Consistency evaluation method, device and equipment based on satellite-ground rainfall detection product

Abstract

The embodiment of the invention provides a consistency evaluation method, device and equipment based on satellite-ground rainfall detection products, and is applied to the technical field of atmospheric detection. The method comprises the following steps: acquiring foundation rainfall data and a satellite rainfall detection product; based on a preset identification conversion relation, obtaining a ground precipitation identification product according to the foundation precipitation data; performing time matching and space matching on the satellite rainfall detection product and the ground rainfall identification product to obtain a satellite-ground rainfall detection product; the satellite-ground rainfall detection products are fused according to stations and time; and based on a preset evaluation index and a preset evaluation dimension, carrying out consistency evaluation on the fused satellite-ground rainfall detection product. In this way, data can be observed by using the ground rain gauge, authenticity inspection can be carried out through matching and analysis of satellite-ground data, consistency analysis and evaluation work of satellite-ground rainfall detection products can be carried out, and support is provided for manufacturing and application of satellite-ground rainfall fusion products.

Description

Technical Field

[0001] This disclosure relates to the field of data processing technology, and more particularly to the field of atmospheric detection technology, specifically to a consistency evaluation method, apparatus, and equipment based on satellite-to-ground precipitation detection products. Background Technology

[0002] The spatiotemporal distribution of global precipitation is one of the most important variables in the systematic research of meteorology, climate, hydrology, ecology, economics, agriculture, and other disciplines. Satellites, as a crucial means of space-based observation, can provide relatively continuous spatiotemporal observations of global precipitation distribution, becoming an important tool for monitoring and studying global precipitation changes. With the increasing quantification of remote sensing products, the need to develop technologies and methods for verifying the authenticity of quantitative products is becoming increasingly urgent.

[0003] However, due to the extremely uneven spatial and temporal distribution and intensity variation of precipitation, conventional rain gauges and ground-based radars can only measure a limited spatial range, making precipitation one of the most difficult meteorological and hydrological parameters to measure. Summary of the Invention

[0004] This disclosure provides a method, apparatus, equipment, and storage medium for consistency evaluation based on satellite-to-ground precipitation detection products.

[0005] According to a first aspect of this disclosure, a consistency assessment method based on satellite-to-ground precipitation detection products is provided. The method includes: Acquire ground-based precipitation data and satellite precipitation detection products; Based on the preset identifier conversion relationship, a surface precipitation identifier product is obtained from the ground precipitation data; The satellite precipitation detection product and the ground precipitation labeling product are time-matched and space-matched to obtain a satellite-to-ground precipitation detection product. The aforementioned satellite precipitation detection products are integrated according to station and time. Based on preset evaluation indicators and preset evaluation dimensions, a consistency evaluation is conducted on the fused satellite-to-ground precipitation detection products.

[0006] In addition to the aspects and any possible implementations described above, a further implementation is provided, wherein obtaining the surface precipitation labeling product based on the ground precipitation data according to the preset labeling conversion relationship includes: Based on the precipitation data of the foundation precipitation, the corresponding foundation precipitation label conversion value is obtained; The ground precipitation labeling product is obtained based on the station latitude and longitude of the ground precipitation data and the ground precipitation label conversion value.

[0007] In addition to the aspects and any possible implementations described above, a further implementation is provided in which time matching of the satellite precipitation detection product and the ground precipitation labeling product includes: The transit time of the satellite observation pixels is obtained based on the satellite orbit parameters and scan line time count of the satellite precipitation detection product. Determine the time matching window based on the transit time; Based on the time matching window, the satellite precipitation detection product and the ground precipitation labeling product are time-matched.

[0008] In addition to the aspects and any possible implementations described above, a further implementation is provided in which spatial matching of the satellite precipitation detection product and the ground precipitation labeling product includes: The satellite network is obtained based on the geographic coordinates of the satellite observation pixels of the satellite precipitation detection product; Map the station latitude and longitude of the ground-based precipitation data to the satellite network; Based on the mapped satellite network, spatial matching is performed on the satellite precipitation detection products and the ground precipitation labeling products.

[0009] In addition to the aspects and any possible implementations described above, a further implementation is provided in which, after fusing the satellite-to-ground precipitation detection products according to station and time, the method further includes: Based on preset feature values ​​or threshold values, the fused satellite-to-ground precipitation detection products are labeled and removed.

[0010] In addition to the aspects described above and any possible implementations, a further implementation is provided, wherein the preset evaluation indicators include false alarm rate, false negative rate, hit rate, and success rate.

[0011] In addition to the aspects and any possible implementations described above, a further implementation is provided, wherein the preset evaluation dimensions include spatial dimension, altitude dimension, time dimension, and holistic dimension.

[0012] According to a second aspect of this disclosure, a conformity assessment device based on satellite-to-ground precipitation detection products is provided. The device includes: The acquisition module is used to acquire ground-based precipitation data and satellite precipitation detection products; The conversion module is used to obtain a ground precipitation labeling product based on the ground precipitation data according to a preset labeling conversion relationship; The matching module is used to perform time and space matching between the satellite precipitation detection product and the ground precipitation labeling product to obtain the satellite-to-ground precipitation detection product. The fusion module is used to fuse the satellite-to-ground precipitation detection products according to station and time. The evaluation module is used to conduct a consistency evaluation of the fused satellite-to-ground precipitation detection products based on preset evaluation indicators and preset evaluation dimensions.

[0013] According to a third aspect of this disclosure, an electronic device is provided. The electronic device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the program to implement the method described above.

[0014] According to a fourth aspect of this disclosure, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the method described above.

[0015] This application provides a consistency evaluation method based on satellite-to-ground precipitation detection products. This method acquires ground-based precipitation data and satellite precipitation detection products; then, based on a preset identifier conversion relationship, obtains ground precipitation identifier products from the ground-based precipitation data; further, it performs time and spatial matching between the satellite precipitation detection products and the ground precipitation identifier products to obtain satellite-to-ground precipitation detection products; finally, it fuses the satellite-to-ground precipitation detection products according to station and time; and then, based on preset evaluation indicators and preset evaluation dimensions, it performs a consistency evaluation on the fused satellite-to-ground precipitation detection products. Based on this, ground rain gauge observation data can be used to conduct authenticity verification through matching and analysis of satellite and ground data, and to perform consistency analysis and evaluation of satellite-to-ground precipitation detection products, providing support for the production and application of satellite-to-ground fused precipitation products.

[0016] It should be understood that the description in the Summary of the Invention is not intended to limit the key or essential features of the embodiments of this disclosure, nor is it intended to restrict the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0017] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. The drawings are provided for a better understanding of the invention and are not intended to limit the scope of this disclosure. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein: Figure 1 A flowchart is shown for a consistency assessment method based on satellite-to-ground precipitation detection products according to an embodiment of the present disclosure; Figure 2 A block diagram of a conformity assessment apparatus for satellite-to-ground precipitation detection products according to an embodiment of the present disclosure is shown; Figure 3 A block diagram of an exemplary electronic device capable of implementing embodiments of the present disclosure is shown. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0019] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0020] In this disclosure, ground rain gauge observation data can be used to conduct authenticity verification and consistency analysis and evaluation of satellite-ground precipitation detection products through matching and analysis of satellite-ground data, providing support for the production and application of satellite-ground precipitation fusion products.

[0021] Figure 1 A flowchart of a consistency evaluation method 100 based on satellite-to-ground precipitation detection products according to an embodiment of the present disclosure is shown.

[0022] In box 110, obtain ground-based precipitation data and satellite precipitation detection products.

[0023] In some embodiments, the FY-3E satellite, equipped with 11 instruments, can monitor various elements such as the three-dimensional atmosphere, ocean wind field, nighttime low light, the sun, and the ionosphere, and enhance the monitoring and analysis capabilities of weather, climate, atmospheric environment, and space weather. It has also begun to stably provide quantitative inversion products. The satellite precipitation detection products can be selected from the FY-3E L2 quantitative inversion products, namely the precipitation detection products inverted by the Fengyun-3E satellite microwave hygrometer II (MWHS II).

[0024] Specifically, the precipitation detection product can be one of the FY-3E L2 quantitative inversion products, with a spatial resolution of 16KM (nadir point), a coverage area of ​​60°S~80°N, a scan width of 2660km / track, a temporal resolution of 28 tracks / day, and a data format of HDF5. The product outputs global surface precipitation markers. Compared to the FY-3D precipitation detection product, which is only applicable to the sea surface, FY-3E will be applicable to land, water, sea ice and other surface environments.

[0025] In some embodiments, precipitation detection products retrieved using the microwave humidity meter II (MWHS II) of Fengyun-3E satellite can be used in multiple research directions, such as precipitation intensity retrieval, atmospheric temperature and humidity profile retrieval, and satellite data numerical assimilation applications, providing necessary support for precipitation screening.

[0026] In frame 120, based on the preset label conversion relationship, the ground precipitation label product is obtained from the ground precipitation data.

[0027] In some embodiments, since ground-based minute precipitation data is precipitation amount data, while satellite precipitation detection products are precipitation markers (i.e., whether precipitation occurred), the ground-based precipitation data needs to be preprocessed into ground precipitation marker products to form proxy products. This allows for subsequent spatiotemporal matching between the ground-based products and the corresponding satellite-borne precipitation detection products, generating corresponding spatiotemporal matching data results and providing data samples for the next evaluation step. For example, after obtaining ground-based minute precipitation data, it needs to be processed into a precipitation-related product based on whether the precipitation amount is greater than 0. The correspondence between the precipitation markers of ground station precipitation and satellite-ground precipitation detection products is shown in Table 1.

[0028] Table 1: Correspondence between precipitation labels of ground stations and satellite-ground precipitation detection products In some embodiments, the above-mentioned method of obtaining a surface precipitation labeling product based on ground precipitation data according to a preset labeling conversion relationship specifically includes: Based on the precipitation data from the foundation precipitation data, the corresponding foundation precipitation label conversion value is obtained; Surface precipitation labeling products are obtained based on the station latitude and longitude of the ground precipitation data and the ground precipitation label conversion value.

[0029] In some embodiments, the processing relationship for obtaining the corresponding ground precipitation label conversion value based on the precipitation amount of the ground precipitation data is shown in Table 2.

[0030] Table 2: Processing Relationships for Converting Precipitation Amount to Precipitation Label Values In some embodiments, since satellite products are applicable to land, water, and sea ice, ground-based stations need to be classified, such as into land stations and sea stations. This can be done by pre-classifying stations based on their latitude and longitude, classifying island stations, buoy stations, and platform stations as sea stations, and other inland stations as land stations. To improve data processing efficiency, stations are further subdivided into land / sea, and then converted to land / sea precipitation status based on actual observed precipitation markers. The ground precipitation labeling product is obtained based on the station latitude and longitude of the ground precipitation data and the converted ground precipitation marker values; the conversion relationship of the ground precipitation markers is shown in Table 3.

[0031] Table 3: Conversion Relationship between Precipitation Amount, Precipitation Marker Values, and Surface Precipitation Label Products In frame 130, time and space matching are performed on satellite precipitation detection products and ground precipitation labeling products to obtain satellite-to-ground precipitation detection products.

[0032] In some embodiments, the matching algorithm between spaceborne precipitation detection products and ground stations includes temporal matching and spatial matching. For example, FY-3E is temporally matched with ground precipitation labeling product data to form a matching result; FY-3E is spatially matched with ground precipitation labeling product data to form a matching result.

[0033] In some embodiments, time matching is performed between satellite precipitation detection products and ground precipitation labeling products, specifically including: The transit time of satellite observation pixels is obtained based on the satellite orbit parameters and scan line time counts of the satellite precipitation detection products. Determine the time matching window based on the transit time; Based on the time matching window, time matching is performed on satellite precipitation detection products and ground precipitation labeling products.

[0034] In some embodiments, ground-based precipitation data are continuous minute-by-minute observation data. It is necessary to select stations within the transit period based on the satellite transit time, and after processing, match them by utilizing the consistent time characteristics.

[0035] In some embodiments, since the microwave hygrometer (MWHS II) onboard the FY-3E satellite operates in polar orbit, its precipitation detection products are orbital-level products with a resolution of approximately 15 km below the satellite's nadir, featuring high scanning frequency and wide coverage. In contrast, ground-based precipitation data is typically recorded continuously at the minute level, with a temporal resolution far exceeding that of instantaneous satellite observations. To achieve effective matching between the two in the temporal dimension, firstly, the transit time of each satellite observation pixel can be precisely determined based on the FY-3E satellite's orbital parameters and scan line times (Scnlin_daycnt and Scnlin_mscnt). Subsequently, a reasonable time matching window, such as ±5 minutes, is constructed to filter precipitation records for the corresponding time period from the ground-based precipitation data.

[0036] In some embodiments, if a valid precipitation record exists at any observation time within the time window, the station is considered to have a representative precipitation event at that time, and its consistency with the corresponding satellite pixels can be verified. This strategy leverages the continuity of ground-based precipitation data, combined with the discontinuity and transient nature of satellite observations, to ensure the rationality and representativeness of the time matching. A minimum threshold can be set for the number of valid precipitation records to eliminate instrument noise or false alarms.

[0037] In some embodiments, spatial matching of satellite precipitation detection products and ground precipitation labeling products specifically includes: The satellite network is obtained based on the geographic coordinates of the satellite observation pixels of the satellite precipitation detection product; Map the latitude and longitude of ground-based precipitation data stations to a satellite network; Based on the mapped satellite network, spatial matching is performed on satellite precipitation detection products and ground precipitation labeling products.

[0038] In some embodiments, spatial matching aims to map FY-3E satellite observation pixels to ground observation stations geographically, thereby verifying the consistency of satellite-ground data in the spatial dimension. The MWHS II precipitation detection product provides geographic coordinates (Latitude, Longitude) for each observation pixel with a spatial resolution of approximately 15 km, and the product retains the original scan structure and resolution of the observations. Since the satellite product has a resolution of 15 km, it may contain multiple stations within its spatial range. Therefore, when a grid in the satellite network contains multiple stations, it can be set so that precipitation is considered to have occurred at any one of the multiple stations.

[0039] In some embodiments, the latitude and longitude of ground-based precipitation stations can be mapped to the satellite network, either simultaneously with or before / after time matching. Nearest neighbor interpolation or grid matching algorithms are then used to assign each ground station to its nearest satellite pixel for spatial matching. Projection transformation can be introduced here to improve matching accuracy.

[0040] In some embodiments, when a satellite pixel contains multiple stations, the following matching logic can be used: If at least one station within a grid point observes precipitation within the corresponding time window, then the satellite grid point is determined to be "with precipitation"; If no precipitation is observed at any station within the grid point, it is determined as "no precipitation".

[0041] In some embodiments, the above method combines the sensitivity of microwave scattering channels to precipitation particles with the point distribution characteristics of ground stations, enhancing the robustness of the matching results through a "multi-point judgment" approach. For scattering contamination pixels appearing in satellite observations, i.e., those with large Scattering Index values, ground station precipitation information can be used to verify whether it truly reflects precipitation events or is a misjudgment caused by interference from terrain, snow surfaces, high-altitude ice clouds, etc. Furthermore, terrain-corrected altitude and land-sea masking can be used to correct station matching accuracy, improving the accuracy of spatial matching.

[0042] In frame 140, the satellite-to-ground precipitation detection products are integrated according to station and time.

[0043] In some embodiments, to further ensure the accuracy of spatiotemporal matching, the real-time matching results and spatial matching results, i.e., the satellite-to-ground precipitation detection products, can be merged according to the station and time to form a unified spatiotemporal matching result.

[0044] In some embodiments, after fusing the satellite-to-ground precipitation detection products according to station and time, the method further includes: Based on preset feature values ​​or threshold values, the fused satellite-to-ground precipitation detection products are labeled and removed.

[0045] In some embodiments, preset feature values ​​or limit values ​​can be set according to the user's actual needs.

[0046] In some embodiments, to ensure the accuracy of the evaluation, data with eigenvalues ​​or exceeding the threshold values ​​need to be removed before participating in the evaluation. According to the official algorithm documentation of different observation products, the threshold values ​​of different observation products are shown in Table 4. If an observation product exceeds the corresponding threshold value, the sample needs to be marked and removed.

[0047] Table 4: Boundary values ​​for different observation products In box 150, a consistency assessment is conducted on the fused satellite-to-ground precipitation detection products based on preset evaluation indicators and preset evaluation dimensions.

[0048] In some embodiments, preset evaluation metrics and preset evaluation dimensions can be set according to the user's actual needs.

[0049] In some embodiments, the spatiotemporal matching results can be evaluated according to preset evaluation indicators, and the evaluation results can be obtained according to spatial and temporal dimensions.

[0050] In some embodiments, the aforementioned preset evaluation indicators include, but are not limited to, fair warning score, false alarm rate / false alarm rate / false alarm rate, missed alarm rate, detection rate / hit rate, and success rate.

[0051] In some embodiments, the frequency statistics listed after classifying by category based on foundation and actual conditions are shown in Table 5.

[0052] Table 5: Frequency statistics based on foundation and actual conditions, categorized by type. In some embodiments, a fair prognostic assessment includes: Detection rate / hit rate includes: False alarm rate / false alarm rate / false alarm rate includes: Success rate includes: The false negative rate includes: Where N represents the number of ground observation stations; i represents the station number; This represents the values ​​obtained from satellites, with an average value of [value missing]. ; This represents the measured values ​​from the ground station, and its average value is... FAR stands for False Alarm Rate, which is the ratio of false alarms to the total number of stations predicting precipitation. MAR stands for False Miss Rate, which is the ratio of false misses to the total number of stations observing precipitation. POD stands for Accuracy Rate, which is the ratio of correct predictions to the total number of stations observing precipitation, reflecting the probability of accurately predicting precipitation events. PC stands for Success Rate, which is the ratio of correct predictions to the total number of stations observing precipitation, reflecting the probability of accurately predicting precipitation events. The values ​​for FAR, False Miss Rate, and Accuracy Rate all range from 0 to 1. A higher Accuracy Rate and a lower False Miss Rate indicate a lower degree of missed precipitation events and better prediction accuracy from the satellite product. A higher FAR indicates a higher degree of false alarms regarding precipitation events from the satellite product.

[0053] In some embodiments, the aforementioned preset evaluation dimensions include, but are not limited to, spatial dimensions, altitude dimensions, time dimensions, and overall dimensions, i.e., evaluation can be conducted by station, by province, by month, by year, by poster, and by region.

[0054] In some embodiments, to further analyze the differences and patterns in satellite-to-ground precipitation products, a consistency analysis and evaluation can be performed on the spatiotemporal matching results, combining meteorological laws to conduct evaluations on different dimensions, as shown below: 1. The impact of station, province, geographical region, altitude, and surface on precipitation; 2. Monthly, seasonal, and annual variations in precipitation; The consistency and quality of satellite-to-ground precipitation were assessed from the above dimensions to identify equipment problems with ground-based precipitation and to verify the authenticity of satellite products.

[0055] In some embodiments, for an overall assessment, the evaluation can be performed based on the results of matching different satellites, or based on the results of a single orbit or a certain period of time. The overall assessment result is calculated by taking all the matching data samples from each satellite and applying the evaluation formula. In some embodiments, for evaluation of different spatial dimensions, the matching samples can be divided into different samples according to the regional attributes of the ground stations based on the province and administrative region to which the ground observation stations are located, and the evaluation results of sub-stations, provinces and regions can be calculated according to the evaluation formula.

[0056] In some embodiments, for evaluation of different poster height dimensions, all matching data samples can be divided into multiple different groups based on the geographical altitude of the base station, which can be accurate to the meter, and the evaluation results for each altitude can be calculated according to the evaluation formula.

[0057] In some embodiments, the evaluation can be conducted according to months or years for different time dimensions, or the time can be divided into four seasons: winter (December 1 to February 28), spring (March 1 to May 31), summer (June 1 to August 31), and autumn (September 1 to November 30), and the evaluation results for each time period can be calculated according to the evaluation formula.

[0058] According to the embodiments of this disclosure, the following technical effects are achieved: This system can acquire ground-based precipitation data and satellite precipitation detection products; then, based on a preset identifier conversion relationship, obtain ground precipitation identifier products from the ground-based precipitation data; further, perform time and spatial matching between the satellite precipitation detection products and the ground precipitation identifier products to obtain satellite-ground precipitation detection products; then, fuse the satellite-ground precipitation detection products according to station and time; and finally, conduct a consistency evaluation of the fused satellite-ground precipitation detection products based on preset evaluation indicators and dimensions. Based on this, ground rain gauge observation data can be used to conduct authenticity verification and consistency analysis and evaluation of satellite-ground precipitation detection products through matching and analysis of satellite and ground data, providing support for the production and application of satellite-ground fused precipitation products.

[0059] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this disclosure is not limited to the described order of actions, because according to this disclosure, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this disclosure.

[0060] The above is an introduction to the method embodiments. The following describes the solution described in this disclosure further through device embodiments.

[0061] Figure 2 A block diagram of a conformity assessment apparatus 200 based on satellite-to-ground precipitation detection products according to an embodiment of the present disclosure is shown. Figure 2 As shown, the device 200 includes: Acquisition module 210 is used to acquire ground-based precipitation data and satellite precipitation detection products; The conversion module 220 is used to obtain ground precipitation labeling products based on ground precipitation data according to a preset labeling conversion relationship; The matching module 230 is used to perform time and space matching between satellite precipitation detection products and ground precipitation labeling products to obtain satellite-to-ground precipitation detection products. The fusion module 240 is used to fuse satellite-to-ground precipitation detection products according to station and time. Evaluation module 250 is used to conduct a consistency evaluation of the fused satellite-to-ground precipitation detection products based on preset evaluation indicators and preset evaluation dimensions.

[0062] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the described module can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0063] The acquisition, storage, and application of user personal information involved in the technical solution disclosed herein comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0064] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0065] Figure 3A block diagram of an exemplary electronic device 300 capable of implementing embodiments 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 processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0066] Electronic device 300 includes a computing unit 301, which can perform various appropriate actions and processes according to a computer program stored in ROM 302 or a computer program loaded into RAM 303 from storage unit 308. RAM 303 can also store various programs and data required for the operation of electronic device 300. The computing unit 301, ROM 302, and RAM 303 are interconnected via bus 304. I / O interface 305 is also connected to bus 304.

[0067] Multiple components in electronic device 300 are connected to I / O interface 305, including: input unit 306, such as keyboard, mouse, etc.; output unit 307, such as various types of displays, speakers, etc.; storage unit 308, such as disk, optical disk, etc.; and communication unit 309, such as network card, modem, wireless transceiver, etc. Communication unit 309 allows electronic device 300 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0068] The computing unit 301 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 301 performs the various methods and processes described above, such as method 100. For example, in some embodiments, method 100 may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 308.

[0069] In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 300 via ROM 302 and / or communication unit 309. When the computer program is loaded into RAM 303 and executed by computing unit 301, one or more steps of method 100 described above may be performed. Alternatively, in other embodiments, computing unit 301 may be configured to perform method 100 by any other suitable means (e.g., by means of firmware).

[0070] Various embodiments 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-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0071] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0072] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0073] 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 pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, 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 voice input, speech input, or tactile input).

[0074] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0075] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0076] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0077] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A consistency evaluation method based on satellite-to-ground precipitation detection products, characterized in that, include: Acquire ground-based precipitation data and satellite precipitation detection products; Based on the preset identifier conversion relationship, a surface precipitation identifier product is obtained from the ground precipitation data; The satellite precipitation detection product and the ground precipitation labeling product are time-matched and space-matched to obtain a satellite-to-ground precipitation detection product. The aforementioned satellite precipitation detection products are integrated according to station and time. Based on preset evaluation indicators and preset evaluation dimensions, a consistency evaluation is conducted on the fused satellite-to-ground precipitation detection products.

2. The method according to claim 1, characterized in that, The method of obtaining surface precipitation labeling products based on the ground precipitation data according to the preset labeling conversion relationship includes: Based on the precipitation data of the foundation precipitation, the corresponding foundation precipitation label conversion value is obtained; The ground precipitation labeling product is obtained based on the station latitude and longitude of the ground precipitation data and the ground precipitation label conversion value.

3. The method according to claim 1, characterized in that, Time matching of the satellite precipitation detection product and the ground precipitation labeling product includes: The transit time of the satellite observation pixels is obtained based on the satellite orbit parameters and scan line time count of the satellite precipitation detection product. Determine the time matching window based on the transit time; Based on the time matching window, the satellite precipitation detection product and the ground precipitation labeling product are time-matched.

4. The method according to claim 3, characterized in that, Spatial matching of the satellite precipitation detection product and the ground precipitation labeling product includes: The satellite network is obtained based on the geographic coordinates of the satellite observation pixels of the satellite precipitation detection product; Map the station latitude and longitude of the ground-based precipitation data to the satellite network; Based on the mapped satellite network, spatial matching is performed on the satellite precipitation detection products and the ground precipitation labeling products.

5. The method according to claim 1, characterized in that, After fusing the satellite precipitation detection products according to station and time, the method further includes: Based on preset feature values ​​or threshold values, the fused satellite-to-ground precipitation detection products are labeled and removed.

6. The method according to any one of claims 1 to 5, characterized in that, The preset evaluation indicators include false alarm rate, false negative rate, hit rate, and success rate.

7. The method according to any one of claims 1 to 5, characterized in that, The preset evaluation dimensions include spatial dimension, altitude dimension, time dimension, and overall dimension.

8. A consistency evaluation device based on satellite-to-ground precipitation detection products, characterized in that, include: The acquisition module is used to acquire ground-based precipitation data and satellite precipitation detection products; The conversion module is used to obtain a ground precipitation labeling product based on the ground precipitation data according to a preset labeling conversion relationship. The matching module is used to perform time and space matching between the satellite precipitation detection product and the ground precipitation labeling product to obtain the satellite-to-ground precipitation detection product. The fusion module is used to fuse the satellite-to-ground precipitation detection products according to station and time. The evaluation module is used to conduct a consistency evaluation of the fused satellite-to-ground precipitation detection products based on preset evaluation indicators and preset evaluation dimensions.

9. An electronic device, characterized in that, include: At least one processor; as well as A memory that is communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in any one of claims 1-7.

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

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