Ground meteorological element extremum data interaction analysis system based on cloud technology

Abstract

The invention provides a ground meteorological element extremum data interaction analysis system based on a cloud technology, and relates to the technical field of meteorological information, and the system comprises a cloud storage module which is used for storing high-quality source data after quality control cleaning and carrying out the preprocessing and analysis of the source data, and obtaining analysis data for service; and the cloud service module is used for carrying out data communication among the modules and carrying out services such as user request analysis, identity verification, target data retrieval, log updating, load balancing and data transmission. And the cloud application module is used for realizing interactive operation, data downloading and classified image-text display of target data. The meteorological extreme value analysis system is developed on the basis of a meteorological big data cloud platform (sky engine) of the China Meteorological Administration, and the problems that a meteorological extreme value analysis system developed on the basis of a relational database is general in performance, does not support multi-person high-concurrency operation, cannot perform real-time interactive display, does not support remote operation and is high in labor cost consumption are solved.

Description

Technical Field

[0001] The present invention relates to the field of meteorological information analysis and application technology, and in particular to a ground meteorological element extreme value data interactive analysis system based on cloud technology. Background Art

[0002] A unit once used the ADO database to compile a meteorological element extreme value statistical system. The system required the purchase and maintenance of a large amount of hardware resources, but only provided local operation, did not support simultaneous high-frequency operation by multiple people, did not support remote operations, and its capacity and computing power were limited by the cost of hardware resources. It also did not have the ability to automatically generate analytical images.

[0003] Traditional relational databases will have performance bottlenecks when processing the sorting statistics of large-scale data, especially in complex business scenarios such as interactive analysis of extreme values ​​of meteorological elements, which require high-frequency operations such as multi-table association and aggregation. As the query period increases and the number of sites increases, the analysis time will increase significantly.

[0004] Traditional meteorological extreme value services are mostly conducted manually for data analysis and manual production of charts and texts. The relevant business systems do not have the function of real-time analysis and display of target data, and engineers with meteorological expertise are required to complete the analysis and display work. The labor cost is high, the time is long, and there is a high degree of duplication of labor. It cannot fully meet the current service needs of modernization, informatization, and intensiveness of the meteorological system. Summary of the invention

[0005] In order to overcome the deficiencies of the prior art, the purpose of the present invention is to provide a ground meteorological element extreme value data interactive analysis system based on cloud technology, which has the ability of flexible, convenient and efficient interactive analysis and integrated display of massive meteorological extreme value data. The present invention is developed based on the meteorological big data cloud platform (Tianqing) of the China Meteorological Administration, and solves the problems of the existing meteorological extreme value analysis system developed based on relational database, such as general performance, no support for multi-person high concurrent operation, no real-time interactive display, no support for remote operation, and high labor cost consumption, and meets the current service needs of modernization, informatization and intensiveness of the meteorological system.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] A cloud-based interactive analysis system for extreme data of ground meteorological elements, including:

[0008] Interconnected cloud storage modules, cloud service modules, and cloud application modules;

[0009] The cloud storage module is divided into a data storage bottom layer and a data storage processing layer according to the vertical layered storage technology solution, and is deployed in a cloud analytical database. The data storage bottom layer is used to store historical data sources, including: hourly value data, daily value data, monthly value data, cumulative annual value data and management data of more than 2,400 ground automatic weather stations in China; the data storage processing layer is used to perform deviation, grading, sorting and filtering on the storage source data to obtain sub-theme analysis data; the sub-theme analysis data includes: single-station historical ranking sequence, single-factor historical ranking sequence, single-station time segment ranking sequence, single-factor time segment ranking sequence, single-factor statistical sequence. The cloud service module is deployed on the cloud server, and is used to query the sub-theme analysis data according to current business needs, obtain target data and transmit the target data to the cloud application module or open data download interface, and carry out load balancing, user information verification and system log update at the same time. The cloud application module is deployed on the cloud server, and is used to obtain business needs, and perform graphic rendering and interactive display according to the target data.

[0010] Preferably, the data storage bottom layer is a storage module, which stores the original data sources of ground meteorological elements such as temperature, precipitation, extreme wind, snow depth, etc.

[0011] The data storage processing layer includes:

[0012] A filtering module, a data first sorting module, a second sorting module, a third sorting module, a fourth sorting module, a deviation module, a grading module and a station network information module, all of which are connected to the data storage bottom layer. The data filtering module is used to clean the storage data source to obtain the preprocessed storage data source; the first sorting module is used to sort the preprocessed storage data source for all elements of a single station to obtain a single station historical ranking sequence; the second sorting module is used to sort the single station historical ranking sequence in the smallest area with the station network information module to obtain the smallest area single element historical ranking sequence; the third sorting module is used to sort and analyze the preprocessed storage data source by day, ten days, month and quarter to obtain a single station time segment ranking sequence; the fourth sorting module is used to carry out regional sorting analysis on the single station time segment ranking sequence and the single station historical ranking sequence in conjunction with the station network information module to obtain a regional historical ranking sequence and a regional time segment ranking sequence; the deviation module is used to carry out regional deviation analysis on the single station time segment ranking sequence in conjunction with the station network information to obtain a time segment regional deviation ranking; the grading module is used to perform graded sorting on the preprocessed storage data source according to the element value level to obtain an extreme value ranking according to the element level. All modules are developed based on the algorithm library and processing pipeline of the China Meteorological Administration's meteorological big data cloud platform (TianQing), realizing the unified management of meteorological data processing algorithms.

[0013] Preferably, the cloud service module includes:

[0014] A data analysis module, a data query module, a data processing module, a data transmission module, a load balancing module, an identity authentication module and a log monitoring module connected to the data storage and processing layer;

[0015] The data analysis module is used to analyze user operation parameters to obtain business requirements that can be understood by the system; the data query module is used to perform data query on the analysis data of the sub-topics according to the business requirements in the data storage and processing layer to obtain target data; the data processing module is used to carry out target data communication between the cloud application module and the cloud storage module; the data transmission module is used to provide a data transmission interface and provide target data transmission services; the load balancing module is used to reasonably allocate cloud server resources to improve operating efficiency and fault tolerance; the identity authentication module is used to authenticate the visiting user and return authentication information; the log monitoring module is used to feedback the system status and update the system log.

[0016] Preferably, the cloud application module includes:

[0017] Display module and interactive module;

[0018] The display module is used to render and interactively display the target data; the interactive module is used to obtain the latest business requirements.

[0019] Preferably, the display module comprises:

[0020] Geoinformation mapping unit, historical extreme value display unit, process extreme value display unit, element level display unit, anomaly analysis display unit, space display unit, real-time statistics display unit and text chart display unit;

[0021] The display module is developed in the form of components to achieve the reuse of front-end functions. The geospatial mapping unit is used to carry out functions such as map making, base map clipping, base map zooming, and display the completed map; the historical extreme value display unit is used to obtain the super-historical extreme value situation and historical extreme value ranking of the target data and display it; the process extreme value display unit is used to obtain the super-historical extreme value situation and process extreme value ranking of the target data and display it; the element level display unit is used to obtain the element level ranking of the target data and display it; the deviation analysis display unit is used to obtain the deviation analysis ranking of the target data and display it; the space display unit is used to display the spatial distribution of the target data; the real-time statistics display unit is used to obtain the time period extreme value of the target data and display it; the text and chart display unit is used to make the target data into a chart or template text and display it, where the chart includes administrative coloring layer class, network wind vane layer class, grid data coloring layer class, icon layer class, tile layer class, bar chart, line chart, scatter chart, etc.

[0022] The present invention discloses the following technical effects:

[0023] The present invention provides a ground meteorological element extreme value data interactive analysis system based on cloud technology, including: a cloud storage module, a cloud service module, and a cloud application module that are interconnected. The cloud storage module is divided into a data storage bottom layer and a data storage processing layer according to a vertical layered storage technology scheme. The data storage bottom layer is used to store high-quality source data after quality control cleaning; the data storage processing layer is used to pre-process and analyze the source data to obtain stored analysis data. The cloud service module is used to carry out services such as user request analysis, identity authentication, target data retrieval, log update, load balancing, data transmission, and data communication between modules. The cloud application module is used to realize interactive operations, data downloads, and classified graphic display of target data. The cloud storage module carries out data storage and analysis based on a cloud-based analytical database, relying on the analytical database's large-scale parallel computing, massive data distributed compression, efficient loading and other technical features, to achieve the completion of two billion data tables within two seconds. The full-volume aggregate query of tens of billions of data is realized through the Tianqing processing pipeline, meeting the high concurrency and high timeliness requirements of the interactive analysis and display of meteorological information service business. The cloud service module carries out data communication and services based on the cloud server. Because the cloud service module has technical characteristics such as resource integration, high scalability, automated service deployment and network access, it supports the system to be deployed in multiple locations at the same time, and realizes the effect of concurrent execution of multi-user operations. At the same time, the load balancing technology reasonably allocates cloud server resources to avoid performance degradation caused by single point overload and service interruption caused by single point failure, improves the efficiency, security and flexibility of the system, and supports high-frequency query operations of multiple people at the same time. The cloud application module runs on the cloud server, and users can access the system through the Internet browser of any device. There is no need to install professional software or build and maintain hardware equipment locally. The interactive operation of each preset unit is simple and clear, which reduces the technical cost, labor cost and equipment maintenance cost of users to obtain target meteorological extreme value data. The present invention realizes physical isolation of original data and user operations while quickly responding to user query requests through multiple modules interconnected and interactively collaborated, and ensures the security of original data. The present invention fully considers the future development function construction needs when designing, reserves new function interfaces, and has strong backward development compatibility. This invention is developed based on TianQing and fully responds to the intensive construction goals of the China Meteorological Administration. In the future, as time goes by, the amount of statistical data required will increase. The system can further improve the analysis performance by expanding the cluster without the need for additional code patches and manual maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0025] Figure 1 A schematic diagram of the business process of a ground meteorological element extreme value data interactive analysis system based on cloud technology provided by an embodiment of the present invention;

[0026] Figure 2 A schematic diagram of the structure of a system for interactive analysis of extreme data of ground meteorological elements based on cloud technology provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0029] like Figure 1 As shown, the present invention provides a ground meteorological element extreme value data interactive analysis system based on cloud technology, comprising:

[0030] Interconnected cloud storage modules, cloud service modules and cloud application modules;

[0031] The cloud storage module includes a data storage bottom layer for storing historical data sources and a data storage and analysis layer for performing deviation, grading, sorting and filtering on the stored source data to obtain the data storage and analysis data of the sub-theme. Among them, the data processing processes such as deviation, grading, sorting and filtering are realized by the algorithm of the Tianqing processing pipeline. The stored source data includes: hourly value data, daily value data, monthly value data, cumulative annual value data, statistical analysis data and management data of more than 2,400 ground automatic weather stations in China; the stored data ranking sequence includes: single station historical ranking sequence, single factor historical ranking sequence, time segment ranking sequence, statistical value time segment ranking sequence and station network information. The cloud service module is used to obtain the target data according to the sub-theme analysis data and current business needs, and verify user information and update system logs. The cloud service module also updates the business needs in real time according to the cloud application module, and transmits the target data to the cloud application module, and the cloud application module is used to display and obtain the latest business needs according to the target data.

[0032] Specifically, the data storage bottom layer is used to store historical raw data, including: hourly precipitation, daily cumulative precipitation (daily boundary is 08:00 or 20:00) data, daily maximum temperature, daily minimum temperature, daily average temperature, daily maximum wind speed, daily minimum average relative humidity, hourly visibility, hourly snow depth, China's ground standard climate value data set from 1991 to 2020, etc. of more than 2,400 ground automatic weather stations in China, and reserve storage space and data interface for other ground meteorological elements. The data storage processing layer is used to store analytical data, which is obtained by pre-processing such as deviation, grading, sorting, filtering, etc. by classifying historical raw data. The analytical data includes: single-station single-element historical ranking sequence, single-element (region) historical ranking sequence, time segment region single-element ranking sequence and station network information module. The cloud service module is used to carry out data communication and services. Communication includes data communication between different modules and data communication between different functional units of different modules. Services include data analysis, data query, data processing, data transmission, load balancing, identity authentication and log monitoring update. The user logs in to the interface of the system cloud application module through a web browser and submits an operation request. The cloud service data processing module captures the user identity parameters, request parameters, and system status parameters. The identity authentication module verifies the user identity parameters. After verification, the data analysis module conducts query and data extraction of the target data according to the request parameters, including the meteorological extreme value ranking analysis of different regional ranges, different time periods, and different ground meteorological elements. The query results are communicated to the application layer through the data processing module, or the data download interface is opened to the user through the data transmission module. The cloud application module is used to classify and interactively display the analysis results of various ground meteorological element extreme value data, including real-time element value ranking sequences of elements such as temperature, precipitation, and extreme winds, statistical charts of the number of stations exceeding historical extreme values, station time series charts of important weather processes such as cold waves, high temperature heat waves, typhoons, and autumn rains in western China, temperature and precipitation deviation ranking tables, and real-time meteorological element graphic materials of concern to the meeting. Take the user's request to query "the maximum hourly precipitation in February in Beijing over the years" as an example:

[0033] The system obtains the user's query operation request through the interactive module of the cloud application module, and performs the query operation through the service layer: retrieves the data in the hourly precipitation (Beijing) historical ranking sequence that meets the time condition in February, the cloud service data processing module picks up the target result returned by the data processing layer, and communicates with the cloud application module, the display module of the cloud application module obtains the above-mentioned returned target result, and produces "Beijing February Maximum Precipitation Extreme Value Interactive Analysis Table TOP200" or "Beijing (each station) February Maximum Hourly Precipitation Historical Extreme Value Bar Chart" or "Beijing (each station) February Maximum Hourly Precipitation Historical Extreme Value Spatial Distribution Chart" and other charts, and displays them on the corresponding interface of the web browser used by the user. The above charts can perform simple interactive operations such as selecting the type of display chart, selecting the numerical sorting method in the chart, and selecting the elements to be displayed in the chart.

[0034] Specifically, the system provides hourly analysis of ground meteorological elements across the country. In addition to commonly used elements such as temperature (TEM), precipitation (PRE), and wind (WIN), it also expands ground meteorological observation elements such as snow depth (GSS), visibility (VIS), and dust, and reserves access interfaces and storage space for other meteorological elements. Analysis and sorting of ultra-historical extremes, historical extremes of the same period, process extremes, and actual extremes can be carried out by topic. The analysis results are connected to the special column and the consultation material column in real time, and graphic documents that can be used for business consultations and decision-making materials are immediately generated.

[0035] System structure Figure 2 The back-end (i.e., data end) data is stored based on the analytical database of the TianQing big data cloud platform. The service is implemented through timed scheduling. Management data such as system logs and user behaviors are stored in management data tables for easy access by management personnel at any time. The front-end (i.e., display end) implements multi-functional applications based on the Web portal. The modular design improves the portability and scalability of the system. Nginx is used as a reverse proxy to achieve load balancing of requests and hidden protection of the back-end server. The query and analysis layer performs analysis on the processing layer of the database based on the input parameter query for the HTTP request sent by the front-end, and obtains the analysis results through the interface.

[0036] Furthermore, the data storage bottom layer is a storage module, which is used for the original historical data source.

[0037] Specifically, the original historical data source is the high-quality original observation sequence of ground meteorological stations stored on the TianQing big data cloud platform and obtained through three-level quality control.

[0038] Furthermore, the data storage processing layer includes:

[0039] A filtering module, a data first sorting module, a second sorting module, a third sorting module, a fourth sorting module, an anomaly module, a grading module and a station network information module, all of which are connected to the data storage bottom layer;

[0040] The station network information module is used to conduct analysis of the stations and their regions and obtain the ranking sequence of elements in the specified area.

[0041] Specifically, the data filtering module is used to clean the storage data source, retain the data records with correct quality control results, and obtain the pre-processed storage data source. The first sorting module is used to regularly sort the pre-processed storage data source for single-station full-factors to obtain a single-station historical ranking sequence. The second sorting module is used to perform single-factor minimum area sorting on the single-station historical ranking sequence in conjunction with the station network information module to obtain a minimum area single-factor historical ranking sequence. The third sorting module is used to perform single-station day, ten-day, monthly, and quarterly sorting analysis on the pre-processed storage data source to obtain a single-station time segment ranking sequence. The fourth sorting module is used to sort the pre-processed storage data source in conjunction with the station network information module. The single-station time segment ranking sequence and the single-station historical ranking sequence are used to carry out single-factor regional ranking analysis of administrative regions, river basins, and regions to obtain regional historical ranking sequences and regional time segment ranking sequences. The anomaly module is used to carry out regional anomaly analysis on the single-station time segment ranking sequence in conjunction with the station network information to obtain regional anomaly rankings. The classification module is used to carry out hierarchical sorting of the preprocessed stored data sources according to the element value level to obtain extreme value rankings according to the element level. The station network information module is used to associate the observation data source and station information, including station number, station longitude and latitude, station potential height, station type, station start observation time, station administrative region, station river basin, and station region. This step is implemented through TianQing's algorithm library and processing pipeline to ensure the uniformity and standardization of meteorological algorithms.

[0042] Furthermore, the cloud service module includes:

[0043] The cloud service module includes:

[0044] A data query module, a data processing module, a data analysis module, a data transmission module, an identity authentication module and a log monitoring module, all of which are connected to the data storage processing layer;

[0045] The data query module is used to perform data query on the analysis data of the sub-topic in the data storage and processing layer according to the user's business needs to obtain the target data. The data processing module is used to carry out target data communication between the cloud application module and the data storage and processing layer. The data analysis module is used to analyze the target data request information to obtain the target data. The data transmission module is used to provide a data transmission interface. The identity authentication module is used to authenticate the accessing user and return the authentication information. The log monitoring module is used to update the system log.

[0046] Specifically, with the data storage and processing layer as the source, each surface element table is updated according to the business needs (such as time value, daily value, monthly value, and cumulative annual value) according to five major themes, namely "single station historical extreme value", "single station process (time segment) extreme value", "single element historical extreme value", "single element process (time segment) extreme value", and "statistical value". Interactive analysis of meteorological extreme values ​​in the whole country, administrative divisions, and river basins is carried out respectively. This is the cloud service module. The sorting range of the latest historical extreme value ranking sequence, historical extreme value ranking sequence, and real-time ranking sequence is divided into single station and region. The former directly uses the analysis data of the single station theme, and the latter conducts regional sorting through the associated station network table view to obtain meteorological extreme value ranking sequences in different regions and different spatial resolutions such as the whole country, administrative divisions, and river basins. This step is a sub-theme data extreme value analysis technology. It does not need to store the extreme value sorting of all provinces separately, but calculates on demand, which improves the flexibility of obtaining regional extreme value sorting data and saves storage costs and calculation time.

[0047] Furthermore, user identity authentication is completed on the front end, and the user's query operation and data request are transmitted to the cloud service module. The table in the analysis layer is queried, and the results are returned in json format (including the table name, field, index and other parameters of the result). The modular design enables the system to have other additional functions such as identity authentication and data transmission. The system can quickly respond to Web requests. This step can not only quickly obtain extreme value target data, but also solve the problem that traditional extreme value databases cannot perform real-time process extreme value interactive analysis.

[0048] Display module and interactive module;

[0049] The display module is used to display the target data, and the interaction module is used to obtain the latest business requirements.

[0050] Furthermore, the display module includes:

[0051] Historical extreme value display unit, process extreme value display unit, element level display unit, deviation analysis display unit, spatial display unit, real-time statistics display unit and text chart display unit;

[0052] The historical extreme value display unit is used to query the historical extreme values ​​of the user needs and display them, the process extreme value display unit is used to obtain the process extreme values ​​of the target data and display them, the element level display unit is used to obtain the element level of the target data and display them, the deviation analysis display unit is used to display the deviation analysis data in the target data, the belonging space display unit is used to display the spatial distribution of the target data, the real-time statistics display unit is used to display the real-time statistical data in the target data, and the text and chart display unit is used to make the target data into charts and display them.

[0053] More specifically, the historical extreme value display unit is used for querying and displaying the number of stations and times of super historical extreme values ​​and super historical extreme values ​​(historical same period month, historical same period ten days) of daily precipitation, high temperature, low temperature, extreme wind, minimum average relative humidity, hourly precipitation, snow depth and other elements, statistics and display of precipitation, high temperature, low temperature, extreme wind, snow depth and other commonly used ground meteorological elements in the selected period, including real-time ranking, super historical extreme value ranking, super same period extreme value ranking, time series change diagram of the station where the maximum value of the specified element is located, etc., and retains the interface of the newly added ground meteorological elements. The extreme value interactive analysis module is used for querying and displaying the historical extreme values, process extreme values, element level statistics, daily station number statistics, anomaly ranking, and ranking of China's ground standard climate values ​​of ground meteorological elements, and retains the interface of the newly added ground meteorological elements and the newly added query function. The real-time statistics module is used for querying and displaying the extreme value sorting of temperature, precipitation, extreme wind, visibility, snow depth and other meteorological elements in any period and any area, and retains the interface of the newly added ground meteorological elements. The consultation material module is used for querying and displaying extreme values ​​of real-time precipitation, real-time low temperature, real-time extreme wind, high temperature heat wave, cold wave, real-time temperature drop and other topics, and retains the query and display interface of newly added topics.

[0054] Specifically, the display component library uses the target data of the cloud service module as the source to carry out real-time mapping, table building, WebGIS rendering, etc. This method not only lowers the professional and technical threshold of business personnel, solves the problem that professional APP or software programs must be installed to use the functions, but also solves the problem that the extreme value interactive analysis results cannot be visualized in real time.

[0055] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0056] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A cloud-based ground meteorological element extreme value data interactive analysis system, characterized in that: Interconnected cloud storage modules, cloud service modules, and cloud application modules; The cloud storage module includes a data storage bottom layer and a data storage processing layer, and is deployed in a cloud analytical database; The data storage bottom layer is used to store historical data sources, and the data storage processing layer is used to perform deviation, grading, sorting and filtering on the stored source data to obtain analytical data by subject; the analytical data by subject include: single-station historical ranking sequence, single-factor historical ranking sequence, single-station time segment ranking sequence, single-factor time segment ranking sequence, single-factor statistical sequence. The cloud service module is deployed on the cloud server to query the analytical data of the sub-subject according to current business needs, obtain target data and transmit the target data to the cloud application module or open data download interface, and carry out load balancing, user information verification and system log update at the same time. The cloud application module is deployed on the cloud server to obtain business needs, and perform graphic rendering and interactive display according to the target data.

2. According to the cloud technology-based ground meteorological element extreme value data interactive analysis system of claim 1, it is characterized in that: The data storage processing layer includes: a filtering module, a data first sorting module, a second sorting module, a third sorting module, a fourth sorting module, an anomaly module, a classification module and a station network information module, all of which are connected to the data storage bottom layer; The data filtering module is used to clean the storage data source to obtain the preprocessed storage data source; the first sorting module is used to sort the preprocessed storage data source for all elements of a single station to obtain a single station historical ranking sequence; the second sorting module is used to sort the single station historical ranking sequence in the smallest area with the station network information module to obtain the smallest area single element historical ranking sequence; the third sorting module is used to sort and analyze the preprocessed storage data source by day, ten days, month and quarter to obtain a single station time segment ranking sequence; the fourth sorting module is used to carry out regional sorting analysis on the single station time segment ranking sequence and the single station historical ranking sequence in conjunction with the station network information module to obtain a regional historical ranking sequence and a regional time segment ranking sequence; the deviation module is used to carry out regional deviation analysis on the single station time segment ranking sequence in conjunction with the station network information to obtain a time segment regional deviation ranking; the grading module is used to carry out graded sorting on the preprocessed storage data source according to the element value level to obtain an extreme value ranking sequence according to the element level, and the station network information module is used to carry out station and region analysis to obtain an element ranking sequence of the specified area.

3. The cloud-based ground meteorological element extreme value data interactive analysis system according to claim 1 is characterized in that: The cloud service module includes: A data analysis module, a data query module, a data processing module, a data transmission module, a load balancing module, an identity authentication module and a log monitoring module connected to the data storage and processing layer; The data analysis module is used to analyze user operation parameters to obtain business requirements understood by the system; the data query module is used to conduct data query on the analysis data of the sub-topics according to the business requirements in the data storage and processing layer to obtain target data; the data processing module is used to carry out target data communication between the cloud application module and the cloud storage module; the data transmission module is used to provide a data transmission interface and provide target data transmission services; the load balancing module is used to reasonably allocate cloud server resources to improve operating efficiency and fault tolerance; the identity authentication module is used to authenticate the visiting user and return authentication information; the log monitoring module is used to feedback the system status and update the system log.

4. The cloud-based ground meteorological element extreme value data interactive analysis system according to claim 1, characterized in that: The cloud application module includes: Display module and interactive module; The display module is used to render and interactively display the target data; the interactive module is used to obtain the latest business requirements.

5. The cloud-based ground meteorological element extreme value data interactive analysis system according to claim 4 is characterized in that: The display module comprises: Historical extreme value display unit, process extreme value display unit, element level display unit, deviation analysis display unit, spatial display unit, real-time statistics display unit and text chart display unit; The historical extreme value display unit is used to obtain and display the ultra-historical extreme value situation and historical extreme value ranking of the target data; the process extreme value display unit is used to obtain and display the ultra-historical extreme value situation and process extreme value ranking of the target data; the element level display unit is used to obtain and display the element level ranking of the target data; the deviation analysis display unit is used to obtain and display the deviation analysis ranking of the target data; the space display unit is used to display the spatial distribution of the target data; the real-time statistics display unit is used to obtain and display the extreme values ​​of the target data in different time periods; the text and chart display unit is used to make the target data into a chart or a template text and display it.

Images