Method for improving and testing reflectivity consistency of ground-based radar net and electronic equipment

Abstract

The invention provides a foundation radar net reflectivity consistency improving and testing method and electronic equipment, and relates to the technical field of meteorological analysis. The method comprises the following steps: taking a first reflectivity factor value of a first wave band measured by each ground-based radar in a ground-based radar network in observation of each position of a target rainfall area within a preset time as an independent variable, and applying a linear correction relational expression to obtain a reflectivity factor improved value of each ground-based radar; and according to a first consistency result determined by each reflectivity factor improvement value and a second consistency result determined by each first reflectivity factor value, determining an inspection result of reflectivity factor consistency improvement of the ground-based radar network formed by each ground-based radar.

Description

Technical Field

[0001] This application relates to the field of meteorological analysis technology, and more specifically, to a method for improving and verifying the reflectivity consistency of a ground-based radar network, as well as electronic equipment. Background Technology

[0002] Multiple new-generation Doppler weather radars play a crucial role in weather and climate monitoring, forecasting, and data assimilation. These devices are widely distributed, with varying technical support and maintenance conditions, leading to significant reflectivity detection biases between different Doppler weather radars—that is, inconsistencies in reflectivity between two Doppler weather radars. These inconsistencies in reflectivity factors between two Doppler weather radars significantly affect the observation accuracy of weather radar networks and limit the quantitative application of ground-based weather radar network data.

[0003] Accurate calibration is crucial for reducing inconsistencies between ground-based radars and minimizing system deviations caused by calibration differences between ground-based radars at various sites. However, due to limitations in the accuracy of calibration instruments, time drift of equipment parameters, and limitations in end-to-end calibration methods, accurate calibration of ground-based radar indicators is extremely difficult. Summary of the Invention

[0004] In view of this, this application provides a method and electronic device for improving and verifying the reflectivity consistency of a ground-based radar network.

[0005] One aspect of this application provides a method for improving and verifying the reflectivity consistency of a ground-based radar network, comprising: using the first reflectivity factor value of a first band measured by each ground-based radar in the ground-based radar network at each location of a target precipitation area within a preset time as the independent variable, and applying a linear correction relation to obtain the improved reflectivity factor value of each of the aforementioned ground-based radars; wherein, the aforementioned linear correction relation is used to characterize the relationship between the reflectivity factor value of the first band obtained by the ground-based radar at each location of the target precipitation area and the reflectivity factor value of the first band obtained by the spaceborne radar at the same location at the same time; the reflectivity factor value of the first band of the aforementioned spaceborne radar is obtained by correcting the second reflectivity factor value of the second band of the aforementioned spaceborne radar; and determining the verification result of the reflectivity consistency improvement of the ground-based radar network composed of the various ground-based radars based on the first consistency result determined by each of the aforementioned improved reflectivity factor values ​​and the second consistency result determined by each of the aforementioned first reflectivity factor values.

[0006] According to an embodiment of this application, the process of determining the linear correction relationship includes: obtaining the reflectivity factor correction value corresponding to the second reflectivity factor value at each location in the precipitation area based on the correspondence between the reflectivity factor value of the second band and the reflectivity factor value of the first band of the ground-based radar; wherein, the precipitation area is the overlapping area observed by the spaceborne radar and the ground-based radar during the transit time of the spaceborne radar; determining the coefficients of the preset linear relationship based on the reflectivity factor correction value at each of the above locations and the first reflectivity factor value; and determining the linear correction relationship based on the coefficients of the preset linear relationship.

[0007] According to an embodiment of this application, determining the coefficients of a preset linear relationship based on the reflectance factor correction value at each of the above-mentioned positions and the first reflectance factor value includes: preprocessing and quality screening the matching samples composed of the reflectance factor correction values ​​at each of the above-mentioned positions and the first reflectance factor value to obtain the optimal matching sample; using the first reflectance factor value in the optimal matching sample as the independent variable and the reflectance factor correction value in the optimal matching sample corresponding to the first reflectance factor value as the dependent variable to determine the coefficients of the preset linear relationship.

[0008] According to an embodiment of this application, based on the correspondence between the reflectivity factor value of the second band and the reflectivity factor value of the first band of the ground-based radar, the reflectivity factor correction value corresponding to the second reflectivity factor value at each location in the precipitation area is obtained, including: establishing a lookup table characterizing the correspondence between the reflectivity factor value of each of the second bands and the reflectivity factor value of the first band of the ground-based radar; and determining the reflectivity factor correction value based on the reflectivity factor value of the first band of the ground-based radar corresponding to the second reflectivity factor value in the lookup table.

[0009] According to an embodiment of this application, preprocessing and quality screening are performed on the matching samples composed of the reflectivity factor correction values ​​and the first reflectivity factor values ​​at each of the above-mentioned locations to obtain the optimal matching sample. This includes: removing matching samples from the matching samples whose corresponding heights at each of the above-mentioned locations are lower than a preset height to obtain an initial matching sample; determining matching samples from the initial matching samples whose reflectivity factor correction values ​​and the first reflectivity factor values ​​are both greater than a preset reflectivity factor threshold to obtain a preprocessed matching sample; and performing quality screening on the preprocessed matching sample to obtain the optimal matching sample.

[0010] According to an embodiment of this application, the preprocessed matching samples are subjected to quality screening to obtain the optimal matching samples, including: removing matching samples with terrain occlusion from the preprocessed matching samples to obtain a first matching sample; determining matching samples in the first matching samples whose radial distance meets a preset distance condition to obtain a second matching sample; wherein the radial distance is used to characterize the straight-line distance between each of the ground-based radars and the precipitation area; determining matching samples in the second matching samples whose beam filling coefficient meets a preset filling coefficient condition to obtain a third matching sample; and determining matching samples in the third matching samples for the stratiform precipitation area below the bright band to obtain the optimal matching sample.

[0011] According to an embodiment of this application, determining the test result of reflectivity consistency improvement of a ground-based radar network composed of various ground-based radars based on a first consistency result determined by each of the aforementioned reflectivity factor improvement values ​​and a second consistency result determined by each of the aforementioned first reflectivity factor values ​​includes: determining overlapping echo samples of the ground-based radar network based on each of the aforementioned reflectivity factor improvement values ​​and each of the aforementioned first reflectivity factor values; performing reflectivity consistency improvement test on radar combinations composed of multiple ground-based radars in the ground-based radar network based on the aforementioned overlapping echo samples to obtain multiple initial test results, and using the multiple aforementioned initial test results as the test result of reflectivity consistency improvement of the ground-based radar network composed of various ground-based radars; wherein, the aforementioned radar combination is composed of multiple ground-based radars whose radar detection ranges overlap.

[0012] According to an embodiment of this application, determining the overlapping echo samples of the ground-based radar network based on each of the aforementioned reflectivity factor improvement values ​​and each of the aforementioned first reflectivity factor values ​​includes: sorting all ground-based radars in the ground-based radar network to obtain a ground-based radar sequence; wherein the scanning areas of two adjacent ground-based radars in the ground-based radar sequence have overlapping areas; and determining the overlapping echo samples of the ground-based radar network based on the reflectivity factor improvement values ​​and first reflectivity factor values ​​corresponding to the same precipitation intensity under a preset precipitation event for each of the two adjacent ground-based radars in the ground-based radar sequence.

[0013] According to an embodiment of this application, based on the aforementioned overlapping echo samples, a reflectivity consistency test is performed on a radar combination consisting of multiple ground-based radars in the aforementioned ground-based radar network to obtain multiple initial test results, including: determining the aforementioned first consistency result and the aforementioned second consistency result of two adjacent ground-based radars based on the aforementioned overlapping echo samples; using the difference between the aforementioned first consistency result and the aforementioned second consistency result of two adjacent ground-based radars as the initial test result of the two adjacent ground-based radars to obtain multiple initial test results.

[0014] Another aspect of this application provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to perform the methods described above.

[0015] According to the embodiments of this application, by accurately corresponding the transit time of spaceborne radar with the observation time of ground-based radar, and combining the linear correction formula, the reflectivity factor deviation caused by band differences and spatiotemporal mismatch of observation between spaceborne and ground-based radars is effectively eliminated, significantly improving the observation accuracy of reflectivity factor of ground-based radar. Furthermore, by using the large-scale observation data of spaceborne radar as a reference benchmark to correct the single-point observation data of ground-based radar network, the observation standards of different radars within the ground-based radar network can be unified, enhancing the consistency and comparability of observation data from various devices within the radar network. Based on the comparative analysis of the corrected reflectivity factor improvement value and the original observation value, the observation error of the ground-based radar network can be directly quantified, providing accurate data support for the daily calibration and maintenance of radar equipment. In addition, the ground-based radar network data after consistency verification can be efficiently integrated with spaceborne radar data, which can leverage the advantages of high spatiotemporal resolution of ground-based radar and the global coverage capability of spaceborne radar to provide reliable data support for large-scale, high-precision precipitation monitoring. Attached Figure Description

[0016] The above and other objects, features and advantages of this application will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0017] Figure 1 A flowchart illustrating the method for improving and verifying the reflectivity consistency of a ground-based radar network according to an embodiment of this application is shown schematically.

[0018] Figure 2 A flowchart illustrating a preprocessing and quality screening method according to an embodiment of this application is shown schematically.

[0019] Figure 3 This illustration schematically shows a data matching method for spatial consistency between ground-based radars according to an embodiment of this application.

[0020] Figure 4 A block diagram of a ground-based radar network reflectivity consistency improvement and verification apparatus according to an embodiment of this application is shown schematically.

[0021] Figure 5 A block diagram of an electronic device suitable for implementing a method for improving and verifying the reflectivity consistency of a ground-based radar network, according to an embodiment of this application, is shown schematically. Detailed Implementation

[0022] The embodiments of this application will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of this application. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of this application for ease of explanation. However, it will be apparent that one or more embodiments may be implemented without these specific details. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of this application.

[0023] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0024] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0025] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0026] In the embodiments of this application, the collection, updating, analysis, processing, use, transmission, provision, disclosure, and storage of data (e.g., including but not limited to user personal information) comply with relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. In particular, necessary measures have been taken to prevent unauthorized access to user personal information data and to safeguard user personal information security, network security, and national security.

[0027] In the embodiments of this application, the user's authorization or consent was obtained before obtaining or collecting the user's personal information.

[0028] Spaceborne radars, after rigorous internal and external calibration, can serve as reference standards for correcting ground-based radars. However, most existing technologies focus on one-to-one correction between spaceborne and ground-based radars, neglecting the improvement in the consistency of the ground-based radar network and whether the consistency and continuity among multiple ground-based radars have improved after correction. Therefore, it is necessary to establish methods for evaluating the consistency improvement of ground-based radar networks and verifying the evaluation results.

[0029] Ground-based radar plays a crucial role in severe weather warnings and meteorological operations. Using a new generation of Doppler weather radar as the ground-based radar, the observation data parameters include radar reflectivity factor. It employs the VCP21 volume scan mode specifically for precipitation, completing a volume scan at nine elevation angles every 6 minutes. Ground-based radar types include S-band and C-band. The S-band ground-based weather radar has a radial resolution of 250m, while the C-band ground-based weather radar has a radial resolution of 150m and a beamwidth of 0.98°.

[0030] The Global Precipitation Measurement (GPM) satellite carries Ka-band and Ku-band precipitation radars to achieve dual-frequency precipitation radar (DPR) detection. GPM DPR boasts high accuracy and sensitivity, accurately capturing even weak precipitation. It operates continuously and stably, and its measurement data has undergone rigorous internal and external calibration and verification, ensuring good consistency and high reliability. GPM DPR orbits at an altitude of 407 km, with a measurement range of -65°S to 65°N. Vertically, it covers an altitude of 0 km to 22 km (176 layers in 125m increments) and horizontally, covering 245 km with 49 pixels and a nadir of approximately 5 km. Secondary data products include KaPR and KuPR inversion results, as well as information on scan time, precipitation location, three-dimensional precipitation rate, and precipitation type, along with precipitation particle spectral parameters.

[0031] This application establishes an algorithm for improving the consistency of reflectivity factors of ground-based radar networks based on spaceborne radar, generates improved ground-based radar network base data, and verifies the improvement effect of reflectivity factor consistency of ground-based radar networks through mosaic analysis and the established consistency evaluation algorithm between ground-based radars.

[0032] Figure 1 A flowchart illustrating a method for improving and verifying the reflectivity consistency of a ground-based radar network according to an embodiment of this application is shown.

[0033] like Figure 1 As shown, the method includes operations S101 to S102.

[0034] In operation S101, the first reflectivity factor of the first band measured by each location of the target precipitation area observed by each ground-based radar in the ground-based radar network within a preset time is used as the independent variable. A linear correction relation is applied to obtain the improved reflectivity factor value of each ground-based radar. The linear correction relation is used to characterize the relationship between the reflectivity factor value of the first band obtained by the ground-based radar at each location of the target precipitation area and the reflectivity factor value of the first band obtained by the spaceborne radar at the same location at the same time. The reflectivity factor value of the first band of the spaceborne radar is obtained by correcting the second reflectivity factor value of the second band of the spaceborne radar.

[0035] In operation S102, based on the first consistency result determined by each reflectivity factor improvement value and the second consistency result determined by each first reflectivity factor value, the test result of the reflectivity consistency improvement of the ground-based radar network composed of each ground-based radar is determined.

[0036] In the embodiments of this application, the basic data products of a new generation Doppler weather radar single station that have undergone quality control are used, and the volume scan mode VCP21 for precipitation is adopted. Volume scan data at 9 elevation angles are obtained every 6 minutes, with a beamwidth of 0.98°, an S-band ground-based radar radial resolution of 250m, an effective detection radius of 230km, and the data is stored in polar coordinate format.

[0037] According to an embodiment of this application, the process of determining the linear correction formula includes: obtaining the reflectivity factor correction value corresponding to the second reflectivity factor value at each location in the precipitation area based on the correspondence between the reflectivity factor value of the second band and the reflectivity factor value of the first band of the ground-based radar; wherein, the precipitation area is the overlapping area observed by the spaceborne radar and the ground-based radar during the transit time of the spaceborne radar; determining the coefficients of the preset linear formula based on the reflectivity factor correction value and the first reflectivity factor value at each location; and determining the linear correction formula based on the coefficients of the preset linear formula.

[0038] Specifically, based on the reflectance factor correction value and the first reflectance factor value at each location, the coefficients of the preset linear relationship are determined, including: preprocessing and quality screening the matching samples composed of the reflectance factor correction value and the first reflectance factor value at each location to obtain the optimal matching sample; using the first reflectance factor value in the optimal matching sample as the independent variable and the reflectance factor correction value corresponding to the first reflectance factor value in the optimal matching sample as the dependent variable, the coefficients of the preset linear relationship are determined.

[0039] The following description uses an S-band ground-based radar as an example, with the S-band as the first band, to further illustrate the embodiments of this application.

[0040] The system employs a Global Precipitation Satellite (GPM) dual-frequency precipitation radar (DPR), with a temporal resolution of approximately 90 minutes, a nadir distance of 5 km, a vertical resolution of 125 m, a detection altitude of 22 km, and a minimum Ku-band detection signal of 18 dBZ. Parameters such as radar reflectivity factor and bright band height, corrected for attenuation, are used from the 2AKu product of the GPM DPR. The GPM dual-frequency precipitation radar (DPR) is used as the spaceborne radar, with the Ku-band as the second band.

[0041] Table 1 shows a comparison of the main parameters of ground-based radar and spaceborne radar. The reflectivity factor of the S-band ground-based radar is corrected using spaceborne radar. Specifically, matching samples of ground-based and spaceborne radar are obtained. These samples are preprocessed and quality-screened to generate the optimal matching sample. Monthly linear fitting of the spaceborne and ground-based radar data is performed using the optimal matching sample. Based on the linear fitting relationship, the reflectivity factor of the ground-based radar is corrected using the spaceborne radar, thereby generating improved ground-based radar baseline data.

[0042] Table 1 Comparison of key parameters between ground-based radar and spaceborne radar

[0043]

[0044] The following describes the specific process of correcting the reflectivity factor of S-band ground-based radar using spaceborne radar.

[0045] First, matching samples between ground-based and spaceborne radars are obtained through operations such as spatiotemporal matching, frequency correction, and numerical matching. The specific steps are as follows:

[0046] Spatiotemporal matching includes temporal matching and spatial matching. Based on the GPM DPR transit time, the volumetric scan data of nearby ground-based radars within ±5 minutes of the transit time are used as matching targets. Temporal matching is performed on the ground-based radars to obtain volumetric scan data of both ground-based and spaceborne radars that meet the time requirements. Spatial matching uses a volumetric matching method, with the effective illumination volume as the basic unit, to determine the overlapping area between the spaceborne and ground-based radars. Based on the volumetric scan data of both ground-based and spaceborne radars that meet the time requirements, the average reflectivity factor values ​​of the spaceborne and ground-based radars at the geometric intersection of the spaceborne radar scanning beam and the ground-based radar elevation angle scan are calculated to obtain the spatiotemporally matched dataset. The horizontal resolution of each matching point is approximately 5 km, which is the horizontal resolution of the DPR nadir point, and the vertical resolution is the beam thickness (vertical coverage range) of the matching point.

[0047] According to an embodiment of this application, based on the correspondence between the reflectivity factor value of the second band and the reflectivity factor value of the first band of the ground-based radar, the reflectivity factor correction value corresponding to the second reflectivity factor value at each location in the precipitation area is obtained. This includes: establishing a lookup table, which represents the correspondence between the reflectivity factor value of each second band and the reflectivity factor value of the first band of the ground-based radar; the reflectivity factor correction value is the reflectivity factor value of the first band of the ground-based radar corresponding to the second reflectivity factor value in the lookup table. It also includes: determining the average reflectivity value for each location based on the reflectivity factor correction values ​​corresponding to multiple range databases included at each location, and using the average reflectivity value as the reflectivity factor correction value for each location.

[0048] Assuming the raindrop spectrum follows an MP distribution and the raindrops are spherical, Mie scattering theory is applied. Different spectral parameters, temperatures, and rainfall intensities are set, with rainfall intensity increments of 0.1 mm / h. Based on the frequency correction formula, lookup tables for reflectivity factors of spaceborne radar (Ku-band) and ground-based radar (S-band) are generated. Specifically, for each set rainfall intensity (increasing by 0.1 mm / h from low to high), the radar reflectivity factors for the Ku-band and S-band are calculated respectively, taking into account the corresponding spectral parameters and temperature.

[0049] After the observation areas of the spaceborne radar and the ground-based radar are spatiotemporally matched, the reflectivity factor value measured by the spaceborne radar in the Ku band is determined, and the entry for the Ku-band reflectivity value closest to this value is found in the lookup table. The corresponding S-band reflectivity factor in the entry for the Ku-band reflectivity value closest to this value is directly applied to replace or correct the original Ku-band reflectivity factor, thus completing the frequency correction.

[0050] The average value of all matching points is equal to the sum of the echo values ​​of bins with echoes at the matching point divided by the total number of bins at the matching point. Here, a matching point can be a location in the same space region observed by both spaceborne and ground-based radars; a bin is the smallest observation unit of the radar, and each bin corresponds to a reflectivity factor. A bin with an echo can be understood as meaning that precipitation was indeed observed at that bin's location; that is, the echo value is not invalid.

[0051] Following the above method, based on the corrected reflectivity factor of the Ku band, the final average value of the matching space is obtained, thereby obtaining the corrected value of the reflectivity factor of the spaceborne radar and the reflectivity factor of the ground-based radar corresponding to the matching point, and then obtaining a matching sample composed of the corrected values ​​of the reflectivity factors of the spaceborne radar and the reflectivity factor of the ground-based radar corresponding to multiple matching points.

[0052] In the embodiments of this application, data from the same precipitation area observed by spaceborne radar and ground-based radar are matched and correlated. This matching reduces the difference in reflectivity factors between the spaceborne Ku-band radar and the ground-based S-band radar when measuring the same precipitation area, allowing the data to be aligned, compared, or fused. However, despite the matching operation, differences may still exist in the data observed by the spaceborne and ground-based radars for the same precipitation area due to various influencing factors.

[0053] According to an embodiment of this application, the matching samples composed of the reflectivity factor correction value and the first reflectivity factor value at each location are preprocessed and quality screened to obtain the optimal matching sample, including: removing matching samples whose corresponding heights at each location are lower than a preset height from the matching samples to obtain an initial matching sample; determining matching samples from the initial matching samples whose reflectivity factor correction value and the first reflectivity factor value are both greater than a preset reflectivity factor threshold to obtain a preprocessed matching sample; and performing quality screening on the preprocessed matching sample to obtain the optimal matching sample.

[0054] The process of quality screening of preprocessed matching samples to obtain optimal matching samples includes: removing matching samples with terrain occlusion from the preprocessed matching samples to obtain the first matching sample; identifying matching samples in the first matching sample whose radial distance meets a preset distance condition to obtain the second matching sample; wherein, the radial distance is used to characterize the straight-line distance between each ground-based radar and the precipitation area; identifying matching samples in the second matching sample whose beam filling coefficient meets a preset filling coefficient condition to obtain the third matching sample; and identifying matching samples in the third matching sample for the stratiform precipitation area below the bright band to obtain the optimal matching sample.

[0055] Therefore, by preprocessing and quality screening the matching samples of spaceborne radar and ground-based radar, the optimal dataset of reflectivity factors for spaceborne radar and ground-based radar is established, so as to reduce the uncertainty caused by the above-mentioned interferences when using spaceborne radar to correct ground-based radar.

[0056] Figure 2 A flowchart illustrating a preprocessing and quality screening method according to an embodiment of this application is shown schematically.

[0057] like Figure 2 As shown, the pretreatment and quality screening method includes steps 1 to 5.

[0058] Step 0: Matching ground-based radar and GPM DPR to generate matching samples. Step 0 can be understood as obtaining matching samples through the aforementioned process.

[0059] Step 1: Preprocessing of matching sample data.

[0060] In the embodiments of this disclosure, matching samples with superior overall quality of DPR data products can be selected based on actual circumstances. Various preprocessing operations can also be applied to determine matching samples with superior overall quality of DPR data products.

[0061] When using multiple preprocessing operations to determine the best matching samples for DPR data products, the multiple preprocessing operations may include: (1) removing matching samples with clutter interference at the bottom of the DPR product. Specifically, based on the number of clutter interference samples at the bottom indicated in the DPR product, i.e., the maximum height, matching point sample data below that height are removed; (2) using 15dBZ as the threshold, retaining the reflectivity factors of spaceborne radar and ground-based radar that are greater than the threshold.

[0062] Step 2: Remove data from the matching samples that are obscured by terrain.

[0063] Step 3: Select matching samples with a radial distance of [25, 150) km.

[0064] Step 4: Select a 100% filled matching sample.

[0065] Step 5: Select matching samples of cloud precipitation below the bright band.

[0066] After going through steps 0 to 5 above, the optimal matching sample is obtained.

[0067] In the embodiments of this application, the quality screening criteria are determined through sensitivity comparison experiments, discussing the impact of terrain obstruction, matching distance, beam filling, precipitation type, and phase on the matching samples of space-to-ground radar. The correlation coefficient and standard deviation are used as evaluation indicators. The standard deviation represents the dispersion of the reflectivity factor deviation between ground-based and spaceborne radars. A higher correlation coefficient and a lower standard deviation indicate a higher correlation between the reflectivity factors of spaceborne and ground-based radars, more stable data quality from the ground-based radar, and thus a smaller error in correcting the reflectivity factor of the ground-based radar using spaceborne radar.

[0068] Therefore, steps 2 through 5 all operate based on the correlation coefficient and standard deviation between matched samples at the same location. Taking step 2 as an example, depending on the actual situation, thresholds for the correlation coefficient and standard deviation between matched samples at the same location are set for cases where terrain occlusion exists, and matched samples that do not meet these thresholds are removed. Steps 3 through 5 are similar to step 2 and will not be described in detail here.

[0069] After obtaining the optimal matching samples, the reflectivity factor of the ground-based radar is corrected monthly on a site-by-site basis, using GPM DPR as the reference standard. Specifically, the optimal matching samples are used as the best dataset. Based on the best dataset, the monthly linear fitting coefficients of GPM DPR and the reflectivity factor values ​​of the ground-based radar at each site are calculated, and then... The relationship is used to perform linear correction on ground-based radar. In the process of determining the linear fitting coefficients of the linear correction relationship based on the optimal dataset, the following steps are taken: The ground-based radar reflectivity factor value before correction is given by For the reflectivity factor value of spaceborne radar, after determining the linear fitting coefficients of the linear correction formula, when applying the linear correction formula to correct the reflectivity factor value of ground-based radar, , These are the ground-based radar reflectivity factor values ​​before and after the correction.

[0070] According to an embodiment of this application, the test result of reflectivity consistency improvement of a ground-based radar network composed of various ground-based radars is determined based on a first consistency result determined by each reflectivity factor improvement value and a second consistency result determined by each first reflectivity factor value. This includes: determining overlapping echo samples of the ground-based radar network based on the reflectivity factor improvement values ​​and the first reflectivity factor values ​​of each ground-based radar; performing reflectivity consistency improvement tests on radar combinations composed of multiple ground-based radars in the ground-based radar network based on the overlapping echo samples to obtain multiple initial test results; wherein, the radar combination is composed of multiple ground-based radars whose radar detection ranges overlap; and determining the test result of reflectivity consistency of the ground-based radar network based on each initial test result.

[0071] After correcting the reflectivity factor values ​​of local radars, a consistency assessment of the reflectivity factors among local radars was conducted.

[0072] According to an embodiment of this application, determining the overlapping echo samples of a ground-based radar network based on each reflectivity factor improvement value and each first reflectivity factor value includes: sorting all ground-based radars in the ground-based radar network to obtain a ground-based radar sequence; wherein the scanning areas of two adjacent ground-based radars in the ground-based radar sequence have overlapping areas; and determining the overlapping echo samples of the ground-based radar network based on the reflectivity factor improvement value and the first reflectivity factor value corresponding to the same precipitation intensity under a preset precipitation event for each of the two adjacent ground-based radars in the ground-based radar sequence.

[0073] In the embodiments of this application, when evaluating the consistency of reflectivity factors between ground-based radars, the selected data source is standard format radar volume scan data. The main steps are as follows: First, calculate the distance between the center points of two ground-based radars. If the distance is less than the sum of the effective detection ranges of the two ground-based radars, it is considered that the two ground-based radars have an overlapping area, and the two ground-based radars can perform matching operations. Based on this, determine the sequence of all networked ground-based radars that can be matched and combined in pairs. Second, calculate the fixed overlap table of spatial consistency of the combination composed of two ground-based radars in all combinations of each pair of matching. Specifically, using elevation data, calculate the occlusion information of each radar at different elevation angles in the combination, thereby establishing a fixed overlap table that removes the occlusion effect. Among them, the elevation data can be selected as SRTM (Shuttle Radar) data. The first step involves the Topography Mission (i.e., the Space Shuttle Radar Topography Mission) elevation data; the second step involves selecting pairs of radar base data with consistent observation time and filtering for overlapping points that meet radial temporal consistency; the third step involves the quality screening of overlapping points: eliminating overlapping points that cannot represent radar observation performance, such as those with noise, insufficient filling, non-liquid precipitation, non-stratus precipitation, strong attenuation, and outliers; the fifth step involves outputting the overlapping echo samples of the entire network of ground-based radars that have undergone the first to fourth steps, matched pairwise.

[0074] Figure 3 The illustration shows a schematic diagram of the principle of a data matching method for spatial consistency between ground-based radars according to an embodiment of this application.

[0075] like Figure 3 As shown, in establishing a fixed overlap table for spatial consistency between two radars, based on the spatial consistency of the same meteorological target point between the two radars, the target area overlapping relative to the two radars is called the overlap point. This overlap point information is obtained through precise calculation of geographic coordinates and radar coordinates. The polar coordinates of the target illuminated by the first radar are converted to latitude and longitude projected coordinates. A target with consistent projection is then found in the polar coordinates of the target observed by the second radar. A height threshold is set to achieve spatial matching of the data from the two radars. Standard atmospheric refraction is used in the projection coordinate transformation process, and the influence of the Earth's oblateness is considered. When calculating spatial overlap points, the azimuth calculation interval is 0.5°. Overlap tables for different elevation angles are established, and the overlap points are directly read from the overlap table during calculation, without repeated calculation.

[0076] During time consistency matching, a preliminary screening for volume scan start time consistency is performed based on the radar base data file name time. Since the radar base data stores the observation time for each radial direction, the radial time is directly read. When the time difference between two radial directions is less than the set time difference threshold T, the time consistency match is considered successful. The time difference threshold T is dynamically and automatically adjusted based on the average echo intensity.

[0077] When screening overlapping points, a signal-to-noise ratio (SNR) method was used to address noise impact. For insufficient filling, the standard deviation of radar echo reflectance from surrounding points was used to represent the degree of incomplete reflectance filling, and this was used for screening. For precipitation cloud type, a convective cloud / stratified cloud differentiation algorithm was used to screen for stratiform cloud precipitation. For strong attenuation, an adaptive constrained attenuation correction method was used to calculate the attenuation of each reservoir and eliminate strong attenuation effects. After the above overlapping point sample screening, outliers were further removed using the 3-sigma outlier screening method.

[0078] After obtaining the pairwise matched overlapping echo samples of the entire ground-based radar network, the effect of the consistency improvement of the reflectivity factor of the ground-based radar network is tested, including case tests and statistical tests.

[0079] According to an embodiment of this application, a reflectivity consistency test is performed on a radar combination consisting of multiple ground-based radars in a ground-based radar network based on overlapping echo samples to obtain multiple initial test results, including: determining a first consistency result and a second consistency result of two adjacent ground-based radars based on overlapping echo samples; using the difference between the first consistency result and the second consistency result of two adjacent ground-based radars as the initial test result of the two adjacent ground-based radars to obtain multiple initial test results.

[0080] In the embodiments of this application, based on the overlapping echo samples, a reflectivity consistency test is performed on a radar combination consisting of multiple ground-based radars in the ground-based radar network to obtain multiple initial test results. It may also include: performing a network mosaic on the overlapping echo samples of two adjacent ground-based radars at the same elevation angle to obtain a first qualitative test result corresponding to the improved reflectivity factor values ​​of the two adjacent ground-based radars and a second qualitative test result corresponding to the first reflectivity factor values ​​of the two adjacent ground-based radars.

[0081] In the embodiments of this application, the individual case test selects two adjacent ground-based radars, and the scenario includes different precipitation intensities (light rain, moderate rain, heavy rain, rainstorm) and different precipitation types (plum rain, typhoon). The consistency between ground-based radars before and after the improvement is qualitatively and quantitatively evaluated by the jigsaw puzzle analysis method and the ground-based radar reflectivity factor consistency evaluation algorithm, thereby verifying and evaluating the effect of the ground-based radar network reflectivity factor consistency improvement.

[0082] (1) First, the mosaic analysis method involves creating a mosaic of echo intensity from the baseline data of two adjacent radars at the same elevation angle. By comparing the differences between the mosaics before and after the correction of the ground-based radar network, the effectiveness of the consistency improvement of the reflectivity factor of the ground-based radar network can be qualitatively tested and evaluated. If the differences between the mosaics of adjacent radars decrease and become more continuous, it indicates a good consistency improvement effect.

[0083] (2) Secondly, the overlapping echo samples of two adjacent radars are obtained through the ground-based radar reflectivity factor consistency evaluation algorithm. DM N This indicates two adjacent radars (denoted as GR). M and GR N The difference in reflectivity factor, i.e.: .in, and These represent two adjacent ground-based radars GR M and GR N The reflectivity factor value of the overlapping echo samples, where K represents the reflectivity factor of two adjacent ground-based radars GR. M and GR N The number of overlapping echo samples. DM N A smaller value indicates that the observations from the two radars are closer. Compare the DM values ​​before and after correction for the ground-based radar network. N This is used to quantitatively verify and evaluate the effectiveness of the improvement in the consistency of reflectivity factors in ground-based radar networks. DM N If the absolute value decreases and approaches 0, it indicates a good consistency improvement effect.

[0084] The statistical test utilizes an algorithm for assessing the consistency of reflectivity factors among ground-based radars to obtain overlapping echo samples from each pair of adjacent radars in the entire network. Each pair of adjacent radars is treated as a group, and the correlation coefficient, standard deviation, and mean deviation of the overlapping echo samples for each group are calculated. Comparing the correlation coefficient, standard deviation, and mean deviation before and after the correction of the ground-based radar network indicates a good improvement in consistency among the ground-based radars in the entire network. An increase in the correlation coefficient, a decrease in the standard deviation, and a mean deviation approaching zero indicate a good improvement in consistency among the ground-based radars in the entire network.

[0085] This application establishes an algorithm for improving the consistency of reflectivity factors in ground-based radar networks based on spaceborne radar. The algorithm is then used to evaluate the effectiveness of the improved reflectivity factor consistency in ground-based radar networks through a mosaic analysis method and the established consistency evaluation algorithm between ground-based radars. This provides a foundation for the further formation of uniform and stable ground-based radar network products and is of great significance for improving the quality of precipitation data products from ground-based radar networks and their quantitative applications.

[0086] Figure 4 A block diagram of a ground-based radar network reflectivity consistency improvement and verification apparatus according to an embodiment of this application is shown schematically.

[0087] like Figure 4 As shown, the ground-based radar network reflectivity consistency improvement and verification device 400 includes an improvement value determination module 410 and a verification effect determination module 420.

[0088] The improved value determination module 410 is used to obtain the improved reflectivity factor value of each ground-based radar by using the first reflectivity factor value of the first band measured by each location of the target precipitation area observed by each ground-based radar in the ground-based radar network within a preset time as the independent variable and applying a linear correction relationship. The linear correction relationship is used to characterize the relationship between the reflectivity factor value of the first band obtained by the ground-based radar observing each location of the target precipitation area and the reflectivity factor value of the first band obtained by the spaceborne radar observing the same location at the same time. The reflectivity factor value of the first band of the spaceborne radar is obtained by correcting the second reflectivity factor value of the second band of the spaceborne radar.

[0089] The test result determination module 420 is used to determine the test result of the reflectivity consistency improvement of the ground-based radar network composed of various ground-based radars based on the first consistency result determined by each reflectivity factor improvement value and the second consistency result determined by each first reflectivity factor value.

[0090] Any one or more of the modules, submodules, units, and subunits according to the embodiments of this application, or at least part of the functions of any one or more of them, can be implemented in one module. Any one or more of the modules, submodules, units, and subunits according to the embodiments of this application can be implemented by dividing them into multiple modules. Any one or more of the modules, submodules, units, and subunits according to the embodiments of this application can be at least partially implemented as hardware circuits, such as field-programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems-on-a-chip, systems-on-a-substrate, systems-on-package, application-specific integrated circuits (ASICs), or implemented by hardware or firmware in any other reasonable manner by integrating or packaging circuits, or implemented in any one of software, hardware, and firmware, or in a suitable combination of any of these. Alternatively, one or more of the modules, submodules, units, and subunits according to the embodiments of this application can be at least partially implemented as computer program modules, which, when run, can perform corresponding functions.

[0091] For example, any plurality of the improved value determination module 410 and the inspection effect determination module 420 can be combined into one module / unit / subunit, or any one of the modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least part of the functionality of one or more of these modules / units / subunits can be combined with at least part of the functionality of other modules / units / subunits and implemented in one module / unit / subunit. According to embodiments of this application, at least one of the improved value determination module 410 and the inspection effect determination module 420 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any one of the three implementation methods or a suitable combination of any of them. Alternatively, at least one of the improved value determination module 410 and the test result determination module 420 can be at least partially implemented as a computer program module that can perform corresponding functions when the computer program module is run.

[0092] It should be noted that the data processing device part in the embodiments of this application corresponds to the data processing method part in the embodiments of this application. The specific description of the data processing device part is referred to in the data processing method part, and will not be repeated here.

[0093] Figure 5 A block diagram of an electronic device suitable for implementing a method for improving and verifying the reflectivity consistency of a ground-based radar network, according to an embodiment of this application, is shown schematically. Figure 5 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0094] like Figure 5 As shown, an electronic device 500 according to an embodiment of this application includes a processor 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage portion 508 into a random access memory (RAM) 503. The processor 501 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 501 may also include onboard memory for caching purposes. The processor 501 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of this application.

[0095] RAM 503 stores various programs and data required for the operation of electronic device 500. Processor 501, ROM 502, and RAM 503 are interconnected via bus 504. Processor 501 executes various operations of the method flow according to embodiments of this application by executing programs in ROM 502 and / or RAM 503. It should be noted that programs may also be stored in one or more memories other than ROM 502 and RAM 503. Processor 501 may also execute various operations of the method flow according to embodiments of this application by executing programs stored in one or more memories.

[0096] According to embodiments of this application, the electronic device 500 may further include an input / output (I / O) interface 505, which is also connected to a bus 504. The electronic device 500 may also include one or more of the following components connected to the input / output (I / O) interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the input / output (I / O) interface 505 as needed. A removable medium 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 510 as needed so that computer programs read from it can be installed into the storage section 508 as needed.

[0097] According to embodiments of this application, the method flow according to embodiments of this application can be implemented as a computer software program. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the methods shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by processor 501, it performs the functions defined in the system of embodiments of this application. According to embodiments of this application, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0098] This application also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiments of this application.

[0099] According to embodiments of this application, the computer-readable storage medium can be a non-volatile computer-readable storage medium. Examples include, but are not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this application, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0100] For example, according to embodiments of this application, a computer-readable storage medium may include the ROM 502 and / or RAM 503 described above and / or one or more memories other than ROM 502 and RAM 503.

[0101] Embodiments of this application also include a computer program product comprising a computer program containing program code for performing the methods provided in the embodiments of this application. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the ground-based radar network reflectivity consistency improvement and verification method provided in the embodiments of this application.

[0102] When the computer program is executed by the processor 501, it performs the functions defined in the system / apparatus of this application embodiment. According to the embodiments of this application, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0103] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 509, and / or installed from a removable medium 511. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0104] According to embodiments of this application, program code for executing the computer programs provided in the embodiments of this application can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0105] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions. Those skilled in the art will understand that the features described in the various embodiments of this application can be combined and / or combined in various ways, even if such combinations are not explicitly described in this application. In particular, without departing from the spirit and teachings of this application, the features described in the various embodiments of this application can be combined and / or combined in various ways. All such combinations and / or combinations fall within the scope of this application.

[0106] The embodiments of this application have been described above. However, these embodiments are merely illustrative and not intended to limit the scope of this application. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Without departing from the scope of this application, those skilled in the art can make various substitutions and modifications, all of which should fall within the scope of this application.

Claims

1. A method for improving and verifying the reflectivity consistency of a ground-based radar network, characterized in that, The method includes: Using the first reflectivity factor of the first band measured by each ground-based radar in the ground-based radar network at each location of the target precipitation area within a preset time as the independent variable, a linear correction relation is applied to obtain the improved reflectivity factor value of each ground-based radar; wherein, the linear correction relation is used to characterize the relationship between the reflectivity factor value of the first band obtained by the ground-based radar at each location of the target precipitation area and the reflectivity factor value of the first band obtained by the spaceborne radar at the same location at the same time; the reflectivity factor value of the first band of the spaceborne radar is obtained by correcting the second reflectivity factor value of the second band of the spaceborne radar. The test results of reflectivity consistency improvement of the ground-based radar network composed of various ground-based radars are determined based on the first consistency result determined by each of the improved reflectivity factor values ​​and the second consistency result determined by each of the first reflectivity factor values.

2. The method for improving and verifying the reflectivity consistency of ground-based radar networks according to claim 1, characterized in that, The process of determining the linear correction relation includes: Based on the correspondence between the reflectivity factor value of the second band and the reflectivity factor value of the first band of the ground-based radar, the reflectivity factor correction value corresponding to the second reflectivity factor value at each location in the precipitation area is obtained; wherein, the precipitation area is the overlapping area observed by the spaceborne radar and the ground-based radar during the transit time of the spaceborne radar. Based on the reflectivity factor correction value at each of the aforementioned locations and the first reflectivity factor value, the coefficients of the preset linear relationship are determined; The linear correction relation is determined based on the coefficients of the preset linear relation.

3. The method for improving and verifying the reflectivity consistency of ground-based radar networks according to claim 2, characterized in that, Based on the reflectivity factor correction value at each of the aforementioned locations and the first reflectivity factor value, the coefficients of a preset linear relationship are determined, including: The matching samples, consisting of the reflectance factor correction values ​​at each of the aforementioned locations and the first reflectance factor value, are preprocessed and quality-screened to obtain the optimal matching samples. The coefficients of the preset linear relationship are determined by taking the first reflectance factor value in the optimal matching sample as the independent variable and the reflectance factor correction value corresponding to the first reflectance factor value in the optimal matching sample as the dependent variable.

4. The method for improving and verifying the reflectivity consistency of ground-based radar networks according to claim 2, characterized in that, Based on the correspondence between the reflectivity factor value of the second band and the reflectivity factor value of the first band of the ground-based radar, the reflectivity factor correction values ​​corresponding to the second reflectivity factor values ​​at each location in the precipitation area are obtained, including: Establish a lookup table that represents the correspondence between the reflectivity factor value of each second band and the reflectivity factor value of the first band of the ground-based radar; The reflectivity factor correction value is determined based on the reflectivity factor value of the first band of the ground-based radar corresponding to the second reflectivity factor value in the lookup table.

5. The method for improving and verifying the reflectivity consistency of ground-based radar networks according to claim 3, characterized in that, Preprocessing and quality screening are performed on the matching samples composed of the reflectance factor correction values ​​at each of the aforementioned locations and the first reflectance factor value to obtain the optimal matching samples, including: The initial matching samples are obtained by removing the matching samples whose heights at each of the specified positions are lower than the preset heights. From the initial matching samples, matching samples in which both the reflectance factor correction value and the first reflectance factor value are greater than a preset reflectance factor threshold are determined to obtain preprocessed matching samples; The preprocessed matching samples are subjected to quality screening to obtain the optimal matching samples.

6. The method for improving and verifying the reflectivity consistency of ground-based radar networks according to claim 5, characterized in that, The preprocessed matching samples are subjected to quality screening to obtain the optimal matching samples, including: Remove the preprocessed matching samples that contain terrain occlusion to obtain the first matching sample; A second matching sample is obtained by identifying matching samples in the first matching sample whose radial distances satisfy a preset distance condition; wherein, the radial distance is used to characterize the straight-line distance between each of the ground-based radars and the precipitation area; The third matching sample is obtained by determining the matching sample in the second matching sample whose beam filling coefficient satisfies the preset filling coefficient condition; The optimal matching sample is obtained by identifying the matching sample for the cloud precipitation region below the bright band in the third matching sample.

7. The method for improving and verifying the reflectivity consistency of ground-based radar networks according to claim 1, characterized in that, Based on the first consistency result determined by each of the improved reflectivity factor values ​​and the second consistency result determined by each of the first reflectivity factor values, the verification result of the reflectivity consistency improvement of the ground-based radar network composed of various ground-based radars is determined, including: The overlapping echo samples of the ground-based radar network are determined based on the improved values ​​of each reflectivity factor and the values ​​of each first reflectivity factor. Based on the overlapping echo samples, a reflectivity consistency improvement test is performed on the radar combination consisting of multiple ground-based radars in the ground-based radar network to obtain multiple initial test results. These multiple initial test results are then used as the test results for reflectivity consistency improvement of the ground-based radar network consisting of various ground-based radars. The radar combination consists of multiple ground-based radars whose radar detection ranges overlap.

8. The method for improving and verifying the reflectivity consistency of a ground-based radar network according to claim 7, characterized in that, Based on the improved reflectivity factor values ​​and the first reflectivity factor values, the overlapping echo samples of the ground-based radar network are determined, including: All ground-based radars in the ground-based radar network are sorted to obtain a ground-based radar sequence; wherein, the scanning areas of two adjacent ground-based radars in the ground-based radar sequence have overlapping areas; The overlapping echo samples of the ground-based radar network are determined based on the improved reflectivity factor value and the first reflectivity factor value of each of two adjacent ground-based radars under the same precipitation intensity in a preset precipitation event.

9. The method for improving and verifying the reflectivity consistency of a ground-based radar network according to claim 8, characterized in that, Based on the overlapping echo samples, a reflectivity consistency test is performed on the radar combination consisting of multiple ground-based radars in the ground-based radar network, yielding multiple initial test results, including: Based on the overlapping echo samples, the first consistency result and the second consistency result of two adjacent ground-based radars are determined; The difference between the first consistency result and the second consistency result of two adjacent ground-based radars is used as the initial test result of the two adjacent ground-based radars, and multiple initial test results are obtained.

10. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs. Wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the method of any one of claims 1 to 9.

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