CN108107434B - Regional three-dimensional wind field picture splicing method based on double-Doppler radar inversion - Google Patents

Regional three-dimensional wind field picture splicing method based on double-Doppler radar inversion Download PDF

Info

Publication number
CN108107434B
CN108107434B CN201711430083.8A CN201711430083A CN108107434B CN 108107434 B CN108107434 B CN 108107434B CN 201711430083 A CN201711430083 A CN 201711430083A CN 108107434 B CN108107434 B CN 108107434B
Authority
CN
China
Prior art keywords
inversion
doppler
wind field
radar
radars
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201711430083.8A
Other languages
Chinese (zh)
Other versions
CN108107434A (en
Inventor
罗昌荣
池艳珍
韩颂雨
陈德花
陈自力
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
FUJIAN INSTITUTE OF METEOROLOGICAL SCIENCES
XIAMEN METEOROLOGICAL DISASTER DEFENSE TECHNOLOGY CENTER (LABORATORY OF STRAITS METEOROLOGY XIAMEN LIGHTENING PROTECTION MONITORING TECHNOLOGY CENTER)
Original Assignee
Fujian Institute Of Meteorological Sciences
Xiamen Meteorological Disaster Defense Technology Center (laboratory Of Straits Meteorology Xiamen Lightening Protection Monitoring Technology Center)
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Fujian Institute Of Meteorological Sciences, Xiamen Meteorological Disaster Defense Technology Center (laboratory Of Straits Meteorology Xiamen Lightening Protection Monitoring Technology Center) filed Critical Fujian Institute Of Meteorological Sciences
Priority to CN201711430083.8A priority Critical patent/CN108107434B/en
Publication of CN108107434A publication Critical patent/CN108107434A/en
Application granted granted Critical
Publication of CN108107434B publication Critical patent/CN108107434B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88Radar or analogous systems specially adapted for specific applications
    • G01S13/95Radar or analogous systems specially adapted for specific applications for meteorological use
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02ATECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Landscapes

  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • General Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

The application relates to a regional three-dimensional wind field jigsaw method based on double Doppler radar inversion, which comprises the following steps: grouping a plurality of Doppler radars according to the distance between the two Doppler radars; performing double-Doppler radar three-dimensional wind field inversion on each group of double-Doppler radars; carrying out weight calculation on inversion results of the multiple groups of double Doppler radars to obtain the radial velocity at the inversion grid point, and obtaining the vertical velocity at the inversion grid point according to the radial velocity and a mass continuous equation; and obtaining a jigsaw of the regional three-dimensional wind field according to the radial speed and the vertical speed at all the inversion grid points. The application aims at the Doppler radar dense area, makes full use of the radial velocity information of a plurality of Doppler radars in the Doppler radar dense area, and can obtain a wind field inversion product more accurate than that of a single radar.

Description

Regional three-dimensional wind field picture splicing method based on double-Doppler radar inversion
Technical Field
The application belongs to the technical field of atmospheric remote sensing monitoring and analysis, and particularly relates to a regional three-dimensional wind field picture splicing method based on double-Doppler radar inversion.
Background
Doppler weather radar can provide the radial velocity of precipitation particles in addition to the echo intensity. In view of the fact that each doppler weather radar has a certain observation range, in order to monitor and analyze a wide range of weather systems, the information of a plurality of doppler weather radars needs to be subjected to mosaic analysis.
At present, the application of the domestic and foreign doppler radar jigsaw mainly focuses on the echo intensity jigsaw, namely, the combined reflectivity jigsaw, and the principle is to compare the echo intensities of all the body scanning layers of all the radars covering a certain point and select the maximum value as the combined reflectivity value of the point. However, since the doppler radar radial velocity scan radius is much smaller than the echo intensity scan radius, for example, the SA radar radial velocity scan radius is typically 230km, the SA radar echo intensity scan radius is typically 460km, and the SA radar radial velocity scan radius is much smaller than the echo intensity scan radius; and the technical development of the radar wind field jigsaw is not mature enough, so that the radar wind field jigsaw cannot be well applied.
Under the support of a tropical western Pacific observation test and a national high-influence weather predictability study which are special items in the public welfare industry, a national key laboratory of disaster weather of China researches institute develops a regional Doppler weather radar networking wind field inversion technology based on a 3DVAR of Lanzhou university and a radar data quality control and three-dimensional networking technology which are independently researched, and a 3DVAR single-section wind field inversion method, so that the purpose of inverting a regional high-time and space-resolution three-dimensional wind field is achieved. The technology gives full play to the advantage of large inversion area range of the single radar wind field, and can realize the splicing of the radar wind field in a large range more quickly. However, since the method is based on the single-radar wind field inversion method, only the radial velocity of a single radar is used, and a large error exists compared with the double-radar wind field inversion. For doppler radar dense areas, this technique fails to take full advantage of the radial velocity information of multiple radars.
Disclosure of Invention
In order to overcome the problems in the related art at least to a certain extent, the application provides a regional three-dimensional wind field jigsaw method based on dual-Doppler radar inversion.
According to a first aspect of an embodiment of the present application, there is provided a regional three-dimensional wind field jigsaw method based on dual doppler radar inversion, which includes the following steps:
grouping a plurality of Doppler radars according to the distance between the two Doppler radars;
performing double-Doppler radar three-dimensional wind field inversion on each group of double-Doppler radars;
carrying out weight calculation on inversion results of the multiple groups of double Doppler radars to obtain the radial velocity at the inversion grid point, and obtaining the vertical velocity at the inversion grid point according to the radial velocity and a mass continuous equation;
and obtaining a jigsaw of the regional three-dimensional wind field according to the radial speed and the vertical speed at all the inversion grid points.
Further, the specific process of grouping the multiple doppler radars according to the distance between the two doppler radars is as follows:
according to the setting of a user on a radar wind field inversion area, counting Doppler radars in the radar wind field inversion area;
counting Doppler radars in a preset range around the radar wind field inversion area;
calculating the distance between any two Doppler radars in all the statistical Doppler radars;
and taking two Doppler radars with the distance smaller than or equal to a preset distance threshold value as a group of double Doppler radars.
Further, the specific process of performing dual-doppler radar three-dimensional wind field inversion on each set of dual-doppler radars is as follows:
determining a dynamic global coordinate system;
adopting a grid with equal longitude and latitude and equal altitude corresponding to the dynamic global coordinate system as an inversion grid;
reading base data of the Doppler radar in each group of double Doppler radars, and respectively interpolating the radial velocity and the echo intensity of the double Doppler radars to grid inversion grid points with equal longitude and latitude and equal altitude;
and calculating to obtain the three-dimensional wind speed component at the target point by using the radial speed and the echo intensity of the target point detected by the interpolated double-Doppler radar.
Furthermore, the coordinate origin O of the dynamic earth coordinate system is arranged at the earth center, and the Z axis changes along with the change of the inversion target point.
Furthermore, in the dynamic global coordinate system, the Z axis points to the zenith direction from the origin O through the inversion target point, the Y axis points to the north direction of the inversion target point from the origin O, and the X axis points to the east direction of the inversion target point from the origin O.
Furthermore, the specific process of calculating the three-dimensional wind speed component at the target point by using the radial velocity and the echo intensity of the target point detected by the interpolated dual doppler radar is as follows:
let the target point be P (x, y, Z), and since the Z-axis passes through the target point P (x, y, Z), x-y-0; under a dynamic global coordinate system, if atmospheric refraction is not considered, the radial velocities of the two directions of the target point P (x, y, z) detected by the two doppler radars are respectively:
Figure BDA0001524518350000031
Figure BDA0001524518350000032
wherein R is1And R2Respectively showing the distances from the two Doppler radars to the earth center point O,
Figure BDA0001524518350000033
Figure BDA0001524518350000034
wtthe falling speed of the precipitation particles is expressed by an empirical formula: w is at=3.8I0.072I represents the echo intensity; (x)01,y01,z01)、(x02,y02,z02) Respectively representing the positions of two Doppler radar antennas;
the radial velocities observed by two radars on the same grid point are approximately used as horizontal wind vectors to be synthesized to generate a synthesized wind speed; setting the synthesized wind speed as a horizontal wind speed initial value and setting a vertical speed initial value as 0; and performing iterative calculation by using a mass continuous equation and an empirical formula of the falling speed of the precipitation particles until the error of the two iterations is less than a preset value, and finally obtaining the three-dimensional wind field of the radar wind field inversion region.
Furthermore, the calculation process of the three-dimensional wind field of the radar wind field inversion area is as follows:
1) let w (z ═ z)0) When w is equal to 0, w (z is equal to z)0) Continuous equation of mass taken in 0
Figure BDA0001524518350000035
In the method, a first iteration value u of the radial velocity is obtained through calculation(1)And v(1)
2) The radial velocity is iterated for the first time to obtain a value u(1)And v(1)Substituting into a radial velocity formula under the condition of not considering the influence of standard atmospheric refraction on vertical wind speed projection, and calculating to obtain a first estimated value w of the vertical velocity(1)
3) A first estimate w of the vertical velocity(1)The mass continuity equations are substituted and the radial velocities u and v are recalculated until convergence.
Further, the convergence condition in step 3) is set as:
max|w(k)-w(k-1)|<ε,ε=0.0001m/s。
further, the specific process of performing weight calculation on the inversion results of the multiple groups of double doppler radars to obtain the radial velocity at the inversion grid point and obtaining the vertical velocity at the inversion grid point according to the radial velocity and the mass continuous equation is as follows:
for a certain inversion grid point, if there are m groups of effective dual doppler radars, the radial velocity at the inversion grid point is:
Figure BDA0001524518350000041
in the formula, AiRepresenting a weight coefficient of an included angle, wherein the included angle is an included angle formed between the target point and the double Doppler radars; b isiRepresents a distance weight coefficient, Bi=Di/DmaxWherein D isiIndicating i-th group of dual Doppler beamsDistance between arrivals, DmaxRepresents the maximum value of the distance between two Doppler radars in all the groups of double Doppler radars;
for all the inversion grid points, the vertical velocity is calculated using the radial velocity and mass continuity equations.
Further, when the included angle is greater than 20 ° and less than or equal to 90 °, the included angle weight coefficient is: a. thei=100.-|90.-θiL, |; when the included angle is larger than 90 degrees and smaller than 160 degrees, the weight coefficient of the included angle is as follows: a. thei=100.-1.2*|90.-θiL, |; wherein, thetaiRepresenting the angle, 100 representing the floating point number, 90 representing the floating point number.
The technical scheme provided by the embodiment of the application can have the following beneficial effects: aiming at a Doppler radar dense area, the application adopts a double-Doppler radar wind field inversion algorithm under a dynamic terrestrial coordinate system to perform three-dimensional wind field picture splicing. The method and the device adopt a dynamic global coordinate system and grids with equal longitude and latitude and equal altitude, and are convenient for networking analysis of wind fields inverted by different double Doppler radars. The Doppler radars in the area are grouped to form a plurality of groups of double Doppler radars, wind field inversion is carried out on each group of Doppler double radars respectively, and finally a plurality of inversion values on inversion grid points are optimized or calculated and determined according to weight coefficients, so that the regional three-dimensional wind field jigsaw is obtained. The method and the device make full use of the radial velocity information of the Doppler radars in the Doppler radar dense area, and can obtain a wind field inversion product which is more accurate than that of a single radar.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
Fig. 1 is a flowchart illustrating a regional three-dimensional wind field mosaic method based on dual doppler radar inversion according to an exemplary embodiment.
Fig. 2 is a schematic diagram illustrating dual-doppler radar inversion in a dynamic global coordinate system in a regional three-dimensional wind field jigsaw method based on dual-doppler radar inversion according to an exemplary embodiment.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
Fig. 1 is a flowchart of a regional three-dimensional wind field splicing method based on dual-doppler radar inversion according to an embodiment of the present application. As shown in fig. 1, the regional three-dimensional wind field jigsaw method based on dual doppler radar inversion of the present application includes the following steps:
and S1, grouping a plurality of Doppler radars according to the distance between the two Doppler radars.
Firstly, according to the setting of a user on a radar wind field inversion area, namely a longitude and latitude change range, the Doppler radar in the radar wind field inversion area is counted.
Secondly, in order to fully play the role of detection information of the Doppler radars, the Doppler radars in a preset range around a radar wind field inversion area are counted, and the Doppler radars are also grouped. The preset range around the radar wind field inversion region can be 100km around the radar wind field inversion region.
And thirdly, calculating the distance between any two Doppler radars in all the statistical Doppler radars.
And finally, taking the two Doppler radars with the distance smaller than or equal to a preset distance threshold value as a group of double Doppler radars. The preset distance threshold may be 100 km.
S2, performing double-Doppler radar three-dimensional wind field inversion on each group of double-Doppler radars, wherein the specific process is as follows:
and S21, determining a dynamic global coordinate system.
The origin of coordinates O of the dynamic earth coordinate system is arranged at the center of the earth sphere, and the Z axis changes along with the change of the inversion target point. Specifically, the Z axis is directed from the origin O to the zenith direction through the inversion target point, the Y axis is directed from the origin O to the north direction of the inversion target point, and the X axis is directed from the origin O to the east direction of the inversion target point.
And S22, adopting the equal longitude and latitude and equal altitude grids corresponding to the dynamic earth coordinate system as an inversion grid.
And S23, reading the base data of the Doppler radar in each group of double Doppler radars, and respectively interpolating the radial velocity and the echo intensity of the double Doppler radars to grid inversion grid points with equal longitude and latitude and equal altitude.
S24, calculating the three-dimensional wind speed component at the target point by using the radial velocity and the echo intensity of the target point detected by the interpolated double-Doppler radar, wherein the specific process is as follows:
s241, as shown in fig. 2, sets the target point P (x, y, Z), and since the Z-axis passes through the target point P (x, y, Z), x-y-0. Under a dynamic global coordinate system, if atmospheric refraction is not considered, the radial velocities of the two directions of the target point P (x, y, z) detected by the two doppler radars are respectively:
Figure BDA0001524518350000061
Figure BDA0001524518350000062
wherein R is1And R2Respectively showing the distances from the two Doppler radars to the earth center point O,
Figure BDA0001524518350000063
Figure BDA0001524518350000064
wtthe falling speed of the precipitation particles is expressed by an empirical formula: w is at=3.8I0.072I represents the echo intensity; (x)01,y01,z01)、(x02,y02,z02) Respectively, the positions of the two doppler radar antennas.
And S242, synthesizing the approximate radial velocities observed by the two radars on the same grid point as a horizontal wind vector to generate a synthesized wind speed. The synthesized wind speed is set as the initial value of the horizontal wind speed, and the initial value of the vertical speed is set to 0. And (3) performing iterative calculation by using a mass continuous equation (approximate incompressible atmosphere) and an empirical formula of the falling speed of precipitation particles until the error of the two iterations is less than a preset value, and finally obtaining the three-dimensional wind field of the radar wind field inversion region.
An iterative algorithm is adopted to calculate the three-dimensional wind field, and the specific process is as follows:
1) let w (z ═ z)0) When w is equal to 0, w (z is equal to z)0) Continuous equation of mass taken in 0
Figure BDA0001524518350000065
In the method, a first iteration value u of the radial velocity is obtained through calculation(1)And v(1)
2) The radial velocity is iterated for the first time to obtain a value u(1)And v(1)Substituting into radial velocity equations (1) and (2) without considering the influence of standard atmospheric refraction on vertical wind velocity projection, and calculating to obtain a first estimated value w of the vertical velocity(1)
3) A first estimate w of the vertical velocity(1)And substituting a mass continuous equation, and recalculating the radial velocities u and v until convergence, wherein the convergence condition is as follows:
max|w(k)-w(k-1)|<ε,ε=0.0001m/s。
s3, carrying out weight calculation on inversion results of multiple groups of double Doppler radars to obtain the radial velocity of an inversion grid point, and obtaining the vertical velocity of the inversion grid point according to the radial velocity and a mass continuous equation, wherein the specific process comprises the following steps:
because there are often multiple groups of dual doppler radars in the inversion region where the same inversion grid point is located, the inversion result needs to be rejected according to a certain rule or calculated according to a certain weight coefficient.
The method mainly considers two factors of an included angle between an inversion grid point and two Doppler radars and a distance between the two Doppler radars:
(1) according to the existing analysis result, the size of the inversion error is related to an included angle formed between the target point and the double-Doppler radar, and the closer the formed included angle is to 90 degrees, the smaller the inversion error is. In addition, considering that the inversion error near the connection line of the dual doppler radars is large, for the inversion grid point, only the dual doppler radars which form an included angle with the target point larger than 20 degrees and smaller than 160 degrees perform weight consideration on the inversion grid point.
When the included angle thetaiWhen the angle is more than 20 degrees and less than or equal to 90 degrees, the weight coefficient A of the included anglei=100.-|90.-θi|;
When the included angle thetaiWhen the angle is more than 90 degrees and less than 160 degrees, the weight coefficient A of the included anglei=100.-1.2*|90.-θi|。
Wherein 100 represents a floating point number, and 90 represents a floating point number.
(2) Because the width of each scanning line of the Doppler radar is 1 degree, the closer the distance to the radar is, the higher the spatial resolution is, and the inversion wind field of the area near the double Doppler radar with the closer distance is more accurate. For this purpose, the range weight coefficient of the i-th group of dual-doppler radars is set as: b isi=Di/DmaxWherein D isiRepresenting the distance, D, between the i-th set of dual Doppler radarsmaxRepresents the maximum value of the distance between two Doppler radars in all the groups of double Doppler radars.
For a certain inversion grid point, if there are m groups of effective dual doppler radars, the radial velocity at the inversion grid point is:
Figure BDA0001524518350000081
for all inversion grid points, after the radial velocity is obtained through calculation, the vertical velocity can be obtained through integral calculation through a mass continuous equation.
And S4, obtaining a jigsaw of the regional three-dimensional wind field according to the radial velocity and the vertical velocity of all the inversion grid points.
It is understood that the same or similar parts in the above embodiments may be mutually referred to, and the same or similar parts in other embodiments may be referred to for the content which is not described in detail in some embodiments.
It should be noted that, in the description of the present application, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Further, in the description of the present application, the meaning of "a plurality" means at least two unless otherwise specified.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present application includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.

Claims (9)

1. A regional three-dimensional wind field jigsaw method based on double Doppler radar inversion is characterized in that,
grouping a plurality of Doppler radars according to the distance between the two Doppler radars;
performing double-Doppler radar three-dimensional wind field inversion on each group of double-Doppler radars;
carrying out weight calculation on inversion results of the multiple groups of double Doppler radars to obtain a horizontal wind speed component at an inversion grid point, and obtaining a vertical speed at the inversion grid point according to the horizontal wind speed component and a mass continuous equation;
obtaining a jigsaw of the regional three-dimensional wind field according to the horizontal wind speed components and the vertical speeds at all the inversion grid points;
the specific process of obtaining the vertical speed at the inversion grid point according to the horizontal wind speed component and the mass continuous equation comprises the following steps:
for a certain inversion grid point, if there are m groups of effective dual doppler radars, the horizontal wind speed component at the inversion grid point is:
Figure FDA0002362713560000011
in the formula, AiRepresenting a weight coefficient of an included angle, wherein the included angle is an included angle formed between the target point and the double Doppler radars; b isiRepresents a distance weight coefficient, Bi=Di/DmaxWherein D isiRepresenting the distance, D, between the i-th set of dual Doppler radarsmaxRepresents the maximum value of the distance between two Doppler radars in all the groups of double Doppler radars; u. ofiAnd viInverting the horizontal wind speed component of the ith group of double Doppler radars;
for all inversion grid points, the vertical velocity is calculated using the horizontal wind velocity component and the mass continuity equation.
2. The regional three-dimensional wind field mosaic method based on dual-doppler radar inversion of claim 1, wherein the specific process of grouping a plurality of doppler radars according to the distance between two doppler radars is as follows:
according to the setting of a user on a radar wind field inversion area, counting Doppler radars in the radar wind field inversion area;
counting Doppler radars in a preset range around the radar wind field inversion area;
calculating the distance between any two Doppler radars in all the statistical Doppler radars;
and taking two Doppler radars with the distance smaller than or equal to a preset distance threshold value as a group of double Doppler radars.
3. The regional three-dimensional wind field splicing method based on dual-doppler radar inversion according to claim 1 or 2, wherein the specific process of performing dual-doppler radar three-dimensional wind field inversion on each group of dual-doppler radars is as follows:
determining a dynamic global coordinate system;
adopting a grid with equal longitude and latitude and equal altitude corresponding to the dynamic global coordinate system as an inversion grid;
reading base data of the Doppler radar in each group of double Doppler radars, and respectively interpolating the radial velocity and the echo intensity of the double Doppler radars to inversion grid points with equal longitude and latitude and equal altitude;
and calculating to obtain the three-dimensional wind speed component at the target point by using the radial speed and the echo intensity of the target point detected by the interpolated double-Doppler radar.
4. The regional three-dimensional wind field mosaic method based on dual-doppler radar inversion of claim 3, wherein the origin of coordinates O of said dynamic global coordinate system is set at the center of the earth, and the Z-axis varies with the variation of the inversion target point.
5. The regional three-dimensional wind field mosaic method based on dual-doppler radar inversion of claim 4, wherein in said dynamic global coordinate system, the Z-axis is directed from the origin O to the zenith direction through the inversion target point, the Y-axis is directed from the origin O to the north direction of the inversion target point, and the X-axis is directed from the origin O to the east direction of the inversion target point.
6. The regional three-dimensional wind field mosaic method based on dual-doppler radar inversion of claim 3, wherein the specific process of calculating the three-dimensional wind speed component at the target point by using the radial velocity and the echo intensity of the target point detected by the dual-doppler radar after interpolation is as follows:
let the target point be P (x, y, Z), and since the Z-axis passes through the target point P (x, y, Z), x-y-0; under a dynamic global coordinate system, if atmospheric refraction is not considered, the radial velocities of the two directions of the target point P (x, y, z) detected by the two doppler radars are respectively:
Figure FDA0002362713560000031
Figure FDA0002362713560000032
wherein R is1And R2Respectively showing the distances from the two Doppler radars to the earth center point O,
Figure FDA0002362713560000033
Figure FDA0002362713560000034
wtthe falling speed of the precipitation particles is expressed by an empirical formula: w is at=3.8I0.072I represents the echo intensity; (x)01,y01,z01)、(x02,y02,z02) Respectively representing the positions of two Doppler radar antennas;
the radial velocities observed by two radars on the same grid point are approximately used as horizontal wind vectors to be synthesized to generate a synthesized wind speed; setting the synthesized wind speed as a horizontal wind speed initial value and setting a vertical speed initial value as 0; and performing iterative calculation by using a mass continuous equation and an empirical formula of the falling speed of the precipitation particles until the error of the two iterations is less than a preset value, and finally obtaining the three-dimensional wind field of the radar wind field inversion region.
7. The regional three-dimensional wind field mosaic method based on dual-doppler radar inversion of claim 6, wherein the three-dimensional wind field of the radar wind field inversion region is calculated by the following process:
1) let w (z ═ z)0) When w is equal to 0, w (z is equal to z)0)=Continuous equation of 0-substituted mass
Figure FDA0002362713560000035
In the method, a first iteration value u is obtained through calculation(1)And v(1)
2) The first iteration value u(1)And v(1)Substituting into a radial velocity formula under the condition of not considering the influence of standard atmospheric refraction on vertical wind speed projection, and calculating to obtain a first estimated value w of the vertical velocity(1)
3) A first estimate w of the vertical velocity(1)The mass continuity equation is substituted and the horizontal wind speed components u and v are recalculated until convergence.
8. The regional three-dimensional wind field mosaic method based on dual-doppler radar inversion of claim 7, wherein the convergence condition in step 3) is set as:
max|w(k)-w(k-1)|<ε,ε=0.0001m/s。
9. the regional three-dimensional wind field mosaic method based on dual-doppler radar inversion of claim 1, wherein when said included angle is greater than 20 ° and less than or equal to 90 °, the included angle weight coefficient is: a. thei=100.-|90.-θiL, |; when the included angle is larger than 90 degrees and smaller than 160 degrees, the weight coefficient of the included angle is as follows: a. thei=100.-1.2*|90.-θiL, |; wherein, thetaiRepresenting the angle, 100 representing the floating point number, 90 representing the floating point number.
CN201711430083.8A 2017-12-26 2017-12-26 Regional three-dimensional wind field picture splicing method based on double-Doppler radar inversion Active CN108107434B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201711430083.8A CN108107434B (en) 2017-12-26 2017-12-26 Regional three-dimensional wind field picture splicing method based on double-Doppler radar inversion

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201711430083.8A CN108107434B (en) 2017-12-26 2017-12-26 Regional three-dimensional wind field picture splicing method based on double-Doppler radar inversion

Publications (2)

Publication Number Publication Date
CN108107434A CN108107434A (en) 2018-06-01
CN108107434B true CN108107434B (en) 2020-06-09

Family

ID=62213357

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201711430083.8A Active CN108107434B (en) 2017-12-26 2017-12-26 Regional three-dimensional wind field picture splicing method based on double-Doppler radar inversion

Country Status (1)

Country Link
CN (1) CN108107434B (en)

Families Citing this family (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109100723B (en) * 2018-07-25 2022-05-27 南京信息工程大学 High-altitude wind inversion method based on Doppler weather radar data
CN109405834B (en) * 2018-11-23 2022-08-30 北京电子工程总体研究所 Digital map-based shielding angle real-time resolving method and system
CN112965084B (en) * 2021-01-28 2021-10-22 中国人民解放军国防科技大学 Airport wind field characteristic detection method, device and equipment based on laser radar
CN113009490B (en) * 2021-02-20 2022-10-21 江苏省气象台 Radar three-dimensional wind field inversion method based on high-resolution mode dynamic constraint
CN113514834B (en) * 2021-09-14 2022-03-08 航天宏图信息技术股份有限公司 Wind speed and direction inversion method, device, equipment and storage medium

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7471234B1 (en) * 2004-12-16 2008-12-30 Unisys Corporation Producing improved mosaic of multiple field radar data product to enable improved weather display
CN101937078A (en) * 2009-06-30 2011-01-05 深圳市气象局 Nowcasting method and system of thunder cloud cluster based on boundary recognition and tracer technique
CN105068153A (en) * 2015-06-19 2015-11-18 中国气象科学研究院 Regional automatic rainfall station hourly rainfall data quality control system and method
CN106199606A (en) * 2016-07-20 2016-12-07 国网河南省电力公司电力科学研究院 A kind of multi thresholds squall line recognition methods based on radar return 3 d mosaics
CN106324601A (en) * 2016-08-08 2017-01-11 北京无线电测量研究所 Wind profile radar networking-based three dimension wind field inversion method

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7471234B1 (en) * 2004-12-16 2008-12-30 Unisys Corporation Producing improved mosaic of multiple field radar data product to enable improved weather display
CN101937078A (en) * 2009-06-30 2011-01-05 深圳市气象局 Nowcasting method and system of thunder cloud cluster based on boundary recognition and tracer technique
CN105068153A (en) * 2015-06-19 2015-11-18 中国气象科学研究院 Regional automatic rainfall station hourly rainfall data quality control system and method
CN106199606A (en) * 2016-07-20 2016-12-07 国网河南省电力公司电力科学研究院 A kind of multi thresholds squall line recognition methods based on radar return 3 d mosaics
CN106324601A (en) * 2016-08-08 2017-01-11 北京无线电测量研究所 Wind profile radar networking-based three dimension wind field inversion method

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
Assimilation of Doppler Radar Observations with a Regional 3DVAR System: Impact of Doppler Velocities on Forecasts of a Heavy Rainfall Case;QINGNONG XIAO,et al;《J O U R N A L O F A P P L I E D M E T E O R O L O G Y》;20050630;p768-788 *
华南暴雨试验资料的集成处理及显示;阮征等;《热带气象学报》;20041231;第768-775页 *
双雷达反演台风外围强带状回波风场结构特征研究;罗昌荣等;《大气科学》;20120331;第247-258页 *
白玉洁等.广东天气雷达组网策略及在台风监测中的应用.《热带气象学报》.2012, *

Also Published As

Publication number Publication date
CN108107434A (en) 2018-06-01

Similar Documents

Publication Publication Date Title
CN108107434B (en) Regional three-dimensional wind field picture splicing method based on double-Doppler radar inversion
CN113359097B (en) Millimeter wave radar and camera combined calibration method
CN106842165B (en) Radar centralized asynchronous fusion method based on different distance angular resolutions
CN105760811B (en) Global map closed loop matching process and device
Wang et al. Shader-based sensor simulation for autonomous car testing
AU2016222648B2 (en) Iterative ray-tracing for autoscaling of oblique ionograms
CN109100723B (en) High-altitude wind inversion method based on Doppler weather radar data
CN107843895A (en) A kind of Dual-Doppler weather radar dimensional wind inversion method
Park et al. Radar localization and mapping for indoor disaster environments via multi-modal registration to prior LiDAR map
JP7088288B2 (en) Image processing device, image processing method, and image processing program
CN112051568B (en) Pitching angle measurement method of two-coordinate radar
CN108305277A (en) A kind of heterologous image matching method based on straightway
CN112379393B (en) Train collision early warning method and device
Rogers et al. Three-dimensional UAV-based atmospheric tomography
CN105737850B (en) Mutative scale one direction gravity sample vector matching locating method based on particle filter
CN105388473A (en) Near-field RCS quick measuring method based on high-resolution imaging
CN110187337B (en) LS and NEU-ECEF space-time registration-based high maneuvering target tracking method and system
JP2018077209A (en) Systems and methods for adding functional grid elements to stochastic sparse tree grids for spatial filtering
CN109190647B (en) Active and passive data fusion method
CN107621637B (en) Shear region wind field inversion method based on single Doppler radar
CN112526508A (en) Double-station radar combined target positioning method and system
CN116500648A (en) Wind profile inversion method for foundation laser radar target area
CN111505596B (en) Three-dimensional wind field inversion method based on non-uniform sampling correction VAD technology
CN114236522A (en) Forward scattering radar network target three-dimensional space position estimation method and storage medium
JP6192915B2 (en) Gain setting method, gain setting program, and gain setting device

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
TA01 Transfer of patent application right
TA01 Transfer of patent application right

Effective date of registration: 20200114

Address after: 361006 85 Observatory Road, Huli District, Xiamen, Fujian

Applicant after: Xiamen Meteorological Disaster Defense Technology Center (Xiamen City lightning protection monitoring technology center)

Applicant after: Luo Changrong

Applicant after: Chi Yanzhen

Applicant after: Han Songyu

Applicant after: Chen Dehua

Applicant after: Chen Zili

Address before: 361006 85 Observatory Road, Huli District, Xiamen, Fujian

Applicant before: Xiamen Meteorological Disaster Defense Technology Center (Xiamen City lightning protection monitoring technology center)

Applicant before: Luo Changrong

Applicant before: Chi Yanzhen

Applicant before: Han Songyu

Applicant before: Luo Guanting

TA01 Transfer of patent application right
TA01 Transfer of patent application right

Effective date of registration: 20200326

Address after: 361006 85 Observatory Road, Huli District, Xiamen, Fujian

Applicant after: XIAMEN METEOROLOGICAL DISASTER DEFENSE TECHNOLOGY CENTER (LABORATORY OF STRAITS METEOROLOGY XIAMEN LIGHTENING PROTECTION MONITORING TECHNOLOGY CENTER)

Applicant after: FUJIAN INSTITUTE OF METEOROLOGICAL SCIENCES

Applicant after: Luo Changrong

Applicant after: Chi Yanzhen

Applicant after: Han Songyu

Applicant after: Chen Dehua

Applicant after: Chen Zili

Address before: 361006 85 Observatory Road, Huli District, Xiamen, Fujian

Applicant before: XIAMEN METEOROLOGICAL DISASTER DEFENSE TECHNOLOGY CENTER (LABORATORY OF STRAITS METEOROLOGY XIAMEN LIGHTENING PROTECTION MONITORING TECHNOLOGY CENTER)

Applicant before: Luo Changrong

Applicant before: Chi Yanzhen

Applicant before: Han Songyu

Applicant before: Chen Dehua

Applicant before: Chen Zili

CB03 Change of inventor or designer information
CB03 Change of inventor or designer information

Inventor after: Luo Changrong

Inventor after: Chi Yanzhen

Inventor after: Han Songyu

Inventor after: Chen Dehua

Inventor after: Chen Zili

Inventor before: Luo Changrong

Inventor before: Chi Yanzhen

Inventor before: Han Songyu

Inventor before: Luo Guanting

GR01 Patent grant
GR01 Patent grant