CN107064937A - A kind of measuring method of Dual-linear polarization radar system and strong rain - Google Patents
A kind of measuring method of Dual-linear polarization radar system and strong rain Download PDFInfo
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- CN107064937A CN107064937A CN201710419743.6A CN201710419743A CN107064937A CN 107064937 A CN107064937 A CN 107064937A CN 201710419743 A CN201710419743 A CN 201710419743A CN 107064937 A CN107064937 A CN 107064937A
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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
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
- G01W1/00—Meteorology
- G01W1/10—Devices for predicting weather conditions
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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
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- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
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Abstract
The invention discloses a kind of Dual-linear polarization radar system, including data base module, strong storm pretreatment module, Data Matching and identification module, strong storm processing module, Data correction module and strong storm warning module；Using the efficient communication network application satellite navigation system being adapted with Weather Radar Network, realized with radar network composite to synchronous and the structure that becomes more meticulous the synergistic observation of a wide range of or a specific region weather system the time and space；High-resolution GIS information is combined with synergistic observation, the time and space and quantitative uniformity of radar network observation is realized, improves the ability to the diastrous weather monitoring and warning such as strong rain；Additionally provide a kind of measuring method of corresponding utilization Dual-linear polarization radar system network to the strong rain in plateau simultaneously.
Description
Technical field：
A kind of survey the present invention relates to Dual-linear polarization radar system and using Dual-linear polarization radar system network to the strong rain in plateau
Amount method.
Background technology：
Qinghai-Tibet Platean constitutes about the 1/4 of China's land area, more than mean sea level 4km, is that most tall and big, landform is most in the world
Complicated plateau, is described as the roof of the world.Qinghai-Tibet unique orographic condition is made it have different from plains region and general
The weather characteristics in mountain region.In 1970s and the nineties, China once organized large-scale field section twice to Qinghai-Tibet Platean
Experiment is learned, very important achievement is achieved.To the Circulation Features of highlands, weather system, geothermal source property, plateau monsoon,
South Asia high etc. has carried out more in-depth study, the fact that disclose many new, is Qinghai-Tibet further synoptic climate
Important basis has been established in research.Into after 21 century, under the global Climatic persistently warmed, extreme weather event
Frequently cause the highest attention of domestic and international expert；Particularly in highlands, multiple strong convective weather is to highway, iron
Road and communication etc. cause serious direct harm, and the development to social economy constitutes serious threat.Occur in west within 2013
The heavy snowfall process for hiding plateau causes the interruption of communication of locality, and many places Architectural Equipment is ruined, and greatly affected the normal of people
Live and work.In the case where frequent occur of this strong weather and synoptic climate require seamless forecast, people are to strong convection
The problem of weather and its short forecasting, is just particularly paid close attention to.
China is influenceed very significantly, people's flood season various weather systems to be entered every year frequently in various regions activity, are by monsoon climate
Cause the main cause of meteorological disaster.Detectivity for different scale weather system weather radar is different weather radars
Also the problem of some letters are to be solved is exposed.Be mainly manifested in middle low-level vertical resolution ratio it is relatively low in mountainous region especially
High mountain radar station causes, distance less than normal to atmospheric boundary layer monitoring range and velocity ambiguity using swept-volume pattern, big to clear sky
There is more apparent deviation, networking and association in gas and the monitoring capability of the weak echo in weather system early-stage development deficiency, Precipitation estimation
With problems such as scarce capacities.
The content of the invention：
The technical problems to be solved by the invention are that the shortcoming existed for above-mentioned prior art is double there is provided one kind
Linear polarization radar system and using Dual-linear polarization radar system network to the measuring method of the strong rain in plateau.
The technical scheme adopted by the invention to solve the technical problem is that：A kind of Dual-linear polarization radar system, using with day
The adaptable efficient communication network application satellite navigation system of gas radar fence, is realized to an a wide range of or spy with radar network composite
Determine synchronous and the structure that becomes more meticulous the synergistic observation of the time and space of area weather system.By high-resolution GIS information and association
It is combined with observation, realizes the time and space and quantitative uniformity of radar network observation, improve to diastrous weathers such as strong rain
The ability of monitoring and warning.
The Dual-linear polarization radar system includes data base module, strong storm pretreatment module, Data Matching and identification
Module, strong storm processing module, Data correction module and strong storm warning module.
Further, data base module is used for system journal, forecast score, operation flow and weather background and individual example
Storehouse.
Preferably, the system journal unit, for automatic production record running situation, including network connection situation, money
There is intact survey during the automatic collection of material；It is automatic by messagewindow, alarm song mode according to Time And Event set in advance
Carry out information alert；Forecast score unit, is commented for carrying out WS to different type strong convective weather Application in Potential Prediction and short forecasting
Subsystem, assessment and assay can be inquired about and shown with graphics context mode, and wherein WS points-scoring systems are to utilize and weather thunder
The points-scoring system for the Dual-linear polarization radar system network set up up to the adaptable efficient communication network application satellite navigation system of net；
Operation flow illustrates unit, for by the Making programme of short forecasting early warning, material particular, application affairs processing method and being
System operating instruction is checked at any time with graphics context mode for operator on duty；Weather background and individual example storehouse, it is strong according to different types of history
Convection current example data, intensity, scope, path, the extent of injury and the various Weather Elements letter of comprehensive analysis strong convective weather process
Breath, its origin cause of formation of comprehensive descision sets up strong convection disaster example database；The live material of strong convective weather can be differentiated,
Automatic or manual mode is extracted strong convective weather live material and can be put in storage automatically；Make rational planning for strong convection disaster example database
Database table structure, data base querying and maintenance are integrated in system.
Further, strong storm pretreatment module include scanning submodule, observation submodule and apart from speed parameter
Submodule.
Preferably, the scanning submodule, the increase scanning elevation angle and RHI observation scan patterns, low-level vertical point in raising
Resolution；Submodule is observed, high mountain observation mode is set up, strengthens atmospheric boundary layer detectivity；Distance and speed parameter submodule,
Appropriately distance and the parameter configuration of speed detection are set up, the optimal detection of distance and speed is realized.
Further, the Data Matching and identification module, transfer weather background and individual example storehouse, can be to strong convective weather
Live material is differentiated that automatic or manual mode extracts strong convective weather live material and is identified and matches, with forecast
Guide, forecasting model operation function are analyzed, forecast analysis guide guiding forecaster calls various weather casters successively on request, and
Carry out subjective analysis, it is to avoid the blindness and subjectivity of analysis, forecasting model operation is the various meteorological datas of integrated use, is obtained
Predictor, carries out figure identification, similar differentiation, reasoning and judging or empirical equation, and answering by Model Products interpretation technique
With using strong convective weather diagnostic analysis result, tentatively realizing the quick identification to diastrous weather system, obtain subregional
Strong convective weather Application in Potential Prediction result.
Further, the strong storm processing module, Three-Dimensional Dynamic processing and the storage behaviour for carrying out the strong rain of plateau particularity
Make.
Further, the Data correction module, the automatic Weather Station for combining to form Dual-linear polarization radar system network carries out data
Matching and correction, error is reduced to hundred meters of scopes.
Further, the strong storm warning module, with forecast analysis guide, Objective forecasting method function, with strong right
Flow Application in Potential Prediction similar, forecast analysis guide guiding forecaster calls various weather casters successively on request, and carries out subjective point
Analysis, using the data collected and pre-processed in data collection and pretreatment module, obtains predictor, carries out figure identification, phase
Know differentiation, reasoning and judging or substitute into prognostic equation, draw area and the forecast of intensity of subregional strong convective weather generation, concurrently
Go out early warning prompting.
Present invention also offers a kind of measuring method of utilization Dual-linear polarization radar system network to the strong rain in plateau, wherein, it is double
What linear polarization netted radar system was utilized is above-mentioned Dual-linear polarization radar system.
The present invention is due to taking above-mentioned technical proposal, and it has the advantages that：
Dual-linear polarization radar system of the present invention and the survey using Dual-linear polarization radar system network to the strong rain in plateau
Amount method, which overcome mountainous region's especially plateau radar station is caused to atmospheric boundary layer monitoring range using swept-volume pattern
Less than normal, distance and velocity ambiguity, the monitoring capability deficiency to the weak echo in Cloudless atmosphere and weather system early-stage development, precipitation
There are the problems such as more apparent deviation, networking and cooperative ability deficiency in estimation, and with more preferable effect, with wider
Application and practicality.
Brief description of the drawings：
Fig. 1 is the structural representation of Dual-linear polarization radar system of the present invention.
Fig. 2 is the schematic diagram calculation of streamline particle.
Fig. 3 is the Data correction flow chart of the strong rain in plateau.
Fig. 4 is the schematic diagram detected with reference to example to cold (warm) cutting edge of a knife or a sword.
Embodiment：
Present disclosure is described further below in conjunction with accompanying drawing.
As shown in figure 1, a kind of Dual-linear polarization radar system, should using the efficient communication network being adapted with Weather Radar Network
With satellite navigation system, realized with radar network composite synchronous to a wide range of or a specific region weather system the time and space
With the synergistic observation for the structure that becomes more meticulous.High-resolution GIS information is combined with synergistic observation, radar network observation is realized
Time and space and quantitative uniformity, improve the ability to the diastrous weather monitoring and warning such as strong rain.The Dual-linear polarization radar
System includes data base module, strong storm pretreatment module, Data Matching and identification module, strong storm processing module, data
Correction module and strong storm warning module.
Data base module is used for system journal, forecast score, operation flow and weather background and individual example storehouse.The system
System log unit, has intact during being collected automatically for automatic production record running situation, including network connection situation, data
Survey；According to Time And Event set in advance, information alert is carried out by messagewindow, alarm song mode automatically；Forecast score
Unit, for carrying out WS points-scoring systems to different type strong convective weather Application in Potential Prediction and short forecasting, is assessed and assay
It can be inquired about and be shown with graphics context mode, wherein WS points-scoring systems are to utilize the efficient communication net being adapted with Weather Radar Network
The points-scoring system for the Dual-linear polarization radar system network that network applied satellite navigation system is set up；Operation flow illustrates unit, for inciting somebody to action
Making programme, material particular, application affairs processing method and the system operatio explanation of short forecasting early warning are supplied with graphics context mode
Operator on duty checks at any time；Weather background and individual example storehouse, according to different types of history strong convection example data, comprehensive analysis is strong
Intensity, scope, path, the extent of injury and the various Weather Elements information of convection weather process, its origin cause of formation of comprehensive descision set up strong
Convection current disaster example database；The live material of strong convective weather can be differentiated, automatic or manual mode extracts strong convection
Weather information data can be simultaneously put in storage automatically；Make rational planning for the database table structure of strong convection disaster example database, by data base querying
It is integrated in maintenance in system.
Strong storm pretreatment module includes scanning submodule, observation submodule and distance and speed parameter submodule.Institute
State scanning submodule, the increase scanning elevation angle and RHI observation scan patterns, low-level vertical resolution ratio in raising；Submodule is observed, is built
Vertical high mountain observation mode, strengthens atmospheric boundary layer detectivity；Distance and speed parameter submodule, set up appropriately distance and speed
The parameter configuration of detection is spent, the optimal detection of distance and speed is realized.
Data Matching and identification module, transfer weather background and individual example storehouse, and the live material of strong convective weather can be carried out
Differentiate, automatic or manual mode extracts strong convective weather live material and is identified and matches, with forecast analysis guide, forecast
Model running function, forecast analysis guide guiding forecaster calls various weather casters successively on request, and carries out subjective analysis,
The blindness and subjectivity of analysis are avoided, forecasting model operation is the various meteorological datas of integrated use, obtains predictor, is carried out
Figure identification, similar differentiation, reasoning and judging or empirical equation, and by the application of Model Products interpretation technique, utilize strong convection
Synoptic Diagnostic result, tentatively realizes the quick identification to diastrous weather system, obtains subregional strong convective weather and dives
Gesture forecast result.
Strong storm processing module, carries out the Three-Dimensional Dynamic processing and storage operation of the strong rain of plateau particularity.
The Data correction module, the automatic Weather Station for combining to form Dual-linear polarization radar system network carries out matching and the school of data
Just, error is reduced to hundred meters of scopes.
The strong storm warning module, with forecast analysis guide, Objective forecasting method function, with strong convection Application in Potential Prediction
Similar, forecast analysis guide guiding forecaster calls various weather casters successively on request, and carries out subjective analysis, utilizes data
The data of collection and pretreatment in collection and pretreatment module, obtains predictor, carries out figure identification, knows each other differentiation, reasoning
Judge or substitute into prognostic equation, draw area and the forecast of intensity of subregional strong convective weather generation, and send early warning prompting.
Present invention also offers a kind of measuring method of utilization Dual-linear polarization radar system network to the strong rain in plateau, wherein, it is double
What linear polarization netted radar system was utilized is above-mentioned Dual-linear polarization radar system.
Specific measuring method is as follows：
Step one, set up data base module, for system journal, forecast score, operation flow and weather background and
Individual example storehouse.
Step 2, strong storm pretreatment is observed scan pattern by scanning the submodule increase scanning elevation angle and RHI, improved
Middle low-level vertical resolution ratio；High mountain observation mode is set up by observing submodule, strengthens atmospheric boundary layer detectivity；By away from
From with speed parameter submodule, set up appropriately distance and the parameter configuration of speed detection, realize the optimal spy of distance and speed
Survey.
Step 3, carries out Data Matching and identification, transfers weather background and individual example storehouse, and the fact of strong convective weather can be provided
Material is differentiated that automatic or manual mode extracts strong convective weather live material and is identified and matches.
Step 4, carries out strong storm processing, carries out the Three-Dimensional Dynamic processing and storage operation of the strong rain of plateau particularity.
Step 5, carries out Data correction, and the automatic Weather Station for combining to form Dual-linear polarization radar system network carries out the matching of data
And correction, error is reduced to hundred meters of scopes.
Step 6, carries out forecast analysis guide, Objective forecasting method, using being collected in data collection and pretreatment module and
The data of pretreatment, obtains predictor, carries out figure identification, acquaintance and differentiates, reasoning and judging or substitutes into prognostic equation, draws point
Area and forecast of intensity that the strong convective weather in region occurs, and send early warning prompting.
Specifically, the strong storm processing of step 4 specifically includes process：
S41：Concentration interpolation is carried out to monitoring site data, to obtain the spatial distribution wash with watercolours of various high density rain groups in region
Dye figure；
S42：The high-precision strong rain field in region is simulated using MM5 model, the strong rain field in region includes many
Individual square data array point；
S43：Any point on any side of any square data array point is chosen as initial streamline particle, with
The initial streamline particle determines next streamline particle, and to the square data matrix that next streamline particle is passed through
Row point is split again, the like, until determining all streamline particles in the strong rain field in single timeslice, even
All streamline particles are connect to draw out the streamline in the single timeslice of strong rain field；
S44：S3 is repeated to draw out a plurality of streamline in the multiple timeslices of strong rain field, to generate static strong rain field；
S45：Track following method is used to obtain movement locus of the fluid particle in time-domain and spatial domain to generate
The strong rain field of dynamic；
S46：Rain field strong to the dynamic carries out Visualization；
S47：Figure is rendered to the spatial distribution that the high density rain is rolled into a ball and the strong rain field of the dynamic carries out Three-Dimensional Dynamic superposition
Displaying, to realize the Dynamic Display of strong rain field described in region.
Wherein, for S43 Computing Principle, reference can be made to accompanying drawing 2, first, define streamline is with the intersection point on square side
Streamline particle, it is assumed that have the square data array points of common 100*100 of 1*1km for plateau region is existing, for one of them
Square grid ABCD, using the grid as the starting point of discussion, the P points on its AB side are the streamline particle of certain point streamline, that
According to A (x1, y1), B (x2, y1) 2 points of wind direction angle and wind speed information, point P (x can be calculatedo, yo) wind speed and direction letter
Breath.With a, b represents the corresponding wind vector of A, B respectively, θ,2 points of A, B wind direction angle is represented, M, N represent the mould of A, B vector,
So following formula can be drawn by decomposing wind vector a, b：
For vector a:A=(uA,vA)=(Mcos θ, Msin θ)
For vector b:
Due to A, B, 2 points are located on the same side of square data array, then assuming that i, j：
I=(xo-x2)/(x1-x2)
J=(x1-xo)/(x1-x2)
According to interspace analytic geometry knowledge, then there is the vector p of P points：
Vector p direction is specifically and a, b are vectorial and i, j coefficient are relevant.Different p vectors mean the outlet of streamline particle
Position will be differed.If P points are with x-axis positive direction angulation counterclockwiseThen haveCosine function be：
According to further calculating, you can obtainThe size of value, be：
According to above-mentioned formula, therefore it can calculate using P points as initial streamline particle, the direction and outlet position of next streamline particle
Put on (one of other three side of square grid).
Specifically, referring to accompanying drawing 3, the Data correction of step 5 specifically includes process：
S51：By analyzing message AWSFile synchronizations or time most adjacent meteorology are observed with automatic Weather Station to be tested
Satellite data, identifies the region that strong convective weather, region Heavy Precipitation or cold, warm front cloud system occur, by these regions
The longitude and latitude that projects to where automatic Weather Station of position, there is the automatic Weather Station numbering of above-mentioned synoptic process or weather phenomenon, shape in record
Into set of sites SDS.
S52：Compare between the strong rain key element in each plateau that each website is reported in above-mentioned message AWSFile to be tested
Meteorology relation, including：The relation of dew-point temperature and vapour pressure, the relation of wind direction and wind speed during static wind, precipitation with
The relation of evaporation capacity, adds up the relation of precipitation by minute precipitation and hour；The confidence level Ar of each key element is identified according to this
(st, elem, t), Ar span is [0,100], and initial value is 100, often runs counter to a kind of meteorology relation, and Ar value is reduced
10.For the strong rain key element in plateau (such as extreme wind speed, instantaneous wind speed) that can be checked without meteorology relation, Ar initial values are assigned
It is worth for 0.Wherein, st is site number to be tested, and elem is the strong rain key element in plateau, and t is the time for observing (or transmitting messages).
Any one website (website I might as well be defined as) is selected from the message for treating quality control inspection, with its longitude and latitude
For the center of circle, direct north is 0 degree, angularly divides eight quadrants, is searched successively in each quadrant apart from website I recently some
Individual automatic Weather Station, searches radius and is initially 10 kilometers, if the website number that can be found in certain quadrant is less than 3, radius gradually increases
Plus 10 kilometers, maximum is no more than 110 kilometers, forms a data set DS (st, qua, stx, dist), wherein, qua is that quadrant is compiled
Number, stx is adjacent sites numbering, and dist is distances of the stx apart from st (i.e. website I).
S53：Calculate in DS each strong rain key element in each plateau of website from message observe (or transmitting messages) the time it is past
In 10 minutes, in half an hour, in 1 hour, in 3 hours, in 6 hours, in 12 hours and in 24 hours change difference Dif (st,
Stx, elem, t, dt), wherein, dt is above-mentioned finger time interval (being respectively 10 minutes, 24 hours half an hour ...).With the past
Exemplified by the change difference of 10 minutes temperature, its calculating process is：Search current message (automatic Weather Station of the message to be tested before 10 minutes
The time of transmission of message is observed at intervals of 5 minutes), same station in message was subtracted before 10 minutes with the temperature of current website to be tested
The temperature of point, is as a result the change difference Dif of 10 minutes temperature in the past.5 websites in current sample data are randomly choosed, point
The temperature change feature for analysing each time interval is as shown in Figure 3.From this figure, it can be seen that the rate of temperature change of this 5 websites is each
From all in rational scope, but same past 3 hours and 12 hours, some website temperature risings, and some website temperature
Decline.If the geographical position of these websites is relatively, then the website temperature that numbering is 52106 there is suspicious.Correctly
Whether, in addition it is also necessary to further analysis in the steps below.
Using quadrant as packet unit, use interpolation algorithm calculation procedure 4) in each change difference Dif (st, stx,
Elem, t, dt) apart from website I interpolation IP (st, qua, stx, elem, t, dt).Belong to suspicious (50 for confidence level Ar<Ar
≤ 90) or wrong (Ar≤50) key element value, be not involved in interpolation calculation.The interpolation algorithm formula that this step is used for：
In above formula, n is the quantity of website in a certain quadrant Qua in data set DS；Dist is that a certain website (might as well in Qua
The distance between it is defined as I ') and website I；Avg_dist is the arithmetic mean of instantaneous value of the distance of all site-to-site I in Qua；
It is consistent described in Dif implication and step 4；Avg_dist ' is that (with website I ' for the center of circle, 10 kilometers are half on the basis of website I '
Footpath, searches for websites all in the range of this, if the website quantity searched is less than 3, radius is gradually increased to 10 kilometers, most
It is big to be no more than 110 kilometers), algorithm average value of all websites to I ' distance in the range of this.Similarly, Dif ' is to be with website I '
Benchmark, carries out the result that interpolation calculation is drawn, the interpolation formula is to the Dif of each website in its hunting zone：
In above formula, m is the quantity of website in its hunting zone on the basis of website I '；Dist ' is a certain station in the range of this
The distance between point and website I '；Dif " is the difference of a certain website Dif of itself and website I ' Dif in the range of this；Avg_
Dist ' implication is with described in epimere.
Due to there is 8 quadrants, therefore, 8 IP calculated correspond to 8 quadrants respectively.
S54：Calculate identical element in Dif (st, elem, t, dt) and each quadrant of the strong rain key element in each plateau of website I,
The difference CK (I, qua, elem, t, dt) of IP (st, qua, stx, elem, t, dt) under same time spacing case.Due to station
Point I is website to be tested, therefore, and now the qua in Dif is NULL (sky), and value is 1 to 8 to the qua in IP successively.
Analyzing the strong rain key element in each plateau in website I, (STV is regarded in CK values and the secure threshold STV of each quadrant relation
Different key elements, different zones and Various Seasonal, its threshold value are each different)：
(1) if CK<STV quadrant quantity >=7 (already described above, altogether 8 quadrants), then judge website I present elements
Quality it is credible；
(2) if CK >=STV quadrant quantity >=6, the abnormal quality of website I present elements is judged；
(3) outside both the above situation, the geographic location feature of website in CK >=STV all quadrants is further analyzed：Statistics
In DS 8 quadrants, the website in CK >=STV quadrant, how many website is present in set of sites SDS (above-mentioned " being present in "
Judgment basis be whether the site number of each website in CK >=STV quadrant is contained in set of sites SDS), if two
The common factor X of person is X >=60%, then judges that the quality of website I present elements is credible, if both common factor X are 35%≤X<
60%, then judge that the quality of website I present elements is suspicious, otherwise, is then determined as abnormal quality.
For example, it might as well assume that the website I strong rain key element in dew-point temperature plateau all meets CK in 2,3,4,5 quadrants<
STV, and CK >=STV is all met in 1,6,7,8 quadrants, now meet the situation of above-mentioned " outside both the above situation ", then analyze
1st, how many each website is present in set of sites SDS in 6,7,8 quadrants, that is, in 1,6,7,8 quadrants, how many website position
The geographic area occurred in strong weather.Assuming that the 1 of DS, 6,7, the quantity of website is respectively N1, N2, N3, N4 in 8 all quadrants, and
1st, the website in 6,7,8 all quadrants is present in set of sites SDS website quantity respectively m1, m2, m3, m4 again, then, above-mentioned friendship
Collection X computational methods be：X=(m1+m2+m3+m4)/(N1+N2+N3+N4) × 100%.
S55：It will have determined that the value for the confidence level Ar of the strong rain key element in the suspicious plateau of quality reduces 20；It will have determined that as matter
The value for measuring the confidence level Ar of the abnormal strong rain key element in plateau is assigned to 0, is no longer participate in the calculating of hereafter step；
S56：According to above-mentioned steps, complete in website I after the inspection of all strong rain key elements in plateau, return to step 3) continue to divide
Analyse next website.Until all websites complete above-mentioned flow.
S57：Now, (st, elem t) obtain once brand-new assessment (to the confidence level Ar of all key elements of all websites
It is in step 2 once to assess) in).On the basis of a little, then since first website, S52~S56 is repeated, until all websites
Complete the flow.
S58：By Ar (st, the elem, t) set as each website, the quality control mark of the strong rain key element in each plateau tried to achieve a bit
Know code.
Cold (warm) cutting edge of a knife or a sword is detected with reference to example
, can be with from reflectivity factor Echo Structure and Characteristics of Evolution using the information of the every 5~6min of radar frequent
It is to belong to the first type cold front to differentiate cold front, or Second-Type cold front！First type cold front is shown as in reflectivity factor:Echo is strong
Field distribution is spent than more uniform, typically between 25~45dBz, is distributed in the form of sheets, while to move integrally speed slow for echo, such as
Fig. 4 (a) Second-Type cold fronts, its reflectivity factor is in zonal distribution, and echo strength is typically between 35~60dBz, and echo is overall
Quickly, such as Fig. 4 (b) tends to analyze stronger convergence knot from radial velocity field in strong Second-Type cold front for movement
Structure, while also with the less contra solem structure of yardstick.Fig. 4 (c) is the typical wind field structure figure of cold front, can be analyzed from the figure
Go out cold front position intensity, the Characteristics of Evolution of cold front can be analyzed by being developed using time series.
Above content is to combine specific preferred embodiment further description made for the present invention, it is impossible to assert
The specific implementation of the present invention is confined to these explanations.For general technical staff of the technical field of the invention,
On the premise of not departing from present inventive concept, some simple deduction or replace can also be made, should all be considered as belonging to the present invention's
Protection domain.
Claims (10)
1. a kind of Dual-linear polarization radar system, it is characterised in that：Including data base module, strong storm pretreatment module, data
Matching and identification module, strong storm processing module, Data correction module and strong storm warning module；
Using the efficient communication network application satellite navigation system being adapted with Weather Radar Network, realized with radar network composite to big
Synchronous and the structure that becomes more meticulous the synergistic observation of the time and space of scope or a specific region weather system；
High-resolution GIS information is combined with synergistic observation, the time and space and quantitative one of radar network observation is realized
Cause property, improves the ability to the diastrous weather monitoring and warning such as strong rain.
2. Dual-linear polarization radar system according to claim 1, it is characterised in that：Data base module is used for system day
Will, forecast score, operation flow and weather background and individual example storehouse.
3. Dual-linear polarization radar system according to claim 2, it is characterised in that：The system journal unit, for certainly
There is intact survey during dynamic record system running situation, including the automatic collection of network connection situation, data；According to set in advance
Time And Event, information alert is carried out by messagewindow, alarm song mode automatically；Forecast score unit, for inhomogeneity
Type strong convective weather Application in Potential Prediction and short forecasting carry out WS points-scoring systems, and assessment and assay can be inquired about and with picture and text
Mode shows that wherein WS points-scoring systems are to utilize the efficient communication network application satellite navigation system being adapted with Weather Radar Network
The points-scoring system of the Dual-linear polarization radar system network of establishment；Operation flow illustrates unit, for by the making of short forecasting early warning
Flow, material particular, application affairs processing method and system operatio explanation are checked at any time with graphics context mode for operator on duty；My god
Gas background and individual example storehouse, according to different types of history strong convection example data, the intensity of comprehensive analysis strong convective weather process,
Scope, path, the extent of injury and various Weather Elements information, its origin cause of formation of comprehensive descision set up strong convection disaster example database；
The live material of strong convective weather can be differentiated, automatic or manual mode extracts strong convective weather live material and can be automatic
Storage；Make rational planning for the database table structure of strong convection disaster example database, data base querying and maintenance are integrated in system.
4. Dual-linear polarization radar system according to claim 1, it is characterised in that：The strong storm pretreatment module includes
Scan submodule, observation submodule and distance and speed parameter submodule.
5. Dual-linear polarization radar system according to claim 4, it is characterised in that：The scanning submodule, increase scanning
The elevation angle and RHI observation scan patterns, low-level vertical resolution ratio in raising；Submodule is observed, high mountain observation mode is set up, enhancing is big
Gas boundary layer detectivity；Distance and speed parameter submodule, set up appropriately distance and the parameter configuration of speed detection, realize
The optimal detection of distance and speed.
6. Dual-linear polarization radar system according to claim 1, it is characterised in that：The Data Matching and identification module,
Weather background and individual example storehouse are transferred, the live material of strong convective weather can be differentiated, automatic or manual mode is extracted strong right
Stream weather information data is identified and matched, with forecast analysis guide, forecasting model operation function, and forecast analysis is to guiding
Lead forecaster and call various weather casters successively on request, and carry out subjective analysis, it is to avoid the blindness and subjectivity of analysis, in advance
It is the various meteorological datas of integrated use to report model running, obtains predictor, carries out figure identification, similar differentiation, reasoning and judging
Or empirical equation, and by the application of Model Products interpretation technique, using strong convective weather diagnostic analysis result, preliminary realization pair
The quick identification of diastrous weather system, obtains subregional strong convective weather Application in Potential Prediction result；The strong storm handles mould
Block, carries out the Three-Dimensional Dynamic processing and storage operation of the strong rain of plateau particularity；The Data correction module, combines to form two-wire inclined
Shake netted radar system automatic Weather Station carry out data matching and correction, error is reduced to hundred meters of scopes.
7. the Dual-linear polarization radar system according to any one of claim 1~6, it is characterised in that：The strong storm early warning
Module, similar with strong convection Application in Potential Prediction with forecast analysis guide, Objective forecasting method function, forecast analysis guide guiding
Forecaster calls various weather casters successively on request, and carries out subjective analysis, is received using in data collection and pretreatment module
The data for collecting and pre-processing, obtains predictor, carries out figure identification, acquaintance differentiation, reasoning and judging or substitution prognostic equation, obtains
Go out area and forecast of intensity that subregional strong convective weather occurs, and send early warning prompting.
8. a kind of utilization Dual-linear polarization radar system network is to the measuring method of the strong rain in plateau, it is characterised in that utilize claim 1
The Dual-linear polarization radar system network of Dual-linear polarization radar system component described in~7 any one, is mutually fitted using with Weather Radar Network
The efficient communication network application satellite navigation system answered, is realized to an a wide range of or specific region weather system with radar network composite
Synchronous and the structure that becomes more meticulous the synergistic observation of the time and space of system.
9. measuring method according to claim 8, it is characterised in that：Strong storm processing specifically includes process：
S41：Concentration interpolation is carried out to monitoring site data, rendered with the spatial distribution for obtaining various high density rain groups in region
Figure；
S42：The high-precision strong rain field in region is simulated using MM5 model, the strong rain field in region include it is multiple just
Square data array point；
S43：Any point on any side of any square data array point is chosen as initial streamline particle, with described
Initial streamline particle determines next streamline particle, and the square data array point passed through to next streamline particle
Split again, the like, until determining all streamline particles in the strong rain field in single timeslice, connect institute
There is streamline particle to draw out the streamline in the single timeslice of strong rain field；
S44：S3 is repeated to draw out a plurality of streamline in the multiple timeslices of strong rain field, to generate static strong rain field；
S45：Track following method is used to obtain movement locus of the streamline particle in time-domain and spatial domain to generate dynamic
Strong rain field；
S46：Rain field strong to the dynamic carries out Visualization；
S47：Figure is rendered to the spatial distribution that the high density rain is rolled into a ball and the strong rain field of the dynamic carries out Three-Dimensional Dynamic superposition displaying,
To realize the Dynamic Display of strong rain field described in region.
10. measuring method according to claim 9, it is characterised in that：Data correction specifically includes process：
S51：By analyzing message AWSFile synchronizations or time most adjacent meteorological satellite are observed with automatic Weather Station to be tested
Data, identifies the region that strong convective weather, region Heavy Precipitation or cold, warm front cloud system occur, by the position in these regions
The longitude and latitude projected to where automatic Weather Station is put, record has the automatic Weather Station numbering of above-mentioned synoptic process or weather phenomenon, forms station
Point set SDS；
S52：Compare the gas between the strong rain key element in each plateau that each website is reported in above-mentioned message AWSFile to be tested
As learning relation；
Any one website (website I might as well be defined as) is selected from the message for treating quality control inspection, using its longitude and latitude as circle
The heart, direct north is 0 degree, angularly divides eight quadrants, is searched successively in each quadrant apart from nearest several of website I certainly
Dynamic station, searches radius and is initially 10 kilometers, if the website number that can be found in certain quadrant is less than 3, radius gradually increases by 10
Kilometer, maximum is no more than 110 kilometers, forms a data set DS (st, qua, stx, dist), wherein, qua is quadrant number,
Stx is adjacent sites numbering, and dist is distances of the stx apart from st (i.e. website I)；
S53：Calculate each strong rain key element in each plateau of website in DS and observing (or transmitting messages) past 10 points the time from message
In clock, in half an hour, in 1 hour, in 3 hours, in 6 hours, in 12 hours and in 24 hours change difference Dif (st, stx,
Elem, t, dt), wherein, dt is time interval (being respectively 10 minutes, 24 hours half an hour ...)；
Using quadrant as packet unit, use interpolation algorithm calculation procedure 4) in each change difference Dif (st, stx, elem, t,
Dt) apart from website I interpolation IP (st, qua, stx, elem, t, dt)；Belong to suspicious (50 for confidence level Ar<Ar≤90) or
The key element value of mistake (Ar≤50), is not involved in interpolation calculation.The interpolation algorithm formula that this step is used for：
In above formula, n is the quantity of website in a certain quadrant Qua in data set DS；Dist is that a certain website (might as well be defined in Qua
The distance between for I ') and website I；Avg_dist is the arithmetic mean of instantaneous value of the distance of all site-to-site I in Qua；Dif's
It is consistent described in implication and step 4；Avg_dist ' is that (with website I ' for the center of circle, 10 kilometers are radius, are searched on the basis of website I '
Rope should in the range of all website, if the website quantity searched is less than 3, radius is gradually increased to 10 kilometers, most very much not
More than 110 kilometers), algorithm average value of all websites to I ' distance in the range of this；Similarly, Dif ' is for base with website I '
Standard, carries out the result that interpolation calculation is drawn, the interpolation formula is to the Dif of each website in its hunting zone：
In above formula, m is the quantity of website in its hunting zone on the basis of website I '；Dist ' be in the range of this certain website with
The distance between website I '；Dif " is the difference of a certain website Dif of itself and website I ' Dif in the range of this；Avg_dist’
Implication with described in epimere；
S54：Calculate the Dif (st, elem, t, dt) of the strong rain key element in each plateau of website I and identical element in each quadrant, it is identical
The difference CK (I, qua, elem, t, dt) of IP (st, qua, stx, elem, t, dt) in the case of time interval；Because website I is
Website to be tested, therefore, now the qua in Dif is NULL (sky), and value is 1 to 8 to the qua in IP successively；Analyze website
In CK values and the secure threshold STV of each quadrant relation, (STV regards different key elements, different zones to the strong rain key element in the plateau of each in I
And Various Seasonal, its threshold value is each different)；
S55：It will have determined that the value for the confidence level Ar of the strong rain key element in the suspicious plateau of quality reduces 20；To have determined that for quality it is different
The confidence level Ar of the strong rain key element in normal plateau value is assigned to 0, is no longer participate in the calculating of hereafter step；
S56：According to above-mentioned steps, complete in website I after the inspection of all strong rain key elements in plateau, return to step 3) continue under analyzing
One website.Until all websites complete above-mentioned flow；
S57：Now, (st, elem t) obtain once brand-new assessment (for the first time to the confidence level Ar of all key elements of all websites
Assessment is in step 2) in)；On the basis of a little, then since first website, S52~S56 is repeated, until all websites are completed
The flow；
S58：By Ar (st, the elem, t) set as each website, the quality control identification code of the strong rain key element in each plateau tried to achieve a bit.
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