Satellite-ground fusion radiation observation lattice point product fusion method, device and equipment

Abstract

The embodiment of the invention provides a satellite-ground fusion radiation observation lattice point product fusion method, device and equipment, and is applied to the technical field of satellite-ground radiation observation data fusion. The method comprises the following steps: acquiring foundation radiation data, a first earth surface short-wave radiation product and a second earth surface short-wave radiation product; performing deviation correction on the first earth surface short-wave radiation product and the second earth surface short-wave radiation product; performing data fusion on the first earth surface short-wave radiation product and the second earth surface short-wave radiation product after deviation correction based on a maximum likelihood estimation algorithm to generate an earth surface short-wave radiation satellite data fusion product; and based on an optimal interpolation algorithm, carrying out data fusion by taking the earth surface short-wave radiation satellite data fusion product as a background field and taking the radiation data as a ground observation field to generate an earth surface short-wave radiation fusion grid point product. In this way, a high-precision earth surface short-wave radiation fusion lattice point product with a wide coverage range can be formed, so that the precision of a satellite product is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, in particular to the field of multi-source data fusion technology, and specifically to a method, device and equipment for fusion of satellite-ground fusion radiation observation grid products. Background Art

[0002] Solar radiation is the main energy source for all life activities on Earth and the most important factor in the formation of Earth's climate. It is of decisive significance to the surface radiation balance, energy exchange, and the formation of weather and climate. As an important component of surface solar radiation, Downward Surface Shortwave Radiation (DSSR) is an important component of surface radiation balance and a key input parameter for land surface models and climate models. Therefore, accurate estimation of DSSR is of great significance to applied research such as global radiation budget balance and solar energy estimation.

[0003] Given that the number of ground-based radiation observation stations is still relatively low and unevenly distributed, existing ground-based solar radiation observations are difficult to meet the needs of related services such as photovoltaic power generation prediction, and the application of satellite remote sensing data has become an effective way to make up for this deficiency. However, due to the changes in the sensitivity and response characteristics of instruments such as meteorological observation sensors, there are obvious systematic deviations in satellite inversion data, which leads to low accuracy of satellite products. Summary of the invention

[0004] The present invention provides a method, device and equipment for fusing satellite-ground fusion radiation observation grid products.

[0005] According to a first aspect of the present disclosure, a method for fusing satellite-ground fusion radiation observation grid products is provided. The method comprises:

[0006] Obtaining ground-based radiation data, first surface shortwave radiation products, and second surface shortwave radiation products;

[0007] performing bias correction on the first surface shortwave radiation product and the second surface shortwave radiation product;

[0008] Based on the maximum likelihood estimation algorithm, the first surface shortwave radiation product and the second surface shortwave radiation product after bias correction are fused to generate a surface shortwave radiation satellite data fusion product;

[0009] Based on the optimal interpolation algorithm, data fusion is performed with the surface shortwave radiation satellite data fusion product as the background field and the ground-based radiation data as the ground observation field to generate a surface shortwave radiation fusion grid product.

[0010] According to the above aspects and any possible implementation manner, an implementation manner is further provided, wherein obtaining ground-based radiation data, a first surface shortwave radiation product, and a second surface shortwave radiation product comprises:

[0011] Based on preset quality control rules, ground-based radiation data, first surface shortwave radiation products and second surface shortwave radiation products are obtained;

[0012] The preset quality control rules include:

[0013] Preprocessing the ground-based radiation data, the first surface shortwave radiation product, and the second surface shortwave radiation product;

[0014] Based on the time-space matching algorithm, data extraction is performed on the preprocessed ground-based radiation data, the first surface shortwave radiation product and the second surface shortwave radiation product;

[0015] The extracted data is stored in the product database to obtain multiple product data;

[0016] Calculate the QC code for each product data to obtain the corresponding ground-based observation value QC code and satellite data value QC code;

[0017] The QC code of the ground-based observation value and the QC code of the satellite data value corresponding to each product data are combined and calculated to obtain the corresponding comprehensive QC code, and the product data with the comprehensive QC code as the preset value is retained.

[0018] According to the above aspects and any possible implementation manner, an implementation manner is further provided, wherein obtaining the first surface shortwave radiation product and the second surface shortwave radiation product comprises:

[0019] Based on the bilinear interpolation algorithm, the first surface shortwave radiation product is processed into grid data with the same grid point storage method as the second surface shortwave radiation product.

[0020] According to the above aspect and any possible implementation manner, an implementation manner is further provided, wherein the bias correction of the first surface shortwave radiation product and the second surface shortwave radiation product comprises:

[0021] Taking the ground-based radiation data as true values, verifying and evaluating the first surface shortwave radiation product and the second surface shortwave radiation product, and generating a satellite radiation product system bias correction lookup table;

[0022] The first surface shortwave radiation product and the second surface shortwave radiation product are subjected to bias correction according to the satellite radiation product system bias correction lookup table.

[0023] According to the aspects described above and any possible implementation method, an implementation method is further provided, wherein the satellite radiation product system bias correction lookup table is established according to season, time period and irradiance level, and corresponds to a root mean square error lookup table.

[0024] According to the above aspects and any possible implementation manner, an implementation manner is further provided, wherein the data fusion of the first surface shortwave radiation product and the second surface shortwave radiation product after bias correction based on the maximum likelihood estimation algorithm to generate the surface shortwave radiation satellite data fusion product includes:

[0025] According to the season, time and irradiance level, the weights corresponding to the first surface shortwave radiation product and the second surface shortwave radiation product after bias correction are calculated respectively;

[0026] Based on the maximum likelihood estimation algorithm, the first surface shortwave radiation product after bias correction and the second surface shortwave radiation product after bias correction are fused according to their corresponding weights respectively to generate a surface shortwave radiation satellite data fusion product.

[0027] According to the above aspects and any possible implementation, an implementation is further provided, wherein the data fusion is performed based on the optimal interpolation algorithm, using the surface shortwave radiation satellite data fusion product as the background field and the ground-based radiation data as the ground observation field to generate the surface shortwave radiation fusion grid product, including:

[0028] Calculate the influence radius and spatial correlation variation function of each ground-based site in the ground-based radiation data according to the first surface shortwave radiation product and / or the second surface shortwave radiation product;

[0029] According to the influence radius and spatial correlation variation function of each ground-based site in the ground-based radiation data, determining the spatial variation function corresponding to each grid point and calculating the corresponding weight coefficient;

[0030] Based on the optimal interpolation algorithm and according to the weight coefficient corresponding to each grid point, the surface shortwave radiation satellite data fusion product and the ground-based radiation data corresponding to each grid point are fused to generate the surface shortwave radiation fusion grid product.

[0031] According to a second aspect of the present disclosure, a satellite-ground fusion radiation observation grid product fusion device is provided. The device comprises:

[0032] An acquisition module, used to acquire ground-based radiation data, a first surface shortwave radiation product, and a second surface shortwave radiation product;

[0033] A processing module, used for performing bias correction on the first surface shortwave radiation product and the second surface shortwave radiation product;

[0034] A generation module is used to perform data fusion on the first surface shortwave radiation product and the second surface shortwave radiation product after bias correction based on a maximum likelihood estimation algorithm to generate a surface shortwave radiation satellite data fusion product;

[0035] The generation module is also used to perform data fusion based on the optimal interpolation algorithm, taking the surface shortwave radiation satellite data fusion product as the background field and the ground-based radiation data as the ground observation field, to generate a surface shortwave radiation fusion grid product.

[0036] According to a third aspect of the present disclosure, an electronic device is provided, which includes a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the program, the method described above is implemented.

[0037] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the method described above is implemented.

[0038] The embodiments of the present application provide a method, device and equipment for fusing grid products of satellite-ground fusion radiation observations, which can obtain ground-based radiation data, a first surface shortwave radiation product and a second surface shortwave radiation product; then perform bias correction on the first surface shortwave radiation product and the second surface shortwave radiation product; then, based on the maximum likelihood estimation algorithm, perform data fusion on the first surface shortwave radiation product and the second surface shortwave radiation product after bias correction to generate a surface shortwave radiation satellite data fusion product; then, based on the optimal interpolation algorithm, perform data fusion with the surface shortwave radiation satellite data fusion product as the background field and the ground-based radiation data as the ground observation field to generate a surface shortwave radiation fusion grid product; based on this, the ground-based radiation data can be used as the true value to carry out bias correction of multi-source satellite surface shortwave radiation products, and the maximum likelihood estimation algorithm can be used to form a satellite data product of multi-source satellite surface shortwave radiation products, and then the optimal interpolation algorithm is used to fuse the satellite data product and the ground-based radiation data, and finally form a high-precision surface shortwave radiation fusion grid product with a wide coverage, thereby improving the accuracy of satellite products.

[0039] It should be understood that the contents described in the summary of the invention are not intended to limit the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, among which:

[0041] Figure 1 A flow chart of a method for fusion of satellite-ground fusion radiation observation grid products according to an embodiment of the present disclosure is shown;

[0042] Figure 2 A schematic diagram showing the influence radius and grid points of a ground-based site according to an embodiment of the present disclosure;

[0043] Figure 3 A technical flow chart of surface shortwave radiation fusion grid product according to an embodiment of the present disclosure is shown;

[0044] Figure 4 A block diagram of a satellite-ground fusion radiation observation grid product fusion device according to an embodiment of the present disclosure is shown;

[0045] Figure 5 A block diagram of an exemplary electronic device capable of implementing embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0047] In addition, the term "and / or" in this article is only a description of the association relationship between the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0048] In the present disclosure, ground-based radiation data can be used as the true value to carry out bias correction of multi-source satellite surface shortwave radiation products, and a maximum likelihood estimation algorithm can be used to form a satellite data product that integrates multi-source satellite surface shortwave radiation products. The satellite data product and the ground-based radiation data are then fused using an optimal interpolation algorithm, ultimately forming a high-precision surface shortwave radiation fusion grid product with a wide coverage, thereby improving the accuracy of satellite products.

[0049] Figure 1A flow chart of a satellite-ground fusion radiation observation grid product fusion method 100 according to an embodiment of the present disclosure is shown.

[0050] At block 110 , ground-based radiation data, a first surface shortwave radiation product, and a second surface shortwave radiation product are acquired.

[0051] At block 120 , bias correction is performed on the first surface shortwave radiation product and the second surface shortwave radiation product.

[0052] In block 130, based on a maximum likelihood estimation algorithm, data fusion is performed on the bias-corrected first surface shortwave radiation product and the second surface shortwave radiation product to generate a surface shortwave radiation satellite data fusion product.

[0053] In block 140 , based on an optimal interpolation algorithm, data fusion is performed using the surface shortwave radiation satellite data fusion product as the background field and the field-based radiation data as the ground observation field to generate a surface shortwave radiation fusion grid product.

[0054] In block 110, the ground-based radiation data may be selected from a ground-based radiation station, that is, total radiation hourly data of a ground-based site, and the radiation data is irradiance in watts per square meter (W / m2).

[0055] In some embodiments, the ground-based radiation data may be read through a data service interface, and the ground-based radiation data may be data that has undergone initial quality control such as internal consistency and limit value checks.

[0056] In some embodiments, the first surface shortwave radiation product can be the surface shortwave radiation (SSR) product of the Fengyun-4 meteorological satellite (FY-4 satellite), specifically the L2 product of the FY-4B satellite product, that is, the ground incident solar radiation product, which has a time resolution of 15 minutes, a spatial resolution of 4 km, and a data unit of W / m2, referred to as FY4B_SSR product in this article.

[0057] In some embodiments, the second surface shortwave radiation product can be a solar shortwave radiation (SWR) product of the Himawari-9 satellite, specifically an L2 product of the Himawari-9 satellite product, with a time resolution of 10 minutes, a spatial resolution of 0.05°, and a coverage area of ​​60°S-60°N, 80°E-160°W. The data unit is W / m2, referred to as H9_SWR product in this document.

[0058] In some embodiments, the first surface shortwave radiation product and the second surface shortwave radiation product are surface shortwave radiation products from different satellites.

[0059] In some embodiments, obtaining the ground-based radiation data, the first surface shortwave radiation product, and the second surface shortwave radiation product includes:

[0060] Based on preset quality control rules, ground-based radiation data, first surface shortwave radiation products and second surface shortwave radiation products are obtained;

[0061] The preset quality control rules include:

[0062] Preprocessing the ground-based radiation data, the first surface shortwave radiation product and the second surface shortwave radiation product;

[0063] Based on the time-space matching algorithm, data extraction is performed on the preprocessed ground-based radiation data, the first surface shortwave radiation product and the second surface shortwave radiation product;

[0064] The extracted data is stored in the product database to obtain multiple product data;

[0065] Calculate the QC code for each product data to obtain the corresponding ground-based observation value QC code and satellite data value QC code;

[0066] The QC code of the ground-based observation value and the QC code of the satellite data value corresponding to each product data are combined and calculated to obtain the corresponding comprehensive QC code, and the product data with the comprehensive QC code as the preset value is retained.

[0067] In some embodiments, before processing satellite radiation product data, such as the first surface shortwave radiation product and the second surface shortwave radiation product, and ground-based radiation product data, the product data is preprocessed to remove some missing values ​​and data exceeding the limit value.

[0068] In some embodiments, some data with missing values ​​are eliminated, such as data with a characteristic value of "999999".

[0069] In some embodiments, referring to the boundary values ​​of different observed products as shown in Table 1, data exceeding the boundary values ​​can be eliminated according to the official algorithm documents of different products. If the product data exceeds the corresponding boundary value, the sample is eliminated.

[0070] Table 1: Limit values ​​for different observation products

[0071] product Ground-based radiation products FY4B_SSR products H9_SWR Products Limit value (0，2000] (0，1510] (0，3000]

[0072] In some embodiments, based on the station-level quality control and center-level quality control of ground-based radiation data, a quality control algorithm suitable for satellite-ground calibration can be developed, and multiple quality control situations can be defined. The corresponding quality control (QC) codes can be as shown in Table 2.

[0073] Table 2: Correspondence table of product data quality control codes and quality control meanings

[0074]

[0075]

[0076] In some embodiments, a specific quality control process may include data extraction, data storage, QC code calculation, and comprehensive QC code determination.

[0077] In some embodiments, data can be extracted based on a time-space matching algorithm to form fields such as ground-based observation values, satellite data values, and data time. The ground-based radiation data corresponds to the ground-based observation values, and the first surface shortwave radiation product and the second surface shortwave radiation product correspond to the satellite data values.

[0078] In some embodiments, the extracted data may be stored in a product library for subsequent quality control and analysis.

[0079] In some embodiments, the ground-based observation value QC code and the satellite data value QC code may be calculated for each data record according to the definition in Table 2, so as to identify quality problems and abnormalities of the data.

[0080] In some embodiments, the specific method of determining the comprehensive QC code can be set according to the actual needs of the user, and the ground-based observation value QC code and the satellite data value QC code in the product data can be combined and calculated. For example, if their sum is 0, the comprehensive QC code is marked as 0, indicating that the data is correct; if their sum is greater than 0, the comprehensive QC code can select the larger value of the ground-based observation value QC code and the satellite data value QC code to indicate that there may be problems or errors in the data.

[0081] In some embodiments, each product data record includes elements such as ground-based observation values, satellite data values, integrated QC codes, and data time.

[0082] In some embodiments, in subsequent processing, only ground-based radiation data and satellite radiation data with a comprehensive quality control code of 0 may be selected for processing.

[0083] In some embodiments, obtaining the first surface shortwave radiation product and the second surface shortwave radiation product includes:

[0084] Based on the bilinear interpolation algorithm, the first surface shortwave radiation product is processed into grid data with the same grid point storage method as the second surface shortwave radiation product.

[0085] In some embodiments, in order to facilitate data processing and use during the generation of surface shortwave radiation satellite data fusion products, the data products can be stored in the same grid storage method as the H9_SWR product, such as equal longitude and latitude grid distribution, and the spatial resolution also uses 0.05° interval. Therefore, the FY4B_SSR product needs to be processed into the same grid data as the H9_SWR product.

[0086] In some embodiments, the bilinear interpolation method is to first perform a linear interpolation in one direction, and then perform a linear interpolation in the other direction to obtain the final interpolation result, and linear operations are used, the calculation process is relatively simple, easy to implement, the calculation efficiency is relatively high, the smoothness is good, and the practicability is strong. It is widely used in image processing, such as image scaling, rotation, etc., as well as geographic information systems, grid processing of meteorological data and other fields. In most cases, bilinear interpolation can provide an unbiased estimate, that is, the interpolation result can better reflect the actual change trend of the data near the known point, rather than simply averaging or linear extrapolating; based on this, the bilinear interpolation method can be used to process the FY4B_SSR product into the same grid data as the H9_SWR product.

[0087] Specifically, suppose there is a grid consisting of four known grid points, namely (x 1 ,y 1 )、(x 2 ,y 1 )、(x 1 ,y 2 ) and (x 2 ,y 2 ), the corresponding function value is f(x 1 ,y 1 )、f(x 2 ,y 1 )、f(x 1 ,y 2 ) and f(x 2 ,y 2 ).

[0088] First, linear interpolation in the x direction:

[0089] For a point (x,y 1 ) and (x,y 2 ) to perform linear interpolation to obtain the intermediate value:

[0090]

[0091] Then, linear interpolation in the y direction is performed on the two intermediate values ​​just obtained to obtain the final interpolation result:

[0092]

[0093] In block 120, the bias correction of the first surface shortwave radiation product and the second surface shortwave radiation product specifically includes:

[0094] Taking the ground-based radiation data as the true value, the first surface shortwave radiation product and the second surface shortwave radiation product are tested and evaluated to generate a satellite radiation product system bias correction lookup table;

[0095] According to the satellite radiation product system bias correction lookup table, the first surface shortwave radiation product and the second surface shortwave radiation product are bias corrected.

[0096] In some embodiments, the satellite radiation product system bias correction lookup table is established according to season, time period and irradiance level, and has a corresponding root mean square error (RMSE) lookup table.

[0097] In some embodiments, before data fusion is performed on the first surface shortwave radiation product and the second surface shortwave radiation product, the consistency of the ground-based radiation data with the FY4B_SSR product and the H9_SWR product may be checked and evaluated.

[0098] In some embodiments, ground-based total radiation hourly data can be used to match ground-based radiation sites with the nearest FY4B grid points and H9 grid points through the neighboring point matching method, and a satellite radiation product system bias correction lookup table can be established for different seasons, time periods, and irradiance levels. When generating the satellite radiation product system bias correction lookup table, a corresponding RMSE lookup table can also be generated.

[0099] Specifically, when establishing the satellite radiation product system bias correction lookup table, the seasons are divided into four seasons: spring, summer, autumn and winter, the time periods are divided into 12 time periods, and the lower limit of the irradiance level increases from 0 to 900 by 100, and is divided into 10 levels. The upper limit of each level is 100 higher than the lower limit, and the upper limit of the highest level is 9999. When the number of sample matches within a certain irradiance level is less than 50, the irradiance level is expanded to a higher level until the upper limit is expanded to 9999. If the number of samples is still less than 50, the irradiance level is expanded to a lower level until the lower limit is expanded to 0.

[0100] In some embodiments, the formula for calculating the deviation correction is as follows

[0101]

[0102] In the formula, S represents the corresponding season, T represents the corresponding time period, R represents the irradiance level corresponding to the satellite irradiance value, and n is the number of samples corresponding to the season, time period, and level.

[0103] Finally, the satellite radiation value after bias correction is obtained:

[0104] R satellite_bias =R satellite -bias(S,T,R)

[0105] In block 130, the above-mentioned maximum likelihood estimation algorithm is used to fuse the bias-corrected first surface shortwave radiation product and the second surface shortwave radiation product to generate a surface shortwave radiation satellite data fusion product, which specifically includes:

[0106] According to the season, time and irradiance level, the weights corresponding to the first surface shortwave radiation product and the second surface shortwave radiation product after bias correction are calculated respectively;

[0107] Based on the maximum likelihood estimation algorithm, the first surface shortwave radiation product after bias correction and the second surface shortwave radiation product after bias correction are fused according to their corresponding weights respectively to generate a surface shortwave radiation satellite data fusion product.

[0108] In some embodiments, in the process of data fusion of the bias-corrected first surface shortwave radiation product and the second surface shortwave radiation product, the maximum-likelihood estimation (MLE) method is used to fuse the bias-corrected hourly shortwave radiation products of the FY4B_SSR product and the H9_SWR product. The MLE method provides a weight value based on the error of the ground-based radiation observation value assessment.

[0109] In some embodiments, the mathematical derivation principle of the MLE method is as follows:

[0110] Likelihood function and weight: From the perspective of maximum likelihood estimation, weighted fusion can be regarded as selecting a parameter to maximize the likelihood function. Assuming that the error of each satellite data source follows a normal distribution, the fused data is also normally distributed.

[0111] Bayesian inference: Through the Bayesian method, the observations from each satellite data source can be regarded as conditionally independent observations, and the final fusion result is the weighted sum of these independent observations. In this case, the weight can be understood as the confidence based on the observation error;

[0112] Weighted sum of errors: The weighted fusion method essentially minimizes the total error by weighted sum of errors. The contribution of each data source is the square of the inverse of its error. The smaller the error, the greater the contribution.

[0113] In some embodiments, based on the above mathematical derivation principle, the process of fusing the hourly shortwave radiation products after the FY4B_SSR product and the H9_SWR product bias correction by using the MLE method includes:

[0114] For each grid point in the target grid, within the range of 70-80°E, since it exceeds the coverage of the sunflower satellite product, the FY4B_SSR product is directly used within this range. Within the range of 80-140°E, each grid point has two satellite radiation values, which come from the FY4B_SSR grid point value RFY and the H9_SWR grid point value RKH. According to the RMSE lookup table generated when the satellite radiation product system bias correction lookup table was generated, the corresponding RMSE is matched, which are σFY and σKH respectively. The fusion value can be calculated by weighted average, and the weight is determined by the uncertainty of each value, that is, RMSE. Since the FY4B_SSR product has been interpolated to the same grid points as the H9_SWR product by bilinear interpolation method in the early stage, each grid point on the grid has a corresponding FY4B_SSR grid point value and H9_SWR grid point value. In the process of deviation correction, the RMSE values ​​of the FY4B_SSR product and the H9_SWR product with the ground-based radiation data in the corresponding season, time, and irradiance level can be obtained. The inverse of the square of the RMSE value is used as the weight, and the fused grid data is obtained by calculation.

[0115] In some embodiments, the specific calculation steps of fusing the hourly shortwave radiation products after the FY4B_SSR product and the H9_SWR product bias correction using the MLE method are as follows:

[0116] Based on the above, the RMSE of the corresponding satellite observation data and ground-based observation data has been calculated by season, time period, and irradiance level. The calculation formula is as follows:

[0117]

[0118] Then calculate the weight of each value:

[0119] Weight of FY4B_SSR grid value RFY:

[0120]

[0121] Weight of H9_SWR grid value RKH:

[0122]

[0123] Calculate the total weight:

[0124] ω total =ω FY +ωKH

[0125] Calculate the weighted average to get the final fused value:

[0126]

[0127] In block 140, the above-mentioned data fusion is performed based on the optimal interpolation algorithm, with the surface shortwave radiation satellite data fusion product as the background field and the ground-based radiation data as the ground observation field, to generate the surface shortwave radiation fusion grid product, which specifically includes:

[0128] Calculate the influence radius and spatial correlation variation function of each ground-based site in the ground-based radiation data according to the first surface shortwave radiation product and / or the second surface shortwave radiation product;

[0129] According to the influence radius and spatial correlation variation function of each ground-based site in the ground-based radiation data, the spatial variation function corresponding to each grid point is determined and the corresponding weight coefficient is calculated;

[0130] Based on the optimal interpolation algorithm and according to the weight coefficient corresponding to each grid point, the surface shortwave radiation satellite data fusion product and the ground-based radiation data corresponding to each grid point are fused to generate the surface shortwave radiation fusion grid product.

[0131] In some embodiments, when fusing ground-based radiation data with surface shortwave radiation satellite data fusion products, it is necessary to first determine the shortwave radiation influence radius of each ground-based station. Since the ground-based radiation sites are sparsely distributed, the gridded satellite radiation product can be used to calculate the influence radius. In view of the previous satellite-ground radiation consistency test and evaluation, the H9_SWR product has better evaluation indicators such as correlation coefficient and root mean square error with the ground-based radiation value than the FY4B_SSR product. Therefore, the H9_SWR product can be used to evaluate the influence radius of ground-based radiation data.

[0132] It should be noted that, based on the first surface shortwave radiation product and / or the second surface shortwave radiation product, the influence radius of each ground-based site in the ground-based radiation data can be calculated. If two product data are selected to simultaneously calculate the influence radius of each ground-based site in the ground-based radiation data, the average value can be adopted.

[0133] In some embodiments, the adjacent point matching method can be used to match each ground-based site to the nearest H9_SWR product grid. Based on this H9_SWR product grid, it is expanded outward in the cross direction of the same latitude and longitude, divided into equal parts of 5 km at a time, and expanded to 120 km. The correlation coefficient and root mean square error of the grid radiation value at each 5 km point and the central grid radiation value are calculated.

[0134] In some embodiments, during the calculation process, the correlation coefficient and the root mean square error of the grid radiation value at every 5 km and the central grid radiation value are calculated by season and by the irradiance level of the central grid radiation value.

[0135] In some embodiments, after the calculation is completed, the rules for defining the influence radius may include two conditions: condition one is that the correlation coefficient is greater than 0.7; condition two is that the root mean square error is less than 20% of the upper limit of the corresponding irradiance level, but the upper limit of the root mean square error is 100.

[0136] In some embodiments, the above two conditions are in an or relationship, that is, if any one of the conditions is met, the station passes. The maximum distance that meets any one of the conditions is taken as the influence radius of the ground-based station. According to the general experience of numerical forecast assimilation and spatial variation of radiation data, the upper limit of the influence radius is set to 100 km. Finally, the influence radius corresponding to the ground-based station in different seasons and different irradiance levels can be obtained.

[0137] In some embodiments, the Optimum Interpolation (OI) algorithm provides a more accurate and detailed analysis field by combining observation data and numerical forecast models, and is often used for spatial and temporal interpolation of meteorological variables such as temperature, humidity, and wind speed. Based on the main advantages of the optimal interpolation algorithm, such as the fusion of multi-source information, that is, the optimal interpolation algorithm can effectively fuse data from different sources to improve the reliability and accuracy of the results; error minimization, that is, by minimizing the observation error and the background field error, the optimal interpolation algorithm can provide an analysis field with a smaller error; strong flexibility, that is, the optimal interpolation can be applied to different types of meteorological variables, whether it is a scalar, such as temperature, or a vector, such as wind speed); suitable for sparse data, that is, in areas with sparse observation sites, the optimal interpolation algorithm can still effectively interpolate and provide valuable meteorological information; based on this, the optimal interpolation method can be selected as the fusion algorithm for ground-based total radiation data and satellite surface shortwave radiation products.

[0138] In some embodiments, the optimal interpolation analysis first requires an initial estimate field. Since the surface shortwave radiation satellite data fusion product has a high spatial coverage, the surface shortwave radiation satellite data fusion product generated previously can be selected as the initial estimate field. At the grid points with station distribution in the grid, the ground-based observation data has a higher accuracy, so it is used as the observation value. The soil moisture fusion result A at each grid point k Equal to the initial estimate F of the point k Plus the deviation between the observed value at the grid point and the initial estimate, and this deviation is determined by the known observed values ​​O at n grid points within a certain range. i With the initial estimate F i The bias weighted estimate is obtained as follows:

[0139]

[0140] Where k is the fusion grid, i is the “effective grid”, and W i is the weight coefficient, which represents the weight assigned to the deviation between the observed value at point i and the initial estimate during estimation.

[0141] The weight coefficient W can be solved by the following formula i :

[0142]

[0143] In the formula, indicates the initial estimated field error co-correlation, represents the observation error co-correlation, λ i is the standard deviation of the observation error at point i and the initial estimate error standard deviation ratio.

[0144] The specific solution process is as follows:

[0145] When i When the following conditions are met, the analysis value A k The error variance is minimal:

[0146]

[0147] in, is the background error correlation, is the observation error co-correlation, λ i is the ratio of the standard deviation of the observed error at point i to the standard deviation of the initial estimate error, The error correlation between the analysis point and the initial estimated field.

[0148] Will Denoted as a ij ,So Can be written as:

[0149] i=1,a 11 w 1 +a 12 w 2 +a 1j w j +…+a 1n w n =μ k1

[0150] i=2,a 21 w 1 +a 22 w 2 +a 2j w j +…+a2n w n =μ k2

[0151] …

[0152] i=n,a n1 w 1 +a n2 w 2 +a nj w j +…+a nn w n =μ kn

[0153] Therefore, it can be transformed into a matrix solution problem:

[0154]

[0155] Right now:

[0156] aw=μ

[0157] w=a -1 μ

[0158] In some embodiments, the multi-source satellite surface shortwave radiation product obtained by fusion of the aforementioned MLE method, that is, the surface shortwave radiation satellite data fusion product can be selected as the background field.

[0159] In some embodiments, since the number of ground-based radiation stations is significantly lower than that of common precipitation, temperature, humidity and other stations, and the radiation data are obtained after quality control by quality control algorithms such as internal consistency and limit value checks, it can be considered that the observation of ground-based radiation data has no errors, and this item is set to 0.

[0160] In some embodiments, in the optimal interpolation algorithm, the observation error cocorrelation is considered to be an operator of the observation field. In the definition of spatial correlation of shortwave radiation, it is generally believed that the observation errors at different positions are uncorrelated. Therefore, the observation error covariance matrix is ​​a diagonal matrix. Therefore, since the observation error standard deviation is set to 0, the observation error cocorrelation matrix does not need to be calculated.

[0161] In some embodiments, considering that the above observation error standard deviation is set to 0, In The term is also 0, so the formula simplifies to The important calculation in the calculation step of solving the weight function is thus simplified to the fitting of the background error co-correlation, that is, determining the quantitative functional relationship between the error correlation and the distance between two points.

[0162] In some embodiments, the spatial correlation of satellite shortwave radiation product errors It decreases with increasing distance. You can select H9_SWR product data within a year, use the adjacent point matching method to match each ground-based site to the nearest H9_SWR product grid, and based on this H9_SWR product grid, expand outward in the cross direction of the same latitude and longitude, and divide it into 5km equal parts to 120km, and calculate the correlation coefficient between the 5km grid radiation value and the central grid radiation value. During the calculation process, the irradiance level of the seasonal and central grid radiation value is calculated to calculate the change of the correlation coefficient with distance, forming a sample of the correlation coefficient change with distance for each site by season and irradiance level, so that the negative exponential function of the spatial change of the correlation coefficient of each site by season and irradiance level can be fitted.

[0163] In some embodiments, when performing fusion, an independent spatial correlation variation function may be fitted for each site, and different spatial correlation variation functions are used to calculate weight coefficients for affected grid points.

[0164] See also Figure 2 , square points represent grid points, and circles represent stations. Each affected grid point corresponds to a different station. When corresponding to a single station, the spatial variation function of the irradiance level of the current station and the corresponding season is used. When corresponding to multiple stations, the average irradiance of multiple stations at that time is used as the corresponding irradiance level, and the samples of the correlation coefficient and distance of the corresponding season are selected to fit the corresponding spatial variation function.

[0165] In some embodiments, after the above calculation steps, a multi-source surface shortwave radiation fusion grid product, that is, a surface shortwave radiation fusion grid product, is finally formed. The range of the surface shortwave radiation fusion grid product is 70-140°E, 15-55°N, the spatial resolution is 0.05°, and the time resolution is 1 hour.

[0166] It should be noted that the above-mentioned satellite-ground fusion radiation observation grid product fusion method is not only applicable to the fusion of two satellite products, the first surface shortwave radiation product and the second surface shortwave radiation product, but the fusion of three or more surface shortwave radiation products can also refer to the above-mentioned satellite-ground fusion radiation observation grid product fusion method.

[0167] See also Figure 3 The specific implementation process of a method for fusion of satellite-ground fusion radiation observation grid products includes: using the total radiation observation data of ground-based radiation observation sites, the ground incident solar radiation (SSR) product of the FY4B satellite, and the shortwave radiation (SWR) product of the Sunflower-9 satellite, based on the bias correction method, the maximum likelihood estimation (MLE) method and the optimal interpolation (OI) method to form a multi-source fusion surface shortwave radiation grid product.

[0168] Among them, data fusion includes three steps:

[0169] (1) Taking the ground-based total radiation data as the true value, the surface shortwave radiation products of FY-4B and Sunflower-9 satellites were tested and evaluated, and the system deviation correction table of the surface shortwave radiation products of FY-4B and Sunflower-9 satellites was formed by season, time and irradiance level;

[0170] (2) Based on the satellite radiation product system bias correction table, bias correction is performed on the FY-4B and Sunflower-9 satellite radiation products;

[0171] (3) Based on the maximum likelihood estimation (MLE) method, the bias-corrected FY-4B and Sunflower-9 satellite surface shortwave radiation products are fused to form a surface shortwave radiation satellite data fusion product;

[0172] (4) Based on the optimal interpolation (OI) method, the fused surface shortwave radiation satellite data grid products are used as the background field, and the ground-based total radiation data are used as the ground observation field. The two are fused to form a set of radiation grid products with high temporal and spatial resolution covering a wide area.

[0173] According to the embodiments of the present disclosure, the following technical effects are achieved:

[0174] It can obtain ground-based radiation data, a first surface shortwave radiation product and a second surface shortwave radiation product; then perform bias correction on the first surface shortwave radiation product and the second surface shortwave radiation product; then, based on the maximum likelihood estimation algorithm, perform data fusion on the first surface shortwave radiation product and the second surface shortwave radiation product after bias correction to generate a surface shortwave radiation satellite data fusion product; then, based on the optimal interpolation algorithm, perform data fusion with the surface shortwave radiation satellite data fusion product as the background field and the ground-based radiation data as the ground observation field to generate a surface shortwave radiation fusion grid product; based on this, the ground-based radiation data can be used as the true value to carry out bias correction of multi-source satellite surface shortwave radiation products, and the maximum likelihood estimation algorithm can be used to form a satellite data product of multi-source satellite surface shortwave radiation product fusion, and then the optimal interpolation algorithm can be used to fuse the satellite data product and the ground-based radiation data, and finally a high-precision surface shortwave radiation fusion grid product with a wide coverage is formed, thereby improving the accuracy of satellite products.

[0175] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present disclosure is not limited by the order of the actions described, because according to the present disclosure, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present disclosure.

[0176] The above is an introduction to the method embodiment. The following is a further explanation of the scheme disclosed in the present invention through an apparatus embodiment.

[0177] Figure 4 FIG. 4 is a block diagram of a satellite-ground fusion radiation observation grid product fusion device 400 according to an embodiment of the present disclosure. Figure 4 As shown, the device 400 includes:

[0178] An acquisition module 410 is used to acquire ground-based radiation data, a first surface shortwave radiation product, and a second surface shortwave radiation product;

[0179] A processing module 420 is used to perform bias correction on the first surface shortwave radiation product and the second surface shortwave radiation product;

[0180] A generating module 430 is used to perform data fusion on the first surface shortwave radiation product and the second surface shortwave radiation product after bias correction based on a maximum likelihood estimation algorithm to generate a surface shortwave radiation satellite data fusion product;

[0181] The generation module 430 is also used to generate a surface shortwave radiation fusion grid product based on an optimal interpolation algorithm, using the surface shortwave radiation satellite data fusion product as the background field and the field-based radiation data as the ground observation field for data fusion.

[0182] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described module can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0183] In the technical solution disclosed herein, the acquisition, storage and application of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0184] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0185] Figure 5 A block diagram of an exemplary electronic device 500 capable of implementing an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0186] The electronic device 500 includes a computing unit 501, which can perform various appropriate actions and processes according to a computer program stored in a ROM 502 or a computer program loaded from a storage unit 508 into a RAM 503. In the RAM 503, various programs and data required for the operation of the electronic device 500 can also be stored. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An I / O interface 505 is also connected to the bus 504.

[0187] Multiple components in the electronic device 500 are connected to the I / O interface 505, including: an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a disk, an optical disk, etc.; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 509 allows the electronic device 500 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0188] The computing unit 501 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 501 performs the various methods and processes described above, such as method 100. For example, in some embodiments, the method 100 may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 508.

[0189] In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 500 via the ROM 502 and / or the communication unit 509. When the computer program is loaded into the RAM 503 and executed by the computing unit 501, one or more steps of the method 100 described above may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to execute the method 100 in any other appropriate manner (e.g., by means of firmware).

[0190] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0191] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0192] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0193] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0194] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0195] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0196] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0197] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for fusion of satellite-ground fusion radiation observation grid products, characterized in that: include: Obtaining ground-based radiation data, first surface shortwave radiation products, and second surface shortwave radiation products; performing bias correction on the first surface shortwave radiation product and the second surface shortwave radiation product; Based on the maximum likelihood estimation algorithm, the first surface shortwave radiation product and the second surface shortwave radiation product after bias correction are fused to generate a surface shortwave radiation satellite data fusion product; Based on the optimal interpolation algorithm, data fusion is performed with the surface shortwave radiation satellite data fusion product as the background field and the ground-based radiation data as the ground observation field to generate a surface shortwave radiation fusion grid product.

2. The method according to claim 1, characterized in that The obtaining of ground-based radiation data, a first surface shortwave radiation product and a second surface shortwave radiation product comprises: Based on preset quality control rules, ground-based radiation data, first surface shortwave radiation products and second surface shortwave radiation products are obtained; The preset quality control rules include: Preprocessing the ground-based radiation data, the first surface shortwave radiation product, and the second surface shortwave radiation product; Based on the time-space matching algorithm, data extraction is performed on the preprocessed ground-based radiation data, the first surface shortwave radiation product and the second surface shortwave radiation product; The extracted data is stored in the product database to obtain multiple product data; Calculate the QC code for each product data to obtain the corresponding ground-based observation value QC code and satellite data value QC code; The QC code of the ground-based observation value and the QC code of the satellite data value corresponding to each product data are combined and calculated to obtain the corresponding comprehensive QC code, and the product data with the comprehensive QC code as the preset value is retained.

3. The method according to claim 1, characterized in that The obtaining of the first surface shortwave radiation product and the second surface shortwave radiation product comprises: Based on the bilinear interpolation algorithm, the first surface shortwave radiation product is processed into grid data with the same grid point storage method as the second surface shortwave radiation product.

4. The method according to claim 1, characterized in that: The performing bias correction on the first surface shortwave radiation product and the second surface shortwave radiation product comprises: Taking the ground-based radiation data as true values, verifying and evaluating the first surface shortwave radiation product and the second surface shortwave radiation product, and generating a satellite radiation product system bias correction lookup table; The first surface shortwave radiation product and the second surface shortwave radiation product are subjected to bias correction according to the satellite radiation product system bias correction lookup table.

5. The method according to claim 4, characterized in that The satellite radiation product system bias correction lookup table is established according to season, time period and irradiance level, and has a corresponding root mean square error lookup table.

6. The method according to claim 1, characterized in that The method of fusing the first surface shortwave radiation product and the second surface shortwave radiation product after bias correction based on the maximum likelihood estimation algorithm to generate a surface shortwave radiation satellite data fusion product includes: According to the season, time and irradiance level, the weights corresponding to the first surface shortwave radiation product and the second surface shortwave radiation product after bias correction are calculated respectively; Based on the maximum likelihood estimation algorithm, the first surface shortwave radiation product after bias correction and the second surface shortwave radiation product are fused according to their corresponding weights respectively to generate a surface shortwave radiation satellite data fusion product.

7. The method according to any one of claims 1 to 6, characterized in that: The method of performing data fusion based on the optimal interpolation algorithm, taking the surface shortwave radiation satellite data fusion product as the background field and the ground-based radiation data as the ground observation field, and generating the surface shortwave radiation fusion grid product comprises: Calculate the influence radius and spatial correlation variation function of each ground-based site in the ground-based radiation data according to the first surface shortwave radiation product and / or the second surface shortwave radiation product; According to the influence radius and spatial correlation variation function of each ground-based site in the ground-based radiation data, determining the spatial variation function corresponding to each grid point and calculating the corresponding weight coefficient; Based on the optimal interpolation algorithm and according to the weight coefficient corresponding to each grid point, the surface shortwave radiation satellite data fusion product and the ground-based radiation data corresponding to each grid point are fused to generate the surface shortwave radiation fusion grid product.

8. A satellite-ground fusion radiation observation grid product fusion device, characterized in that: include: An acquisition module, used to acquire ground-based radiation data, a first surface shortwave radiation product, and a second surface shortwave radiation product; A processing module, used for performing bias correction on the first surface shortwave radiation product and the second surface shortwave radiation product; A generation module is used to perform data fusion on the first surface shortwave radiation product and the second surface shortwave radiation product after bias correction based on a maximum likelihood estimation algorithm to generate a surface shortwave radiation satellite data fusion product; The generation module is also used to perform data fusion based on the optimal interpolation algorithm, taking the surface shortwave radiation satellite data fusion product as the background field and the ground-based radiation data as the ground observation field, to generate a surface shortwave radiation fusion grid product.

9. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-7.

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