Calibration method for temperature and humidity Raman laser radar in high aerosol concentration scene

Abstract

The invention discloses a calibration method for a temperature and humidity Raman laser radar in a high aerosol concentration scene, and the method comprises the steps: carrying out the interpolation operation of an aerosol extinction coefficient through an aerosol wavelength index, so as to obtain the aerosol extinction coefficients corresponding to the wavelength of 353 nm, the wavelength of 354 nm and the wavelength of 407 nm; a mixed signal ratio is calculated based on the aerosol extinction coefficients corresponding to the wavelength of 387 nm and the wavelength of 407 nm, the mixed signal ratio is used for correcting the first aerosol transmittance difference, and a water vapor Raman calibration constant is calculated in combination with a water vapor mixing ratio profile obtained by the sonde; and calculating a high-order and low-order rotation signal ratio based on the aerosol extinction coefficients corresponding to the wavelength of 353 nm and the wavelength of 354 nm, the high-order and low-order rotation signal ratio being used for correcting the second aerosol transmittance difference so as to calculate a temperature measurement channel calibration constant in combination with the temperature profile acquired by the sonde. Through the scheme disclosed by the invention, the calibration precision can be improved.

Description

Technical Field

[0001] The present disclosure relates to the field of measurement, and in particular to a temperature and humidity Raman lidar calibration method for high aerosol concentration scenarios. Background Art

[0002] Temperature and humidity Raman lidar has become an important tool in the field of atmospheric remote sensing, playing a key role in meteorological observation, environmental monitoring and climate research. However, in order to ensure the measurement accuracy and reliability of this advanced equipment, the calibration of temperature and humidity Raman lidar has become a crucial link. The calibration process involves the precise calibration of the system parameters of the instrument to eliminate or reduce the influence of various error sources, so as to obtain accurate atmospheric temperature and humidity profiles. The calibration of temperature and humidity Raman lidar is of great significance for improving the quality of atmospheric observation data, supporting the improvement of weather forecast models and deepening the understanding of atmospheric processes. At present, the calibration of temperature and humidity Raman lidar mainly relies on traditional comparative observation methods, such as synchronous measurements of reference instruments such as sounding balloons and microwave radiometers. The working principle of these methods is to establish a correction function or lookup table by comparing the measurement results of the Raman lidar with the data of the reference instrument to correct the original signal of the lidar. However, these existing technologies have some problems: first, the measurement errors of the reference instrument itself will introduce additional uncertainties; second, the spatiotemporal changes in atmospheric conditions may lead to insufficient representativeness of synchronous observations; third, the calibration process is usually time-consuming and difficult to perform frequently, and cannot reflect the dynamic changes in instrument performance in a timely manner.

[0003] To solve the above problems, researchers have proposed a variety of improvement methods. These include using atmospheric radiation transfer models for theoretical calculation-assisted calibration, improving the reliability of calibration through a comprehensive observation network of multiple instruments, and developing an automated calibration system to improve calibration efficiency. However, these methods still have some defects compared to the calibration technology of the new temperature and humidity Raman lidar. For example, theoretical model calculations rely on accurate input of atmospheric parameters, which are often difficult to obtain accurately in the actual atmosphere; although the comprehensive observation network can provide more comprehensive information, it increases the system complexity and operating costs; although the automated calibration system improves efficiency, it may not be able to fully adapt to the complex and changing atmospheric environment.

[0004] Therefore, a technical solution is urgently needed to improve the calibration accuracy. Summary of the invention

[0005] In order to solve the shortcomings of the prior art, the embodiment of the present disclosure provides a calibration method for a temperature and humidity Raman lidar in a high aerosol concentration scenario. The present disclosure solves the technical problems of the prior art such as large calibration constant error and low precision.

[0006] The embodiment of the present disclosure provides a calibration method for a temperature and humidity Raman lidar in a high aerosol concentration scenario, including: collecting elastic scattering and / or Raman scattering signals of multiple wavelengths, the signals including 355nm elastic scattering signals, 387nm Raman scattering signals, 532nm elastic scattering signals and / or 607nm Raman scattering signals; iteratively inverting the collected signals to obtain an aerosol wavelength index, an aerosol extinction coefficient corresponding to the 387nm wavelength and the 607nm wavelength respectively; interpolating the aerosol extinction coefficient using the aerosol wavelength index to obtain a 353nm wavelength. , 354nm and 407nm respectively corresponding to the aerosol extinction coefficient; based on the aerosol extinction coefficient corresponding to the wavelength of 387nm and 407nm respectively, the mixed signal ratio is calculated, and the mixed signal ratio is used to correct the first aerosol transmittance difference, so as to calculate the water vapor Raman calibration constant in combination with the water vapor mixing ratio profile obtained by the sounding instrument; based on the aerosol extinction coefficient corresponding to the wavelength of 353nm and 354nm respectively, the high-order and low-order rotation signal ratio is calculated, and the high-order and low-order rotation signal ratio is used to correct the second aerosol transmittance difference, so as to calculate the temperature measurement channel calibration constant in combination with the temperature profile obtained by the sounding instrument.

[0007] In a possible implementation, before iterative inversion is performed on the collected signal, the method further includes: removing background noise and correcting the noise-reduced signal; including: P c (z i )=P′(z i )-B, where P(z i ) represents the received signal sequence, z i represents the signal of the i-th range gate, τ represents the detector dead time, P′(z i ) represents the dead time corrected signal sequence, B represents the background noise, P c (z i ) indicates the signal sequence after background correction.

[0008] In a possible implementation, the aerosol extinction coefficient is interpolated using the aerosol wavelength index to obtain the aerosol extinction coefficients corresponding to the wavelengths of 353 nm, 354 nm and 407 nm, respectively, including: Where A represents the aerosol wavelength index, that is, the relationship between the aerosol extinction coefficient and the incident wavelength, and α(λ1) and α(λ2) represent the aerosol extinction coefficients at known wavelengths λ1 and λ2, respectively.

[0009] In a possible implementation, the mixed signal ratio is calculated based on the aerosol extinction coefficients corresponding to the wavelength of 387 nm and the wavelength of 407 nm, respectively, including: Among them, R mix(z n ) represents the mixed signal ratio, P(407) and P(386) represent the 407nm and 386nm wavelength signals respectively, α(386) represents the aerosol extinction coefficient at 387nm, α(407) represents the aerosol extinction coefficient at 407nm, Δz i Indicates the resolution of the i-th distance.

[0010] In a possible implementation, the water vapor Raman calibration constant is calculated in combination with the water vapor mixing ratio profile obtained by the radiosonde, including: in, represents the water vapor Raman calibration constant, w r (z i ) represents the water vapor mixing ratio obtained by the radiosonde at the i-th point, R mix (z i ) represents the mixed signal ratio of the i-th point, and n represents the corresponding number of points in the calibration range.

[0011] In one possible implementation, the high-order and low-order rotation signal ratios are calculated based on the aerosol extinction coefficients corresponding to the wavelengths of 353 nm and 354 nm, respectively, including: Among them, R HL (z n ) represents the ratio of high-order and low-order rotation signals, P(353) and P(354) represent the 353nm and 354nm wavelength signals respectively, α 353 represents the aerosol extinction coefficient at 353nm wavelength, α 354 represents the aerosol extinction coefficient at 354 nm, Δz i Indicates the resolution of the i-th distance.

[0012] In one possible implementation, the temperature channel calibration constant is calculated in combination with the temperature profile obtained by the radiosonde, including: y = ax 2 +bx+c; y=ln R HL (z i ), where a, b, and c represent the temperature measurement channel calibration constants, T(z i ) represents the temperature at the i-th point in the temperature profile obtained by the radiosonde, R HL (z i ) represents the ratio of high-order and low-order rotation signals at the i-th point, and y and x represent the fitting independent variables.

[0013] In the temperature and humidity Raman lidar calibration method for high aerosol concentration scenarios provided above, by correcting the aerosol transmittance difference term and combining it with the radiosonde data at the same time, the water vapor Raman calibration and the temperature measurement channel calibration can be corrected, thereby improving the calibration accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0015] Figure 1 A schematic flow chart of a calibration method for a temperature and humidity Raman lidar provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0016] Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present disclosure unless otherwise specifically stated.

[0017] Those skilled in the art can understand that the terms "first", "second" and the like in the embodiments of the present disclosure are only used to distinguish different steps, devices or modules, etc., and neither represent any specific technical meaning nor represent the necessary logical order between them. It should also be understood that in the embodiments of the present disclosure, "multiple" can refer to two or more, and "at least one" can refer to one, two or more. It should also be understood that for any component, data or structure mentioned in the embodiments of the present disclosure, in the absence of explicit limitation or contrary revelation given in the context, it can generally be understood as one or more. In addition, the term "and / or" in the present disclosure is only a description of the association relationship of the associated objects, indicating that there can be three relationships, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present disclosure generally indicates that the associated objects before and after are an "or" relationship. It should also be understood that the description of each embodiment in the present disclosure emphasizes the differences between the embodiments, and the same or similar parts can refer to each other. For the sake of brevity, they will not be repeated one by one.

[0018] At the same time, it should be understood that, for ease of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present disclosure and its application or use. The techniques, methods and devices known to ordinary technicians in the relevant fields may not be discussed in detail, but where appropriate, the techniques, methods and devices should be considered part of the specification. It should be noted that similar numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0019] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0020] Figure 1 A flow chart of a calibration method for a temperature and humidity Raman lidar provided in an embodiment of the present disclosure. It should be understood that the working principle of the temperature and humidity Raman lidar is based on the Raman scattering effect. When the laser beam irradiates the atmospheric molecules, a small part of the photons will undergo inelastic scattering, namely Raman scattering. The wavelength of the scattered light is different from that of the incident light, and this wavelength is related to the vibration and rotational energy levels of the scattering molecules. By analyzing the returned Raman scattered light, information about different components in the atmosphere can be obtained. Raman scattering is an inelastic scattering process, and the energy of the scattered photons is different from that of the incident photons. For atmospheric molecules, there are mainly two types of Raman scattering: vibration Raman scattering, which is related to the vibrational energy level transition of the molecules; rotational Raman scattering, which is related to the rotational energy level transition of the molecules. The spectral lines generated by these two scattering processes are called Raman spectral lines, and their wavelength and intensity contain information about the molecular structure and concentration.

[0021] The receiving system of temperature and humidity Raman lidar usually needs to have the following channels. Elastic scattering receiving channel: 355nm, 532nm and 1064nm; rotational Raman scattering channel: 353nm and 354nm (high and low order quantum numbers); nitrogen molecule vibration Raman scattering channel: 387nm and 607nm; water vapor vibration Raman scattering channel: 407nm. These receiving channels achieve spectral separation through precise optical spectroscopic systems and narrow-band filters.

[0022] Furthermore, calibration is a key step to ensure the measurement accuracy of temperature and humidity Raman LiDAR. It mainly includes two aspects: water vapor Raman calibration and temperature measurement channel calibration. Water vapor Raman calibration mainly involves the channel gain ratio calibration of the 407nm water vapor Raman channel and the 387nm nitrogen Raman channel. The temperature measurement channel calibration involves the channel gain ratio calibration of the 353nm and 354nm high and low order quantum number rotation Raman channels.

[0023] The applicant found that in the prior art, the fixed value wavelength index used in the water vapor Raman calibration cannot reflect the state of the real atmospheric aerosol, such as coarse particle aerosol (sand, sea salt and pollen, etc.) has a wavelength index close to 0, while fine particle aerosol (sulfate, smoke and secondary organic aerosol, etc.) has a wavelength index greater than 1.5. When the aerosol concentration in the atmosphere is high, the transmittance correction term error caused by the wavelength index deviation will be amplified, so that the water vapor Raman calibration constant error exceeds 10%, which is difficult to meet the high-precision inversion requirements of water vapor in business applications. At the same time, for the high-order and low-order rotational Raman signal ratio used in the temperature measurement channel calibration, it ignores the difference in aerosol wavelength transmittance at 353nm and 354nm. When the aerosol concentration in the atmosphere is high, this difference will produce a temperature measurement channel calibration constant deviation of more than 5%, which will eventually be transmitted to the temperature inversion, causing the temperature inversion error to exceed 2K, which is difficult to meet the high-precision temperature inversion requirements in business applications.

[0024] Therefore, in view of the characteristics of the temperature and humidity Raman lidar detection channel, this disclosure proposes a temperature and humidity Raman lidar calibration method that can be applied to high aerosol concentration scenes. Figure 1 As shown, at step S101, elastic scattering and / or Raman scattering signals of multiple wavelengths are collected, and the signals include 355nm elastic scattering signals, 387nm Raman scattering signals, 532nm elastic scattering signals and / or 607nm Raman scattering signals.

[0025] The laser can emit pulsed lasers of 355nm, 532nm and 1064nm, the receiving telescope collects the returned scattered light signals, the spectroscopic system separates the signals of different wavelengths into the corresponding detectors, and the data acquisition system records the photoelectric signal intensity of each channel.

[0026] At step S102, the collected signals are iteratively inverted to obtain the aerosol wavelength index, the aerosol extinction coefficient corresponding to the 387nm wavelength and the 607nm wavelength. The iterative inversion algorithm may include but is not limited to physical models such as the Klett-Fernald inversion algorithm. For example, the initialization assumes the initial aerosol wavelength index and extinction coefficient; the model calculates the theoretical elastic scattering and Raman scattering signals based on the current parameters; the error calculation compares the theoretical signal and the measured signal, and calculates the error function. The parameter update uses an optimization algorithm (such as the Levenberg-Marquardt algorithm) to update the parameters. The above steps are repeated iteratively until the error is less than a preset threshold or the maximum number of iterations is reached.

[0027] In addition, before iterative inversion of the acquired signal, background noise can be removed and the noise-reduced signal can be corrected; including: P c(z i )=P′(z i )-B, where P(z i ) represents the received signal sequence, z i represents the signal of the i-th range gate, τ represents the detector dead time, P′(z i ) represents the dead time corrected signal sequence, B represents the background noise, P c (z i ) indicates the signal sequence after background correction.

[0028] In step S103, the aerosol extinction coefficient is interpolated using the aerosol wavelength index to obtain the aerosol extinction coefficients corresponding to the wavelengths of 353 nm, 354 nm and 407 nm, respectively. The interpolation operation may include:

[0029]

[0030] Wherein, β(λ) represents the aerosol extinction coefficient at the interpolated wavelength λ, β(λ1) represents the aerosol extinction coefficient at the first wavelength λ1, β(λ2) represents the aerosol extinction coefficient at the second wavelength λ2, wherein λ1<λ<λ2, A represents the shape coefficient of the interpolation curve, and m and n represent the curvature coefficients of the interpolation curve. In an implementation scenario, λ1 is a wavelength of 387nm, and λ2 is a wavelength of 607nm. By substituting into the interpolation formula, the aerosol extinction coefficients corresponding to the wavelengths of 353nm, 354nm, and 407nm can be obtained.

[0031] In another embodiment, it may also include: Where A represents the aerosol wavelength index, that is, the relationship between the aerosol extinction coefficient and the incident wavelength; α(λ1) and α(λ2) represent the aerosol extinction coefficients at known wavelengths λ1 and λ2, respectively.

[0032] In step S104, a mixed signal ratio is calculated based on the aerosol extinction coefficients corresponding to the 387 nm wavelength and the 407 nm wavelength, and the mixed signal ratio is used to correct the first aerosol transmittance difference, so as to calculate the water vapor Raman calibration constant in combination with the water vapor mixing ratio profile obtained by the radiosonde.

[0033] First, the mixed signal ratio is calculated based on the aerosol extinction coefficients corresponding to the 387nm wavelength and the 407nm wavelength: Among them, R mix (z n) represents the mixed signal ratio, P(407) and P(386) represent the 407nm and 386nm wavelength signals respectively, α(386) represents the aerosol extinction coefficient at 387nm, α(407) represents the aerosol extinction coefficient at 407nm, Δz i Indicates the resolution of the i-th distance.

[0034] Then, after obtaining the mixed signal ratio, the first aerosol transmittance difference is corrected using the mixed signal ratio: Among them, T corr-1 represents the corrected first aerosol transmittance difference, T orig-1 It represents the original first aerosol transmittance difference, and its value range is usually between -0.3 and 0.3. mix represents the mixed signal ratio, S 387 Indicates the signal intensity at 387nm wavelength, S 407 represents the signal intensity at 407nm wavelength, κ 387 represents the aerosol extinction coefficient at 387 nm, κ 407 It represents the aerosol extinction coefficient at a wavelength of 407nm.

[0035] Next, the water vapor Raman calibration constant is calculated based on the water vapor mixing ratio profile obtained by the radiosonde: in, represents the water vapor Raman calibration constant, h max represents the maximum detection altitude, q(h) represents the water vapor mixing ratio profile obtained by the radiosonde, α 387 represents the aerosol extinction coefficient at 387nm wavelength, α 407 represents the aerosol extinction coefficient at a wavelength of 407 nm, h represents the height, and τ corr-1 represents the corrected first aerosol transmittance difference. In another embodiment, it can also be simplified as: in, represents the water vapor Raman calibration constant, w r (z i ) represents the water vapor mixing ratio obtained by the radiosonde at the i-th point, R mix (z i ) represents the mixed signal ratio of the i-th point, and n represents the corresponding number of points in the calibration range.

[0036] In step S105, the high-order and low-order rotation signal ratios are calculated based on the aerosol extinction coefficients corresponding to the wavelengths of 353 nm and 354 nm respectively. The high-order and low-order rotation signal ratios are used to correct the difference in the second aerosol transmittance, so as to calculate the temperature measurement channel calibration constants in combination with the temperature profile obtained by the sounding instrument.

[0037] First, the ratio of high-order and low-order rotation signals is calculated based on the aerosol extinction coefficients corresponding to the wavelengths of 353 nm and 354 nm: Among them, R HL (z n ) represents the ratio of high-order and low-order rotation signals, P(353) and P(354) represent the 353nm and 354nm wavelength signals respectively, α 353 represents the aerosol extinction coefficient at 353nm wavelength, α 354 represents the aerosol extinction coefficient at 354 nm, Δz i Indicates the resolution of the i-th distance. HL When it is close to 1 (i.e., the high-order and low-order signals are similar), the correction term is close to 0, and the transmittance remains almost unchanged. HL The correction effect is more pronounced when the extinction coefficients deviate significantly from 1. The greater the difference in extinction coefficients, the more pronounced the correction effect.

[0038] Then, after obtaining the high-order and low-order rotation signals, the high-order and low-order rotation signals are used to correct the second aerosol transmittance difference: Among them, T corr-2 represents the corrected second aerosol transmittance difference, T orig-2 Represents the original second aerosol transmittance difference, and its value range is usually between -0.1 and 0.1. 353 represents the aerosol extinction coefficient at 353nm wavelength, α 354 represents the aerosol extinction coefficient at 354 nm wavelength, R HL represents the ratio of high-order and low-order rotation signals, λ 354 Indicates 354nm wavelength, λ 353 Indicates 353nm wavelength.

[0039] Next, the temperature channel calibration constant is calculated based on the temperature profile obtained by the radiosonde: Among them, C T Indicates the temperature measurement channel calibration constant, λ 354 Indicates 354nm wavelength, λ 353 represents the wavelength of 353 nm, z0 and z1 represent the height boundaries of the sounding, σ 353 represents the aerosol extinction coefficient at 353 nm wavelength, σ 354 represents the aerosol extinction coefficient at a wavelength of 354 nm, H represents the atmospheric scale height, T corr-2 represents the corrected second aerosol transmittance difference, T(z) represents the temperature profile, and z represents the sounding height. In another embodiment, it can also be simplified to a quadratic function: y=ax 2 +bx+c; y=ln R HL (z i), where a, b, and c represent the temperature measurement channel calibration constants, T(z i ) represents the temperature at the i-th point in the temperature profile obtained by the radiosonde, R HL (z i ) represents the ratio of high-order and low-order rotation signals at the i-th point, and y and x represent the fitting independent variables.

[0040] It should be noted that the formulas described in the above embodiments involve multiple empirical constants and system parameters, which can be obtained by performing multiple iterative fitting of historical data sets, including but not limited to combining gradient descent method, genetic algorithm, simulated annealing algorithm, etc.

[0041] In summary, the disclosed embodiment makes full use of the multi-wavelength receiving characteristics of the temperature and humidity Raman lidar, adopts the iterative multi-wavelength Raman lidar inversion method to obtain the accurate aerosol wavelength index and the aerosol extinction coefficient at two wavelengths, and interpolates the aerosol extinction coefficient at other bands, so that the difference in aerosol wavelength transmittance between different channels can be corrected, greatly reducing the calibration error in high aerosol concentration scenarios. The calibration accuracy of the temperature and humidity lidar can be effectively improved, so that the calibration accuracy of the water vapor Raman channel in high aerosol concentration scenarios is better than 10%, and the calibration accuracy of the temperature measurement channel is better than 5%, ultimately improving the accuracy of the temperature and humidity products.

[0042] Furthermore, an embodiment of the present disclosure also provides a calibration device for a temperature and humidity Raman lidar, comprising: a processor, a memory, and a system bus; the processor and the memory are connected via the system bus; the memory is used to store one or more programs, and the one or more programs include instructions, which, when executed by the processor, enable the processor to execute any of the above methods.

[0043] Furthermore, an embodiment of the present disclosure also provides a computer program product, which, when executed on a terminal device, enables the terminal device to execute any one of the above processing methods.

[0044] It can be known from the description of the above implementation mode that those skilled in the art can clearly understand that all or part of the steps in the above-mentioned embodiment method can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present disclosure is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network communication device such as a media gateway, etc.) to execute the methods described in each embodiment of the present disclosure or some parts of the embodiments.

[0045] It should be noted that the various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the various embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0046] It should also be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0047] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A calibration method for temperature and humidity Raman lidar in high aerosol concentration scenarios. It is characterized in that include: Collecting elastic scattering and / or Raman scattering signals of multiple wavelengths, the signals including 355nm elastic scattering signals, 387nm Raman scattering signals, 532nm elastic scattering signals and / or 607nm Raman scattering signals; The collected signals are iteratively inverted to obtain the aerosol wavelength index, the aerosol extinction coefficient corresponding to the wavelength of 387nm and 607nm: The aerosol extinction coefficient is interpolated using the aerosol wavelength index to obtain the aerosol extinction coefficients corresponding to the wavelengths of 353 nm, 354 nm, and 407 nm. The mixed signal ratio is calculated based on the aerosol extinction coefficients corresponding to the wavelengths of 387 nm and 407 nm, respectively. The mixed signal ratio is used to correct the difference in the first aerosol transmittance, so as to calculate the water vapor Raman calibration constant in combination with the water vapor mixing ratio profile obtained by the radiosonde; The high-order and low-order rotation signal ratios are calculated based on the aerosol extinction coefficients corresponding to the wavelengths of 353 nm and 354 nm respectively. The high-order and low-order rotation signal ratios are used to correct the difference in the second aerosol transmittance, so as to calculate the temperature measurement channel calibration constants in combination with the temperature profile obtained by the radiosonde.

2. The calibration method according to claim 1, It is characterized in that in, Before iterative inversion of the acquired signal, it also includes: Remove background noise and perform corrections on the noise-reduced signal; these include: P c (z i )=P′(z i )-B, Among them, P(z i ) represents the received signal sequence, z i represents the signal of the i-th range gate, τ represents the detector dead time, P′(z i ) represents the dead time corrected signal sequence, B represents the background noise, P c (z i ) indicates the signal sequence after background correction.

3. The calibration method according to claim 1, It is characterized in that in, The aerosol extinction coefficient is interpolated using the aerosol wavelength index to obtain the aerosol extinction coefficients corresponding to the wavelengths of 353 nm, 354 nm, and 407 nm, including: Where A represents the aerosol wavelength index, that is, the relationship between the aerosol extinction coefficient and the incident wavelength, α(λ 1 ) and α(λ 2 ) represent the known wavelength λ 1 and λ 2 The aerosol extinction coefficient at .

4. The calibration method according to claim 1, It is characterized in that in, The mixed signal ratio is calculated based on the aerosol extinction coefficients corresponding to the 387nm wavelength and the 407nm wavelength, including: Among them, R mix (z n ) represents the mixed signal ratio, P(407) and P(386) represent the 407nm and 386nm wavelength signals respectively, α(386) represents the aerosol extinction coefficient at 387nm, α(407) represents the aerosol extinction coefficient at 407nm, Δz i Indicates the resolution of the i-th distance.

5. The calibration method according to claim 1, It is characterized in that in, Combined with the water vapor mixing ratio profile obtained by the radiosonde, the water vapor Raman calibration constant is calculated, including: in, represents the water vapor Raman calibration constant, w r (z i ) represents the water vapor mixing ratio obtained by the radiosonde at the i-th point, R mix (z i ) represents the mixed signal ratio of the i-th point, and n represents the corresponding number of points in the calibration range.

6. The calibration method according to claim 1, It is characterized in that in, The ratio of high-order and low-order rotation signals is calculated based on the aerosol extinction coefficients corresponding to the wavelengths of 353nm and 354nm, including: Among them, R HL (z n ) represents the ratio of high-order and low-order rotation signals, P(353) and P(354) represent the 353nm and 354nm wavelength signals respectively, α 353 represents the aerosol extinction coefficient at 353nm wavelength, α 354 represents the aerosol extinction coefficient at 354 nm, Δz i Indicates the resolution of the i-th distance.

7. The calibration method according to claim 1, It is characterized in that in, Combined with the temperature profile obtained by the radiosonde, the temperature channel calibration constants are calculated, including: y=ax 2 +bx+c; y=ln R HL (z i ), Among them, a, b, c represent the calibration constants of the temperature measurement channel, T(z i ) represents the temperature at the i-th point in the temperature profile obtained by the radiosonde, R HL (z i ) represents the ratio of high-order and low-order rotation signals at the i-th point, and y and x represent the fitting independent variables.

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