A Method and Apparatus for Global Precipitation Product Evaluation and Precipitation Data Fusion Based on Multiple Error Interpretation Indicators

Abstract

This invention relates to a method for evaluating global precipitation products and fusing precipitation data based on the fusion of multiple error interpretation indices. On one hand, by ranking the performance of different error interpretation indices, a correlation matrix is ​​obtained. Then, weighting factors for different error interpretation indices are calculated. The preprocessed results of the error interpretation indices are weighted and fused with the weighting factors to obtain a fusion value that quantitatively describes the comprehensive performance of global precipitation products. Using this fusion value as weight, a high-precision precipitation fusion value is obtained. Simultaneously, the comprehensive performance of various global precipitation products is ranked according to the magnitude of the comprehensive performance fusion value, identifying the global precipitation product with the best comprehensive performance. This invention obtains a fusion value of multiple error interpretation indices that quantifies the comprehensive performance of global precipitation products by aggregating the results of multiple error interpretation indices and weighting and fusing them, thereby obtaining a ranking of the comprehensive performance of various global precipitation products and a precipitation fusion value with significantly improved accuracy.

Description

Technical Field

[0001] This invention relates to the fields of hydrology and meteorology, and in particular to a method and apparatus for global precipitation product evaluation and precipitation data fusion based on the fusion of multiple error interpretation indicators. Background Technology

[0002] High-precision precipitation data is crucial for accurately representing the spatiotemporal variations of regional precipitation; precipitation is one of the important parameters in various Earth system models, global water cycle, and energy cycle. Based on satellite, atmospheric reanalysis models, and surface precipitation observations, domestic and international research institutions and researchers have developed various global precipitation products, providing rich precipitation data support for fields such as hydrology, meteorology, climate, ecology, and agriculture. Precipitation exhibits strong spatiotemporal heterogeneity, and obtaining high-precision precipitation information remains challenging with current technologies and methods, especially in areas lacking surface precipitation observations, where existing global precipitation products have significant errors and uncertainties. To fully understand the performance and errors of existing global precipitation products, leverage the advantages of different global precipitation products, and meet specific application needs and research objectives, the authenticity verification of global precipitation products is a necessary step before applying them to various scenarios. Improving precipitation accuracy through multi-source precipitation data fusion is a key means and approach to expanding the depth and breadth of these products' applications. The authenticity verification of global precipitation products mainly uses high-precision surface precipitation products as reference values, combined with a series of error interpretation indicators, to quantify the errors and performance of global precipitation products from different error characteristics.

[0003] Furthermore, existing multi-source precipitation data fusion methods often use correlation coefficients as weights to obtain high-precision precipitation fusion values ​​through weighted fusion. However, each error interpretation index can only capture and quantify a certain characteristic of the error, failing to reflect the overall distribution characteristics of the error independently. This leads to inconsistencies in the conclusions regarding the optimal performance of global precipitation products guided by different error interpretation indices, making it difficult to determine which global precipitation product has the best overall performance. This significantly impacts the judgment of the overall performance of global precipitation products and the accurate selection of products in practical applications. Similarly, using the result of a single error interpretation index to determine the weights in data fusion makes it difficult to accurately and comprehensively characterize the error characteristics and overall performance of global precipitation products, resulting in precipitation fusion values ​​that are unlikely to reach the optimal level. Summary of the Invention

[0004] The purpose of this invention is to at least address one of the shortcomings of the prior art by providing a method for global precipitation product evaluation and precipitation data fusion based on the fusion of multiple error interpretation indices.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: Specifically, a global precipitation product evaluation and precipitation data fusion method based on the fusion of multiple error interpretation indices is proposed, including the following: Step 110: Obtain global precipitation products and surface precipitation products for the target area, and unify the spatiotemporal resolution of the global precipitation products and surface precipitation products; Step 120: Using the ground precipitation product as a reference value for ground precipitation in the target area, calculate various different error interpretation indices of the global precipitation product to obtain a first result, and perform standardization and directional consistency processing on the first result to obtain a preprocessed first result; Step 130: Construct a performance ranking matrix based on the preprocessed first result; Step 140: Calculate the correlation matrix of the performance ranking matrix to obtain the first weight factor for each error interpretation index; Step 150: For each global precipitation product, its error interpretation index is weighted and accumulated according to the first weighting factor to obtain the fusion value of the current global precipitation product based on the weighted accumulation of all its error interpretation indices. Step 160: Use the magnitude of the fusion value as a representation of the comprehensive performance of global precipitation products in the target area, sort them, and then evaluate the global precipitation products. Step 170: Using a pre-selected independent ground precipitation product other than the aforementioned ground precipitation product as a reference value for ground precipitation in the target area, for the pure satellite global precipitation product, run steps 120 to 150 to obtain the fused value of the pure satellite global precipitation product, and use this as the second weighting factor for the pure satellite global precipitation product in the target area. Based on the second weighting factor, perform weighted accumulation on the pure satellite global precipitation product to obtain a high-precision precipitation fused value.

[0006] Furthermore, specifically, the global precipitation products include IMERG-F, GSMAP-G, CHRIPS, PCDR, ERA5, MSWEP, and MGP, with spatial and temporal resolutions of 0.25° and daily, respectively.

[0007] Furthermore, specifically, the error interpretation metrics include, Detection rate, false alarm rate, success index, root mean square error, correlation coefficient, bias, and Kling-Gupta efficiency coefficient.

[0008] Furthermore, specifically, the process of standardizing and directional consistency processing the first result to obtain the preprocessed first result includes: For the false alarm rate, root mean square error and bias in the error interpretation index, the positive correlation between the larger the index value and the better the performance is obtained by taking the absolute value of the result and inverting it, thus completing the direction consistency processing; The error interpretation index after completing the direction consistency processing is then standardized. The expression for the standardization process is as follows: ; in, Let j be the standardized value of the error interpretation index for the i-th global precipitation product; Let j be the result value of the error interpretation index for the i-th global precipitation product; Let j be the minimum value of the j-th error interpretation index among all global precipitation products; The j-th error interpretation index is the maximum value among all global precipitation products.

[0009] Furthermore, specifically, construct a performance ranking matrix. for, ; in, Let i be the performance ranking of the i-th global precipitation product on the j-th error interpretation index.

[0010] Furthermore, specifically, the process of calculating the correlation matrix of the performance ranking matrix to obtain the first weight factor for each error interpretation metric includes, The calculated correlation matrix The expression is: ; Among them, coef( () indicates calculating the correlation coefficient. The element in the middle is the correlation coefficient; Based on the correlation matrix, the weight factor for each error interpretation index is calculated, and the expression for the weight factor is as follows: ; in, Let be the weight factor for the j-th error interpretation index; This represents the sum of the j-th column of the correlation matrix; It is the sum of all elements of the correlation matrix.

[0011] Furthermore, specifically, the expression for calculating the weighted sum of all error interpretation indices for the current global precipitation product is as follows: ; in, This is the fusion value of all error interpretation index results for the i-th global precipitation product.

[0012] Furthermore, specifically, the calculation process for obtaining high-precision precipitation agglomeration values ​​includes, The pure satellite global precipitation products include IMERG-E, IMERG-L, GSMAP-N, and GSMAP-M; The expression for the weighted fusion is: ; Where MP is the high-precision precipitation fusion value, Let k be the precipitation estimate for the k-th pure satellite global precipitation product. This is the fusion value of all error interpretation index results for the k-th pure satellite global precipitation product.

[0013] This invention also proposes a global precipitation product evaluation and precipitation data fusion device based on the fusion of multiple error interpretation indices, including the following: The data acquisition module is used to acquire global precipitation products and surface precipitation products of the target area, and to unify the spatiotemporal resolution of the global precipitation products and surface precipitation products. The preprocessing module is used to calculate various error interpretation indices of the global precipitation product as a reference value for the ground precipitation in the target area to obtain a first result, and to standardize and perform directional consistency processing on the first result to obtain a preprocessed first result. The first weight factor calculation module is used to construct a performance ranking matrix based on the preprocessed first result, and calculate the correlation matrix of the performance ranking matrix to obtain the first weight factor for each error interpretation index. The fusion value calculation module is used to calculate the fusion value of the current global precipitation product by weighting and accumulating its error interpretation indicators according to the first weighting factor for each global precipitation product. The global precipitation product evaluation module is used to characterize the comprehensive performance of global precipitation products in the target area based on the magnitude of the fused values, and to rank them to evaluate the global precipitation products. The precipitation fusion value calculation module is used to use a pre-selected independent ground precipitation product other than the ground precipitation product as the reference value of ground precipitation in the target area. For pure satellite global precipitation products, the preprocessing module is run to the fusion value calculation module to obtain the fusion value of the pure satellite global precipitation products. This value is used as the second weighting factor of the pure satellite global precipitation products in the target area. Based on the second weighting factor, the pure satellite global precipitation products are weighted and accumulated to obtain a high-precision precipitation fusion value.

[0014] The present invention also proposes an electronic device, comprising: At least one storage device for storing a computer program for the method proposed in this invention; At least one processor is configured to execute the computer program of the storage device, wherein when the computer program is run, the processor is configured to execute the method proposed in this invention.

[0015] The beneficial effects of this invention are as follows: This invention proposes a method and apparatus for evaluating global precipitation products and fusing precipitation data based on the fusion of multiple error interpretation indices. By introducing a correlation matrix for ranking the performance of error interpretation indices, the weighting factors of different error interpretation indices are determined, thereby weighting and fusing the results of multiple error interpretation indices to obtain a fusion value that can quantitatively describe the comprehensive performance of global precipitation products. This allows for the identification of the global precipitation product with the best comprehensive performance among multiple global precipitation products. This addresses the problem that existing authenticity verification methods cannot individually reflect the comprehensive performance of global precipitation products through all error interpretation indices, and that the conclusions of the best-performing global precipitation products guided by different error interpretation indices are often inconsistent. This invention provides a method for objectively quantifying the comprehensive performance of global precipitation products, and offers a means and approach to identify the global precipitation product with the best comprehensive performance from multiple global precipitation products, providing strong methodological support for users to select the most suitable global precipitation product. Furthermore, by using the fusion value, which can quantitatively describe the comprehensive performance of global precipitation products, as the weight of global precipitation products, a high-precision precipitation fusion value is obtained through weighted fusion. This solves the problem that traditional methods use an error interpretation index to determine the weight, which makes it difficult to accurately and comprehensively characterize the error characteristics and comprehensive performance of global precipitation products, and the resulting precipitation fusion value is difficult to achieve the optimal value. Attached Figure Description

[0016] The above and other features of this disclosure will become more apparent from the detailed description of the embodiments illustrated in conjunction with the accompanying drawings. In the accompanying drawings, the same reference numerals denote the same or similar elements. Obviously, the drawings described below are merely some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained from these drawings without any creative effort. In the drawings: Figure 1 A flowchart illustrating a global precipitation product evaluation and precipitation data fusion method based on the fusion of multiple error interpretation indices, provided in an embodiment of the present invention. Figure 2 A schematic diagram of the structure of the authenticity verification and multi-source precipitation data fusion device provided in this embodiment of the invention; Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0017] The following will provide a clear and complete description of the concept, specific structure, and technical effects of the present invention in conjunction with embodiments and accompanying drawings, so as to fully understand the purpose, solution, and effects of the present invention. It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The same reference numerals used throughout the accompanying drawings indicate the same or similar parts.

[0018] Example 1, referring to Figure 1 This invention proposes a method for global precipitation product evaluation and precipitation data fusion based on the fusion of multiple error interpretation indices, including the following: Step 110: Obtain global precipitation products and surface precipitation products for the target area, and unify the spatiotemporal resolution of the global precipitation products and surface precipitation products; Step 120: Using the ground precipitation product as a reference value for the ground precipitation in the target area (using the ground precipitation product as a reference value, calculate the result of the error interpretation index of the global precipitation product on the observation grid containing ground rain gauges), calculate multiple different error interpretation indices of the global precipitation product (which can be determined according to the type of error interpretation index to be calculated in advance) to obtain a first result, and perform standardization and directional consistency processing on the first result to obtain a preprocessed first result; Step 130: Construct a performance ranking matrix based on the preprocessed first result; Step 140: Calculate the correlation matrix of the performance ranking matrix to obtain the first weight factor for each error interpretation index; Step 150: For each global precipitation product, its error interpretation index is weighted and accumulated according to the first weighting factor to obtain the fusion value of the current global precipitation product based on the weighted accumulation of all its error interpretation indices (here, all error interpretation indices refer to all different error interpretation indices determined in the calculation of the first result). Step 160: Use the magnitude of the fusion value as a representation of the comprehensive performance of global precipitation products in the target area, sort them, and then evaluate the global precipitation products. Among them, the best global precipitation product is identified by the fusion value of the results of multiple error interpretation indicators. The fusion values ​​of all global precipitation products are sorted from large to small. The larger the fusion value, the better the overall performance and the higher the overall performance ranking, thus identifying the best global precipitation product in terms of overall performance. Step 170: Using a pre-selected independent surface precipitation product (other than the aforementioned surface precipitation product) as a reference value for surface precipitation in the target area, and for the pure satellite global precipitation product, run steps 120 to 150 to obtain the fused value of the pure satellite global precipitation product. Use this fused value as the second weighting factor for the pure satellite global precipitation product in the target area. Based on the second weighting factor, perform a weighted summation of the pure satellite global precipitation product to obtain a high-precision precipitation fused value. Step 170 considers that the process of obtaining a high-precision precipitation fused value is only related to the pure satellite global precipitation product; therefore, other surface precipitation products are selected (a higher-precision surface precipitation product can be selected as a reference relative to other global precipitation products). This ensures that there is no data overlap between the pure satellite global precipitation product and the global precipitation product mentioned above when calculating the fused value, thus obtaining a more accurate precipitation fused value.

[0019] In a preferred embodiment of the present invention, the global precipitation products include IMERG-F, GSMAP-G, CHRIPS, PCDR, ERA5, MSWEP, and MGP, with spatial resolution and temporal resolution of 0.25° and daily, respectively.

[0020] In a preferred embodiment of the present invention, the error interpretation index specifically includes: Detection rate, false alarm rate, success index, root mean square error, correlation coefficient, bias, and Kling-Gupta efficiency coefficient.

[0021] In a preferred embodiment of the present invention, specifically, the process of standardizing and performing directional consistency processing on the first result to obtain the preprocessed first result includes: For the false alarm rate, root mean square error and deviation in the error interpretation indicators (considering that the larger their values ​​are, the worse the corresponding product performance), the positive correlation between the larger the value of the indicator and the better the performance is obtained by taking the absolute value of the result and inverting it, thus completing the directional consistency processing; The error interpretation index after completing the direction consistency processing is then standardized. The expression for the standardization process is as follows: ; in, Let j be the standardized value of the error interpretation index for the i-th global precipitation product; Let j be the result value of the error interpretation index for the i-th global precipitation product; Let j be the minimum value of the j-th error interpretation index among all global precipitation products; The j-th error interpretation index is the maximum value among all global precipitation products.

[0022] As a preferred embodiment of the present invention, specifically, a performance ranking matrix is ​​constructed. for, ; in, Let i be the performance ranking of the i-th global precipitation product on the j-th error interpretation index.

[0023] In a preferred embodiment of the present invention, specifically, the process of calculating the correlation matrix of the performance ranking matrix to obtain the first weight factor for each error interpretation index includes: The calculated correlation matrix The expression is: ; Among them, coef( () indicates calculating the correlation coefficient. The element in the middle is the correlation coefficient; Based on the correlation matrix, the weight factor for each error interpretation index is calculated, and the expression for the weight factor is as follows: ; in, Let be the weight factor for the j-th error interpretation index; This represents the sum of the j-th column of the correlation matrix; It is the sum of all elements of the correlation matrix.

[0024] In a preferred embodiment of the present invention, specifically, the expression for calculating the fusion value of the current global precipitation product based on the weighted sum of all its error interpretation indices is as follows: ; in, This is the fusion value of all error interpretation index results for the i-th global precipitation product.

[0025] As a preferred embodiment of the present invention, specifically, the calculation process for obtaining high-precision precipitation fusion values ​​includes, The pure satellite global precipitation products include IMERG-E, IMERG-L, GSMAP-N, and GSMAP-M; The expression for the weighted fusion is: ; Where MP is the high-precision precipitation fusion value, Let k be the precipitation estimate for the k-th pure satellite global precipitation product. This is the fusion value of all error interpretation index results for the k-th pure satellite global precipitation product. In this formula, the summation is equivalent to accumulating from k=1 to k=4, which are the above 4 pure satellite global precipitation products.

[0026] As can be seen from the spatial distribution map of China's best-performing products under different error interpretation indices by traditional authenticity verification methods, the conclusions of the best-performing products guided by each error interpretation index are inconsistent, making it difficult to identify the precipitation product with the best overall performance. This makes it difficult for users to select the most suitable product, and it is necessary to develop new methods to solve this problem. Therefore, it is necessary to select the precipitation product with the best overall performance through the method proposed in this invention.

[0027] In practical applications, the spatial distribution map of global precipitation products with the best overall performance in China, obtained by the method of combining the authenticity verification of global precipitation products and the fusion of multi-source precipitation data provided by the present invention, shows that the MGP is the global precipitation product with the best overall performance in most grids. It can clearly identify the best precipitation product in China and solve the problem that traditional authenticity verification methods are difficult to identify products with the best overall performance.

[0028] For four precipitation events, the best-performing global precipitation product for China exhibits regional and event-dependent attributes. For light rain events, ERA5 and CHRIPS are the best-performing precipitation products for southern China, while MGP is the best-performing product for other regions. For moderate rain events, MGP is the best-performing precipitation product for southern China, while PCDR and CHRIPS are the best-performing products for other regions. For heavy rain events, the best precipitation products are diverse. For torrential rain events, IMERG-F is the best-performing precipitation product for most parts of China. Similarly, the method provided by this invention can clearly identify the best precipitation product for different precipitation events, solving the problem that traditional authenticity verification methods are unable to identify the best-performing product.

[0029] A comparison of the spatial distribution of three error indices of the product produced by the method of the present invention, which combines global precipitation product authenticity verification and multi-source precipitation data fusion, with other products in China shows that MF is the product produced by the method of the present invention. This product significantly and effectively improves the performance of precipitation data in most parts of China in terms of correlation coefficient CC, bias β, and KGE, thus demonstrating the advanced nature of the method of the present invention.

[0030] Reference Figure 2 Example 2: This invention also proposes a global precipitation product evaluation and precipitation data fusion device based on the fusion of multiple error interpretation indices, including the following: The data acquisition module is used to acquire global precipitation products and surface precipitation products of the target area, and to unify the spatiotemporal resolution of the global precipitation products and surface precipitation products. The preprocessing module is used to calculate various error interpretation indices of the global precipitation product as a reference value for the ground precipitation in the target area to obtain a first result, and to standardize and perform directional consistency processing on the first result to obtain a preprocessed first result. The first weight factor calculation module is used to construct a performance ranking matrix based on the preprocessed first result, and calculate the correlation matrix of the performance ranking matrix to obtain the first weight factor for each error interpretation index. The fusion value calculation module is used to calculate the fusion value of the current global precipitation product by weighting and accumulating its error interpretation indicators according to the first weighting factor for each global precipitation product. The global precipitation product evaluation module is used to characterize the comprehensive performance of global precipitation products in the target area based on the magnitude of the fused values, and to rank them to evaluate the global precipitation products. The precipitation fusion value calculation module is used to use a pre-selected ground precipitation product other than the aforementioned ground precipitation product as a reference value for ground precipitation in the target area. For pure satellite global precipitation products, the preprocessing module is run to the fusion value calculation module to obtain the fusion value of the pure satellite global precipitation products. This value is then used as the second weighting factor for the pure satellite global precipitation products in the target area. Based on the second weighting factor, the pure satellite global precipitation products are weighted and accumulated to obtain a high-precision precipitation fusion value.

[0031] Reference Figure 3 Example 3: Based on the method in the embodiments of the present invention, an electronic device is provided in this embodiment of the present invention, as shown in Figure 7. This electronic device may include: a processor 310, a communication interface 320, a memory 330, and a communication bus 340. The communication bus 340 interconnects the processor 310, the communication interface 320, and the memory 330 to achieve communication. The processor 310 can call computer program instructions stored in the memory 330 to execute the method in the above embodiments.

[0032] The computer program stored in the aforementioned memory 330 is implemented as a software function and can be sold or used as an independent product. In this case, the software product can be stored in a computer's readable storage medium. That is to say, the technical method of this invention, either in essence or as a contribution to the prior art, or in part as a part of the technical method, can be presented in the form of a software product. This software product is stored on a storage medium and can execute all or part of the steps of the method described in the embodiments of this invention on a computer, such as a personal computer, server, or network device.

[0033] Furthermore, the modules described above as separate components may or may not be physically separate. Similarly, the components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of the solution in this embodiment, depending on actual needs.

[0034] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0035] If the integrated module is implemented as a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or system capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0036] Although the description of the invention has been quite detailed and particularly of several described embodiments, it is not intended to limit it to any of these details or embodiments or any particular embodiment, but should be considered as providing a broad possible interpretation of the claims by referring to the appended claims and taking into account the prior art, thereby effectively covering the intended scope of the invention. Furthermore, the invention has been described above with respect to embodiments foreseeable by the inventors in order to provide a useful description, and non-substantial modifications to the invention that have not yet been foreseen may still represent equivalent modifications.

[0037] The above description is merely a preferred embodiment of the present invention. The present invention is not limited to the above-described embodiments. Any embodiment that achieves the technical effects of the present invention using the same means should fall within the protection scope of the present invention. Within the protection scope of the present invention, various modifications and variations can be made to the technical solutions and / or implementation methods.

Claims

1. A global precipitation product evaluation and precipitation data fusion method based on fusion of multiple error interpretation indicators, characterized in that, Including the following: Step 110: Obtain global precipitation products and surface precipitation products for the target area, and unify the spatiotemporal resolution of the global precipitation products and surface precipitation products; Step 120: Using the ground precipitation product as a reference value for ground precipitation in the target area, calculate various different error interpretation indices of the global precipitation product to obtain a first result, and perform standardization and directional consistency processing on the first result to obtain a preprocessed first result; Step 130: Construct a performance ranking matrix based on the preprocessed first result; Step 140: Calculate the correlation matrix of the performance ranking matrix to obtain the first weight factor for each error interpretation index; Step 150: For each global precipitation product, its error interpretation index is weighted and accumulated according to the first weighting factor to obtain the fusion value of the current global precipitation product based on the weighted accumulation of all its error interpretation indices. Step 160: Use the magnitude of the fusion value as a representation of the comprehensive performance of global precipitation products in the target area, sort them, and then evaluate the global precipitation products. Step 170: Using a pre-selected independent ground precipitation product other than the aforementioned ground precipitation product as a reference value for ground precipitation in the target area, for the pure satellite global precipitation product, run steps 120 to 150 to obtain the fused value of the pure satellite global precipitation product, and use this as the second weighting factor for the pure satellite global precipitation product in the target area. Based on the second weighting factor, perform weighted accumulation on the pure satellite global precipitation product to obtain a high-precision precipitation fused value.

2. The global precipitation product evaluation and precipitation data fusion method based on fusion of multiple error interpretation indicators according to claim 1, characterized in that, Specifically, the global precipitation products include IMERG-F, GSMAP-G, CHRIPS, PCDR, ERA5, MSWEP, and MGP, with spatial and temporal resolutions of 0.25° and daily, respectively. 3.The global precipitation product evaluation and precipitation data fusion method based on fusion of multiple error interpretation indicators, according to claim 1, characterized in that, Specifically, the error interpretation metrics include, Detection rate, false alarm rate, success index, root mean square error, correlation coefficient, bias, and Kling-Gupta efficiency coefficient.

4. The global precipitation product evaluation and precipitation data fusion method based on fusion of multiple error interpretation indicators, according to claim 3, characterized in that, Specifically, the process of standardizing and directional consistency processing the first result to obtain the preprocessed first result includes: For the false alarm rate, root mean square error and bias in the error interpretation index, the positive correlation between the larger the index value and the better the performance is obtained by taking the absolute value of the result and inverting it, thus completing the direction consistency processing. The error interpretation index after completing the direction consistency processing is then standardized. The expression for the standardization process is as follows: ； in, Let j be the standardized value of the error interpretation index for the i-th global precipitation product; Let j be the result value of the error interpretation index for the i-th global precipitation product; Let j be the minimum value of the j-th error interpretation index among all global precipitation products; The j-th error interpretation index is the maximum value among all global precipitation products.

5. The method for global precipitation product evaluation and precipitation data fusion based on the fusion of multiple error interpretation indices as described in claim 1, characterized in that, Specifically, construct a performance ranking matrix. for, ； in, Let i be the performance ranking of the i-th global precipitation product on the j-th error interpretation index.

6. The method for global precipitation product evaluation and precipitation data fusion based on the fusion of multiple error interpretation indices as described in claim 5, characterized in that, Specifically, the process of calculating the correlation matrix of the performance ranking matrix to obtain the first weight factor for each error interpretation index includes, The calculated correlation matrix The expression is: ； Among them, coef( () indicates calculating the correlation coefficient. The element in the middle is the correlation coefficient; Based on the correlation matrix, the weight factor for each error interpretation index is calculated, and the expression for the weight factor is as follows: ； in, Let be the weight factor for the j-th error interpretation index; This represents the sum of the j-th column of the correlation matrix; It is the sum of all elements of the correlation matrix.

7. The method for global precipitation product evaluation and precipitation data fusion based on the fusion of multiple error interpretation indices as described in claim 6, characterized in that, Specifically, the expression for calculating the weighted sum of all error interpretation indices for the current global precipitation product is as follows: ； in, This is the fusion value of all error interpretation index results for the i-th global precipitation product.

8. The method for global precipitation product evaluation and precipitation data fusion based on the fusion of multiple error interpretation indices as described in claim 7, characterized in that, Specifically, the calculation process for obtaining high-precision precipitation blending values ​​includes: The pure satellite global precipitation products include IMERG-E, IMERG-L, GSMAP-N, and GSMAP-M; The expression for the weighted fusion is: ； Where MP is the high-precision precipitation fusion value, Let k be the precipitation estimate for the k-th pure satellite global precipitation product. This is the fusion value of all error interpretation index results for the k-th pure satellite global precipitation product.

9. A global precipitation product evaluation and precipitation data fusion device based on the fusion of multiple error interpretation indices, characterized in that, Including the following: The data acquisition module is used to acquire global precipitation products and surface precipitation products of the target area, and to unify the spatiotemporal resolution of the global precipitation products and surface precipitation products. The preprocessing module is used to calculate various error interpretation indices of the global precipitation product as a reference value for the ground precipitation in the target area to obtain a first result, and to standardize and perform directional consistency processing on the first result to obtain a preprocessed first result. The first weight factor calculation module is used to construct a performance ranking matrix based on the preprocessed first result, and calculate the correlation matrix of the performance ranking matrix to obtain the first weight factor for each error interpretation index. The fusion value calculation module is used to calculate the fusion value for each global precipitation product by weighting and accumulating its error interpretation indicators according to the first weighting factor. The global precipitation product evaluation module is used to characterize the comprehensive performance of global precipitation products in the target area based on the magnitude of the fused values, and to rank them to evaluate the global precipitation products. The precipitation fusion value calculation module is used to use a pre-selected independent ground precipitation product other than the ground precipitation product as the reference value of ground precipitation in the target area. For pure satellite global precipitation products, the preprocessing module is run to the fusion value calculation module to obtain the fusion value of the pure satellite global precipitation products. This value is used as the second weighting factor of the pure satellite global precipitation products in the target area. Based on the second weighting factor, the pure satellite global precipitation products are weighted and accumulated to obtain a high-precision precipitation fusion value.

10. An electronic device, characterized in that, include: At least one storage device for storing a computer program for the method of any one of claims 1-8; At least one processor is configured to execute the computer program of the storage device, wherein when the computer program is run, the processor is configured to perform the method of any one of claims 1-8.

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