the production line path corresponding to the first meteorological data under the current production date.

[0141] The target data source can be a user-specified meteorological data source, such as WRF. If the user preference includes "error-sensitive," this indicates that the target weather forecast information is a product that is sensitive to errors. Furthermore, the user can indicate that the target weather forecast is sensitive to errors in a specific meteorological element, such as temperature. Based on the user's preferences, the server can determine a set of candidate weather data that meets the user's requirements, establish soft links for these candidate weather data in a unified path, and directly use them when generating the target weather forecast information.

[0142] Next, the server determines the first meteorological data from multiple sets of candidate meteorological data according to the user preference.

[0143] The server may determine that the data source of each set of candidate meteorological data is historical meteorological data within a first preset time period;

[0144] And obtain historical meteorological forecast information generated by historical meteorological data, the historical meteorological forecast information indicates a variety of forecast data, and the first preset time period is a time period before the current production date.

[0145] The various forecast data may include, for example, forecast values ​​of meteorological elements such as temperature, humidity, etc. The first preset time period may be a historical time period, for example, a time period before the first production date.

[0146] The server can then obtain a variety of real-time data within the first preset time period. It can be understood that the meteorological elements corresponding to the various forecast data and the various real-time data are the same. For example, the various real-time data can include real-time values ​​of meteorological elements such as temperature and humidity.

[0147] Based on multiple forecast data and multiple actual data, a comparison index is determined. The comparison index includes one or more of the following: root mean square error (RMSE), correlation coefficient, and mean bias. The root mean square error (RMSE) measures the absolute deviation between the forecast data and the actual data, the correlation coefficient (CORR) reflects the linear correlation between the forecast data and the actual data, and the mean bias reflects the direction and magnitude of the overall deviation between the forecast data and the actual data, that is, the degree to which historical weather forecast information is systematically over- or under-biased.

[0148] In a possible implementation, the server may calculate the root mean square error, correlation coefficient, and average deviation for each meteorological data in the forecast data and the actual data, which may be determined by the following formula:

[0149]

[0150] Among them, Si is the i-th predicted value, Oi is the i-th actual value, and n is the number of samples.

[0151]

[0152] Among them, Si is the i-th predicted value, Oi is the i-th actual value, and n is the number of samples.

[0153]

[0154] Among them, Si is the i-th forecast value, Oi is the i-th actual value, n is the number of samples, is the mean of n forecast values, is the mean of n actual values.

[0155] In one possible implementation, if the user preferences indicate that the target weather forecast is sensitive to the error of a certain meteorological element, such as the error of temperature, then the server can calculate the root mean square error, correlation coefficient and average deviation only for the temperature in the forecast data and the actual data.

[0156] After calculating one or more of the root mean square error, correlation coefficient, and mean deviation, the server may determine a priority value for the data sources of the multiple sets of candidate meteorological data based on the comparison index of each set of candidate meteorological data. The server may then determine the first meteorological data from the multiple sets of candidate meteorological data based on the priority values ​​for the data sources of the multiple sets of candidate meteorological data.

[0157] For example, for any set of candidate meteorological data, if the server calculates the root mean square error, correlation coefficient, and mean deviation, the root mean square error, correlation coefficient, and mean deviation can be standardized to values ​​between 0 and 1, and then the sum of the standardized values ​​of the root mean square error, correlation coefficient, and mean deviation can be calculated to obtain the priority value of the set of candidate meteorological data. Then, based on the priority values ​​of the data sources of the multiple sets of candidate meteorological data, the first meteorological data can be determined from the multiple sets of candidate meteorological data. For example, the candidate meteorological data with the highest priority value can be determined as the first meteorological data.

[0158] In one possible implementation, after the root mean square error, correlation coefficient, and mean deviation are standardized into values ​​in the range of 0-1, the weighted total score can be calculated according to the weight of each comparison indicator (e.g., RMSE: 40%, CORR: 30%, BIAS: 30%) to obtain the priority value of each group of candidate meteorological data.

[0159] In this embodiment, if the user preference includes sensitivity to errors, a set of candidate meteorological data that meets the user's requirements can be found by calculating a comparison index, thereby improving the accuracy of meteorological product production.

[0160] In a possible implementation, before calculating the root mean square error, the correlation coefficient, and the mean deviation, the server may preprocess the various live data within the first preset time period, such as removing outliers, to ensure data comparability.

[0161] In one possible implementation, when the demand information of the target weather forecast information changes, for example, the target weather variables, user preferences and other information in the demand information that the server can obtain changes, the server can update the production line path in the unified directory according to the changed demand information (including addition, deletion, etc.), thereby achieving seamless switching without affecting the production of the target weather forecast information.

[0162] Figure 3 A flow chart of another method for generating weather forecast information provided in an embodiment of the present application is shown as follows: Figure 3As shown, the method can be executed by a device for generating weather forecast information, which can be implemented by a computer program; it can also be implemented by a medium storing a relevant computer program, such as a USB flash drive and / or a CD, or it can also be implemented by a physical device integrated or installed with a relevant computer program, such as a chip or electronic device. The electronic device can be a server, a server cluster, a terminal device such as a computer, etc. The following description takes a server as an example. Figure 3 As shown, the method may include the following steps:

[0163] S301. Obtain target weather forecast information requirement information, where the requirement information includes a target forecast date, a target time scale, and a target spatial scale.

[0164] S302: Acquire meteorological data of multiple meteorological elements on the current production date, where the meteorological data of each meteorological element includes meteorological data at multiple time scales and multiple spatial scales.

[0165] S303: Store meteorological data of multiple meteorological elements, and generate an actual storage path of the meteorological data of each meteorological element.

[0166] S304: Determine meteorological data of a target meteorological element from the meteorological data of the multiple meteorological elements, and determine target meteorological data corresponding to a target spatial scale and a target time scale from the meteorological data of the target meteorological element.

[0167] S305: For any target meteorological variable, determine that the data source of each set of candidate meteorological data is historical meteorological data within a first preset time period;

[0168] S306: Acquire historical meteorological forecast information generated by historical meteorological data, where the historical meteorological forecast information indicates a variety of forecast data, and the first preset time period is a time period before the current production date.

[0169] S307: Acquire a variety of live data within a first preset time period.

[0170] S308. Determine a comparison index based on the multiple forecast data and the multiple actual data. The comparison index includes one or more of a root mean square error, a correlation coefficient, and a mean deviation.

[0171] S309: Obtain priority values ​​of data sources of multiple groups of candidate meteorological data according to the comparison index of each group of candidate meteorological data.

[0172] S310 . Determine first meteorological data from the multiple groups of candidate meteorological data according to the priority values ​​of the data sources of the multiple groups of candidate meteorological data.

[0173] S311. Create a soft link for the target meteorological data in a unified directory according to the actual storage path of the first meteorological data, so as to generate a production line path corresponding to the target meteorological element under the current production date.

[0174] S312. Perform monitoring operations on production line paths corresponding to multiple target meteorological elements under multiple production dates in the unified directory at preset time intervals to obtain monitoring results.

[0175] The monitoring operation includes determining whether the meteorological data under each production line path is readable and whether the size occupied by the meteorological data under each production line path is accurate.

[0176] S313. If the monitoring result indicates that any production line path is abnormal, the unified directory is updated.

[0177] S314. Determine, based on the target forecast date, whether there is a production line path for the first production date among the production line paths of the target meteorological elements under multiple production dates, where the first production date is the date closest to the target forecast date.

[0178] If so, execute S315.

[0179] S315 . Determine, based on the target time scale and the target spatial scale, whether there is a production line path corresponding to the target time scale and the target spatial scale in the production line paths of the first production date as the target production line path.

[0180] If so, execute S316.

[0181] S316. Acquire target meteorological data according to the target production line path, and generate target meteorological forecast information according to the target meteorological data.

[0182] The specific implementation method and technical effects of this embodiment are similar to those of the above embodiment and will not be repeated here.

[0183] Figure 4 This is a schematic diagram of the structure of a device for generating weather forecast information provided by an embodiment of the present application. Figure 4 As shown, the weather forecast information generating device 40 includes: an acquisition module 401 , a determination module 402 and a generation module 403 .

[0184] The acquisition module 401 is used to acquire the demand information of the target weather forecast information, where the demand information includes the target forecast date, target time scale and target spatial scale.

[0185] Determination module 402 is used to determine whether there is a target production line path available for generating target weather forecast information in the unified directory based on demand information. The unified directory includes production line paths corresponding to multiple target weather elements under multiple production dates. Each target weather element corresponds to multiple production line paths. The time scales and / or spatial scales corresponding to the multiple production line paths are different. The target weather elements are the weather elements required for the target weather forecast information.

[0186] The generating module 403 is configured to obtain target meteorological data according to the target production line path if there is a target production line path available for generating target meteorological forecast information in the unified directory, and generate target meteorological forecast information according to the target meteorological data.

[0187] In a possible implementation, the determining module 402 is specifically configured to:

[0188] According to the target forecast date, determine whether there is a production line path for the first production date among the production line paths of the target meteorological elements under multiple production dates, and the first production date is the date closest to the target forecast date.

[0189] If so, according to the target time scale and the target space scale, determine whether there is a production line path corresponding to the target time scale and the target space scale in the production line path of the first production date as the target production line path.

[0190] In a possible implementation, the demand information further includes target meteorological elements and user preferences; the apparatus further includes a processing module 404, which is configured to:

[0191] Obtain meteorological data of multiple meteorological elements on the current production date. The meteorological data of each meteorological element includes meteorological data at multiple time scales and multiple spatial scales.

[0192] The meteorological data of various meteorological elements are stored, and the actual storage path of the meteorological data of each meteorological element is generated.

[0193] The meteorological data of the target meteorological element is determined among the meteorological data of the multiple meteorological elements, and the target meteorological data corresponding to the target spatial scale and the target time scale are determined among the meteorological data of the target meteorological element.

[0194] According to the actual storage path of the target meteorological data, a soft link is created for the target meteorological data in a unified directory to generate the production line path corresponding to the target meteorological element under the current production date.

[0195] In a possible implementation, the processing module 404 is further configured to:

[0196] At preset time intervals, monitoring operations are performed on the production line paths corresponding to multiple target meteorological elements under multiple production dates in the unified directory to obtain monitoring results. The monitoring operations include: determining whether the meteorological data under each production line path is readable and whether the size occupied by the meteorological data under each production line path is accurate.

[0197] If the monitoring results indicate that there is an anomaly in any production line path, the unified directory will be updated.

[0198] In one possible implementation, there are multiple target meteorological variables, and the target meteorological data includes candidate meteorological data corresponding to each target meteorological variable. For any target meteorological variable, there are multiple groups of candidate meteorological data for the target meteorological variable, and each group of candidate meteorological data has a different data source. The demand information also includes user preferences, and the user preferences include the source of the target data and / or sensitivity to error.

[0199] The processing module 404 is specifically configured to:

[0200] For any target meteorological variable, the first meteorological data is determined from multiple sets of candidate meteorological data of the target meteorological variable according to user preference; and according to the actual storage path of the first meteorological data, a soft link is created for the first meteorological data in a unified directory to generate the production line path corresponding to the first meteorological data under the current production date.

[0201] In a possible implementation, the user preference includes sensitivity to errors, and the processing module 404 is specifically configured to:

[0202] The data source of each set of candidate meteorological data is determined to be historical meteorological data within a first preset time period.

[0203] Historical meteorological forecast information generated by historical meteorological data is obtained, where the historical meteorological forecast information indicates a variety of forecast data, and a first preset time period is a time period before the current production date.

[0204] A variety of live data within a first preset time period is acquired.

[0205] A comparison index is determined based on a plurality of forecast data and a plurality of actual data. The comparison index includes one or more of a root mean square error, a correlation coefficient and a mean deviation.

[0206] According to the comparison index of each set of candidate meteorological data, priority values ​​of data sources of the multiple sets of candidate meteorological data are obtained.

[0207] The first meteorological data is determined from the multiple groups of candidate meteorological data according to the priority values ​​of the data sources of the multiple groups of candidate meteorological data.

[0208] The device of this embodiment can be used to execute the technical solution of the above method embodiment. The specific implementation method and technical effects are similar and will not be repeated here.

[0209] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown in FIG. Figure 5 As shown, the electronic device 50 may include: at least one processor 501 and a memory 702 .

[0210] The memory 502 is used to store programs. Specifically, the programs may include program codes, and the program codes include computer-executable instructions.

[0211] The memory 502 may include a random access memory (RAM), and may also include a non-volatile memory (Non-volatile Memory), such as at least one disk memory.

[0212] The processor 501 is configured to execute computer-executable instructions stored in the memory 502 to implement the method described in the aforementioned method embodiment. The processor 501 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0213] Optionally, the electronic device 50 may further include a communication interface 503. In a specific implementation, if the communication interface 503, the memory 502, and the processor 501 are implemented independently, the communication interface 503, the memory 502, and the processor 501 may be interconnected via a bus and communicate with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be classified as address buses, data buses, control buses, etc., but this does not mean that there is only one bus or only one type of bus.

[0214] Optionally, in a specific implementation, if the communication interface 503, the memory 502 and the processor 501 are integrated on a chip, the communication interface 503, the memory 502 and the processor 501 can complete communication through an internal interface.

[0215] The electronic device 50 may be a server, a server cluster, a computer or other terminal device.

[0216] The electronic device of this embodiment can be used to execute the technical solution of the above method embodiment. The specific implementation method and technical effects are similar and will not be repeated here.

[0217] An embodiment of the present application provides a computer-readable storage medium, which may include: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a RAM, a disk or an optical disk, and other media that can store computer-executable instructions. Specifically, the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a computer, the technical solution shown in the above method embodiment is executed. The specific implementation method and technical effect are similar and will not be repeated here.

[0218] An embodiment of the present application provides a computer program product, including a computer program. When the computer program is executed by a computer, the technical solution shown in the above method embodiment is executed. The specific implementation method and technical effect are similar and will not be repeated here.

[0219] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all optional embodiments, and the actions and modules involved are not necessarily required by this application.

[0220] It should be further noted that, although the various steps in the flowchart are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps may be performed in other orders. Moreover, at least a portion of the steps in the flowchart may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily performed at the same time, but may be performed at different times. The execution order of these sub-steps or stages is not necessarily to be performed in sequence, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0221] It should be understood that the above-described device embodiments are merely illustrative, and the device of the present application may also be implemented in other ways. For example, the division of units / modules in the above-described embodiments is merely a logical functional division, and actual implementations may employ other division methods. For example, multiple units, modules, or components may be combined or integrated into another system, or some features may be omitted or not implemented.

[0222] In addition, unless otherwise specified, the functional units / modules in the various embodiments of the present application may be integrated into a single unit / module, each unit / module may exist physically separately, or two or more units / modules may be integrated together. The aforementioned integrated units / modules may be implemented in the form of hardware or software program modules.

[0223] If the integrated unit / module is implemented in hardware, the hardware may be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor may be any appropriate hardware processor, such as a CPU, a graphics processing unit (GPU), a field programmable gate array (FPGA), a digital signal processing (DSP) chip, and an application-specific integrated circuit (ASIC). Unless otherwise specified, the storage unit may be any appropriate magnetic storage medium or magneto-optical storage medium, such as resistive random access memory (RRAM), dynamic random access memory (DRAM), static random access memory (SRAM), enhanced dynamic random access memory (EDRAM), high-bandwidth memory (HBM), hybrid memory cube (HMC), etc.

[0224] If the integrated unit / module is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes various media that can store program codes, such as USB flash drives, ROM, RAM, mobile hard drives, magnetic disks or optical disks.

[0225] In the above embodiments, the description of each embodiment has its own emphasis. For parts not described in detail in a particular embodiment, please refer to the relevant description of other embodiments. The technical features of the above embodiments can be combined in any way. To keep the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0226] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present application that follow the general principles of the present application and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0227] It should be understood that the present application is not limited to the exact structure described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for generating weather forecast information, characterized in that: include: Obtaining target weather forecast information requirement information, wherein the requirement information includes a target forecast date, a target time scale, and a target spatial scale; Determining, based on the demand information, whether a target production line path available for generating the target weather forecast information exists in a unified catalog, the unified catalog including production line paths corresponding to multiple target weather elements under multiple production dates, each target weather element corresponding to multiple production line paths, the multiple production line paths corresponding to different time scales and / or spatial scales, the target weather elements being the weather elements required for the target weather forecast information; If so, target meteorological data is acquired according to the target production line path, and the target meteorological forecast information is generated according to the target meteorological data.

2. The method according to claim 1, characterized in that Determining, based on the demand information, whether there is a target production line path in the unified directory that is available for generating the target weather forecast information includes: determining, based on the target forecast date, whether there is a production line path for a first production date among the production line paths of the target meteorological element under the multiple production dates, where the first production date is the date closest to the target forecast date; If so, based on the target time scale and the target spatial scale, determine whether there is a production line path corresponding to the target time scale and the target spatial scale in the production line path of the first production date as the target production line path.

3. The method according to claim 1 or 2, characterized in that The demand information also includes target meteorological elements and user preferences; the method further includes: Obtain meteorological data of various meteorological elements on the current production date. The meteorological data of each meteorological element includes meteorological data at multiple time scales and multiple spatial scales. Storing meteorological data of the plurality of meteorological elements and generating an actual storage path of the meteorological data of each meteorological element; Determining meteorological data of the target meteorological element from the meteorological data of the multiple meteorological elements, and determining target meteorological data corresponding to the target spatial scale and the target time scale from the meteorological data of the target meteorological element; According to the actual storage path of the target meteorological data, a soft link is created for the target meteorological data in the unified directory to generate a production line path corresponding to the target meteorological element under the current production date.

4. The method according to claim 3, characterized in that The method further comprises: At preset time intervals, monitoring operations are performed on production line paths corresponding to multiple target meteorological elements under multiple production dates in the unified catalog to obtain monitoring results, wherein the monitoring operations include: determining whether meteorological data under each production line path is readable and whether the size occupied by the meteorological data under each production line path is accurate; If the monitoring result indicates that any production line path has an abnormality, the unified directory is updated.

5. The method according to claim 3 or 4, characterized in that There are multiple target meteorological variables, and the target meteorological data includes candidate meteorological data corresponding to each target meteorological variable. For any target meteorological variable, there are multiple groups of candidate meteorological data for the target meteorological variable, and each group of candidate meteorological data has a different data source. The demand information also includes user preferences, and the user preferences include the source of the target data and / or sensitivity to error; According to the actual storage path of the target meteorological data, a soft link is created for the target meteorological data in the unified directory to generate a production line path corresponding to the target meteorological element under the current production date, including: For any target meteorological variable, determining first meteorological data from multiple groups of candidate meteorological data of the target meteorological variable according to the user preference; And according to the actual storage path of the first meteorological data, a soft link is created for the first meteorological data in the unified directory to generate a production line path corresponding to the first meteorological data under the current production date.

6. The method according to claim 5, characterized in that The user preference includes sensitivity to error, and determining the first meteorological data from multiple sets of candidate meteorological data according to the user preference includes: Determining that the data source of each set of candidate meteorological data is historical meteorological data within a first preset time period; Acquiring historical meteorological forecast information generated by the historical meteorological data, wherein the historical meteorological forecast information indicates a plurality of forecast data, and the first preset time period is a time period before the current production date; Acquiring a variety of live data within the first preset time period; Determining a comparison index based on the plurality of forecast data and the plurality of actual data, the comparison index comprising one or more of a root mean square error, a correlation coefficient, and a mean deviation; According to the comparison index of each set of candidate meteorological data, priority values ​​of data sources of multiple sets of candidate meteorological data are obtained; The first meteorological data is determined from the multiple groups of candidate meteorological data according to the priority values ​​of the data sources of the multiple groups of candidate meteorological data.

7. A device for generating weather forecast information, characterized in that: include: An acquisition module is used to acquire demand information of target weather forecast information, wherein the demand information includes a target forecast date, a target time scale, and a target spatial scale; a determination module, configured to determine, based on the demand information, whether a target production line path available for generating the target weather forecast information exists in a unified catalog, the unified catalog including production line paths corresponding to multiple target weather elements under multiple production dates, each target weather element corresponding to multiple production line paths, the multiple production line paths corresponding to different time scales and / or spatial scales, the target weather elements being the weather elements required for the target weather forecast information; A generation module is used to obtain target meteorological data according to the target production line path if there is a target production line path available for generating the target meteorological forecast information in the unified directory, and generate the target meteorological forecast information according to the target meteorological data.

8. An electronic device, characterized in that: include: a processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 6 when executed by a processor.

10. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 6 when the computer program is executed by a processor.

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