Meteorological fusion observation method, platform, medium and equipment based on radar technology

Abstract

A weather fusion observation method, platform, medium and equipment based on radar technology, relate to the field of weather information digital intelligent technology. The method comprises: receiving a plurality of types of weather data sent by each local radar device; converting each weather data into standard weather data according to a preset standard format block; filtering impurity data in each standard weather data to obtain target weather data; in response to a fusion instruction, fusing at least two target weather data according to the fusion instruction to obtain fusion weather data for weather analysis through the fusion weather data. Through the data fusion of multiple weather equipment, the accuracy of analyzing weather data can be improved by implementing the technical solution provided in the application.

Description

Technical Field

[0001] This application relates to the field of meteorological information and digital intelligence technology, specifically to a meteorological fusion observation method, platform, medium, and equipment based on radar technology. Background Technology

[0002] With the development of technology, the techniques for analyzing and predicting weather conditions have become increasingly sophisticated. People need to understand weather conditions for industrial production and daily travel. The forecasting of local weather conditions by meteorological departments in various regions is becoming increasingly important, thus requiring a precise and rapid weather observation system to complete the real-time observation of weather conditions.

[0003] Currently, meteorological staff in various regions use meteorological equipment to collect single data points for analysis to determine weather conditions. However, weather conditions are usually complex and changeable, and analyzing complex and changeable weather conditions using single meteorological data has the problem of low accuracy. Summary of the Invention

[0004] This application provides a meteorological fusion observation method, platform, electronic device, and storage medium based on radar technology, which helps meteorological staff improve the accuracy of comprehensive analysis of meteorological data.

[0005] Firstly, this application provides a meteorological fusion observation method based on radar technology, including: It receives various types of meteorological data transmitted by radar equipment in different locations; According to the preset standard format block, each meteorological data is converted into standard meteorological data; Impurities in the standard meteorological data are filtered out to obtain the target meteorological data; In response to a fusion command, at least two types of target meteorological data are fused according to the fusion command to obtain fused meteorological data for meteorological analysis.

[0006] By adopting the above technical solution, when analyzing weather conditions, meteorological data collected by multiple radar devices can be converted into standard meteorological data, thereby fusing multiple standard meteorological data to obtain a fusion result; based on the fusion result obtained from the fusion of multiple meteorological data, the accuracy of meteorological data analysis can be further improved.

[0007] Optionally, the preset standard format block includes a common data block and a radial data block, the meteorological data includes first meteorological data and second meteorological data, and the step of converting each of the meteorological data into standard meteorological data according to the preset standard format block includes: Based on the public data block, the first meteorological data is converted into first standard meteorological data, the first meteorological data including identification file data, radar station data and scanning configuration data; Based on the radial data block, the second meteorological data is converted into second standard meteorological data, which includes status data, acquisition time data, and radial data.

[0008] By adopting the above technical solution, after the server receives the meteorological data uploaded by each radar device, it converts the collected meteorological data into standard meteorological data according to the data format standard, thus providing a basic condition for subsequent meteorological data fusion processing.

[0009] Optionally, after converting the meteorological data into standard meteorological data according to a preset format standard, the method further includes: The standard meteorological data is stored in a distributed database, including the Cassandra database.

[0010] By adopting the above technical solutions, distributed databases can distribute data across multiple nodes, facilitating the persistent storage and retrieval of standard meteorological data.

[0011] Optionally, the step of filtering the standard meteorological data to obtain the target meteorological data includes: The standard meteorological data are subjected to quality control processing to obtain the target meteorological data. The quality control processing includes ground clutter suppression processing, defolding algorithm processing, or velocity deblurring algorithm processing.

[0012] By adopting the above technical solution, the server filters the standard meteorological data and processes it through a preset algorithm to remove impurities from the standard meteorological data, thereby preventing these impurities from interfering with subsequent analysis and improving the accuracy of the fused meteorological data.

[0013] Optionally, the fusion instruction includes a cloud movement speed fusion instruction, and in response to the fusion instruction, at least two types of target meteorological data are fused according to the fusion instruction to obtain fused meteorological data, including: In response to the cloud movement speed fusion command, cloud measuring instrument data and wind field data are retrieved according to the cloud movement speed fusion command; Based on the cloud height data from the cloud measuring instrument and the wind field data, determine the airflow isobaric surface corresponding to the cloud height; Determine the prevailing wind direction in the isobaric surface of the airflow; Based on the prevailing wind direction and a preset formula, the cloud movement speed is determined, and the cloud movement speed is used as the fused meteorological data.

[0014] By adopting the above technical solution, cloud height and wind field data are fused from the meteorological data to obtain the cloud movement speed. Compared with the traditional method of collecting and analyzing single meteorological data, this fused meteorological data can reflect the cloud movement speed from multiple dimensions, thereby improving the accuracy of comprehensive weather analysis.

[0015] Optionally, the fusion instruction includes a zero-degree layer location fusion instruction, and in response to the fusion instruction, at least two types of target meteorological data are fused according to the fusion instruction to obtain fused meteorological data, including: In response to the zero-degree-layer position fusion command, cloud measuring instrument data and microwave radiometer data are retrieved according to the zero-degree-layer position fusion command; Based on the cloud measuring instrument data and the microwave radiometer data, the location of the zero-degree layer is determined, and the location of the zero-degree layer is used as the fused meteorological data.

[0016] By adopting the above technical solution, the zero-degree layer position information in the cloud measuring instrument data and the microwave radiometer data are called up and fused together. Compared with the traditional method of collecting and analyzing single meteorological data, this fused meteorological data can reflect the zero-degree layer position from multiple dimensions, thereby improving the accuracy of comprehensive meteorological analysis.

[0017] Optionally, the fusion command includes a fusion hydrogel command, wherein, in response to the fusion command, at least two types of target meteorological data are fused to obtain fused meteorological data, including: In response to the fusion water condensate command, the cloud intensity data from the millimeter-wave cloud measuring instrument and the water vapor intensity data from the aerosol laser observation instrument are retrieved according to the fusion water condensate command; The grayscale image is determined based on the cloud intensity data from the millimeter-wave cloud measuring instrument and the water vapor intensity data from the aerosol laser observation instrument. Calculate the area of ​​connected components in the grayscale image, determine the hydrogel image based on the area of ​​connected components, and use the hydrogel image as the fused meteorological data.

[0018] By adopting the above technical solution, cloud intensity data from millimeter-wave cloud measuring instruments and water vapor intensity data from aerosol laser observation instruments are fused to obtain a fused water condensate image. Compared with traditional single meteorological data collection and analysis, this fused meteorological data can reflect water condensate image information from multiple dimensions, thereby improving the accuracy of comprehensive meteorological analysis.

[0019] A second aspect of this application provides a radar-based meteorological fusion observation platform, comprising: The data generation module is used to receive multiple types of different meteorological data sent by radar equipment in various locations; The data conversion module is used to convert the meteorological data into standard meteorological data according to the preset standard format blocks; The quality control module is used to filter the standard meteorological data to obtain the target meteorological data; The data fusion module is used to respond to a fusion command and, according to the fusion command, fuse at least two types of target meteorological data to obtain fused meteorological data.

[0020] A third aspect of this application provides an electronic device.

[0021] A fourth aspect of this application provides a computer-readable storage medium.

[0022] In summary, by using the embodiments of this application, cloud data and wind field data are called, and cloud height, wind direction and other data in the meteorological data are fused to obtain the cloud movement speed. Compared with the traditional method of collecting and analyzing single meteorological data, this fused meteorological data can reflect the cloud movement speed from multiple dimensions, thereby improving the accuracy of comprehensive weather analysis. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of a system architecture provided in an embodiment of this application; Figure 2 This is a schematic diagram of information interaction under a system architecture provided in an embodiment of this application; Figure 3 This is a schematic flowchart of a meteorological fusion observation method based on radar technology provided in an embodiment of this application; Figure 4 This is a schematic diagram of a cloud profile information visualization interface provided in an embodiment of this application; Figure 5 This is a schematic diagram of a visualization interface for zero-degree layer bright band thickness information provided in an embodiment of this application; Figure 6 This is a schematic diagram of the structure of a meteorological fusion observation platform based on radar technology provided in an embodiment of this application; Figure 7 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application.

[0024] Explanation of reference numerals in the attached figures: 601, Data generation module; 602, Data conversion module; 603, Quality control module; 604, Data fusion module; 700, Electronic device; 701, Processor; 702, Memory; 703, User interface; 704, Network interface; 705, Communication bus. Detailed Implementation

[0025] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0026] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0027] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0028] To facilitate understanding of the methods and platforms provided in the embodiments of this application, the background of the embodiments of this application will be introduced before introducing the embodiments of this application.

[0029] Currently, meteorological staff typically analyze meteorological data using data from a single device, resulting in one-sided and inaccurate analysis. When analyzing complex weather conditions, staff need to manually synthesize data from multiple devices, but the resulting analysis often has lower accuracy.

[0030] Having read the background information above, those skilled in the art can understand the problems existing in the prior art. The technical solutions in the embodiments of this application will be described in detail below with reference to the accompanying drawings. The described embodiments are only some embodiments of this application, and not all embodiments.

[0031] Please refer to Figure 1The figure shows a system architecture diagram of a meteorological fusion method based on radar technology according to this application. This system architecture can be implemented as a platform for meteorological fusion observation based on radar technology. The platform can include: radar equipment, a server, and a display device. The server is directly or indirectly connected to the radar equipment and the display device through a communication network, thereby enabling information exchange among the three.

[0032] For example, radar equipment refers to various meteorological data acquisition devices. In the embodiments of this application, the type and number of radar devices are not unique, and the geographical location of each radar device can be within a large range without specific limitation.

[0033] For example, the server can be a backend server that receives meteorological data transmitted by the radar equipment, processes and fuses the meteorological data, and transmits the processed and fused meteorological data to a display device for visualization. The server can be a single server, a server cluster consisting of multiple servers, or a cloud computing service center.

[0034] Furthermore, display devices include, but are not limited to: Android system devices, Apple's iOS mobile operating system devices, personal computers (PCs), World Wide Web (web) devices, virtual reality (VR) devices, augmented reality (AR) devices, etc.

[0035] Please refer to Figure 2 ,exist Figure 1 Based on the description, a schematic diagram of information interaction under this system architecture is provided.

[0036] like Figure 2 As shown, the resource layer mainly includes the real-time transmission of meteorological data collected by various radar devices to the server via API interfaces. The server acquisition layer classifies the meteorological data into spectral data, base data, state data, and calibration data according to data type. Meteorological data that does not require immediate processing is stored in a MySQL or Cassandra database in the data persistence layer. This allows the subsequent data analysis layer to retrieve the data from the database in a timely manner when needed for analysis, enabling operations such as inferential statistics, sequence analysis, cluster analysis, reliability analysis, regression analysis, trend analysis, and correlation analysis. Meteorological data that requires immediate processing is directly introduced into the algorithm engine for data quality control and data fusion processing.

[0037] Furthermore, the server's business layer can perform operations such as data parsing, data querying, data processing, system management, equipment maintenance, and status monitoring, and these operations can be visualized through the display devices in the presentation layer.

[0038] It should be noted that, in the embodiments of this application... Figure 2 The demonstration only illustrates a portion of the information interaction process within the system architecture provided in this application, and does not represent the entirety. The above description explains the system architecture and the information interaction process within that architecture. Please refer to the embodiments described above for further information. Figure 3 A flowchart illustrating a meteorological fusion observation method based on radar technology is presented. This method can be implemented using a computer program, a microcontroller, or run on a radar-based meteorological fusion observation platform. The computer program can be integrated into the aforementioned server or run as a standalone application. Specifically, the method includes steps 301 to 304, as follows: Step 301: Receive multiple types of different meteorological data sent by radar equipment in various locations.

[0039] In this embodiment, radar equipment refers to meteorological detection equipment, specifically including millimeter-wave cloud measuring instruments, microwave radiometers, aerosol laser observation instruments, wind profilers, etc. Radar equipment in different locations can be understood as radar equipment situated in different geographical locations, where the geographical scope can be a region or a city, depending on the actual situation of the meteorological data to be analyzed. Furthermore, due to the different types and models of radar equipment in different locations, the types of meteorological data collected will also differ, and the meteorological data may include cloud intensity data, water vapor density data, etc.

[0040] For example, different types of radar equipment in various locations can send collected meteorological data to a server. The server can also proactively send meteorological data acquisition commands to designated radar equipment to receive meteorological data in real time. For instance, when encountering special extreme weather such as heavy rain, the server needs to retrieve meteorological data from relevant radar equipment for meteorological analysis; while for routine meteorological analysis, the server typically receives meteorological data in real time to make weather forecasts.

[0041] Step 302: Convert each meteorological data into standard meteorological data according to the preset standard format block.

[0042] For example, a standard format block can be understood as a storage module that stores the conversion relationships of different data types. It is mainly used to convert the above-mentioned different types of meteorological data into a unified meteorological data format to facilitate the subsequent processing of meteorological data. The meteorological data converted by the preset standard format block is defined as standard meteorological data.

[0043] Furthermore, in a feasible implementation provided in this application embodiment, the preset standard format block may include a common data format block and a radial data format block, and the corresponding meteorological data includes first meteorological data and second meteorological data. The step of converting each meteorological data into standard meteorological data may further include the following steps: Based on the public data block, the first meteorological data is converted into first standard meteorological data, and based on the radial data block, the second meteorological data is converted into second standard meteorological data.

[0044] The common data block refers to the module that stores the configuration and content information of radar equipment and meteorological data. It mainly includes a general header block, a site configuration block, a radar configuration block, a task configuration block, and a scan configuration block. The general header block is mainly used to identify the file category, file format version, file type, and other information. The site configuration block and radar configuration block are mainly used to describe radar station information. The task configuration block mainly provides general information for radar scanning tasks, including PPI, RHI, and sector scan information. The scan configuration block mainly provides specific scan configuration information, including scan elevation angle, azimuth angle, etc.

[0045] Radial data blocks refer to modules that store the status information of meteorological data. They mainly include radial header blocks and radial data blocks. The radial header blocks mainly provide information such as data status and acquisition time. The radial database is mainly used to store radial data from radar detection, such as reflectivity Z, radial velocity V, and spectral width W. It includes radial data headers and radial data. The number of data blocks is determined by the number of data categories in the radial data header.

[0046] Furthermore, the first meteorological data refers to the radar equipment and the configuration and content information of the meteorological data, while the second meteorological data refers to the status information of the meteorological data.

[0047] For example, when the server receives meteorological data uploaded by each radar device, it converts the first meteorological data into first standard meteorological data according to the common data block, and converts the second meteorological data into second standard meteorological data according to the radial data block. The process mainly involves converting the field names, byte types, byte units, and byte ranges in the meteorological data into a standardized form to facilitate subsequent data processing.

[0048] Step 303: Filter out impurity data in each of the standard meteorological data to obtain the target meteorological data.

[0049] Among them, screening refers to the operation of filtering impurities in various standard meteorological data, and the data obtained after screening the standard meteorological data is defined as the target meteorological data.

[0050] Specifically, since the amount of meteorological data transmitted by radar equipment in various regions is large and complex, in order to reduce the error caused by other useless meteorological data when analyzing meteorological data and to improve the speed of data processing, the meteorological data is usually filtered, and the target meteorological data obtained after filtering can be stored in a distributed database.

[0051] Based on the above embodiments, as an optional embodiment, the filtering process may specifically involve performing quality control processing on each standard meteorological data to obtain the target meteorological data.

[0052] Quality control processing can include ground clutter suppression, defolding algorithms, and velocity deblurring algorithms. For example, the main factors affecting radar data quality include ground clutter, range folding, and velocity ambiguity. Ground clutter can cause problems such as high reflectivity, irregular distribution, sudden data changes, non-smooth gradients, speckle formation, and wide range of speckle values. Ground clutter can be suppressed using a high-pass filter. When the radar target is located outside the radar's unambiguous range, range folding is likely to occur, leading to inaccurate target positioning. Therefore, defolding algorithms can be used to improve range folding. When the radar detects a velocity exceeding the maximum average radial velocity, velocity ambiguity is likely to occur. Velocity deblurring algorithms can be used to attempt to identify and correct the ambiguous velocity.

[0053] Step 304: In response to the fusion command, at least two types of target meteorological data are fused according to the fusion command to obtain fused meteorological data for meteorological analysis.

[0054] The instruction is the directive and command to the server to work. It can be understood as the control code that formulates the execution of a certain operation or function. The fusion instruction can be understood as the control code generated when fusion is required. In the embodiments of this application, the fusion instruction carries the mapping relationship between the fused meteorological data and at least two target meteorological data.

[0055] Specifically, in response to the fusion command, the server retrieves the target meteorological data that has a mapping relationship with the fusion command, and further performs fusion processing on the target meteorological data to obtain fused meteorological data.

[0056] Based on the above embodiments, as an optional embodiment, the step of responding to a fusion command and fusing at least two types of target meteorological data to obtain fused meteorological data may further include the following steps: Step 401: In response to the cloud movement speed fusion command, retrieve cloud measurement data and wind field data according to the cloud movement speed fusion command.

[0057] Among them, cloud data refers to meteorological data collected by millimeter-wave cloud measuring instruments, which may specifically include cloud intensity data; wind field data refers to airflow data corresponding to the height distribution pressure matched by the CMA model field, which includes wind direction, wind speed, etc.

[0058] For example, in response to the cloud movement speed fusion command, the server determines the meteorological data to be fused according to the cloud movement speed fusion command, and retrieves the cloud measuring instrument data and wind field data from the database accordingly.

[0059] Step 402: Determine the airflow isobaric surface corresponding to the cloud height based on the cloud height data from the cloud measuring instrument and the wind field data.

[0060] For example, the server determines the height of the cloud layer based on the cloud instrument data, calculates the pressure distribution at that cloud height, compares the calculated pressure distribution at the cloud height with the wind field data to determine the airflow data, and then matches the airflow isobaric surface at the corresponding cloud height in the cloud instrument data based on the airflow data.

[0061] Step 403: Determine the cloud movement speed based on the prevailing wind direction and a preset formula, and use the cloud movement speed as the fused meteorological data.

[0062] Specifically, based on the airflow isobaric surface information, the server can further determine the horizontal wind direction of each isobaric surface, and then filter each horizontal wind direction, taking the wind direction with a proportion of more than 50% as the dominant wind direction, and calculate multiple wind speeds of the dominant wind direction to obtain the average wind speed, which is then used as the cloud movement speed.

[0063] After the above steps are completed, the server combines the cloud intensity data with the prevailing wind direction and cloud movement speed, and then sends the prevailing wind direction and cloud movement speed to the display device. The display device can generate a fused image displaying cloud profile information. Please refer to [link / reference needed]. Figure 4 , Figure 4 A schematic diagram of a cloud profile information visualization interface is shown, which allows for the analysis of cloud movement through information visualization.

[0064] Based on the above embodiments, as another optional embodiment, the step of responding to a fusion command and fusing at least two types of target meteorological data to obtain fused meteorological data may further include the following steps: Step 501: In response to the zero-degree layer position fusion command, retrieve cloud measurement data and microwave radiometer data according to the zero-degree layer position fusion command.

[0065] Among them, cloud meter data refers to meteorological data collected by millimeter-wave cloud meter, which includes data such as reflectivity factor; microwave radiometer data refers to data collected by microwave radiometer, which includes data such as temperature and water vapor density.

[0066] For example, in response to the zero-degree-layer position fusion command, the server determines the target meteorological data to be fused according to the zero-degree-layer position fusion command, and retrieves the cloud measuring instrument data and microwave radiometer data from the database accordingly.

[0067] Step 502: Determine the zero-degree layer position based on the cloud measuring instrument data and the microwave radiometer data, and use the zero-degree layer position as the fused meteorological data.

[0068] The zero-degree layer position refers to the altitude in the atmosphere when the air temperature drops to zero degrees Celsius. It is mainly used for artificial rainmaking and precipitation forecasting. The zero-degree layer position is primarily determined by identifying the zero-degree layer bright band, which is a phenomenon on a reflectivity factor image, appearing as a distinct bright band.

[0069] Specifically, the server retrieves cloud data and uses a preset rotating coordinate system method to calculate the height of the zero-degree layer bright band. Simultaneously, based on the retrieved microwave radiometer data, a preset interpolation algorithm is used to obtain the zero-degree height. Thus, the height of the zero-degree layer bright band and the zero-degree height can be combined to obtain the intersection of the two heights. Then, the median value of the intersection is used to draw the zero-degree contour line, thereby obtaining a more accurate location of the zero-degree layer.

[0070] In a feasible real-time approach, the thickness of the zero-degree layer bright band can be calculated primarily through parametric and derivative methods. The parametric method involves the server retrieving reflectivity factor data from a cloud measuring instrument, processing this data using a pre-defined program to form an image, and then incorporating the reflectivity factors into the image. A preset attenuation range for the peak reflectivity factor is then used as the thickness of the zero-degree layer bright band. The derivative method involves the server processing the retrieved cloud measuring instrument data using a preset rotating coordinate system to obtain the thickness of the zero-degree layer bright band.

[0071] After the above steps are completed, the server sends the zero-degree layer brightness band thickness to the display device. The display device can then generate a fused image displaying the zero-degree layer brightness band thickness. Please refer to [link / reference]. Figure 5 , Figure 5 A schematic diagram of a visualization interface for zero-degree layer bright band thickness information is shown.

[0072] Based on the above embodiments, as another optional embodiment, the step of responding to a fusion command and fusing at least two types of target meteorological data to obtain fused meteorological data may further include the following steps: Step 601: In response to the fusion water condensate command, retrieve the cloud intensity data from the millimeter-wave cloud measuring instrument and the water vapor intensity data from the aerosol laser observation instrument according to the fusion water condensate command.

[0073] Specifically, in response to the fusion water vapor command, the server determines the target meteorological data to be fused based on the fusion water vapor command, and retrieves the cloud intensity data from the millimeter-wave cloud measuring instrument and the water vapor intensity data from the aerosol laser observation instrument from the database.

[0074] Step 602: Determine the grayscale image based on the cloud intensity data from the millimeter-wave cloud measuring instrument and the water vapor intensity data from the aerosol laser observation instrument.

[0075] Specifically, to select the maximum value of the combination of cloud intensity data and water vapor intensity data, the server filters according to a preset range in the distance database, and uses the combination of cloud intensity data and water vapor intensity data with the highest intensity within the preset range as the fusion value. Based on this comparison method, the fusion value is accumulated according to a preset time series. When the number of accumulations exceeds a preset threshold, the accumulated data is converted into grayscale image information.

[0076] Step 603: Calculate the area of ​​connected components in the grayscale image, determine the hydrogel image based on the area of ​​connected components, and use the hydrogel image as the fused meteorological data.

[0077] Specifically, after the grayscale image conversion is completed, the server marks the grayscale image using a connected component marking algorithm; after the connected components are marked, the area of ​​the marked connected components in the grayscale image is calculated, and the marked connected components are filtered according to a preset area threshold to obtain the filtered hydrogel fusion image.

[0078] The connected component labeling algorithm used in the above embodiments is based on the Seed-Filling algorithm for image labeling. The main method of this algorithm is to select a random pixel in the image as the seed for the algorithm to start traversing, and to traverse each pixel in the image in order from left to right and from top to bottom. Then, the pixel is judged to determine whether it has been traversed. If the pixel has been traversed, the traversal continues. If the pixel has not been traversed, it is used as the seed for the start of traversal, and pixels that meet the conditions are pushed onto the stack according to the adjacency relationship. The above traversal steps are repeated until all images have been traversed and all pixels belong to the same connected region.

[0079] In addition, this meteorological fusion method also includes the fusion of data collected by various other radar devices, and is not limited to the three fusion methods mentioned above, which will not be elaborated on here.

[0080] The following are platform embodiments of this application, which can be used to execute the method embodiments of this application. For details not disclosed in the platform embodiments of this application, please refer to the method embodiments of this application.

[0081] Please refer to Figure 6 This application provides a radar-based meteorological fusion observation platform, which may include: a data generation module 601, a data conversion module 602, a quality control module 603, and a data fusion module 604, wherein: The data generation module 601 is used to receive multiple types of different meteorological data sent by radar equipment in various locations; The data conversion module 602 is used to convert the meteorological data into standard meteorological data according to the preset standard format block; The quality control module 603 is used to filter out impurity data in the standard meteorological data to obtain the target meteorological data; The data fusion module 604 is used to respond to a fusion command and, according to the fusion command, fuse at least two types of target meteorological data to obtain fused meteorological data for meteorological analysis.

[0082] Based on the above embodiments, as an optional embodiment, the data conversion module 602 further includes: a common data block conversion unit and a radial data block conversion unit, wherein: The public data block conversion unit is used to convert the first meteorological data into first standard meteorological data.

[0083] A radial data block conversion unit is used to convert the second meteorological data into second standard meteorological data.

[0084] Based on the above embodiments, as an optional embodiment, the quality control module 603 further includes: a quality control processing unit, wherein: The quality control processing unit is used to perform quality control processing on each of the standard meteorological data to obtain the target meteorological data. The quality control processing includes ground clutter suppression processing, defolding algorithm processing, or velocity deblurring algorithm processing.

[0085] Based on the above embodiments, as an optional embodiment, the data fusion module 604 includes: a cloud movement speed fusion unit, a zero-degree layer position fusion unit, and a fusion water condensate unit, wherein: The cloud movement speed fusion unit is used to respond to a cloud movement speed fusion command, call cloud measuring instrument data and wind field data according to the cloud movement speed fusion command; determine the airflow isobaric surface corresponding to the cloud height according to the cloud height in the cloud measuring instrument data and the wind field data; determine the prevailing wind direction in the airflow isobaric surface; determine the cloud movement speed according to the prevailing wind direction and a preset formula, and use the cloud movement speed as the fused meteorological data.

[0086] The zero-degree layer position fusion unit is used to respond to the zero-degree layer position fusion command, call cloud instrument data and microwave radiometer data according to the zero-degree layer position fusion command; determine the zero-degree layer position according to the cloud instrument data and microwave radiometer data, and use the zero-degree layer position as the fused meteorological data.

[0087] The fusion water condensate unit is used to respond to the fusion water condensate command, call cloud intensity data from a millimeter-wave cloud measuring instrument and water vapor intensity data from an aerosol laser observation instrument according to the fusion water condensate command; determine a grayscale image based on the cloud intensity data from the millimeter-wave cloud measuring instrument and the water vapor intensity data from the aerosol laser observation instrument; calculate the area of ​​connected regions in the grayscale image, determine the water condensate image based on the area of ​​connected regions, and use the water condensate image as the fusion meteorological data.

[0088] It should be noted that the platform provided in the above embodiments is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the platform and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0089] This application also discloses an electronic device. (See reference...) Figure 7 , Figure 7 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application. The electronic device 700 may include: at least one processor 701, at least one network interface 704, a user interface 703, a memory 702, and at least one communication bus 705.

[0090] The communication bus 705 is used to enable communication between these components.

[0091] The user interface 703 may include a display screen and a camera. Optionally, the user interface 703 may also include a standard wired interface and a wireless interface.

[0092] The network interface 704 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0093] The processor 701 may include one or more processing cores. The processor 701 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 702, and by calling data stored in memory 702. Optionally, the processor 701 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 701 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface graphics, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also be implemented as a separate chip without being integrated into the processor 701.

[0094] The memory 702 may include random access memory (RAM) or read-only memory. Optionally, the memory 702 may include a non-transitory computer-readable storage medium. The memory 702 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 702 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 702 may also be at least one storage platform located remotely from the aforementioned processor 701. (Refer to...) Figure 7 The memory 702, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for a meteorological fusion observation method based on radar technology.

[0095] exist Figure 7 In the illustrated electronic device 700, the user interface 703 is mainly used to provide an input interface for the user and acquire user input data; while the processor 701 can be used to call an application program of a radar-based meteorological fusion observation platform stored in the memory 702. When executed by one or more processors 701, the electronic device 700 performs one or more of the methods described in the above embodiments. It should be noted that, for the foregoing method embodiments, for the sake of simplicity, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0096] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0097] In the various embodiments provided in this application, it should be understood that the disclosed platform can be implemented in other ways. For example, the platform embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interfaces; the indirect coupling or communication connection between the platform or units may be electrical or other forms.

[0098] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0099] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0100] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, 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. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0101] The above description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of the specification and the disclosure of practical truths.

[0102] This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A meteorological fusion method based on radar technology, characterized in that, include: It receives various types of meteorological data transmitted by radar equipment in different locations; According to the preset standard format block, each meteorological data is converted into standard meteorological data; Impurities in the standard meteorological data are filtered out to obtain the target meteorological data; In response to a fusion command, at least two types of target meteorological data are fused according to the fusion command to obtain fused meteorological data, which is then used for meteorological analysis. The fusion command includes a cloud movement speed fusion command. In response to the fusion command, at least two types of target meteorological data are fused according to the fusion command to obtain fused meteorological data, including: In response to the cloud movement speed fusion command, cloud measuring instrument data and wind field data are retrieved according to the cloud movement speed fusion command; Based on the cloud height data from the cloud measuring instrument and the wind field data, determine the airflow isobaric surface corresponding to the cloud height; Determine the prevailing wind direction in the isobaric surface of the airflow; Based on the prevailing wind direction and a preset formula, the cloud movement speed is determined, and the cloud movement speed is used as the fused meteorological data.

2. The meteorological fusion method based on radar technology according to claim 1, characterized in that, The preset standard format block includes a common data block and a radial data block, and the meteorological data includes first meteorological data and second meteorological data. The step of converting each of the meteorological data into standard meteorological data according to the preset standard format block includes: Based on the public data block, the first meteorological data is converted into first standard meteorological data, the first meteorological data including identification file data, radar station data and scanning configuration data; Based on the radial data block, the second meteorological data is converted into second standard meteorological data, which includes status data, acquisition time data, and radial data.

3. The meteorological fusion method based on radar technology according to claim 1, characterized in that, After converting the meteorological data into standard meteorological data according to a preset format standard, the process further includes: The standard meteorological data is stored in a distributed database, including the Cassandra database.

4. The meteorological fusion method based on radar technology according to claim 1, characterized in that, The process of filtering out impurities from the standard meteorological data to obtain the target meteorological data includes: The standard meteorological data are subjected to quality control processing to obtain the target meteorological data. The quality control processing includes ground clutter suppression processing, defolding algorithm processing, or velocity deblurring algorithm processing.

5. The meteorological fusion method based on radar technology according to claim 1, characterized in that, The fusion command includes a zero-degree layer location fusion command. In response to the fusion command, at least two types of target meteorological data are fused according to the fusion command to obtain fused meteorological data, including: In response to the zero-degree-layer position fusion command, cloud measuring instrument data and microwave radiometer data are retrieved according to the zero-degree-layer position fusion command; Based on the cloud measuring instrument data and the microwave radiometer data, the location of the zero-degree layer is determined, and the location of the zero-degree layer is used as the fused meteorological data.

6. The meteorological fusion method based on radar technology according to claim 1, characterized in that, The fusion command includes a hydrogel fusion command. In response to the fusion command, at least two types of target meteorological data are fused to obtain fused meteorological data, including: In response to the fusion water condensate command, the cloud intensity data from the millimeter-wave cloud measuring instrument and the water vapor intensity data from the aerosol laser observation instrument are retrieved according to the fusion water condensate command; The grayscale image is determined based on the cloud intensity data from the millimeter-wave cloud measuring instrument and the water vapor intensity data from the aerosol laser observation instrument. Calculate the area of ​​connected components in the grayscale image, determine the hydrogel image based on the area of ​​connected components, and use the hydrogel image as the fused meteorological data.

7. A meteorological fusion platform based on radar technology, characterized in that, The platform includes: The data generation module (601) is used to receive multiple types of different meteorological data sent by radar equipment in various locations; The data conversion module (602) is used to convert the meteorological data into standard meteorological data according to the preset standard format block; The quality control module (603) is used to filter the standard meteorological data to obtain the target meteorological data; The data fusion module (604) is configured to, in response to a fusion command, fuse at least two types of target meteorological data to obtain fused meteorological data, wherein... The fusion command includes a cloud movement speed fusion command. In response to the fusion command, at least two types of target meteorological data are fused according to the fusion command to obtain fused meteorological data, including: In response to the cloud movement speed fusion command, cloud measuring instrument data and wind field data are retrieved according to the cloud movement speed fusion command; Based on the cloud height data from the cloud measuring instrument and the wind field data, determine the airflow isobaric surface corresponding to the cloud height; Determine the prevailing wind direction in the isobaric surface of the airflow; Based on the prevailing wind direction and a preset formula, the cloud movement speed is determined, and the cloud movement speed is used as the fused meteorological data.

8. An electronic device, characterized in that, The device includes a processor (701), a memory (702), a user interface (703), and a network interface (704). The memory (702) is used to store instructions. The user interface (703) and the network interface (704) are used to communicate with other devices. The processor (701) is used to execute the instructions stored in the memory (702) to cause the electronic device (700) to perform the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed, perform the steps of the method as described in any one of claims 1-6.

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