KR101871316B1 - Method and apparatus of quality controlling for evaluation rainfall measurement of dual polarization radar, computer readable medium for performing the method - Google Patents

Method and apparatus of quality controlling for evaluation rainfall measurement of dual polarization radar, computer readable medium for performing the method Download PDF

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KR101871316B1
KR101871316B1 KR1020180043444A KR20180043444A KR101871316B1 KR 101871316 B1 KR101871316 B1 KR 101871316B1 KR 1020180043444 A KR1020180043444 A KR 1020180043444A KR 20180043444 A KR20180043444 A KR 20180043444A KR 101871316 B1 KR101871316 B1 KR 101871316B1
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terrain
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오영아
정성화
석미경
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대한민국
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Abstract

A quality control apparatus and method for estimating a rainfall amount of a dual polarization radar, and a recording medium for performing the method. The quality control apparatus for estimating the rainfall amount of the dual polarized radar includes a data collection unit for collecting observation data of the dual polarized radar, a terrestrial echo discrimination variable from the pre-filtering and the post-filtering reflectance of the observation data, Echo discrimination variable is calculated from the dual polarization parameter of the observation data, and if the non-geocoder echo discrimination variable satisfies the threshold condition And a non-meteorological echo discrimination section for discriminating and removing the corresponding region as a non-terrestrial echo other than the terrestrial echo.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to a quality control apparatus and method for estimating a rainfall amount of a dual-polarized radar, and a recording medium for performing the same. 2. Description of the Related Art [

The present invention relates to a quality control apparatus and method for estimating a rainfall amount of a dual polarized radar, and a recording medium for performing the same. More particularly, the present invention relates to a non-meteorological echo area classified as terrestrial echo, blue echo, The present invention relates to a quality control apparatus and method for estimating a rainfall amount of a dual polarized radar, and a recording medium for performing the method.

The quality control algorithm of radar data currently operated by Korea Meteorological Administration is a fuzzy logic based algorithm. The fuzzy logic-based algorithm uses only the change in the direction of sight of the dual polarized variable as a discriminant variable. The cross correlation coefficient (ρ HV ), which is a parameter indicating the similarity of the particles in the observation volume, is decreased due to attenuation. There is a limit.

Also, according to the fuzzy logic-based algorithm, the amount of change in the direction of the line of sight of the dual polarization variable is calculated at every lattice point, which slows the operation speed.

(Prior Art 1) Korean Patent No. 10-1528525

One aspect of the present invention is to estimate a rainfall amount of a dual polarized radar that calculates a terrestrial echo discrimination variable from the pre-filtering DZ and the post-filtering reflectance CZ of the dual polarized radar, And a recording medium for carrying out the method.

Another aspect of the present invention is to calculate the non-meteoric echo discrimination variable using the correlation between the dual polarization parameter (ρ HV ) and the differential reflectivity (Z DR ) and the reflectivity (Z H ) of the observed data of the dual polarized radar And a recording medium for performing the method. The present invention also provides a quality management apparatus and method for estimating a rainfall amount of a dual polarized radar that reflects a PIA in an attenuation correction factor.

Another aspect of the present invention is a device and method for quality control for estimating the rainfall amount of a dual polarized radar that compares a non-vapor echo discrimination variable with a threshold condition and reflects the PIA as an attenuation correction factor when discriminating a non-vapor echo , And provides a recording medium for performing this.

In order to solve the above problems, a quality management apparatus for estimating the rainfall amount of a dual polarized radar includes a data collecting unit for collecting observational data of a dual polarized radar, a terrain echo discrimination variable from the pre-filtering reflectance and the post- A terrain echo discriminator for discriminating the terrain echo discrimination variable as a terrestrial echo when the terrestrial echo discrimination variable satisfies a threshold condition and a non-terrestrial echo discrimination variable from a double polarity parameter of the observation data, Echo discrimination unit for discriminating the corresponding region as a non-geo-echo other than the terrestrial echo and removing the non-geo-echo when the critical condition is satisfied.

The terrain echo discrimination unit may calculate a plurality of terrain echo discrimination variables by using a difference between the pre-filtering degree and the post-filtering degree, and the gaze direction standard deviation of the pre-filtering degree and the post- Comparing the plurality of terrain echo discrimination variables with a threshold condition that is set differently according to the terrain echo discrimination variable, and when at least one terrestrial echo discrimination variable among the plurality of terrain echo discrimination variables satisfies the threshold condition, It can be discriminated and removed.

The terrain echo judging unit may calculate the difference between the pre-filtering degree and the post-filtering degree by using the terrestrial echo discrimination variable, and if the terrestrial echo discrimination variable satisfies the threshold condition, .

Also, the terrain echo judging unit may calculate the difference between the pre-filtering and post-filtering reflectivity with respect to the post-filtering reflectivity as the terrain echo discriminating variable, and if the terrestrial echo discriminating variable satisfies the threshold condition, And can be removed.

The terrestrial echo discrimination unit may calculate the gaze direction standard deviation of the pre-filtering reflectivity and the gaze direction standard deviation of the post-filtering reflectivity as the terrestrial echo discrimination variable, and calculate a gaze direction standard deviation of the pre- If all of the standard deviations of the viewing direction of the reflectivity satisfy the critical condition, the corresponding area can be discriminated as a terrain echo and removed.

The terrain echo determining unit may calculate a difference between a gaze direction standard deviation of the pre-filtering reflectivity and a gaze direction standard deviation of the post-filtering reflectivity as the terrain echo discrimination variable, and when the terrain echo discrimination variable satisfies a threshold condition The area can be identified and removed as a terrain echo.

The non-vapor echo discrimination unit may calculate a plurality of non-vapor echo discrimination variables according to the relationship between the cross correlation coefficient (ρ HV ) and the differential reflectance (Z DR ) included in the dual polarization parameter and the pre- Wherein the at least one non-meteorological echo discriminating variable of the plurality of non-meteorological echo discriminating variables compares the threshold condition differently set for the plurality of non-meteorological echo discriminating variables with the plurality of the non-meteorological echo discriminating variables, , The corresponding region can be identified and removed as non-terrestrial echoes other than terrain echoes.

Also, the non-vapor echo discrimination unit calculates a cross correlation coefficient (ρ HV ) of the double polarization parameter as a non-gaseous echo discriminating variable, and when the non-gaseous echo discriminating variable satisfies the threshold condition, It can be distinguished by weather echo and removed.

The non-vapor echo discrimination unit may calculate the differential reflectivity (Z DR ) of the dual polarization parameter as a non-vapor phase echo discrimination variable, and if the non-gas phase echo discrimination variable satisfies the critical condition, It can be discriminated by echo and removed.

Also, the non-vapor echo discrimination section calculates a distance cumulative attenuation value from the pre-filtering degree of refraction, and represents a distribution between the cross-correlation coefficient (ρ HV ) and the pre-filtering degree of refraction among the dual polarization parameters, Function, and calculates the non-meteoric echo discrimination variable by using the function. If the non-meteorological echo discrimination variable satisfies the threshold condition, the corresponding region can be discriminated as a non-meteoric echo except for the terrestrial echo.

Also, the non-vapor echo discrimination unit may determine the non-vapor echo discrimination variable by applying a cross correlation coefficient (ρ HV ) of the double polarized parameter to the value of the differential reflectance (Z DR ) of the double polarized parameter versus the pre- And if the non-meteorological echo discrimination variable satisfies the threshold condition, the corresponding region can be discriminated as a non-meteoric echo except for the topographic echo and removed.

According to another aspect of the present invention, there is provided a quality control method for estimating a rainfall amount of a dual polarized radar, comprising: collecting observation data of a dual polarized radar; calculating a terrestrial echo discrimination variable from the pre- Wherein when the terrestrial echo discrimination variable satisfies the threshold condition, the corresponding region is discriminated as a terrestrial echo and removed, and a non-terrestrial echo discrimination variable is calculated from the double polarization parameter of the observation data, , The corresponding region can be identified and removed as non-terrestrial echoes other than terrain echoes.

In addition, when the terrestrial echo discrimination variable is calculated from the pre-filtering and post-filtering reflectivity of the observation data and the terrestrial echo discriminating variable satisfies the threshold condition, discrimination of the terrain echo as the terrestrial echo is performed, Calculating a plurality of terrain echo discrimination variables using the difference between the reflectance after filtering and the gaze direction standard deviation of the reflectance before filtering and the reflectivity after filtering and comparing the threshold condition that is set differently for the plurality of terrain echo discrimination variables, And if the at least one terrain echo discrimination variable among the plurality of terrain echo discrimination variables satisfies the threshold condition, the corresponding terrain echo discrimination variable may be determined to be a terrain echo.

In addition, when the terrestrial echo discrimination variable is calculated from the pre-filtering and post-filtering reflectivity of the observation data and the terrestrial echo discriminating variable satisfies the threshold condition, discrimination of the terrain echo as the terrestrial echo is performed, The difference in reflectivity after filtering may be calculated as the terrain echo discrimination variable, and if the terrestrial echo discrimination variable satisfies the threshold condition, the terrain echo discrimination may be performed to discriminate the corresponding region as the terrestrial echo.

In addition, if the terrain echo discrimination variable is calculated from the pre-filtering and post-filtering reflectivity of the observation data and the terrestrial echo discrimination variable satisfies the threshold condition, Calculating a difference between the pre-filtering degree and the post-filtering degree of reflection as the terrain echo discriminating variable, and if the terrestrial echo discriminating variable satisfies the threshold condition, discriminating the terrain echo as a terrain echo and removing the terrain echo discriminating variable.

If the terrain echo discrimination variable is calculated from the pre-filtering and post-filtering reflectivity of the observation data, and if the terrestrial echo discriminating variable satisfies the threshold condition, discriminating the terrain echo as the terrain echo and removing the pre- The gaze direction standard deviation and the gaze direction standard deviation of the reflectivity after filtering are calculated as the terrain echo discrimination variable, and when the gaze direction standard deviation of the pre-filtering degree and the gaze direction standard deviation of the reflectivity after filtering all satisfy the threshold condition It may be to identify and remove the area as a terrain echo.

If the terrain echo discrimination variable is calculated from the pre-filtering and post-filtering reflectivity of the observation data, and if the terrestrial echo discriminating variable satisfies the threshold condition, discriminating the terrain echo as the terrain echo and removing the pre- The difference between the gaze direction standard deviation and the gaze direction standard deviation of the reflectivity after filtering may be calculated as the terrain echo discrimination variable and if the terrestrial echo discrimination variable satisfies the threshold condition, the corresponding region may be discriminated as the terrain echo and removed .

In addition, if the non-meteorological echo discrimination variable is calculated from the double polarization parameter of the observation data and the non-meteoric echo discriminating variable satisfies the threshold condition, discriminating the corresponding region as a non-meteoric echo other than the terrestrial echo, A plurality of non-vapor echo discrimination variables according to the relationship between the cross correlation coefficient (ρ HV ) and the differential reflectivity (Z DR ) included in the variable and the pre-filtering reflectivity are calculated and set differently for the plurality of non- Wherein the at least one non-meteorological echo discriminating variable discriminates the corresponding region as a non-meteoric echo other than the terrestrial echo if the at least one non-meteorological echo discriminating variable satisfies the threshold condition To remove it.

In addition, if the non-meteorological echo discrimination variable is calculated from the double polarization parameter of the observation data and the non-meteoric echo discriminating variable satisfies the threshold condition, discriminating the corresponding region as a non-meteoric echo other than the terrestrial echo, The cross correlation coefficient (ρ HV ) among the parameters may be calculated as a non-gaseous echo discriminating variable, and if the non-gaseous echo discriminating variable satisfies the threshold condition, the corresponding region may be discriminated as a non-gaseous echo except for the terrestrial echo.

In addition, if the non-meteorological echo discrimination variable is calculated from the double polarization parameter of the observation data and the non-meteoric echo discriminating variable satisfies the threshold condition, discriminating the corresponding region as a non-meteoric echo other than the terrestrial echo, (Z DR ) is calculated as a non-Gaussian echo discrimination variable, and if the non-Gaussian echo discrimination variable satisfies the threshold condition, the corresponding region may be discriminated as a non-geophone echo and removed.

In addition, when the non-meteorological echo discrimination variable is calculated from the double polarized parameter of the observation data and the non-meteorological echo discriminating variable satisfies the threshold condition, discriminating the corresponding region as a non-meteoric echo other than the terrestrial echo, Calculating a distance cumulative attenuation value from the reflectivity, defining a function to which the distance cumulative attenuation value is applied, expressing a distribution between the cross correlation coefficient (ρ HV ) and the pre-filtering reflectivity among the dual polarized variables, And if the non-meteorological echo discriminating variable satisfies the threshold condition, it may be determined that the corresponding region is identified as a non-meteoric echo other than the terrestrial echo.

In addition, when the non-meteorological echo discrimination variable is calculated from the double polarized parameter of the observation data and the non-meteorological echo discriminating variable satisfies the threshold condition, discriminating the corresponding region as a non-meteoric echo other than the terrestrial echo, Calculating a non-meteoric echo discrimination variable by applying a cross correlation coefficient (ρ HV ) of the double polarized parameter to the value of the differential reflectance (Z DR ) of the double polarized parameter with respect to the reflectivity, It is possible to discriminate the corresponding region from the non-terrestrial echo and remove the terrestrial echo.

Further, it may be a computer-readable recording medium in which a computer program is recorded for performing a quality control method for estimating a rainfall amount of a dual polarized radar.

According to the present invention, by calculating the terrestrial echo discrimination variable from the pre-filtering DZ and the post-filtering reflectance CZ of observation data of the dual polarized radar, It is possible to prevent the gaseous echo having the general characteristic of echo from being removed, and to remove the terrain echo having the motion characteristic.

In addition, by calculating the non-meteorological echo discrimination variable using the correlation between the cross correlation coefficient (ρ HV ), the differential reflectivity (Z DR ) and the reflectivity (Z H ) It is possible to discriminate and remove the non - gaseous echoes which are difficult to classify only by the cross correlation coefficient (ρ HV ) and the differential reflectivity (Z DR ), and the accuracy of the non - gaseous echo cancellation can be improved by attenuation correction.

In addition, accuracy improvement can be expected in the quantitative output calculation using quality control data.

In addition, since the operation speed is faster than the fuzzy logic-based quality control method, the driving speed is improved.

1 is a diagram illustrating a quality management apparatus for estimating a rainfall amount of a dual polarized radar according to an embodiment of the present invention.
2 is a control block diagram of the terrain echo classifying unit shown in Fig.
Fig. 3 is a radar reflectivity image before and after filtering in the case of clear sky and rainfall.
4 is an exemplary image for explaining an advantageous effect of the terrain echo removal in the terrain echo classification section shown in Fig.
5 is a control block diagram of the non-vapor echo sorting unit shown in FIG.
FIGS. 6A, 6B, and 7 are diagrams for explaining the calculation of the non-vapor echo discrimination variable in the non-vapor echo classifying unit shown in FIG.
Figs. 8 and 9 are exemplary images for explaining an advantageous effect of non-vapor echo elimination in the non-vapor echo classifying unit shown in Fig.
10 is a view for explaining an advantageous effect of a quality control apparatus for estimating a rainfall amount of a dual polarized radar according to an embodiment of the present invention.
11 is a flowchart of a quality control method for estimating a rainfall amount of a dual polarized radar according to an embodiment of the present invention.

The following detailed description of the invention refers to the accompanying drawings, which illustrate, by way of illustration, specific embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention. It should be understood that the various embodiments of the present invention are different, but need not be mutually exclusive. For example, certain features, structures, and characteristics described herein may be implemented in other embodiments without departing from the spirit and scope of the invention in connection with an embodiment. It is also to be understood that the position or arrangement of the individual components within each disclosed embodiment may be varied without departing from the spirit and scope of the invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is to be limited only by the appended claims, along with the full scope of equivalents to which such claims are entitled, if properly explained. In the drawings, like reference numerals refer to the same or similar functions throughout the several views.

Hereinafter, preferred embodiments of the present invention will be described in more detail with reference to the drawings.

1 is a diagram illustrating a quality management apparatus for estimating a rainfall amount of a dual polarized radar according to an embodiment of the present invention.

1, the quality management apparatus 100 for estimating the rainfall amount of the dual polarized radar according to the present embodiment includes a data collecting unit 110, a terrain echo classifying unit 150, and a non-geocoder echo classifying unit 180 .

The quality management apparatus 100 for estimating the rainfall amount of the dual polarized radar according to the present embodiment may be implemented with software (application) for performing quality control, and the configuration of the data collection unit 110, 100 of the present invention.

The quality management apparatus 100 for estimating the rainfall amount of the dual polarized radar according to the present embodiment may be a separate terminal or a module of the terminal. The apparatus 100 may be in the form of a computer, a server or an engine and may be a device, an apparatus, a terminal, a user equipment (UE), a mobile station ), Another term such as a mobile terminal (MT), a user terminal (UT), a subscriber station (SS), a wireless device, a personal digital assistant (PDA), a wireless modem, a handheld device, Lt; / RTI >

The quality management apparatus 100 for estimating the rainfall amount of the dual polarized radar according to the present embodiment calculates the parameters for discriminating the non-geophone echo based on the real-time observation data of the dual polarized radar, , It is possible to improve the non - echo echo discrimination performance and to improve the accuracy of rainfall estimation from the quality - controlled radar data.

Hereinafter, each configuration of the quality management apparatus 100 for estimating the rainfall amount of the dual polarized radar according to the present embodiment shown in FIG. 1 will be described in detail.

The data collecting unit 110 may collect observation data of the dual polarized radar from the radar system 10. The data collection unit 110 may receive data from the radar system 10 through wired / wireless communication. Here, the radar system 10 may be a working dual polarized radar. Dual polarized radar can observe information related to particle size, type and distribution, as well as the reflection intensity of the observed rainfall / snow particles with a single polarized radar. Dual polarized radar has the advantage that it is easy to distinguish between non - meteorological echo and meteoric echo compared with single polarized radar because of this characteristic and it can correct its own error.

The observation data of the dual polarized radar collected by the data collection unit 110 may include the reflectivity Z H and the dual polarization parameters (cross correlation coefficient ρ HV , differential reflectivity Z DR ). Here, the reflectivity Z H can be roughly divided into a pre-filtering reflectivity DZ and a post-filtering reflectivity CZ. The radar system 10 may proceed with a preprocessing step that applies a filter to the reflectivity of the dual polarized radar. The filter is a filter using the frequency distribution of the reflectivity line speed, for example, an IIR (Infinite Impulse Response) filter.

The terrain echo classifying unit 150 may classify terrestrial echoes among the non-meteoric echoes included in the observation data. This will be described with reference to Figs. 2 to 4. Fig.

FIG. 2 is a control block diagram of the terrain echo classifying unit shown in FIG. 1, FIG. 3 is a radar reflectance image before and after filtering in a clear sky and rainfall case, FIG. 4 is a topographical echo removing Is an exemplary image for explaining an advantageous effect according to the present invention.

Referring to FIG. 2, the terrain echo classifying unit 150 may include a terrain echo discriminating variable calculating unit 151 and a terrain echo removing unit 153.

The terrain echo discriminant variable calculating unit 151 can calculate the terrestrial echo discriminating variable for distinguishing the terrestrial echo using the observation data of the double polarized radar. The terrain echo discrimination variable calculating unit 151 can calculate a plurality of terrain echo discrimination variables from the pre-filtering reflectivity (DZ) and the post-filtering reflectivity (CZ) of observation data of the dual polarized radar.

Terrain echoes are detected by reflection after the radar beam hits the ground. It is mainly caused by high terrain, such as mountain, building, and land. Since the terrain echo is caused by fixed targets on the ground, it is observed in a point echo shape with a small area with a small change in position over time and a reflectivity of up to 80 dBZ.

For example, referring to FIG. 3, the pre-filtering (DZ) observed in KST on May 03, 2013 (Cheongchon case) and the reflectivity (DZ) observed in KST on August 14, 2017 Can be confirmed. When we look at the filtering pre-reflection (DZ) in the case of Cheoncheon, it can be confirmed that the area corresponding to the terrestrial echo exhibits strong reflectivity, and the corresponding area shows similar reflectivity in the case of precipitation.

On the other hand, the reflectivity after filtering (CZ) is the reflectivity to which the filter using the frequency distribution of the visual velocity such as the IIR filter is applied to the reflectivity of the dual polarized radar as described above, and thereby the terrain echo can be removed.

For example, referring to FIG. 3, the post-filtering reflectance (CZ) observed on KST of May 03, 2013 and the post-filtering reflectance (CZ) observed on KST of August 14, 2017 ). When we look at the reflectivity (CZ) after filter filtering in the case of Cheoncheon, it can be confirmed that the region corresponding to the terrestrial echo which shows strong reflectivity in the pre-filtering reflectivity (DZ) is removed. It can be seen that the area corresponding to the terrestrial echo, which exhibits strong reflectivity in the pre-filtering DZ, is also removed in the reflectivity (CZ) after filtering the precipitation case.

However, the reflectivity after filtering (CZ) is applied to the gaze velocity-based filter, and when the gaze velocity has a value other than 0, such as terrestrial echo caused by a mobility object (wood, ship, wind power generator, Can not be removed. In addition, there is a problem in that a gaseous echo whose gaze speed is close to 0 is removed, and an error may be caused in the quantitative use of the reflectivity.

Therefore, the terrain echo discrimination variable calculating section 151 calculates the terrestrial echo discrimination variable calculating section 151 using the difference between the pre-filtering reflectivity DZ and the post-filtering reflectivity CZ and the gaze direction standard deviation of the pre-filtering reflectivity DZ and the post- Can be calculated.

First, the terrain echo discriminant variable calculating unit 151 may calculate the difference between the pre-filtering reflectivity DZ and the post-filtering reflectivity CZ as a topographic echo discriminating variable as shown in Equation 1 below. In the following description, the terrain echo discrimination variable calculated by Equation (1) is defined as a first terrain echo discrimination variable (DIFF ZH ). 3, since the reflectivity of the terrain echo area differs before and after filtering, the terrain echo discrimination variable calculating unit 151 calculates the difference between the pre-filtering reflectivity DZ and the post-filtering reflectivity CZ as the first topography Can be calculated by the echo discrimination variable (DIFF ZH ).

Figure 112018037133707-pat00001

The terrain echo discrimination variable calculating unit 151 may calculate the difference between the reflectance before filtering DZ and the reflectance CZ after filtering according to the following Equation 2 as a terrain echo discriminating variable. In the following description, the terrain echo discrimination variable calculated by Equation (2) is defined as a second terrain echo discrimination variable (Z FILTER ). The terrain echo discriminating variable calculating section 151 may calculate the second terrestrial echo discriminating variable (Z FILTER ) so as to also discriminate the terrain echo representing some weak reflectivity intensity.

Figure 112018037133707-pat00002

The terrain echo discriminant value calculation unit 151 may calculate the gaze direction standard deviation of the pre-filtering reflectivity DZ and the gaze direction standard deviation of the post-filtering reflectivity CZ as the terrain echo discriminating variables, respectively. In the following description, the gaze direction standard deviation of the pre-filtering degree of reflection DZ and the gaze direction standard deviation of the post-filtering degree of reflection CZ are respectively referred to as third terrain echo discrimination variable STDEV (DZ) and fourth terrain echo discrimination variable STDEV (CZ). The gaze direction standard deviation of the pre-filtering DZ and post-filtering CZ represents the line-of-sight texture of each reflectivity, which can be calculated by the following equation (3).

Figure 112018037133707-pat00003

As shown in FIG. 3, the terrain echo discrimination variable calculating unit 151 calculates the gaze direction standard deviation of the pre-filtering reflectivity DZ and the post-filtering reflectivity CZ using the feature that the spatial extent of the topographic echo area is large, (STDEV (DZ)) and the fourth terrain echo discrimination variable (STDEV (CZ)), respectively.

The terrain echo discrimination variable calculating section 151 calculates the difference between the gaze direction standard deviation of the pre-filtering reflectivity DZ and the gaze direction standard deviation of the reflectance CZ after filtering as the terrain echo discriminating variable . In the following description, the terrain echo discrimination variable calculated by the equation (4) is defined as a fifth terrain echo discrimination variable (DIFF STDEV ). Even in the case of hail or strongly convective cells among the meteoric echoes, the spatial variation of reflectivity can be significant. The terrain echo discriminant variable calculating section 151 can calculate the fifth terrain echo discriminating variable (DIFF STDEV ) so as to prevent discrimination of the terrestrial echo with the feature of the feature.

Figure 112018037133707-pat00004

The terrain echo removal unit 153 compares the terrestrial echo discrimination variable with the threshold condition, and if the terrestrial echo discrimination variable satisfies the threshold condition, it can perform the quality control of the observation data by discriminating the corresponding area as the terrestrial echo. The terrain echo removal unit 153 sets a threshold condition for each of the plurality of terrain echo discrimination variables, compares the plurality of terrestrial echo discrimination variables and the threshold condition, respectively, and compares at least one of the plurality of terrestrial echo discrimination variables If the discriminant variable satisfies the critical condition, the corresponding region can be identified as the terrestrial echo and removed from the observed data.

Critical conditions of the first to eigth type echo discrimination variables to the fifth type echo discrimination variable can be set as shown in Table 1 below. It is needless to say that the threshold conditions of the first to fifth echo discrimination variables to the fifth terrain echo discrimination variable shown in Table 1 are exemplary values derived by experiments, but they are not limited thereto and may be set differently.

Figure 112018037133707-pat00005

When the terrain echo discrimination variable calculating unit 151 calculates the first terrain echo discriminating variable (DIFF ZH ) to be equal to or greater than 7.0 dB, the terrain echo removing unit 153 can discriminate the corresponding terrain echo and remove the terrain echo.

If the terrain echo discrimination variable calculating unit 151 calculates the second geographical echo discriminating variable (Z FILTER ) to be 20% or more, the terrain echo removing unit 153 can discriminate the corresponding area as the terrestrial echo and remove the terrain echo .

The terrain echo removal unit 153 receives the third terrain echo discrimination variable STDEV (DZ) and the fourth terrestrial echo discrimination variable STDEV (CZ) , The area can be discriminated as a terrain echo and removed.

When the terrain echo discrimination variable calculating unit 151 calculates the fifth terrain echo discriminating variable (DIFF STDEV ) to be equal to or greater than 4.7 or equal to or less than -2.5, the terrain echo removing unit 153 discriminates the corresponding area as a terrestrial echo Can be removed.

Thus, the terrain echo classifying unit 150 calculates the difference between the pre-filtering reflectivity DZ and the post-filtering reflectance CZ and the difference between the pre-filtering reflectance DZ and the post-filtering reflectance CZ, By distinguishing the terrestrial echo by the terrestrial echo discrimination variable using the direction standard deviation, it is possible to prevent the erosion of the meteoric echo having the general characteristics of the terrestrial echo, such that the gaze speed is close to zero or the spatial variation of the reflectivity is large, It is possible to remove the terrain echo having the motion characteristics. Furthermore, accuracy improvement can be expected in the quantitative yield calculation using observation data quality-controlled by the terrain echo classifying unit 150.

Referring to FIG. 4, in the reflectivity image observed at KST on August 14, 2017, the pre-filtering reflectance image (a), the post-filtering reflectivity image (b), and the conventional fuzzy logic- (C) and the terrain echo classifying unit 150 according to the present embodiment can be confirmed.

In the case of the reflection image c in which the terrain echo is removed by the conventional fuzzy logic-based quality management method, even if the terrain echo is removed, there still remains an area showing strong reflection at the edge. On the other hand, in the case of the reflection image (d) in which the terrain echo is removed by the terrain echo classifying unit 150, the terrestrial echo is completely eliminated compared with the reflection image (c) in which the terrain echo is removed by the fuzzy logic- Can be confirmed.

Referring again to FIG. 1, the non-meteoric echo classifier 180 may classify non-meteoric echoes other than the terrain echo included in the radar observation data. In this regard, the description will be made with reference to Figs. 5 to 9. Fig.

Fig. 5 is a control block diagram of the non-gaseous echo classifying unit shown in Fig. 1, and Figs. 6A, 6B and 7 are diagrams for explaining the calculation of the non-gaseous echo discriminating variable in the non- And FIGS. 8 and 9 are exemplary images for explaining an advantageous effect of the non-vapor echo elimination in the non-vapor echo classifying section shown in FIG.

5, the non-gaseous echo classifier 180 may include a non-gaseous echo discriminant variable calculating unit 181 and a non-gaseous echo canceller 183.

The non-meteorological echo discriminant variable calculating section 181 can calculate the non-meteorological echo discriminating variable for discriminating the non-meteoric echo (wave echo, chaff echo, etc.) except the terrestrial echo using the observation data of the double polarized radar. Calculating a non-gaseous echo determination variable portion 181 is observed reflectivity (Z H) of the material of the dual polarization radar, dual polarization parameters (cross-correlation coefficient (ρ HV) and differential reflectivity (Z DR)) a plurality of non-vapor echo determination from Variables can be calculated. The non-meteorological echo discrimination variable calculating unit 181 may reflect the distance cumulative attenuation (PIA) as the attenuation correction factor when calculating the non-meteorological echo discrimination variable.

More specifically, the non-vapor phase echo discrimination variable calculating section 181 can calculate the cross correlation coefficient (rho HV ) as a non-gas phase echo discriminating variable. The cross correlation coefficient (ρ HV ) is a variable representing the similarity of the particles in the observation volume. It is close to 0 in the case of the echogenic echoes and 0 in the non-echogenic echoes. . In the following description, the cross correlation coefficient (rho HV ) is defined as the first non-wakeup echo discrimination variable (rho HV ).

Also, the non-vapor echo discrimination variable calculating section 181 can calculate the differential reflectivity (Z DR ) as a non-gas phase echo discriminating variable. The differential reflectivity (Z DR ) increases with increasing reflectivity in precipitation echoes and is therefore widely used as a discriminator of the nasal echo classification. In the following description, the differential reflectivity (Z DR ) is defined as a second non-vapor echo discrimination variable (Z DR ).

On the other hand, the cross correlation coefficient (ρ HV ) shows a value close to 1 of 0.7 to 0.9 in the wave echo and chaff echo, and less than 0.7 in the edge of the precipitation echo or in the region where the damping is severe. The correlation coefficient (ρ HV ) alone is difficult to classify non-meteorological echoes. The differential reflectivity (Z DR ) also tends to indicate the negative value when the attenuation is severe, and it is difficult to classify the non-meteorological echo with only the cross correlation coefficient (ρ HV ).

Therefore, the non-vapor echo discrimination variable calculating section 181 can calculate the non-gas echo discriminating variable by using the correlation between the cross correlation coefficient (ρ HV ) and the reflectance (Z H ) in the rain area. Here, the reflectance (Z H ) means the pre-filtering reflectivity (DZ). Non weather echo determination variable calculation unit 181 is cross-correlation, such as the reflectivity (Z H), the distance equation (6) below, calculates the cumulative amount of attenuation (PIA) to the attenuation correction factor, and based on as shown in Equation 5 below (ρ HV ) And the reflectivity (Z H ), and a function to which the attenuation correction factor (PIA) is applied can be defined, and the reflectivity weighting cross correlation coefficient (ρ ZH ) can be calculated using this. In the following description, the reflectivity weighted cross correlation coefficient? ZH is defined as a third non-wakeup echo discrimination variable? ZH . The third non-meteorological echo discriminator (ρ ZH ) can compensate for the cross correlation coefficient (ρ HV ) which shows a low value in the region where the attenuation of the precipitation echo is severe.

Figure 112018037133707-pat00006

In Equation 5 a, b are each in accordance with the coefficient of Ryzhkov (2013) 1.54X10 -5, has a 0.62 may be used.

Referring to FIG. 6A, the cross correlation coefficient (ρ HV ) and the reflectivity (Z H ) in the rainfall region observed in the YIT can be confirmed. The distribution between the cross correlation coefficient (ρ HV ) and the reflectivity (Z H ) follows the exponential function form as shown in FIG. 6b. The non-vapor echo discrimination variable calculating section 181 calculates the third non-vapor echo discriminating variable (ρ ZH ) based on the distribution form between the cross correlation coefficient (ρ HV ) and the reflectance (Z H ) Can be defined.

Figure 112018037133707-pat00007

And can be set to 5T = 70 dBz so that a value of 0.993 can be calculated at a reflectivity of 70 dB in Equation (6) (see FIG. 6B).

The non-vapor echo discrimination variable calculating section 181 can calculate the non-gas echo discriminating variable by using the correlation between the differential reflectance (Z DR ) in the rain area and the reflectivity (Z H ).

Referring to FIG. 7, the differential reflectivity (Z DR ) and reflectivity (Z H ) in a rainfall region observed in KNU and WRC can be confirmed. The distribution between the differential reflectivity (Z DR ) and the reflectivity (Z H ) is highly correlated with the rainfall area. On the other hand, the correlation is low in non-meteoric echoes such as blue echoes and chaff echoes. The differential reflectivity (Z DR ) in the non-vapor echo of blue echoes, chaff echoes, etc. has a value that is ideally large or small.

Therefore, the non-vapor phase echo discrimination variable calculating section 181 applies the cross correlation coefficient? HV as the attenuation correction factor to the value of the differential reflectance (Z DR ) relative to the reflectance (Z H ) as shown in Equation (7) Can be calculated as an echo discrimination variable. The cross correlation coefficient (ρ HV ) gives a weight to the precipitation echo and can compensate for the effect of the decrease in differential reflectivity (Z DR ) due to attenuation. In the following description, the non-meteoric echo discrimination variable calculated by Equation (7) is defined as the fourth non-meteorological echo discrimination variable (Z ratio ).

Figure 112018037133707-pat00008

The non-meteoric echo cancellation 183 compares the non-meteorological echo discrimination variable with the threshold condition, and if the non-meteorological echo discrimination variable satisfies the threshold condition, the quality of the observed data can be managed by determining the corresponding region as the non- have. The non-vapor echo removing unit 183 sets a threshold condition for each of the plurality of non-vapor echo discrimination variables, compares the plurality of non-gas echo discrimination variables and the threshold condition, respectively, If one non-meteorological echo discrimination variable satisfies the critical condition, it can be identified and removed by the non-meteorological echo in the observed data.

The critical conditions of the first to third non-meteorological echo discrimination variables to the fourth non-meteorological echo discrimination variable can be set as shown in Table 2 below. The critical conditions of the first to third non-vapor-phase echo discrimination variables to the fourth non-gaseous echo discrimination variable shown in Table 2 are exemplary values derived by experiments, but they are not limited thereto and may be set differently.

Figure 112018037133707-pat00009

The non-vapor echo removing unit 183 calculates the first non-vapor echo discriminating variable (ρ HV ) to be less than 0.65 by the non-vapor echo discriminating variable calculating unit 181, and if the PIA is less than 1.5 dB, It can be distinguished by non-echo echo except echo and can be removed.

The non-vapor phase echo canceling unit 183 calculates the second non-vapor phase echo discriminating variable Z DR by 7.5 dB or more, the PIA is 1.5 dB or less, and the non-vapor echo discriminating variable calculating unit 181 calculates -1.5 dB, it is possible to identify the area as a non-meteoric echo, excluding the terrestrial echo.

When the third non-vapor echo discriminating variable (? ZH ) is calculated to be 0.4 or less by the non-vapor echo discriminating variable calculating section 181, the non-vapor echo removing section 183 calculates the non- It can be discriminated by echo and removed.

When the fourth non-vapor echo discrimination variable (Z ratio ) is calculated to be 0.25 or more by the non-vapor echo discrimination variable calculating unit 181, the non-gas echo removing unit 183 calculates the non- It can be discriminated by echo and removed.

As described above, the non-vapor echo classifying section 180 can classify the non-geophone echo discriminating variables excluding the terrestrial echo by the non-meteorological echo discriminating variable using the correlation between the cross correlation coefficient (ρ HV ) and the differential reflectivity (Z DR ) The non-meteoric echo can be identified. The non-geophone echo classifier 180 can determine the non-geophone echo by calculating the non-gaseous echo discrimination variable and the non-echo echo discrimination variable and the threshold conditional comparison to the attenuation correction factor (PIA) . Therefore, the non-vapor echo classifying unit 180 can discriminate and remove the non-vapor echo which is difficult to classify only by the cross correlation coefficient p HV and the differential reflectivity Z DR , and furthermore, Accuracy can be increased.

8, the third non-meteorological echo discriminating variable (ρ ZH ) image (a), the distance cumulative attenuation amount (PIA) image (b), and the fourth non- you can check the non-vapor echo determination variable (Z ratio) image (c) and the second non-gaseous echo determination variable (Z DR) image (d).

The third non-meteorological echo discriminant variable (ρ ZH ) image (a) shows that the third non-meteorological echo discriminant variable (ρ ZH ) shows a larger value as the reflectivity (Z H ) and the cross correlation coefficient (ρ HV ) Therefore, it can be confirmed that it is possible to discriminate the non-vapor echo with a low cross-correlation coefficient (ρ HV ) while the reflectivity (Z H ) is low. Also, it can check that the precipitation zone is 0.4 or less nasal number area and classification of having a lower third non-gaseous echo determination parameters of NNE (ρ ZH), this third non-gaseous echo determination parameters (ρ ZH) calculated at the distance This is because the cumulative attenuation (PIA) is reflected in the attenuation correction factor.

Also, when the fourth non-vapor echo discrimination variable (Z ratio ) image c and the second non-vapor echo discrimination variable Z DR image d are compared, the second non-vapor echo discrimination variable Z DR is strong The fourth non-meteoric echo discrimination variable (Z ratio ) has a value of 0.3 or more in the nasal water echo area, which is easy to distinguish from precipitation echo, although it can be confirmed that it has a similar value in the precipitation echo and weak nasal water echo area have.

Referring to FIG. 9, the reflectivity data (CZ) after filtering after a strong precipitation echo is located long in the direction of the radar line in the south-west direction with the reflection data observed at 0600 KST SBS site on July 16, (C), and the reflectance (C) image (d) observed on the site at 0600 KST MYN on July 16, 2017 .

After the filtering, the intensity (CZ) image (a) shows that the intensity decreases as the intensity approaches the backside of the precipitation echo, and the underestimation due to the attenuation can be predicted. (b). Comparing the reflectivity image (c) after the attenuation correction with the MYN site reflectance (d) at the same time, it can be seen that the accuracy can be improved in the quantitative application of the reflectivity by correcting it to a similar intensity.

Thus, the quality management apparatus 100 for estimating the rainfall amount of the dual polarized radar can calculate the terrestrial echo discrimination variable and the non-echo echo discrimination variable, and can perform quality control on the radar data by using the same. In particular, in this embodiment, the quality management apparatus 100 for estimating the rainfall amount of the dual polarized radar calculates a plurality of terrain echo discrimination variables from the pre-filtering reflectivity (DZ) and the post-filtering reflectivity (CZ) And the correlation between the differential polarization (ρ HV ) and the differential reflectivity (Z DR ) and the reflectivity (Z H ) is used to calculate the non - meteorological echo discrimination variable, Comparing the non-meteorological echo discrimination variable with the threshold condition, the PIA can be reflected as the attenuation correction factor.

Therefore, the quality management apparatus 100 for estimating the amount of rainfall of the dual polarized radar according to the present embodiment is capable of estimating the intensity of the precipitation echo even in the attenuation region, as compared with the fuzzy logic-based quality management method using only the direction- It is possible to discriminate and shows high accuracy in blue echo classification. In addition, it is possible to show more accurate classification results even in the vicinity of strong precipitation at a close range or at a weak precipitation area at a distance. Also, since the operation speed is faster than the fuzzy logic-based quality control method that calculates the change amount of the eye direction of the dual polarization parameter at each lattice point, the driving speed is improved.

The quality management apparatus 100 for estimating the rainfall amount of the dual polarized radar according to the present embodiment can calculate quality controlled radar parameters and echo classification ID by performing quality control on the radar observation data. These radar variables and echo classification ID can be used for quantitative prediction of weather conditions such as rainfall.

10 is a view for explaining an advantageous effect of a quality control apparatus for estimating a rainfall amount of a dual polarized radar according to an embodiment of the present invention.

Referring to FIG. 10, the results of the echo discrimination of the rainfall events of May 01, 2017, and June 01, 2017 can be seen. In both cases, strong convective precipitation with a reflectivity of 60dBZ or more, and a case of rainfall accompanied by hail are cases where the distance cumulative attenuation (PI) is above 7dBZ.

According to the fuzzy logic-based quality control method, the nasal echo is discriminated by using the cross-correlation coefficient (ρ HV ) and the change in the direction of sight of the bi-polarized variables and the value of the cross correlation coefficient (ρ HV ) , Or a part of the blue echo area with little visual direction variation is classified as a precipitation echo (Fig. 10 (a)). Meanwhile, the quality management apparatus 100 for estimating the rainfall amount of the dual polarized radar according to an embodiment of the present invention uses the non-meteorological echo discrimination variable calculated based on the correlation between the dual polarization parameters, (Fig. 10 (b)), which is superior to the fuzzy logic-based quality control method.

In addition, according to the fuzzy logic-based quality control method, the center of the precipitation region is classified as a wedge-shaped nasal water echo as the cross correlation coefficient (ρ HV ) is observed to decrease due to the attenuation (FIG. 10 (c) , Fig. 10 (e)). Meanwhile, the quality management apparatus 100 for estimating the rainfall amount of the dual polarized radar according to an exemplary embodiment of the present invention calculates the non-meteorological echo discrimination variable and the distance cumulative attenuation (PIA) when comparing the non-meteorological echo discrimination variable and the threshold condition 10 (d), 10 (f)). The results are shown in Fig. 10 (f).

In addition, the quality management apparatus 100 for estimating the rainfall amount of the dual polarized radar according to an embodiment of the present invention is more accurate than the fuzzy logic-based quality management method in separating strong near precipitation boundaries, And the continuity of the classified echoes is also increased.

Hereinafter, a quality control method for estimating a rainfall amount of a dual polarized radar according to an embodiment of the present invention will be described with reference to FIG. The quality management method for estimating the rainfall amount of the dual polarized radar according to an embodiment of the present invention can be performed in substantially the same configuration as the quality management apparatus 100 for estimating the rainfall amount of the dual polarized radar shown in FIG. Therefore, the same components as those of the quality management apparatus 100 for estimating the rainfall amount of the dual polarized radar of FIG. 1 are denoted by the same reference numerals, and repeated description thereof will be omitted.

11 is a flowchart of a quality control method for estimating a rainfall amount of a dual polarized radar according to an embodiment of the present invention.

Referring to FIG. 11, the data collection unit 110 may collect observation data of the dual polarized radar from the radar system 10 (1000). The observation data of the dual polarized radar collected by the data collection unit 110 may include the reflectivity Z H and the dual polarization parameters (cross correlation coefficient ρ HV , differential reflectivity Z DR ) H can be roughly divided into a pre-filtering reflectivity DZ and a post-filtering reflectivity CZ.

The terrain echo classifying unit 150 can calculate the terrestrial echo discriminating variable using the observation data (1100).

The terrain echo classifying unit 150 classifies the plurality of terrestrial echoes using the difference between the pre-filtering reflectivity DZ and the post-filtering reflectance CZ and the gaze direction standard deviation of the pre-filtering reflectivity DZ and the post- Variables can be calculated.

The terrain echo classifying unit 150 may calculate the difference between the pre-filtering reflectivity DZ and the post-filtering reflectivity CZ as a first terrain echo discriminating variable as shown in Equation 1 above.

The terrain echo classifying unit 150 may calculate the difference between the reflectance before filtering DZ and the reflectance after filtering CZ as a second topographic echo discriminating variable as shown in Equation 2 .

The terrain echo classifying unit 150 may calculate the gaze direction standard deviation of the pre-filtering reflectivity DZ and the gaze direction standard deviation of the post-filtering reflectivity CZ using Equation (3) Echo discrimination variable and fourth terrestrial echo discrimination variable.

The terrain echo classifying unit 150 classifies the difference between the gaze direction standard deviation of the pre-filtering reflectivity DZ and the gaze direction standard deviation of the post-filtering reflectivity CZ as a fifth terrain echo discriminating variable Can be calculated.

The non-meteorological echo classifier 180 can calculate the non-meteorological echo discrimination variable using the observed data (1200).

The non-vapor echo classifier 180 can calculate a plurality of non-vapor echo discrimination variables from the dual polarization parameters (cross correlation coefficient (ρ HV ) and differential reflectivity (Z DR )) of the observation data of the dual polarized radar.

The non-vapor echo classifying unit 180 may calculate the cross correlation coefficient p HV as the first non-meteorological echo discriminating variable.

The non-vapor echo classifying unit 180 may calculate the differential reflectance Z DR as a second non-vapor echo discriminating variable.

The non-vapor echo classifying section 180 can calculate the distance-cumulative attenuation amount (PIA) based on the reflectivity Z H as the attenuation correction factor using the above-described equation (5). The non-vapor echo classifying unit 180 may represent an exponential function to which the attenuation correction factor (PIA) is applied, representing the distribution between the cross correlation coefficient p HV and the reflectivity Z H , as shown in Equation (6) , And the reflectivity weighted cross correlation coefficient (ρ ZH ) calculated therefrom can be calculated as the third non-meteorological echo discriminating variable.

The non-vapor echo classifying unit 180 applies the cross correlation coefficient? HV to the value of the differential reflectance Z DR relative to the reflectance Z H as an attenuation correction factor as shown in Equation 7 to obtain the fourth non- It can be calculated as a discriminant variable.

The terrestrial echo classifier 150 and the non-geophone echo classifier 180 may perform the quality control of the observation data of the dual polarized radar using the terrestrial echo discrimination variable and the non-echo echo discrimination variable 1300, respectively.

The terrain echo classifying unit 150 sets a threshold condition for each of the plurality of terrain echo discrimination variables, compares the plurality of terrain echo discrimination variables and the threshold condition, respectively, and compares at least one of the plurality of terrain echo discrimination variables If the discriminant variable satisfies the threshold condition, the corresponding region can be discriminated as a terrain echo and removed.

The non-vapor echo classifying unit 180 sets a threshold condition for each of the plurality of non-gas echo discrimination variables, compares the plurality of non-gas echo discrimination variables with the threshold condition, and calculates the attenuation correction factor And the at least one non-meteorological echo discrimination variable among the plurality of non-meteorological echo discrimination variables satisfies the threshold condition, the corresponding region can be discriminated as the non-meteoric echo except for the terrestrial echo.

Such a quality control method for estimating the rainfall amount of the dual polarized radar may be implemented in an application or may be implemented in the form of program instructions that can be executed through various computer components and recorded on a computer-readable recording medium. The computer-readable recording medium may include program commands, data files, data structures, and the like, alone or in combination.

The program instructions recorded on the computer-readable recording medium may be ones that are specially designed and configured for the present invention and are known and available to those skilled in the art of computer software.

Examples of computer-readable media include magnetic media such as hard disks, floppy disks and magnetic tape, optical recording media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like.

Examples of program instructions include machine language code such as those generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like. The hardware device may be configured to operate as one or more software modules for performing the processing according to the present invention, and vice versa.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it will be understood by those skilled in the art that various changes and modifications may be made therein without departing from the spirit and scope of the invention as defined in the appended claims. It will be possible.

10: Radar system
100: Quality control device for estimation of rainfall of dual polarized radar
110: Data collection unit
150: terrain echo classifier
180: Non-vapor echo classifier

Claims (23)

A data collection unit for collecting observation data of the dual polarized radar;
A terrain echo discrimination unit for calculating a terrain echo discrimination variable from the pre-filtering and the post-filtering reflectivity of the observation data and discriminating the terrain echo as the terrestrial echo if the terrestrial echo discriminating variable satisfies the threshold condition; And
And a non-meteorological echo discrimination unit for calculating a non-meteoric echo discrimination variable from the dual polarization parameter of the observation data and discriminating the non-meteorological echo discrimination variable other than the terrestrial echo by the non-meteorological echo discrimination variable if the non- Quality Control System for Rainfall Estimation of Dual Polarized Radar. The method according to claim 1,
Wherein the terrain echo discrimination unit comprises:
A plurality of terrain echo discrimination variables are calculated using the difference between the pre-filtering and post-filtering reflectivity and the gaze direction standard deviation of the pre-filtering and post-filtering reflectivity, and are set differently for the plurality of terrain echo discrimination variables Wherein the terrestrial echo discrimination parameter is a threshold value and the terrestrial echo discrimination variable is at least one of the plurality of terrestrial echo discrimination variables. Quality control system for rainfall estimation. The method according to claim 1,
Wherein the terrain echo discrimination unit comprises:
And estimating a rainfall amount of the dual polarized radar that calculates the difference between the pre-filtering degree and the post-filtering degree by using the terrain echo discrimination variable and discriminates the terrain echo discrimination variable as a terrestrial echo if the terrestrial echo discrimination variable satisfies the threshold condition. Quality control device. The method according to claim 1,
Wherein the terrain echo discrimination unit comprises:
The method of claim 1, further comprising: calculating a difference between the pre-filtering degree and the post-filtering degree with respect to the post-filtering degree of reflection as the topographic echo discriminating variable, and if the topographic echo discriminating variable satisfies the threshold condition, Quality control device for estimating the rainfall amount of. The method according to claim 1,
Wherein the terrain echo discrimination unit comprises:
Calculating a gaze direction standard deviation of the pre-filtering degree and a gaze direction standard deviation of the post-filtering degree of reflection as the terrestrial echo discrimination variable; and calculating a gaze direction standard deviation of the pre- And a quality control device for estimating the amount of rainfall of the double polarized radar device which discriminates and removes the area as a terrain echo when the critical condition is satisfied. The method according to claim 1,
Wherein the terrain echo discrimination unit comprises:
Calculating a difference between a gaze direction standard deviation of the pre-filtering degree and a gaze direction standard deviation of the reflectivity after filtering as the terrain echo discrimination variable, and if the terrain echo discrimination variable satisfies the threshold condition, A quality control system for estimating the rainfall of a double polarized radar to be removed. The method according to claim 1,
Wherein the non-vapor echo discrimination unit comprises:
Calculating a plurality of non-vapor echo discrimination variables according to a relationship between a cross correlation coefficient (ρ HV ) and a differential reflectivity (Z DR ) included in the dual polarization parameter and the pre-filtering reflectivity, Wherein the at least one non-meteorological echo discriminating variable of the plurality of non-meteorological echo discriminating variables compares the threshold condition that is set differently with the plurality of non-meteorological echo discriminating variables respectively, Quality Control System for Estimating Rainfall of Double Polarized Radar Detected by Echo. The method according to claim 1,
Wherein the non-vapor echo discrimination unit comprises:
Wherein a cross correlation coefficient (ρ HV ) among the dual polarization parameters is calculated as a non-gaseous echo discrimination variable, and if the non-gaseous echo discrimination variable satisfies the threshold condition, the region is discriminated as a non- Quality control system for estimating rainfall of radar. The method according to claim 1,
Wherein the non-vapor echo discrimination unit comprises:
The dual-polarized radar system according to claim 1, wherein the dual-polarized radar system calculates a differential reflectivity (Z DR ) of the dual polarization parameter as a non-geophone echo discrimination variable and, if the non-geophone echo discrimination variable satisfies the threshold condition, Quality control device for estimating the rainfall amount of. The method according to claim 1,
Wherein the non-vapor echo discrimination unit comprises:
Calculating a distance cumulative attenuation value from the pre-filtering degree of refraction, defining a function to which the distance cumulative attenuation value is applied, expressing a distribution between the cross-correlation coefficient (ρ HV ) and the pre- A quality control apparatus for estimating a rainfall amount of a dual polarized radar system that calculates a non-meteoric echo discrimination variable and discriminates the corresponding region as a non-meteoric echo other than a terrestrial echo if the non-meteoric echo discrimination variable satisfies a threshold condition. The method according to claim 1,
Wherein the non-vapor echo discrimination unit comprises:
Calculating a non-meteoric echo discrimination variable by applying a cross correlation coefficient (ρ HV ) of the dual polarized parameter to the value of the differential reflectance (Z DR ) of the double polarized parameter versus the pre-filtering degree of refraction, Is a non-geophone echo other than the terrestrial echo, if the critical condition is met, and the corresponding region is removed. Observation data of dual polarization radar are collected,
Calculating a terrain echo discrimination variable from the pre-filtering and post-filtering reflectivity of the observation data, and if the terrestrial echo discriminating variable satisfies the threshold condition, discriminating the terrain echo as a terrain echo,
The non-meteorological echo discrimination variable is calculated from the double polarization parameter of the observation data, and when the non-meteorological echo discrimination variable meets the threshold condition, the rainfall amount estimation of the double polarized radar is performed to discriminate the corresponding region as the non- Quality control method for. 13. The method of claim 12,
Calculating a terrain echo discrimination variable from the pre-filtering and post-filtering reflectivity of the observation data, and if the terrestrial echo discriminating variable satisfies the threshold condition,
A plurality of terrain echo discrimination variables are calculated using the difference between the pre-filtering and post-filtering reflectivity and the gaze direction standard deviation of the pre-filtering and post-filtering reflectivity, and are set differently for the plurality of terrain echo discrimination variables Comparing the threshold condition with the plurality of terrain echo discrimination variables, and if at least one terrestrial echo discrimination variable of the plurality of terrain echo discrimination variables meets a threshold condition, discriminating the corresponding terrain echo as a terrestrial echo, Quality Control Method for Radar Rainfall Estimation. 13. The method of claim 12,
Calculating a terrain echo discrimination variable from the pre-filtering and post-filtering reflectivity of the observation data, and if the terrestrial echo discriminating variable satisfies the threshold condition,
Wherein a difference between the pre-filtering and the post-filtering reflectance is calculated as the terrestrial echo discriminating variable, and if the terrestrial echo discriminating variable satisfies the threshold condition, the corresponding region is discriminated as a terrestrial echo and removed. Quality control method for. 13. The method of claim 12,
Calculating a terrain echo discrimination variable from the pre-filtering and post-filtering reflectivity of the observation data, and if the terrestrial echo discriminating variable satisfies the threshold condition,
Calculating a difference between the pre-filtering degree of reflection and the degree of post-filtering degree with respect to the post-filtering degree of reflection as the topographic echo discriminating variable, and if the topographic echo discriminating variable satisfies the threshold condition, discriminating the corresponding area as a topographic echo, A Quality Control Method for Rainfall Estimation of Polarized Radar. 13. The method of claim 12,
Calculating a terrain echo discrimination variable from the pre-filtering and post-filtering reflectivity of the observation data, and if the terrestrial echo discriminating variable satisfies the threshold condition,
Calculating a gaze direction standard deviation of the pre-filtering degree and a gaze direction standard deviation of the post-filtering degree of reflection as the terrestrial echo discrimination variable; and calculating a gaze direction standard deviation of the pre- And if the critical condition is satisfied, the corresponding region is discriminated as a terrain echo and removed, and a quality control method for estimating the rainfall amount of the double polarized radar. 13. The method of claim 12,
Calculating a terrain echo discrimination variable from the pre-filtering and post-filtering reflectivity of the observation data, and if the terrestrial echo discriminating variable satisfies the threshold condition,
Calculating a difference between a gaze direction standard deviation of the pre-filtering degree and a gaze direction standard deviation of the reflectivity after filtering as the terrain echo discrimination variable, and if the terrain echo discrimination variable satisfies the threshold condition, A method for quality control for estimating the amount of rainfall in a dual polarized radar. 13. The method of claim 12,
The non-meteorological echo discrimination variable is calculated from the double polarized parameter of the observation data, and if the non-meteorological echo discrimination variable satisfies the threshold condition, the corresponding region is discriminated as the non-terrestrial echo,
Calculating a plurality of non-vapor echo discrimination variables according to a relationship between a cross correlation coefficient (ρ HV ) and a differential reflectivity (Z DR ) included in the dual polarization parameter and the pre-filtering reflectivity, Wherein the at least one non-meteorological echo discriminating variable of the plurality of non-meteorological echo discriminating variables compares the threshold condition that is set differently with the plurality of non-meteorological echo discriminating variables respectively, A method for quality control for estimating the amount of rainfall in a dual polarized radar that is discriminated and removed by echo. 13. The method of claim 12,
The non-meteorological echo discrimination variable is calculated from the double polarized parameter of the observation data, and if the non-meteorological echo discrimination variable satisfies the threshold condition, the corresponding region is discriminated as the non-terrestrial echo,
(Ρ HV ) among the above dual polarization parameters is calculated as a non-gaseous echo discriminating variable, and when the non-gaseous echo discriminating variable satisfies the threshold condition, the corresponding region is discriminated as a non-gaseous echo other than the terrestrial echo, A Quality Control Method for Rainfall Estimation of Dual Polarized Radar. 13. The method of claim 12,
The non-meteorological echo discrimination variable is calculated from the double polarized parameter of the observation data, and if the non-meteorological echo discrimination variable satisfies the threshold condition, the corresponding region is discriminated as the non-terrestrial echo,
Wherein the differential reflectivity (Z DR ) of the dual polarization parameter is calculated as a non-gaseous echo discrimination variable, and if the non-gaseous echo discrimination variable satisfies the threshold condition, the corresponding region is discriminated as a non- A Quality Control Method for Rainfall Estimation of Polarized Radar. 13. The method of claim 12,
The non-meteorological echo discrimination variable is calculated from the double polarized parameter of the observation data, and if the non-meteorological echo discrimination variable satisfies the threshold condition, the corresponding region is discriminated as the non-terrestrial echo,
Calculating a distance cumulative attenuation value from the pre-filtering degree of refraction, defining a function to which the distance cumulative attenuation value is applied, expressing a distribution between the cross-correlation coefficient (ρ HV ) and the pre- Calculating a non-meteoric echo discrimination variable, and if the non-meteorological echo discrimination variable meets a threshold condition, discriminating the region as a non-meteoric echo other than the terrestrial echo and eliminating it. 13. The method of claim 12,
The non-meteorological echo discrimination variable is calculated from the double polarized parameter of the observation data, and if the non-meteorological echo discrimination variable satisfies the threshold condition, the corresponding region is discriminated as the non-terrestrial echo,
Calculating a non-meteoric echo discrimination variable by applying a cross correlation coefficient (ρ HV ) of the dual polarized parameter to the value of the differential reflectance (Z DR ) of the double polarized parameter versus the pre-filtering degree of refraction, Wherein the region is identified as a non-gaseous echo other than the terrain echo if the threshold condition is satisfied, and the region is removed. 22. A computer-readable recording medium for performing a quality control method for estimating a rainfall amount of a dual polarized radar according to any one of claims 12 to 22.
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