CN109684388B - Meteorological data index and visual analysis method based on super-cubic grid tree - Google Patents
Meteorological data index and visual analysis method based on super-cubic grid tree Download PDFInfo
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Abstract
The invention belongs to the technical field of weather analysis, and discloses a weather data index and visual analysis method based on super-cubic grid trees; establishing a multi-level unbalanced index Tree for meteorological data under different time-space granularity and meteorological elements according to availability indexes of time, space and element structures by using the super-cubic grid Tree SHG-Tree; carrying out availability index of mass meteorological data, establishing a mapping between the availability index and the storage of the meteorological data, and enabling the storage and warehousing of the meteorological data to simultaneously establish the availability index and the storage mapping; acquiring the retrieved data and the data storage position in real time through the availability view; according to the characteristics of the meteorological data, database selection and data visual analysis, data availability condition setting and judgment, meteorological data discovery result visual analysis and data availability judgment are carried out, and the indexing of the meteorological data is realized. The invention increases the data availability analysis link and the data discovery result analysis link, and effectively reduces the downloading of invalid data.
Description
Technical Field
The invention belongs to the technical field of weather analysis, and particularly relates to a weather data index and visual analysis method based on a super-cubic grid tree.
Background
With the further development and improvement of the observation system, china has built a national weather observation network, performs data sharing with the international weather organization, generates hundreds of data each day, generates thousands of various forecast and service products, generates information of more than 2000GB each day, and forms massive weather data by a large amount of historical weather data and real-time data, and the data strongly supports the development of weather business and scientific research. The meteorological data sharing in China is developed rapidly, the accumulated massive historical meteorological data and real-time observation data are shared by all provincial meteorological offices, regional meteorological centers and national meteorological offices, and a meteorological data management service platform is established, so that a data access service system has a good application effect.
Characteristics of meteorological data
(1) Mass characteristic of meteorological data
In the period of 'fifteen' and under the support of national origin-to-change commission, the China weather bureau arranges main real-time observation data and historical observation data in the existing weather observation system and establishes a national weather data service management service platform, so that the main weather data of China can be shared on the Internet, and users can inquire, retrieve and download relevant weather data, thereby promoting the development of weather service and scientific research.
(2) Meteorological data diversity feature
The weather data service management service platform or the weather information sharing service platform of each stage provides a large number of concurrent access services for various weather businesses and scientific researches of each stage. The data in the platform has the following features:
1) Element diversity: the platform can provide meteorological data of various factors such as temperature, precipitation, wind speed, wind direction, air pressure and the like;
2) Time diversity: any weather element is closely related to time and can be expressed as a weather element at a certain moment, on the other hand, from the time interval, the weather element can be as small as a unit interval of seconds, can be as long as a unit interval of ten days, months, seasons, years, ten years or year average, can be real-time weather data, and can be historical weather data;
3) Spatial and spatial scale diversity: the meteorological elements are closely related to the space position, and can be elements of a certain station or elements on a certain grid point, the distribution of the stations is uneven, and the grid division can be different in size, so that different meteorological elements can have different space scales, or the same element can have different space scales;
4) Diversity of data content: can be observation data, objective analysis products, forecast products, service products, other products, etc.;
5) Diversity of observation means: different observation means such as manual observation, automatic observation, radar observation, satellite observation and the like can be adopted;
6) Data format diversity: the weather data provided by the platform can be digital, character, graphic, and animated;
7) Storage format diversity: the numerical forecasting products can be stored in a file, a database, a MICAPS format, various graphic formats and a GRIB mode;
8) Storage mode diversity: the method can be online, near-line or offline, and the medium can be a magnetic disk, a tape drive or the like. Thus, meteorological data is complex information of multi-dimension, multi-scale, multi-time equality.
(3) Meteorological data availability features
According to the characteristics of weather data diversity, the weather data in the platform are expressed as:
Y＝F(s,r,t,z,g,l,b)…
wherein Y represents meteorological data in the platform, F is a function, s represents meteorological elements, r represents the spatial position of the elements, t represents time, z represents data type, g represents observation means, l represents the expression mode of the meteorological data, and b represents the storage mode of the data.
S, r, t, z, g, l, b are referred to as meteorological data association parameters. In actual business, for example, the original 2300 observation stations are developed to 3-4 ten thousands in the national scope, automatic stations, GPS/Met, atmospheric components, phased array radars and the like are added to the observation equipment, manual observation can only be performed once every three hours in the past, the current automatic observation can be performed to obtain observation data once every ten minutes, and once the observation instrument breaks down, the observation data can not be obtained at a certain observation station for a certain time, so that data missing measurement is formed. Thus, the actual meteorological data described by the above equation is an incomplete sequence.
The requirements of meteorological business and scientific research on data are various, such as temperature, precipitation and soil humidity data in a northern hemisphere range with longitude and latitude of 5 degrees by 5 degrees in units of months. This is a typical requirement for the use of materials in meteorological business and scientific research, from which the need for data is more manifested in the need for data sets, which are massive in terms of data volume, on the other hand it is desirable that the materials have certain rules, i.e. that they are relatively complete, and only so can they be used.
Thus, in theory, current observation data may not meet business and scientific needs, and it is often necessary to balance or coordinate the needs for meteorological data according to the situation of the observation data. This process is referred to as weather data availability analysis, and the weather-related parameters in equation (1) may also be referred to as weather data availability parameters. The availability requirements of different businesses and scientific researches on the meteorological data are different, namely the individualized demand characteristics of the meteorological data are obvious. Meteorological business and scientific research are based on meteorological data (information), so that querying, searching and finding meteorological data meeting conditions is one of the main frequent basic works. Namely, the discovery of the meteorological data plays fundamental and critical roles for meteorological business and scientific research.
In summary, the problems of the prior art are:
along with the proposal of new requirements of weather service and scientific research, the method has the advantages that the required data is difficult to quickly find in a massive shared library, a great amount of time and effort are required to find and process massive weather data, repeated downloading of the data, resource waste and weak real-time response capability of data access are caused, and the use efficiency of the massive weather data is not fully exerted;
existing indexing methods are inefficient in finding weather data or difficult to find the useful information needed. On the other hand, the current searching (finding) platform is simply a searching method for other applications (industries), cannot adapt to complex mass meteorological data, provides few available tools and means, and does not have an analysis means for searching (finding) objects.
The existing visual discovery method of the meteorological data has poor fuzzy discovery effect on the usability of the meteorological data; the phenomenon of missing meteorological data is not solved from the aspects of multi-time space granularity and factors, and available data cannot be found rapidly for massive meteorological data, so that the success rate of meteorological data finding is low.
Difficulty and meaning for solving the technical problems:
for meteorological data with multiple time-space granularity and multiple elements, due to the reasons of equipment deployment and observation data acquisition and the like which are difficult to test, the defects in time continuity and space continuity are easy to cause, and for meteorological business and meteorological research work, one important index for the usability of research data is that the time and space continuity of the data needs to reach a certain degree, and a data set with poor continuity has little business or research value. The large-scale meteorological data stored by the structured database is lack of quantitative judgment on time continuity, space continuity, multi-time space granularity satisfaction and multi-meteorological element satisfaction, so that the availability judgment of the current meteorological data is always carried out by adopting the conditions of a set time period and a space range, and the space-time continuity of the inquired result data is judged by artificial experience.
Disclosure of Invention
Aiming at the problems existing in the prior art, the invention provides a weather data index and visual analysis method based on a super-square grid tree.
The invention is realized in such a way that a weather data index and visual analysis method based on super-cubic grid trees comprises the following steps:
firstly, establishing a multi-level unbalanced index Tree for meteorological data under different space-time granularity and meteorological elements by using availability indexes of a super-cubic grid Tree SHG-Tree constructed by time, space and elements;
secondly, carrying out availability index of mass meteorological data, establishing a mapping between the availability index and the storage of the meteorological data, and establishing the availability index and the storage mapping when the meteorological data is stored and warehoused; acquiring the retrieved data and the storage position of the data in real time through the availability view; the 'black box' of the meteorological data storage is changed into the 'white box' visible according to the data structure and the data availability through the construction of the SHG-Tree, and high-efficiency service is provided for data ordering and use;
and thirdly, according to the characteristics of the meteorological data, database selection and data visual analysis, data availability condition setting and judging, meteorological data discovery result visual analysis and data availability judging are carried out, so that indexing of the meteorological data is realized.
Further, the third step, the database selection and data visualization analysis method comprises: establishing a plurality of databases according to the long-time series historical data and the real-time meteorological data accumulated by the data management platform;
selecting a related database according to the query and the search content;
and carrying out database catalog structure analysis and feature analysis, calculation, display and statistics related information on the selected database.
Further, in the third step, the method for setting and determining the data availability condition includes:
setting availability parameters based on the basis of the data availability analysis and the purpose of the search query;
after the availability parameters are set, judging the meeting condition of the availability conditions, and inquiring the database according to the storage index and the data mapping relation to acquire the data set content meeting the conditions when the conditions are met;
when the availability condition is not satisfied, the system does not acquire data download, returns to the availability condition setting again, and the user adjusts parameters according to the data condition and the service requirement condition so as to satisfy the modified availability condition.
Further, in the third step, the method for visual analysis of the weather data discovery result includes:
analyzing the quality, time sequence and spatial uniformity of the data; and displaying the data condition, the data quantity and the quantity of the data quantity, the number of stations contained in the data and the missing measurement condition of the data which meet the conditions in the current database.
Further, in the third step, the method for determining availability of data includes: analyzing the results and determining whether the data is available; if available, downloading; if not, returning to the usability condition setting again, and finding the required data by analyzing and adjusting the usability condition;
the visual analysis of the meteorological data discovery result further comprises the following steps:
performing dimension reduction and degree reduction mutation treatment on the data discovery availability index set to form a mutation index item set;
performing SHG-Tree retrieval on the variation index item set to calculate the integrity level, and constructing a large-scale visual discovery result set;
and carrying out maximum sub-frequent pattern mining on the SFP-Tree constructed by the result set, and visually presenting the mining result.
Further, the weather data index and visual analysis method based on the super-cubic grid tree further comprises the following steps:
data encapsulation and downloading: the meteorological data is packaged before being downloaded and then downloaded and used.
Another object of the present invention is to provide a weather data index and visual analysis platform based on super-cubic grid tree.
It is another object of the present invention to provide a computer program for implementing the above-mentioned super-grid tree-based weather data index and visual analysis method.
Another object of the present invention is to provide an information data processing terminal for implementing the above-mentioned super-square-grid-tree-based weather data index and visual analysis method.
It is another object of the present invention to provide a computer readable storage medium comprising instructions that when executed on a computer cause the computer to perform the above-described super-grid tree based weather data indexing and visualization analysis method.
The invention has the advantages and positive effects that:
compared with the traditional data indexing method, the indexing method based on weather data availability analysis increases a data availability analysis link and a data discovery result analysis link, effectively reduces the downloading of invalid data, and provides an effective indexing data method for service scientific researchers.
The research on the aspect of domestic and foreign weather data discovery is focused on two aspects, namely, the data set packaging subject is published, and the method can only provide limited data sets and is difficult to meet the personalized requirements; and secondly, the index and parameterization query method of the meteorological metadata is used for extracting and packaging data according to query parameters of users and obtaining the data through a network or other modes. Therefore, the efficiency of data discovery is low, thereby limiting the benefits of a shared platform. Based on the problems, the invention provides a mass weather data discovery model based on weather data availability condition analysis, solves the problem of low weather data discovery efficiency, and realizes the accuracy, timeliness, intuitiveness and effectiveness of the data sharing service of the data service management business platform.
Drawings
FIG. 1 is a flowchart of a method for indexing and visually analyzing weather data based on a super-square grid tree according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the following examples in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The universal relation sub-group mining technology provided by the embodiment of the invention solves the problem of fuzzy discovery of availability of the meteorological data, solves the problem that massive meteorological data with outstanding phenomenon of missing meteorological data can quickly discover the available data from multiple time-space granularity and elements, and greatly improves the success rate of meteorological data discovery.
Meteorological data is inefficient to discover or difficult to discover useful information required by business researchers. On the other hand, the current searching (finding) platform is simply a searching method for other applications (industries), cannot adapt to complex mass meteorological data, provides few available tools and means, and does not have an analysis means for searching (finding) objects. According to the characteristics of the meteorological data, particularly the usability characteristic analysis of the meteorological data, the invention provides a meteorological data discovery model.
The principle of application of the invention is described in detail below with reference to the accompanying drawings.
The invention establishes a multi-level unbalanced index Tree for meteorological data under different time-space granularity and meteorological elements by using availability indexes of super-cubic grid Tree SHG-Tree constructed by time, space and elements; carrying out availability index of mass meteorological data, establishing a mapping between the availability index and the storage of the meteorological data, and establishing the availability index and the storage mapping while storing the meteorological data; acquiring the retrieved data and the storage position of the data in real time through the availability view; thus, the construction of the SHG-Tree changes the "black box" of the meteorological data store to a "white box" visible by data structure and data availability, providing an efficient service for data ordering and use.
As shown in fig. 1, the weather data index and visual analysis method based on the super-square grid tree provided by the embodiment of the invention,
1) Database selection and data visualization analysis: the data management platform (shared platform) accumulates long-time series of historical data and real-time meteorological data, and a plurality of databases are established based on the convenience of management and the requirements of business scientific research services. Firstly, under the support of the interactive tool and the software of the graphical interface, selecting a relevant database of data possibly needed according to the purposes of query and retrieval; and secondly, under the support of the software of the interactive tool and the graphical interface, the selected database can be conveniently subjected to database catalog structure analysis and record characteristic analysis, and can calculate, display and count related information, so that preparation is made for the subsequent data availability parameter setting.
2) Data availability condition setting and determination: the availability parameters may be set based on the basis of the data availability analysis and the purpose of the search query. After the availability parameter is set, the system judges the meeting condition of the availability condition, and when the condition is met, the system acquires the data (set) meeting the condition according to the storage index, the data mapping relation and a specific algorithm; when the availability condition is not satisfied, the system does not acquire data download, but returns to the availability condition setting again, and the user can adjust parameters according to the data condition and the service scientific research requirement condition, so that the modified availability condition is satisfied.
3) Visual analysis of meteorological data discovery results: conventional data retrieval and query methods do not provide analysis of the findings, and seemingly find the desired data set, but in practice the quality of the data set is problematic (e.g., the data set contains a lot of missing data, identified by "9999"), and careful analysis of the material after download is not available. Therefore, visual analysis of the weather data findings is very important. Under the support of background real-time calculation and visualization tools and graphical interfaces, a user can analyze the quality, time sequence, spatial uniformity and the like of data, for example, the data condition meeting the conditions in the current database can be seen immediately, for example, the total data quantity, the quantity of the data, the number of stations contained in the data, the missing measurement condition of the data and the like.
4) Data availability determination: whether the data is available is determined by analysis of the results. If available, download is performed, and if not, the availability condition is readied back to the availability condition setting, and the required data is striven for by analyzing and adjusting the availability condition.
5) Data encapsulation and downloading: the meteorological data is more used in a data set mode when the meteorological data is applied, so the data must be packaged before being downloaded, and the downloading and the use are convenient. And the whole data discovery processing process can be completed by transmitting and downloading after standardized packaging.
The visual analysis of the meteorological data discovery result further comprises the following steps:
performing dimension reduction and degree reduction mutation treatment on the data discovery availability index set to form a mutation index item set;
performing SHG-Tree retrieval on the variation index item set to calculate the integrity level, and constructing a large-scale visual discovery result set;
and carrying out maximum sub-frequent pattern mining on the SFP-Tree constructed by the result set, and visually presenting the mining result.
Compared with the traditional number index and visual analysis method, the index method based on meteorological data availability analysis increases the data availability analysis link and the data discovery result analysis link, effectively reduces the downloading of invalid data, and provides an effective index data method for service researchers.
The embodiment of the invention provides a weather data indexing method based on a super-cubic grid tree, which is a weather service model based on multiple time-space granularity and multiple elements of a simulation training platform, wherein the model considers multiplexing of complex and various special weather data, has the effect of dynamic deduction of the weather data, and provides real-time weather data for aircrafts, radar detectors and weapons of the training platform, so that a real training field weather environment is simulated. The simulation training of pilots can be provided with various typical special weather phenomena (such as lines, high crosswinds, wind shear, thunderstorms, downwind and downwind storm flows, and the like), and the weather data of the special weather region boundary and the surrounding global weather are fused, so that the evolution of the weather phenomena is simulated to be more real by using a dynamic deduction model. The weather service establishes indexes for the generated weather data with each space-time granularity by using the super-square grid tree, so that real-time data insertion and real-time data query are realized, and the simulation training effect proves that the weather service can effectively meet the simulation efficiency requirement: when the number of simulation entities is more than or equal to 500, the time from the time when the simulation entities release the current position to the time when the simulation platforms receive the real-time meteorological data of the position when the simulation entities push the platform is not more than 400 milliseconds, and the realistic effect of meteorological simulation is very obvious.
When the simulation area is enlarged and the simulation entity is increased, because the super-square grid tree is adopted to build an index of the unbalanced tree for the meteorological data, and meanwhile, the motion trail of the simulation entity has continuity, the area data can be continuously provided for the simulation entity by the area query method of the super-square grid tree, and the response time of data query shows relatively stable query response speed and only linearly increases under the condition of data and exponential increase of the request.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (8)
1. The weather data index and visual analysis method based on the super-cubic grid tree is characterized by comprising the following steps of:
firstly, establishing a multi-level unbalanced index Tree for meteorological data under different space-time granularity and meteorological elements by using availability indexes of a super-cubic grid Tree SHG-Tree constructed by time, space and elements;
secondly, carrying out availability index of mass meteorological data, establishing a mapping between the availability index and the storage of the meteorological data, and establishing the availability index and the storage mapping when the meteorological data is stored and warehoused; acquiring the retrieved data and the storage position of the data in real time through the availability view;
thirdly, according to the characteristics of the meteorological data, database selection and data visual analysis, data availability condition setting and judging, meteorological data discovery result visual analysis and data availability judging are carried out, and indexing of the meteorological data is achieved;
the third step, the method for judging the availability of the data comprises the following steps: analyzing the results and determining whether the data is available; if available, downloading; if not, returning to the usability condition setting again, and finding the required data by analyzing and adjusting the usability condition;
the visual analysis of the meteorological data discovery result further comprises the following steps:
performing dimension reduction and degree reduction mutation treatment on the data discovery availability index set to form a mutation index item set;
performing SHG-Tree retrieval on the variation index item set to calculate the integrity level, and constructing a large-scale visual discovery result set;
and carrying out maximum sub-frequent pattern mining on the SFP-Tree constructed by the result set, and visually presenting the mining result.
2. The method for indexing and visualizing analysis of weather data based on a super-cubic grid tree as in claim 1, wherein the third step of database selection and data visualization analysis method comprises: establishing a plurality of databases according to the long-time series historical data and the real-time meteorological data accumulated by the data management platform;
selecting a related database according to the query and the search content;
and carrying out database catalog structure analysis and feature analysis, calculation, display and statistics related information on the selected database.
3. The method for indexing and visually analyzing meteorological data based on a super-cubic grid tree according to claim 1, wherein the method for setting and determining data availability conditions comprises the steps of:
setting availability parameters based on the basis of the data availability analysis and the purpose of the search query;
after the availability parameters are set, judging the meeting condition of the availability conditions, and when the conditions are met, acquiring a data set meeting the conditions according to the storage index and the data mapping relation;
when the availability condition is not satisfied, the system does not acquire data download, returns to the availability condition setting again, and the user adjusts parameters according to the data condition and the service requirement condition so as to satisfy the modified availability condition.
4. The method for indexing and visually analyzing weather data based on super-cubic grid tree as set forth in claim 1, wherein the method for visually analyzing the result of finding weather data comprises the steps of:
analyzing the quality, time series and spatial uniformity of the data; and displaying the data condition, the data quantity and the quantity of the data quantity, the number of stations contained in the data and the missing measurement condition of the data which meet the conditions in the current database.
5. The method for indexing and visually analyzing weather data based on a super-cubic grid tree according to claim 1, further comprising:
data encapsulation and downloading: the meteorological data is packaged before being downloaded and then downloaded and used.
6. The super-square-tree-based weather data index and visual analysis platform of the super-square-tree-based weather data index and visual analysis method of claim 1.
7. An information data processing terminal for implementing the super-square-grid-tree-based weather data index and visual analysis method according to any one of claims 1 to 5.
8. A computer readable storage medium comprising instructions which, when run on a computer, cause the computer to perform the super-grid tree based meteorological data indexing and visualization analysis method of any one of claims 1 to 5.
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| A parallel sort-balance mutual range-join algorithm on hypercube computers;R. Wong;《百度学术》;20020806;全文 * |
| 多维空间索引结构SHG-Tree;刘胤田;《百度学术》;20090612;全文 * |
| 市县级公共气象服务集约化业务平台设计;李超;《CNKI中国知网》;20160630;全文 * |
| 时空信息云平台下数据管理及可视化方法;郭云嫣;《百度学术》;20161231;全文 * |
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