CN111856424A - Rainstorm monitoring and approaching early warning method based on radar echo - Google Patents

Rainstorm monitoring and approaching early warning method based on radar echo Download PDF

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Publication number
CN111856424A
CN111856424A CN202010734828.5A CN202010734828A CN111856424A CN 111856424 A CN111856424 A CN 111856424A CN 202010734828 A CN202010734828 A CN 202010734828A CN 111856424 A CN111856424 A CN 111856424A
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rainstorm
radar
radar echo
precipitation
echo intensity
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祝院生
蔡国成
舒雷
梁后军
韩飞
卢恬强
王�锋
旷世希
曹自收
李甜甜
毕梦玲
陈煜�
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Anhui Water Water Science And Technology Co ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details 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
    • G01S7/415—Identification of targets based on measurements of movement associated with the target
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO 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
    • G01S13/00—Systems 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
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/886—Radar or analogous systems specially adapted for specific applications for alarm systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01W—METEOROLOGY
    • G01W1/00—Meteorology
    • G01W1/14—Rainfall or precipitation gauges

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Abstract

The invention relates to the technical field of rainstorm monitoring and early warning, in particular to a rainstorm monitoring and approaching early warning method based on radar echo, which sequentially comprises the following steps: s10: acquiring a radar echo intensity data file; s20: extrapolating the radar echo intensity for 1-3 hours in the future according to the echo intensity; s30: radar estimation of precipitation; s40: determining the range of a rainstorm area according to radar estimated precipitation statistics; s50: and early warning of a display area. The method for rainstorm monitoring and proximity early warning based on radar echo comprises the steps of carrying out extrapolation on the radar echo intensity for 1-3 hours in the future by adopting a semi-Lagrange method according to the current radar echo intensity, carrying out gridding quantitative analysis on the radar echo intensity for 1-3 hours after extrapolation, converting the radar echo intensity into rainfall estimation for 1-3 hours in the future, and starting regional rainstorm early warning if the rainfall of a certain region reaches the rainstorm level within 1-3 hours in the future.

Description

Rainstorm monitoring and approaching early warning method based on radar echo
Technical Field
The invention relates to the technical field of rainstorm monitoring and early warning, in particular to a rainstorm monitoring and approaching early warning method based on radar echo.
Background
The traditional rainstorm monitoring and early warning is that the rainfall collected by the hydrological automatic remote sensing station is counted in real time, and when the rainstorm level is reached, the rainstorm early warning is started. The early warning in the mode is usually post-disaster early warning, because the precipitation collected by the hydrological automatic telemetry station is the actual precipitation falling to the ground, after the water conservancy department receives relevant early warning information, the precipitation basically tends to end, and disasters such as urban waterlogging or landslide cause personnel or property loss.
Aiming at the problems, a method for monitoring rainstorm and carrying out proximity early warning based on radar echo is designed.
Disclosure of Invention
The invention aims to provide a rainstorm monitoring and approaching early warning method based on radar echo, so as to solve the technical problem.
In order to solve the technical problems, the invention adopts the following technical scheme:
a rainstorm monitoring and approaching early warning method based on radar echo sequentially comprises the following steps:
s10: obtaining radar echo intensity data files
Acquiring a radar echo data file from a server, analyzing according to a file format, and determining relevant information of the size of a radar echo grid, an area range and longitude and latitude coordinates;
s20: extrapolating future radar echo intensities from echo intensity
According to the current echo intensity, extrapolating the radar echo intensity by adopting a semi-Lagrange extrapolation method, and generating radar echo intensity data of each specific time interval in 1-3 hours in the future;
semi-lagrange extrapolation formula
semi-Lagrange's basic equation:
Figure BDA0002604553590000011
wherein:
Figure BDA0002604553590000021
u (x, t) is a given equation, equation 1-1 indicates that scalar F is a constant value along the fluid trajectory; the actual fluid particle trajectory is in the x-t plane at tnTime + Δ t reaches grid point xmThe trajectory of (2); the essence of the method is to perform approximate integration along an approximate fluid motion track; the following can thus be derived:
Figure BDA0002604553590000022
wherein:
αm＝ΔtU(xm-αm，tn)
wherein a ismIs the distance the particle moves on x in time Δ t as it follows the fluid trajectory; due to the fact thatIf we know amWe can then derive tn+ Δ t time xmThe value of F above; the key of the existing problem is to solve the problem am；tnThe predicted value of F at the + Δ t end is tn-value of departure point at time Δ t; typically we select the end point (arrival point) at the grid point and the start point xm-2amIt does not necessarily fall exactly on the regular grid points of the pattern, so t is at these pointsnValue F (x) of- Δ tm-2am，tnΔ t) must be determined by interpolation or other methods from the values at the regular points;
the algorithm steps of this semi-lagrange extrapolation method are summarized as follows:
(1) using the equation for all grid points xmSolving for amWhere an initial guess (typically its value at the previous time step) needs to be set and an interpolation formula needs to be used;
(2) estimation of grid points x using interpolation formulam-2amAt tn-F value at time at;
(3) estimation of the time tn+ Δ t endpoint xmF values at grid points;
s30: radar estimation of precipitation
Carrying out gridding quantitative analysis according to the radar echo intensity data of each specific time interval in 1-3 hours in the future; converting the radar echo intensity into grid precipitation of each specific time interval through a radar ZR relation formula;
radar ZR relation formula
Convection precipitation: z is 300 × R1.4;
lamellar cloud precipitation: z is 200 × R1.6;
warming precipitation: z230 × R1.25;
snowing: z is 75 × R2.0;
in the above formula, Z represents radar reflectivity, and R represents precipitation rate;
s40: determining rainstorm zone range from radar estimated precipitation statistics
Estimating precipitation according to the radar of each specific time interval of 1-3 hours in the future, and counting the precipitation of 1-3 hours in the future; judging whether rainstorm occurs in each grid in the future 1-3 hours, and recording area coordinate information of areas where the rainstorm occurs;
s50: display area warning
And displaying the rainstorm area coordinate information in the application system according to the rainstorm area coordinate information recorded in the S40.
Preferably, the method for displaying the area alarm in step S50 further includes sending the information of the rainstorm area coordinate recorded in step S40 to a mobile phone of a relevant person through a short message.
Preferably, each of the specific time intervals of the step S20, the step S30, and the step S40 is any one of three, i.e., 5 minutes, 10 minutes, and 15 minutes.
The invention has the beneficial effects that:
according to the method for rainstorm monitoring and approaching early warning based on radar echoes, the radar echo intensity is extrapolated in the future for 1-3 hours by adopting a semi-Lagrange method according to the current radar echo intensity, the extrapolated radar echo intensity in the 1-3 hours is subjected to gridding quantitative analysis, the extrapolated radar echo intensity is converted into rainfall estimation in the future for 1-3 hours, and if the rainfall amount of a certain area reaches the rainstorm level in the future for 1-3 hours, the regional rainstorm early warning is started;
after receiving the related early warning information, the water conservancy department can release the rainstorm information to the area 1-3 hours in advance, and make disaster prevention measures in advance to avoid or reduce the loss of personnel and property.
Drawings
FIG. 1 is a flow chart of the warning information processing of the present invention;
fig. 2 is a diagram showing the warning information of the present invention in an application system.
Detailed Description
In order to make the technical means, the original characteristics, the achieved purposes and the effects of the invention easily understood, the invention is further described below with reference to the specific embodiments and the attached drawings, but the following embodiments are only the preferred embodiments of the invention, and not all embodiments. Based on the embodiments in the implementation, other embodiments obtained by those skilled in the art without any creative efforts belong to the protection scope of the present invention.
Specific embodiments of the present invention are described below with reference to the accompanying drawings.
Example 1
As shown in fig. 1-2, a method for monitoring rainstorm and early warning based on radar echo sequentially includes the following steps:
s10: obtaining radar echo intensity data files
Acquiring a radar echo data file from a server, analyzing according to a file format, and determining relevant information of the size of a radar echo grid, an area range and longitude and latitude coordinates;
s20: extrapolating future radar echo intensities from echo intensity
According to the current echo intensity, extrapolating the radar echo intensity by adopting a semi-Lagrange extrapolation method, and generating radar echo intensity data of each specific time interval in 1-3 hours in the future;
principle and main formula of semi-Lagrange extrapolation method
1.1, half Lagrange extrapolation principle
An observer observes that the world changes around the observer are in a fixed place, the method can well work for a regular cartesian grid, but the requirement on the time step is often over strict due to the stability of the calculation, and the time step is required to be within a very small range in order to ensure the stability of the calculation result, while in the lagrange method, the observer observes the changes around the observer as if the observer follows the movement of a fluid particle, the time step adopted by the method can be much larger than that of the euler method, but the defect is that the particles with very regular intervals at first become the particles without spatial regularity at the back, so the important characteristics of the particle flow can not be well expressed always; the original intention of the semi-Lagrange extrapolation method is to combine the advantages of the semi-Lagrange extrapolation method and the Lagrange extrapolation method, so that the regular resolution of the Euler method is achieved, and the stability of the Lagrange method can be kept.
1.2, half Lagrange extrapolation formula
semi-Lagrange's basic equation:
Figure BDA0002604553590000051
wherein:
Figure BDA0002604553590000052
u (x, t) is a given equation, equation 1-1 indicates that scalar F is a constant value along the fluid trajectory; the actual fluid particle trajectory is in the x-t plane at tnTime + Δ t reaches grid point xmThe trajectory of (2); the essence of the method is to perform approximate integration along an approximate fluid motion track; the following can thus be derived:
Figure BDA0002604553590000053
wherein:
αm＝ΔtU(xm-αm，tn)
wherein a ismIs the distance the particle moves on x in time Δ t as it follows the fluid trajectory; thus if we know amWe can then derive tn+ Δ t time xmThe value of F above; the key of the existing problem is to solve the problem am；tnThe predicted value of F at the + Δ t end is tn-value of departure point at time Δ t; typically we select the end point (arrival point) at the grid point and the start point xm-2amIt does not necessarily fall exactly on the regular grid points of the pattern, so t is at these pointsnValue F (x) of- Δ tm-2am，tnΔ t) must be determined by interpolation or other methods from the values at the regular points;
the algorithm steps of this semi-lagrange extrapolation method are summarized as follows:
(1) using the equation for all grid points xmSolving for amWherein an initial guess value is set (typically to be set)Its value at the previous time step) and an interpolation formula is needed;
(2) estimation of grid points x using interpolation formulam-2amAt tn-F value at time at;
(3) estimation of the time tn+. DELTA t end point xmF values at grid points;
s30: radar estimation of precipitation
Carrying out gridding quantitative analysis according to the radar echo intensity data of each specific time interval in 1-3 hours in the future; converting the radar echo intensity into grid precipitation of each specific time interval through a radar ZR relation formula;
radar ZR relation formula
Convection precipitation: z is 300 × R1.4;
lamellar cloud precipitation: z is 200 × R1.6;
warming precipitation: z230 × R1.25;
snowing: z is 75 × R2.0;
in the above formula, Z represents radar reflectivity, and R represents precipitation rate;
s40: determining rainstorm zone range from radar estimated precipitation statistics
Estimating precipitation according to the radar of each specific time interval of 1-3 hours in the future, and counting the precipitation of 1-3 hours in the future; judging whether rainstorm occurs in 1-3 hours in the future of each grid, wherein the rainstorm is strong rainfall with the precipitation of 50 millimeters or more in 24 hours, and recording area coordinate information of an area where the rainstorm occurs;
s50: display area warning
And displaying the rainstorm area coordinate information in the application system according to the rainstorm area coordinate information recorded in the S40.
The method for displaying the area alarm in the step S50 further includes sending the information of the rainstorm area coordinate recorded in the step S40 to the mobile phone of the relevant person through a short message.
Each of the specific time intervals in step S20, step S30, and step S40 is any one of three, 5 minutes, 10 minutes, and 15 minutes.
In the present invention, unless otherwise expressly stated or limited, "above" or "below" a first feature means that the first and second features are in direct contact, or that the first and second features are not in direct contact but are in contact with each other via another feature therebetween. Also, the first feature being "on," "above" and "over" the second feature includes the first feature being directly on and obliquely above the second feature, or merely indicating that the first feature is at a higher level than the second feature. A first feature being "under," "below," and "beneath" a second feature includes the first feature being directly under and obliquely below the second feature, or simply meaning that the first feature is at a lesser elevation than the second feature.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and the preferred embodiments of the present invention are described in the above embodiments and the description, and are not intended to limit the present invention. The scope of the invention is defined by the appended claims and equivalents thereof.

Claims (3)

1. A rainstorm monitoring and approaching early warning method based on radar echo is characterized in that: the method sequentially comprises the following steps:
s10: obtaining radar echo intensity data files
Acquiring a radar echo data file from a server, analyzing according to a file format, and determining relevant information of the size of a radar echo grid, an area range and longitude and latitude coordinates;
s20: extrapolating future radar echo intensities from echo intensity
According to the current echo intensity, extrapolating the radar echo intensity by adopting a semi-Lagrange extrapolation method, and generating radar echo intensity data of each specific time interval in 1-3 hours in the future;
semi-lagrange extrapolation formula
semi-Lagrange's basic equation:
Figure FDA0002604553580000011
wherein:
Figure FDA0002604553580000012
u (x, t) is a given equation, equation 1-1 indicates that scalar F is a constant value along the fluid trajectory; the actual fluid particle trajectory is in the x-t plane at tnTime of + Deltat reaches grid point xmThe trajectory of (2); the essence of the method is to perform approximate integration along an approximate fluid motion track; the following can thus be derived:
Figure FDA0002604553580000013
wherein:
αm＝ΔtU(xm-αm，tn)
wherein a ismIs the distance a particle moves on x in time Δ t as it follows the fluid trajectory; thus if we know amWe can then derive tnAt time x +. DELTA.tmThe value of F above; the key of the existing problem is to solve the problem am；tnThe predicted value of F at the end of +. t is tn-value of starting point at time Δ t; typically we select the end point (arrival point) at the grid point and the start point xm-2amIt does not necessarily fall exactly on the regular grid points of the pattern, so t is at these pointsnValue F (x) of-Deltatm-2am,tnΔ t) must be determined by interpolation or other methods from the values at the regular points;
the algorithm steps of this semi-lagrange extrapolation method are summarized as follows:
(1) using the equation for all grid points xmSolving for amWhere an initial guess is set (typically to its value at the previous time step) and interpolation is requiredA value formula;
(2) estimation of grid points x using interpolation formulam-2amAt tnF value at time Δ t;
(3) estimation of the time tn+. DELTA t end point xmF values at grid points;
s30: radar estimation of precipitation
Carrying out gridding quantitative analysis according to the radar echo intensity data of each specific time interval in 1-3 hours in the future; converting the radar echo intensity into grid precipitation of each specific time interval through a radar ZR relation formula;
radar ZR relation formula
Convection precipitation: z is 300 × R1.4;
lamellar cloud precipitation: z is 200 × R1.6;
warming precipitation: z230 × R1.25;
snowing: z is 75 × R2.0;
in the above formula, Z represents radar reflectivity, and R represents precipitation rate;
s40: determining rainstorm zone range from radar estimated precipitation statistics
Estimating precipitation according to the radar of each specific time interval of 1-3 hours in the future, and counting the precipitation of 1-3 hours in the future; judging whether rainstorm occurs in each grid in the future 1-3 hours, and recording area coordinate information of areas where the rainstorm occurs;
s50: display area warning
And displaying the rainstorm area coordinate information in the application system according to the rainstorm area coordinate information recorded in the S40.
2. The method of claim 1, wherein the method comprises the following steps: the method for displaying the area alarm in the step S50 further includes sending the information of the rainstorm area coordinate recorded in the step S40 to a mobile phone of a relevant person through a short message.
3. The method of claim 1, wherein the method comprises the following steps: each specific time interval of the step S20, the step S30, and the step S40 is any one of three, 5 minutes, 10 minutes, and 15 minutes.
CN202010734828.5A 2020-07-28 2020-07-28 Rainstorm monitoring and approaching early warning method based on radar echo Pending CN111856424A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114063082A (en) * 2021-11-15 2022-02-18 最美天气(上海)科技有限公司 Weather short-term prediction method and weather prediction system based on time sequence radar echo intensity

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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
CN106872981A (en) * 2017-02-17 2017-06-20 水利部南京水利水文自动化研究所 The precipitation strong center tracking of rainfall radar and forecasting procedure
US20170351005A1 (en) * 2016-06-02 2017-12-07 The Climate Corporation Computing radar based precipitation estimate errors based on precipitation gauge measurements
CN108535731A (en) * 2018-04-18 2018-09-14 青岛心中有数科技有限公司 It is short to face precipitation forecast method and device
CN108983323A (en) * 2018-08-08 2018-12-11 湖北河海科技发展有限公司 Precipitation forecast method and early warning platform based on optical flow method

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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
US20170351005A1 (en) * 2016-06-02 2017-12-07 The Climate Corporation Computing radar based precipitation estimate errors based on precipitation gauge measurements
CN106872981A (en) * 2017-02-17 2017-06-20 水利部南京水利水文自动化研究所 The precipitation strong center tracking of rainfall radar and forecasting procedure
CN108535731A (en) * 2018-04-18 2018-09-14 青岛心中有数科技有限公司 It is short to face precipitation forecast method and device
CN108983323A (en) * 2018-08-08 2018-12-11 湖北河海科技发展有限公司 Precipitation forecast method and early warning platform based on optical flow method

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
伊凡: "基于半拉格朗日方法的雷达图像运动分析", 《中国优秀博硕士学位论文全文数据库(硕士)信息科技辑》 *
李娜等: "两种基于雷达的临近预报算法在赣江流域的应用", 《气象科学》 *
李致家等: "《现代水文模拟与预报技术》", 31 October 2010, 河海大学出版社 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114063082A (en) * 2021-11-15 2022-02-18 最美天气(上海)科技有限公司 Weather short-term prediction method and weather prediction system based on time sequence radar echo intensity

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