Aerosol optical thickness collaborative inversion method, device and equipment and storage medium

Abstract

The embodiment of the invention provides an aerosol optical thickness collaborative inversion method, device and equipment and a storage medium. The method is applied to the technical field of atmospheric environment, and comprises the following steps: inputting an aerosol optical thickness initial value as an input value into an atmospheric radiation transmission model to obtain a solar spectral irradiance calculated value; performing regression analysis on the solar spectral irradiance calculated value and the solar spectral irradiance observed value to obtain a regression analysis result; and adjusting an input value of an atmospheric radiation transmission model according to a regression analysis result until the fitting degree of the solar spectral irradiance calculated value and the solar spectral irradiance observed value is less than or equal to a target threshold value, and taking the adjusted input value of the atmospheric radiation transmission model as an aerosol optical thickness inversion value. In this way, the reliability and accuracy of the aerosol optical thickness inversion result can be improved.

Description

Technical Field

[0001] The present disclosure relates to the field of atmospheric environment technology, and in particular to a method, device, equipment and storage medium for collaborative inversion of aerosol optical thickness. Background Art

[0002] As one of the important pollution components, atmospheric aerosols have a significant impact on the environment, climate and human health. Atmospheric optical thickness is a key parameter that describes the absorption and scattering ability of aerosols and gases in the atmosphere to solar radiation. It is of great significance to environmental monitoring, climate change research, atmospheric pollution control and other fields. At present, the observation of atmospheric optical thickness and its components (such as aerosol optical thickness) mainly relies on sun photometers or filter radiometers in the form of multi-wavelength filters. These instruments invert atmospheric optical parameters by measuring direct solar radiation at specific wavelengths.

[0003] The main atmospheric optical thickness parameter measurement methods currently adopted include:

[0004] The Langley method is a fitting method based on the linear relationship between the original response signal of the instrument and the optical atmospheric mass. The Langley method uses the physical characteristics of the atmosphere itself, obtains the base signal at high altitudes as a zero calibration, and then transfers it to the observation site for measurement. Although the Langley method is the mainstream method for determining aerosol optical depth in meteorological observations and is recommended by the World Meteorological Organization (WMO), its disadvantage is the lack of a reliable metrological traceability chain and uncertainty in the metrological compatibility of the measurement data.

[0005] The inversion method of direct solar spectral irradiance and Lambert-Beer's law is based on the ideal solar spectral irradiance at the top of the atmosphere and the direct solar spectral irradiance data observed on the surface, and the atmospheric optical thickness is solved by the Beer's law equation. Although the physical meaning is clear, the uncertainty of this method is still significant due to factors such as the measurement error of spectral irradiance, the error of the preset value of solar spectral irradiance at the top of the atmosphere, and the change of the deflection angle of solar rays caused by the change of medium density in the atmosphere.

[0006] There is no effective solution to the technical problems of low reliability and accuracy of current aerosol optical thickness measurement methods. Summary of the invention

[0007] The present disclosure provides a method, device, equipment and storage medium for collaborative inversion of aerosol optical thickness.

[0008] According to a first aspect of the present disclosure, a collaborative inversion method for aerosol optical depth is provided. The method comprises: taking an initial value of aerosol optical depth as an input value, inputting it into an atmospheric radiation transfer model, and obtaining a calculated value of solar spectral irradiance;

[0009] Perform regression analysis on the calculated value of solar spectrum irradiance and the observed value of solar spectrum irradiance to obtain the regression analysis result;

[0010] According to the regression analysis results, the input value of the atmospheric radiation transfer model is adjusted until the degree of fit between the calculated value of the solar spectral irradiance and the observed value of the solar spectral irradiance is less than or equal to the target threshold, and the adjusted input value of the atmospheric radiation transfer model is used as the aerosol optical thickness inversion value.

[0011] According to the above aspects and any possible implementation, an implementation is further provided, in which a regression analysis is performed on the calculated solar spectrum irradiance value and the observed solar spectrum irradiance value to obtain a regression analysis result, including:

[0012] Based on the calculated value of solar spectral irradiance and the observed value of solar spectral irradiance, the sum of squares of the fitting residuals between the two and the mean of the fitting band spectral differences are determined.

[0013] According to the above aspects and any possible implementation, an implementation is further provided, wherein the input value of the atmospheric radiation transfer model is adjusted according to the regression analysis result until the degree of fit between the calculated solar spectral irradiance value and the observed solar spectral irradiance value is less than or equal to the target threshold, and the aerosol optical thickness inversion value is obtained, including:

[0014] With the goal of making the sum of squares of fitting residuals less than the target residual threshold and the mean of the spectral difference of the fitting bands less than or equal to the target spectral difference threshold, a dual-objective function is established, and the input value of the atmospheric radiation transfer model is adjusted using a dual-objective optimization algorithm.

[0015] According to the above aspects and any possible implementation manner, an implementation manner is further provided, wherein the method further includes:

[0016] The Langley method is used to calculate the aerosol optical thickness and obtain the calculated value of aerosol optical thickness;

[0017] The data quality of the aerosol optical depth inversion value is marked according to the deviation between the aerosol optical depth inversion value and the aerosol optical depth measured value.

[0018] According to the above aspects and any possible implementation, an implementation is further provided, wherein the Langley method is used to calculate the aerosol optical thickness to obtain a measured value of the aerosol optical thickness, including:

[0019] The solar spectroradiometer system is used to measure the baseline dark spectrum, dark noise spectrum and original signal spectrum;

[0020] Determine a net signal spectrum according to the baseline dark spectrum, the dark noise spectrum and the original signal spectrum;

[0021] Based on the optical atmospheric mass and the net signal spectrum, the total optical thickness of the atmosphere is inverted to obtain the inversion value of the total optical thickness of the atmosphere;

[0022] The calculated value of aerosol optical thickness is determined based on the inverted values ​​of Rayleigh optical thickness and total atmospheric optical thickness.

[0023] According to the above aspects and any possible implementation, an implementation is further provided, wherein the initial value of aerosol optical thickness is used as an input value and input into an atmospheric radiation transfer model to obtain a calculated value of solar spectrum irradiance, including:

[0024] Parameter configuration of the SMARTS atmospheric radiation transfer model, where the model parameters of the SMARTS atmospheric radiation transfer model include solar-terrestrial geometric parameters, solar spectral irradiance at the top of the atmosphere, and optical atmospheric quality;

[0025] The initial value of aerosol optical depth is used as the input value and input into the configured SMARTS atmospheric radiation transfer model to obtain the calculated value of solar spectral irradiance.

[0026] According to the aspects and any possible implementations described above, there is further provided an implementation, in which the solar spectral irradiance at the top of the atmosphere is the solar spectral irradiance at the top of the atmosphere corrected according to the distance between the sun and the earth.

[0027] According to a second aspect of the present disclosure, an aerosol optical thickness collaborative inversion device is provided.

[0028] The device includes:

[0029] An input module is used to input the initial value of aerosol optical thickness as an input value into the atmospheric radiation transfer model to obtain the calculated value of solar spectrum irradiance;

[0030] An analysis module is used to perform regression analysis on the calculated solar spectrum irradiance value and the observed solar spectrum irradiance value to obtain a regression analysis result;

[0031] The adjustment module is used to adjust the input value of the atmospheric radiation transfer model according to the regression analysis results until the degree of fit between the calculated value of the solar spectral irradiance and the observed value of the solar spectral irradiance is less than or equal to the target threshold, and the adjusted input value of the atmospheric radiation transfer model is used as the aerosol optical thickness inversion value.

[0032] According to a third aspect of the present disclosure, an electronic device is provided, which includes a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the program, the method described above is implemented.

[0033] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the method according to the first aspect of the present disclosure is implemented.

[0034] The present disclosure improves the reliability and accuracy of aerosol optical thickness inversion results by performing collaborative inversion of aerosol optical thickness based on solar direct spectral irradiance and atmospheric radiation transfer model.

[0035] It should be understood that the contents described in the summary of the invention are not intended to limit the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, among which:

[0037] Figure 1 A flow chart of a collaborative inversion method of aerosol optical thickness according to an embodiment of the present disclosure is shown;

[0038] Figure 2 A block diagram of an aerosol optical depth collaborative inversion method capable of implementing an embodiment of the present disclosure is shown;

[0039] Figure 3 A block diagram of an aerosol optical thickness collaborative inversion device according to an embodiment of the present disclosure is shown;

[0040] Figure 4 A block diagram of an exemplary electronic device capable of implementing embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0041] 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.

[0042] In addition, the term "and / or" in this article is only a description of the association relationship between 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 this article generally indicates that the associated objects before and after are in an "or" relationship.

[0043] Optical thickness, atmospheric (total) optical thickness and component optical thickness (aerosol optical thickness, Rayleigh optical thickness, water vapor optical thickness, ozone optical thickness, mixed gas optical thickness)

[0044] The transmission of light in a medium conforms to the attenuation law of monochromatic radiation - the Bouguer-Lambert-Beer law, usually referred to as the Lambert-Beer law or Beer's law.

[0045]

[0046] in:

[0047] λ——wavelength of light,

[0048] l——the distance that light travels in the medium along the propagation direction starting from position 0,

[0049] E λ,0 —— irradiance with wavelength λ at position 0,

[0050] E λ,l ——irradiance with wavelength λ at position l,

[0051] k λ ——the extinction coefficient of the medium for light with wavelength λ,

[0052] ρ——density of the medium

[0053] Based on the law described by the mathematical model of the Bouguer-Lambert-Beer law, the expression term without a negative sign on the e index is defined as δ, as shown in the following formula:

[0054]

[0055] δ λ It is called the optical depth (OD, optical depth, dimensionless) of monochromatic light in the medium.

[0056] It means the total attenuation of light in a medium due to absorption and scattering per unit cross section along the transmission path of the light in the medium.

[0057] Therefore, the Bouguer-Lambert-Beer law can be expressed as follows:

[0058]

[0059] Therefore, optical thickness is a parameter that represents the exponential term when light is transmitted in a medium and exhibits an exponential decay law.

[0060] In the observation of solar spectral radiation, the sun is used as the radiation source, and the transmission of sunlight emitted by it uses the atmosphere as the transmission medium of light, passing through the thickness of the entire atmosphere to reach the observation instrument on the ground. At this time, the optical thickness of sunlight when it penetrates the atmosphere is called the atmospheric (total) optical thickness.

[0061] The atmospheric optical thickness can be decomposed according to the effects of its components, such as aerosol optical thickness, (single / mixed) gas optical thickness, Rayleigh scattering optical thickness, etc., so as to analyze the influence of single factors.

[0062] Since the movement of the sun forms the phenomenon of day and night alternation in a 24-hour cycle, different geometric relationships are formed between the sunlight incident on the ground and the ground, which are usually expressed by the incident zenith angle and azimuth angle.

[0063] Different incident zenith angles correspond to different distances that light travels obliquely in the atmosphere, so the atmospheric optical thickness is usually written as a function of the incident zenith angle θ.

[0064] Usually the atmospheric optical thickness can be decomposed and expressed according to the attenuation of different components.

[0065] δ λ (θ) = δ λ,R (θ)+δ λ,A (θ)+δ λ,O (θ)+δ λ,V (θ)+δ λ,G (θ) (4)

[0066] in,

[0067] δ λ (θ)——atmospheric (total) optical thickness,

[0068] δ λ,R (θ)——Rayleigh optical thickness caused by gas scattering,

[0069] δ λ,A (θ)——aerosol optical depth caused by aerosol scattering,

[0070] δ λ,O (θ)——ozone optical depth caused by ozone absorption,

[0071] δ λ,V (θ)——water vapor optical depth caused by water vapor absorption,

[0072] δ λ,G (θ)——Optical thickness of mixed gas caused by trace mixed gas absorption.

[0073] For wavelengths recommended by WMO without the effects of gas absorption, the aerosol optical depth can be expressed as the total atmospheric optical depth minus the Rayleigh optical depth.

[0074] δ λ,A (θ) = δ λ (θ)-δ λ,R (θ) (5)

[0075] The Lambert-Beer law is a core law equation describing the transmission of radiation in the atmosphere. It was proposed by Bouguer in 1725, Lambert in 1760, and Beer in 1852 respectively. It describes the attenuation law of light transmission in a medium that is related to the absorption coefficient of the medium, the optical path length of the medium, and the concentration of the medium, and was eventually merged into a unified equation.

[0076] In 1904, Rayleigh proposed the theory of light scattering in media. In the 1920s, scientists began to combine Rayleigh scattering theory with Lambert-Beer law to study atmospheric radiation transfer. In the 1940s, scientists began to develop numerical solutions. In 1943, the first generation of atmospheric radiation transfer model (Atmospheric Radiative Transfer Model, ARTM) was proposed.

[0077] The atmospheric radiation transfer model is a more complex and refined equation system with the Lambert-Beer law equation and the Rayleigh scattering equation as the core, as well as a variety of basic atmospheric parameters, and also includes the numerical solution algorithm of the equation.

[0078] Atmospheric radiation transfer models usually consist of the following parts:

[0079] ① Atmospheric parameters: including atmospheric composition (expansion line), temperature, pressure, density, etc.

[0080] ② Radiation parameters: including the spectral irradiance of the sun at the top of the atmosphere, the wavelength of radiation, the geometric relationship between the sun and the earth (such as the angle of incidence and the angle of exit), etc.

[0081] ③Radiation transfer equation: describes the transmission process of radiation in the atmosphere.

[0082] ④Numerical solution method: algorithm used to solve the radiation transfer equation.

[0083] The current atmospheric radiation transfer models include rigorous models such as LOWTRAN and MODTRAN, as well as other atmospheric radiation transfer models with varying degrees of simplification. For example, atmospheric radiation transfer models of moderate complexity such as SMARTS and 6S have been widely used and verified to have high accuracy.

[0084] Normally, the atmospheric optical thickness parameter is used as input in the atmospheric radiation transfer model, and the radiation under different conditions is used as output. This process of inputting atmospheric parameters to solve the spectral radiation is the forward calculation process of the atmospheric radiation transfer model. When ground observation instruments and equipment provide the direct solar spectral irradiance as the observed radiation data, the atmospheric optical thickness parameter and other parameters can also be determined in reverse, which is called the reverse calculation (abbreviated as inversion) method.

[0085] In the present disclosure, by performing a collaborative inversion of aerosol optical depth based on solar direct spectral irradiance and an atmospheric radiation transfer model, the reliability and accuracy of the aerosol optical depth inversion results are improved.

[0086] Figure 1 A flow chart of a collaborative inversion method 100 of aerosol optical depth according to an embodiment of the present disclosure is shown. The method 100 comprises the following steps:

[0087] Step S110, taking the initial value of aerosol optical thickness as an input value, inputting it into the atmospheric radiation transfer model, and obtaining the calculated value of solar spectrum irradiance;

[0088] Step S120, performing regression analysis on the calculated solar spectrum irradiance value and the observed solar spectrum irradiance value to obtain a regression analysis result;

[0089] Step S130, adjusting the input value of the atmospheric radiation transfer model according to the regression analysis result until the degree of fit between the calculated solar spectral irradiance value and the observed solar spectral irradiance value is less than or equal to the target threshold, and using the adjusted input value of the atmospheric radiation transfer model as the aerosol optical thickness inversion value.

[0090] In some embodiments, a regression analysis is performed on the calculated solar spectrum irradiance value and the observed solar spectrum irradiance value to obtain a regression analysis result, including:

[0091] Based on the calculated value of solar spectral irradiance and the observed value of solar spectral irradiance, the sum of squares of the fitting residuals between the two and the mean of the fitting band spectral differences are determined.

[0092] The residual sum of squares is a concept in regression analysis. It represents the sum of squares of the differences between the model calculated values ​​and the actual observed values, reflecting the degree of fit between the model predicted data and the actual observed data.

[0093] For example, the calculated value of the model is recorded as The corresponding actual observation value is recorded as y i , the amount of data is n, then the sum of squares of the fitting residuals is E rs It can be expressed as:

[0094]

[0095] Among them, E rs The smaller it is, the smaller the difference between the model's predicted value and the actual observed value is, and the better the model fit is.

[0096] The mean of the fitted band spectral differences refers to the average of the absolute values ​​of the differences between the model calculated values ​​and the actual observed values.

[0097] For example, if we have a set of observations y i and the corresponding model calculated value Where i represents the index of the data point, then the mean of the fitted band spectral difference is It can be calculated according to the following formula:

[0098]

[0099] The mean of the fitted band spectral differences provides a measure of the model's predicted fit residuals averaged over all data points.

[0100] According to an embodiment of the present disclosure, the degree of fit between the calculated value of solar spectral irradiance and the observed value of solar spectral irradiance is determined by fitting the sum of squares of residuals and the mean of the spectral differences of the fitting bands, so as to find the optimal input value so that the difference between the calculated value and the observed value of the model is minimized.

[0101] In some embodiments, the input value of the atmospheric radiation transfer model is adjusted according to the regression analysis result until the degree of fit between the calculated solar spectral irradiance value and the observed solar spectral irradiance value is less than or equal to a target threshold, and the aerosol optical thickness inversion value is obtained, including:

[0102] With the goal of making the sum of squares of fitting residuals less than the target residual threshold and the mean of the spectral difference of the fitting bands less than or equal to the target spectral difference threshold, a dual-objective function is established, and the input value of the atmospheric radiation transfer model is adjusted using a dual-objective optimization algorithm.

[0103] Optionally, the bi-objective optimization algorithm may be a genetic algorithm (GA), a multi-objective particle swarm optimization (MOPSO), a non-dominated sorting genetic algorithm (NSGA-II), or the like.

[0104] The atmospheric radiation transfer model is combined with the dual-objective optimization algorithm. The aerosol optical depth is taken as the optimization variable. The optimization algorithm is run to adjust the input value of the aerosol optical depth until a solution is found that satisfies both the sum of squares of the fitting residuals less than the target residual threshold and the mean of the spectral differences of the fitting bands less than or equal to the target spectral difference threshold.

[0105] According to the embodiments of the present disclosure, the degree of fit between the calculated solar spectral irradiance value obtained by calculating the atmospheric radiation transfer model and the actual solar spectral irradiance observation value is improved through dual-objective optimization, thereby obtaining a more accurate aerosol optical thickness inversion value.

[0106] In some embodiments, the method further comprises:

[0107] The Langley method is used to calculate the aerosol optical thickness and obtain the calculated value of aerosol optical thickness;

[0108] The data quality of the aerosol optical depth inversion value is marked according to the deviation between the aerosol optical depth inversion value and the aerosol optical depth measured value.

[0109] For example, the Langley method is used to calculate the aerosol optical depth δ LY,λ500,A (θ = 0), where λ500 represents the measurement at a wavelength of 500 nm, A represents the type or source of the aerosol, and θ = 0 represents the observation when the sun is at the zenith;

[0110] Calculate the measured value δ LY,λ500,A The deviation dδ between (θ = 0) and the inverted value of aerosol optical thickness LY,λ500,A (θ=0);

[0111] Marking quality level:

[0112] High quality (H): the deviation is less than the first threshold dδ th1 , indicating that the data is very reliable.

[0113] Medium quality (M): the deviation is between two thresholds, i.e. dδ th2 ≥dδ LY,λ500,A (θ=0)≥dδ th1 , indicating that the data has a certain degree of reliability, but may need further verification.

[0114] Low quality (L): the deviation is greater than the second threshold dδ th2 , indicating that the data may be unreliable and needs to be used with caution;

[0115] Manually check and revise the data to correct possible measurement or calculation errors; use charts and other visualization tools to check the consistency and outliers of the data; readjust the algorithm parameters based on the results of quality control to improve the accuracy and reliability of the data; analyze the impact of deviations on the final results and determine the applicability and limitations of the data; generate detailed reports to record the process, methods and results of data processing and revision, as well as the final assessment of data quality.

[0116] According to the embodiments of the present disclosure, quality control is performed through the measured values ​​of the Langley method, which can ensure that the data of aerosol optical thickness is not only accurate in quantity but also meets the requirements of scientific research and environmental monitoring in terms of quality. This strict quality control and data processing process is crucial to improving the credibility and practicality of the data.

[0117] In some embodiments, the aerosol optical thickness is calculated using the Langley method to obtain a measured value of the aerosol optical thickness, including:

[0118] The solar spectroradiometer system is used to measure the baseline dark spectrum, dark noise spectrum and original signal spectrum;

[0119] Determine a net signal spectrum according to the baseline dark spectrum, the dark noise spectrum and the original signal spectrum;

[0120] Based on the optical atmospheric mass and the net signal spectrum, the total optical thickness of the atmosphere is inverted to obtain the inversion value of the total optical thickness of the atmosphere;

[0121] The calculated value of aerosol optical thickness is determined based on the inverted values ​​of Rayleigh optical thickness and total atmospheric optical thickness.

[0122] Baseline Dark Spectrum: Measuring the dark current spectrum of a solar spectroradiometer system in the absence of sunlight helps identify and correct for noise in the system itself.

[0123] Dark Noise Spectrum: Measures the dark noise of a system, which typically includes electronic noise and noise from other internal sources.

[0124] Original signal spectrum: Measure the direct radiation spectrum of sunlight at different times and conditions.

[0125] The raw signal spectrum is corrected using the baseline dark spectrum and dark noise spectrum to eliminate the effects of system noise and dark current; the dark spectrum and noise spectrum are subtracted from the raw signal spectrum to obtain the net signal spectrum. This is the actual measurement of sunlight after passing through the atmosphere.

[0126] Rayleigh optical depth is the optical depth caused by molecular scattering in the atmosphere and can be calculated using known atmospheric models and meteorological data. For example, the Rayleigh optical depth can be calculated using the empirical equation proposed by Hansen & Travis (1974). The aerosol optical depth can be obtained by subtracting the Rayleigh optical depth from the total atmospheric optical depth.

[0127] According to the embodiments of the present disclosure, the aerosol optical thickness can be accurately measured through the above steps.

[0128] In some embodiments, the initial value of aerosol optical thickness is used as an input value and input into an atmospheric radiation transfer model to obtain a calculated value of solar spectrum irradiance, including:

[0129] Parameter configuration of the SMARTS atmospheric radiation transfer model, where the model parameters of the SMARTS atmospheric radiation transfer model include solar-terrestrial geometric parameters, solar spectral irradiance at the top of the atmosphere, and optical atmospheric quality;

[0130] The initial value of aerosol optical depth is used as the input value and input into the configured SMARTS atmospheric radiation transfer model to obtain the calculated value of solar spectral irradiance.

[0131] The solar-terrestrial geometry parameters describe the position of the sun in the sky and are essential for simulating the propagation of solar radiation in the atmosphere, including:

[0132] Apparent zenith angle θ: The angle between the sun's rays and the vertical line, which can be calculated using astronomical algorithms.

[0133] Azimuth α: The position of the Sun in the sky, usually defined as the angle measured clockwise from north.

[0134] Earth-Sun distance ds: The average distance between the Earth and the Sun, which can be calculated based on the elliptical shape of the Earth's orbit.

[0135] Time information: includes year, month, day, hour, minute and time zone, which is used to determine the position of the sun and the duration of sunshine.

[0136] Geographic information: including the longitude, latitude and altitude of the observation site, which affects the incident angle and atmospheric path of solar radiation.

[0137] The solar spectral irradiance at the top of the atmosphere is the intensity of solar radiation at the top of the atmosphere and is the starting condition for simulating the propagation of solar radiation in the atmosphere.

[0138] Optical atmospheric mass is a parameter that describes the density of solar radiation passing through the atmospheric column and is very important for calculating the attenuation of solar radiation in the atmosphere. A suitable empirical equation for optical atmospheric mass can be selected to calculate the optical atmospheric mass, such as the empirical equation proposed by Kasten (1965) and Young (1989).

[0139] According to an embodiment of the present disclosure, the SMARTS atmospheric radiation transfer model can be effectively used to estimate the aerosol optical depth.

[0140] In some embodiments, the solar spectral irradiance at the top of the atmosphere is the solar spectral irradiance at the top of the atmosphere corrected according to the distance between the sun and the earth.

[0141] Based on the standard model of solar spectral radiation, the solar spectral irradiance E at the top of the atmosphere is obtained by considering the spectral radiation characteristics of the sun. aot (λ rs ) Due to the elliptical shape of the Earth's orbit, the solar spectrum irradiance at the top of the atmosphere needs to be corrected according to the distance between the Sun and the Earth, ds, and the calculated value is E aot-dm (λ rs ).

[0142] According to the embodiments of the present disclosure, the solar spectrum irradiance at the top of the atmosphere is corrected according to the sun-earth distance ds, thereby improving the parameter accuracy of the SMARTS atmospheric radiation transfer model.

[0143] like Figure 2 As shown, the method 100 of the embodiment of the present disclosure is described below with a specific implementation case:

[0144] The aerosol optical depth collaborative inversion method of the embodiment of the present disclosure is based on the hyperspectral solar direct irradiance and the atmospheric radiation transfer model to perform aerosol optical depth collaborative inversion. The complete process is as follows:

[0145] The step S110: using the initial value of aerosol optical thickness as an input value and inputting it into the atmospheric radiation transmission model to obtain the calculated value of solar spectrum irradiance; specifically includes:

[0146] Input initial value: Input the initial value of aerosol optical thickness δ λ500,A (θ=0).

[0147] Calculation model solar spectral irradiance: Use the atmospheric radiation transfer model to calculate the ground direct solar spectral irradiance E dni-rtm (λ rs ).

[0148] Observed solar spectral irradiance: Obtain direct solar spectral irradiance E from observed data dni-obs (λ rs ).

[0149] The step S120: performing regression analysis on the calculated solar spectrum irradiance value and the observed solar spectrum irradiance value to obtain a regression analysis result; specifically includes:

[0150] Calculate the sum of squares of the residuals of the fitted band: Calculate the sum of squares of the residuals of the fitted band between the model calculated values ​​and the observed values ​​E rs .

[0151] The step S130: adjusting the input value of the atmospheric radiation transfer model according to the regression analysis result until the fitting degree between the calculated value of the solar spectrum irradiance and the observed value of the solar spectrum irradiance is less than or equal to the target threshold, and using the adjusted input value of the atmospheric radiation transfer model as the aerosol optical thickness inversion value; specifically includes:

[0152] Check if the residual is less than the target threshold: If E rs Less than the target threshold E rth , then continue, otherwise adjust the input aerosol optical density and recalculate.

[0153] Calculate and check the mean of the fitted band spectral difference: Calculate the fitted band spectral difference D s The mean of (npx). If Ds The mean of (npx) is greater than the target threshold D sth , then continue to adjust the input, otherwise complete the calculation.

[0154] Adjust input AOD: Adjust the AOD input based on the residual and spectral difference results. The adjustment can be a linear or exponential adjustment.

[0155] Repeat calculation: Repeat the above steps until all conditions are met.

[0156] Among them, the direct solar spectral irradiance E on the ground is calculated using the atmospheric radiation transfer model. dni-rtm (λ rs ), the relevant physical and geographical parameters are calculated as follows:

[0157] 1. Sun-Earth geometric parameters: apparent zenith angle, azimuth, distance between the sun and the earth, time information (year, month, day, hour, minute, time zone), geographic information (longitude, latitude, altitude).

[0158] 2. Solar spectral irradiance at the top of the atmosphere: Calculate the solar spectral irradiance E at the top of the atmosphere aot (λ rs );The solar spectral irradiance E at the top of the atmosphere corrected according to the distance between the sun and the earth aot-dm (λ rs ).

[0159] 3. Optical atmospheric mass: Select the empirical equation for calculating the optical atmospheric mass AM(θ).

[0160] Among them, the direct solar spectral irradiance E is obtained from the observation data dni-obs (λ rs ), including calibration and correction, as follows:

[0161] 1. Instrument measurement parameters: including integration time t i and sensor temperature T s .

[0162] 2. Spectral radiation calibration: spectral responsivity R (npx, unit) and dimension unit unit; nonlinear correction coefficient c (t i ); wavelength calibration coefficients w(npx,npw) and wavelength resampling configuration.

[0163] 3. Signal processing: including baseline dark spectrum (sp-darkbase), dark noise spectrum (sp-darknoise), raw signal spectrum (sp-signalraw), net signal spectrum (sp-signalnet) and signal-to-noise ratio spectrum (sp-SNR).

[0164] The aerosol optical depth input is adjusted according to the results of the residual and spectral difference. The adjustment can be a linear adjustment or an exponential adjustment, including:

[0165] Inversion and quality control of aerosol optical depth:

[0166] 1. Aerosol optical depth inversion based on Langley method: Use Langley method to calculate aerosol optical depth δ LY,λ500,A (θ=0).

[0167] 2. Quality control mark: According to the measured value δ LY,λ500,A Deviation dδ of (θ=0) LY,λ500,A (θ=0) to mark the mass:

[0168] High quality (H): dδ LY,λ500,A (θ=0) <dδ th1 .

[0169] Medium mass (M): dδ th2 >dδ LY,λ500,A (θ=0)>dδ th1 .

[0170] Low quality (L): dδ LY,λ500,A (θ=0)>dδ th2 .

[0171] 3. Data processing and revision:

[0172] Manual post-processing of data, visual verification of algorithmic processes, re-adjustment and revision of data parameters, and analysis of the impact of deviations; generating data revision reports.

[0173] The core sub-algorithms cited are as follows:

[0174] 1. Optical atmosphere mass algorithm: based on the correction of the distance between the sun and the earth and the calculation of optical thickness; the optical atmosphere mass is calculated using empirical equations such as those proposed by Kasten (1965) and Young (1989).

[0175] 2. Atmospheric model selection: SMARTS atmospheric radiation transfer model.

[0176] 3. Calculation of Rayleigh Optical Depth: The Rayleigh optical depth was calculated using the empirical equation proposed by Hansen & Travis (1974).

[0177] 4. Solar Position Algorithm: Solar Position Algorithm (SPA) of the National Renewable Energy Laboratory (NREL).

[0178] 5. Sun-Earth distance algorithm: The Sun-Earth distance algorithm in Appendix D of Chapter 7 of the World Meteorological Organization (WMO) Guide to Instruments and Methods of Observation (CIMO).

[0179] Through these steps and calculation methods, high-precision aerosol optical thickness inversion can be achieved, and the reliability of the data can be guaranteed through quality control marking.

[0180] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present disclosure is not limited by the order of the actions described, because according to the present disclosure, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present disclosure.

[0181] The above is an introduction to the method embodiment. The following is a further explanation of the scheme disclosed in the present invention through an apparatus embodiment.

[0182] Figure 3 The block diagram of the aerosol optical thickness collaborative inversion device according to an embodiment of the present disclosure is shown. The device 300 includes:

[0183] An input module 310 is used to input the initial value of aerosol optical thickness as an input value into an atmospheric radiation transfer model to obtain a calculated value of solar spectrum irradiance;

[0184] The analysis module 320 is used to perform regression analysis on the calculated solar spectrum irradiance value and the observed solar spectrum irradiance value to obtain a regression analysis result;

[0185] The adjustment module 330 is used to adjust the input value of the atmospheric radiation transfer model according to the regression analysis results until the degree of fit between the calculated solar spectral irradiance value and the observed solar spectral irradiance value is less than or equal to the target threshold, and the adjusted input value of the atmospheric radiation transfer model is used as the aerosol optical thickness inversion value.

[0186] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described module can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0187] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0188] Figure 4A block diagram of an exemplary electronic device 400 capable of implementing an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0189] The electronic device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in the ROM 402 or a computer program loaded from the storage unit 408 into the RAM 403. In the RAM 403, various programs and data required for the operation of the electronic device 400 can also be stored. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An I / O interface 405 is also connected to the bus 404.

[0190] Multiple components in the electronic device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a disk, an optical disk, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the electronic device 400 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0191] The computing unit 401 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 401 performs the various methods and processes described above, such as method 100. For example, in some embodiments, the method 100 may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by the computing unit 401, one or more steps of the method 100 described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to perform the method 100 in any other appropriate manner (e.g., by means of firmware).

[0192] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0193] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0194] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0195] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0196] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0197] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0198] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0199] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A collaborative inversion method for aerosol optical thickness, characterized in that: include: The initial value of aerosol optical thickness is used as input into the atmospheric radiation transfer model to obtain the calculated value of solar spectrum irradiance; Perform regression analysis on the calculated value of solar spectrum irradiance and the observed value of solar spectrum irradiance to obtain the regression analysis result; The input value of the atmospheric radiation transfer model is adjusted according to the regression analysis result until the degree of fit between the calculated value of the solar spectral irradiance and the observed value of the solar spectral irradiance is less than or equal to the target threshold, and the adjusted input value of the atmospheric radiation transfer model is used as the aerosol optical thickness inversion value.

2. The method according to claim 1, characterized in that The regression analysis of the calculated solar spectrum irradiance value and the observed solar spectrum irradiance value is performed to obtain the regression analysis result, including: Based on the calculated value of solar spectral irradiance and the observed value of solar spectral irradiance, the sum of squares of the fitting residuals between the two and the mean of the fitting band spectral differences are determined.

3. The method according to claim 2, characterized in that The input value of the atmospheric radiation transfer model is adjusted according to the regression analysis result until the fitting degree between the calculated solar spectral irradiance value and the observed solar spectral irradiance value is less than or equal to the target threshold value, and the aerosol optical thickness inversion value is obtained, including: With the goal that the sum of squares of fitting residuals is less than the target residual threshold and the mean of fitting band spectral differences is less than or equal to the target spectral difference threshold, a dual objective function is established, and the input value of the atmospheric radiation transfer model is adjusted using a dual objective optimization algorithm.

4. The method according to claim 1, characterized in that: The method further comprises: The Langley method is used to calculate the aerosol optical thickness and obtain the calculated value of aerosol optical thickness; According to the deviation between the aerosol optical thickness inversion value and the aerosol optical thickness measured value, the data quality of the aerosol optical thickness inversion value is marked.

5. The method according to claim 4, characterized in that The Langley method is used to calculate the aerosol optical thickness to obtain the aerosol optical thickness measurement value, including: The solar spectroradiometer system is used to measure the baseline dark spectrum, dark noise spectrum and original signal spectrum; Determining a net signal spectrum according to the baseline dark spectrum, the dark noise spectrum and the original signal spectrum; Inverting the total optical thickness of the atmosphere based on the optical atmospheric mass and the net signal spectrum to obtain an inversion value of the total optical thickness of the atmosphere; The aerosol optical thickness measurement value is determined based on the Rayleigh optical thickness and the inverted value of the total optical thickness of the atmosphere.

6. The method according to claim 1, characterized in that The initial value of aerosol optical thickness is used as an input value and input into the atmospheric radiation transmission model to obtain the calculated value of solar spectrum irradiance, including: Parameter configuration is performed on the SMARTS atmospheric radiation transfer model, wherein the model parameters of the SMARTS atmospheric radiation transfer model include solar-terrestrial geometric parameters, solar spectrum irradiance at the top of the atmosphere, and optical atmospheric quality; The initial value of aerosol optical depth is used as the input value and input into the configured SMARTS atmospheric radiation transfer model to obtain the calculated value of solar spectral irradiance.

7. The method according to claim 6, characterized in that The solar spectral irradiance at the top of the atmosphere is the solar spectral irradiance at the top of the atmosphere corrected according to the distance between the sun and the earth.

8. An aerosol optical thickness collaborative inversion device, characterized in that: include: An input module is used to input the initial value of aerosol optical thickness as an input value into the atmospheric radiation transfer model to obtain the calculated value of solar spectrum irradiance; An analysis module is used to perform regression analysis on the calculated solar spectrum irradiance value and the observed solar spectrum irradiance value to obtain a regression analysis result; An adjustment module is used to adjust the input value of the atmospheric radiation transfer model according to the regression analysis result until the degree of fit between the calculated value of the solar spectral irradiance and the observed value of the solar spectral irradiance is less than or equal to a target threshold, and the adjusted input value of the atmospheric radiation transfer model is used as the aerosol optical thickness inversion value.

9. An electronic device, comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 7.

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