CN105759274A - Typhoon attention area radar rainfall estimation method - Google Patents
Typhoon attention area radar rainfall estimation method Download PDFInfo
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- CN105759274A CN105759274A CN201610263226.XA CN201610263226A CN105759274A CN 105759274 A CN105759274 A CN 105759274A CN 201610263226 A CN201610263226 A CN 201610263226A CN 105759274 A CN105759274 A CN 105759274A
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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
- 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
- G01S13/95—Radar or analogous systems specially adapted for specific applications for meteorological use
- G01S13/958—Theoretical aspects
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- Y—GENERAL 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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Abstract
The invention disclosed a typhoon attention area radar rainfall estimation method. The method adopts an intersection correlation tracking algorithm to carry out estimation. Dynamic configuration is performed on an area division value in the intersection correlation tracking algorithm through using the following method and the method comprises the following steps of calculating f(x), wherein the f(x) satisfies an equation defined in the description and the x is a radar elevation angle; and (2) carrying out rounding off on the f(x) so as to acquire the area division value. In the invention, through carrying out dynamic configuration on the radar elevation angle and the area division value, according to a specific condition of a typhoon attention area, correlation parameters can be properly changed, and movement of an echo is accurately calculated so as to estimate rainfall of the typhoon attention area.
Description
Technical field
The invention belongs to radar pinch-reflex ion diode Applied research fields, be specifically related to a kind of typhoon and pay close attention to district's radar precipitation estimating and measuring method.
Background technology
Crosscorrelation tracing algorithm is used to follow the trail of the algorithm of a kind of comparative maturity that radar return moves.Utilize the method seeking maximum correlation coefficient, it is possible to set up the best fit relation between trace regions.By calculate the trace regions in radar scanning moment and front one scan moment with the change of position between its region mated most, determine the movement of echo.This mobile vector is utilized to go prediction echo in the position of subsequent time.
But the changeless elevation angle configuration that the crosscorrelation tracing algorithm of China's China New Generation Weather Radar adopts at present and CAPPI contour plane height, and in reflectivity factor matrix, region divide value is also changeless.Chinese Regional is wide, and each department terrain differences is very big, and with seasonal variations, whether preset parameter is applicable to various places environment is also worth discussion.
Summary of the invention
The invention aims to solve the defect that prior art exists, it is provided that a kind of carry out the radar elevation angle, precipitation estimation method that region divide value dynamically configures, the movement of Accurate Estimation echo, thus estimating typhoon to pay close attention to the precipitation in district.
In order to achieve the above object, the invention provides a kind of typhoon and pay close attention to district's radar precipitation estimating and measuring method, the method adopts crosscorrelation tracing algorithm to estimate；Wherein, the region divide value in crosscorrelation tracing algorithm adopts following methods to carry out dynamically configuration:
(1) f (x) is calculated,, wherein, x is the radar elevation angle；
(2) f (x) is carried out round, obtain described region divide value.
The radar elevation angle in crosscorrelation tracing algorithm carries out three grades of elevation angle configurations according to radar position.Being set to the center of circle so that radar is in place, if there being chevron obstacle within j kilometer, then using 3.4 ° of elevations angle；There is chevron obstacle beyond j kilometer, within k kilometer, then use 2.4 ° of elevations angle；There is chevron obstacle beyond k kilometer, then use 1.5 ° of elevations angle.Wherein, j value is 15-25, k value is 40-50.
CAPPI contour plane height in crosscorrelation tracing algorithm is set between 3-3.6km.Concrete arrange by user's height guiding air-flow according to a certain weather system, specify should the CAPPI contour plane height of height layer voluntarily.The guide layer of most of precipitation systems is 700hPa, this highly corresponding 3-3.6km.
Typhoon of the present invention pays close attention to district's radar precipitation estimating and measuring method, specifically comprises the following steps that
(1) read radar data secondary time former and later two, and the polar data of radar is processed into Descartes's rectangular coordinate data；
(2) pay close attention to the feature of district's landform according to typhoon, configure the above-mentioned radar elevation angle；
(3) CAPPI contour plane height is read；
(4) according to the radar elevation angle, dynamic configuring area divide value；
(5) being divided by above-mentioned zone divide value the reflectivity factor field of radar scanning, be divided into several sizable " regions ", these " regions " have identical horizontal scale；Reflectivity factor in " region " is Z1(i), subsequent time t2(t2=t1Reflectivity factor in+Δ t) " region " becomes Z2(i), then by these at t1" region " in moment respectively with subsequent time t2Search radius each " region " make crosscorrelation, namely seek Z1With Z2Cross-correlation R, be expressed as:
In formula, Z1And Z2Respectively a certain " region " interior t1And t2Moment reflectivity factor matrix, n is the number of data points of matrix；The correlation coefficient of two matrixes of interval of delta t time can be obtained by above formula, repeat this process, until finding maximum correlation coefficient, now, the center pointing to T+ Δ t rectangular area from the center of T moment rectangular area is CTREC vector (motion vector of echo)；
(6) smoothing processing and extrapolation: before this wind field was smoothed so that substantially the point of distortion wind field meansigma methods about replaces；Then extrapolation wind field in addition level is limited without divergence so that it is meet continuity equation；And it is extrapolated to whole echo field；
(7) the echo field according to extrapolation, by according to the relational expression pinch-reflex ion diode between radar reflectivity factor and precipitation intensity:
If 1 hourly rainfall depth record of all pluviometer observation adds up to N, pluviometer observation GnRepresent, n=1,2,3 ... n, to the n-th rainfall value Gn, have M the radar echo intensity Z that space-time is corresponding with itdBnm, m=1,2,3...M, according to the relation between radar reflectivity factor and precipitation intensity, by ZdBnmIt is converted into precipitation intensity Inm, namely
(2)
Wherein, between radar reflectivity factor and precipitation intensity, parameter A and the b of relation is so that radar estimated value approaches the optimized parameter of measured value most.The value followed the example of as constantly adjusting parameter A and the b in formula (2) of A and b, until discriminant function CTFTill reaching minima.Wherein, best discriminant function CTFFor
(3)
I in formulaiFor the raininess value of each sample that radar is estimated, RiFor the raininess value that automatic rainfall station is measured.
The present invention has the advantage that the present invention is by dynamically configuring the radar elevation angle, region divide value compared to existing technology, such that it is able to the concrete condition according to typhoon concern district suitably changes relevant parameter, the movement of Accurate Estimation echo, and in conjunction with radar pinch-reflex ion diode technology, the extrapolating results of CTREC being carried out extrapolation estimation, the estimation result obtained is more accurate.Adopting estimating and measuring method of the present invention to the motility of Wind-field Retrieval method to be one well to supplement, it can play a role in instructing Small and Medium Sized forecast.
Accompanying drawing explanation
Fig. 1 is the flow chart that typhoon of the present invention pays close attention to district's radar precipitation estimating and measuring method；
The estimation result that Fig. 2 is in embodiment compares figure with fact.
Detailed description of the invention
Below in conjunction with accompanying drawing, the present invention is described in detail.
Embodiment 1
The data in certain city on August 1st, 2011 that typhoon pays close attention to district is carried out radar precipitation estimation, as it is shown in figure 1, specifically comprise the following steps that
Step 1: read radar data secondary during two before and after 6 minutes.
Step 2: carry out Coordinate Conversion, exports matrix data secondary when two.
Step 3: according to the feature of certain city's landform, has background return within its 20km, should not use the low layer elevation angle；Background return is can't detect beyond 45km.Therefore, configure rule (using 3.4 ° of elevations angle within 20km, 20-45km uses 2.4 ° of elevations angle, uses 1.5 ° of elevations angle beyond 45km) according to the radar elevation angle and adopt 3.4 ° of elevations angle.
Step 4: through the consideration to this concern district landform and the height guiding air-flow summer, arranging CAPPI contour plane height is 3.3km.
Step 5: according to radar elevation angle configuring area divide value.
(1) f (x) is calculated,, wherein, x is the radar elevation angle；
(2) f (x) is carried out round, obtain region divide value.
Step 6: by region divide value, data secondary during according to formula (1) to two carry out related operation, and output motion vector is also extrapolated to whole echo field.
Step 7: the echo field according to extrapolation, by according to the relational expression pinch-reflex ion diode between radar reflectivity factor and precipitation intensity.
Adopt the result of said method extrapolation and live contrast, as in figure 2 it is shown, it can be seen that extrapolation effect substantially conforms to.
Claims (4)
1. typhoon pays close attention to district's radar precipitation estimating and measuring method, and the method adopts crosscorrelation tracing algorithm to estimate；It is characterized in that, the region divide value in described crosscorrelation tracing algorithm adopts following methods to carry out dynamically configuration:
(1) f (x) is calculated,, wherein, x is the radar elevation angle；
(2) f (x) is carried out round, obtain described region divide value.
2. typhoon pays close attention to district's radar precipitation estimating and measuring method according to claim 1, it is characterized in that, the radar elevation angle in described crosscorrelation tracing algorithm adopts following methods to carry out dynamically configuration: carry out three grades of elevation angle configurations according to radar position, it is set to the center of circle so that radar is in place, if there being chevron obstacle within j kilometer, then use 3.4 ° of elevations angle；There is chevron obstacle beyond j kilometer, within k kilometer, then use 2.4 ° of elevations angle；There is chevron obstacle beyond k kilometer, then use 1.5 ° of elevations angle；Wherein, j value is 15-25, k value is 40-50.
3. typhoon pays close attention to district's radar precipitation estimating and measuring method according to claim 2, it is characterised in that the CAPPI contour plane height in described crosscorrelation tracing algorithm is set between 3-3.6km.
4. typhoon pays close attention to district's radar precipitation estimating and measuring method according to claim 3, it is characterised in that comprise the following steps:
(1) read radar data secondary time former and later two, and the polar data of radar is processed into Descartes's rectangular coordinate data；
(2) pay close attention to the feature of district's landform according to typhoon, configure the described radar elevation angle；
(3) described CAPPI contour plane height is read；
(4) according to the described radar elevation angle, described region divide value is dynamically configured；
(5) being divided by described region divide value the reflectivity factor field of radar scanning, be divided into several sizable " regions ", these " regions " have identical horizontal scale；Reflectivity factor in " region " is Z1(i), subsequent time t2(t2=t1Reflectivity factor in+Δ t) " region " becomes Z2(i), then by these at t1" region " in moment respectively with subsequent time t2Search radius each " region " make crosscorrelation, namely seek Z1With Z2Cross-correlation R, be expressed as:
In formula, Z1And Z2Respectively a certain " region " interior t1And t2Moment reflectivity factor matrix, n is the number of data points of matrix；Can being obtained the correlation coefficient of two matrixes of interval of delta t time by above formula, repeat this process, until finding maximum correlation coefficient, now, the center pointing to T+ Δ t rectangular area from the center of T moment rectangular area is CTREC vector；
(6) smoothing processing and extrapolation: before this wind field was smoothed so that substantially the point of distortion wind field meansigma methods about replaces；Then extrapolation wind field in addition level is limited without divergence so that it is meet continuity equation；And it is extrapolated to whole echo field；
(7) the echo field according to extrapolation, by according to the relational expression pinch-reflex ion diode between radar reflectivity factor and precipitation intensity:
If 1 hourly rainfall depth record of all pluviometer observation adds up to N, pluviometer observation GnRepresent, n=1,2,3 ... n, to the n-th rainfall value Gn, have M the radar echo intensity Z that space-time is corresponding with itdBnm, m=1,2,3...M, according to the relation between radar reflectivity factor and precipitation intensity, by ZdBnmIt is converted into precipitation intensity Inm, namely
(2)
Wherein, between radar reflectivity factor and precipitation intensity, parameter A and the b of relation is so that radar estimated value approaches the optimized parameter of measured value most；The value followed the example of as constantly adjusting parameter A and the b in formula (2) of A and b, until discriminant function CTFTill reaching minima；Wherein, best discriminant function CTFFor
(3)
I in formulaiFor the raininess value of each sample that radar is estimated, RiFor the raininess value that automatic rainfall station is measured.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106950543A (en) * | 2017-02-28 | 2017-07-14 | 四川九洲电器集团有限责任公司 | One parameter configuration method and equipment |
| CN107102309A (en) * | 2017-04-28 | 2017-08-29 | 北京怡孚和融科技有限公司 | Wind field spatial distribution is converted into the method and aerosol spatial and temporal distributions of wind field time orientation and the stacking method of wind field spatial and temporal distributions |
| CN107656278A (en) * | 2017-08-31 | 2018-02-02 | 武汉中心气象台(长江流域水文气象预报台湖北省决策气象服务中心) | Based on dense precipitation station Quantitative Precipitation estimating and measuring method |
| 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 |
| CN108828691A (en) * | 2018-04-18 | 2018-11-16 | 青岛心中有数科技有限公司 | It is short to face precipitation forecast method and device |
| CN116027333A (en) * | 2023-02-24 | 2023-04-28 | 南京信息工程大学 | Method for generating three-dimensional scanning elevation angle parameters of microwave rain-measuring radar |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110267340A1 (en) * | 2010-04-29 | 2011-11-03 | Friedrich-Alexander-Universitaet Erlangen-Nuernberg | Method and apparatus for motion correction and image enhancement for optical coherence tomography |
| CN103529492A (en) * | 2013-09-22 | 2014-01-22 | 天津大学 | Storm body position and form prediction method based on Doppler radar reflectivity image |
| CN104849777A (en) * | 2014-12-08 | 2015-08-19 | 国家电网公司 | Power grid equipment area convection weather forecasting method based on cross correlation tracking method |
| CN104977584A (en) * | 2015-06-29 | 2015-10-14 | 深圳市气象台 | Convective weather approach prediction method and system |
| CN105388467A (en) * | 2015-11-03 | 2016-03-09 | 南京信息工程大学 | Method of correcting Doppler weather radar echo attenuation |
-
2016
- 2016-04-26 CN CN201610263226.XA patent/CN105759274B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110267340A1 (en) * | 2010-04-29 | 2011-11-03 | Friedrich-Alexander-Universitaet Erlangen-Nuernberg | Method and apparatus for motion correction and image enhancement for optical coherence tomography |
| CN103529492A (en) * | 2013-09-22 | 2014-01-22 | 天津大学 | Storm body position and form prediction method based on Doppler radar reflectivity image |
| CN104849777A (en) * | 2014-12-08 | 2015-08-19 | 国家电网公司 | Power grid equipment area convection weather forecasting method based on cross correlation tracking method |
| CN104977584A (en) * | 2015-06-29 | 2015-10-14 | 深圳市气象台 | Convective weather approach prediction method and system |
| CN105388467A (en) * | 2015-11-03 | 2016-03-09 | 南京信息工程大学 | Method of correcting Doppler weather radar echo attenuation |
Non-Patent Citations (3)
| Title |
|---|
| 王改利 等: "多普勒雷达资料在暴雨临近预报中的应用", 《应用气象学报》 * |
| 王改利: "暴雨回波的多尺度识别及其演变信息提取方法研究", 《中国博士学位论文全文数据库 基础科学辑》 * |
| 魏明英: "基于多普勒雷达资料的降水定量估测及其应用研究", 《中国优秀硕士学位论文全文数据库 基础科学辑》 * |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106950543A (en) * | 2017-02-28 | 2017-07-14 | 四川九洲电器集团有限责任公司 | One parameter configuration method and equipment |
| CN106950543B (en) * | 2017-02-28 | 2020-06-09 | 四川九洲电器集团有限责任公司 | Parameter configuration method and equipment |
| CN107102309A (en) * | 2017-04-28 | 2017-08-29 | 北京怡孚和融科技有限公司 | Wind field spatial distribution is converted into the method and aerosol spatial and temporal distributions of wind field time orientation and the stacking method of wind field spatial and temporal distributions |
| CN107656278A (en) * | 2017-08-31 | 2018-02-02 | 武汉中心气象台(长江流域水文气象预报台湖北省决策气象服务中心) | Based on dense precipitation station Quantitative Precipitation estimating and measuring method |
| CN107656278B (en) * | 2017-08-31 | 2020-09-11 | 武汉中心气象台(长江流域水文气象预报台湖北省决策气象服务中心) | Quantitative precipitation estimation method based on dense rainfall station |
| 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 |
| CN108828691A (en) * | 2018-04-18 | 2018-11-16 | 青岛心中有数科技有限公司 | It is short to face precipitation forecast method and device |
| CN108828691B (en) * | 2018-04-18 | 2021-06-22 | 青岛心中有数科技有限公司 | Method and device for forecasting short rainfall |
| CN116027333A (en) * | 2023-02-24 | 2023-04-28 | 南京信息工程大学 | Method for generating three-dimensional scanning elevation angle parameters of microwave rain-measuring radar |
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