KR20190068793A - Generation Device and Method of Quasi-Vertical Profile of Observation Variables from Weather Radar and Recording Medium thereof - Google Patents

Abstract

The present invention relates to a generation device and a method of a quasi-vertical profile of observation variables from a weather radar, and a recording medium thereof, which are able to, when identifying a vertical structure of precipitation by using a radar, calculate vertical observation data with a high resolution with data of a specific altitude angle. According to the present invention, the generation device of the quasi-vertical profile of observation variables from the weather radar comprises: an altitude angle selection unit which selects an altitude angle; a first profile generation unit which generates a quasi-vertical profile of single and dual polarimetric variables in accordance with the selected altitude angle; a pre-processing unit which pre-processes a radial velocity; a Fourier coefficient calculation unit which displays a radial velocity-azimuth curve in a type of Fourier series to calculate a Fourier coefficient; and a second profile generation unit which uses the calculated Fourier coefficient to calculate one or more of a speed substance, shear transformation, elongational flow, synthetic deformation, and horizontal convergence/divergence, and to generate each quasi-vertical profile.

Description

BACKGROUND OF THE INVENTION Field of the Invention The present invention relates to a device for generating a quasi-vertical profile of a weather radar observation parameter,

The present invention relates to an apparatus, a method and a recording medium for generating a quasi-vertical profile of a weather radar observation parameter, and more particularly, to a method of generating a quasi-vertical profile of a precipitation, The present invention relates to an apparatus, a method and a recording medium for creating a quasi-vertical profile of a weather radar observation parameter.

The precipitation system shows different growth processes depending on the ascending current and convergence / divergence in the clouds, and affects the melting layer altitude, thickness and rainfall intensity. Thus, ascertaining the ascendant currents in the precipitation system can help to study the characteristics of the dual polarization variables due to rainfall growth and development. The vertical structure of rainfall can observe vertical reflectance or vertical velocity components through vertical orientation observations, but there are difficulties due to mechanical or observation strategic limitations. In addition to this, the RHI (Range Height Indicator) observation can be performed in a specific azimuth direction, or the vertical structure can be grasped by utilizing the sectional view of the radar volume file. However, considering the direction of movement of the rainfall system, there is a limit to perform RHI observation in a commercial weather radar. Also, the cross-section of the volume file has a very low vertical resolution, making it difficult to determine the vertical structure of the precipitation system.

Ryzhkov et al. (2016) developed a Quasi-Vertical Profile (QVP) generation technique using azimuthal averaging of single elevation angular radar observations over 20 ° altitude to analyze the vertical structure of precipitation . The analysis using the quasi-vertical profiles of the dual polarization parameters was used to analyze the evolution of various precipitation microfluidics and single / dual polarization radar variables such as precipitation systems and sea ratios (Kaltenboeck et al. 2017) The vertical structure of the wind was not analyzed. Kumjian and Lombardo (2017) attempted to estimate the linear wind field components using the characteristics of the Velocity-Azimuth Display (VAD) curve. However, horizontal convergence / divergence of the snowfall area was analyzed using a low elevation angle of 10 ° altitude, and no analysis was made for a rainfall system with common rainfall and snowfall.

Korean Patent Publication No. 10-2017-0032982 Korean Patent No. 10-1531224

One aspect of the present invention is to calculate the quasi-vertical profile of the single / dual polarized radar variable of the dual polarized radar and to classify the snowfall and rainfall regions using the bright band altitude detected by the reflectivity, And a method of generating a quasi-vertical profile of a weather radar observation parameter capable of calculating a quasi-vertical profile.

The technical problem of the present invention is not limited to the technical problems mentioned above, and other technical problems which are not mentioned can be understood by those skilled in the art from the following description.

An apparatus for generating a quasi-vertical profile of a weather radar observation parameter according to an embodiment of the present invention includes: an altitude angle selecting unit for selecting a altitude angle to generate a quasi-vertical profile; A first profile generator for generating a quasi-vertical profile of the single and dual polarization parameters of the dual polarized radar for a specific azimuth range of a single altitude facet when the observed altitude angles selected by the altitude angle selector are not line speeds; A preprocessing unit for preprocessing a line speed corresponding to the altitude angle selected by the altitude angle selection unit when the altitude angle selected by the altitude angle selection unit is the line speed; A Fourier coefficient calculation unit for calculating a Fourier coefficient by expressing a gaze velocity-azimuth curve generated using the gaze velocity preprocessed by the pre-processing unit as a Fourier series; And a second profile generation unit that generates a respective quasi-vertical profile through calculation of at least one of a velocity component, a shear deformation, an extension deformation, a synthetic deformation, and a horizontal convergence / divergence using the Fourier coefficient calculated by the Fourier coefficient calculation unit .

In one embodiment, the first profile generator includes: an observation parameter selector for selecting at least one of a reflectivity, a differential reflectivity, a differential phase difference, and a cross correlation coefficient; A rainfall region selection unit for selecting a rainfall region; An azimuthal average generator for generating azimuthal averages of the selected radar observation variables in the rainfall area selected from the single altitude angles corresponding to the altitude angles selected by the altitude angle selector; And a variable profile generating unit for generating a quasi-vertical profile for each of at least one of the reflectivity, the differential reflectivity, the differential phase difference, and the cross correlation coefficient using the azimuthal average generated by the azimuthal average generating unit.

In one embodiment, the preprocessing unit performs the pre-processing such that the line-of-sight velocity observed at an arbitrary altitude angle, distance, and azimuth angle of the dual-polarized radar generates a line-speed-velocity folding phenomenon and prevents a discontinuity of the line-velocity- Performs velocity unfolding and removes point echoes caused by observation noise.

In one embodiment, the Fourier coefficient calculator includes a curve generator for generating a gaze velocity-azimuth curve using the gaze velocity preprocessed by the preprocessor; And a coefficient calculating unit for calculating a Fourier coefficient by expressing the line velocity-azimuth curve generated by the curve generating unit in the form of a Fourier series.

In one embodiment, the second profile generation unit may generate a velocity profile for generating a velocity component quasi-vertical profile through east-west, north-north, vertical velocity components and wind direction or wind speed calculation using the Fourier coefficients calculated by the Fourier coefficient calculation unit. A profile generator; A deformation profile generation unit for generating a shear deformation and an elongation quasi-vertical profile using the Fourier coefficients calculated by the Fourier coefficient calculation unit; And a horizontal convergence / divergence profile generation unit for generating a horizontal convergence / divergence quasi-vertical profile using the Fourier coefficients calculated by the Fourier coefficient calculation unit.

In one embodiment, the deformation profile generator calculates shear deformation and elongation deformation through east-west and north-south components calculated using the relationship between each Fourier coefficient and linear wind field components, A deformation calculating unit for calculating a synthetic deformation appearing as a sum; And a first generating unit for generating a quasi-vertical profile of shear deformation, elongation deformation, and synthetic deformation through shear deformation, elongation deformation, and synthetic deformation calculated by the deformation calculating unit.

In one embodiment, the horizontal convergence / divergence profile generator includes: a precipitation type classifier for classifying whether a rainfall area or a snowfall area is determined using a bright band quality index calculated by reflectivity; A falling rate calculator for calculating a falling rate according to the rainfall area or the snowfall area classified by the precipitation type classifying part; And a second generator for generating a horizontal convergence / divergence quasi-vertical profile by calculating the horizontal convergence / divergence for the snowfall or rainfall area by applying the calculated fall rate to the fall rate calculation unit.

In one embodiment, when the entire volume of the radar beam is included in the bright band region, the lower part of the lowest altitude may be defined as a rainfall region, and the uppermost region as the highest altitude may be classified as a snowfall region .

In one embodiment, the horizontal convergence / divergence profile generator may calculate the horizontal convergence / divergence using a calculation formula that takes into account the falling rate calculated using the reflectivity in the case of a rainfall area, The horizontal convergence / divergence can be calculated.

A method of generating a quasi-vertical profile of a weather radar observation parameter according to another embodiment of the present invention includes: selecting a height angle to generate a quasi-vertical profile; Generating a quasi-vertical profile of the single and dual polarization parameters of the dual polarized radar for a specific azimuth range of a single elevation facet if the observed elevation angle of the selected elevation angle is not a line of sight velocity; Preprocessing the gaze speed according to the selected altitude angle when the observation variable of the selected altitude angle is the gaze speed; Calculating a Fourier coefficient by expressing a line velocity-azimuth curve generated using the preprocessed line-of-sight velocity in the form of a Fourier series; And generating each quasi-vertical profile through calculation of at least one of a velocity component, shear deformation, elongation deformation, synthetic deformation, and horizontal convergence / divergence using the calculated Fourier coefficients.

In one embodiment, generating a quasi-vertical profile of the single and dual polarization parameters comprises: selecting at least one of a reflectivity, a differential reflectivity, a differential phase difference, and a cross correlation coefficient; Selecting a rainfall area; Generating an azimuthal average of the selected radar observation variables in the rainfall area selected from a single elevation facet according to the selected elevation angle; And generating a quasi-vertical profile for each of at least one of the reflectivity, the differential reflectivity, the differential phase difference, and the cross correlation coefficient using the generated azimuthal average.

In one embodiment, the preprocessing step may be performed in such a way that the observer velocity observed at any elevation angle, distance and azimuth angle of the dual polarized radar may be such that a visual velocity folding phenomenon occurs and a discontinuity of the visual velocity- It is possible to perform eye velocity unfolding and remove the point echo caused by the observation noise.

In one embodiment, the step of calculating the Fourier coefficients comprises: generating a gaze velocity-azimuth curve using the preprocessed gaze velocity; And generating the Fourier coefficient by expressing the generated gaze speed-azimuth curve in a Fourier series form.

In one embodiment, the step of generating each quasi-vertical profile comprises generating a quasi-vertical profile of velocity components through east-west, north-north, vertical velocity components and wind direction or wind velocity calculation using the calculated Fourier coefficients, ; Generating a quasi-vertical profile of shear deformation, elongation deformation, and synthetic deformation using the calculated Fourier coefficients; And generating a horizontal convergence / divergence quasi-vertical profile using the calculated Fourier coefficients.

In one embodiment, generating the quasi-vertical profiles of the shear strain, stretch strain, and synthetic strain may comprise shearing strain through the east-west and north-south components calculated using the relationship between each Fourier coefficient and linear wind field components And calculating a synthetic strain, which is expressed by a sum of an elongation strain and a shear strain; And generating a shear strain, an elongation strain and a quasi-vertical profile of the synthetic strain through the calculated shear strain, elongation strain and synthetic strain.

In one embodiment, the step of generating the horizontal convergence / divergence quasi-vertical profile may include: identifying a rain zone or a snow zone using a light band quality index calculated with reflectivity; Calculating a falling speed according to the divided rainfall area or the snowfall area; And generating the horizontal convergence / divergence quasi- vertical profile by calculating the horizontal convergence / divergence for the snow area or the rain area by applying the calculated drop rate.

In one embodiment, the step of classifying whether the rainfall area or the snowfall area includes all of the volume of the radar beam is included in the bright zone, the lower area of the lowest altitude is defined as a rainfall area, Can be classified into snow areas.

In one embodiment, the step of generating the horizontal convergence / divergence quasi-vertical profile may include calculating horizontal convergence / divergence using a calculation formula that takes into account the falling velocity calculated using reflectivity in the case of a rainfall region, The horizontal convergence / divergence can be calculated through a formula that does not consider the velocity.

A computer program for performing a method of generating a quasi-vertical profile of a weather radar observation parameter is recorded in a computer-readable recording medium according to an embodiment of the present invention for realizing the above-described another embodiment of the present invention.

According to one aspect of the present invention, the vertical structure of the precipitation can be explained using the dual polarization observation variable and the gaze velocity, and the growth and development process of the precipitation is analyzed using the quasi-vertical profile data expressed in time series The utilization of the weather radar can be increased.

1 is a diagram showing a schematic configuration of an apparatus for generating a quasi-vertical profile of a weather radar observation parameter according to an embodiment of the present invention.
2 is a view for explaining the first profile generator shown in FIG.
3 is a diagram for explaining the Fourier coefficient calculation unit shown in Fig.
4 is a view for explaining the second profile generator shown in FIG.
5 is a flowchart illustrating a method of generating a quasi-vertical profile of a weather radar observation parameter according to another embodiment of the present invention.
6 is a diagram showing the principle of generating a quasi-vertical profile using a single altitude angle data.
FIG. 7 is a flowchart for generating a quasi-vertical profile using a single altitude observation data.
8 is a view showing a PPI image of a dual polarization parameter of a test bed radar.
9 is a diagram showing a quasi-vertical profile calculated using dual polarization data of a test bed radar.
10 is a flow chart illustrating generation of a time series quasi-vertical profile image.
11 is a diagram showing a quasi-vertical profile time series sample image of the reflectivity, differential reflectance, cross correlation coefficient, and differential phase difference of the test bed radar.
12 is a view for explaining quality information according to the relative positions of bright bands.
Fig. 13 is a view for explaining the time series of the reflectivity of the test bed radar, the quasi-vertical profile of the cross correlation coefficient, and the light band height.
Figure 14 is a graph illustrating an example and corrected DSD of data observed with 2DVD.
FIG. 15 is a graph showing the scattering degree of the reflectivity-line-of-sight velocity and the average line-of-sight velocity value calculated by the two-dimensional optical system.
16 is a view for explaining a time series of the quasi-vertical profile of the reflectivity and the falling rate quasi-vertical profile calculated using the quasi-vertical profile.
Figure 17 is a diagram showing the reflectivity, differential reflectivity, cross correlation coefficient, vertical velocity component, falling velocity, and quasi-vertical profile of horizontal convergence divergence observed with the testbed dual polarized radar.
FIG. 18 is a view comparing the observed value of the vertical wind gust equipment with the vertical component of the estimated linear wind field in the case of FIG. 17; FIG.

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 showing a schematic configuration of an apparatus for generating a quasi-vertical profile of a weather radar observation parameter according to an embodiment of the present invention.

The apparatus for generating a quasi-vertical profile of a weather radar observation parameter according to an exemplary embodiment of the present invention includes an altitude angle selecting unit 100, a first profile generating unit 200, a preprocessing unit 300, A calculation unit 400 and a second profile generation unit 500.

The altitude angle selection unit 100 selects the altitude angle at which the quasi-vertical profile is to be generated.

The first profile generating unit 200 generates a first profile when the observation angle of the elevation angle selected by the elevation angle selecting unit 100 is not the gaze velocity (i.e., at least one of the reflectance, differential reflectance, differential phase difference, Variable) Creates a quasi-vertical profile of the single and dual polarization parameters of a dual polarized radar for a specific azimuthal range of a single elevation facet.

The preprocessing unit 300 preprocesses the gaze speed according to the selected altitude angle when the altitude angle observation parameter selected by the altitude angle selection unit 100 is the gaze speed.

In one embodiment, the preprocessing unit 300 may prevent the observer's eye velocity observed at arbitrary elevation angles, distances, and azimuth angles of the dual-polarized radar from occurring to cause discontinuities in the gaze velocity-azimuth curve due to eye velocity folding And the point echo caused by the observation noise can be removed.

The Fourier coefficient calculation unit 400 calculates the Fourier coefficient by expressing the line velocity-azimuth curve generated using the line speed pre-processed by the preprocessing unit 300 in the form of Fourier series.

The second profile generation unit 500 generates the second profile by using the Fourier coefficient calculated by the Fourier coefficient calculation unit 400 and calculates the second profile by using at least one of the velocity component, the shear deformation, the extension deformation, Create a quasi-vertical profile.

2 is a view for explaining the first profile generator shown in FIG.

2, the first profile generator 200 includes an observation parameter selector 210, a rain area selector 220, an azimuth averager 230, and a variable-by-variable profile generator 240. .

The observation parameter selector 210 selects at least one of the reflectivity, the differential reflectivity, the differential phase difference, and the cross correlation coefficient.

The rainfall area selection unit 220 selects a rainfall area.

The azimuth average generator 230 generates azimuth averages of selected radar observation variables in a selected rainfall area on a single altitude facet according to the altitude selected by the altitude selector 100. [

The variable-specific profile generating unit 240 generates a quasi-vertical profile for each of at least one of the reflectivity, the differential reflectance, the differential phase difference, and the cross correlation coefficient using the azimuthal average generated by the azimuthal average generator 230 do.

3 is a diagram for explaining the Fourier coefficient calculation unit shown in Fig.

Referring to FIG. 3, the Fourier coefficient calculation unit 400 includes a curve generation unit 410 and a coefficient calculation unit 420.

The curve generating unit 410 generates a gaze velocity-azimuth curve using the gaze velocity preprocessed by the preprocessing unit 300.

The coefficient calculating unit 420 calculates the Fourier coefficient by expressing the line velocity-azimuth curve generated by the curve generating unit 410 in the form of a Fourier series.

4 is a view for explaining the second profile generator shown in FIG.

Referring to FIG. 4, the second profile generator 500 includes a velocity component profile generator 510, a deformation profile generator 520, and a horizontal convergence / divergence profile generator 530.

The velocity component profile generation unit 510 generates a velocity component quasi-vertical profile by using the Fourier coefficients calculated by the Fourier coefficient calculation unit 400 and calculating the east-west, north-north, vertical velocity components, and wind direction or wind velocity.

The deformation profile generating unit 520 generates the shear deformation and the elongation quasi-vertical profile using the Fourier coefficients calculated by the Fourier coefficient calculating unit 400. [

In one embodiment, the deformation profile generating unit 520 may include a deformation calculating unit 521 and a first generating unit 522. [

The strain calculation unit 521 calculates the shear strain and the elongation strain through the east-west component and the north-south component calculated using the relationship between the respective Fourier coefficients and the linear wind field components, Calculate the composite strain.

The first generating unit 522 generates the shear deformation, the elongation deformation, and the quasi-vertical profile of the synthetic deformation through the shear deformation, the elongation deformation, and the synthetic deformation calculated by the deformation calculation unit 521.

The horizontal convergence / divergence profile generation unit 530 generates a horizontal convergence / divergence quasi-vertical profile using the Fourier coefficients calculated by the Fourier coefficient calculation unit 400. [

In one embodiment, the horizontal convergence / divergence profile generation unit 530 may include a precipitation type classification unit 531, a falling rate calculation unit 532, and a second generation unit 533.

The precipitation type classifying unit 531 distinguishes whether rainfall or snowfall is caused by using a bright band quality index calculated by reflectivity.

In one embodiment, when the entire volume of the radar beam is included in the bright band region, the lower region of the lowest altitude is set as a rainfall region, and the uppermost region as the highest altitude is set as a snowfall region .

The falling rate calculation section 532 calculates the falling rate in accordance with the rainfall region or the snowfall region classified by the precipitation type classification section 531. [

The second generating unit 533 generates the horizontal convergence / divergence quasi-vertical profile by calculating the horizontal convergence / divergence for the snowfall area or the rainfall area by applying the calculated fall rate to the fall rate calculation unit 532. [

The horizontal convergence / divergence profile generation unit 530 having the above-described configuration calculates the horizontal convergence / divergence through a calculation formula that takes into account the falling speed calculated using the reflectivity in the case of the rainfall region, The horizontal convergence / divergence can be calculated through an equation which is not considered.

5 is a flowchart illustrating a method of generating a quasi-vertical profile of a weather radar observation parameter according to another embodiment of the present invention.

Referring to FIG. 5, a method of creating a quasi-vertical profile of a weather radar observation parameter first selects an elevation angle to generate a quasi-vertical profile (S510).

If at least one of the reflectivity, differential reflectivity, differential phase difference, and cross correlation coefficient is a radar observation variable (No in S520), the single altitude A quasi-vertical profile of the single and dual polarization parameters of the dual polarized radar for a particular azimuthal range of facets is generated (S530).

FIG. 6 is a diagram illustrating the principle of generating a quasi-vertical profile using a single altitude angular data, which is defined as an azimuthal average of single / dual polarized radar data for a specific azimuth range at a single altitude facet. The average of the azimuth directions has the same distance from the radar at all azimuths and can be converted to a higher altitude. Thus, a vertical profile of variables according to altitude can be generated. The azimuthally averaged value when the averaged rainfall system is horizontally homogeneous can represent the corresponding rainfall characteristics.

In the creation of the quasi-vertical profile, the averaging of the azimuthal directions reduces the statistical random error implicated in the radar observations, especially when trying to calculate the vertical profile of the back-scattering differential phase shift , And to reduce the noise of the differential phase shift (? _DP ) in the melting layer. Using the quasi-vertical profile technique, the temporal variation of the vertical structure of the cloud and precipitation system can be analyzed from double polarized radar data.

The step S530 of generating the quasi-vertical profile of the single and double polarization parameters may be performed by selecting at least one of the reflectivity, the differential reflectivity, the differential phase difference, and the cross correlation coefficient, selecting the rainfall region, The azimuthal average of the selected radar observation variables in the selected rainfall area on the single altitude facet according to the selected altitude angle in step S510 described above.

FIG. 7 is a flowchart for generating a quasi-vertical profile using observation data of reflectance, differential reflectance, differential phase difference, and cross correlation coefficient. 7, the first select a particular elevation in the radar volume file (S710) after a selected height using the respective single and double polarization-variable azimuth the texture threshold (S720) of the (radial texture) and ρ _hv of And only the rain echo region from which the non-vapor echo such as the terrain echo and the chaff echo is removed is extracted (S730). However, it is only applied to the radar range of 2km or less in order to minimize the quality control of the low-level data and the loss of data above the fusion layer. When the quasi-vertical profile is applied to winter season, it is necessary to lower the threshold value of ρ _hv or to disable the rain area selection function in the rain area selection. In order to eliminate the influence of the azimuth generated by the beam shielding, a radar beam shielding result (S750) based on a digital elevation model (DEM) (S740) ) Using only the azimuth angle (Yes in S760) creates a quasi-vertical profile. In order to minimize the influence due to echoes and noise around the radar, only the azimuthal average is performed for each distance (S780) when the number of effective radar bins is more than the threshold value (72 or more) (Yes in S770). As a threshold value of the cross correlation coefficient, 0.7 is used to generate a quasi-vertical profile with only 0.7 or more data (S790).

FIG. 8 is a PPI image of a dual polarization parameter of an altitude of 13.3 ° at an elevation angle of 2100 KST test bed radar on June 25, 2015, and FIG. 9 is a PPI image of dual polarization data of altitude angles of 6.22 °, 9.12 °, 13.27 °, and 19.06 ° Lt; / RTI > is a quasi-vertical profile calculated using the following equation.

Figure 9 clearly shows the signal of the fusing layer at an altitude of 4.5 km in the quasi-vertical profile at all elevation angles. The reflectivity and differential reflectivity were higher near the altitude of 4.5km than the surrounding altitude, and the cross correlation coefficient was relatively low (0.95). However, as the elevation angle increases, the signal of the bright band becomes narrower and clearer due to the decrease of the beam width increasing effect. Comparing the PPI image at the elevation angle of 13.27 ° in FIG. 8 with the quasi-vertical profile image in the elevation angle of 13.27 ° in FIG. 9, the elevation of the melting layer is not clearly revealed in the PPI image of 13.27 °, The signal of the layer became clear. The comparison shows that the quasi-vertical profile is more usable than the PPI of altitude data.

Next, the technique of generating the time series image of the quasi - vertical profiles of each altitude and observation variables (reflectivity, differential reflectance, cross correlation coefficient, differential phase difference, velocity component, shear deformation, elongation deformation, synthetic deformation, horizontal convergence / divergence) Explain.

10 is a flow chart illustrating generation of a time-series image of a quasi-vertical profile.

Referring to FIG. 10, in the generation of the time-series image of the quasi-vertical profile, the configuration file such as altitude angle, variable type, start time, end time, and the like is read first (S1010).

)하게 되면 입력 디렉토리(Quasi-vertical profile(

))를 탐색하게 된다(S1030).After reading the configuration file in step S1010, the memory is allocated (step S1020)

), The input directory (Quasi-vertical profile

) (S1030).

의 조건에 해당하는 경우에 한하여(S1040의 Yes의 경우) 개별 준-연직프로파일을 읽어 들이게 된다(S1050).If the input directory input in step S1030 is found,

(S1040: YES), the individual quasi-vertical profile is read (S1050).

After reading the individual quasi-vertical profiles in step S1050, a time series of quasi-vertical profiles is created in the memory (S1060), and a time series of quasi-vertical profiles is generated (S1070).

Figure 12 shows a quasi-vertical profile time series image of reflectivity, differential reflectance, cross correlation coefficient, and differential phase difference of 13.27 ° at Yongin test bed radar altitude of 0000KST ~ July 12, 2015, 2355KST, July 12, 2015. The quasi - vertical profile time series was linearly interpolated to the surrounding values by weighting in inverse proportion to the time interval of the data generated based on the observation time interval of 5 minutes.

Hereinafter, generation of a quasi-vertical profile of a linear wind field component using the gaze velocity will be described.

The radar altitude, the observed line speed at a certain distance, can be expressed as a velocity azimuthal display (VAD) curve. The VAD curve in the uniform wind field has a complete sinusoidal shape, but the linear wind field including the advection in the north, south, south, and south directions can be expressed as the Fourier series.

However, because radar observing strategy exceeds the maximum observable sight speed and oblique velocity of the VAD curve occurs due to the visual velocity folding phenomenon at the observation, it is necessary to perform the unfolding of the visual velocity and remove the point echo caused by the observation noise You must give.

Thus, in step S510, when the observing variable at any elevation angle is the gaze speed (Yes in S520), the gaze speed unfolding is performed and the preprocessing for removing the point echo caused by the observation noise is performed (S540).

The VAD curve generated from the gaze velocity data preprocessed in step S540 is expressed as a Fourier series to calculate the Fourier coefficient.

Accordingly, a gaze velocity-azimuth curve is generated using the gaze velocity preprocessed in step S540, and then expressed as a Fourier series to calculate a Fourier coefficient (S550).

In one embodiment, calculating the Fourier coefficient (S550) may include generating a gaze velocity-azimuth curve using the preprocessed gaze velocity, and then expressing the generated gaze velocity-azimuth curve as a Fourier series to obtain a Fourier coefficient Can be calculated.

This can be used to calculate linear wind field components. At this time, horizontal convergence / divergence among the visual velocity components is influenced by the falling speed of the strong importer, and there is a great difference in the falling speed of rainfall and snowfall. Therefore, the horizontal convergence / divergence was calculated by separating the rainfall and snowfall regions using the bright band quality index calculated by the reflectivity.

The quasi-vertical profiles are generated by calculating at least one of the velocity component, the shear deformation, the stretch deformation, the synthetic deformation, and the horizontal convergence / divergence using the Fourier coefficients calculated in the step S550 described above (S560).

In one embodiment, generating a quasi-vertical profile (S560) includes generating a quasi-vertical profile of velocity components through east-west, north-north, vertical velocity components and wind direction or wind velocity calculation using the calculated Fourier coefficients, The calculated Fourier coefficients can be used to generate a quasi-vertical profile of shear deformation, stretch deformation, and synthetic deformation, or to generate a horizontal convergence / divergence quasi- vertical profile using the calculated Fourier coefficients.

The generation of the quasi-vertical profile of the shear strain, elongation strain and synthetic strain described above is calculated by calculating the shear strain and elongation strain through the east-west and north-south components calculated using the relationship between each Fourier coefficient and linear wind field components After that, synthetic strains appearing as the sum of the elongation and shear strains can be calculated and the shear strains, stretch strains and synthetic quasi-vertical profiles of the synthetic strains can be generated through computed shear strains, stretch strains and synthetic strains.

Hereinafter, the calculation of the linear wind field using the gaze velocity-azimuth curve will be described.

)과 남북성분(

)은 수학식 1과 같이 정의될 수 있다.East-West Composition of Linear Wind Fields

) And the north-south component

) Can be defined as Equation (1).

), 거리 및 방위각(

)에서 관측된 레이더 시선속도(

)는 수학식 2와 같이 선형바람장의 성분(

)으로 표현이 가능하다. Any radar altitude angle (

), Distance and azimuth (

) Radar line-of-sight velocity (

) Is a linear wind field component (

) Can be expressed as.

은 일정한 고도각(

)에서 방위각(

)에 따라 변하는 수학식 3의 2차 푸리에 급수로 표현할 수 있다.Expressed as a component of a linear wind field

Is a constant altitude angle

) To the azimuth angle

The second order Fourier series of Equation (3) which varies according to the second order Fourier series.

Each Fourier coefficient can be expressed by Equation (4). The Fourier coefficients can be calculated by regression analysis of observed line speeds per azimuth angle.

성분을 계산할 수 있으며, 이를 이용한 바람장의 신장변형(

) 및 시어변형(

), 신장변형과 시어변형의 합으로 나타나는 합성변형을 수학식 5와 같이 계산할 수 있다.Using the relationship between each Fourier coefficient and linear wind field components,

And the elongation of the wind field

) And shear strain

), The composite strain represented by the sum of the elongation strain and the shear strain can be calculated as shown in Equation (5).

)과 연직 속도성분(

)의 합으로 나타난다.Since the 360 degree azimuthal direction average of the periodic function in the Fourier series is 0, the azimuthal average of the gaze speed is expressed by Equation 6 as horizontal convergence / divergence

) And the vertical velocity component (

).

) 으로 나타낼 수 있다. When all gaze velocity data exist for the azimuth of the elevation angle at homogeneous atmospheric conditions, the average horizontal convergence / divergence is the average of the gaze velocity

).

로부터 수평 수렴/발산을 계산하였다. 연직속도성분(

)은 연직공기속도(

)와 강수입자 낙하속도(

)의 합으로 나타낼 수 있다.

는 평균을 통해 무시 가능하여,

값은

가 우세한 값을 가진다. 또한, 강설영역에 대하여 고도각 10° 및 강설입자의 낙하속도를 고려했을 때 관측된 평균 시선속도에서

의 기여도는 약 0.1ms^-1 ~ 0.2ms^-1로 작으므로,

으로 가정 할 수 있으며, 강설영역에 대한 수평 수렴/발산은 수학식 7로 계산 할 수 있다.In the present invention, when there is radar data above a certain threshold value (90% of the total azimuth angle), the Fourier coefficient

To calculate the horizontal convergence / divergence. Vertical velocity component (

) Is the vertical air velocity (

) And river importer falling rate (

). ≪ / RTI >

Can be neglected through an average,

The value is

Has a dominant value. In addition, considering the elevation angle of 10 ° and the falling velocity of the snow particles with respect to the snowfall area,

Lt; ^-1 > to 0.2ms < ^-1 >

, And horizontal convergence / divergence with respect to the snowfall region can be calculated by Equation (7).

)가 1ms^-1 ∼10ms^-1로 무시할 수 없으므로 관측된 반사도(

)-낙하속도(

) 관계식으로 추정된 낙하속도(

)를 적용하여 강우영역에 대한 수평 수렴/발산을 수학식 8과 같이 계산하였다.However, the falling velocity of rainfall particles

) Can not be ignored in the range of ¹ ms ^{-1 to} 10 ms ^-1,

) - Dropping speed (

) Falling velocity estimated by the relational expression (

) Was applied to calculate the horizontal convergence / divergence for the rainfall area as shown in equation (8).

Accordingly, the generation of the horizontal convergence / divergence quasi-vertical profile is performed by calculating the horizontal convergence / divergence using Equation 8 considering the falling speed calculated using the reflectivity in the case of the rainfall region, The horizontal convergence / divergence can be calculated by Equation (7).

Next, we explain the classification of snowfall and precipitation using bright band quality information in horizontal convergence / divergence quasi-vertical profile generation.

To generate the horizontal convergence / divergence quasi-vertical profile described above, a rainfall zone or a snowfall zone is classified using a light band quality index calculated by reflectivity, a fall velocity is calculated according to a divided rainfall zone or a snowfall zone The horizontal convergence / divergence quasi-vertical profile can be generated by calculating the horizontal convergence / divergence for the snowfall or rainfall area by applying the calculated fall rate.

By using the vertical profile information of the radar reflectivity, it is possible to distinguish the melting layer (light band), and it is possible to distinguish the rain zone under the light zone and the snow zone on the bright zone. It is possible to distinguish snowfall and rainfall areas by using a bright band index (BI) including the light band quality information of each radar bin.

Referring to FIG. 12, BI is expressed as 1 if the bin of the radar is not included in the bright band region below the bright band height, 0 if the bin is partially included, or 0 if the bin is included in the bright band region, It is expressed as 0 to 0.5 if it is included in altitude, or 0.5 if it is not included.

In one embodiment, if the entire volume of the radar beam is included in the bright band region, the lower region of the lowest altitude is defined as a rainfall region, and the uppermost region of the highest altitude is defined as a snowfall region .

) 아래를 강우영역, 가장 높은 고도(

) 위를 강설영역으로 구분하여 수평 수렴발산을 계산하였다.In the present invention, when the entire volume of the radar beam is included in the bright band region (BI = 0), the lowest altitude

) Below the rainfall area, the highest altitude (

) Were divided into snow areas and horizontal convergence divergence was calculated.

)와 하단부(

)를 탐지했을 경우 하층 강수성장이나 밝은띠의 반사도 감소로 인해 밝은띠 고도의 급격한 변화를 방지하기 위하여 이전시간 밝은띠 고도를 이용한 연속성 검사 수행하였다.By using BI,

) And the lower end

), The continuity test using the previous time light band height was performed to prevent sudden change of the light band height due to lower precipitation growth and decrease of reflection of the light band.

)와 이전 시간(t-1)의 밝은띠 고도(

)를 비교하여 차이가 1km이하일 경우 탐지된 밝은띠 고도를 사용(

)하였으며, 고도차이가 1km 이상일 경우 이전 시간의 밝은띠 고도(

)와 비교하여 차이가 적은 고도 사용하였다. BI를 이용해 밝은띠를 탐지하지 못한 경우 이전 시간에 기록된 밝은띠 정보를 사용하며, 이전 시간에 기록된 밝은띠 정보가 하루 이상 차이나는 경우 기후학적 밝은띠 정보를 사용하였다.The bright band height detected at the time (t)

) And the bright band height of the previous time (t-1)

) And use the detected bright band altitude if the difference is less than 1 km (

), And when the altitude difference is more than 1km,

) Were used. If bright bands can not be detected using BI, bright band information recorded at the previous time is used. If bright band information recorded at the previous time is different by one day or more, climatological bright band information is used.

Fig. 13 is a quasi-vertical profile time series of the July 4, 2016 reflection (Fig. 13A) and the cross correlation coefficient (Fig. 13B) of the acceptance test bed radar. A bright band with a high reflectivity and a cross correlation coefficient of less than 0.96 appeared at about 5 km. In the BI of the same case (Fig. 13c, d), a bright band around 5km was detected. However, BI decreased the light band height to about 2.5 km at about 14 o'clock (Fig. 13C). (Fig. 13d, + shape) for the time when no altitude discontinuity and bright band were detected (Fig. 13d, +), and a climatological bright band height was used before 06 o'clock We detected successively bright band altitudes by using bright band altitude at the previous time in the vicinity of the lower bright band altitude near the city.

In the following, the estimation of the reflectivity-dropping velocity relation using the right-hand size distribution data is explained.

)-낙하속도(

) 관계식은 대구 및 보성지역에서 관측된 경북대학교 이차원광학우적계(2D-video disdrometer; 2DVD)의 우적크기분포(Drop size distribution; DSD)자료를 사용하였으며, 계산한

및

의 선형 회귀분석을 통해 도출하였다. DSD로부터 레이더로 관측된

를 계산하기 위하여 관측된 자료는 수학식 9의 직경(D)-강우입자 낙하속도(

) 관계식을 이용하여 전처리 과정을 수행하였으며, 총 26,326개의 1분 DSD를 관계식 산출에 사용하였다. 2DVD 자료 사용 시 큰 입자의 그림자로 인해 작은 입자가 관측 되지 않는 문제로 인한 작은 입자의 과소추정을 보완하기 위하여 1분 DSD 자료에서 0.7mm 이하 입자에 대하여 동일한 강우강도를 가지는 Marshall-Palmer분포(M-P 분포)로 추정된 DSD를 사용하였다.The reflectivity used in the estimation (

) - Dropping speed (

) Relational data was obtained by using the drop size distribution (DSD) data of 2D-video disdrometer (2DVD) of Kyungpook National University observed in Daegu and Boseong area.

And

The results are summarized as follows. Observed as radar from DSD

(D) of the equation (9) - the falling velocity of the precipitation particles

), And a total of 26,326 1 minute DSDs were used for the calculation of the relational expression. In order to compensate for the underestimation of small particles due to the problem that small particles are not observed due to large particle shadows when using 2DVD data, the Marshall-Palmer distribution with the same rainfall intensity for particles less than 0.7 mm in 1 minute DSD data (MP Distribution) was used.

이고

이다.here,

ego

to be.

In FIG. 14, the dashed line represents an example of the data observed by 2DVD, and each point is a DSD in which small particles are corrected using an M-P distribution. Each observed 1 minute DSD corrected the data (3 channels) below 0.7mm as shown below.

를 산출하였다. 산출시 입자 크기에 따른 낙하속도 관계식은 Atlas and Ulbrich의 관계식(

)을 사용하였다.Using the quality control and small particle size corrected population size distribution data,

Respectively. The falling velocity dependence of the particle size at the time of calculation is given by the relation of Atlas and Ulbrich

) Were used.

형태의 시선속도-반사도 관계식을 산출하였으며, 반사도는 선형규모(

)로 변환하여 사용하였다. 도 15의 선형회귀분석을 통해 a=2.54, b=0.10인

관계식을 산출하였다.Using the preprocessed DSD, the T-matrix scattering simulation was used to calculate the reflectivity. At this time, the wavelength was 2.875 GHz, the altitude angle was 0 °, and Thurai et al. (2007). Linear regression analysis was performed using the average Doppler velocities for every 1 dB of radar reflectivity.

The visual velocity - reflectivity relation of the form was calculated, and the reflectivity was linear scale

). The linear regression analysis of FIG. 15 shows that a = 2.54, b = 0.10

A relational expression was calculated.

관계식과 비교했을 때 Joss and Waldvogel (1970)에 제시된 a=2.60, b=0.107과 유사한 값을 가졌으나 Steiner (1991)과 비교했을 때 동일한 반사도에 대하여

를 작게 추정하였다.Existing

Compared with the relationship, it has similar values as a = 2.60 and b = 0.107 in Joss and Waldvogel (1970), but compared to Steiner (1991)

Respectively.

위 강설영역에서의 낙하속도는 Lee et al. (2001)에서 제시된

을 사용하여 낙하속도를 계산하였다. 밝은띠 영역에서 낙하속도는 밝은띠 고도 하단부에서 강우영역에 대한

관계식으로 산출된 낙하속도와 상단부에서 강설영역에 대한

관계식으로 산출된 낙하속도 값을 이용하여 선형 내삽하였다.

The rate of fall in the snowfall region is shown in Lee et al. (2001)

Was used to calculate the falling rate. The drop velocity in the bright zone is the light band height,

The falling rate calculated from the relation and the

Linear interpolation was performed using the falling velocity values calculated by the relational expression.

Figure 16 is a time series of the quasi-vertical profile of the observed reflectivity and the drop rate quasi-vertical profile calculated using it from May 15-16, 2016. In Fig. 16, " + " represents the upper end and the lower end of the light band. The drop rate under the light band height is mainly in the range of 3 ~ 8ms ^-1 , and the drop rate on the light band height is 0.3 ~ 1ms ^-1 , which is distributed according to the reflectance intensity. The falling velocity of the bright band region gradually increased from the upper end of the light band to the lower end.

Finally, the result of generating the quasi-vertical profile for the case of May 16, 2016 according to the present invention will be described.

Figure 17 shows the reflectivity, differential reflectivity, cross correlation coefficient, vertical velocity component, falling velocity and quasi-vertical profile of horizontal convergence / divergence observed with an acceptance testbed dual polarized radar. The bright bands detected by the vertical reflectivity profile were at an altitude of about 4 to 5 km and bright bands appeared at the same positions in the differential reflectivity (FIG. 17B) and the quasi-vertical profile of the cross correlation coefficient (FIG. From 00KST on May 16, 2016, the light band reflectivity has weakened and the light band height has decreased since 01KST.

The wind speed from 1800 KST to the cold frontal line in the quasi-vertical profile of the vertical velocity component and horizontal wind component calculated from the Velocity-Azimuth Display (VAD) curve rapidly changed from southwest wind to northwest wind (Fig. 17d). Generally, when two air ponds with different properties are encountered on the front surface, a rising air current may be generated. The upward convergence (blue in Fig. 17F) and the divergence in the upper layer (red in Fig. 17F) along the front surface were observed, and the upward airflow of the front surface was observed in the quasi-vertical profile of horizontal convergence / divergence.

로부터 산출된

의 분포도이고, 도 18(b)는 2016년 5월 15일부터 1일까지의

와

이다.FIG. 18 is a view comparing the observed value of the vertical wind gust equipment with the vertical component of the estimated linear wind field in the case of FIG. 17; FIG. Figure 18 (a) shows the wind profile calculated from QVP and

From the calculated

FIG. 18 (b) shows a distribution chart of the period from May 15 to 1, 2016

Wow

to be.

)는 입자의 낙하속도(

)와 연직 공기속도(

)의 합으로 관측되며, QVP에서 산출된 연직속도 성분 중 주어진 고도에서 수평/발산을 무시(

)한

, 연직 공기속도를 무시한 반사도로 추정된 　

와 비교하였다. 수평/발산을 무시했을 경우

의 표준편차를 가졌으며,

와 QVP로 산출된

를 비교했을 때 표준편차가

로 낮아졌다.Referring to Figure 18, the vertical Doppler velocity

) Is the falling velocity of the particles (

) And vertical air velocity (

) And ignoring the horizontal / divergence at a given elevation of the vertical velocity components calculated from the QVP (

)One

, Estimated by the reflectivity ignoring the vertical air velocity

. Ignoring horizontal / divergence

, ≪ / RTI >

And QVP

The standard deviation is

Respectively.

Such a quasi-vertical profile generation method of the weather radar observation parameters may be implemented in an application or implemented in the form of program instructions that can be executed through various computer components and recorded in 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 CDROMs and DVDs, magneto-optical media such as floptical disks, , 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.

It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the present invention as defined by the following claims. You will understand.

According to the present invention, it is possible to calculate the quasi-vertical profiles of the radar observation variables and the linear wind field components by using the average distance and azimuth angle-azimuth curve in the azimuthal direction with the same distance in the specific radar altitude data.

Accordingly, the present invention can be applied and applied to the fields of weather, fire prevention, hydrometeorological and aeronautical weather, and the analysis method of the precipitation vertical structure using the quasi-vertical profile is related to the interest of the weather agency and the disaster prevention agency Is highly marketable, and related private institutions are also highly interested in the technology, which can provide a promising business.

100: altitude angle selection unit 200: first profile generation unit
210: observation parameter selection unit 220: rainfall area selection unit
230: azimuthal average generating unit 240: profile generating unit for each variable
300: Pretreatment performing unit 400: Fourier coefficient calculating unit
410: curve generation unit 420: coefficient calculation unit
500: second profile generator 510: velocity component profile generator
520: deformation profile generating unit 521: deformation calculating unit
522: first generating unit 530: horizontal convergence /

Claims (19)

An altitude angle selection unit for selecting altitude angles to generate a quasi-vertical profile;
A first profile generator for generating a quasi-vertical profile of the single and dual polarization parameters of the dual polarized radar for a specific azimuth range of a single altitude facet when the observed altitude angles selected by the altitude angle selector are not line speeds;
A preprocessing unit for preprocessing a line speed corresponding to the altitude angle selected by the altitude angle selection unit when the altitude angle selected by the altitude angle selection unit is the line speed;
A Fourier coefficient calculation unit for calculating a Fourier coefficient by expressing a gaze velocity-azimuth curve generated using the gaze velocity preprocessed by the pre-processing unit as a Fourier series; And
A second profile generation unit that generates respective quasi-vertical profiles by calculating at least one of a velocity component, a shear deformation, an elongation deformation, a synthetic deformation, and a horizontal convergence / divergence using Fourier coefficients calculated by the Fourier coefficient calculation unit A device for generating a quasi-vertical profile of a meteorological radar observing variable comprising:
The apparatus of claim 1, wherein the first profile generator comprises:
An observation parameter selection unit for selecting at least one of radar observation variables, a reflection degree, a differential reflectivity, a differential phase difference, and a cross correlation coefficient;
A rainfall region selection unit for selecting a rainfall region;
An azimuthal average generator for generating azimuthal averages of the selected radar observation variables in the rainfall area selected from the single altitude angles corresponding to the altitude angles selected by the altitude angle selector; And
And a variable profile generating unit for generating a quasi-vertical profile for each of at least one of the reflectivity, the differential reflectivity, the differential phase difference, and the cross correlation coefficient using the azimuthal average generated by the azimuthal average generator. Apparatus for generating quasi - vertical profiles of weather radar observational variables.
The image processing apparatus according to claim 1,
In order to prevent the discontinuity of the visual velocity-azimuth curve from occurring due to the visual velocity folding phenomenon occurring at arbitrary elevation angles, distances and azimuth angles of the dual polarized radar, the visual velocity folding unfolding is performed, Wherein the point echo generated by the weather radar observation parameter is removed.
2. The apparatus of claim 1, wherein the Fourier coefficient calculator comprises:
A curve generating unit for generating a gaze velocity-azimuth curve using the gaze velocity preprocessed by the preprocessing unit; And
And a coefficient calculator for calculating a Fourier coefficient by expressing the line velocity-azimuth curve generated by the curve generator as a Fourier series form.
The apparatus according to claim 1,
A velocity component profile generation unit for generating a velocity component quasi-vertical profile through east-west, north-north, vertical velocity components and wind direction or wind speed calculation using the Fourier coefficient calculated by the Fourier coefficient calculation unit;
A deformation profile generation unit for generating a shear deformation and an elongation quasi-vertical profile using the Fourier coefficients calculated by the Fourier coefficient calculation unit; And
And a horizontal convergence / divergence profile generation unit for generating a horizontal convergence / divergence quasi-vertical profile using the Fourier coefficients calculated by the Fourier coefficient calculation unit.
6. The apparatus according to claim 5,
A shear strain and an elongation strain are calculated through the east-west component and the north-south component calculated by using the relationship between the respective Fourier coefficients and the linear wind field components, and then the strain calculation section calculates the synthetic strain represented by the sum of the elongation strain and the shear strain ; And
And a first generator for generating a quasi-vertical profile of shear deformation, elongation deformation, and synthetic deformation through shear deformation, elongation deformation and synthetic deformation calculated by said deformation calculation unit. Vertical Profile Generator.
6. The apparatus of claim 5, wherein the horizontal convergence /
A precipitation type classification unit for classifying rainfall or snowfall using a light band quality index calculated by reflectivity;
A falling rate calculator for calculating a falling rate according to the rainfall area or the snowfall area classified by the precipitation type classifying part; And
And a second generator for generating a horizontal convergence / divergence quasi- vertical profile by calculating horizontal convergence / divergence for a snowfall area or a rainfall area by applying the calculated falling speed to the falling speed calculation part Apparatus for generating quasi-vertical profiles of observed variables.
The method according to claim 7,
Wherein when the entire volume of the radar beam is included in the bright band region, a lower region of the lowest altitude is defined as a rainfall region, and an upper region of the highest altitude is classified as a snowfall region. Profile generating device.
8. The apparatus of claim 7, wherein the horizontal convergence /
The horizontal convergence / divergence is calculated through a calculation formula that takes into account the falling speed calculated using the reflectivity in the case of the rainfall region, and the horizontal convergence / divergence is calculated through the calculation formula in which the falling velocity is not considered in the snowfall region. Apparatus for generating quasi - vertical profiles of radar observations.
Selecting an elevation angle to generate a quasi-vertical profile;
Generating a quasi-vertical profile of the single and dual polarization parameters of the dual polarized radar for a specific azimuth range of a single elevation facet if the observed elevation angle of the selected elevation angle is not a line of sight velocity;
Preprocessing the gaze speed according to the selected altitude angle when the observation variable of the selected altitude angle is the gaze speed;
Calculating a Fourier coefficient by expressing a line velocity-azimuth curve generated using the preprocessed line-of-sight velocity in the form of a Fourier series; And
Generating a quasi-vertical profile by calculating at least one of a velocity component, a shear strain, an elongation strain, a synthetic strain, and a horizontal convergence / divergence using the calculated Fourier coefficients; - How to create a vertical profile.
11. The method of claim 10, wherein generating a quasi-vertical profile of the single and dual polarization parameters comprises:
Selecting at least one of a radar, a differential reflectance, a differential phase difference, and a cross correlation coefficient;
Selecting a rainfall area;
Generating an azimuthal average of the selected radar observation variables in the rainfall area selected from a single elevation facet according to the selected elevation angle; And
And generating a quasi-vertical profile for each of at least one of the reflectivity, the differential reflectivity, the differential phase difference, and the cross correlation coefficient using the generated azimuthal average. The quasi-vertical profile of the weather radar observation parameter Generation method.
11. The method of claim 10, wherein the pre-
In order to prevent the discontinuity of the visual velocity-azimuth curve from occurring due to the visual velocity folding phenomenon occurring at arbitrary elevation angles, distances and azimuth angles of the dual polarized radar, the visual velocity folding unfolding is performed, And removing the point echoes generated by the weather radar observation parameters.
11. The method of claim 10, wherein calculating the Fourier coefficients comprises:
Generating a gaze velocity-azimuth curve using the preprocessed gaze velocity; And
And generating the Fourier coefficient by expressing the generated gaze-azimuth curve in the form of a Fourier series, thereby calculating a Fourier coefficient.
11. The method of claim 10, wherein generating the respective quasi-vertical profiles comprises:
Generating a velocity component quasi-vertical profile through east-west, north-north, vertical velocity components and wind direction or wind speed calculation using the calculated Fourier coefficients;
Generating a quasi-vertical profile of shear deformation, elongation deformation, and synthetic deformation using the calculated Fourier coefficients; And
Generating a horizontal convergence / divergence quasi- vertical profile using the calculated Fourier coefficients; and generating a horizontal convergence / divergence quasi- vertical profile using the calculated Fourier coefficients.
15. The method of claim 14, wherein generating the shear strain, stretch strain, and quasi-vertical profile of the synthetic strain comprises:
Calculating the shear strain and the elongation strain through the east - west component and the north - south component calculated using the relationship between the respective Fourier coefficients and the linear wind field components, and then calculating the synthetic strain represented by the sum of the elongation strain and the shear strain; And
Generating a quasi-vertical profile of shear deformation, elongation deformation, and synthetic deformation through computed shear deformation, elongation deformation, and synthetic deformation.
15. The method of claim 14, wherein generating the horizontal convergence / divergence quasi-
Dividing the rainfall region or the snowfall region by using the bright band quality index calculated by the reflectance;
Calculating a falling speed according to the divided rainfall area or the snowfall area; And
And generating a horizontal convergence / divergence quasi- vertical profile by calculating the horizontal convergence / divergence for a snowfall or a rainfall area by applying the calculated dropping rate to the horizontal / vertical profile of the weather radar observation variable Generation method.
The method according to claim 16, wherein the step of classifying whether the rainfall area or the snowfall area includes:
Wherein when the entire volume of the radar beam is included in the bright band region, a lower region of the lowest altitude is defined as a rainfall region, and an upper region of the highest altitude is classified as a snowfall region. How to create a profile.
17. The method of claim 16, wherein generating the horizontal convergence / divergence quasi-
The horizontal convergence / divergence is calculated through a calculation formula that takes into account the falling speed calculated using the reflectivity in the case of the rainfall region, and the horizontal convergence / divergence is calculated through the calculation formula in which the falling velocity is not considered in the snowfall region. A method of generating a quasi-vertical profile of a radar observation parameter.
A computer-readable recording medium having recorded thereon a computer program for performing a method of generating a quasi-vertical profile of a weather radar observation parameter according to any one of claims 10 to 18.

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