Wind direction quality control method and system based on meteorological data file

Abstract

The embodiment of the invention provides a wind direction quality control method and system based on a meteorological data file. The method is applied to the technical field of meteorological observation automation and comprises the steps that a time sequence wind direction angle value is read and analyzed from a time sequence data file, wind direction frequency statistics is conducted on the whole range of 0-360 degrees according to an instantaneous value per minute, and wind direction distribution characteristics under different time scales are obtained; obtaining a wind direction frequency distribution data set; developing a special program, and automatically converting the wind direction frequency distribution data set into a visual chart in batches; based on the confirmed suspicious graphic features, establishing an anomaly classification system, and performing association mapping on each type of anomaly and potential physical causes; and obtaining a diagnosis knowledge system. The technical problems that the data quality is easily reduced after a long time due to data abnormity generated in the uploading process of the ground observation data, the availability of the data is influenced, and the quality of the wind direction observation data is further reduced are solved.

Description

Technical Field

[0001] This invention relates to the field of automated meteorological observation technology, and in particular to a wind direction quality control method and system based on meteorological data files. Background Technology

[0002] Currently, high-quality ground-based observation data is of vital value for weather forecasting and meteorological services. High-quality wind direction data not only ensures the correct use of wind speed data but also plays a crucial role in weather forecasting, urban planning, pollutant dispersion, and wind energy resource utilization. Automated ground-based observation significantly reduces the possibility of erroneous data due to operator error. However, because wind sensors are exposed to harsh external environments for extended periods, lightning, high temperatures, and high humidity can all damage them. Since equipment calibration is typically performed periodically, failure to detect sensor damage promptly can lead to persistent anomalies in observational data.

[0003] Currently, wind direction observations at ground meteorological stations primarily utilize photoelectric Gray code wind direction sensors. These sensors are susceptible to damage from lightning strikes and other causes, and their mechanical components may deform, leading to sluggish rotation. Even after these issues occur, observational data is still generated, easily misinterpreted as normal sensor operation, making wind direction data anomalies difficult to detect. Existing methods and procedures for routinely checking wind direction at stations have certain shortcomings. From observation to transmission to the national level, ground observation data undergoes a series of processing steps, and problems at any stage can cause data anomalies. If these anomalies are not detected promptly, they accumulate, degrading data quality and severely impacting data usability. To improve the quality of wind direction observation data, it is necessary to further inspect and analyze wind direction observation data from automatic weather stations to promptly identify anomalies. Summary of the Invention

[0004] This invention provides a wind direction quality control method and system based on meteorological data files. It addresses the technical problem that existing methods or procedures for routine wind direction checks at weather stations can lead to data anomalies during the uploading of ground observation data, which can easily cause data quality degradation over time, severely affecting data availability and further reducing the quality of wind direction observation data.

[0005] According to a first aspect of the present invention, a wind direction quality control method based on meteorological data files is provided, comprising: The original time-series data file collected by the weather station contains wind direction angle values ​​recorded every minute in a time series; the time-series wind direction angle values ​​are read and parsed from the time-series data file, and based on the instantaneous values ​​every minute, wind direction frequency statistics are performed on the entire range of 0-360° to obtain the wind direction distribution characteristics at different time scales; thus, a wind direction frequency distribution dataset is obtained. Develop a dedicated program to automatically and batch convert wind direction frequency distribution datasets into visual charts. In the visual charts, the wind direction distribution of each station is presented in the form of a continuous angle spectrum. A normal distribution map should show a continuous and smooth distribution pattern, while a distribution map with data anomalies will show obvious abnormal graphic features such as missing angles, unnatural peaks, or discontinuities. The result is a wind direction angle distribution map set presented in the form of images, covering all meteorological stations and specified time periods. Using image recognition algorithms, stations with suspicious graphic features are selected from the wind direction angle distribution map set; historical data from different time periods are reviewed to generate wind direction angle distribution map sets for the stations, eliminating instantaneous interference; based on the confirmed suspicious graphic features, an anomaly classification system is established, and each type of anomaly is associated with a potential physical cause; thus, a diagnostic knowledge system containing the correspondence between anomaly map library, anomaly type, and possible cause is obtained.

[0006] According to a second aspect of the present invention, a wind direction quality control system based on meteorological data files is provided, comprising: The dataset acquisition module is used to collect raw time-series data files from weather stations, which contain wind direction angle values ​​recorded every minute in a time series. It reads and parses the time-series wind direction angle values ​​from the time-series data files, and performs wind direction frequency statistics on the entire range of 0-360° based on the instantaneous values ​​every minute to obtain the wind direction distribution characteristics at different time scales; thus obtaining a wind direction frequency distribution dataset. The visualization conversion module is used to develop dedicated programs that automatically and in batches convert wind direction frequency distribution datasets into visual charts. In the visual charts, the wind direction distribution of each station is presented in the form of a continuous angle spectrum. A normal distribution map should show a continuous and smooth distribution pattern, while a distribution map with data anomalies will show obvious abnormal graphic features such as missing angles, unnatural peaks, or discontinuities. The result is a wind direction angle distribution map set presented in image form, covering all meteorological stations and a specified time period. The association mapping module is used to filter out stations with suspicious graphic features from the wind direction angle distribution map set through image recognition algorithms; it backtracks historical data from different time periods to generate wind direction angle distribution map sets for the stations, eliminating instantaneous interference; based on the confirmed suspicious graphic features, it establishes an anomaly classification system and associates each type of anomaly with its potential physical causes; thus obtaining a diagnostic knowledge system that includes the correspondence between anomaly map library, anomaly type, and possible causes.

[0007] According to a third aspect of the present invention, an electronic device is provided. The electronic device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the program to implement the method according to the first aspect of the present invention.

[0008] According to a fourth aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method according to a first aspect of the present invention.

[0009] Compared with existing technologies, the advantages and positive effects of this invention are: This invention extracts wind direction angle values ​​from raw time-series data files collected from meteorological stations, performs frequency statistics, obtains wind direction distribution characteristics, and forms a wind direction frequency distribution dataset. A dedicated program is developed to transform the wind direction frequency distribution dataset into visual charts, intuitively displaying the wind direction distribution at each station to observe the continuity and smoothness of the wind direction distribution. Image recognition algorithms are used to filter out stations with suspicious graphic features, eliminating transient interference, and generating a wind direction angle distribution atlas for each station. By establishing an anomaly classification system, each type of anomaly is associated with possible physical causes, constructing a diagnostic knowledge system.

[0010] It should be understood that the description in the Summary of the Invention is not intended to limit the key or essential features of the embodiments of the present invention, nor is it intended to restrict the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0011] The above and other features, advantages, and aspects of the various embodiments of the present invention will become more apparent from the accompanying drawings and the following detailed description. The drawings are provided for a better understanding of the invention and are not intended to limit the invention. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein: Figure 1 A flowchart of a wind direction quality control method based on meteorological data files according to an embodiment of the present invention is shown; Figure 2 A block diagram of a wind direction quality control system based on meteorological data files according to an embodiment of the present invention is shown; Figure 3 P3545 shows a schematic diagram of wind distribution in September 2024, illustrating an embodiment of the present invention. Figure 4 A schematic diagram of wind distribution in November 2024 (P3545) is shown, illustrating an embodiment of the invention that can be implemented. Figure 5 P3592 shows a schematic diagram of wind distribution in September 2024, which enables the implementation of embodiments of the present invention; Figure 6 P3592 shows a schematic diagram of wind distribution in November 2024, which enables the implementation of embodiments of the present invention; Detailed Implementation

[0012] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0013] Furthermore, the term "and / or" in this invention is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this invention generally indicates that the preceding and following related objects have an "or" relationship.

[0014] Figure 1 This diagram illustrates a flow chart of a wind direction quality control method 100 based on meteorological data files according to an embodiment of the present invention. Figure 1 As shown, the method 100 includes: S110: The raw time-series data file collected by the weather station, which contains wind direction angle values ​​recorded every minute in a time series; the time-series wind direction angle values ​​are read and parsed from the time-series data file, and wind direction frequency statistics are performed on the entire range of 0-360° based on the instantaneous values ​​every minute to obtain the wind direction distribution characteristics at different time scales; a wind direction frequency distribution dataset is obtained; a map is drawn according to the actual wind direction in degrees, with a resolution of 1°.

[0015] Optionally, in some embodiments, the process of obtaining the wind direction frequency distribution dataset specifically includes the following steps: S111: The original time series data file is traversed and parsed, and the entire circumference from 0 to 360 degrees is divided into basic analytical units of 1 to 3 degrees for full coverage; each independent wind direction angle value in the original time series data file is scanned and extracted, and the value corresponds to a certain basic analytical unit.

[0016] In this embodiment of the application, the process of corresponding a numerical value to a certain basic analytical unit specifically includes the following steps: S1111: Establish the division rules for a continuous circle from 0 to 360 degrees, define 1 to 3 degrees as the width parameter of the basic analytical unit, generate a continuous and non-overlapping sequence of micro-analytical units, and output a fine analytical reference frame for wind direction containing the structured reference system defined by all micro-analytical units.

[0017] S1112: Read each wind direction angle value in the original time series data file in sequence, match and calculate each wind direction angle value with the wind direction fine analysis benchmark framework, determine the unique analysis unit corresponding to each angle value, record the belonging relationship between the angle value and the analysis unit, and obtain the time series wind direction unit belonging relationship set.

[0018] S1113: Traverse all micro-analytical units in the fine-grained wind direction analysis benchmark framework, check the coverage status of each micro-analytical unit in the time-series wind direction unit affiliation set, mark micro-analytical units with data coverage, and generate full coverage verification results.

[0019] S112: Calculate the frequency of wind direction angle values ​​falling within each 1 to 3 degree basic analytical unit in the time series data of the basic analytical unit at each time scale; generate multiple frequency statistical subsets associated with different time spans.

[0020] S113: Aggregate and integrate frequency statistics subsets from various independent time-series scales, organize and encapsulate them; output a structured multi-scale wind direction frequency distribution dataset.

[0021] In this embodiment, when traversing and parsing the original time-series data file, the circumference is divided into basic analytical units for full coverage. Each independent wind direction angle value is scanned and extracted, corresponding to the basic analytical unit, achieving refined positioning and classification of the wind direction angle values. The frequency of wind direction angle values ​​falling within each basic analytical unit is calculated for each time scale, generating multiple frequency statistical subsets associated with different time spans, achieving quantitative statistics of wind direction frequency across multiple time dimensions. The frequency statistical subsets at each independent time scale are aggregated and integrated, organized and encapsulated, and output as a structured multi-scale wind direction frequency distribution dataset, forming a wind direction frequency data set with a unified structure and complete time coverage. This achieves complete parsing and multi-scale frequency statistics of the original wind direction data, generating a wind direction frequency distribution dataset with a unified structure and multi-time dimension coverage, providing a comprehensive data foundation for wind direction pattern analysis.

[0022] S120: Develop a dedicated program to automatically and batch convert wind direction frequency distribution datasets into visual charts; in the visual charts, the wind direction distribution of each station is presented in the form of a continuous angle spectrum. A normal distribution map should present a continuous and smooth distribution pattern, while a distribution map with data anomalies will show obvious abnormal graphic features such as missing angles, unnatural peaks, or discontinuities; obtain a wind direction angle distribution map set in the form of images, covering all meteorological stations and specified time periods; Optionally, in some embodiments, the process of automatically and in batches converting wind direction frequency distribution datasets into visual charts specifically includes the following steps: S121: Establish rules to map abstract data to specific graphic attributes. Assign a graphic representation attribute to the frequency value of each micro-angle unit in the wind direction frequency distribution dataset. The graphic representation attribute corresponds to the position of the micro-angle unit on the circumference. At the same time, map the magnitude of the frequency value to the level of a certain visual intensity dimension in the graphic. Output a set of wind direction frequency graphic elements.

[0023] S122: Based on the time-series wind direction angle values ​​in ascending order, all graphic elements belonging to the same time-scale wind direction frequency graphic element set are seamlessly spliced ​​and combined to generate a continuous angle spectrum graphic sequence; the continuous angle spectrum graphic sequence consists of multiple complete ring graphics, each graphic showing the full-angle wind direction frequency distribution pattern at a specific time scale.

[0024] In this embodiment of the application, the process of generating a continuous angular spectrum graphic sequence specifically includes the following steps: S1221: Based on the inherent position of the micro-angle unit corresponding to each graphic element on the 0-360 degree circle, perform systematic sorting; based on the wind direction angle value itself, reorganize all graphic elements into a circular data sequence in an order starting from 0 degrees and increasing in steps of 1-3 degrees, and output an ordered graphic element sequence.

[0025] S1222: For any two angularly adjacent graphic elements in an ordered sequence of graphic elements, check and process the transition of their graphic representation attributes at the connection boundary to generate a seamless graphic unit sequence; each graphic element in the seamless graphic unit is seamlessly connected with its preceding and following adjacent graphic elements.

[0026] S1223: Maps the sequence of linear seamless graphic units connected end to end into a ring-shaped visual space layout; processes the connection boundary between the first (near 0 degrees) and the last (near 360 degrees) graphic element in the seamless graphic unit sequence, applies boundary smoothing processing, and forms a complete ring-shaped graphic without start or end points; outputs a continuous angle spectrum graphic sequence.

[0027] In this embodiment of the application, the process of forming a complete ring shape without start or end points specifically includes the following steps: S12231: Identify and extract the graphic representation attributes of the first and last graphic units in the seamless graphic unit; obtain the attribute state of the starting side of the first graphic unit and the attribute state of the ending side of the last graphic unit, and capture and record the two attribute states as a pair of specific boundary data; output the beginning and end boundary state descriptors to define the visual connection conditions to be processed at the ring closure.

[0028] S12232: Taking the captured start and end boundary state descriptors as input, execute the calculation rules; the calculation rules generate a set of parameters to guide the graphics rendering, ensuring that the visual performance from the end of the last graphics unit to the beginning of the first graphics unit in the linear seamless graphics unit sequence is consistent with the visual transition effect between any two adjacent graphics units within the linear seamless graphics unit sequence, achieving visual smoothness and continuity; generate ring-shaped connection transition parameters, which are a set of instructions generated for the start and end boundaries to achieve seamless visual closure.

[0029] It should be noted that, in this embodiment, the process of generating the ring-shaped transition parameters specifically includes the following steps: S122321: From the generated linear seamless graphic unit sequence, analyze the computation rules between all angularly adjacent graphic unit pairs, capture and formalize the proven smoothing logic within the sequence; output a set of smooth transition rules for graphic units. S122322: Obtain the internal unit smooth transition rule set and the initial first and last boundary state descriptors; input the first and last boundary states as a pair of adjacent units into the internal unit smooth transition rule set; generate a circular closed transition strategy that realizes the smooth transition from the tail graphic unit state to the first graphic unit state by executing the calculation logic defined in the internal unit smooth transition rule set. In this embodiment of the application, the process of generating a circular closed transition strategy that smoothly transitions from the tail graphic unit state to the head graphic unit state specifically includes the following steps: S1223221: Logically reconstruct the two independent states captured in the first and last boundary state descriptors, belonging to the two ends of the sequence, into a virtual continuous structure; define the end-side state of the tail graphic unit as the predecessor state in the new structure, and define the start-side state of the first graphic unit as the successor state in the continuous structure, logically forming a temporary data pair with the same data structure as any adjacent graphic unit pair within the linear seamless graphic unit sequence; output simulated adjacent unit pairs, which are structurally equivalent to a standard internal adjacent unit pair.

[0030] S1223222: Substitute the simulated adjacent unit pairs into the calculation engine defined by the internal unit smooth transition rule set. Based on the rules embedded in the calculation engine, calculate and output a specific relationship that describes the trajectory of how the graphic representation attributes should change continuously from the end side of the tail graphic unit to the start side of the head graphic unit; obtain the attribute change path that must be followed to achieve visual smoothness at the beginning and end boundaries.

[0031] It should be noted that, in this embodiment, the process of calculating and outputting a specific relationship includes the following steps: S12232221: Analyze the predecessor and successor values ​​of the attribute states of all adjacent unit pairs in the internal unit smooth transition rule set, identify and extract the core operation sequence shared by all unit pairs for calculating intermediate states, and solidify the operation sequence into a program for calculating intermediate states based on the states at both ends.

[0032] S12232222: Fix the end-side attribute state of the tail graphic unit in the simulated adjacent unit pair as the starting input parameter of the program, and fix the start-side attribute state of the first graphic unit in the simulated adjacent unit pair as the ending input parameter of the program; complete the parameter binding, so that the program is transformed into a single-variable program that only depends on the relative position within the transition interval.

[0033] S12232223: Within the relative position range of 0% to 100%, the number and position of sampling points are determined according to the preset rendering precision. At each sampling point position, a single-variable program is called to obtain the graphic attribute value of the sampling point. All sampling points and their corresponding attribute values ​​are recorded in position order to form an ordered sequence of numerical pairs and output the attribute change path.

[0034] S1223223: Evaluate the attribute change path and verify whether its application can achieve visual attribute self-consistency and continuity in the global scope of the annular space; after verification, output the annular closure transition strategy, including all the calculation logic and parameters required to achieve seamless closure of the beginning and end boundaries.

[0035] S122323: Converts the calculated circular closure transition strategy into a series of control instructions that are recognized and executed by the graphics rendering engine, specifying how to adjust the graphic representation attributes in the connection area of ​​the first and last graphics units to achieve visual smooth closure; outputs a structured set of instructions for the circular connection transition parameters.

[0036] S12233: Arrange the linear seamless graphic unit sequence within a ring-shaped visual space. Apply the instructions defined by the ring-connection transition parameters to perform the final graphic rendering of the connection area between the tail graphic unit and the head graphic unit in the linear seamless graphic unit sequence, achieving visual closure of the ring space at the graphic level; output a continuous angular spectrum graphic sequence, each graphic being a visually completely closed and continuous seamless ring spectrum, with the visual quality at the head and tail connection points being completely consistent with the interior of the ring, marking the completion of the final transformation from discrete data to a continuous ring-shaped visual representation.

[0037] S123: Perform uniformity verification of rendering parameters for each ring graphic in the continuous angle spectrum graphic sequence. The ring graphics that pass the verification are associated and encapsulated according to the predefined station identifier and time scale label, and output as a wind direction angle distribution map atlas in the specified format.

[0038] This embodiment achieves the spatial transformation of wind direction and frequency data by mapping abstract data to graphical attributes, enabling discrete angular frequency values ​​to form a set of graphical elements with geometric positioning and visual intensity grading. Through temporal sorting and seamless stitching operations, a continuous angular spectrum graphic sequence is generated, fully preserving the distribution pattern of wind direction data over time. The uniformity verification and standardized encapsulation of the ring-shaped graphics ensure the comparability and systematic output of data across multiple time scales. Ultimately, a visualization atlas is formed that combines spatial orientation representation and frequency intensity presentation, realizing the cross-dimensional transformation of meteorological data from numerical values ​​to spatial forms.

[0039] S130: Using image recognition algorithms, stations with suspicious graphic features are selected from the wind direction angle distribution map set; historical data from different time periods are reviewed to generate wind direction angle distribution map sets for the stations, eliminating instantaneous interference; based on the confirmed suspicious graphic features, an anomaly classification system is established, and each type of anomaly is associated with potential physical causes; a diagnostic knowledge system containing the correspondence between anomaly map library, anomaly type, and possible causes is obtained.

[0040] Optionally, in some embodiments, the process of filtering stations with suspicious graphic features from the wind direction angle distribution map set specifically includes the following steps: S131: For each ring-shaped spectral map in the station wind direction angle distribution map set, extract a series of quantitative indicators describing the shape of the graphic along the circumference. The quantitative indicators are used to characterize the continuity of the ring contour, the smoothness of the undulation, and the presence of local peaks or depressions. Output a set of station image feature vectors. Each feature vector is a digital summary of the ring-shaped wind direction spectral map shape of a station, converting visual information into structured data that can be processed by the algorithm. S132: Based on a predefined set of quantitative rules for normal wind direction distribution patterns, compare and calculate the feature vector of each station's image one by one; if the calculated feature vector of any station's image deviates significantly from the normal pattern rules, it is marked as a preliminary suspicious target; generate a preliminary suspicious station list. S133: Represent the original ring spectrum corresponding to the stations in the initial suspicious station list, combine the preliminary abnormal feature vector calculation results, perform rule-assisted visual verification to eliminate the very few false alarms caused by the algorithm rules being too sensitive, and finally confirm those stations that do show clear abnormal graphic features; output the confirmed suspicious station list.

[0041] This embodiment extracts wind direction angle values ​​from raw time-series data files collected by meteorological stations and performs frequency statistics to obtain wind direction distribution characteristics, forming a wind direction frequency distribution dataset. A dedicated program is developed to transform the wind direction frequency distribution dataset into visual charts, intuitively displaying the wind direction distribution at each station to observe the continuity and smoothness of the wind direction distribution. Image recognition algorithms are used to filter out stations with suspicious graphic features, eliminating transient interference, and generating a wind direction angle distribution atlas for each station. By establishing an anomaly classification system, each type of anomaly is associated with possible physical causes, constructing a diagnostic knowledge system.

[0042] This embodiment automates and batch processes wind direction data, reducing the workload of manual review; it uses image recognition technology to quickly identify data anomalies, improving the accuracy of anomaly detection; it establishes a correspondence between anomalies and their causes, providing possible physical explanations for wind direction data anomalies, assisting in decision-making and problem investigation; it eliminates transient interference, ensuring the integrity and reliability of wind direction data; and it can systematically perform quality control on wind direction data, improving data accuracy and usability, and providing reliable data support for meteorological analysis and forecasting.

[0043] Due to the large number of meteorological stations and the heavy workload of data quality inspection, this invention utilizes a self-developed mini-program to quickly and batch-complete wind direction quality checks at meteorological stations, significantly improving work efficiency. It can not only promptly identify explicit wind direction data issues such as missing directions or unchanging wind directions, but also reveal implicit problems in the map: for example, the regular absence of a small angle (e.g., 1-3°) that might be difficult to detect from the 16 directions. Quality inspection can significantly improve the usability of wind direction data quality. The distribution map set can quickly identify the types and causes of wind direction data anomalies, greatly saving manpower and material resources for meteorological station data quality control and instrument malfunction handling and maintenance. The research results of this invention will be used to conduct a wind direction quality inspection and evaluation of meteorological stations throughout the province, providing a quality assessment and analysis report, and regular inspections and evaluations can be conducted in the future. The quality control process will be organized and summarized into a standard operating procedure, introduced into the PDCA cycle of the meteorological quality management system, and its promotion will be promoted.

[0044] This invention utilizes wind direction and wind speed data (minute-by-minute wind speed values) from 45 weather stations in Yueyang with wind-related elements as an example to establish a method for detecting abnormal or suspicious wind direction data. It employs a time-segmented statistical wind direction frequency distribution method to create a 0-360° wind direction distribution atlas with 1-3° intervals. Based on this atlas, stations with suspicious wind direction frequency distributions within a given time period are identified, thus determining whether abnormal wind direction observation data truly exists. Furthermore, this invention summarizes and categorizes abnormal wind direction data, analyzes the causes of various types of anomalies, and provides a basis for data quality control and instrument malfunction troubleshooting at weather stations. This invention is a self-evaluation report for the comprehensive performance evaluation of an innovative development project of a provincial meteorological bureau, task number: CXFZ2024-FZZX22; The team members involved in this invention are all front-line integrated observation operations and equipment support personnel, including one senior engineer (equipment chief researcher) and two associate senior engineers. Team members have a solid foundation in observation data quality inspection and extensive experience in meteorological instrument and equipment maintenance. They have already read a large amount of relevant literature and possess the ability to develop mini-programs. Some data has been collected and processed according to the project design concept. The 1° resolution wind direction frequency distribution map developed and produced is in its initial stages, laying the foundation for further research in the project.

[0045] This invention provides a wind direction distribution mapping mini-program: it checks wind direction data from meteorological stations at 1° intervals, enabling one-click batch mapping; it can quickly complete batch wind direction quality checks at meteorological stations, significantly improving work efficiency; it creates a wind direction distribution atlas: from the distribution atlas, the types and causes of wind direction data anomalies can be quickly identified, greatly saving manpower and material costs for meteorological station data quality control and instrument fault handling and maintenance; it generates a province-wide wind direction data quality assessment and analysis report: quality control of wind direction data from 2024 meteorological stations across the province revealed anomalies at 121 stations. Quality checks can significantly improve the quality of wind direction data; and it establishes a wind direction quality control operation process: simple and easy to operate, facilitating widespread application.

[0046] In September 2024, quality control at three meteorological stations in a certain city—P3545 (Jianxin Farm Meteorological Observatory in a certain district), P3592 (Xianggugang Meteorological Observatory in a certain district), and P3605 (Yingtian Water Conservancy Bureau Meteorological Observatory in a certain district)—indicated abnormal wind direction. After investigation and replacement of the wind direction sensors, a new quality control check was conducted in November, and the wind direction data had returned to normal. (See comparison chart below.) Figures 3-6 .

[0047] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0048] The above is an introduction to the method embodiments. The following describes the solution of the present invention further through device embodiments.

[0049] Figure 2 A block diagram of a wind direction quality control system 200 based on meteorological data files according to an embodiment of the present invention is shown. Figure 2 As shown, system 200 includes: The dataset acquisition module 210 is used to collect the original time-series data files of the weather station, which contain the wind direction angle values ​​recorded every minute in a time series; read and parse the time-series wind direction angle values ​​from the time-series data files, and perform wind direction frequency statistics on the entire range of 0-360° based on the instantaneous values ​​every minute to obtain the wind direction distribution characteristics at different time scales; thus obtaining the wind direction frequency distribution dataset. The visualization conversion module 220 is used to develop dedicated programs to automatically and batch convert wind direction frequency distribution datasets into visual charts. In the visual charts, the wind direction distribution of each station is presented in the form of a continuous angle spectrum. A normal distribution map should present a continuous and smooth distribution pattern, while a distribution map with data anomalies will show obvious abnormal graphic features such as missing angles, unnatural peaks, or discontinuities. The result is a wind direction angle distribution map set presented in the form of images, covering all meteorological stations and a specified time period. The association mapping module 230 is used to filter out stations with suspicious graphic features from the wind direction angle distribution map set through image recognition algorithm; to backtrack historical data of different time periods to generate wind direction angle distribution map sets of stations and eliminate instantaneous interference; to establish an anomaly classification system based on the confirmed suspicious graphic features, and to associate each type of anomaly with the potential physical cause; and to obtain a diagnostic knowledge system containing the correspondence between anomaly map library, anomaly type and possible cause.

[0050] The dataset acquisition module in this embodiment can efficiently collect and analyze raw wind direction data from weather stations, perform full-range statistical analysis of wind direction angle values, and obtain wind direction distribution characteristics at different time scales, providing an accurate wind direction frequency distribution dataset for analysis. The visualization conversion module automatically transforms complex wind direction frequency data into intuitive visual charts, presenting the wind direction distribution of each station in the form of a continuous angle spectrum, facilitating rapid identification of data anomalies and distribution characteristics. The association mapping module utilizes image recognition technology to filter out stations with suspicious graphic features, traces back historical data to eliminate transient interference, establishes an anomaly classification system and diagnostic knowledge system, and achieves rapid diagnosis of the causes of anomalies.

[0051] In summary, this embodiment can automatically and efficiently perform quality control and anomaly diagnosis on wind direction data from weather stations, improving data accuracy and reliability and providing strong support for meteorological analysis and forecasting. Furthermore, the application of visual charts and a diagnostic knowledge system also enhances the efficiency and accuracy of data quality control.

[0052] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the described module can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0053] According to embodiments of the present invention, the present invention also provides an electronic device and a readable storage medium.

[0054] Various embodiments of the systems and techniques described above in this invention can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0055] The program code used to implement the methods of the present invention can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0056] In the context of this invention, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0057] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including voice input, speech input, or tactile input).

[0058] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0059] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0060] It should be understood that the various forms of processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this invention can be achieved, and this invention does not impose any limitations on them.

[0061] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for wind direction quality control based on meteorological data files, characterized in that, The method comprises the following steps: The meteorological station collects original time series data files, which contain wind direction angle values recorded in time series every minute; Read and parse the time series wind direction angle values from the time series data file, and obtain the wind direction distribution characteristics at different time scales by counting the wind direction frequency in the full range of 0-360° according to the instantaneous value of each minute; Obtain the wind direction frequency distribution dataset; automatically and batch convert the wind direction frequency distribution dataset into the wind direction angle distribution atlas; Through image recognition algorithm, filter out the stations with suspicious graphic features from the wind direction angle distribution atlas; Trace back the historical data of different time periods, generate the wind direction angle distribution atlas of the station, and exclude transient interference; based on the confirmed suspicious graphic features, establish an abnormal classification system, and associate each type of abnormality with the potential physical cause; obtain the diagnostic knowledge system containing the corresponding relationship of abnormal atlas library- abnormal type- possible cause.

2. The meteorological data file based wind direction quality control method of claim 1, wherein, The process of automatically and batch converting the wind direction frequency distribution dataset into visual charts includes the following steps: Establish the rule of mapping abstract data to specific graphic attributes, assign a graphic representation attribute to the frequency value of each micro angle unit in the wind direction frequency distribution dataset; the graphic representation attribute corresponds to the position of the micro angle unit on the circumference; at the same time, the size of the frequency value is mapped to the high and low of a certain visual intensity dimension in the graph; output the wind direction frequency graphic element set; According to the order of the time series wind direction angle value from small to large, seamlessly splice and combine all graphic elements belonging to the same time scale wind direction frequency graphic element set to generate a continuous angle spectrum graphic sequence; the continuous angle spectrum graphic sequence is composed of multiple complete ring-shaped graphics, and each graphic displays the full-angle wind direction frequency distribution form at a specific time scale; Uniformity check of rendering parameters for each ring-shaped graphic in the continuous angle spectrum graphic sequence, associate and package the ring-shaped graphics that pass the check according to the predefined station identification and time scale label, and output the wind direction angle distribution atlas in the specified format.

3. The meteorological data file based wind direction quality control method of claim 2, wherein, The process of generating a continuous angle spectrum graphic sequence includes the following steps: According to the inherent position of each graphic element on the 0-360 degree circumference, the system is systematically sorted; based on the wind direction angle value itself, all graphic elements are reorganized into a ring-shaped data sequence in the order of starting from 0 degrees and increasing by 1-3 degrees as a step, and an ordered graphic element sequence is output; For any two adjacent graphic elements in the ordered graphic element sequence, check and process the transition of their graphic representation attributes at the connection boundary to generate a seamless graphic unit sequence; each graphic element in the seamless graphic unit seamlessly connects with its adjacent graphic elements before and after it; Map the linear seamless graphic unit sequence with the first and last ends connected to a ring-shaped visual space layout; process the connection boundary between the first and last graphic elements in the seamless graphic unit sequence, apply boundary smoothing processing, and form a complete ring-shaped graphic without starting and ending points; output the continuous angle spectrum graphic sequence.

4. The meteorological data file based wind direction quality control method of claim 3, wherein, The process of forming a ring-shaped graphic includes the following steps: Identify and extract the graphical representation attributes of the first and last graphic units in the seamless graphic unit; obtain the attribute state of the starting side of the first graphic unit and the attribute state of the ending side of the last graphic unit, and capture and record the two attribute states as a pair of specific boundary data; output the head-tail boundary state descriptor to define the visual connection condition to be processed at the ring-shaped closure; Take the captured head-tail boundary state descriptor as input to execute the calculation rule; the calculation rule generates a set of parameters for guiding graphic rendering, and the visual performance from the ending side of the tail graphic unit to the starting side of the head graphic unit in the linear seamless graphic unit sequence is consistent with the visual transition effect between any two adjacent graphic units in the linear seamless graphic unit sequence, realizing visual smoothness and continuity; generate ring-shaped connection transition parameters to generate a set of instructions for realizing seamless visual closure for the head-tail boundary; Arrange the linear seamless graphic unit sequence in a ring-shaped visual space, apply the instructions defined by the ring-shaped connection transition parameters, and finally render the connection area between the tail graphic unit and the head graphic unit in the linear seamless graphic unit sequence; output a continuous angular spectrum graphic sequence.

5. The meteorological data file based wind direction quality control method of claim 4, wherein, The process of generating ring-shaped connection transition parameters includes the following steps: From the generated linear seamless graphic unit sequence, analyze all angularly adjacent graphic unit pairs to implement the calculation rule, capture and formalize the smooth logic that has been verified to be effective in the sequence; output the graphic unit smooth transition rule set; Obtain the internal unit smooth transition rule set and the initial head-tail boundary state descriptor; input the head-tail boundary state as a pair of adjacent units into the internal unit smooth transition rule set; generate a ring-shaped closure transition strategy that realizes the smooth transition from the tail graphic unit state to the head graphic unit state by executing the calculation logic defined by the internal unit smooth transition rule set; Convert the calculated ring-shaped closure transition strategy into a series of control instructions recognized and executed by the graphic rendering engine to specify how to adjust the graphical representation attributes in the connection area between the head and tail graphic units to achieve visual smooth closure; output a structured ring-shaped connection transition parameter set of instructions.

6. The meteorological data file based wind direction quality control method of claim 5, wherein, The process of generating a ring-shaped closure transition strategy that realizes the smooth transition from the tail graphic unit state to the head graphic unit state includes the following steps: Reconstruct the two independent states captured in the head-tail boundary state descriptor and belonging to the two ends of the sequence into a virtual continuous structure in logic; define the ending side state of the tail graphic unit as the predecessor state in the new structure, and define the starting side state of the head graphic unit as the successor state in the continuous structure, logically forming a temporary data pair with the same data structure as any adjacent graphic unit pair in the linear seamless graphic unit sequence; output a simulated adjacent unit pair that is structurally equivalent to a standard internal adjacent unit pair; The simulation adjacent unit pair is substituted into the calculation engine defined by the internal unit smooth transition rule set, and a specific relationship is calculated and output according to the rules embedded in the calculation engine, describing the trajectory of how the graphical representation attributes should change continuously between the end side of the tail figure unit and the start side of the head figure unit; the attribute change path required to achieve visual smoothness at the head and tail boundaries is obtained; The attribute change path is evaluated to verify whether it can achieve self-consistency and continuity of visual attributes in the global range of the annular space after application; after verification, the annular closed transition strategy is output, including all the calculation logic and parameters required for seamless closure at the head and tail boundaries.

7. The meteorological data file based wind direction quality control method of claim 6, wherein, The process of calculating and outputting a specific relationship includes the following steps: Parse the attribute state predecessor value and successor value of all adjacent unit pairs in the internal unit smooth transition rule set, identify and abstract the core operation sequence used to calculate the intermediate state that is common to all unit pairs, and solidify the operation sequence as a program for calculating the intermediate state from the two end states; Fix the attribute state at the end side of the tail figure unit in the simulation adjacent unit pair as the starting input parameter of the program, and fix the attribute state at the start side of the head figure unit in the simulation adjacent unit pair as the termination input parameter of the program; complete parameter binding to convert the program into a single-variable program that only depends on the relative position within the transition interval; Within the relative position interval of 0% to 100%, determine the number and position of sampling points according to the preset rendering accuracy, call the single-variable program at each sampling point position to obtain the graphical attribute value of the sampling point, record all sampling points and their corresponding attribute values in order to form an ordered sequence of value pairs, and output the attribute change path.

8. The meteorological data file based wind direction quality control method of claim 1, wherein, The process of selecting stations with suspicious graphical features from the wind direction angle distribution set includes the following steps: For each annular spectrum in the wind direction angle distribution set of the station, a series of quantitative indicators describing the shape of the graph are extracted along the circumferential direction, and the quantitative indicators are used to describe the continuity, smoothness of fluctuations, and whether there are local peaks or concave features in the annular contour; output the set of station image feature vectors, each feature vector is a digital summary of the shape of the annular wind direction spectrum of a station, and the visual information is converted into structured data that can be processed by an algorithm; According to the pre-defined quantitative rule set for normal wind direction distribution shape, each station's station image feature vector is compared and calculated one by one; if the calculation result of any station's station image feature vector deviates significantly from the normal shape rule, it is marked as a preliminary screening suspicious target; generate a preliminary screening suspicious station list; The original annular spectrum of the station in the preliminary screening suspicious station list is presented again, combined with the preliminary abnormal feature vector calculation result, and a rule-based visual review is performed, and a list of confirmed suspicious stations is output.

9. The meteorological data file based wind direction quality control method of claim 1, wherein, The visualization conversion module is used for developing a special program to automatically and in batches convert the wind direction frequency distribution dataset into visual charts, in which the wind direction distribution of each station is presented in the form of a continuous angle spectrum, and a normal distribution chart should present a continuous and smooth distribution form, while a distribution chart with data abnormality presents obvious angle missing, unnatural peaks or discontinuity and other abnormal graphical features. The wind direction angle distribution chart set covering all weather stations and a specified period is obtained in the form of pictures.

10. A wind direction quality control system based on meteorological data files for implementing the wind direction quality control method based on meteorological data files according to any one of claims 1 to 9, characterized in that, The method comprises the following steps: The dataset acquisition module is used for collecting original time series data files of weather stations, which contain wind direction angle values recorded in time series every minute. The time series wind direction angle values are read and parsed from the time series data files, the wind direction frequency statistics are performed on the full range of 0-360° according to the instantaneous values every minute, and the wind direction distribution characteristics at different time scales are obtained. The wind direction frequency distribution dataset is obtained. The visualization conversion module is used for developing a special program to automatically and in batches convert the wind direction frequency distribution dataset into visual charts, in which the wind direction distribution of each station is presented in the form of a continuous angle spectrum, and a normal distribution chart should present a continuous and smooth distribution form, while a distribution chart with data abnormality presents obvious angle missing, unnatural peaks or discontinuity and other abnormal graphical features. The wind direction angle distribution chart set covering all weather stations and a specified period is obtained in the form of pictures. The correlation mapping module is used for screening out stations with suspicious graphical features from the wind direction angle distribution chart set through an image recognition algorithm. The historical data of different periods are traced back to generate the wind direction angle distribution chart set of the station, and transient interference is excluded; based on the confirmed suspicious graphical features, an abnormal classification system is established, each type of abnormality is associated with a potential physical cause, and a diagnostic knowledge system containing the corresponding relationship of the abnormal atlas library, the abnormal type and the possible cause is obtained. The visualization conversion module is used for developing a special program to automatically and in batches convert the wind direction frequency distribution dataset into visual charts, in which the wind direction distribution of each station is presented in the form of a continuous angle spectrum, and a normal distribution chart should present a continuous and smooth distribution form, while a distribution chart with data abnormality presents obvious angle missing, unnatural peaks or discontinuity and other abnormal graphical features. The wind direction angle distribution chart set covering all weather stations and a specified period is obtained in the form of pictures. The correlation mapping module is used for screening out stations with suspicious graphical features from the wind direction angle distribution chart set through an image recognition algorithm. The historical data of different periods are traced back to generate the wind direction angle distribution chart set of the station, and transient interference is excluded; based on the confirmed suspicious graphical features, an abnormal classification system is established, each type of abnormality is associated with a potential physical cause, and a diagnostic knowledge system containing the corresponding relationship of the abnormal atlas library, the abnormal type and the possible cause is obtained.

Images