CN115657013A - Method for estimating number concentration of ice crystal particles in ice cloud based on laser radar and cloud radar - Google Patents
Method for estimating number concentration of ice crystal particles in ice cloud based on laser radar and cloud radar Download PDFInfo
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Abstract
The invention relates to a method for estimating the number concentration of ice crystal particles in ice cloud based on a laser radar and a cloud radar, which belongs to the technical field of meteorological radar detection, considers the characteristics of the atmospheric radiation transmission physical process of laser and millimeter waves and the high space-time resolution observation of two remote sensing devices, utilizes a cloud analysis radar simulation model to calculate the simulation observed values of the laser and the millimeter radar on the basis of initial values of the given ice crystal particle number concentration, the effective particle radius, ice crystal particle weight functions in various typical shapes and the like, utilizes an optimal estimation method to adjust the initial set values of the ice crystal particle number concentration and the effective particle radius by comparing the simulation observed values output by a simulator with the difference of the actual observed values of the two radars, judges whether the ice crystal particle number concentration and the effective particle radius are converged based on the minimum principle of a value function, further realizes the estimation of the ice crystal particle number concentration in a mixed state and the ice crystal particle number concentrations in different shapes, and finally obtains higher estimation precision of the ice crystal particle number concentration.
Description
Technical Field
The invention relates to the technical field of meteorological radar detection, in particular to a method for estimating the number and concentration of ice crystal particles in ice cloud based on a laser radar and a cloud radar.
Background
The ice cloud composed of ice crystal particles with various shapes has important regulation function on radiation balance and water vapor circulation of the earth-atmosphere system; therefore, in the process of improving and optimizing the atmospheric climate mode, accurate measurement or estimation of micro-physical parameters of ice crystal particles in the ice cloud, such as the shape, size, concentration and the like of the ice crystal particles, becomes more and more important, and the micro-physical parameters directly influence accurate understanding and mathematical modeling of the scattering radiation characteristic of the ice cloud, and further influence the accuracy of the output result of the climate mode; among the ice crystal micro-physical parameters, accurate measurement of the ice crystal population concentration (Ni) is particularly important. Ni links the change characteristics of the aerosol with the dynamic effect of vertical convection for promoting cloud formation, namely the change of Ni directly influences the electromagnetic wave radiation characteristics of ice cloud and the development and life cycle of precipitation and cloud. Therefore, accurate measurement or estimation of Ni is necessary and meaningful.
However, at present, the most direct detection means for Ni is to directly measure the interior of ice cloud by using an airplane-mounted measuring instrument, but the method mainly has the following problems: 1. due to the limitation of observation time of an airplane measurement experiment, the space-time resolution of data sampling is low, and the data volume is small; 2. the ice crystal particles in the ice cloud are affected by the flight disturbance of the airplane to generate a crushing phenomenon, so that the original state of the ice crystal in the ice cloud is damaged, and the Ni measurement has larger deviation. In addition, when observing non-precipitation cloud, the Ka-band millimeter radar is a common instrument, and a plurality of cloud micro physical inversion algorithms are developed based on the instrument. However, limited by the sensitivity of millimeter wave radar, accurate detection of the number concentration of the ice particles within the ice cloud, which are very small on an ice cloud scale, cannot be achieved by means of it alone. Meanwhile, some researches are carried out on Ni by utilizing passive remote sensing data of a satellite, and the method has the biggest defect that the spatial resolution of the satellite is very low, so that the aim of finely detecting the high spatial resolution of ice cloud cannot be fulfilled. Moreover, the existing research on the ice crystal particle number concentration estimation in the ice cloud does not consider the inversion result of the number concentration of ice crystal particles in each shape under the mixed state of ice crystal particles in different shapes, the final ice crystal particle number concentration estimation result only reflects the average distribution state of the ice crystal particle groups in different shapes, and the estimation strategy cannot realize the fine observation of the number concentration of the ice crystal particles in each typical shape.
It is noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure and therefore may include information that does not constitute prior art that is already known to a person of ordinary skill in the art.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, provides a method for estimating the number concentration of ice crystals in ice cloud based on a laser radar and a cloud radar, and overcomes the defects of the conventional method for estimating the number concentration of ice crystals.
The purpose of the invention is realized by the following technical scheme: the method for estimating the number concentration of ice crystal particles in ice cloud based on laser radar and cloud radar comprises the following steps:
s1, acquiring data of a laser radar and a millimeter wave radar for processing to form multi-parameter vectors observed by the laser radar and the cloud radar, and acquiring DARDARDARDAR cloud parameters of joint inversion of the laser radar and the millimeter wave radar of a satellite and an atmospheric contour line field of atmospheric temperature and humidity of NCEP;
s2, extracting longitude, latitude and observation time information of the DARDARDAR and NCEP data, combining the longitude, latitude and observation time information of the lidar and the cloud radar, performing time and space interpolation on the DARDARDAR and NCEP data by using a linear interpolation method, obtaining the DARDAR and NCEP interpolation data of the observation positions of the lidar and the cloud radar, further generating data of atmospheric temperature, atmospheric humidity, effective particle radius and concentration which are matched with the radar observation space-time, and taking the data as initial values of an inversion process;
s3, setting a weight initial value for each ice crystal shape forming the ice crystal particles, setting effective radius, number concentration, shape and radar frequency of the ice crystal particles, calculating the ice crystal particle scattering characteristic of a laser radar wave band by using a physical optical approximation method, and obtaining the ice crystal particle backscattering characteristic of a millimeter wave band by using a T matrix model;
s4, writing the acquired NCEP atmospheric temperature and humidity profiles which are matched with the radar space-time, the calculated ice crystal scattering characteristics, the frequency, the power, the pulse width and the signal-to-noise ratio parameters of the laser radar and the millimeter wave radar into a model control file, inputting the control file into a cloud analysis radar simulation model, and performing simulation calculation to obtain the observed values of the laser radar and the millimeter wave radar;
s5, comparing the difference between the simulation and the observation of the real laser radar and the millimeter wave radar, establishing the relation between the ice crystal state and the radar observation value according to the set effective particle radius and the initial value of the particle number concentration and the cloud analysis radar simulation, and calculating to obtain the particle number concentration value through a Bayes theory and a Levenberg-Marquardt iteration method.
The step S1 specifically includes the following contents:
s11, collecting and acquiring data of the laser radar and the millimeter wave radar, eliminating rain data of the laser radar and the millimeter wave radar by using a threshold method, and then performing time and space matching on the laser radar and the millimeter wave radar to form multi-parameter vectors observed by the laser radar and the millimeter wave radar;
and S12, acquiring the DARDARDARDAR cloud parameters of joint inversion of the laser radar and the millimeter wave radar of the satellite and the atmospheric contour line field of atmospheric temperature and humidity of the NCEP according to the time and position information of the observation matching data set of the laser radar and the millimeter wave radar acquired in the step S1.
The physical optical approximation method comprises the following steps: according to different shapes of particles and the track of the laser beam, the backscattering characteristics of the particles to the light are calculated by solving Maxwell equations, and the calculation formula is as follows:
in the formula s 1 Is the area of illumination incident on the target,
and s are the unit vectors of the incident directions, rRepresents the distance, k represents the wave number,
is the incident electric field at the origin of the coordinates,
representative point
An outward unit normal vector of (a), e is an autologarithm, j represents an imaginary component, and j 2 =﹣1。
The method for obtaining the ice crystal particle backscattering characteristics of the millimeter wave band by using the T matrix model comprises the following steps: describing an incident field and a scattering field of electromagnetic waves as vector spherical wave functions, and inputting the effective particle radius, number concentration, shape, particle spectrum distribution and electromagnetic wave frequency of ice crystal particles into a T matrix model by utilizing a T matrix correlation function expansion term to calculate the backscattering characteristic parameters of the ice crystal particles with specific frequency.
The ice crystal state is related to a radar observed value by: y = F (x, b) + ε, where x is the state vector of the parameter to be inverted, b is the other parameters required by the radar simulation model, ε is the observation error of the radar, y is the radar observation vector, and F is the forward simulation model where the radar observation vector y and the other parameters b required by the radar simulation model are used to simulate radar observations.
The step S5 of calculating the particle number concentration value by using a bayesian theory and a Levenberg-Marquardt iterative method specifically includes:
solving the problem of minimizing the cost function by solving the state vector x through Bayes theory:
wherein x is a Is the initial value of the state vector, S a Is a state vector prior covariance matrix, S ε Is the observation error covariance matrix, y is the radar observation vector, X 2 Is a cost function;
the method is characterized in that the true value of the number concentration of ice crystal particles is gradually approximated by a Levenberg-Marquardt iteration methodAnd through
Calculating to obtain a particle number concentration value by a formula, wherein x i+1 Is the state vector result of the i +1 th iteration, x i Is the state vector result of the ith iteration, F (x) i And b) the radar observation vector, gamma, of the ith radar simulation model simulation of the state vector iteration i Is the Levenberg-Marquardt parameter, K i The method is a Jacobian matrix calculated in the ith iteration, and through multiple iterations, the minimization of a cost function is realized, and finally the estimation of the number concentration of ice crystal particles is realized.
The invention has the following advantages: a method for estimating the number concentration of ice crystal particles in ice cloud based on a laser radar and a cloud radar includes such steps as calculating the simulative observation values of laser and millimeter-wave radars by using a cloud analytic radar simulation model on the basis of the initial values of ice crystal particle number concentration, effective particle radius and weight functions of ice crystal particles in different typical shapes, comparing the simulative observation values output by a simulator with the actual observation values of two radars, regulating the initial setting values of ice crystal particle number concentration and effective particle radius by using an optimal estimation method, and judging if inversion is converged based on the principle of minimizing value function to estimate the number concentration of ice crystal particles in mixed state and the number concentrations of ice crystal particles in different shapes. In the estimation process, joint observation of the laser radar and the dual-polarization millimeter wave cloud radar is used, so that the estimation accuracy of the number concentration of the obtained ice crystal particles is high. In addition, the algorithm gives the weight distribution of the ice crystal particles with various common shapes at the same time, and the weight distribution is more approximate to the situation that the ice crystal particles in the actual ice cloud are mixed by the ice crystals with various shapes.
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FIG. 1 is a schematic flow diagram of the present invention;
FIG. 2 is a schematic flow chart of a backscattering calculation method by physical-optical approximation according to the present invention;
FIG. 3 is a schematic flow chart of a backscattering calculation method by a T matrix method according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the detailed description of the embodiments of the present application provided below in connection with the appended drawings is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application. The invention is further described below with reference to the accompanying drawings.
The invention particularly relates to a method for estimating the number concentration of ice crystal particles in ice cloud based on a laser radar and a dual-polarization millimeter wave cloud radar, which comprises the following steps: collecting data of the laser and millimeter wave dual-polarization cloud radar, eliminating rain data of the laser and dual-polarization millimeter wave cloud radar, and performing time and space matching on the laser and millimeter wave radar to form a multi-parameter vector observed by the laser and millimeter wave radar. Acquiring DARDARDAR (liDAR/liDAR) cloud parameters of joint inversion of laser and millimeter wave raDAR of a satellite and atmospheric temperature and humidity atmospheric profile line fields of a national environmental prediction center (NCEP) according to time and position information of a laser and millimeter wave raDAR observation matching data set; performing time and space two-dimensional linear interpolation space-time matching on the DARDARDAR and NCEP data to generate data of atmospheric temperature, atmospheric humidity, effective particle radius and number concentration which are matched with radar observation space-time, and taking the data as initial values of an inversion process; setting the initial weight value of each ice crystal particle shape on the assumption that the ice crystal particles consist of a plurality of ice crystal shapes; calculating the ice crystal particle scattering characteristic of a laser radar wave band by using physical optics approximation, and calculating the ice crystal particle scattering characteristic of a millimeter wave band by using a T matrix method; calculating the observation of the laser radar and the dual-polarization millimeter wave cloud radar by using a cloud analysis radar simulation model (CR-SIM); comparing the differences observed by the simulation and the real laser radar and the millimeter wave dual-polarization cloud radar, adjusting the initial values of the effective particle radius and the number concentration by using an optimal estimation model, simultaneously calculating a value function, and performing multiple iterations on the effective particle radius and the number concentration by using a Newton iteration method to minimize the value function and finally realize the estimation of the ice crystal particle number concentration.
As shown in fig. 1 to fig. 3, the following contents are specifically included:
step 1: collecting data of the laser and dual-polarization millimeter wave cloud radar, removing rain data of the laser and dual-polarization millimeter wave cloud radar by using a threshold method, and then performing time and space matching on the laser and millimeter wave radar to form a multi-parameter vector observed by the laser and millimeter wave radar.
And 2, step: and (2) acquiring a laser and millimeter wave raDAR joint inversion DARDARDARDAR (liDAR/RADAR) cloud parameter of the satellite and an atmospheric temperature and humidity atmospheric profile field of a national environmental prediction center (NCEP) according to the time and position information of the laser and millimeter wave raDAR observation matching data set acquired in the step (1).
And step 3: and (3) performing time and space two-dimensional linear interpolation line space-time matching on the DARDARDARDAR and NCEP data, generating data of atmospheric temperature, atmospheric humidity, effective particle radius and number concentration matched with the radar observation space-time obtained in the step (1), and taking the data as initial values of an inversion process.
And 4, step 4: assuming that the ice crystal particles consist of ice crystals in 5 shapes such as solid column, bullet petal-shaped, aggregate-shaped, hollow column-shaped and flat plate-shaped shapes, setting initial weight values of the ice crystal particles in the shapes, and setting the initial weight values of all types to be 0.2; and 3, taking the effective particle radius, number concentration, shape, radar frequency and observation mode of the ice crystal particles in the step 3 as input data, calculating the ice crystal particle scattering characteristic of the laser radar in the 532nm waveband by using physical optics approximation, and calculating the ice crystal particle backscattering characteristic of the Ka waveband millimeter wave radar by using a T matrix method.
The physical optical approximation method is characterized in that the backscattering characteristics of the particles to light are calculated through solving Maxwell equations according to different shapes of the particles and the tracks of the laser beams, and a specific calculation formula is as follows;
in the formula s 1 Is the area of illumination incident on the target,
and s are unit vectors of incident directions, r represents a distance, k represents a wave number,
is the incident electric field at the origin of the coordinates,
representative point
An outward unit normal vector of (a), e is an autologarithm, j represents an imaginary component, and j 2 =﹣1。
The method of the T matrix model comprises the following steps: describing an incident field and a scattering field of electromagnetic waves as vector spherical wave functions, and inputting the effective particle radius, number concentration, shape, particle spectrum distribution and electromagnetic wave frequency of ice crystal particles into a T matrix model by utilizing a T matrix correlation function expansion term to calculate the backscattering characteristic parameters of the ice crystal particles with specific frequency.
Wherein the ice crystal particle backscatter properties include: the ice crystal particle scattering phase function, the scattering cross section, the extinction coefficient, the absorption coefficient, the scattering coefficient and the extinction efficiency of laser 532nm and millimeter wave Ka wave band.
And 5: inputting the NCEP atmospheric temperature and humidity profile obtained in the step 2, the ice crystal scattering characteristics calculated in the step 4, the frequency, power, pulse width and signal-to-noise ratio parameters of the laser and millimeter wave radar into a cloud analytical radar simulation model (CR-SIM), and performing simulation calculation to obtain the observed values of the laser and dual-polarization millimeter wave cloud radar. The wavelength of the laser radar is set to 532nm, the millimeter wave radar is set to a Ka waveband, and the observation mode is vertical direction.
And 6: comparing the difference observed by a simulation and a real 532nm laser radar and a Ka-band dual-polarization millimeter wave cloud radar, assuming that an initial value of effective particle radius and concentration is given, a relation between an ice crystal state and a radar observation value can be established according to a cloud analysis radar simulation model, as y = F (x, b) + epsilon, wherein x is a state vector of a parameter to be inverted, b is other parameters required by the radar simulation model, epsilon is an observation error of the radar, y is a radar observation value vector, and F is a forward simulation model for simulating radar observation by using the radar observation value vector y and other parameters required by the radar simulation model b. Based on Bayesian theory, solving the problem that the state vector x is converted into the minimum of the yielding value function:
in the formula, x a Is the initial value of the state vector, S a Is a state vector prior covariance matrix, S ε Is an observation error covariance matrix, y is a radar observation vector, X 2 Is a cost function.
A Levenberg-Marquardt iteration method was further used to step-wise approximate the true ice crystal population. The particle number concentration value is obtained by iterative calculation of the following formula:
in the formula, x i+1 Is the state vector result of the i +1 th iteration, x i Is the state vector result of the ith iteration, F (x) i And b) is a radar observation vector of the ith radar simulation model simulation of the state vector iteration. Gamma ray i Is the Levenberg-Marquardt parameter, K i Is the jacobian matrix calculated at the ith iteration. And through multiple iterations, minimizing the cost function, and finally estimating the number concentration of the ice crystal particles.
The foregoing is illustrative of the preferred embodiments of the present invention, and it is to be understood that the invention is not limited to the precise form disclosed herein and is not to be construed as limited to the exclusion of other embodiments, and that various other combinations, modifications, and environments may be used and modifications may be made within the scope of the concepts described herein, either by the above teachings or the skill or knowledge of the relevant art. And that modifications and variations may be effected by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (6)
1. The method for estimating the number concentration of ice crystal particles in ice cloud based on laser radar and cloud radar is characterized by comprising the following steps: the estimation method comprises the following steps:
s1, acquiring data of a laser radar and a millimeter wave radar for processing to form multi-parameter vectors observed by the laser radar and the cloud radar, and acquiring DARDARDARDAR cloud parameters of joint inversion of the laser radar and the millimeter wave radar of a satellite and an atmospheric contour line field of atmospheric temperature and humidity of NCEP;
s2, extracting longitude, latitude and observation time information of the DARDAR and NCEP data, combining the longitude, latitude and observation time information of the laser radar and the cloud radar, performing time and space interpolation on the DAR and NCEP data by using a linear interpolation method, obtaining the DAR and NCEP interpolation data of the observation positions of the laser radar and the cloud radar, further generating data of atmospheric temperature, atmospheric humidity, effective particle radius and concentration which are matched with the radar observation space-time, and taking the data as initial values of an inversion process;
s3, setting a weight initial value for each ice crystal shape forming the ice crystal particles, setting effective radius, number concentration, shape and radar frequency of the ice crystal particles, calculating the ice crystal particle scattering characteristic of a laser radar wave band by using a physical optical approximation method, and obtaining the ice crystal particle backscattering characteristic of a millimeter wave band by using a T matrix model;
s4, writing the acquired NCEP atmospheric temperature and humidity profiles which are matched with the radar space-time, the calculated ice crystal scattering characteristics, the frequency, the power, the pulse width and the signal-to-noise ratio parameters of the laser radar and the millimeter wave radar into a model control file, inputting the control file into a cloud analysis radar simulation model, and performing simulation calculation to obtain the observed values of the laser radar and the millimeter wave radar;
s5, comparing the difference between the simulation and the observation of the real laser radar and the millimeter wave radar, establishing the relation between the ice crystal state and the radar observation value according to the set effective particle radius and the initial value of the particle number concentration and the cloud analysis radar simulation, and calculating to obtain the particle number concentration value through a Bayes theory and a Levenberg-Marquardt iteration method.
2. The method for estimating the number concentration of ice crystal particles in ice cloud based on lidar and cloud radar as claimed in claim 1, wherein: the step of S1 specifically includes the following:
s11, collecting and acquiring data of the laser radar and the millimeter wave radar, eliminating rain data of the laser radar and the millimeter wave radar by using a threshold method, and then performing time and space matching on the laser radar and the millimeter wave radar to form multi-parameter vectors observed by the laser radar and the millimeter wave radar;
and S12, acquiring DARDARDARDAR cloud parameters of joint inversion of the laser radar and the millimeter wave radar of the satellite and an atmosphere contour line field of atmospheric temperature and humidity of the NCEP according to the time and position information of the observation matching data set of the laser radar and the millimeter wave radar acquired in the step S1.
3. The method for estimating the number concentration of ice crystal particles in ice cloud based on lidar and cloud radar as claimed in claim 1, wherein: the physical optical approximation method comprises the following steps: according to different shapes of particles and the track of the laser beam, the backscattering characteristics of the particles to the light are calculated by solving Maxwell equations, and the calculation formula is as follows:
in the formula s 1 Is the area of illumination incident on the target,
and s is respectivelyThe unit vector of the radiation direction, r represents the distance, k represents the wave number,
is the incident electric field at the origin of the coordinates,
representative point
An outward unit normal vector of (a), e is an autologarithm, j represents an imaginary part, and j 2 =﹣1。
4. The lidar and cloud radar-based ice crystal population concentration estimation method according to claim 1, wherein: the method for obtaining the ice crystal particle backscattering characteristics of the millimeter wave band by using the T matrix model comprises the following steps: describing an incident field and a scattering field of electromagnetic waves as vector spherical wave functions, and inputting the effective particle radius, number concentration, shape, particle spectrum distribution and electromagnetic wave frequency of the ice crystal particles into a T matrix model by utilizing a T matrix correlation function expansion term to calculate the backscattering characteristic parameters of the ice crystal particles with specific frequency.
5. The lidar and cloud radar-based ice crystal population concentration estimation method according to claim 1, wherein: the ice crystal state is related to a radar observed value by: y = F (x, b) + ε, where x is the state vector of the parameter to be inverted, b is the other parameters required by the radar simulation model, ε is the observation error of the radar, y is the radar observation vector, and F is the forward simulation model where the radar observation vector y and the other parameters b required by the radar simulation model are used to simulate radar observations.
6. The lidar and cloud radar-based ice crystal population concentration estimation method according to claim 5, wherein: in the step of S5, the calculating of the particle number concentration value by using a bayesian theory and a Levenberg-Marquardt iterative method specifically includes:
solving the problem of minimizing the cost function by solving the state vector x through Bayes theory:
wherein x is a Is the initial value of the state vector, S a Is a state vector prior covariance matrix, S ε Is an observation error covariance matrix, y is a radar observation vector, X 2 Is a cost function;
by Levenberg-Marquardt iteration to progressively approximate the true ice crystal population concentration value and by
Calculating to obtain a particle number concentration value by a formula, wherein x i+1 Is the state vector result of the i +1 th iteration, x i Is the state vector result of the ith iteration, F (x) i And b) the radar observation vector, gamma, of the ith radar simulation model simulation of the state vector iteration i Is the Levenberg-Marquardt parameter, K i The method is a Jacobian matrix calculated in the ith iteration, and through multiple iterations, the minimization of a cost function is realized, and finally the estimation of the number concentration of ice crystal particles is realized.
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