Joint calibration method and system for reflectivity factors of spaceborne and multi-band ground-based radars

Abstract

The present invention relates to the field of meteorological analysis technology, and more specifically, to a method and system for jointly verifying the reflectivity factors of spaceborne and multi-band ground-based radars. The method includes setting data sources for spaceborne radars and ground-based weather radars; performing data quality control based on the data sources of the spaceborne radars and ground-based weather radars to form a revised data source; matching and comparing the reflectivity factors of the spaceborne radars and ground-based weather radars based on the revised data source to form optimal paired data; establishing a fused networked radar consistency assessment algorithm to determine an alarm list and form a problem level; performing a standard comparison of the ground-based radar reflectivity factor to form a matching result between a standard database and a new spaceborne radar FY3-G / PMR; and setting an assessment classification to form and store assessment results under different classifications of the matching results of the standard database and the new spaceborne radar FY3-G / PMR.

Description

Technical Field

[0001] The present invention relates to the field of meteorological analysis technology, and more specifically, to a method and system for jointly verifying reflectivity factors of spaceborne and multi-band ground-based radars. Background Art

[0002] On April 16, 2023, China's first dedicated precipitation measurement meteorological satellite, Fengyun-3G (FY-3G), was successfully launched from the Jiuquan Satellite Launch Center. The Precipitation Measurement Radar (PMR) is the primary payload on the satellite, comprising two Ku- and Ka-band radars that can obtain three-dimensional structural information within the precipitation system. FY3-G / PMR's secondary products include bright band detection, precipitation classification, three-dimensional droplet profiles, three-dimensional precipitation rate profiles, and three-dimensional equivalent radar reflectivity factor profiles. There is an urgent need to verify the authenticity of FY3-G / PMR secondary products. This is to assess and verify the accuracy and applicability of these secondary products and provide a reference for improving and optimizing the FY3-G / PMR secondary product algorithms. The radar reflectivity factor is a key parameter of the FY3-G / PMR secondary products.

[0003] Prior to the present invention, the reflectivity factor verification method for the dual-frequency precipitation radar (DPR) carried by the Global Precipitation Measurement Mission (GPM) and the precipitation radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) was mostly based on direct use of S-band ground-based weather radar to conduct satellite-ground radar consistency analysis research. However, in reality, China's ground-based weather radars mainly include S-band, C-band, and X-band. The three bands of ground-based radars are used for coordinated observation and each has its own advantages. S-band ground-based radar has the smallest attenuation, the widest detection range, the highest data quality, but the lowest resolution. X-band ground-based radar has the strongest attenuation, the smallest detection range, slightly lower data quality, but the highest resolution. Compared with S-band ground-based radar, it can observe detailed information on precipitation in a small area in more detail. C-band ground-based radar attenuation, detection range, and resolution are all between S-band and X-band ground-based radars. Currently, ground-based weather radars in central and coastal China primarily use the S-band, while those in the northeast, northwest, and southwest regions primarily use the C-band. X-band ground-based radars are dispersed across provinces. To verify and evaluate the authenticity of the Mercury reflectivity factor in China, ground-based radars in all three bands must be deployed to cover the entire country, each with its own advantages. Furthermore, these ground-based radars are widely distributed, with varying technical support and maintenance conditions. Limited calibration methods can lead to inconsistent observations in the overlapping areas of radars at each site, resulting in uneven data quality at each site, which can introduce errors into the authenticity verification of the Mercury reflectivity factor. Therefore, a joint calibration of the reflectivity factor using spaceborne and multi-band ground-based radars is urgently needed. Summary of the Invention

[0004] In view of the above problems, the present invention proposes a joint verification method and system for the reflectivity factors of spaceborne and multi-band ground-based radars, matches and compares the reflectivity factors of multi-band ground-based weather radars (S, C, and X bands) and spaceborne radar GPM / DPR, establishes algorithms for ground-to-ground radar reflectivity factor matching and satellite-to-ground radar reflectivity factor matching, thereby establishing a fused networked radar consistency assessment algorithm, verifies the ground-based weather radar reflectivity factor data, and generates a ground-based weather radar standard database and problem list; based on the ground-based weather radar standard database, the satellite-to-ground radar reflectivity factor matching algorithm is used to carry out the authenticity verification of the reflectivity factor of the new spaceborne radar FY3-G / PMR, forming a set of joint verification methods and systems for the reflectivity factors of spaceborne and multi-band ground-based radars.

[0005] According to a first aspect of an embodiment of the present invention, a method for jointly verifying reflectivity factors of spaceborne and multi-band ground-based radars is provided.

[0006] In one or more embodiments, preferably, the method for jointly verifying the reflectivity factors of spaceborne and multi-band ground-based radars includes:

[0007] Set up data sources for spaceborne radar and ground-based weather radar;

[0008] Performing data quality control based on the data sources of the spaceborne radar and the ground-based weather radar to form a revised data source;

[0009] Match and compare the reflectivity factors of spaceborne radar GPM / DPR and ground-based weather radar based on the corrected data source to form the optimal paired data;

[0010] Establish a fusion network radar consistency assessment algorithm to determine the alarm list and form a problem level;

[0011] Conduct standard comparisons of ground-based radar reflectivity factors to generate matching results between the standard database and the new spaceborne radar FY3-G / PMR;

[0012] Set the evaluation categories, form the matching results of the standard database and the new spaceborne radar FY3-G / PMR in different categories and store them.

[0013] In one or more embodiments, preferably, setting the data sources of the spaceborne radar and the ground-based weather radar specifically includes:

[0014] The data source of the spaceborne radar GPM / DPR is set to use the Global Precipitation Satellite (GPM) Dual-Frequency Rainfall Radar (DPR);

[0015] The data source of the spaceborne radar FY3-G / PMR is set to use the Fengyun-3G precipitation measurement radar;

[0016] The data source for setting up the ground-based weather radar adopts the basic data of a single ground-based weather radar (S, C, X band) that has undergone quality control.

[0017] In one or more embodiments, preferably, performing data quality control based on the data sources of the spaceborne radar and the ground-based weather radar to form a corrected data source specifically includes:

[0018] For spaceborne radar GPM / DPR data, reduce the data source if the quality does not meet the preset level;

[0019] The S-band and C-band data of Doppler weather radar are quality controlled by noise point filtering, fault image recognition, electromagnetic interference echo recognition, ground object / super-refraction echo recognition, wave echo recognition and velocity deblurring. The X-band data of ground-based radar are quality controlled by using Z H -K DP The comprehensive correction method is used to correct the echo intensity attenuation and complete the correction of the ground-based weather radar.

[0020] In one or more embodiments, preferably, matching and comparing the reflectivity factors of the spaceborne radar GPM / DPR and the ground-based weather radar based on the corrected data source to form optimal paired data specifically includes:

[0021] The reflectivity factors of spaceborne radar and ground-based radar are obtained through time matching, space matching and digital matching;

[0022] Calculating the correlation coefficient using the first calculation formula according to the reflectivity factor of the spaceborne radar and the reflectivity factor of the ground-based radar;

[0023] Calculate the average deviation using the second calculation formula;

[0024] Calculate the standard deviation using the third calculation formula;

[0025] After the original pairing of satellite-to-ground radar reflectivity factors is successful, the overlap area between the two scans is screened to see if the reflectivity is greater than 1000km. 2 The precipitation echo is considered to be a valid pairing event;

[0026] Establish screening and comparison conditions for effective matching events;

[0027] Among them, the screening and comparison conditions include: the first condition: control the quality of spaceborne radar data products, and the overall quality is excellent; the second condition: eliminate the paired data with clutter interference at the bottom of the spaceborne radar; the third condition: the average value threshold limit of the satellite-to-ground radar reflectivity factor, dBZ DPR ≥18dBZ,dBZ GR ≥15dBZ; Fourth condition: Control the quality of spaceborne radar data products, that is, the quality of precipitation type products and bright band products are both excellent; Fifth condition: The echo coverage threshold of the satellite-ground radar pairing space is equal to 100%; Sixth condition: The radial distance between the satellite-ground radar pairing space and the ground-based radar center point is controlled within 25-200km for S-band, 25-150km for C-band, and 25-100km for X-band; Seventh condition: The paired data is stratiform precipitation; Eighth condition: Select paired data with an altitude below the bright band; Ninth condition: Select paired data with no obstruction at the lowest five elevation angles (0.5°, 1.5°, 2.4°, 3.4°, and 4.3°) of the ground-based radar;

[0028] Set the relationship between the screening conditions, where the first, second and third conditions are preprocessing conditions, and the fourth, fifth, sixth, seventh, eighth and ninth conditions are screening and comparison conditions. When the fourth, fifth, sixth, seventh, eighth and ninth conditions are met at the same time, the matching point sample data is selected as the optimal pairing data;

[0029] The first calculation formula is:

[0030]

[0031] Where R is the correlation coefficient, dBZ DPR is the matching DPR reflectivity factor value, is the average value of the matched DPR reflectivity factor, N is the number of matched samples, i is the matching sample number, dBZ GR is the matching ground-based radar reflectivity factor value, is the average value of the matched ground-based radar reflectivity factor;

[0032] The second calculation formula is:

[0033]

[0034] Among them, Bias is the average deviation;

[0035] The third calculation formula is:

[0036]

[0037] Where Std_bias is the standard deviation, and x is the difference between the DPR and the ground-based radar reflectivity factor, in dB.

[0038] In one or more embodiments, preferably, the establishing of a fused networked radar consistency assessment algorithm to determine an alarm list and form a problem level specifically includes:

[0039] Combined with the actual echo difference of ground-based weather radar, the consistency evaluation standard of ground-based weather radar is formulated using the three indicators of average deviation, standard deviation and correlation of echo intensity data on the equidistant line in the overlapping area of ​​adjacent radars. The evaluation criteria include: 1) when av≤3, std≤5, and R2≥0.5 are met at the same time, it is considered credible; 2) when any one of 3<av≤5, 5<std≤8, and 0.3≤R2<0.5 is met, it is considered suspicious; 3) when any one of av>5, std>8, and R2<0.3 is met, it is considered suspicious, where av is the average deviation, std is the standard deviation, and R2 is the correlation coefficient;

[0040] Obtain the correlation coefficient of the optimal pairing data of the GPM / DPR and ground-based radar reflectivity factors of a single station, and determine whether it is less than the preset value. If it is less than, it is considered to be abnormal data and added to the blacklist. Otherwise, it is considered that the station has good consistency between the satellite and the ground;

[0041] Determine whether the STD is less than the preset value. If so, the site is stable. Otherwise, it is added to the blacklist and graylist.

[0042] Determine the average deviation of the site. If the deviation is within the threshold, add it to the whitelist; otherwise, add it to the graylist.

[0043] Add blacklist, greylist and blacklist data to the alarm list;

[0044] The specific evaluation criteria are as follows: For S-band ground-based weather radars, the correlation coefficient threshold is 0.6, the standard deviation threshold is 4 dB, and the average deviation threshold is [-5.5 dB, 2.5 dB]. For C-band and X-band ground-based weather radars, the correlation coefficient threshold is 0.5, the standard deviation threshold is 5 dB, and the average deviation threshold is determined based on the probability distribution of a single band, ensuring that 70% of single-band ground-based radar sites are on the whitelist.

[0045] The alarm analysis table is set up by integrating the results of the ground-based radar network consistency verification algorithm based on space-borne radar and the results of the adjacent radar echo intensity consistency detection algorithm, combined with the maintenance and upgrade information of the ground-based weather radar.

[0046] For sites on the monthly blacklist or black / graylist, the problem level is determined based on the pre-set alarm analysis table;

[0047] For sites on the annual blacklist or black / graylist, the problem level is determined based on the pre-set alarm analysis table;

[0048] For greylisted sites, the problem level is determined based on a pre-set overall average deviation analysis table.

[0049] In one or more embodiments, preferably, the standard comparison of the ground-based radar reflectivity factor to form a matching result between the standard database and the new spaceborne radar FY3-G / PMR specifically includes:

[0050] Extracting the standard database of the ground-based radar reflectivity factor and matching it with the data of the spaceborne radar FY3-G / PMR;

[0051] Specifically, the standard database of ground-based radar reflectivity factors is a white list and a revised gray list;

[0052] Add matching of the bands corresponding to the reflectivity factors of the S band, C band, and X band, and use the matching results as the matching results of the standard database.

[0053] In one or more embodiments, preferably, the setting of evaluation categories to form and store evaluation results of the matching results of the standard database and the new spaceborne radar FY3-G / PMR under different categories specifically includes:

[0054] Multiple classifications were made by station, province, radar type, month, altitude, precipitation intensity and frequency;

[0055] The evaluation results corresponding to different sites, provinces, radar types, months, altitudes, precipitation intensity and frequency are displayed and stored according to the classification;

[0056] The overall evaluation results of all spaceborne radars and ground-based radars are displayed and stored according to the evaluation indicators.

[0057] According to a second aspect of an embodiment of the present invention, a joint calibration system for spaceborne and multi-band ground-based radar reflectivity factors is provided.

[0058] In one or more embodiments, preferably, the spaceborne and multi-band ground-based radar reflectivity factor joint calibration system includes:

[0059] The data source determination module is used to set the data source of the spaceborne radar and the ground-based weather radar;

[0060] A data quality control module is used to perform data quality control based on the data sources of the spaceborne radar and the ground-based weather radar to form a corrected data source;

[0061] The matching and comparison module is used to match and compare the reflectivity factors of the spaceborne radar GPM / DPR and the ground-based weather radar based on the corrected data source to form the optimal matching data;

[0062] The consistency fusion module is used to establish a fusion network radar consistency assessment algorithm to determine the alarm list and form a problem level;

[0063] The standard comparison module is used to perform standard comparison on the reflectivity factor of ground-based radar to form the matching result between the standard database and the new spaceborne radar FY3-G / PMR;

[0064] The authenticity assessment module is used to set the assessment categories, form a standard database and store the assessment results of the new spaceborne radar FY3-G / PMR in different categories.

[0065] According to a third aspect of an embodiment of the present invention, a computer-readable storage medium is provided, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the method according to any one of the first aspect of the embodiment of the present invention is implemented.

[0066] According to a fourth aspect of an embodiment of the present invention, an electronic device is provided, comprising a memory and a processor, wherein the memory is used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement any one of the methods described in the first aspect of the embodiment of the present invention.

[0067] The technical solutions provided by the embodiments of the present invention may have the following beneficial effects:

[0068] In the solution of the present invention, the two perspectives of satellite-ground comparison and ground-to-ground comparison are integrated to establish a fused Chinese network radar consistency assessment algorithm to classify, grade and correct ground-based weather radar data, covering the S, C and X bands, and generate a ground-based weather radar standard database and problem list.

[0069] In the solution of the present invention, by establishing a fused networked radar consistency assessment algorithm, the reflectivity factor data of multi-band ground-based weather radars are quality controlled, classified, graded, and corrected, providing a reference for the application of ground-based radar networking data and numerical model assimilation. A ground-based weather radar standard database is established to verify the data quality of FY-3G / PMR, reduce the error of ground verification sources, and provide a basis for the improvement of satellite algorithm products.

[0070] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purposes and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0071] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0073] Figure 1 The present invention is a flowchart of an embodiment of a method for jointly verifying reflectivity factors of spaceborne and multi-band ground-based radars.

[0074] Figure 2 This is a flow chart for setting data sources for spaceborne radar and ground-based weather radar in one embodiment of the present invention.

[0075] Figure 3This is a flow chart of performing data quality control based on the data sources of the spaceborne radar and the ground-based weather radar to form a corrected data source in one embodiment of the present invention.

[0076] Figure 4 This is a flow chart of matching and comparing the reflectivity factors of spaceborne radar GPM / DPR and ground-based weather radar according to the corrected data source to form optimal paired data in one embodiment of the present invention.

[0077] Figure 5 It is a flowchart of establishing a fused network radar consistency assessment algorithm to determine an alarm list and form a problem level in one embodiment of the present invention.

[0078] Figure 6 The present invention is a flowchart of performing a standard comparison on the reflectivity factor of a ground-based radar to form a matching result between a standard database and a new space-borne radar FY3-G / PMR in one embodiment of the present invention.

[0079] Figure 7 This is a flowchart of setting evaluation categories, forming a standard database, and storing evaluation results of the new spaceborne radar FY3-G / PMR under different categories in one embodiment of the present invention.

[0080] Figure 8 It is a structural diagram of a joint verification system for spaceborne and multi-band ground-based radar reflectivity factors according to an embodiment of the present invention.

[0081] Figure 9 It is the quality identification process of the two methods of star-to-ground comparison and ground-to-ground comparison. DETAILED DESCRIPTION

[0082] In an embodiment of the present invention, a method and system for jointly verifying the reflectivity factors of spaceborne and multi-band ground-based radars is provided. This solution matches and compares the reflectivity factors of multi-band ground-based weather radars (S, C, and X bands) and spaceborne radar GPM / DPR, establishes algorithms for matching ground-to-ground radar reflectivity factors and satellite-to-ground radar reflectivity factors, and thus establishes a fused networked radar consistency assessment algorithm. This verifies the reflectivity factor data of ground-based weather radars and generates a standard database and problem list for ground-based weather radars. Based on the standard database for ground-based weather radars, the satellite-to-ground radar reflectivity factor matching algorithm is used to conduct authenticity verification of the reflectivity factors of the new spaceborne radar FY3-G / PMR, forming a set of joint verification methods and systems for the reflectivity factors of spaceborne and multi-band ground-based radars.

[0083] According to a first aspect of an embodiment of the present invention, a method for jointly verifying reflectivity factors of spaceborne and multi-band ground-based radars is provided. Figure 1 As shown, the joint verification method of the reflectivity factors of spaceborne and multi-band ground-based radars includes:

[0084] S101. Set the data sources for spaceborne radar and ground-based weather radar;

[0085] S102, performing data quality control based on the data sources of the spaceborne radar and the ground-based weather radar to form a corrected data source;

[0086] S103, matching and comparing the reflectivity factors of the spaceborne radar GPM / DPR and the ground-based weather radar based on the corrected data source to form optimal paired data;

[0087] S104. Establish a fusion network radar consistency assessment algorithm to determine the alarm list and form a problem level;

[0088] S105. Conduct standard comparison of ground-based radar reflectivity factors to form matching results between the standard database and the new spaceborne radar FY3-G / PMR;

[0089] S106. Setting evaluation categories, forming and storing evaluation results of the matching results of the standard database and the new spaceborne radar FY3-G / PMR under different categories.

[0090] In this embodiment of the present invention, the existing technology does not systematically evaluate and calibrate the emissivity factor of ground-based weather radars from both ground-based and space-based observation perspectives. Research from the ground-based observation perspective alone is affected by the lack of a unified reference standard, while research from the space-based observation perspective alone is affected by small sample sizes and high randomness. By integrating both satellite-to-ground and ground-to-ground comparisons, a fused networked radar consistency assessment algorithm is established to classify, grade, and calibrate ground-based weather radar data, generating a ground-based weather radar standard database and problem list.

[0091] There is an urgent need to verify the authenticity of the reflectivity factor of the second-level product of my country's first precipitation star FY3-G / PMR. Previous studies on similar precipitation stars (GPM / DPR, TRMM / PR) have not systematically conducted verification on the S, C, and X bands. These three bands of ground-based radars have their own advantages, and multi-band ground-based radars can cover the entire country, so further research is needed.

[0092] like Figure 2 As shown, in one or more embodiments, preferably, setting the data sources of the spaceborne radar and the ground-based weather radar specifically includes:

[0093] S201. Set the GPM / DPR data source to use the Global Precipitation Satellite (GPM) Dual-Frequency Rainfall Radar (DPR);

[0094] S202, set the FY3G / PMR data source to use the Fengyun-3G precipitation measurement radar;

[0095] S203. Setting the data source of the ground-based weather radar to use the quality-controlled basic data of a single ground-based weather radar (S, C, X bands).

[0096] In the embodiment of the present invention, the data sources of spaceborne radar data and ground-based weather radar are determined, specifically including the following parts: 1) Spaceborne radar GPM / DPR data source: The Global Precipitation Satellite (GPM) dual-frequency rain measuring radar (DPR) is used, using 2Aku V07 product data, with a product file of approximately 1.5 hours. The runtime trajectory can be obtained by combining the Longitude, Latitude, and ScanTime data sets in the product file. The scanning mode used is FS, and the data set is the attenuation-corrected reflectivity factor ['FS']['SLV']['zFactorFinal']. The vertical height uses the layer of data closest to the ground (the corresponding data level is 176 layers). 2) FY3G / PMR Spaceborne Radar Data Source: This data uses the Precipitation Measurement Radar (PMR) from Fengyun-3G, China's first precipitation satellite. Ku-band precipitation rate data is provided in a 13-15-orbit product file. The runtime trajectory can be obtained by combining it with the Geo_Fields dataset in the product file. The reflectivity factor after attenuation correction is ['SLV']['zFactorCorrected'], and the vertical height is the near-surface altitude. Compared to GPM / DPR 2Aku V07, the reflectivity factor data has been enhanced with frequency correction modules ['FRE']['zFactorFrequencyCorrectionS'], ['FRE']['zFactorFrequencyCorrectionC'], and ['FRE']['zFactorFrequencyCorrectionX']. 3) Multi-band Ground-Based Weather Radar Data Source: This data uses quality-controlled baseline data from a single station of China's new generation Doppler weather radar (S- and C-bands), with one file every six minutes. Volume scanning mode VCP21 completes a volume scan at nine elevation angles every six minutes, using reflectivity factor data matching and evaluation. It uses quality-controlled baseline data products from a single Chinese X-band ground-based weather radar station, producing a new file every three to five minutes. The volume scan uses reflectivity factor data matching and evaluation. Specifically, differences between satellite-based radar and ground-based radar data include: ① Band differences: ground-based radars operate in the S-band, C-band, and X-band, while GPM / DPR and FY3-G / PMR operate in the Ku-band. ② Temporal resolution: S-band and C-band ground-based radars have a temporal resolution of six minutes, X-band ground-based radars have a temporal resolution of 3-5 minutes, GPM / DPR has a temporal resolution of approximately 1.5 hours, and FY3-G / PMR has a temporal resolution of 1.6-1.9 hours. ③ The sampling volume (effective illumination volume) differs.The radial resolution of the sampling volume for S-band ground-based radars is 250m, that for C-band ground-based radars is 150m, and that for X-band ground-based radars is 75m. The beamwidth is 0.98°, and the sampling volume increases with distance. The horizontal resolution for GPM / DPR is 5km, and the vertical resolution is 0.125km. The horizontal resolution for FY3-G / PMR is 5km, and the vertical resolution is 0.050km. (④) The effects of attenuation and ground objects are different. Ground objects have a significant impact on ground-based radars, resulting in fixed ground object echoes, super-refractive ground object echoes, and beam obstruction. While the effect of attenuation is negligible for S-band ground-based radars, it is significant for C-band and X-band ground-based radars, GPM / DPR, and FY3-G / PMR.

[0097] like Figure 3 As shown, in one or more embodiments, preferably, performing data quality control based on the data sources of the spaceborne radar and the ground-based weather radar to form a corrected data source specifically includes:

[0098] S301. For spaceborne radar GPM / DPR data, reduce the quality of data sources that do not meet the preset level;

[0099] S302, Doppler weather radar S-band data and C-band data, through noise point filtering, fault bad image identification, electromagnetic interference echo identification, ground object / super refraction echo identification, wave echo identification and velocity deblurring quality control, ground-based radar X-band data, by using Z H -K DP The comprehensive correction method is used to correct the echo intensity attenuation and complete the correction of the ground-based weather radar.

[0100] In the embodiment of the present invention, the specific data quality control process includes two steps: 1) Spaceborne radar quality control: For spaceborne radar GPM / DPR data, use ['FS']['FLG']['qualityFlag'] to control data quality, ['FS'][attr_key]['qualityBB'] to control the quality of bright band products, and ['FS'][attr_key]['qualityTypePrecip'] to control the quality of precipitation type classification products; for spaceborne radar FY3-G / PMR data, use ['SLV']['qualitySLV'] to control data quality, and ['CSF']['flagBB'] to control the quality of bright band products. 2) Multi-band ground-based weather radar quality control: For the new generation of Doppler weather radar (S-band, C-band) data, quality control is performed through noise point filtering, fault image recognition, electromagnetic interference echo recognition, ground object / super-refraction echo recognition, wave echo recognition, velocity deblurring, etc., among which the C-band ground-based radar also performs attenuation correction. For the ground-based radar X-band data, by using Z H -K DP The comprehensive correction method is used to correct echo intensity attenuation.

[0101] like Figure 4 As shown, in one or more embodiments, preferably, matching and comparing the reflectivity factors of the spaceborne radar GPM / DPR and the ground-based weather radar based on the corrected data source to form the optimal paired data specifically includes:

[0102] S401. Obtaining a reflectivity factor of a spaceborne radar and a reflectivity factor of a ground-based radar through time matching, space matching, and digital matching;

[0103] S402, calculating a correlation coefficient using a first calculation formula according to the reflectivity factor of the spaceborne radar and the reflectivity factor of the ground-based radar;

[0104] S403, calculating the average deviation using the second calculation formula;

[0105] S404, calculating the standard deviation using a third calculation formula;

[0106] After the original pairing of S405 and satellite-to-ground radar reflectivity factors is successful, the precipitation echoes with an area larger than 1000 km2 in the overlapping area of ​​the two scans are screened and considered as valid pairing events;

[0107] S406, establishing screening and comparison conditions for valid matching events;

[0108] S407, wherein the screening and comparison conditions include: first condition: control the quality of spaceborne radar data products, and the overall quality is excellent; second condition: eliminate the paired data with clutter interference at the bottom of the spaceborne radar; third condition: the average value threshold limit of the satellite-to-ground radar reflectivity factor, dBZDPR ≥ 18dBZ, dBZGR ≥ 15dBZ; fourth condition: control the quality of spaceborne radar data products, that is, the quality of precipitation type products and bright band products are both excellent; fifth condition: the space echo of the satellite-to-ground radar pairing is full of coverage The coverage thresholds are all equal to 100%; the sixth condition: the radial distance between the satellite-to-ground radar pairing space and the center point of the ground-based radar is controlled within 25-200 km for S-band, 25-150 km for C-band, and 25-100 km for X-band; the seventh condition: the paired data is stratiform precipitation; the eighth condition: paired data with an altitude below the bright band is selected; the ninth condition: paired data with no obstruction at the lowest five elevation angles of the ground-based radar (0.5°, 1.5°, 2.4°, 3.4°, and 4.3°) is selected;

[0109] S408. Setting the relationship between the screening conditions, wherein the first, second, and third conditions are pre-processing conditions, and the fourth, fifth, sixth, seventh, eighth, and ninth conditions are screening and comparison conditions. When the fourth, fifth, sixth, seventh, eighth, and ninth conditions are simultaneously met, the matching point sample data is screened as the optimal pairing data.

[0110] The first calculation formula is:

[0111]

[0112] Where R is the correlation coefficient, dBZ DPR is the matching DPR reflectivity factor value, is the average value of the matched DPR reflectivity factor, N is the number of matched samples, i is the matching sample number, dBZ GR is the matching ground-based radar reflectivity factor value, is the average value of the matched ground-based radar reflectivity factor;

[0113] The second calculation formula is:

[0114]

[0115] Among them, Bias is the average deviation;

[0116] The third calculation formula is:

[0117]

[0118] Where Std_bias is the standard deviation, and x is the difference between the DPR and the ground-based radar reflectivity factor, in dB.

[0119] In an embodiment of the present invention, the matching and comparison process specifically includes temporal, spatial, and numerical matching; and then, based on the matching results, an optimal satellite-to-ground radar reflectivity factor matching database is generated. During the temporal matching process, the start and end times of the satellite's transit over the ground-based radar coverage area are calculated: the mid-transit time = (end-transit time - start-transit time) / 2 + start-transit time. For S-, C-, and X-band ground-based radars, the ground-based radar data closest to the mid-transit time within the ±5-minute time period of the satellite's transit are selected for matching. Spatial matching uses a geometric matching method, matching the area where the satellite-borne radar and ground-based radar beams overlap, using the effective illumination volume as the unit. The average satellite-borne radar reflectivity factor value and the ground-based radar reflectivity factor value at the geometric intersection of the satellite-borne radar scanning beam and each ground-based radar elevation scan are calculated. At the matching points, the horizontal resolution of the spaceborne radar is low. The horizontal resolution of each matching point is equal to the 5 km horizontal resolution of the GPM / DPR subsatellite point. The radial library set of the ground-based radar is derived based on the horizontal beam coverage of the GPM / DPR. The vertical resolution of the ground-based radar is low. The vertical resolution of each matching point is equal to the beam thickness (vertical beam coverage) at the matching point. The radial library set of the DPR is derived based on the vertical beam coverage of the ground-based radar. During the numerical matching process, frequency correction and average calculation are performed. Specifically, the following steps are performed: 1) Frequency correction is performed by setting the parameters μ = 0, 2, 4, temperatures T = 0, 10, 15, 20°C, and rainfall amounts from 0.1 to 199.9 mm⁻¹ in increments of 0.1 mm⁻¹, within a reasonable droplet spectrum parameter range. Frequency correction equations are established to generate lookup tables for the reflectivity factor (dBZ) and Z for the Ku and S bands. After the DPR and S-band ground-based radar are matched, the lookup table is used to find the location closest to the DPR Ku-band reflectivity factor value. The DPR Ku-band reflectivity factor is then frequency-corrected to the S-band reflectivity factor corresponding to that location. For C-band and X-band ground-based radars, the calculation of the radar reflectivity factor Z using Rayleigh scattering is discarded, and the equivalent reflectivity factor Ze is calculated using Mie scattering. 2) Average calculation: After obtaining the matching library set, invalid values ​​in the DPR and ground-based radar data are removed to obtain valid values ​​for subsequent average calculation. Specific invalid values ​​include: -32768, -1280, -999, -999.9, and -33 for S- and C-band ground-based radars; and -994, -995, -996, -997, and -998 for X-band ground-based radars. The specific average calculation formula is: Average = Sum of all valid values ​​ / Number of matching libraries.In the horizontal direction, for the radial range bins matched to the ground-based radar, the reflectivity factor values ​​at each bin are converted from dBZ to Z (dBZ = 10log(Z)), the average is calculated, and the average is converted back to dBZ, which is used as the reflectivity factor of the ground-based radar at that location (average value in the matching space). In the vertical direction, for the radial (vertical) range bins within the DPR region, the reflectivity factor values ​​at each bin are converted from dBZ to Z (dBZ = 10log(Z)), the average is calculated, and the average is converted back to dBZ, which is used as the reflectivity factor of the spaceborne radar at that location (average value in the matching space). The screening and comparison conditions include the following: First, the quality of the spaceborne radar data product is controlled, ensuring that the overall quality is excellent. The parameter ['FS']['FLG']['qualityFlag'] of the spaceborne radar GPM / DPR at the matching point is used. If this parameter is equal to 0, it indicates that the overall quality of the spaceborne radar GPM / DPR data product at that matching point is excellent. Second, paired data with clutter interference at the bottom of the spaceborne radar are eliminated. The spaceborne radar GPM / DPR parameter ['FS']['PRE']['binClutterFreeBottom'] is used. This parameter indicates the maximum height at which the base of the spaceborne radar is cluttered. If the matching point is below this height, the matching point sample data is discarded. The third condition is the threshold for the average reflectivity factor of the satellite-to-ground radar: dBZDPR ≥ 18dBZ, dBZGR ≥ 15dBZ. The fourth condition is to control the quality of the spaceborne radar data products, that is, the quality of both the precipitation type product and the bright band product is excellent. The matching point spaceborne radar GPM / DPR parameter ['FS'][attr_key]['qualityTypePrecip'] is used. This parameter indicates the quality of the precipitation type product. When it is equal to 1, the precipitation type product quality is excellent. The matching point spaceborne radar GPM / DPR parameter ['FS'][attr_key]['qualityBB'] is used. This parameter indicates the quality of the bright band product. When it is equal to 1, the bright band product quality is excellent. If the quality of both the precipitation type product and the bright band product at a matching point is excellent, the matching point is selected; otherwise, it is rejected. The fifth condition is that the echo coverage threshold for both the satellite-ground radar pairing space must be equal to 100%. To analyze the impact of echo coverage in the matching space on the results, the echo coverage f for both the ground-based radar and the GPM / DPR is defined in the matching space as the number of bins with echoes divided by the total number of matched bins. A minimum echo coverage threshold, fmin, is set, and matching samples are selected where both the ground-based radar and the GPM / DPR satisfy f≥fmin. Here, fmin is set to 100%, and only matching samples with an echo coverage of 100%, i.e., complete coverage, are selected. The sixth condition is that the radial distance between the satellite-ground radar pairing space and the center point of the ground-based radar is controlled within 25-200 km for S-band, 25-150 km for C-band, and 25-100 km for X-band.Seventh condition: The paired data is stratiform precipitation. Using the parameter ['FS'][attr_key]['typePrecip'] of the spaceborne radar GPM / DPR, which is ≥ 10,000,000 and < 20,000,000, it indicates stratiform precipitation. Eighth condition: Select paired data with an altitude below the bright band. Using the parameter ['FS'][attr_key]['binBBBottom'] of the spaceborne radar GPM / DPR, which indicates the altitude of the bottom of the bright band, select the sample data for that matching point if its center altitude is below this altitude. Ninth condition: Select paired data with unobstructed elevation angles at the lowest five layers of the ground-based radar (0.5°, 1.5°, 2.4°, 3.4°, and 4.3°).

[0120] like Figure 5 As shown, in one or more embodiments, preferably, the establishment of a fused network radar consistency assessment algorithm to determine an alarm list and form a problem level specifically includes:

[0121] S501. Based on the actual echo difference of ground-based weather radars, the three indicators of average deviation, standard deviation, and correlation of echo intensity data on equidistant lines in the overlapping area of ​​adjacent radars are used to formulate a consistency evaluation standard for ground-based weather radars, wherein the evaluation standard includes: 1) when av≤3, std≤5, and R2≥0.5 are all met, it is considered credible; 2) when any one of 3<av≤5, 5<std≤8, and 0.3≤R2<0.5 is met, it is considered suspicious; 3) when any one of av>5, std>8, and R2<0.3 is met, it is considered a suspected error, wherein av is the average deviation, std is the standard deviation, and R2 is the correlation coefficient;

[0122] S502: Obtain the correlation coefficient of the optimal pairing data of the GPM / DPR and ground-based radar reflectivity factors of a single station, and determine whether it is less than a preset value. If so, it is considered to be abnormal data and added to the blacklist. Otherwise, it is considered that the station has good satellite-ground consistency;

[0123] S503: Determine whether the STD is less than a preset value. If so, the site is stable. Otherwise, it is added to the blacklist and graylist.

[0124] S504: Determine the average deviation of the site. If the deviation is within the threshold, add the site to the whitelist; otherwise, add the site to the graylist.

[0125] S505. Add the blacklist, graylist, and blacklist data to the alarm list. Specific evaluation criteria are as follows: for S-band ground-based weather radar, the correlation coefficient threshold is 0.6, the standard deviation threshold is 4 dB, and the average deviation threshold is [-5.5 dB, 2.5 dB]. For C-band and X-band ground-based weather radars, the correlation coefficient threshold is 0.5, the standard deviation threshold is 5 dB, and the average deviation threshold is determined based on the probability distribution of a single band, ensuring that 70% of the single-band ground-based radar stations are on the whitelist.

[0126] S506. Integrate the results of the ground-based radar network consistency verification algorithm based on the spaceborne radar and the results of the adjacent radar echo intensity consistency detection algorithm, and combine the ground-based weather radar maintenance and upgrade information to set an alarm analysis table.

[0127] S507. Determine the problem level for the monthly blacklist or black / graylist sites according to a pre-set alarm analysis table;

[0128] S508. Determine the problem level of the site on the annual blacklist or black / graylist according to a pre-set alarm analysis table;

[0129] S509: For the gray-listed sites, determine the problem level according to a pre-set overall average deviation analysis table.

[0130] In an embodiment of the present invention, first, ground-based radars in the same band perform consistency detection on the echo intensities of adjacent radars. This is performed separately for the S, C, and X band ground-based radars. The specific process is as follows: CAPPI grid point data of the same contour surface of adjacent radars at the same time is read, the echo overlapping area is found, and the equidistance line with equal distance to the two radars is calculated within the overlapping area (the equidistance line width threshold is adjustable). Finally, the radar echo data on the equidistance line is output for analysis. The specific steps are as follows: (1) Analyze the single-station radar grid data file after data quality control and before puzzle, and read the CAPPI data of the two radars at the same time; (2) Read the station latitude and longitude values ​​and the number of latitude and longitude grid points in the data file, and number the grid data with latitude and longitude; (3) Traverse the generated data to determine the same observation area of ​​the two radars; (4) To reduce the influence of beam broadening and distance attenuation, use the distance formula to find the set of points in the same observation area with equal distances to the two radars, that is, equidistant lines; (5) Determine the width of the equidistant line (the threshold is adjustable) and eliminate abnormal echoes to obtain the echo data that can be used for adjacent radar consistency analysis.

[0131] Specifically, the consistency evaluation criteria are shown in Table 1;

[0132] Table 1 Evaluation criteria for consistency of adjacent radar echo strengths

[0133]

[0134] Secondly, a consistency check algorithm based on spaceborne radar was applied to ground-based radar networks in the same band. This was performed separately for the S, C, and X-band ground-based radars. Using the uniform and stable GPM of Mercury as a reference standard, the results of the Mercury and ground-based radar networks were compared, and consistency standards were established based on the overall situation to evaluate the consistency between the ground-based radars. Because the data source for comparison is the same, the algorithm's evaluation results are reliable and have comparative value. Evaluation indicators were calculated based on the optimal pairing of reflectivity factors of satellite-ground radars at each station, and quality assessment was applied to the ground-based radars based on these indicators.

[0135] White list: the reflectivity factor consistency of satellite-to-ground radar is good, the ground-based radar is stable and has good networking consistency, and there is no problem with the data of this type of ground-based radar during the evaluation period; Black list: one type of alarm list, the reflectivity factor consistency of satellite-to-ground radar is poor, and there are obvious problems in the evaluation period of this type of ground-based radar; Black-gray list: one type of alarm list, the reflectivity factor consistency of satellite-to-ground radar is good but the ground-based radar is not stable enough, and there are problems in the evaluation period of this type of ground-based radar; Gray list: one type of alarm list, the reflectivity factor consistency of satellite-to-ground radar is good, the ground-based radar is stable but has poor networking consistency, and this type of ground-based radar needs calibration or data correction.

[0136] The Chinese radar network consistency assessment algorithm and scheme for integrating ground-based radars in the same band are evaluated separately for the S, C, and X-band ground-based radars. Considering the frequency of satellite passes and precipitation, the ground-based radar network consistency verification algorithm based on spaceborne radars is suitable for timescales of months or longer. Shorter timescales result in insufficient sample size and high randomness. The consistency detection algorithm for echo intensity of adjacent radars compares ground-based radars, lacking a unified reference standard and potentially subject to deviation. Therefore, the two algorithms are integrated to provide complementary evidence.

[0137] If there are problems with the data of the stations on the alarm list, further confirmation is required to determine whether they are key focus stations and feedback to the stations for verification or calibration correction. The results of the adjacent radar echo intensity consistency detection algorithm and the ground-based radar network consistency verification algorithm based on space-borne radar are integrated with the maintenance and upgrade information of ground-based weather radars to establish a highly accurate and applicable Chinese network radar consistency assessment algorithm and scheme. The evaluation results are given in a cyclic evaluation method, the ground-based radar alarm list is graded, and the quality judgment results are given. The specific judgment process is as follows: Figure 9 shown.

[0138] Taking a single month as an example, the detailed plan and process are as follows: First, a monthly report is given to report the problem stations of the month. (1) The ground-based radar network consistency check algorithm based on the spaceborne radar is used to obtain the alarm list of the month; (2) The quality judgment given by the adjacent radar echo intensity consistency detection algorithm is output for the alarm list of the month. If the quality judgment is suspicious or erroneous, the station is comprehensively judged as the problem station of the month. If there is no information record of downtime maintenance and upgrade for the problem station of the month, the problem station needs to be pointed out in the monthly report of the month, and the feedback station needs to verify the specific problem. Among them, the stations judged as problem stations by the gray list need to calculate the difference between the average deviation of the station and the overall average deviation of the same band in China, as well as the difference between the overall average deviation of the same band in the province where they are located. The specific data are given in the monthly report for reference in radar calibration or data correction.

[0139] Secondly, when giving the monthly report for the current month, a list of key concerns for the previous 6 months (including the current month) is given. The evaluation indicators and quality judgments of the alarm list for the previous 6 months (including the current month) are calculated back, as well as the quality judgments of the previous 6 months given by the consistency detection algorithm of the adjacent radar echo intensity of each station. According to the results of the previous 6 months, the radar quality problems (consistency problems) are graded, and it is determined whether to mark them as key concern sites, and the types of radar problems are qualitatively described. (1) For blacklist or black-graylist sites, the quality problems are graded according to the standards in Table 2, and are divided into Level I, Level II, Level III, Level IV, and Level V. The lower the level, the more serious the problem. Level I, Level II, and Level III are marked as key concern sites. If there is no information record of downtime maintenance and upgrades during this period, the site needs to report the problem to the station for verification, otherwise the log record will be followed up for observation; Level IV and Level V are marked as non-key concern sites, and the log record will be followed up for observation. The proportions in Tables 2 and 4 are valid proportions. The alarm ratio (P1) is the ratio of the frequency of alarms at a station to the frequency of quality identification results. For example, if a station has three alarms in a year and 10 months with quality identification, the alarm ratio is 3 / 10. The adjacent radar echo intensity consistency detection algorithm gives the suspicious or suspected error ratio (P2) and the adjacent radar echo intensity consistency detection algorithm gives the suspicious or suspected error ratio (P2) to the frequency of quality identification results. For example, if the adjacent radar echo intensity consistency detection algorithm gives the suspicious or suspected error ratio 25 times and quality identification results 50 times in a year, the adjacent radar echo intensity consistency detection algorithm gives the suspicious or suspected error ratio 1 / 2.

[0140] Table 2: Quality rating standards for sites on the blacklist or black-graylist

[0141]

[0142]

[0143] (2) For the gray list stations, calculate the difference between the average deviation of the previous 6 months (including the current month) and the overall average deviation of the same band in China, as well as the difference between the average deviation of the same band in the province. According to the standards in Table 3, the consistency grade scores of the station compared with China and the province are calculated respectively. The sum of the two scores is the consistency grade score. For example, the difference of Yueyang Station compared with China in 2021 is -4.72 to -3.63, and the difference with the province is -4.50 to -2.20. The consistency grade score compared with China is 2, the consistency grade score compared with the province is 2, and the consistency grade score of the station is 4. According to the consistency grade score, the consistency problem level is divided into Level I (4 points), Level II (3 points), Level III (2 points), Level IV (1 point), and Level V (0 points). The lower the level, the more serious the problem. Level I and Level II are marked as key focus sites. If there is no record of downtime for maintenance and upgrades during this period, the site needs to report the problem to the station for verification, otherwise the log record will be used for follow-up observation; Level III, Level IV, and Level V are marked as non-key focus sites, and the log record will be used for follow-up observation.

[0144] For grey-listed sites, the grade score is determined based on a pre-set overall average deviation analysis table.

[0145] Table 3 Greylist site consistency problem level score standard

[0146] Difference Qualitative description Level score Always greater than 0 and the minimum value is ≥ 2 Abnormally large 2 Always greater than 0 and 0<minimum value<2 Too big 1 There are positive and negative Normal 0 Always less than 0 and the maximum value is ≤ -2 Abnormally small 2 Always less than 0 and 0<maximum value≤-2 Small 1

[0147] If the consistency assessment results for China's ground-based weather radars are given on an annual scale, the results for the previous 12 months (including the current month) must be calculated when designating the priority list. The standards in Table 2 should be replaced with those in Table 4. The remaining procedures remain unchanged, and the quality (consistency) issues should be graded. For assessments on other time scales, the standards given on the monthly and annual scales can be used as a reference.

[0148] Table 4: Quality rating standards for sites on the blacklist or black-graylist

[0149]

[0150]

[0151] The standards in Tables 2, 3, and 4 apply to all S-band, C-band, and X-band frequencies. The alert list specifically refers to problem sites identified by the ground-based radar network consistency verification algorithm for spaceborne radars; the focus list is based on the integrated Chinese network radar consistency assessment algorithm and solution, which classifies the quality issues (consistency issues) on the alert list and comprehensively identifies sites with serious problems.

[0152] Based on the above evaluation results, a standard radar database was established. The specific development standards are as follows: (1) The stations and their base data reflectivity factors whose quality judgment is whitelisted during the evaluation period; (2) The stations and their base data reflectivity factors whose quality judgment is graylisted during the evaluation period and whose comprehensive quality judgment is consistency problem level III, IV, and V; (3) The stations and their base data reflectivity factors whose quality judgment is graylisted during the evaluation period and whose comprehensive quality judgment is consistency problem level I and II. A linear relationship is established between the optimal paired data of the satellite-borne radar GPM / DPR and ground-based radar reflectivity factors during the evaluation period. Based on the linear relationship, the base data reflectivity factor is obtained by linearly correcting the ground-based radar reflectivity factor using the satellite-borne radar GPM / DPR.

[0153] The principle for obtaining the problem list is to identify sites whose quality is judged to be on the blacklist or black-gray list during the evaluation period and their base data reflectivity factors.

[0154] Figure 6 The present invention is a flowchart of performing a standard comparison on the reflectivity factor of a ground-based radar to form a matching result between a standard database and a new type of spaceborne radar FY3-G / PMR.

[0155] like Figure 6 As shown, in one or more embodiments, preferably, the standard comparison of the ground-based radar reflectivity factor to form a matching result between the standard database and the new spaceborne radar FY3-G / PMR specifically includes:

[0156] S601, extracting the standard database of the ground-based radar reflectivity factor and matching it with the data of the spaceborne radar FY3-G / PMR;

[0157] S602: Add matching of the bands corresponding to the reflectivity factors of the S band, C band, and X band, and use the matching results as the matching results of the standard database.

[0158] In an embodiment of the present invention, the spaceborne radar FY3-G / PMR is matched and compared with the standard database of multi-band ground-based weather radar reflectivity factors, and the results of matching the S-band, C-band, and X-band reflectivity factors of the FY3-G / PMR frequency correction module and the corresponding band ground-based radar reflectivity factors are added, wherein the ground-based radar reflectivity factor selects the standard database of the ground-based radar reflectivity factor.

[0159] Figure 7 This is a flowchart of setting evaluation categories, forming a standard database, and storing evaluation results of the new spaceborne radar FY3-G / PMR under different categories in one embodiment of the present invention.

[0160] like Figure 7As shown, in one or more embodiments, preferably, the setting of evaluation categories, forming and storing the evaluation results of the standard database and the new spaceborne radar FY3-G / PMR under different categories, specifically includes:

[0161] S701, multi-group classification by station, province, radar type, month, altitude, precipitation intensity and frequency;

[0162] S702: Display and store evaluation results corresponding to different sites, provinces, radar types, months, altitudes, precipitation intensities, and frequencies according to the classification;

[0163] S703: Display and store the overall evaluation results of all spaceborne radars and ground-based radars according to the evaluation indicators.

[0164] In an embodiment of the present invention, when using a single-band ground-based radar reflectivity factor standard database to conduct authenticity verification and evaluation of the reflectivity factor of the spaceborne radar FY3-G / PMR, the following eight points are considered. The evaluation is conducted sequentially for the three bands S, C, and X. 1) Overall evaluation: Matching samples of the spaceborne radar FY3-G / PMR and the Chinese ground-based radar reflectivity factor are used to calculate an overall result according to the evaluation indicators. Simultaneously, matching samples of the spaceborne radar FY3-G / PMR and the Chinese ground-based radar reflectivity factor standard database are used to calculate an overall result according to the evaluation indicators. By comparing the differences before and after, the impact of establishing a standard database for ground-based radar reflectivity factors on the authenticity verification results of the spaceborne radar FY3-G / PMR reflectivity factor is determined. 2) Sub-site evaluation: Matching samples of the spaceborne radar FY3-G / PMR and the Chinese ground-based radar reflectivity factor standard database are used to calculate the results for each site according to the evaluation indicators, obtaining the evaluation results for the authenticity verification of the FY3-G / PMR reflectivity factor at each site. 3) Provincial Evaluation: Based on the province to which the ground-based radar site belongs, the matching samples of the spaceborne radar FY3-G / PMR and the China Standard Database of Ground-Based Radar Reflectivity Factors are used to calculate the provincial results according to the evaluation indicators, and the provincial evaluation results of the FY3-G / PMR reflectivity factor authenticity test are obtained. 4) Radar Type Evaluation: Based on the radar type to which the ground-based radar site belongs, the matching samples of the spaceborne radar FY3-G / PMR and the China Standard Database of Ground-Based Radar Reflectivity Factors are used to calculate the radar type results according to the evaluation indicators, and the radar type evaluation results of the FY3-G / PMR reflectivity factor authenticity test are obtained. 5) Monthly Evaluation: Based on the matching samples of the spaceborne radar FY3-G / PMR and the China Standard Database of Ground-Based Radar Reflectivity Factors are used to calculate the monthly results according to the evaluation indicators, and the monthly evaluation results of the FY3-G / PMR reflectivity factor authenticity test are obtained. 6) Altitude Evaluation: Based on the altitude of the ground-based radar site, matching samples from the FY3-G / PMR spaceborne radar and the Chinese standard database of ground-based radar reflectivity factors were used to calculate the results for different altitude intervals according to the evaluation indicators. The results of the FY3-G / PMR reflectivity factor authenticity test were obtained for the ground-based radar at different altitude intervals. 7) Precipitation Intensity Evaluation: Based on the precipitation intensity, matching samples from the FY3-G / PMR spaceborne radar and the Chinese standard database of ground-based radar reflectivity factors were used to calculate the results for different precipitation intensity intervals according to the evaluation indicators. The results of the FY3-G / PMR reflectivity factor authenticity test were obtained for the ground-based radar at different precipitation intensity intervals. 8) Frequency Correction Algorithm Evaluation: Based on the frequency correction algorithm, matching samples from the FY3-G / PMR spaceborne radar and the Chinese standard database of ground-based radar reflectivity factors were used to calculate the results for different frequency correction algorithms according to the evaluation indicators. The results of the FY3-G / PMR reflectivity factor authenticity test were obtained for the ground-based radar at different frequency correction algorithms.The two frequency correction algorithms refer to the algorithm in this design and the algorithm provided by FY3-G / PMR.

[0165] According to a second aspect of an embodiment of the present invention, a joint calibration system for spaceborne and multi-band ground-based radar reflectivity factors is provided.

[0166] Figure 8 It is a structural diagram of a joint verification system for spaceborne and multi-band ground-based radar reflectivity factors according to an embodiment of the present invention.

[0167] In one or more embodiments, preferably, the spaceborne radar and spaceborne and multi-band ground-based radar reflectivity factor joint calibration system includes:

[0168] The data source determination module 801 is used to set the data source of the spaceborne radar and the ground-based weather radar;

[0169] A data quality control module 802 is configured to perform data quality control based on the data sources of the spaceborne radar and the ground-based weather radar to form a corrected data source;

[0170] The matching and comparison module 803 is used to match and compare the reflectivity factors of the spaceborne radar GPM / DPR and the ground-based weather radar based on the corrected data source to form the optimal matching data;

[0171] The consistency fusion module 804 is used to establish a fused network radar consistency assessment algorithm to determine the alarm list and form a problem level;

[0172] The standard comparison module 805 is used to perform standard comparison on the reflectivity factor of the ground-based radar to form a matching result between the standard database and the new space-borne radar FY3-G / PMR;

[0173] The authenticity evaluation module 806 is used to set evaluation categories, form a standard database and store evaluation results of the new spaceborne radar FY3-G / PMR under different categories.

[0174] In the embodiment of the present invention, a system applicable to different structures is realized through a series of modular designs. The system can achieve closed-loop, reliable and efficient execution through collection, analysis and control.

[0175] The technical solutions provided by the embodiments of the present invention may have the following beneficial effects:

[0176] In the solution of the present invention, the two perspectives of satellite-ground comparison and ground-to-ground comparison are integrated to establish a fused Chinese network radar consistency assessment algorithm to classify, grade and correct ground-based weather radar data, covering the S, C and X bands, and generate a ground-based weather radar standard database and problem list.

[0177] In the solution of the present invention, by establishing a fused networked radar consistency assessment algorithm, the reflectivity factor data of multi-band ground-based weather radars are quality controlled, classified, graded, and corrected, providing a reference for the application of ground-based radar networking data and numerical model assimilation. A ground-based weather radar standard database is established to verify the data quality of FY-3G / PMR, reduce the error of ground verification sources, and provide a basis for the improvement of satellite algorithm products.

Claims

1. A joint calibration method for spaceborne and multi-band ground-based radar reflectivity factors, characterized in that: The method includes: Set up data sources for spaceborne radar and ground-based weather radar; Performing data quality control based on the data sources of the spaceborne radar and the ground-based weather radar to form a revised data source; Match and compare the reflectivity factors of spaceborne radar GPM / DPR and ground-based weather radar based on the corrected data source to form the optimal paired data; Establish a fusion network radar consistency assessment algorithm to determine the alarm list and form a problem level; Conduct standard comparisons of ground-based radar reflectivity factors to generate matching results between the standard database and the new spaceborne radar FY3-G / PMR; Set evaluation categories, generate and store the matching results of the standard database and the new spaceborne radar FY3-G / PMR in different categories; The matching and comparison of the reflectivity factors of the spaceborne radar GPM / DPR and the ground-based weather radar based on the corrected data source to form the optimal paired data specifically includes: The reflectivity factors of spaceborne radar and ground-based radar are obtained through time matching, space matching and digital matching; Establish screening and comparison conditions for valid pairing events; wherein, the screening and comparison conditions include: first condition: control the quality of satellite-borne radar data products, and the overall quality is excellent; second condition: eliminate the pairing data with clutter interference at the bottom of the satellite-borne radar; third condition: the average value threshold limit of the satellite-to-ground radar reflectivity factor, dBZ DPR ≥18 dBZ, dBZ GR ≥15dBZ; Fourth condition: Control the quality of spaceborne radar data products, that is, the quality of precipitation type products and bright band products are both excellent; Fifth condition: The echo coverage threshold of the satellite-ground radar pairing space is equal to 100%; Sixth condition: The radial distance between the satellite-ground radar pairing space and the ground-based radar center point is controlled within 25-200 km for S-band, 25-150 km for C-band, and 25-100 km for X-band; Seventh condition: The paired data is stratiform precipitation; Eighth condition: Select paired data with an altitude below the bright band; Ninth condition: Select paired data with no obstructions at the lowest five elevation angles of 0.5°, 1.5°, 2.4°, 3.4°, and 4.3° for the ground-based radar. Set the relationship between the screening conditions, where the first, second and third conditions are preprocessing conditions, and the fourth, fifth, sixth, seventh, eighth and ninth conditions are screening and comparison conditions. When the fourth, fifth, sixth, seventh, eighth and ninth conditions are met at the same time, the matching point sample data is selected as the optimal pairing data; in, is the matching DPR reflectivity factor value, is the matching ground-based radar reflectivity factor value.

2. The method for joint verification of spaceborne and multi-band ground-based radar reflectivity factors according to claim 1, wherein: The data sources of the spaceborne radar and the ground-based weather radar are specifically set up as follows: The GPM / DPR data source of the spaceborne radar is set to use the Global Precipitation Satellite (GPM) Dual-Frequency Rainfall Radar (DPR); The data source of the spaceborne radar FY3-G / PMR is set to use the Fengyun-3G precipitation measurement radar; The data source for setting up the ground-based weather radar adopts the basic data of the ground-based weather radar S, C, and X bands that have been quality controlled by a single station.

3. The method for joint verification of spaceborne and multi-band ground-based radar reflectivity factors according to claim 1, wherein: The data quality control is performed based on the data sources of the spaceborne radar and the ground-based weather radar to form a corrected data source, specifically including: For spaceborne radar GPM / DPR data, reduce the data source if the quality does not meet the preset level; The S-band and C-band data of Doppler weather radar are quality controlled by noise point filtering, fault image recognition, electromagnetic interference echo recognition, ground object / super-refraction echo recognition, wave echo recognition and velocity deblurring. The X-band data of ground-based radar are quality controlled by using Z H -K DP The comprehensive correction method is used to correct the echo intensity attenuation and complete the correction of the ground-based weather radar.

4. The method for joint verification of reflectivity factors of spaceborne and multi-band ground-based radars according to claim 1, wherein: The matching and comparison of the reflectivity factors of the spaceborne radar GPM / DPR and the ground-based weather radar based on the corrected data source to form the optimal paired data specifically includes: The reflectivity factors of spaceborne radar and ground-based radar are obtained through time matching, space matching and digital matching; Calculating the correlation coefficient using the first calculation formula according to the reflectivity factor of the spaceborne radar and the reflectivity factor of the ground-based radar; Calculate the average deviation using the second calculation formula; Calculate the standard deviation using the third calculation formula; After the original pairing of satellite-to-ground radar reflectivity factors is successful, the overlap area between the two scans is screened to see if the reflectivity is greater than 1000km. 2 The precipitation echo is considered to be a valid pairing event; The first calculation formula is: Where R is the correlation coefficient, is the matching DPR reflectivity factor value, is the average value of the matched DPR reflectivity factor, N is the number of matched samples, i is the matching sample number, is the matching ground-based radar reflectivity factor value, is the average value of the matched ground-based radar reflectivity factor; The second calculation formula is: Among them, Bias is the average deviation; The third calculation formula is: Among them, Std_bias is the standard deviation, It is the difference between DPR and the reflectivity factor of ground-based radar, expressed in dB.

5. The method for joint verification of reflectivity factors of spaceborne and multi-band ground-based radars according to claim 1, characterized in that: The establishment of the integrated network radar consistency assessment algorithm determines the alarm list and forms the problem level, specifically including: Combined with the actual echo difference of ground-based weather radar, the consistency evaluation standard of ground-based weather radar is formulated using the three indicators of average deviation, standard deviation and correlation of echo intensity data on the equidistance line in the overlapping area of ​​adjacent radars. The evaluation criteria include: 1) when av≤3, std≤5, and R2≥0.5 are all met, it is considered credible; 2) when any one of 3<av≤5, 5<std≤8, and 0.3≤R2<0.5 is met, it is considered suspicious; 3) when any one of av>5, std>8, and R2<0.3 is met, it is considered a false error, where av is the average deviation, std is the standard deviation, and R2 is the correlation coefficient; Obtain the correlation coefficient of the optimal pairing data of the GPM / DPR and ground-based radar reflectivity factors of a single station, and determine whether it is less than the preset value. If it is less than, it is considered to be abnormal data and added to the blacklist. Otherwise, it is considered that the station has good consistency between the satellite and the ground; Determine whether the STD is less than the preset value. If so, the site is stable. Otherwise, it is added to the blacklist and graylist. Determine the average deviation of the site. If the deviation is within the threshold, add it to the whitelist; otherwise, add it to the graylist. Add blacklist, greylist and blacklist data to the alarm list; The specific evaluation criteria are as follows: For S-band ground-based weather radars, the correlation coefficient threshold is 0.6, the standard deviation threshold is 4 dB, and the average deviation threshold is [-5.5 dB, 2.5 dB]. For C-band and X-band ground-based weather radars, the correlation coefficient threshold is 0.5, the standard deviation threshold is 5 dB, and the average deviation threshold is determined based on the probability distribution of the single band, ensuring that 70% of the single-band ground-based radar sites are on the whitelist. The alarm analysis table is set up by integrating the results of the ground-based radar network consistency verification algorithm based on space-borne radar and the results of the adjacent radar echo intensity consistency detection algorithm, combined with the maintenance and upgrade information of the ground-based weather radar.

6. The method for joint verification of reflectivity factors of spaceborne and multi-band ground-based radars according to claim 1, wherein: The standard comparison of the ground-based radar reflectivity factor forms the matching result of the standard database and the new spaceborne radar FY3-G / PMR, specifically including: Extracting the standard database of the ground-based radar reflectivity factor and matching it with the data of the spaceborne radar FY3-G / PMR; Specifically, the standard database of ground-based radar reflectivity factors is a white list and a revised gray list; Add matching of the bands corresponding to the reflectivity factors of the S band, C band, and X band, and use the matching results as the matching results of the standard database.

7. The method for joint verification of reflectivity factors of spaceborne and multi-band ground-based radars according to claim 1, wherein: The setting of the evaluation classification forms and stores the evaluation results of the matching results between the standard database and the new spaceborne radar FY3-G / PMR under different categories, specifically including: Multiple classifications were made by station, province, radar type, month, altitude, precipitation intensity and frequency; The evaluation results corresponding to different sites, provinces, radar types, months, altitudes, precipitation intensity and frequency are displayed and stored according to the classification; The overall evaluation results of all spaceborne radars and ground-based radars are displayed and stored according to the evaluation indicators.

8. A joint calibration system for spaceborne and multi-band ground-based radar reflectivity factors, characterized by: The system is used to implement the method according to any one of claims 1 to 7, and the system comprises: The data source determination module is used to set the data source of the spaceborne radar and the ground-based weather radar; A data quality control module is used to perform data quality control based on the data sources of the spaceborne radar and the ground-based weather radar to form a corrected data source; The matching and comparison module is used to match and compare the reflectivity factors of the spaceborne radar GPM / DPR and the ground-based weather radar based on the corrected data source to form the optimal matching data; The consistency fusion module is used to establish a fusion network radar consistency assessment algorithm to determine the alarm list and form a problem level; The standard comparison module is used to perform standard comparison on the reflectivity factor of ground-based radar to form the matching result between the standard database and the new spaceborne radar FY3-G / PMR; The authenticity assessment module is used to set the assessment categories, form a standard database and store the assessment results of the new spaceborne radar FY3-G / PMR in different categories.

9. A computer-readable storage medium storing computer program instructions, characterized in that: The computer program instructions implement the method according to any one of claims 1 to 7 when executed by a processor.

10. An electronic device comprising a memory and a processor, characterized in that: The memory is configured to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method according to any one of claims 1 to 7.

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