Atmospheric stratosphere nitric acid chloride vertical profile inversion algorithm based on ground-based remote sensing

Abstract

The invention relates to the technical field of atmospheric stratosphere nitric acid chloride vertical profile inversion, in particular to an atmospheric stratosphere nitric acid chloride vertical profile inversion algorithm based on foundation remote sensing. According to the technical scheme, the method comprises the following steps: determining a gas spectrum inversion fitting window, acquiring a C LONO2 gas spectral line parameter and an absorption cross section according to a high-resolution molecular parameter database, and selecting a window according to spectral absorption line characteristics of target gas and interference gas to invert atmosphere C LONO2; and performing inversion model parameter setting, and obtaining a vertical profile of the target gas from the high-resolution spectral data. According to the method, the vertical profile of the atmospheric stratosphere nitric acid chloride is effectively inverted from the foundation remote sensing spectral data, high-precision nitric acid chloride concentration vertical distribution information is provided, and data support is provided for monitoring the total amount of active chlorine in the stratosphere and researching the characteristics of ozone-destroying substances; the algorithm can be suitable for inversion of hyperspectral data observed by any foundation remote sensing, and the algorithm has strong adaptability.

Description

Technical Field

[0001] The invention relates to the technical field of vertical profile inversion of stratospheric nitrate chloride, and in particular to an inversion algorithm of vertical profile of stratospheric nitrate chloride based on ground-based remote sensing. Background Art

[0002] The UN-supported Scientific Assessment Panel of the Montreal Protocol on Substances that Deplete the Ozone Layer published the executive summary of the 2022 Scientific Assessment Report on Ozone Depletion at the 103rd Annual Meeting of the American Meteorological Society. The report shows the satellite measurement results of chlorine. In the altitude range of the ozone layer in the mid-latitude region, the reservoir gases hydrogen chloride (HCl) and CLONO2 account for about 90% of the available chlorine. Although they do not react directly with ozone, they will release active chlorine (chlorine radicals such as Cl, ClO, ClO2 and other species) that destroy ozone. By analyzing the content of the two, the content of active chlorine that depletes ozone can be inferred, and the distribution of active chlorine at the vertical height of the stratosphere can be mastered. my country is located in the middle and high latitudes. In order to explore the process of ozone depletion, it is crucial to obtain the vertical profiles of atmospheric stratospheric chlorine reservoir gases (HCL and CLONO2) in non-polar regions. At present, the research on the vertical profile inversion algorithm of atmospheric HCL measured by ground-based remote sensing at home and abroad is relatively mature, while there are fewer ground-based remote sensing stratospheric atmospheric CLONO2 inversion algorithms. Ground-based high-resolution FTIR spectroscopy has the advantage of high-precision detection of the vertical profile and column total of trace gases in the entire atmosphere. In view of this, we propose an inversion algorithm for the vertical profile of stratospheric nitrate chloride based on ground-based remote sensing. Summary of the invention

[0003] The purpose of the present invention is to address the problem of lack of ground-based remote sensing stratospheric atmospheric CLONO2 vertical distribution inversion algorithm in the background technology, and to propose a vertical profile inversion algorithm of atmospheric stratospheric nitrate chloride based on ground-based remote sensing.

[0004] The technical solution of the present invention is an inversion algorithm for the vertical profile of nitrate chloride in the stratosphere of the atmosphere based on ground-based remote sensing, comprising the following steps:

[0005] Determine the gas spectrum inversion fitting window, obtain the ClONO2 gas spectrum line parameters and absorption cross section based on the high-resolution molecular parameter database, and select the window to invert atmospheric ClONO2 according to the absorption line characteristics of the target gas and interfering gas spectra;

[0006] The inversion model parameters are set, and atmospheric pressure, temperature and water vapor prior profile parameters are obtained from atmospheric reanalysis data to determine the atmospheric initial state vector x a , using the global atmospheric model to simulate and generate the prior profiles of target gases and interfering gases;

[0007] Simulate the solar transmittance spectrum and set the initial state vector x a Substitute it into the forward model, and calculate the transmittance spectrum of sunlight after passing through the entire atmosphere by combining atmospheric radiation transmission with instrument linear parameters, solar spectrum parameters, gas prior profiles, atmospheric temperature, pressure and humidity profiles;

[0008] Carry out spectral fitting, substitute the simulated spectrum and the measured spectrum after quality control into the iterative algorithm, and determine whether the iteration ends by judging the cost function value. If it is less than the threshold, the iteration converges to obtain the atmospheric vertical profile parameters representing the real atmospheric state, otherwise update the state vector and continue the iteration;

[0009] Separate the stratospheric vertical profile, separate the stratospheric ClONO2 vertical profile in a specific height range from the obtained atmospheric parameters of each layer of the target gas, and integrate it to obtain the stratospheric atmospheric partial column content.

[0010] Optionally, the high-resolution molecular parameter database is HITRAN2012.

[0011] Optionally, in the separation stratosphere vertical profile, the specific height range is 20-40 km.

[0012] Optionally, the atmospheric reanalysis data are reanalysis data from the National Centers for Environmental Prediction of the United States, and the global atmospheric model is a global atmospheric climate model.

[0013] Optionally, in the inversion model parameter setting, a Tikhonov-Phillips regularization algorithm is used to constrain the prior covariance matrix.

[0014] Optionally, in the spectrum fitting step, the cost function is expressed by the following formula:

[0015]

[0016] The right side of the equation represents the measured value consisting of m elements and the inversion state vector consisting of n elements; F m and x n represent measurement error and a priori error respectively.

[0017] Optionally, in the spectrum fitting step, the iterative algorithm adopts a nonlinear least squares fitting optimal estimation method.

[0018] Optionally, in the simulated solar transmittance spectrum, the initial state vector of the atmosphere is substituted into a forward model, and the forward model simulates and obtains a calculated spectrum based on a priori gas profiles, atmospheric temperature and pressure profiles, solar spectrum parameters, and instrument functions.

[0019] Compared with the prior art, the present invention has the following beneficial technical effects:

[0020] 1) High-precision inversion results: The algorithm can effectively invert the vertical profile of stratospheric nitrate chlorine from ground-based remote sensing spectral data, providing high-precision vertical distribution information of nitrate chlorine concentration. It provides data support for the monitoring of the total amount of active chlorine in the stratosphere and the study of the characteristics of ozone-depleting substances, and is of great significance to atmospheric science research and the verification of climate change models.

[0021] 2) The algorithm has strong adaptability: The algorithm is combined with ground-based remote sensing equipment and is not limited to the inversion of spectra of high-resolution FTIR spectrometers. It can be applied to the inversion of any hyperspectral data of ground-based remote sensing observations. The algorithm has strong adaptability. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a flowchart of the inversion algorithm of the atmospheric stratospheric CLONO2 vertical profile based on ground-based remote sensing;

[0023] Figure 2 The spectral fitting results and residual graph of CLONO2 in a wide window;

[0024] Figure 3 The spectral fitting results and residual graph of CLONO2 in a narrow window;

[0025] Figure 4 This is an example of the vertical profile of CLONO2 in the entire atmosphere obtained using this algorithm. DETAILED DESCRIPTION

[0026] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments.

[0027] The components of the embodiments of the present invention generally described and shown in the drawings herein may be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention.

[0028] Example

[0029] In the embodiment of the present invention, in order to accurately invert the vertical profile information of atmospheric stratospheric CLONO2, as shown in FIG. Figure 1-Figure 4 As shown in the figure, the inversion algorithm of the atmospheric stratospheric CLONO2 vertical profile based on ground-based remote sensing is described in detail below for each step.

[0030] Step 1: Determine the spectral inversion fitting window

[0031] 1) Determine the gas spectral line parameters

[0032] The gas spectral line parameters of this algorithm are from the high-resolution molecular absorption spectral database HITRAN2012. The ground-based measured spectrum of atmospheric CLONO2 at 780.22 cm -1 The Q branch of the v4 band at is more suitable for spectral inversion because the absorption line characteristics of the target gas in this band are strong and are less interfered by other gas components.

[0033] 2) Determine the spectral window by using the wide and narrow double window two-step fitting method

[0034] Due to the uncertainty of atmospheric pressure, temperature and initial concentration distribution, it is necessary to minimize the interference of the absorption of interfering gases such as water vapor (H2O), ozone (O3), carbon dioxide (CO2) and nitric acid (HNO3) on the ClONO2 inversion. The wide and narrow double window two-step fitting method is used to determine the spectral window. First, a 779.30-780.60cm -1 The wide window band of 780.05-780.355cm was used to obtain the concentration scaling factors of gases H2O, O3, CO2, and HNO3. -1 The target gas is fitted within a narrow window band.

[0035] Table 1 CLONO2 spectral inversion window

[0036]

[0037] Step 2: Inversion model parameter setting

[0038] 1) Determine the initial state vector of the atmosphere

[0039] The pressure, temperature and water vapor prior profile parameters of the atmosphere are obtained based on the reanalysis data of the National Center for Environmental Prediction (NCEP) of the United States. Based on the simulation data of the World Atmospheric Climate Model (WACCM), the prior information of the vertical profile of atmospheric CLONO2 and its interfering gases is obtained to determine the initial state vector x of the atmosphere. a , to give the best estimate of the true atmospheric state.

[0040] 2) Inversion parameter setting

[0041] The parameters adopted by this algorithm to invert CLONO2 are specifically based on the Tikhonov-Phillips regularization algorithm to constrain the prior covariance matrix. Table 2 shows the parameters required for inversion and their sources.

[0042] Table 2 CLONO2 inversion model parameter settings

[0043]

[0044] Step 3: Simulate the solar transmittance spectrum

[0045] The initial state vector x a (As x i ) is substituted into the forward model, and the forward model simulates the calculated spectrum based on the gas prior profile, atmospheric temperature and pressure profile, solar spectrum parameters, and instrument functions.

[0046] The relationship between the measurement vector y and the atmospheric state vector x is described as follows:

[0047] y=F(x,b)+ε (1)

[0048] Among them, the measured quantity is represented by the measurement vector y, and all the measured quantities involved are equations of the state vector x. F is the forward model function, which describes the entire physical process of the measurement. x represents the state vector represented by n elements, which contains the quantity to be inverted; b contains all the parameters that affect the measurement, and ε is the measurement noise. The inversion problem is to find a state vector that is close to the true state vector x. The measurement vector y is given by the prior profile x a and the corresponding covariance matrix, S a Prior information describing the state of the atmosphere is calculated using a forward model.

[0049] Step 4: Spectral fitting

[0050] 1) Measurement spectrum screening

[0051] The observed spectra measured by the spectrometer need to be strictly quality controlled to remove spectra affected by clouds during acquisition.

[0052] 2) Iterative inversion

[0053] Substitute the simulated spectrum and the screened observed spectrum into the iterative algorithm, and determine whether the iteration ends by judging the value of the cost function. If it is less than the threshold, the iteration converges. If not, update the state vector x i+1 , continue nonlinear iteration, then the last x i is the desired solution. Generally, when the number of iterations is less than 10, the inverted vertical profile is considered stable.

[0054] For spectra measured using ground-based FTIR techniques, the forward model is nonlinear and equation (1) is solved using Gauss-Newton iteration:

[0055]

[0056]

[0057] Among them, K i is the weight function matrix of the i-th iteration

[0058]

[0059] Among them, x a is the prior profile, S z is the measurement noise covariance matrix, is the inversion profile, A is the average kernel matrix, I is the identity matrix, G y is the gain matrix, K b is the sensitivity matrix of b, b r are the estimated model parameters, y r is the simulated measurement state vector after inversion. The judgment basis of inversion is to judge whether the cost function is less than the set threshold. The cost function is expressed as follows:

[0060]

[0061] The right side of the equation represents the measured value consisting of m elements and the inversion state vector consisting of n elements; σ ε,m and σ a,n They represent measurement error and prior error respectively. The inversion problem is the optimization problem of the cost function, and the algorithm to find the best state is the optimal estimation method.

[0062] Step 5: Separation of Stratospheric Vertical Profiles

[0063] The atmospheric parameters of each layer of the target gas are separated from the atmospheric CLONO2 vertical profile at an altitude of 20-40 km to obtain the atmospheric stratospheric profile. Further integration of the stratospheric profile can be used to obtain the stratospheric atmospheric partial column content.

[0064] The above specific embodiments are only several optional embodiments of the present invention. Based on the technical solutions of the present invention and the relevant inspirations of the above embodiments, those skilled in the art can make various alternative improvements and combinations to the above specific embodiments.

Claims

1. An inversion algorithm for the vertical profile of stratospheric nitrate chloride based on ground-based remote sensing, characterized in that: The following steps are involved: Determine the gas spectrum inversion fitting window, obtain the ClONO2 gas spectrum line parameters and absorption cross section based on the high-resolution molecular parameter database, and select the window to invert atmospheric ClONO2 according to the absorption line characteristics of the target gas and interfering gas spectra; The inversion model parameters are set, and the atmospheric pressure, temperature and water vapor prior profile parameters are obtained from the atmospheric reanalysis data to determine the atmospheric initial state vector x a , using the global atmospheric model to simulate and generate the prior profiles of target gases and interfering gases; Simulate the solar transmittance spectrum and set the initial state vector x a Substitute it into the forward model, and calculate the transmittance spectrum of sunlight after passing through the entire atmosphere by combining atmospheric radiation transmission with instrument linear parameters, solar spectrum parameters, gas prior profiles, atmospheric temperature, pressure and humidity profiles; Carry out spectral fitting, substitute the simulated spectrum and the measured spectrum after quality control into the iterative algorithm, and determine whether the iteration ends by judging the cost function value. If it is less than the threshold, the iteration converges to obtain the atmospheric vertical profile parameters representing the real atmospheric state, otherwise update the state vector and continue the iteration; Separate the stratospheric vertical profile, separate the stratospheric ClONO2 vertical profile in a specific height range from the atmospheric parameters of each layer of the target gas, and integrate it to obtain the stratospheric atmospheric partial column content.

2. The vertical profile inversion algorithm of atmospheric stratospheric nitric acid chloride based on ground-based remote sensing according to claim 1, characterized in that: The high-resolution molecular parameter database is HITRAN2012.

3. The vertical profile inversion algorithm of atmospheric stratospheric nitric acid chloride based on ground-based remote sensing according to claim 1 is characterized in that: In the vertical profile of the detached stratosphere, the specific altitude range is 20-40 km.

4. The inversion algorithm for the vertical profile of stratospheric nitric acid chloride based on ground-based remote sensing according to claim 1 is characterized in that: The atmospheric reanalysis data are reanalysis data from the National Center for Environmental Prediction of the United States, and the global atmospheric model is a global atmospheric climate model.

5. The vertical profile inversion algorithm of atmospheric stratospheric nitric acid chloride based on ground-based remote sensing according to claim 1 is characterized in that: In the inversion model parameter setting, the Tikhonov-Phillips regularization algorithm is used to constrain the prior covariance matrix.

6. The vertical profile inversion algorithm of atmospheric stratospheric nitric acid chloride based on ground-based remote sensing according to claim 1 is characterized in that: In the spectrum fitting step, the cost function is expressed as follows: The right side of the equation represents the measured value consisting of m elements and the inversion state vector consisting of n elements; F m and x n represent measurement error and a priori error respectively.

7. The vertical profile inversion algorithm of atmospheric stratospheric nitric acid chloride based on ground-based remote sensing according to claim 1 is characterized in that: In the spectrum fitting step, the iterative algorithm adopts the nonlinear least squares fitting optimal estimation method.

8. The vertical profile inversion algorithm of atmospheric stratospheric nitric acid chloride based on ground-based remote sensing according to claim 1 is characterized in that: In the simulated solar transmittance spectrum, the initial state vector of the atmosphere is substituted into the forward model, and the forward model simulates and obtains the calculated spectrum based on the gas prior profile, the atmospheric temperature and pressure profile, the solar spectrum parameters, and the instrument function.

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