A cloud-based interactive analysis system for extreme data of ground meteorological elements

Abstract

The present invention provides a ground meteorological element extreme value data interactive analysis system based on cloud technology, which relates to the field of meteorological information technology. The system includes: a cloud storage module for storing high-quality source data after quality control cleaning and pre-processing and analyzing the source data to obtain analysis data for service. The cloud service module is used to carry out data communication between modules, as well as to carry out user request analysis, identity authentication, target data retrieval, log update, load balancing, data transmission and other services. The cloud application module is used to realize interactive operation, data download and classified graphic display of target 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 meteorological extreme value analysis systems developed based on relational databases, such as general performance, support for multi-person high concurrent operation, inability to interactively display in real time, support for remote operations, and high labor cost consumption.

Description

Technical Field

[0001] The present invention relates to the field of meteorological information analysis and application technology, and in particular to a cloud-based system for interactive analysis of extreme value data of ground meteorological elements. 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 face performance bottlenecks when processing the sorting and statistics of large-scale data. This is especially true in complex business scenarios such as interactive analysis of extreme values ​​of meteorological elements, which require multi-table association and aggregation operations with high frequency. As the query period increases and the number of sites increases, the analysis time increases significantly.

[0004] Traditional meteorological extreme value services rely heavily on manual data analysis and chart creation. These systems lack real-time analysis and display capabilities for target data, requiring engineers with meteorological expertise to perform these tasks. This process is labor-intensive, time-consuming, and involves significant duplication of effort, failing to fully meet the current demands for modern, information-based, and intensive meteorological services. Summary of the Invention

[0005] In order to overcome the shortcomings of the prior art, the purpose of the present invention is to provide a cloud-based interactive analysis system for extreme value data of ground meteorological elements, which has the ability to flexibly, conveniently and efficiently interactively analyze and integrate the display of massive amounts of meteorological extreme value data. The present invention is developed based on the meteorological big data cloud platform (TianQing) of the China Meteorological Administration. It solves the problems of the existing meteorological extreme value analysis system developed based on relational databases, such as general performance, lack of support for multi-person high-concurrency operations, inability to interactively display in real time, lack of support for remote operations, and high labor costs, and meets the current service needs of the modernization, informatization and intensification 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 value 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 a vertical layered storage technology solution, and is deployed on a cloud-based analytical database. The data storage bottom layer is used to store historical data sources, including: hourly data, daily data, monthly data, cumulative annual data, and management data from more than 2,400 Chinese ground-based automatic weather stations; the data storage processing layer is used to perform deviation, grading, sorting, and filtering on the stored 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, and single-factor statistical sequence. The cloud service module is deployed on a 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 a cloud application module or an open data download interface, while carrying out load balancing, user information verification, and system log updates. The cloud application module is deployed on a cloud server and is used to obtain business needs and perform graphic rendering and interactive display based on the target data.

[0010] Preferably, the data storage bottom layer is a storage module that 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 perform data cleaning on the storage data source to obtain a preprocessed storage data source; the first sorting module is used to perform single-station full-factor sorting on the preprocessed storage data source 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 daily, ten-day, monthly, and quarterly sorting analysis on the preprocessed storage data source to obtain a single-station time segment ranking sequence; the fourth sorting module is used to perform 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 perform 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 factor value level to obtain an extreme value ranking according to the factor 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 and obtain business requirements that can be understood by the system; the data query module is used to conduct data query on the analysis data of the sub-topic according to the business requirements in the data storage 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 needs.

[0019] Preferably, the display module includes:

[0020] Geoinformation mapping unit, 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;

[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 production, 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 them; 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 them; the element level display unit is used to obtain the element level ranking of the target data and display them; the deviation analysis display unit is used to obtain the deviation analysis ranking of the target data and display them; the affiliated 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-divided 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 direction pole 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 cloud-based interactive analysis system for extreme value data of ground meteorological elements, comprising: an interconnected cloud storage module, a cloud service module, and a cloud application module. The cloud storage module is divided into a data storage bottom layer and a data storage processing layer according to a vertically layered storage technology solution. The data storage bottom layer is used to store high-quality source data after quality control and cleaning; the data storage processing layer is used to preprocess and analyze the source data to obtain stored analytical data. The cloud service module is used to perform services such as user request analysis, identity authentication, target data retrieval, log updates, load balancing, and data transmission, as well as to carry out data communication between modules. The cloud application module is used to implement interactive operations, data downloads, and classified graphical and textual displays of target data. The cloud storage module performs data storage and analysis based on a cloud-based analytical database. Leveraging the analytical database's technical features such as large-scale parallel computing, massive data distributed compression, and efficient loading, it can complete a related query between two tables with tens of billions of data records within two seconds. Through the Tianqing processing pipeline, it can achieve full-scale aggregate query of tens of billions of data records, meeting the high concurrency and high timeliness requirements of the interactive analysis and display of meteorological information services. The cloud service module carries out data communication and services based on the cloud server. Because the cloud service module has technical features such as resource integration, high scalability, automated service deployment and network access, it supports the system to be deployed simultaneously in multiple locations, achieving the effect of concurrent execution of multi-user operations. At the same time, load balancing technology rationally allocates cloud server resources, avoids 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 by 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 operations of each preset unit are simple and clear, reducing 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 the interconnection and interaction of multiple modules, thereby ensuring 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 and the amount of statistical data required increases, the system can further improve 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 following briefly introduces the drawings required for use in the embodiments. 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 any creative work.

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

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

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts 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 cloud-based system for interactive analysis of extreme value data of ground meteorological elements, including:

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

[0031] The cloud storage module includes a data storage base layer for storing historical data sources and a data storage and analysis layer for leveling, grading, sorting, and filtering the stored source data to generate thematically analyzed data. The data processing processes, including leveling, grading, sorting, and filtering, are implemented using the TianQing processing pipeline algorithm. The stored source data includes hourly, daily, monthly, and cumulative annual data, statistical analysis data, and management data from over 2,400 ground-based automatic weather stations in China. The stored data ranking sequences include single-station historical ranking sequences, single-factor historical ranking sequences, time-segmented ranking sequences, statistical value time-segmented ranking sequences, and station network information. The cloud service module is used to obtain target data based on thematically analyzed data and current business needs, verify user information, and update system logs. The cloud service module also updates business needs in real time based on the cloud application module and transmits the target data to the cloud application module, which then displays the target data and obtains the latest business needs.

[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, and the China Ground Standard Climate Value Dataset from 1991 to 2020 from more than 2,400 ground automatic weather stations in China. Storage space and data interfaces are reserved for other ground meteorological elements. The data storage processing layer is used to store analytical data, which is obtained by pre-processing historical raw data through deviation, grading, sorting, filtering, etc. The analytical data includes: single-station single-element historical ranking series, single-element (regional) historical ranking series, time-segmented regional single-element ranking series, and station network information modules. 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 in different modules. Services include data analysis, data query, data processing, data transmission, load balancing, identity authentication, and log monitoring updates. 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 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 a data download interface is opened to the user through the data transmission module. The cloud application module is used to 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 wind, 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 user query operation requests through the interactive module of the cloud application module and performs query operations through the service layer: retrieving 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 results 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 results, and produces charts such as "Beijing's 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 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 surface meteorological elements nationwide. In addition to commonly used elements such as temperature (TEM), precipitation (PRE), and wind (WIN), it also expands to include ground-based meteorological observation elements such as snow depth (GSS), visibility (VIS), and dust storms, and reserves access interfaces and storage space for other meteorological elements. Analysis and ranking of extreme values ​​exceeding historical records, historical extreme values ​​for the same period, process extreme values, and actual extreme values ​​can be conducted by topic. The analysis results are directly linked to thematic columns and discussion materials, instantly generating graphic documents that can be used for business consultations and decision-making.

[0035] System structure such as Figure 2 The back-end (i.e., data end) data is stored in the analytical database of the TianQing big data cloud platform. Services are implemented through timed scheduling. Management data such as system logs and user behavior are stored separately in management data tables, which are convenient for management personnel to check 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 conducts analysis on the database processing layer based on the input parameters of the HTTP request issued 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 and processing layer includes:

[0039] 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;

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

[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 all elements of a single station to obtain a single-station historical ranking sequence. The second sorting module is used to perform single-element minimum area sorting on the single-station historical ranking sequence in conjunction with the station network information module to obtain a minimum area single-element 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. Single-station time segment ranking sequences and single-station historical ranking sequences are used to perform single-factor regional ranking analysis for administrative regions, river basins, and regions, resulting in regional historical ranking sequences and regional time segment ranking sequences. The anomaly module is used to perform regional anomaly analysis on the single-station time segment ranking sequences in conjunction with station network information to obtain regional anomaly rankings. The grading module is used to perform graded sorting of the preprocessed stored data sources by factor value level to obtain extreme value rankings by factor level. The station network information module is used to associate observation data sources with station information, including station number, station latitude and longitude, station geopotential height, station type, station start observation time, station administrative region, station river basin, and station region. This step is implemented using 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 connected to the data storage and processing layer;

[0045] The data query module is used to perform data queries on the analytical data of the sub-themes in the data storage and processing layer based on the user's business needs to obtain the target data. The data processing module is used to communicate the target data 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 associated identity authentication module is used to authenticate the accessing user and return authentication information. The log monitoring module is used to update the system log.

[0046] Specifically, using the data storage and processing layer as the source, each surface feature table is updated according to business needs (e.g., hourly, daily, monthly, and cumulative annual values) according to five key themes: "Single-station Historical Extreme Values," "Single-station Process (Time Segment) Extreme Values," "Single-element Historical Extreme Values," "Single-element Process (Time Segment) Extreme Values," and "Statistical Values." This cloud service module conducts interactive analysis of meteorological extreme values ​​for the entire country, administrative divisions, and river basins. The ranking ranges for the latest historical extreme value ranking series, historical extreme value ranking series for the same period, and real-time ranking series are divided into single-station and regional rankings. The former directly uses analysis data from the single-station theme, while the latter performs regional rankings through linked station network table views, resulting in meteorological extreme value ranking series for different regions and spatial resolutions, such as the entire country, administrative divisions, and river basins. This step utilizes thematic data extreme value analysis techniques. Extreme value rankings for all provinces do not need to be stored separately, but are instead calculated on demand. This increases the flexibility of acquiring regional extreme value ranking data and reduces storage costs and computational time.

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

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

[0054] Specifically, the display component library uses the target data from the cloud service module as a source to perform real-time mapping, table creation, WebGIS rendering, and other tasks. This approach not only lowers the technical requirements for business personnel, resolving the issue of requiring specialized apps or software to use functions, but also addresses the issue of inability to visualize extreme value interactive analysis results 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] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only intended to help understand the method and core concept of the present invention. At the same time, those skilled in the art will find that the specific implementation methods and application scopes may vary based on the concept of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims

1. A cloud-based interactive analysis system for extreme value data of ground meteorological elements, characterized by: 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 on 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 historical data sources to obtain analytical data for each sub-theme; the analytical data for each sub-theme include: single-station historical ranking sequence, single-factor historical ranking sequence, single-station time segment ranking sequence, single-factor time segment ranking sequence, and single-factor statistical sequence. The cloud service module is deployed on the cloud server and is used to query the analytical data for each sub-theme according to current business needs, obtain target data and transmit the target data to the cloud application module or the open data download interface, while carrying out load balancing, user information verification and system log updates. 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. 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, a deviation 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 historical data source to obtain a 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-element minimum area of ​​the single-station historical ranking sequence in conjunction with the station network information module to obtain a minimum 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 sequence according to the element level; the station network information module is used to perform station and region analysis to obtain an element ranking sequence for the specified area; 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 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.

2. The cloud-based ground meteorological element extreme value data interactive analysis system according to claim 1, characterized in that: The cloud service module also includes: 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 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.

3. 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 needs.

4. The cloud-based ground meteorological element extreme value data interactive analysis system according to claim 3, characterized in that: The display module includes: 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 target data's ultra-historical extreme value situation and historical extreme value ranking; the process extreme value display unit is used to obtain and display the target data's ultra-historical extreme value situation and process extreme value ranking; 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 belonging 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 time period extreme values ​​of the target data; the text and chart display unit is used to make the target data into a chart or template text and display it.

Images