Aerosol profile retrieval method based on dual-wavelength Mie scattering lidar data

Abstract

The disclosure provides an aerosol profile inversion method and device based on dual-wavelength Mie scattering lidar data, which comprises: obtaining an aerosol component profile initial value; constructing a mixed-mode aerosol optical property forward model; inputting the aerosol component profile initial value into the forward model to obtain an aerosol lidar ratio and a simulated aerosol extinction coefficient profile; based on the aerosol lidar ratio, using the Fernald method to obtain an inversion aerosol extinction coefficient profile; obtaining an aerosol extinction coefficient profile ratio according to the simulated aerosol extinction coefficient profile and the inversion aerosol extinction coefficient profile, and using it to adjust the aerosol total concentration; adjusting the aerosol component proportion based on the aerosol optical thickness value; obtaining a new aerosol component profile according to the adjusted aerosol total concentration and the component proportion; repeating the above steps until the difference between the simulated aerosol extinction coefficient profile and the inversion aerosol extinction coefficient profile is less than a threshold value, and completing the aerosol profile inversion.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of aerosol measurement, and in particular to an aerosol profile inversion method and device based on dual-wavelength Mie scattering lidar data, an electronic device and a storage medium. BACKGROUND

[0002] Atmospheric aerosol refers to a considerable number of solid or liquid particles suspended in the atmosphere, with a size of 0.001 μm to 100 μm, which plays an important role in the earth's climate, radiation, environment, etc. For example, aerosol is the condition for forming cloud and rain, and can provide condensation nuclei or freezing nuclei for the condensation or freezing of water vapor in the atmosphere. Secondly, it can absorb and scatter solar radiation, long-wave radiation emitted by the atmosphere and the ground, and change the radiation balance of the earth. Aerosol is also one of the important causes of haze, which directly affects the visibility of the air and the health of the human body. In addition, the change of the composition and content of atmospheric aerosol is also an important indicator of geological movement, ecological change and human activity. Therefore, monitoring the total amount, vertical distribution and composition of aerosol in the atmosphere can provide important research data for many fields.

[0003] Atmospheric detection lidar can realize the inversion of aerosol extinction coefficient profile and optical thickness information by actively emitting laser to the earth's atmosphere and receiving the backscattering echo signals of aerosol particles, atmospheric molecules and cloud particles, and is currently the only means to obtain long-time high vertical resolution aerosol profile information.

[0004] The most widely used aerosol inversion method for lidar at present is the Fernald method, which is characterized by decomposing the lidar Mie scattering echo signal into two parts of atmospheric molecules and aerosol based on the lidar equation, assuming the boundary value of aerosol extinction coefficient and the lidar ratio, and solving the equation to obtain the aerosol extinction coefficient profile. However, due to the complexity of atmospheric physical and chemical changes and the diversity of aerosol composition, the existence of assumptions such as the dependence of aerosol lidar ratio on empirical values and the setting of single-mode aerosol in the atmosphere will introduce large errors in the inversion of aerosol extinction coefficient profile. At the same time, there is no mature lidar signal inversion algorithm that can realize the extraction of aerosol composition information while obtaining the aerosol extinction coefficient profile. This has brought a bottleneck to the research and application of atmospheric detection lidar in the fields of ecology, environment, climate, etc. SUMMARY

[0005] To solve the problems in the prior art, the present disclosure provides a method and device for retrieving aerosol profile based on dual-wavelength Mie scattering lidar data, electronic equipment and storage medium, which constructs the relationship between aerosol component profile and dual-channel lidar echo signal, iteratively optimizes the aerosol lidar ratio at different wavelengths, and realizes high-precision detection of atmospheric aerosol extinction coefficient profile and accurate evaluation of aerosol component composition information.

[0006] The first aspect of the present disclosure provides a method for retrieving aerosol profile based on dual-wavelength Mie scattering lidar data, comprising: S1, obtaining the initial value of the aerosol component profile according to the atmospheric detection lidar data; S2, constructing a mixed-mode aerosol optical property forward model; S3, inputting the initial value of the aerosol component profile into the mixed-mode aerosol optical property forward model for simulation to obtain the aerosol lidar ratio of the dual-wavelength channel and the simulated aerosol extinction coefficient profile; S4, based on the aerosol lidar ratio, using the Fernald method to retrieve the retrieval aerosol extinction coefficient profile of the atmospheric detection lidar data; S5, according to the simulated aerosol extinction coefficient profile and the retrieval aerosol extinction coefficient profile, obtaining the aerosol extinction coefficient profile ratio of the dual-wavelength channel, adjusting the total concentration of the aerosol based on the aerosol extinction coefficient profile ratio, and calculating the aerosol optical thickness value, and adjusting the aerosol component proportion based on the aerosol optical thickness value; S6, calculating the new aerosol component profile according to the adjusted total concentration of the aerosol and the proportion of each component; S7, judging whether the result difference between the simulated aerosol extinction coefficient profile obtained in S3 and the retrieval aerosol extinction coefficient profile obtained in S4 is less than a threshold value; if not, repeating steps S3-S6 until the result difference between the simulated aerosol extinction coefficient profile obtained in S3 and the retrieval aerosol extinction coefficient profile obtained in S4 is less than a threshold value, and the iteration is ended, completing the retrieval of the aerosol profile.

[0007] Further, the mixed-mode aerosol optical property forward model is constructed in S2, comprising: S21, obtaining the aerosol size spectrum distribution and the aerosol complex refractive index according to the aerosol component profile; S22, obtaining the mixed-mode aerosol optical characteristic parameter based on the Mie scattering theory according to the aerosol size spectrum distribution and the aerosol complex refractive index; wherein the mixed-mode aerosol optical characteristic parameter is used to realize the mixed-mode aerosol optical property forward model.

[0008] Further, the aerosol size spectrum distribution is obtained according to the aerosol component profile in S21, comprising: S211, calculating the volume concentration of each component according to the mass mixing ratio profile of the aerosol component; S212, obtaining the volume spectrum distribution of the aerosol by using the logarithmic normal distribution function according to the volume concentration of each component of the aerosol; S213, calculating the aerosol number concentration spectrum distribution according to the volume spectrum distribution of the aerosol.

[0009] Further, the mixed-mode aerosol optical characteristic parameters include extinction coefficients, backscattering coefficients, aerosol lidar ratios and aerosol optical thicknesses of different types of aerosols.

[0010] Further, the S1 includes obtaining the initial value of the aerosol component profile according to the atmospheric sounding lidar data, and the S1 includes: S11, obtaining the atmospheric sounding lidar data; S12, obtaining the corresponding time information and latitude and longitude information according to the atmospheric sounding lidar data; S13, obtaining the corresponding aerosol profile historical data from the fourth generation of global atmospheric component reanalysis database of the European Centre for Medium-Range Weather Forecasts according to the time information and latitude and longitude information; and S14, obtaining the initial value of the aerosol component profile corresponding to the atmospheric sounding lidar data according to the analysis and evaluation of the aerosol profile data.

[0011] Further, the S4 includes obtaining the inversion aerosol extinction coefficient profile of the atmospheric sounding lidar data by using the Fernald method based on the aerosol lidar ratio, and the S4 includes: S41, selecting the aerosol backscattering coefficient corresponding to the position of the clean atmosphere near the tropopause as the boundary value of the inversion; and S42, obtaining the inversion aerosol extinction coefficient profile of the atmospheric sounding lidar data by using the Fernald method based on the aerosol lidar ratio and the boundary value.

[0012] Further, the aerosol profile data includes one or more of dust, sea salt, sulfate, organic matter and black carbon aerosols.

[0013] The second aspect of the present disclosure provides an aerosol profile inversion device based on dual-wavelength Mie scattering lidar data, comprising: a data acquisition module, configured to acquire a corresponding aerosol component profile initial value according to atmospheric sounding lidar data; an optical property forward model construction module, configured to construct a mixed-mode aerosol optical property forward model; a data simulation module, configured to input the aerosol component profile initial value into the mixed-mode aerosol optical property forward model for simulation, to obtain an aerosol lidar ratio corresponding to a dual-wavelength channel and a simulated aerosol extinction coefficient profile; a data inversion module, configured to obtain an inversion aerosol extinction coefficient profile of the atmospheric sounding lidar data by using the Fernald method based on the aerosol lidar ratio; an aerosol profile optimization module, configured to acquire an aerosol extinction coefficient profile ratio of the dual-wavelength channel according to the simulated aerosol extinction coefficient profile and the inversion aerosol extinction coefficient profile, adjust an aerosol profile total concentration based on the aerosol extinction coefficient profile ratio, and calculate an aerosol optical thickness value; adjust an aerosol component proportion based on the aerosol optical thickness value; an aerosol component profile updating module, configured to calculate a new aerosol component profile according to the adjusted aerosol total concentration and the component proportions; and an inversion iteration module, configured to judge whether a result difference between the simulated aerosol extinction coefficient profile obtained in the data simulation module and the inversion aerosol extinction coefficient profile obtained in the data inversion module is less than a threshold value; if not, data inversion iteration is performed until the result difference between the simulated aerosol extinction coefficient profile obtained in the data simulation module and the inversion aerosol extinction coefficient profile obtained in the data inversion module is less than the threshold value, and the iteration is ended, and the aerosol profile inversion is completed.

[0014] The third aspect of the present disclosure provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the method for aerosol profile inversion based on dual-wavelength Mie scattering lidar data provided by the first aspect of the present disclosure is implemented.

[0015] The fourth aspect of the present disclosure provides a computer readable storage medium, having a computer program stored thereon, and when the computer program is executed by a processor, the method for aerosol profile inversion based on dual-wavelength Mie scattering lidar data provided by the first aspect of the present disclosure is implemented.

[0016] The present disclosure has at least the following beneficial effects relative to the prior art:

[0017] (1) The method for aerosol profile inversion based on dual-wavelength Mie scattering lidar data provided by the present disclosure avoids the problem that the setting of the lidar ratio in the current algorithm depends on empirical statistics, and the lidar ratio is not determined by empirical values.

[0018] (2) Compared with the single mode aerosol and its extinction coefficient and backscattering coefficient between the forward relationship database, by constructing the optical properties of mixed mode aerosol forward model, the aerosol lidar ratio and extinction characteristics parameter profile closer to the real state can be obtained.

[0019] (3) According to the observation information of the laser radar on the double channel, more constraints are introduced in the solution of the laser radar equation, and through the iterative adjustment of the aerosol lidar ratio, component profile and extinction coefficient profile on different wavelengths, the aerosol inversion result closer to the real situation can be obtained. Among them, the acquisition of aerosol component profile can provide more intuitive basic data for climate, environmental and other related research and policy specification. BRIEF DESCRIPTION OF DRAWINGS

[0020] For a more complete understanding of the present disclosure and its advantages, reference is now made to the following description taken in conjunction with the accompanying drawings in which:

[0021] Figure 1 The flow chart of the aerosol profile inversion method based on the dual-wavelength Mie scattering lidar data according to an embodiment of the present disclosure is schematically shown;

[0022] Figure 2 The flow chart of acquiring the initial value of the aerosol component profile corresponding to the atmospheric sounding lidar data according to an embodiment of the present disclosure is schematically shown;

[0023] Figure 3 The flow chart of constructing the mixed mode aerosol optical property forward model according to an embodiment of the present disclosure is schematically shown;

[0024] Figure 4 The flow chart of generating the inversion aerosol extinction coefficient profile according to an embodiment of the present disclosure is schematically shown;

[0025] Figure 5 The block diagram of the aerosol profile inversion device based on the dual-wavelength Mie scattering lidar data according to an embodiment of the present disclosure is schematically shown;

[0026] Figure 6 The block diagram of the electronic device suitable for implementing the method described above according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0027] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It is to be understood, however, that the description is merely exemplary of the present disclosure, and is not intended to limit the scope of the present disclosure. In the following detailed description of the embodiments of the present disclosure, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure. However, it will be apparent to one skilled in the art that the present disclosure can be practiced without these specific details. In other instances, well-known structures and functions have not been described in detail in order to avoid obscuring aspects of the present disclosure.

[0028] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the present disclosure. As used herein, the term "includes" and tautological equivalents thereof, means that the named feature can be present, but not exclusive, without a presence or addition of one or more other features, steps, operations, elements, and / or components.

[0029] All terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this present disclosure pertains, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of the specification, and should not be interpreted in an idealized or overly formal way.

[0030] In the case where expressions such as "at least one of A, B, and C, etc." are used, it generally should be interpreted that the meaning is the same as "at least one of the group consisting of A, B, and C" (for example, "a system having at least one of A, B, and C" should include a system having A alone, a system having B alone, a system having C alone, a system having A and B together, a system having A and C together, a system having B and C together, and / or a system having A, B, and C together, etc.). In the case where expressions such as "at least one of A, B, or C, etc." are used, it generally should be interpreted that the meaning is the same as "at least one of the group consisting of A, B, and C" (for example, "a system having at least one of A, B, or C" should include a system having A alone, a system having B alone, a system having C alone, a system having A and B together, a system having A and C together, a system having B and C together, and / or a system having A, B, and C together, etc.).

[0031] Some of the blocks and / or combinations of the blocks in the flowcharts can be implemented by computer program instructions. Such computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in the flowcharts and / or flow diagrams block or blocks. The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operations to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus implement the functions / acts specified in the flowcharts and / or flow diagrams block or blocks.

[0032] The specific process of the aerosol profile inversion method based on dual-wavelength Mie scattering lidar data in the specific embodiments of the present disclosure will be described in detail below. It should be understood that the process and calculation structure of the aerosol profile inversion method based on dual-wavelength Mie scattering lidar data shown in the accompanying drawings are only exemplary to help those skilled in the art understand the technical solutions of the present disclosure, and are not intended to limit the protection scope of the present disclosure.

[0033] Figure 1 A flowchart of the aerosol profile inversion method based on dual-wavelength Mie scattering lidar data according to an embodiment of the present disclosure is schematically shown. As shown in Figure 1 , the method comprises steps S1-S7.

[0034] In operation S1, according to the atmospheric sounding lidar data, the corresponding aerosol component profile initial value is obtained.

[0035] In the embodiments of the present disclosure, the aerosol in the real atmospheric environment is mixed by multiple component particles, each component of the particles has its own distribution and is mixed according to different components. Taking the atmosphere in the local area as the main research object, it is necessary to collect the aerosol profile data in the local area as the prior information for the atmospheric aerosol profile inversion.

[0036] According to the embodiments of the present disclosure, as shown in Figure 2 , in S1, according to the obtained atmospheric sounding lidar data, the corresponding aerosol component profile initial value is obtained, specifically comprising: S11, obtaining the atmospheric sounding lidar data; S12, obtaining the corresponding time information and latitude and longitude information according to the atmospheric sounding lidar data; S13, obtaining the corresponding aerosol profile historical data from the European Centre for Medium-Range Weather (ECMWF) Atmospheric Composition Reanalysis 4 (EAC4) according to the time information and the latitude and longitude information; S14, obtaining the aerosol component profile initial value corresponding to the atmospheric sounding lidar data according to the aerosol profile data analysis and evaluation.

[0037] Specifically, the aerosol profile history data at least includes one or more of dust, sea salt, sulfate, organic matter and black carbon aerosol. The type composition of local atmospheric aerosol and its concentration level can be evaluated by monthly / seasonal averaging of at least ten years of data, and the aerosol component profile initial value for laser radar atmospheric detection data inversion is the aerosol component profile initial value including local atmospheric aerosol profile data and local atmospheric aerosol optical thickness data, which is the aerosol multi-year monthly average profile.

[0038] In operation S2, a mixed-mode aerosol optical property forward model is constructed.

[0039] In an embodiment of the present disclosure, a mixed-mode aerosol optical property forward model is constructed based on Mie scattering theory and the complex refractive index of aerosol to obtain the extinction coefficient profile corresponding to the aerosol component profile.

[0040] Specifically, as shown in Figure 3 The mixed-mode aerosol optical property forward model constructed in S2 specifically includes steps S21-S22.

[0041] In operation S21, the aerosol size spectrum distribution and the aerosol complex refractive index are obtained according to the aerosol component profile.

[0042] In an embodiment of the present disclosure, the complex refractive index of particles is related to composition and changes with wavelength. The Hitran database is a commonly used atmospheric molecular spectral database worldwide, which gives the complex refractive index of aerosol particles corresponding to sodium chloride, sea salt, water-soluble aerosol, ammonium sulfate, black carbon, volcanic dust, sulfuric acid, atmospheric dust, quartz, hematite, sand and dust-like dust in the 0.2-40 μm wavelength band. For different types of aerosols that are dominant in the local atmosphere, select appropriate complex refractive index data to obtain the aerosol complex refractive index.

[0043] According to an embodiment of the present disclosure, the aerosol size spectrum distribution is obtained according to the aerosol component profile in S21, specifically including: S211, calculating the volume concentration of each component according to the mass mixing ratio profile of the aerosol component; S212, obtaining the volume spectrum distribution of the aerosol by using the logarithmic normal distribution function according to the volume concentration of each component of the aerosol; S213, calculating the number concentration spectrum distribution of the aerosol according to the volume spectrum distribution of the aerosol.

[0044] Specifically, the logarithmic normal distribution function is used to describe the volume spectrum distribution of aerosol particles, which satisfies the following relationship:

[0045]

[0046] Wherein, r represents the particle radius of the aerosol particle; V(r) represents the aerosol volume related to the aerosol radius; Cv Indicates the volume concentration of aerosols; r v σ represents the median radius of the aerosol particle size distribution, and σ represents the root mean square error of the aerosol particle radius.

[0047] It can be determined by the aerosol volume spectrum distribution. To calculate the aerosol number concentration spectral distribution The relationship between the two can be expressed as:

[0048]

[0049] Where N(r) represents the aerosol particle number density.

[0050] In operation S22, based on Mie scattering theory, and according to the aerosol scale spectral distribution and aerosol complex refractive index, the optical characteristic parameters of the mixed-mode aerosol are obtained. These mixed-mode aerosol optical characteristic parameters are used to realize a forward model of the optical properties of the mixed-mode aerosol.

[0051] In the embodiments of this disclosure, based on Mie scattering theory, the optical characteristic parameters of hybrid-mode aerosols are obtained according to the aerosol scale spectral distribution, aerosol complex refractive index, and the relationship between the Mie scattering cross section and the geometric cross section of spherical particles. These hybrid-mode aerosol optical characteristic parameters include: extinction coefficients, backscattering coefficients, aerosol lidar ratios, and aerosol optical thicknesses for different types of aerosols.

[0052] Mie scattering theory refers to the scattering phenomenon of uniform spherical particles of arbitrary composition within a certain scale range. It describes the scattering interaction between light and particles when the wavelength is comparable to the particle size. Based on Mie scattering theory, and according to the relationship between the Mie scattering cross section and the geometric cross section of the spherical particle, the extinction efficiency factor Q can be calculated. ext Scattering efficiency factor Q sca Absorption efficiency factor Q abs and backscattering efficiency factor Q back They respectively satisfy the following relations:

[0053]

[0054]

[0055] Q abs =Q ext -Q sca

[0056]

[0057] in,

[0058] x = ka = 2πr / λ

[0059]

[0060]

[0061]

[0062]

[0063] h n (x) = j n (x) + iy n (x)

[0064] In the above formula, x represents the scale parameter of the scattering particle; λ is the wavelength of the incident light in the medium around the particle; m represents the complex refractive index of the scattering particle relative to the surrounding medium, m = m r + im i , m r is the real part of the complex refractive index, representing the scattering effect of the particle on light; m i is the imaginary part of the complex refractive index, representing the absorption effect.a n and b n are functions related to the scale parameter x and the complex refractive index m of the particle; j n (x) and h n (x) represent the n-order Bessel function and the first kind Hankel function respectively, and their derivative recursive relations are as follows:

[0065] [xj n (x)]' = xj n-1 (x) - nj n (x)

[0066] [xh n (x)]' = xh n-1 (x) - nh n (x)

[0067] where J n+0.5 , Y n+0.5 represent the first kind and second kind Bessel functions, and their initial values are:

[0068]

[0069]

[0070] It should be noted that the value of the infinite series n in all formulas represents the superposition of the scattering field generated by the forced oscillation of the internal field of the scattering particle and the incident field and the divergence field. In the actual calculation process, a finite term must be taken, and the maximum value of the series term n max can be calculated by the following formula:

[0071]

[0072] The extinction efficiency factor can be obtained by step-by-step iteration.

[0073] Thus, the Mie scattering extinction coefficient β e may be expressed as:

[0074]

[0075] wherein the integral limits r1, r2 are the minimum and maximum characteristic radii of the particle system, which can be taken as 0.005 μm and 20 μm respectively. It can be seen that the aerosol extinction coefficient is a function of the complex refractive index m, the particle radius r and the number (concentration) of particles in the dr particle size range.

[0076] In the embodiments of the present disclosure, on the basis of obtaining the aerosol spectrum distribution of each component and the complex refractive index, the extinction coefficient, the backscattering coefficient, the laser radar ratio (the ratio of the aerosol extinction coefficient and the backscattering coefficient) and the aerosol optical thickness of different types of aerosols can be obtained by using the above method, and the construction of the forward model of the optical properties of the mixed mode aerosol is realized.

[0077] In operation S3, the aerosol component profile initial value is input to the forward model of the optical properties of the mixed mode aerosol for simulation, and the aerosol laser radar ratio of the dual-wavelength channel and the simulated aerosol extinction coefficient profile are obtained.

[0078] In the embodiments of the present disclosure, the aerosol component profile initial value is input to the forward model of the optical properties of the mixed mode aerosol for simulation, and the aerosol laser radar ratio of the dual-wavelength channel and the simulated aerosol extinction coefficient profile are obtained. Wherein, the laser radar ratio S total The calculation method is as follows:

[0079] S total = p1S1+ p2S2+ … + p n S n

[0080] Wherein, n represents the number of aerosol types; p1, p2,..., p n represent the mass ratio of the aerosol of this type to the total aerosol respectively; S1, S2,..., S n represent the laser radar ratio of the aerosol of this type.

[0081] In operation S4, based on the aerosol laser radar ratio, the inversion aerosol extinction coefficient profile of the atmospheric detection laser radar data is obtained by using the Fernald method.

[0082] In the embodiments of the present disclosure, the laser radar equation can quantitatively describe the propagation process of the laser pulse signal in the atmosphere, is a mathematical expression of the working principle of the laser radar, and describes the energy of the atmospheric backscattering echo signal received by the laser radar at different heights when the laser beam vertically emitted by the laser radar passes through the atmosphere. According to the Mie scattering theory, combined with the working principle of the laser radar, the atmospheric backscattering echo power P(R) received by the laser radar at the detection distance R can be expressed by the Mie scattering laser radar equation as follows:

[0083]

[0084] wherein C represents a system constant, E represents the energy of the emitted laser pulse, and is a known parameter; β(R) represents the atmospheric backscattering coefficient at the detection distance R; and σ represents the atmospheric extinction coefficient. The Fernald method considers the scattering of light by particles of two components, i.e., atmospheric molecules and aerosol particles, and the above formula can be expressed as:

[0085]

[0086] wherein since the equation contains two unknown quantities, i.e., the backscattering coefficient β a (R) and the extinction coefficient σ a (R) of the aerosol particles at the detection distance R, the backscattering coefficient β m (R) and the extinction coefficient σ m (R) of the atmospheric molecules can be obtained according to the U.S. standard atmospheric model. In the Fernald method, the aerosol lidar ratio is defined as the ratio of the aerosol extinction coefficient to the backscattering coefficient S a (R) = σ a (R) / β a (R), and it is assumed to be a constant that does not change with height. At the same time, the aerosol backscattering / extinction coefficient at a reference height, i.e., the boundary value, needs to be known in advance.

[0087] Thus, by using the backscattering signals at different heights or detection distances detected by the laser radar, the atmospheric aerosol extinction characteristic parameters at the corresponding detection distance can be obtained by solving the laser radar equation, as shown in the following formula: Figure 4 FIG. 1 shows a flowchart of the process of obtaining the aerosol extinction coefficient by inversely calculating the laser radar observation data.

[0088] It is assumed that the extinction coefficient of air molecules and the backscattering ratio Based on the Mie scattering laser radar equation, after a series of transformations such as integration, taking the natural logarithm, and derivation, under the premise that the backscattering coefficients of the aerosol particles and the air molecules at a reference height R f are known in advance, the reference height R fThe aerosol particle backscatter coefficient at each height above the reference height R can be expressed as (near-end solution, forward integration):

[0089]

[0090] Thus, the reference height R f The aerosol particle extinction coefficient σ a (R) at each height above the reference height R

[0091]

[0092] Similarly, the reference height R f The aerosol extinction coefficient σ a (R) at each height above the reference height R

[0093]

[0094] where X(R) = P(R)R 2 .

[0095] In the embodiments of the present disclosure, the lidar ratio is obtained based on a forward model of optical properties of mixed-mode aerosols. The inversion aerosol extinction coefficient profile of the atmospheric sounding lidar data is obtained by inversion using the Fernald method, including: S41, selecting the aerosol backscatter coefficient corresponding to the position of clean atmosphere near the tropopause as the boundary value of inversion; S42, based on the aerosol lidar ratio and the boundary value, using the Fernald method for inversion to obtain the inversion aerosol extinction coefficient profile of the atmospheric sounding lidar data.

[0096] Further, the determination of the boundary value uses the clean layer method, which selects the reference layer as the position of clean atmosphere near the tropopause containing almost no aerosol particles, and the selection method is The height r c corresponding to the minimum value. According to the molecular backscatter β m (r c ) at the reference height, the boundary value β a (r c ) can be determined, which is determined by the aerosol backscatter ratio R(r c ).

[0097]

[0098] Generally, the aerosol scattering ratio at the reference height is assumed to be a very small constant value (for example, 1.01).

[0099] At operation S5, the aerosol extinction coefficient profile ratio of the dual-wavelength channel is obtained according to the simulated aerosol extinction coefficient profile and the inverted aerosol extinction coefficient profile; the total concentration of the aerosol is adjusted based on the aerosol extinction coefficient profile ratio, and the aerosol optical thickness value is calculated, and the aerosol component proportion is adjusted based on the aerosol optical thickness value.

[0100] In the embodiments of the present disclosure, the aerosol extinction coefficient profiles of the dual channels are obtained by using the optical property forward model of the mixed-mode aerosol and the Fernald inversion method respectively, the aerosol extinction coefficient profile ratio K of the dual-wavelength channel is obtained, and the total concentration of the aerosol is adjusted based on the aerosol component profile. At the same time, the aerosol optical thickness values obtained by using the optical property forward model of the mixed-mode aerosol and the Fernald inversion method respectively are compared to adjust the aerosol component proportion.

[0101] At operation S6, the new aerosol component profile is calculated according to the adjusted total concentration of the aerosol and the component proportion.

[0102] At operation S7, it is judged whether the result difference between the simulated aerosol extinction coefficient profile obtained at S3 and the inverted aerosol extinction coefficient profile obtained at S4 is less than a threshold value. If not, steps S3-S6 are repeated until the result difference between the simulated aerosol extinction coefficient profile obtained at S3 and the inverted aerosol extinction coefficient profile obtained at S4 is less than a threshold value, the iteration is ended, and the aerosol profile inversion is completed.

[0103] In the embodiments of the present disclosure, it is judged whether the result difference between the simulated aerosol extinction coefficient profile obtained at S3 and the inverted aerosol extinction coefficient profile obtained at S4 is less than a threshold value. If not, steps S3-S6 are repeated until the result difference between the simulated aerosol extinction coefficient profile obtained at S3 and the inverted aerosol extinction coefficient profile obtained at S4 is less than a threshold value, the iteration is ended, and the aerosol profile inversion is completed. The threshold value can be 20% of the aerosol extinction coefficient profile or other numerical values.

[0104] The aerosol profile inversion method based on dual-wavelength Mie scattering lidar data provided by the embodiments of the present disclosure can realize high-precision acquisition of aerosol extinction coefficient profile, component concentration profile, optical thickness, and lidar ratio, and achieve the purpose of accurate detection of atmospheric environment, and can be well applied in atmospheric detection lidar system, and is also conducive to determining the regional atmospheric aerosol mode.

[0105] Figure 5 A block diagram of an aerosol profile inversion device based on dual-wavelength Mie scattering lidar data according to an embodiment of the present disclosure is schematically shown.

[0106] As Figure 5As shown, the aerosol profile inversion device 500 based on dual-wavelength Mie scattering lidar data includes a data acquisition module 510, an optical property forward model construction module 520, a data simulation module 530, a data inversion module 540, an aerosol profile optimization module 550, an aerosol component profile updating module 560, and an inversion iteration module 570. The device 500 can be used to implement the method for aerosol profile inversion based on dual-wavelength Mie scattering lidar data as described above. Figure 1 The method for aerosol profile inversion based on dual-wavelength Mie scattering lidar data as described above.

[0107] The data acquisition module 510 is configured to acquire a corresponding aerosol component profile initial value according to the atmospheric sounding lidar data. The data acquisition module 510 can be used to perform the S1 step as described above. Figure 1 The S1 step as described above will not be repeated here.

[0108] The optical property forward model construction module 520 is configured to construct a mixed-mode aerosol optical property forward model. The optical property forward model construction module 520 can be used to perform the S2 step as described above. Figure 1 The S2 step as described above will not be repeated here.

[0109] The data simulation module 530 is configured to input the aerosol component profile initial value into the mixed-mode aerosol optical property forward model for simulation to obtain the aerosol lidar ratio corresponding to the dual-wavelength channel and the simulated aerosol extinction coefficient profile. The data simulation module 530 can be used to perform the S3 step as described above. Figure 1 The S3 step as described above will not be repeated here.

[0110] The data inversion module 540 is configured to obtain the inversion aerosol extinction coefficient profile of the atmospheric sounding lidar data by using the Fernald method based on the aerosol lidar ratio. The data inversion module 540 can be used to perform the S4 step as described above. Figure 1 The S4 step as described above will not be repeated here.

[0111] The aerosol profile optimization module 550 is configured to obtain the aerosol extinction coefficient profile ratio of the dual-wavelength channel according to the simulated aerosol extinction coefficient profile and the inversion aerosol extinction coefficient profile, adjust the total concentration of the aerosol profile based on the aerosol extinction coefficient profile ratio, and calculate the aerosol optical thickness value; and adjust the aerosol component proportion based on the aerosol optical thickness value. The aerosol profile optimization module 550 can be used to perform the S5 step as described above. Figure 1 The S5 step as described above will not be repeated here.

[0112] The aerosol component profile updating module 560 is configured to calculate a new aerosol component profile according to the adjusted total concentration of the aerosol and the proportion of each component. The aerosol component profile updating module 560 can be used to perform the S6 step as described above.Figure 1 The described S6 step is not repeated here.

[0113] The inversion iteration module 570 is configured to determine whether the result difference between the simulated aerosol extinction coefficient profile obtained by the data simulation module and the inversion aerosol extinction coefficient profile obtained by the data inversion module is less than a threshold value. If not, the data inversion is iterated until the result difference between the simulated aerosol extinction coefficient profile obtained by the data simulation module and the inversion aerosol extinction coefficient profile obtained by the data inversion module is less than a threshold value. The iteration ends, and the aerosol profile inversion is completed. The inversion iteration module 570 may, for example, be used to perform the above-mentioned S6 step. Figure 1 The described S7 step is not repeated here.

[0114] Any one or more of the modules, sub-modules, units, sub-units according to the embodiments of the present disclosure, or at least part of any one or more of the modules, sub-modules, units, sub-units can be implemented in one module. Any one or more of the modules, sub-modules, units, sub-units according to the embodiments of the present disclosure can be split into multiple modules for implementation. Any one or more of the modules, sub-modules, units, sub-units according to the embodiments of the present disclosure can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), an on-chip device, a device on a substrate, a device on a package, an application specific integrated circuit (ASIC), or any other reasonable way of hardware or firmware through integration or packaging of circuits, or in any one of software, hardware and firmware or in a proper combination of any of them. Alternatively, one or more of the modules, sub-modules, units, sub-units according to the embodiments of the present disclosure can be at least partially implemented as computer program modules that can perform corresponding functions when the computer program modules are run.

[0115] For example, any and more of the following modules can be combined into one module: data acquisition module 510, optical property forward model construction module 520, data simulation module 530, data inversion module 540, aerosol profile optimization module 550, aerosol composition profile update module 560, and inversion iteration module 570. Alternatively, any one of these modules can be split into multiple modules. Or, at least some of the functionality of one or more of these modules can be combined with at least some of the functionality of other modules and implemented in one module. According to embodiments of this disclosure, at least one of the data acquisition module 510, the optical property forward model construction module 520, the data simulation module 530, the data inversion module 540, the aerosol profile optimization module 550, the aerosol composition profile update module 560, and the inversion iteration module 570 can be at least partially implemented as hardware circuits, such as field-programmable gate arrays (FPGAs), programmable logic arrays (PLAs), on-chip devices, on-substrate devices, on-package devices, application-specific integrated circuits (ASICs), or any other reasonable means of integrating or packaging circuits, or implemented in software, hardware, or firmware, or in any one of the three implementation methods or any appropriate combination of any of them. Alternatively, at least one of the data acquisition module 510, the optical property forward model construction module 520, the data simulation module 530, the data inversion module 540, the aerosol profile optimization module 550, the aerosol composition profile update module 560, and the inversion iteration module 570 can be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0116] Figure 6 A block diagram schematically illustrates an electronic device suitable for implementing the methods described above, according to embodiments of the present disclosure. Figure 6 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0117] like Figure 6 As shown, the electronic device 600 described in this embodiment includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage portion 608 into a random access memory (RAM) 603. The processor 601 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include onboard memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to embodiments of this disclosure.

[0118] In the RAM 603, various programs and data required for the operation of the electronic device 600 are stored. The processor 601, the ROM 602, and the RAM 603 are connected to each other via the bus 604. The processor 601 performs various operations of the method flow according to the embodiments of the present disclosure by executing the programs in the ROM 602 and / or the RAM 603. It should be noted that the programs can also be stored in one or more memories other than the ROM 602 and the RAM 603. The processor 601 can also perform various operations of the method flow according to the embodiments of the present disclosure by executing the programs stored in the one or more memories.

[0119] According to an embodiment of the present disclosure, the electronic device 600 can further include an input / output (I / O) interface 605, which is also connected to the bus 604. The electronic device 600 can further include one or more of the following components connected to the I / O interface 605: an input part 606 including a keyboard, a mouse, etc.; an output part 607 including a display such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage part 608 including a hard disk, etc.; and a communication part 609 including a network interface card such as a LAN card, a modem, etc. The communication part 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as necessary. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is attached to the drive 610 as necessary, so that a computer program read out therefrom is installed in the storage part 608 as necessary.

[0120] According to an embodiment of the present disclosure, the method flow according to the embodiments of the present disclosure can be implemented as a computer software program. For example, the embodiments of the present disclosure include a computer program product including a computer program carried on a computer-readable storage medium, the computer program containing program codes for executing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network by the communication part 609, and / or installed from the removable medium 611. When the computer program is executed by the processor 601, the above-described functions defined in the apparatus of the embodiments of the present disclosure are performed. According to an embodiment of the present disclosure, the apparatus, device, apparatus, module, unit, etc. described above can be implemented by computer program modules.

[0121] The embodiment of the present disclosure further provides a computer readable storage medium, which can be included in the device / apparatus / arrangement described in the above embodiment, or can exist independently without being assembled into the device / apparatus / arrangement. The computer readable storage medium carries one or more programs, and when the one or more programs are executed, the method for retrieving aerosol profile based on dual-wavelength Mie scattering lidar data according to the embodiment of the present disclosure is implemented.

[0122] According to the embodiment of the present disclosure, the computer readable storage medium can be a non-volatile computer readable storage medium, for example, can include but is not limited to: portable computer diskette, hard disk, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), portable compact disc read only memory (CD-ROM), optical storage device, magnetic storage device, or any appropriate combination of the foregoing. In the embodiment of the present disclosure, the computer readable storage medium can be any tangible medium that contains or stores a program, which can be used by or in connection with an instruction execution device, apparatus or device. For example, according to the embodiment of the present disclosure, the computer readable storage medium can include the ROM 602 and / or the RAM 603 described above and / or one or more memories other than the ROM 602 and the RAM 603.

[0123] The embodiment of the present disclosure further includes a computer program product, which includes a computer program containing program codes for executing the method shown in the flow chart. When the computer program product is run in the computer device, the program codes are used to make the computer device implement the method for retrieving aerosol profile based on dual-wavelength Mie scattering lidar data provided by the embodiment of the present disclosure.

[0124] The above functions defined in the apparatus / arrangement of the embodiment of the present disclosure are executed when the computer program is executed by the processor 601. According to the embodiment of the present disclosure, the apparatus, arrangement, module, unit and the like described above can be implemented by the computer program modules.

[0125] In one embodiment, the computer program can rely on tangible storage media such as optical storage media, magnetic storage media and the like. In another embodiment, the computer program can also be transmitted, distributed and downloaded in the form of signals on network media, and be downloaded and installed through the communication part 609 and / or installed from the detachable medium 611. The program codes contained in the computer program can be transmitted by any appropriate network media, including but not limited to: wireless, wired and the like, or any appropriate combination of the foregoing.

[0126] In such embodiments, the computer program can be downloaded and installed from the network via the communication section 609, and / or installed from the removable media 611. When the computer program is executed by the processor 601, the above-described functions defined in the apparatus of the embodiments of the present disclosure are performed. According to the embodiments of the present disclosure, the apparatus, device, apparatus, module, unit, and the like described above can be implemented by the computer program modules.

[0127] According to the embodiments of the present disclosure, the program code for executing the computer program provided by the embodiments of the present disclosure can be written in any combination of one or more programming languages, and specifically, these computer programs can be implemented by using high-level procedural and / or object-oriented programming language, and / or assembly / machine language. The programming language includes, but is not limited to, such as Java, C++, python, “C” language or similar programming language. The program code can be executed entirely on the user computing device, partially on the user device, partially on a remote computing device, or entirely on a remote computing device or server. In the case involving a remote computing device, the remote computing device can be connected to the user computing device through any kind of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, connected through the Internet by using an Internet service provider).

[0128] It should be noted that each functional module in the various embodiments of the present disclosure can be integrated in one processing module, or each module can exist physically independently, or two or more modules can be integrated in one module. The integrated module can be realized in the form of hardware or in the form of a software functional module. When the integrated module is realized in the form of a software functional module and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present disclosure, essentially or in the form of a contribution to the prior art, or all or part of the technical solutions can be embodied in the form of a software product.

[0129] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using dedicated hardware-based means to perform the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0130] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this disclosure can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure can be combined and / or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0131] Although this disclosure has been shown and described with reference to specific exemplary embodiments thereof, those skilled in the art will understand that various changes in form and detail may be made to this disclosure without departing from the spirit and scope of the disclosure as defined by the appended claims and their equivalents. Therefore, the scope of this disclosure should not be limited to the above embodiments, but should be defined not only by the appended claims, but also by their equivalents.

Claims

1. A method for aerosol profile retrieval based on dual-wavelength Mie scattering lidar data, characterized in that, The method comprises the following steps: S1, obtaining an initial value of an aerosol composition profile according to atmospheric sounding lidar data; S2, constructing a mixed-mode aerosol optical property forward model; comprising: S21, obtaining an aerosol size spectrum distribution and a complex refractive index of aerosol according to the aerosol composition profile; S22, obtaining a mixed-mode aerosol optical characteristic parameter according to the aerosol size spectrum distribution and the complex refractive index of aerosol based on Mie scattering theory; wherein the mixed-mode aerosol optical characteristic parameter is used to realize the mixed-mode aerosol optical property forward model; wherein the aerosol size spectrum distribution is obtained according to the aerosol composition profile in S21, comprising: S211, calculating the volume concentration of each component according to the mass mixing ratio profile of the aerosol composition; S212, obtaining the volume spectrum distribution of the aerosol by using a logarithmic normal distribution function according to the volume concentration of each component of the aerosol; S213, calculating the number concentration spectrum distribution of the aerosol according to the volume spectrum distribution of the aerosol; S3, inputting the initial value of the aerosol composition profile into the mixed-mode aerosol optical property forward model for simulation to obtain an aerosol lidar ratio of a dual-wavelength channel and a simulated aerosol extinction coefficient profile; S4, obtaining an inversion aerosol extinction coefficient profile of the atmospheric sounding lidar data by using Fernald method based on the aerosol lidar ratio; S5, obtaining a ratio of aerosol extinction coefficient profiles of the dual-wavelength channel according to the simulated aerosol extinction coefficient profile and the inversion aerosol extinction coefficient profile, adjusting the total concentration of the aerosol based on the ratio of the aerosol extinction coefficient profiles, and calculating an aerosol optical thickness value, and adjusting the proportion of the aerosol composition based on the aerosol optical thickness value; S6, calculating a new aerosol composition profile according to the adjusted total concentration of the aerosol and the proportion of each component; S7, judging whether the result difference between the simulated aerosol extinction coefficient profile obtained in S3 and the inversion aerosol extinction coefficient profile obtained in S4 is less than a threshold value; if not, repeating steps S3-S6 until the result difference between the simulated aerosol extinction coefficient profile obtained in S3 and the inversion aerosol extinction coefficient profile obtained in S4 is less than a threshold value, and the iteration is ended, and the aerosol profile inversion is completed.

2. The dual-wavelength Mie scattering lidar data based aerosol profile retrieval method according to claim 1, characterized in that, The mixed-mode aerosol optical characteristic parameter comprises an extinction coefficient, a backscattering coefficient, an aerosol lidar ratio and an aerosol optical thickness of different types of aerosols.

3. The dual-wavelength Mie scattering lidar data based aerosol profile retrieval method according to claim 1, characterized in that, In S1, the initial value of the aerosol composition profile corresponding to the atmospheric sounding lidar data is obtained, comprising: S11, obtaining atmospheric sounding lidar data; S12, obtaining corresponding time information and latitude and longitude information according to the atmospheric sounding lidar data; S13, obtaining corresponding aerosol profile historical data from the fourth-generation global atmospheric composition reanalysis database of the European Centre for Medium-Range Weather Forecasts according to the time information and the latitude and longitude information; S14, obtaining the initial value of the aerosol composition profile corresponding to the atmospheric sounding lidar data by analyzing and evaluating the aerosol profile historical data.

4. The dual-wavelength Mie scattering lidar data based aerosol profile retrieval method according to claim 1, characterized in that, The S4 is based on the aerosol lidar ratio in the S4, and the Fernald method is used to obtain the inversion aerosol extinction coefficient profile of the atmospheric sounding lidar data, comprising: S41, selecting the aerosol backscattering coefficient corresponding to the position of the clean atmosphere near the tropopause as the boundary value of the inversion; S42, based on the aerosol lidar ratio and the boundary value, the Fernald method is used for inversion to obtain the inversion aerosol extinction coefficient profile of the atmospheric sounding lidar data.

5. The dual-wavelength Mie scattering lidar data based aerosol profile retrieval method according to claim 3, characterized in that, The aerosol profile data includes one or more of dust, sea salt, sulfate, organic matter and black carbon aerosol.

6. An apparatus for aerosol profile retrieval based on dual-wavelength Mie scattering lidar data, characterized in that, Comprising: Data acquisition module, for acquiring corresponding aerosol component profile initial value according to atmospheric sounding lidar data; Optical property forward model construction module, for constructing mixed mode aerosol optical property forward model; comprising: obtaining aerosol size spectrum distribution and aerosol complex refractive index according to the aerosol component profile; based on Mie scattering theory, obtaining mixed mode aerosol optical characteristic parameters according to the aerosol size spectrum distribution and the aerosol complex refractive index; wherein the mixed mode aerosol optical characteristic parameters are used to realize the mixed mode aerosol optical property forward model; the aerosol size spectrum distribution is obtained according to the aerosol component profile, comprising: calculating the volume concentration of each component according to the mass mixing ratio profile of aerosol component; the volume concentration of each component of the aerosol is obtained by using the logarithmic normal distribution function; the aerosol number concentration spectrum distribution is calculated according to the volume spectrum distribution of the aerosol; Data simulation module, for inputting the aerosol component profile initial value into the mixed mode aerosol optical property forward model for simulation to obtain the aerosol lidar ratio corresponding to the double wavelength channel and the simulated aerosol extinction coefficient profile; Data inversion module, based on the aerosol lidar ratio, using Fernald method to obtain the inversion aerosol extinction coefficient profile of the atmospheric sounding lidar data; Aerosol profile optimization module, for obtaining the ratio of aerosol extinction coefficient profile of double wavelength channel according to the simulated aerosol extinction coefficient profile and the inversion aerosol extinction coefficient profile, adjusting the total concentration of aerosol profile based on the ratio of aerosol extinction coefficient profile, and calculating the aerosol optical thickness value; adjusting the proportion of aerosol component based on the aerosol optical thickness value; Aerosol component profile updating module, for calculating new aerosol component profile according to the adjusted total concentration of aerosol and the proportion of each component; Inversion iteration module, for judging whether the result difference between the simulated aerosol extinction coefficient profile obtained in the data simulation module and the inversion aerosol extinction coefficient profile obtained in the data inversion module is less than a threshold value; if not, data inversion iteration, until the result difference between the simulated aerosol extinction coefficient profile obtained in the data simulation module and the inversion aerosol extinction coefficient profile obtained in the data inversion module is less than a threshold value, iteration ends, and the inversion of aerosol profile is completed.

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