CN106646476A - Inversion method for microphysical parameters of liquid cloud - Google Patents
Inversion method for microphysical parameters of liquid cloud Download PDFInfo
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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
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- 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
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- 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
- G01S7/411—Identification of targets based on measurements of radar reflectivity
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- 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
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Abstract
The invention discloses an inversion method for microphysical parameters of liquid cloud. The inversion method mainly includes the following process: according to radar reflectivity factors provided by a millimeter waves cloud radar, based on the optimal estimation theory, adopting an empirical formula calculation value as a prior value, assuming that particle spectrum submits to logarithmic normal distribution, a function relationship of radar reflectivity factors and liquid cloud physical parameters is established, and the inversion optimal solution is obtained in a condition when the difference value weighing of to-be-inverted parameters, the prior value, the radar reflectivity factors and function calculation value achieves the minimum value. Besides, according to an error transmission theory, uncertainty of liquid cloud microphysical parameters is calculated. The invention can make up a shortcoming of poor adaptability of a traditional empirical formula. Also, besides, common cloud particle diameter and cloud water content, particle concentration and distribution width can also be obtained; the inversion result is more comprehensive. Since the radar reflectivity factor in real time monitoring is adopted for prior value calculation, the inversion result accuracy is improved.
Description
Technical field
The present invention relates to a kind of reflectivity factor inverting liquid Cloud microphysical parameter of utilization millimeter wave cloud radar acquisition
Method, the inversion method of theoretical and empirical equation the liquid Cloud microphysical parameter of more particularly to a kind of combination optimal estimation.
Background technology
The distribution on global of cloud and its Microphysical Structure affect global climate and environmental change, and to the earth-Atmosphere System
Radiation budget is balanced and Water, steam circulation has important regulative, by the global Cloud Layer Character of observation, is obtained from Bao Yun to dense
The vertical section feature of cloud, inverting obtains measuring cloud water content, cloud particle size and other parameters, to climatic study, finely
Change the aspects such as synoptic process analysis, weather forecasting, weather modification significant.
With the fast development for surveying cloud, Chinese scholars deepen continuously and study the inversion method of Cloud microphysical parameter,
Achieve some application achievements.The empirical relation algorithm that traditional cloud physics parametric inversion is mainly obtained by statistical analysis has come
Into that is, based on substantial amounts of experimental data, using the mode of Function Fitting the pass of radar reflectivity and cloud physics parameter being set up
System.
Such as Atlas, Sauvageot, Kropfli and Kelly, Fox and Illingworth et al. combine 35GHz radars
Mysorethorn is worn with aircraft and surveys spectrum supplemental characteristic, obtain the functional relation between radar reflectivity and particle effective radius, liquid water content,
For exponential form;
Neil et al. has probed into the cloud water content and Effective radius size of stratus using 8mm ground cloud radars, checking
Relation between Liquid water content three in radar reflectivity factor, particle effective radius, cloud, as a result with Atlas and Sauvageot
Result coincide.
Austin and Stephens is theoretical based on optimal estimation, develops a kind of liquid Cloud microphysical based on optimal estimation
The business inversion algorithm of parameter, using priori data information, state vector (treating inverting parameter) and priori data difference with
And known measurement vectorial (radar reflectivity factor) and forward model value difference point weighting sum minimum when, obtain liquid cloud speck
Reason parameter.
The advantage of experience inverting commonly used in the prior art is to calculate simple, needs substantial amounts of detection data to be counted
Analysis, and it is different according to the difference key inverting coefficient of observation place, time and the varieties of clouds, but algorithm applicability and autgmentability
It is poor, for example, when there is drizzle precipitation in cloud, due to contribution very little of the precipitation particles to liquid water content in cloud, utilize
The result that Atlas empirical equation invertings are obtained is bigger than normal, and needs count the relational expression suitable for drizzle and light rain.Optimal estimation
Inversion accuracy is affected by priori data, and observation statistical value adopt at present for priori data, have some limitations with not
Foot.
Patent aspect, Anhui Normal University propose " one kind using A-Train series of satellites data collaborative Retrieval of Cloud phase and
The new method of cloud parameter " (publication number:CN102707336A) a kind of " cloud radar is proposed with Meteorological Observation Centre of CMA
With satellite sounding data fusion method and system " (publication number:CN105445816A), system adopts neural metwork training, sets up
The relation of bright temperature and cloud-top height, the height of cloud base and reflectivity factor;Beijing Radio Measurement research department proposes a kind of " millimeter
The data fusion method and system of ripple cloud radar " (publication number:CN104345312A), system globe area radar multi-mode working mode
The detection data for obtaining, improves the quality of data and detection efficient.Additionally, in terms of detection means, Nanjing Information engineering Univ Shen
A kind of please " cloud particle detection method and detector " (publication number:CN105115862A patent), using the scattering of cloud particle
Signal detection obtains cloud particle phase and cloud particle size;The Chinese Academy of Space Technology has applied for a kind of " ground for surveying cloud
Face Terahertz radar system " (publication number:) and a kind of " survey mysorethorn based on Terahertz active cloud detection radar CN104569980A
Experiment device and method " (publication number:CN104597454A).In the Patents for being retrieved, correlative study master both domestic and external
Cloud detecting devices or instrument are concentrated on, division unit proposes multisource data fusion processing method, the research of cloud inversion method
It is less.
The content of the invention
The radar reflectivity factor that the purpose of the present invention is provided according to millimeter wave cloud radar, it is theoretical based on optimal estimation, adopt
It is priori value with empirical equation calculated value, it is assumed that particle spectra obeys logarithm normal distribution, sets up radar reflectivity factor and liquid
The functional relation of cloud physics parameter, in the difference for treating inverting parameter and priori data and radar reflectivity factor and function value
Value weighting tries to achieve inverting optimal solution in the case of obtaining minimum of a value.
In order to realize object above, the present invention is achieved by the following technical solutions:
A kind of inversion method of liquid Cloud microphysical parameter, inversion algorithm is asked in the case where cost function obtains minimum of a value
Optimal solution is obtained, the cost function is state vector and priori data difference and known measurement vector sum forward model value difference point
Weighting sum,
In formula, xaIt is according to the calculated priori data of radar reflectivity factor, SaFor the covariance square of priori data
Battle array, F (x) for radar reflectivity factor forward physical pattern, SyIt is the covariance square of radar reflectivity factor measure error
Battle array, y is radar reflectivity factor for measurement vector, and x is that unknown state vector treats inverting parameter, described to treat inverting parameter bag
Include cloud particle number density, geometrical mean radius and dispersion of distribution parameter.
By priori data xaAs iterative initial value, cost function D is minimized by continuous, finally try to achieve and treat inverting parameter x
Iterative solution.
Preferably, it is assumed that the size distribution of the cloud particle in air meets logarithm normal distribution, radar reflection is set up according to this
The rate factor and liquid cloud physics parameter are cloud particle number density, efficient radius of cloud particle, the function of cloud particle dispersion of distribution parameter
Relation;
In formula:NTIt is cloud particle number density;R is efficient radius of cloud particle;rgIt is geometrical mean radius;σlogIt is the dispersion of distribution
Parameter, is dimensionless variable;σgFor geometric standard deviation;Ln represents natural logrithm conversion;Horizontal line is represented seeks arithmetic mean of instantaneous value.
In non-rainfall or there is light rain, or in the case of having drizzle, it is believed that cloud particle yardstick is sufficiently small, meets Rayleigh scattering
Condition, according to Liquid water content C in cloudLW, efficient radius of cloud particle reWith the definition of radar reflectivity factor Z, it is derived by down
Row formula.
In formula:ρωRepresent water density.
Preferably, the priori data xaWith the covariance matrix S of priori dataaGrain is obtained according to by historical statistical data
Subnumber density NTAnd distribution width sigmalogTo be calculated,
In formula, range bin zi;z1And znThe range bin on cloud base and cloud top in radar profile is represented respectively, and subscript a represents state
The priori value of vector x, rga、NTaAnd σlogaIt is the priori for representing efficient radius of cloud particle, Particle number concentration and the dispersion of distribution respectively
Value.
Preferably, it is efficient radius of cloud particle r by cloud particle sizee, Particle number concentration NTAnd distribution width sigmalog, calculate
Go out forward physical model F (x) of the radar reflectivity factor;
Measurement vector y and state vector x relation between the two, forward physical mould are set up by forward physical model F (x)
Formula is represented by
Y=F (x)+εy
ε in formulayRepresent measure error, ZFM(zi) it is each range bin ziRadar reflectivity factor;z1And znThunder is represented respectively
The range bin on cloud base and cloud top up in profile.
Preferably, derived by the defined formula of radar reflectivity factor and calculate each range bin ziRadar reflectivity factor
ZFM(zi);
K=(m2-1)/(m2+2)
In formula, m represents complex refractive index.Preferably, the measurement vector y is with unknown state vector x
In formula:ZdB(zi)、rg(zi)、NT(zi) and σlog(zi) represent respectively radar reflectivity factor, geometrical mean radius,
Cloud particle number density and dispersion of distribution parameter are in range bin ziThe value at place;N represents the cloud range bin number in profile.
Preferably for profile is observed per bar, state vector x is to treat inverting parameter in each range bin, it is known that measurement
Vectorial y only has the radar reflectivity factor in respective distances storehouse, needs by priori data xaRow constraint is entered to inverting, it is ensured that repeatedly
Withhold hold back and inversion result reliability.
Preferably, it is described by priori data xaAs iterative initial value, cost function D is minimized by continuous, try to achieve and treat anti-
The iterative solution of parameter x is drilled, and the condition of convergence of iteration is met when calculating is iterated;
In formula:Subscript i and i+1 represent iterations, and L represents sensitivity of the forward physical pattern to state vector x.
Preferably, the condition of convergence of the iteration is:
In formula:SxThe error co-variance matrix of iterative state vector, represent three variances for treating inverting physical quantity and
Covariance between each parameter, SyIt is the covariance matrix of radar reflectivity factor measure error.
Compared with prior art, present invention has the advantages that:
The present invention can make up traditional empirical equation shortcoming poor for applicability, and except common cloud particle radius and cloud
Water content, is also obtained Particle number concentration and the dispersion of distribution, and the result for arriving of inverting is more fully;As a result of sight in real time
The radar reflectivity factor of survey improves inversion result accuracy calculating priori value.
Description of the drawings
Fig. 1 is a kind of flow chart of the inversion method of liquid Cloud microphysical parameter of the invention;
Fig. 2 be a kind of inversion method of liquid Cloud microphysical parameter of the invention one embodiment in the cloud particle half that adopts
Footpath priori data schematic diagram;
Fig. 3 be a kind of inversion method of liquid Cloud microphysical parameter of the invention one embodiment in the liquid that obtains of inverting
Cloud microphysical parameter schematic diagram.
Specific embodiment
Below in conjunction with accompanying drawing, by describing a preferably specific embodiment in detail, the present invention is further elaborated.
Millimeter wave cloud radar utilizes scattering properties of the cloud particle to electromagnetic wave, and by the analysis on radar echoes to cloud cloud is understood
Both macro and micro characteristic, you can detection diameter from several microns to weak precipitation particles, the vertical section of continuous detection cloud.Echo is strong
Degree reflects the size and concentration of particle in cloud, and echo strength change over time and space reflects cloud micro-physical process and drills
Become feature.The reflectivity factor that radar is surveyed is pre-processed, you can obtain continuous, effective profile in the domain of cloud sector and
Section echo data, and its control information.
As shown in figure 1, a kind of inversion method of liquid Cloud microphysical parameter,
Inversion algorithm tries to achieve optimal solution in the case where cost function obtains minimum of a value, and the cost function is state vector
The weighting sum divided with priori data difference and known measurement vector sum forward model value difference,
In formula, xaIt is according to the calculated priori data of radar reflectivity factor, SaFor the covariance square of priori data
Battle array, F (x) for radar reflectivity factor forward physical pattern, SyThe covariance matrix of radar measurement errors, y for measurement to
Amount is radar reflectivity factor, and x is that unknown state vector treats inverting parameter, described to treat that inverting parameter includes that cloud particle subnumber is close
Degree, geometrical mean radius and dispersion of distribution parameter.
By priori data xaAs iterative initial value, cost function D is minimized by continuous, finally try to achieve and treat inverting parameter x
Iterative solution.
Assume that the size distribution of cloud particle in air meets logarithm normal distribution, set up according to this radar reflectivity factor with
Liquid cloud physics parameter is cloud particle number density, efficient radius of cloud particle, the functional relation of cloud particle dispersion of distribution parameter;
In formula:NTIt is cloud particle number density;R is efficient radius of cloud particle;rgIt is geometrical mean radius;σlogIt is the dispersion of distribution
Parameter, is dimensionless variable;σgFor geometric standard deviation;Ln represents natural logrithm conversion;Horizontal line is represented seeks arithmetic mean of instantaneous value.
For priori data is obtained and is calculated, rule of thumb formula, by the radar effective reflectivity factor cloud particle is calculated
Sub- radius and liquid water content.Forefathers using cloud radar and other cloud particles spectrum detecting devices, measure cloud particle drop-size distribution distribution,
Liquid water content in Particle number concentration, particle effective radius and cloud, the statistical fit for carrying out mass data draws cloud radar inverting
The empirical relation of particle radii and aqueous water, draws the conventional empirical equation of classics,
Z=138 × 10-12D6 (4)
Wherein CLWLiquid water content in cloud is represented, D is particle diameter, and Z is the radar reflectivity that millimeter wave cloud radar is measured
The factor.
In non-rainfall or there is light rain, or in the case of having drizzle, it is believed that cloud particle yardstick is sufficiently small, meets Rayleigh scattering
Condition, according to Liquid water content C in cloudLW, efficient radius of cloud particle reWith the definition of radar reflectivity factor Z, it is derived by down
Row formula.
In formula:ρωRepresent water density.
The priori data xaWith the covariance matrix S of priori dataaPopulation density is obtained according to by historical statistical data
NTAnd distribution width sigmalogObtained by historical statistical data to calculate Particle number concentration and the dispersion of distribution, and calculate priori according to this
The covariance matrix of data.
In formula, range bin zi;z1And znThe range bin on cloud base and cloud top in radar profile is represented respectively, and subscript a represents priori
Value, rgaRepresent the priori data of efficient radius of cloud particle, in the same manner, NTaAnd σlogaIt is to represent Particle number concentration and distribution width respectively
The priori value of degree.
Forward physical model F (x) of described radar reflectivity factor is by known cloud particle size i.e. cloud particle
Effective radius re, Particle number concentration NTAnd distribution width sigmalog, extrapolate forward physical model F (x) of radar reflectivity factor;I.e.
When considering that millimeter cloud radar receives the cloud particle scattering energy of given distance, the two-way decay on institute's pathway footpath obtains Jing decay
Revised radar reflectivity factor ZFM;Derived by the defined formula of radar reflectivity factor Z and calculate each range bin ziThunder
Up to reflectivity factor ZFM(zi);
K=(m2-1)/(m2+2) (12)
In formula, z1And znThe range bin on cloud base and cloud top in radar profile is represented respectively, and subscript FM represents forward physical pattern
Calculated value, m represents complex refractive index.
Measurement vector y is set up by forward physical model F (x) and inverting parameter x relations between the two, forward physical is treated
Pattern is represented by
Y=F (x)+εy (13)
ε in formulayRepresent measure error.
The measurement vector y is with unknown state vector x
In formula:ZdB(zi)、rg(zi)、NT(zi) and σlog(zi) represent respectively radar reflectivity factor, geometrical mean radius,
Cloud particle number density and dispersion of distribution parameter are in range bin ziThe value at place;N represents the cloud range bin number in profile.
For profile is observed per bar, state vector x is to treat inverting parameter in each range bin, it is known that measurement vector y is only
There is the radar reflectivity factor in respective distances storehouse, need by priori data xaRow constraint is entered to inverting, it is ensured that iteration convergence
And the reliability of inversion result.
It is described by priori data xaAs iterative initial value, cost function D is minimized by continuous, try to achieve and treat inverting parameter x
Iterative solution, and the condition of convergence of iteration is met when calculating is iterated;
In formula:Subscript i and i+1 represent iterations, and L represents sensitivity of the forward physical pattern to state vector x.
The condition of convergence of the iteration is:
In formula:SxThe error co-variance matrix of iterative state vector, represent three variances for treating inverting physical quantity and
Covariance between each parameter, SyIt is the covariance matrix of cloud radar measurement errors.
Inversion error is mainly derived from radar reflectivity factor and priori data acquisition algorithm, theoretical according to error propagation,
Calculate the standard deviation and error for the treatment of inverted parameters of inverting, also referred to as uncertainty.
According to the inversion method of the liquid Cloud microphysical parameter, refutation process is realized using CloudSat measured datas,
And analyze inversion result.Selected inverting example be stratocumulus, inverting adopt cloud particle radius priori data as shown in Fig. 2 with
The fixed priori data adopted in existing refutation process compare (i.e. effective radius priori data for fixed value, and not with height and
Longitude and latitude changes), can more reflect the true of cloud physics parameter by the calculated Effective radius of actual measurement radar reflectivity factor
True property.
The liquid Cloud microphysical parametric results that inverting is obtained are as shown in Figure 3.Cloud microphysical parameter include Effective radius,
The maximum of Liquid water content, Particle number concentration and dispersion of distribution parameter, Effective radius and cloud liquid water content occurs
The stronger region of portion's radar return in the clouds, cloud particle Particle density is presented with the trend that gradually increases highly is increased, is distributed width
Degree parameter is then gradually reduced with height increase, and spatial distribution and variation tendency and the CloudSat of each parameter issue result basic
Cause, and meet the water dust characteristic parameter scope of the cumulus of Chinese scholars statistics, inversion result is credible.
Although present disclosure has been made to be discussed in detail by above preferred embodiment, but it should be appreciated that above-mentioned
Description is not considered as limitation of the present invention.After those skilled in the art have read the above, for the present invention's
Various modifications and substitutions all will be apparent.Therefore, protection scope of the present invention should be limited to the appended claims.
Claims (8)
1. a kind of inversion method of liquid Cloud microphysical parameter, it is characterised in that
Inversion algorithm tries to achieve optimal solution in the case where cost function obtains minimum of a value, and the cost function is state vector and elder generation
The weighting sum of data difference and known measurement vector sum forward model value difference point is tested,
In formula, xaIt is according to the calculated priori data of radar reflectivity factor, SaFor the covariance matrix of priori data, F
(x) for radar reflectivity factor forward physical pattern, SyIt is the covariance matrix of radar reflectivity factor measure error, y is
Measurement vector is radar reflectivity factor, and x is that unknown state vector treats inverting parameter, described to treat that inverting parameter includes cloud particle
Subnumber density, geometrical mean radius and dispersion of distribution parameter;
By priori data xaAs iterative initial value, cost function D is minimized by continuous, finally try to achieve the iteration for treating inverting parameter x
Solution.
2. a kind of inversion method of liquid Cloud microphysical parameter as claimed in claim 1, it is characterised in that in assuming air
The size distribution of cloud particle meets logarithm normal distribution, sets up radar reflectivity factor and liquid cloud physics parameter i.e. cloud particle subnumber
Density, efficient radius of cloud particle, the functional relation of cloud particle dispersion of distribution parameter;
In formula:NTIt is cloud particle number density;R is efficient radius of cloud particle;rgIt is geometrical mean radius;σlogIt is dispersion of distribution ginseng
Number, is dimensionless variable;σgFor geometric standard deviation;Ln represents natural logrithm conversion;Horizontal line is represented seeks arithmetic mean of instantaneous value;
In the case where rainfall is not considered, it is believed that cloud particle yardstick is sufficiently small, Rayleigh scattering condition is met, according to aqueous water in cloud
Content CLW, efficient radius of cloud particle reWith the definition of radar reflectivity factor Z, following equation is derived by,
In formula:ρωRepresent water density.
3. a kind of inversion method of liquid Cloud microphysical parameter as claimed in claim 2, it is characterised in that the priori data
xaWith the covariance matrix S of priori dataaPopulation density N is obtained according to by historical statistical dataTAnd distribution width sigmalogTo count
Obtain,
In formula, range bin zi;z1And znThe range bin on cloud base and cloud top in radar profile is represented respectively;Subscript a represents state vector
The priori value of x, rga、NTaAnd σlogaIt is the priori value for representing efficient radius of cloud particle, Particle number concentration and the dispersion of distribution respectively.
4. a kind of inversion method of liquid Cloud microphysical parameter as claimed in claim 1, it is characterised in that by cloud particle chi
Very little i.e. efficient radius of cloud particle re, Particle number concentration NTAnd distribution width sigmalog, extrapolate the forward direction of the radar reflectivity factor
Multiplicative model F (x);
Measurement vector y and state vector x relation between the two are set up by forward physical model F (x), forward physical pattern can
It is expressed as
Y=F (x)+εy
ε in formulayRepresent measure error;ZFM(zi) it is each range bin ziRadar reflectivity factor;z1And znIt is wide that radar is represented respectively
The range bin on cloud base and cloud top in line.
5. a kind of inversion method of liquid Cloud microphysical parameter as claimed in claim 4, it is characterised in that by radar reflection
The defined formula of the rate factor is derived and calculates each range bin ziRadar reflectivity factor ZFM(zi);
K=(m2-1)/(m2+2)
In formula, m represents complex refractive index.
6. a kind of inversion method of the liquid Cloud microphysical parameter as described in claim 1 or 4, it is characterised in that the measurement
Vectorial y is with state vector x
In formula:ZdB(zi)、rg(zi)、NT(zi) and σlog(zi) radar reflectivity factor, geometrical mean radius, cloud particle are represented respectively
Subnumber density and dispersion of distribution parameter are in range bin ziThe value at place;N represents the cloud range bin number in profile.
7. a kind of inversion method of liquid Cloud microphysical parameter as claimed in claim 6, it is characterised in that by the priori number
According to xaAs iterative initial value, by continuously minimizing the cost function D, the iterative solution for treating inverting parameter x is tried to achieve, and
The condition of convergence of iteration is met when being iterated calculating,
In formula:Subscript i and i+1 represent iterations, and L represents sensitivity of the forward physical pattern to state vector x.
8. a kind of inversion method of liquid Cloud microphysical parameter as claimed in claim 7, it is characterised in that the receipts of the iteration
The condition of holding back is:
In formula:SxIt is the error co-variance matrix of iterative state vector, represents three variances and each parameter for treating inverting physical quantity
Between covariance;SyIt is the covariance matrix of radar measurement errors.
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