CN116150570B - Storage and superposition analysis calculation method and device for high-precision grid rainfall - Google Patents
Storage and superposition analysis calculation method and device for high-precision grid rainfall Download PDFInfo
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Abstract
The invention discloses a storage and superposition analysis calculation method and device of high-precision grid rainfall, firstly, a rectangular boundary box is used for calculating provincial areas, gridding division is carried out, high-precision grids are obtained, each grid is given a unique number, and the rainfall of each grid is obtained through an interpolation algorithm based on rainfall data monitored by a local hydrologic bureau; and based on the grid numbers and the rainfall of the corresponding grids, performing time superposition calculation on the rainfall of the grids to obtain the total rainfall of the rainfall period. The invention adopts a finer granularity division standard, not only can macroscopically present a rainfall statistical chart of an oversized region, but also can present a rainfall statistical chart of a specified rainfall period of any specific microscopic region, has higher flexibility and higher analysis precision, provides an important reference function for whether the rainfall is at a normal level, and has guiding significance for flood disaster prevention and agricultural production.
Description
Technical Field
The invention relates to the field of rainfall statistics, in particular to a high-precision grid rainfall storage and superposition analysis calculation method and device.
Background
Rainfall is an important climate phenomenon affecting the aspects of social production and life, and rainfall is a measure of rainfall degree and can be classified into annual rainfall, quarterly rainfall, monthly rainfall, daily rainfall, hour rainfall and the like in time. The rainfall analysis is not only effectively helpful to agricultural production, but also can early warn flood disasters possibly occurring in advance, so that the life and property safety of people is guaranteed to the greatest extent.
In conclusion, the rainfall has important guiding effects on the fields of agricultural production, water conservancy and hydropower, flood control and waterlogging prevention and the like.
The conventional rainfall statistics charts are often displayed on a macroscopic level, and the corresponding rainfall charts cannot be obtained for specific areas with finer granularity, and the conventional charts are integral, such as the rainfall charts of whole Chinese provinces, so that the chart has low access flexibility and is not efficient and visual when analyzing the specific areas.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a high-precision grid rainfall storage and superposition analysis calculation method and device, which are used for dividing a rainfall meteorological graph of an oversized area into grids and storing the grids by using a higher-performance storage mode, so that the subsequent superposition analysis calculation efficiency is expected to be effectively improved, and the obtained calculation result can provide an important reference effect on whether the rainfall is at a normal level or not and has guiding significance for flood disaster prevention and agricultural production.
The aim of the invention is realized by the following technical scheme: in a first aspect, the present invention provides a method for storing and stacking, analyzing and calculating high-precision grid rainfall, the method comprising the steps of:
(1) Using rectangular boundaries to frame provincial areas needing to be calculated on a satellite map;
(2) Performing rasterization division on the rectangular area divided in the step (1) to obtain high-precision grids of the provincial area to be calculated, and giving a unique number to each grid;
(3) Calibrating whether each grid belongs to the area range needing to be calculated;
(4) Based on rainfall data monitored by a local hydrologic bureau in a provincial area to be calculated, obtaining the rainfall of each calibrated grid in the high-precision grid through an interpolation algorithm;
(5) Constructing a database based on the grid numbers and the rainfall of the corresponding grids, storing the database in a picture form, and associating the picture data item indexes in the database with the grid numbers;
(6) And aiming at the local rainfall period, carrying out time superposition calculation on the rainfall of the corresponding grid to obtain the total rainfall of the rainfall period.
Further, in the step (1), based on the longitude and latitude of the provincial area to be calculated, the regional coverage is performed by using the maximum circumscribed rectangle boundary of the provincial area.
Further, in the step (2), the specific process of assigning a unique number to each grid is: and (3) rasterizing and dividing the rectangular area by using longitude and latitude not higher than 0.01 degrees, wherein each grid is provided with a unique number, the numbering rule uses the longitude and latitude value of the lower left corner of the grid as a parameter, the calculation is carried out according to a formula of longitude 10000+latitude 100, and the calculation result is the number of the grid.
Further, in the step (3), a marking array is set, the outside of the provincial area to be calculated is marked as False, the inside of the provincial area is marked as True, when the superposition calculation is carried out subsequently, whether the longitude and latitude of the position are outside the provincial area or not is judged, no processing is carried out outside the provincial area, and the calculation analysis is carried out in the provincial area.
Further, in the step (4), the missing part data of the rainfall data monitored by the hydrologic bureau is estimated by adopting an inverse distance weighted interpolation algorithm.
Further, in step (5), the database stores rainfall data including file storage, line storage, column storage, and line-column hybrid storage.
Further, the rank hybrid storage specifically includes: and (3) for the calibrated grid, 2 x2 or 3*3 local grids are aggregated into one piece of data for storage.
Further, in the step (6), after the total rainfall in the rainfall period is obtained, the rainfall in the area can be obtained by positioning the area with any requirement, specifically as follows:
1) Firstly, framing an external rectangular boundary according to a custom region;
2) Then, using a shadow drawing tool to draw grid areas outside the target area into shadows in the rectangular area, and obtaining a shadow rectangular frame;
3) Superposing the obtained shadow rectangular frame and the corresponding region of the picture data stored in the step (5), and directly generating a corresponding marking matrix, wherein the shadow part is marked as-1;
4) The rainfall value of each grid is calculated using an inverse distance weighted interpolation algorithm.
In a second aspect, the present invention also provides a storage and superposition analysis computing device for high-precision grid rainfall, which includes a memory and one or more processors, where the memory stores executable codes, and the processors execute the executable codes to implement the steps of the storage and superposition analysis computing method for high-precision grid rainfall.
In a third aspect, the present invention also provides a computer-readable storage medium having stored thereon a program which, when executed by a processor, implements the steps of the storage and superposition analysis calculation method of high-precision grid rainfall.
The invention has the beneficial effects that: the invention adopts a finer granularity dividing standard, not only can macroscopically present a rainfall statistical chart of an oversized region, but also can present a rainfall statistical chart of a specified rainfall period of any specific microscopic region, and has higher flexibility and higher analysis precision. The result obtained by statistical storage, analysis and calculation of the rainfall historical data of the specific area can provide an important reference function for whether the rainfall is at a normal level or not, and has guiding significance for flood disaster prevention and agricultural production.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for storing, overlapping, analyzing and calculating high-precision grid rainfall, which is provided by the invention;
FIG. 2 is a diagram of a chart generation process;
FIG. 3 is a schematic diagram of an interpolation algorithm;
FIG. 4 is a schematic diagram of file storage;
FIG. 5 is a schematic diagram of a line store;
FIG. 6 is a schematic diagram of a columnar memory;
FIG. 7 is a rank hybrid storage schematic;
FIG. 8 is a schematic diagram of superposition calculations;
FIG. 9 is a schematic diagram of mapping table generation and query;
FIG. 10 is a flow chart of a quick calibration;
FIG. 11 is a detailed process diagram of storage and superposition analysis calculations for high-precision grid rainfall.
Fig. 12 is a block diagram of a high-precision grid rainfall storage and superposition analysis calculation device provided by the invention.
Detailed Description
The following describes the embodiments of the present invention in further detail with reference to the drawings.
As shown in fig. 1 and 11, the present invention provides a method for storing, overlapping, analyzing and calculating high-precision grid rainfall, and the method is described below by taking a rainfall as an example, and specifically includes the following steps:
1. region division
Since the rainfall monitoring of the partial area requires a finer-grained area to be monitored, it is necessary to perform an area division operation on the selected whole area.
The region dividing method of the invention divides the selected region according to longitude and latitude, and performs gridding division according to longitude and latitude of 0.01 degrees, and the selected region can be divided into 30 ten thousand grid regions in total. And separately carrying out rainfall statistical storage on each area. The data of the present invention originate from the water-saving office a.
Each grid is provided with a unique number, the numbering rule takes the longitude and latitude value of the lower left corner of the grid as a parameter, the longitude and latitude value is calculated according to a formula of longitude 10000+latitude 100, and the calculated result is the number of the grid.
And (3) calibrating whether the rainfall in the area to be calculated is within the range of the area to be calculated, if the upper left corner is not within the area A, the rainfall in the grid is not required to be calculated statistically. A tag array may be provided to tag the outside of the provincial region as False and the inside of the provincial region as True. When the grid area is subjected to superposition calculation analysis, whether the longitude and latitude of the position is outside the provincial area or not is firstly judged, no processing is performed outside the provincial area, and calculation analysis is performed in the provincial area.
2. Data statistics
In the data statistics stage, the precipitation amount of each grid area (data is provided by the water bureau of a) is counted, the precipitation amount data of each hour is recorded and counted, and for the convenience of analysis and observation, the data is diagrammed as shown in fig. 2, so that a precipitation amount chart of the whole province a in the hour can be obtained, the chart is subjected to rasterization, namely the hour precipitation amount chart of the whole province a is divided, 30 ten thousand small charts can be obtained, and each small chart also has a corresponding data file format, so that the whole hour precipitation amount chart of the province a can be thinned into 30 ten thousand small grid pictures with finer granularity.
The data provided by the water conservation bureau A is that the installation positions of all the rainfall collecting devices are relatively sparse, the dimension of the corresponding data matrix is smaller, and the high-precision rainfall statistical storage realized by the invention is that the grid rainfall matrix divided by the longitude and latitude step length of 0.01 degree is needed to be obtained, so that the vacancy value in the grid rainfall matrix is needed to be estimated by an algorithm. The invention uses an inverse distance weighted interpolation algorithm (INVERSE DISTANCE WEIGHTED, IDW).
The IDW algorithm considers two types of points, one being a discrete set of points of known value and the other being an insertion set of points with estimated values. The algorithm considers the influence of all surrounding discrete points when estimating each insertion point value, distributes different weight values for the discrete points according to the distance between the discrete points and the insertion point, and finally synthesizes the weights of all the discrete points and the estimated value calculated by the numerical value to the insertion point. The specific algorithm flow is as follows:
Step1 first calculate the distance d from the ith discrete point to the insertion point (x t,yt) i
Step2. calculate the weight λ i of the i-th discrete point to the insertion point (x t,yt):
step3. calculate the value of the insertion point v t:
The dots of the left picture in fig. 3 represent hydrologic monitoring points, namely rainfall data provided by hydrologic bureau, and the right is interpolation point estimated rainfall data obtained by an IDW interpolation algorithm, so that the completion of grid point data is realized.
3. Data storage
The picture storage of the same grid needs to number each picture, so that the uniqueness of each picture is ensured. The numbering rules of the pictures are year, month, day and hour. The rainfall statistics at 10, e.g. month 18 of 22, can be named 22.6.18.10 for storage.
Since data statistics are performed every hour per grid, the amount of data for a whole year is quite large. A rainfall map is generated per hour on 30 ten thousand grids, which together produce about 26 hundred million data maps in a year. How to store these 26 hundred million pictures efficiently is a key issue.
The invention provides four solutions of file storage, line storage, column storage and row-column hybrid storage, which can be selected according to different conditions.
Scheme one: file storage
As shown in fig. 4, the file storage is to generate a data file for each picture and store the data file in the form of a file. This has the advantage that the storage efficiency block does not require any format conversion. The disadvantage is that the disk space required for file storage can be relatively large.
Scheme II: row memory
As shown in fig. 5, the line storage type stores a piece of data corresponding to each picture in a wide column form. The line type storage is a very visual storage mode, is relatively consistent with the reading habit of human beings, and each line of data is an independent entity, so that all the attributes related to the line type storage are aggregated. In line storage, data is stored continuously in disk according to the relationship of individual entities.
The advantages are that: in a large-scale grid computing scenario, the reading efficiency in units of entities is high.
Disadvantages: under the reading scene taking certain attributes as units, the reading efficiency is high, because the whole entity is read completely and then the attributes are extracted, and in the process, a large number of disk IO (input/output) or even network IO operations are required, so that the time cost is high, and the memory requirement is high.
Scheme III: column type storage
As shown in fig. 6, each picture corresponds to 30 ten thousand grids, each grid corresponds to one piece of data, and is stored in a single grid form, and one row of data in the database represents one grid picture.
The advantages are that: and under the small-range grid computing scene, the reading efficiency is high.
Scheme IV: rank hybrid storage
As shown in fig. 7, each picture corresponds to 30 ten thousand grids, and is stored by gathering partial grids such as 2×2 and 3*3 into one piece of data;
the advantages are that: and the specific storage design is carried out on specific scene requirements, so that the reading efficiency is effectively improved and the calculated amount is reduced.
4. Superposition computational analysis
As shown in fig. 8, in the above several stages, mainly obtained is a single-hour rainfall, the time rainfall is taken as a rainfall statistical unit of the finest granularity, statistical calculation can be conveniently performed, and daily rainfall, month rainfall, year rainfall and the like can be obtained by performing superposition calculation of the time rainfall.
And (3) superposition calculation is performed to calculate the total rainfall of certain areas in a rainfall period, so that all picture history data of the areas in the rainfall period are extracted and superposed, and a final calculation result is obtained and displayed in the form of a total rainfall map.
And starting from an actual rainfall period, analyzing and calculating, adding the rainfall values of grids corresponding to the same number of each picture in each period to obtain the corresponding grid rainfall value of the superimposed picture, and forming a complete grid rainfall picture in the rainfall period.
For some fixed rainfall periods such as specific periods of plum rain, typhoon, flood season and the like, preprocessing can be performed, namely, superposition calculation is performed in the period to generate an analysis data chart of the rainfall period, and the analysis data chart is stored as historical data to be stored for subsequent repeated calling.
In addition, the rainfall period can be customized, and the result picture calculated in real time can be called.
In addition, a rainfall period superposition scene in a specific space range can be obtained, and a grid rainfall picture in the city B range is taken as an example:
1. and (5) taking an outsourcing rectangle which completely covers the administrative division range of the B city as a grid range, and listing the contained single grid sequence.
2. And (3) matching the sequence by using an n-by-m grid boundary, finding the optimal n and m to obtain an optimal area outsourcing rectangle, wherein the matching mode is to perform rectangular frame matching according to longitude and latitude of administrative areas, determine east-west longitude and north-south latitude of B city, and round and obtain the optimal circumscribed rectangle of B city.
3. And (3) storing the data in the form of n x m by using a row-column hybrid mode, and performing time sequence superposition calculation to obtain a final result.
5. Quick positioning
Because a specific space can be selected for analysis and calculation, and because of the discretion of the selected area, how to quickly locate and read data of a designated area is a problem that needs to be solved by quick data location. As shown in fig. 9, the quick positioning scheme provided by the invention is to establish a mapping table between indexes of grid pictures and longitude and latitude grids, establish the mapping table between the grid pictures and the longitude and latitude grids in a traversing manner at the beginning of large-area modeling, and then divide a selected area through longitude and latitude to quickly position the indexes of the required grid pictures directly through the mapping table, so that the quick positioning effect is achieved. I.e. sacrifice a part of the memory space for a fast positioning effect.
Optimization algorithm: the method for determining the calibration matrix by traversing the grid has high time cost, and as shown in fig. 10, the invention also provides an improved optimization algorithm for accelerating the generation of the calibration matrix. The algorithm execution process is as follows:
step1, firstly, framing an external rectangular boundary according to a custom region;
Step2, then using a shadow drawing tool to draw the grid areas outside the target area into shadows in the rectangular selected area;
Step3, superposing the obtained shadow rectangular frame and the corresponding area of the original picture, and directly generating a corresponding marking matrix, wherein the shadow part is marked as-1;
Step4. Calculate the rain value for each grid using an inverse distance weighted interpolation algorithm.
Example 1: a water-saving flood season (4 months 15 days-10 months 15 days) is explained
The annual hydrological season of province a is between 4 months 15 days and 10 months 15 days, with 7 months 15 days and 10 months 15 days also known as main season. This example is to analyze the total rainfall level of province a during this hydrological flood period.
Step1, modeling a region, and selecting the east-west longitude and the north-south latitude of the province A to determine the size of a circumscribed rectangle of the model.
Stepp2. Dividing the area into a longitudinal direction and a latitudinal direction, dividing the whole rectangular area into regular small grids by a step of 0.01 degrees.
Step3. Data statistics, obtain rainfall value per hour zone of past history time from interface provided by water-saving bureau a
Step4, traversing the grid to determine a marking matrix and a picture mapping matrix.
Marking matrix: small grids outside the a province boundary are recorded as False, small grids inside the a province boundary are recorded as True, and the grids recorded as False are discarded in the subsequent superposition calculation analysis. The generation of the marking matrix can be quickly generated in a mode of overlapping two pictures, namely, firstly, a region outside the boundary A is painted into a shadow region by a drawing tool for the region in the rectangular frame, a shadow rectangular picture is obtained, then the shadow rectangular picture is overlapped with an original picture, and the places (shadows) where the two pictures are different are marked as False.
Picture mapping matrix: and a mapping matrix between the picture group index and the longitude and latitude of the region is established, so that the specific region can be quickly positioned after being searched, and traversal from the head calculation is not needed.
Step5. Data storage, a storage scheme (file storage/line storage/column storage/line and column mixed storage) is selected according to the requirement scene, if the rainfall data of an extra large area such as full province needs to be analyzed, the line storage scheme can be adopted, and the rainfall data of a small area such as a certain area needs to be analyzed, the column storage scheme can be adopted.
Step6. superposition calculation analysis. First, the hour rainfall data between 4 months 15 days and 10 months 15 days are read from the database according to a defined time frame. Because the grid data of the whole A province is needed to be used in the embodiment, the picture mapping matrix has little effect on the part, all grids in the boundary range belonging to the A province are determined according to the marking matrix, and the corresponding grid rainfall data are overlapped according to time, so that a final total rainfall overlapping result chart is obtained.
Example 2: the user-defined C basin (5 months 1 day-6 months 1 day) is explained as an example
The implementation is based on example 1, i.e. the marking matrix as well as the picture mapping matrix have been obtained.
Step1. Firstly, 6 month 1 day rainfall data of 5 month 1 day are read from a database according to a limited time range,
In the process of reading data, the data item index of the corresponding grid chart is obtained according to the mapping matrix, the data of the corresponding index is directly imported from the database, and the whole-province rainfall data is not required to be imported for screening, so that the positioning speed is improved, and the pressure of the memory is reduced.
And step2, performing superposition calculation on the read data to obtain a final total rainfall result chart of the C basin.
Corresponding to the embodiment of the storage and superposition analysis calculation method of the high-precision grid rainfall, the invention also provides an embodiment of the storage and superposition analysis calculation device of the high-precision grid rainfall.
Referring to fig. 12, the storage and superposition analysis calculation device for high-precision grid rainfall according to the embodiment of the invention includes a memory and one or more processors, where the memory stores executable codes, and the processors are configured to implement the storage and superposition analysis calculation method for high-precision grid rainfall according to the embodiment when executing the executable codes.
The embodiment of the high-precision grid rainfall storage and superposition analysis calculation device can be applied to any device with data processing capability, such as a computer or the like. The apparatus embodiments may be implemented by software, or may be implemented by hardware or a combination of hardware and software. Taking software implementation as an example, the device in a logic sense is formed by reading corresponding computer program instructions in a nonvolatile memory into a memory by a processor of any device with data processing capability. In terms of hardware, as shown in fig. 12, a hardware structure diagram of an apparatus with data processing capability where the high-precision grid rainfall storage and superposition analysis computing device of the present invention is located is shown, and in addition to the processor, the memory, the network interface, and the nonvolatile memory shown in fig. 12, the apparatus with data processing capability where the device is located in the embodiment generally includes other hardware according to the actual function of the apparatus with data processing capability, which is not described herein.
The implementation process of the functions and roles of each unit in the above device is specifically shown in the implementation process of the corresponding steps in the above method, and will not be described herein again.
For the device embodiments, reference is made to the description of the method embodiments for the relevant points, since they essentially correspond to the method embodiments. The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purposes of the present invention. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
The embodiment of the invention also provides a computer readable storage medium, on which a program is stored, which when executed by a processor, implements the storage and superposition analysis calculation method of high-precision grid rainfall in the above embodiment.
The computer readable storage medium may be an internal storage unit, such as a hard disk or a memory, of any of the data processing enabled devices described in any of the previous embodiments. The computer readable storage medium may also be an external storage device of any device having data processing capabilities, such as a plug-in hard disk, a smart memory card (SMART MEDIA CARD, SMC), an SD card, a flash memory card (FLASH CARD), etc. provided on the device. Further, the computer readable storage medium may include both internal storage units and external storage devices of any data processing device. The computer readable storage medium is used for storing the computer program and other programs and data required by the arbitrary data processing apparatus, and may also be used for temporarily storing data that has been output or is to be output.
The above-described embodiments are intended to illustrate the present invention, not to limit it, and any modifications and variations made thereto are within the spirit of the invention and the scope of the appended claims.
Claims (8)
1. The method for storing, overlapping, analyzing and calculating the high-precision grid rainfall is characterized by comprising the following steps of:
(1) Using rectangular boundaries to frame provincial areas needing to be calculated on a satellite map;
(2) Performing rasterization division on the rectangular area divided in the step (1) to obtain high-precision grids of the provincial area to be calculated, and giving a unique number to each grid; the method comprises the following steps: the specific process of assigning each grid a unique number is: grid division is carried out on a rectangular area by longitude and latitude which are not higher than 0.01 degrees, each grid is provided with a unique number, the numbering rule takes the longitude and latitude value of the lower left corner of the grid as a parameter, calculation is carried out according to a formula of longitude 10000+latitude 100, and the calculation result is the number of the grid;
(3) Calibrating whether each grid belongs to the area range needing to be calculated;
(4) Based on rainfall data monitored by a local hydrologic bureau in a provincial area to be calculated, obtaining the rainfall of each calibrated grid in the high-precision grid through an interpolation algorithm;
(5) Constructing a database based on the grid numbers and the rainfall of the corresponding grids, storing the database in a picture form, and associating the picture data item indexes in the database with the grid numbers;
(6) Extracting all picture history data in a local rainfall period aiming at the local rainfall period, performing time superposition calculation on rainfall of each picture corresponding to the grid with the same number in each rainfall period to obtain the total rainfall of the rainfall period, and displaying the total rainfall in a form of a total rainfall map; after the total rainfall of the rainfall period is obtained, the rainfall of the area can be obtained by positioning the area with any requirement, and the method is as follows:
1) Firstly, framing an external rectangular boundary according to a custom region;
2) Then, using a shadow drawing tool to draw grid areas outside the target area into shadows in the rectangular area, and obtaining a shadow rectangular frame;
3) Superposing the obtained shadow rectangular frame and the corresponding region of the picture data stored in the step (5), and directly generating a corresponding marking matrix, wherein the shadow part is marked as-1;
4) The rainfall value of each grid is calculated using an inverse distance weighted interpolation algorithm.
2. The method for storing and analyzing and calculating the high-precision grid rainfall according to claim 1, wherein in the step (1), the regional coverage is performed by using the maximum circumscribed rectangular boundary of the provincial area based on the longitude and latitude of the provincial area to be calculated.
3. The method for storing, overlapping and analyzing and calculating the high-precision grid rainfall according to claim 1, wherein in the step (3), a mark array is set, the outside of a provincial area to be calculated is marked as False, the inside of the provincial area is marked as True, when the overlapping calculation is carried out subsequently, whether the longitude and latitude of the grid position are outside the provincial area is judged firstly, the processing is not carried out outside the provincial area, and the calculation and the analysis are carried out in the provincial area.
4. The method for storing and analyzing and calculating the high-precision grid rainfall according to claim 1, wherein in the step (4), the missing part data of the rainfall data monitored by the hydrologic bureau is estimated by adopting an inverse distance weighted interpolation algorithm.
5. The method of claim 1, wherein in step (5), the database stores rainfall data including file storage, line storage, column storage and line-column hybrid storage.
6. The method for storing and stacking, analyzing and calculating high-precision grid rainfall according to claim 5, wherein the row-column mixed storage is specifically: and (3) for the calibrated grid, 2 x 2 or 3*3 local grids are aggregated into one piece of data for storage.
7. A storage and superposition analysis computing device for high-precision grid rainfall, comprising a memory and one or more processors, the memory having executable code stored therein, wherein the processor, when executing the executable code, is configured to implement the steps of a storage and superposition analysis computing method for high-precision grid rainfall as defined in any one of claims 1-6.
8. A computer-readable storage medium having stored thereon a program which, when executed by a processor, implements the steps of a method of storage and superposition analysis calculation of high-precision grid rainfall according to any one of claims 1-6.
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