CN113607654B - Global glyoxal concentration remote sensing inversion method and system based on hyperspectral satellite - Google Patents
Global glyoxal concentration remote sensing inversion method and system based on hyperspectral satellite Download PDFInfo
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Abstract
The invention discloses a global glyoxal concentration remote sensing inversion method, a system, equipment and a storage medium based on a hyperspectral satellite.
Description
Technical Field
The invention relates to the technical field of air quality remote sensing monitoring, in particular to a global glyoxal concentration remote sensing inversion method, a system, equipment and a storage medium.
Background
Accurate Volatile Organic Compound (VOC) monitoring of atmospheric pollution is the key to prevention and control of ozone pollution and Secondary Organic Aerosols (SOA). Glyoxal (CHOCHO), an important oxidation product of VOCs, has an important indicator for the observation of VOCs. The traditional ground sampling and remote sensing observation can not realize continuous effective observation in a large range for a long time.
The satellite glyoxal observation can realize large-range global observation generally, and has important significance for identifying VOC sources, accurately positioning discharge of chemical industrial parks and preventing and controlling regional pollution. However, due to the weak absorption of spectrum of glyoxal and interference of coherent gas, the inversion and accuracy of glyoxal are also easily limited.
In view of this, it is necessary to develop a high-precision remote sensing inversion scheme for glyoxal concentration according to the observation data of the satellite.
Disclosure of Invention
The invention aims to provide a global glyoxal concentration remote sensing inversion method, a system, equipment and a storage medium based on a hyperspectral satellite, which are suitable for hyperspectral satellite instrument characteristics and spectral characteristics and can realize the high-precision inversion of the concentration of a vertical column of glyoxal.
The purpose of the invention is realized by the following technical scheme:
a global glyoxal concentration remote sensing inversion method based on a hyperspectral satellite comprises the following steps:
fitting the simulated spectrum and the earth albedo spectrum observed by the satellite to obtain the concentration of the glyoxal inclined column;
calculating a scattering weight for each satellite observation pixel using a radiation transmission module;
calculating a vertical glyoxal shape factor by using the sum of the prior glyoxal profile and the concentration of each layer of profile in a model simulation mode to obtain the vertical glyoxal shape factor of each satellite observation pixel;
calculating an atmospheric quality factor by using the scattering weight of each satellite observation pixel and the vertical shape factor of glyoxal;
and calculating the vertical column concentration of the glyoxal by combining the corrected atmospheric quality factor of each satellite observation pixel with the glyoxal inclined column concentration of the corresponding satellite observation pixel obtained by fitting.
A global glyoxal concentration remote sensing inversion system based on a hyperspectral satellite comprises:
the glyoxal inclined column concentration calculating unit is used for fitting the simulated spectrum and the earth albedo spectrum observed by the satellite to obtain the glyoxal inclined column concentration;
a scattering weight calculation unit for calculating a scattering weight using the radiation transmission module for each satellite observation pixel;
the glyoxal vertical shape factor calculation unit is used for calculating the glyoxal vertical shape factor by using the sum of the prior glyoxal profile and the concentration of each layer of profile in a model simulation mode to obtain the glyoxal vertical shape factor of each satellite observation pixel;
the atmospheric quality factor calculation unit is used for calculating an atmospheric quality factor by using the scattering weight of each satellite observation pixel and the vertical shape factor of glyoxal;
and the vertical column concentration calculation unit of the glyoxal calculates the vertical column concentration of the glyoxal by combining the corrected atmospheric quality factors of the corresponding satellite observation pixels with the glyoxal inclined column concentration of the corresponding satellite observation pixels obtained by fitting.
A processing device, comprising: one or more processors; a memory for storing one or more programs;
wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the aforementioned methods.
A readable storage medium, storing a computer program, characterized in that the computer program realizes the aforementioned method when executed by a processor.
According to the technical scheme provided by the invention, the atmospheric quality factor can be accurately calculated by calculating the scattering weight and the vertical glyoxal shape factor and matching with terrain correction, so that the vertical glyoxal column concentration can be accurately inverted by combining the inclined glyoxal column concentration.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
FIG. 1 is a flow chart of a global glyoxal concentration remote sensing inversion method based on hyperspectral satellites according to an embodiment of the invention;
FIG. 2 is a schematic diagram illustrating a variation of a stripe offset value with time according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a stripe correction result according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a wavelength test result provided by an embodiment of the present invention;
FIG. 5 is a Chinese local area distribution diagram of glyoxal according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of a factory source VOC identification implementation provided by an embodiment of the present invention;
fig. 7 is a schematic diagram of a global glyoxal concentration remote sensing inversion system based on hyperspectral satellites according to an embodiment of the invention;
fig. 8 is a schematic diagram of a processing apparatus according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
The terms that may be used herein are first described as follows:
the terms "comprising," "including," "containing," "having," or other similar terms in describing these terms are to be construed as non-exclusive inclusions. For example: including a feature (e.g., material, component, ingredient, carrier, formulation, material, dimension, part, component, mechanism, device, process, procedure, method, reaction condition, processing condition, parameter, algorithm, signal, data, product, or article of manufacture), is to be construed as including not only the particular feature explicitly listed but also other features not explicitly listed as such which are known in the art.
The method for remote sensing inversion of the global glyoxal concentration based on the hyperspectral satellite provided by the invention is described in detail below. Details which are not described in detail in the embodiments of the invention belong to the prior art which is known to the person skilled in the art. Those not specifically mentioned in the examples of the present invention were carried out according to the conventional conditions in the art or conditions suggested by the manufacturer. The instruments used in the embodiments of the present invention are not indicated by manufacturers, and can be conventional products.
As shown in fig. 1, a global glyoxal concentration remote sensing inversion method based on a hyperspectral satellite comprises the following steps:
In the embodiment of the invention, nonlinear least square iterative fitting (Levenberg-Marquardt) is carried out on the simulated spectrum and the earth reflection illumination spectrum observed by a satellite to obtain the concentration of glyoxal inclined column (SCD), and the simulated spectrum is expressed as:
wherein e represents a natural constant, I s For the constructed simulated spectrum, I 0 Representing the daily solar irradiance spectrum, a represents I 0 Correction factor of X r Representing a Raman spectrum, alpha r Represents X r Fitting coefficient of (C) j Represents the absorption cross section, s, of different trace gases j j Differential oblique column concentrations (one of which contains the SCD of glyoxal) for different trace gases j, S is the slit function of the satellite instrument,
a convolution algorithm;
and
representing the stretching and shifting polynomials, respectively, represent the low frequency structure in the spectrum.
Preferably, significant band offset values are present in the observed results due to differences in performance of different instruments in the satellite detector array, and these offset values vary with time and are randomly free of fixed values, as shown in fig. 2, which is the case of band offset values with time. The invention selects an area with a relatively clean concentration value of glyoxal close to 0 as a standard area to carry out strip correction (for example, the Sahara desert is taken as the standard area), and supposing that the concentration change of the area is caused by the difference of a satellite detector, the adjusting and correcting scheme provided by the invention takes the concentration of the glyoxal inclined column in the standard area as a reference to correct the concentration of the glyoxal inclined column obtained in the step 1, and the formula is as follows:
SCD i_correction ＝SCD i_original -Mean(SCD i )
wherein, SCD i Indicating a standard area(e.g., the previously mentioned sub-saharan desert area) daily inverted glyoxal batter column concentration, SCD i_original 、SCD i_correction Each represents the concentration of the glyoxal diagonal column before and after the band correction, i represents the channel of the detector, mean (SCD) i ) As standard region SCD i Average value of (a).
The band correction method is applied to correction of the concentration of the glyoxal inclined column in the global range. Illustratively, the range of the correction reference area may be selected as: 20N to 30N, 10W to 30E, since the longitude range of the reference area spans a large extent, if a single satellite orbit cannot completely cover the entire reference area, it is necessary to merge multiple orbits to obtain daily slice correction values.
As shown in fig. 3, the left graph shows the result of the band correction, and the right graph shows the result of the band correction.
And 2, calculating scattering weight by using a radiation transmission module aiming at each satellite observation pixel.
In the embodiment of the invention, for each satellite observation pixel, a lookup table calculated by using a radiation transmission model (vlidot version 2.4) can be used for obtaining a scattering weight W (z) by utilizing interpolation, wherein z represents the number of layers of radiation light penetrating through the atmosphere to a satellite instrument, and the W (z) depends on wavelength, cloud cover, cloud pressure, yun Fanzhao rate, surface albedo, SZA (solar zenith angle), VZA (observation zenith angle), surface pressure and a CHOCHO profile, and the input information is utilized for searching the lookup table during calculation to obtain W (z).
Preferably, since the size of the observation grid of the satellite is different from the size of the model simulation profile grid, such deviations will cause distortion of the AMF when applying the model profile, especially in areas with large terrain undulations, and therefore a correction of the altitude information of the terrain grid of the satellite is required. The elevation information of the satellite is converted into the earth surface pressure through the temperature and air pressure information of model grid simulation, and then the earth surface pressure is applied to AMF calculation. The conversion is as follows: h is obtained by high-resolution earth surface elevation interpolation of earth surface height information of the satellite eff Surface temperature T through model simulation surf And surface pressure p GEOS Is converted into a toiletSurface pressure p of star terrain grid eff The conversion equation is as follows (assuming that the temperature variation varies linearly with height):
wherein h is eff Representing the height information of the earth's surface consistent with the size of the satellite pixel grid, h GEOS Represents the height information of the earth's surface in accordance with the size of the model mesh, K represents the correction coefficient, K = -g/RΓ, g represents the gravitational acceleration, and R is constant in dry air (e.g., R =287J kg) -1 K -1 ) And Γ represents the temperature decrease rate.
The above operation is equivalent to correcting the surface pressure, and inputting the corrected surface pressure and other information into a lookup table to perform lookup interpolation to obtain W (z).
Preferably, in the embodiment of the present invention, a cloud scenario is also considered. When the scattering weight is calculated, if the satellite observation pixel is a pixel not containing cloud (namely a non-cloud scene), the scattering weight W (z) = W is obtained by directly searching interpolation in the lookup table by using the scheme clear W is as described clear And the contribution value of the scattered sunlight of different height layers under the cloud-free condition to the total scattered light intensity received by the satellite detector is shown. If the satellite observation pixel is a pixel containing cloud, performing cloud correction, and decomposing the scattering weight W (z) into a non-cloud scene W clear With a cloud scene W cloud And respectively represents the contribution value of the scattered sunlight of different height layers under the conditions of no cloud and cloud to the total scattered light intensity received by the satellite detector. The scattering weight is calculated as follows:
wherein, I clear And I cloud Representing the intensity of the backscattered radiation, C, of a non-cloudy scene and a cloudy scene, respectively f Represents an effective cloud amount; w clear 、W cloud 、I clear And I cloud All can be calculated by VLIDORTAnd (5) obtaining the product.
And 3, calculating the vertical glyoxal shape factor by using the sum of the prior glyoxal profile and the concentration of each layer of profile in a model simulation mode to obtain the vertical glyoxal shape factor of each satellite observation pixel.
In the embodiment of the invention, a GEOS-Chem model (Goddard Earth Observing System v 12-3) can be used for calculation. The vertical glyoxal form factor S (z) consists essentially of the prior glyoxal profile n (z) and the sum VCD of the concentrations of each layer profile sum And S (z) is n (z) per layer divided by the sum of the profile concentrations of each layer VCD sum . Illustratively, these profiles have a spatial resolution of 0.25 ° × 0.3125 °, with 47 layers layered vertically, i.e., z = 1.
It should be noted that, the execution sequence of step 1, step 2 and step 3 is not distinguished, and may be executed synchronously, or may be executed sequentially according to any sequence.
And 4, calculating the atmospheric quality factor by using the scattering weight of each satellite observation pixel and the vertical shape factor of glyoxal.
From the results obtained in the foregoing steps 2 and 3, the atmospheric mass factor AMF can be calculated by integrating for each height layer:
where zs and zt represent the bottom and top layers of the atmosphere, respectively.
And 5, calculating the vertical column concentration of the glyoxal by utilizing the corrected atmospheric quality factor of each satellite observation pixel and combining the glyoxal inclined column concentration of the corresponding satellite observation pixel obtained by fitting.
The concentration of the glyoxal inclined column of each pixel is positioned at the atmospheric quality factor AMF of the corresponding pixel, so that the corresponding concentration of the glyoxal vertical column can be obtained, and the specific calculation process can refer to the conventional technology, which is not described herein again.
Preferably, in order to reduce the calculation amount and ensure the inversion accuracy, the optimal inversion waveband is selected in advance, and the above steps are only performed on the relevant information of the optimal inversion waveband. The principle of selecting the optimal inversion band is as follows: since glyoxal absorbs weakly in the visible band and the selection of inversion wavelength has a great influence on the result, the wavelength is subjected to a sensitive test, four different reference regions are selected in the global range as shown in table 1, and the regions represent that different glyoxal contents also include the influence of high sand albedo and liquid water absorption. Based on the sensitivity test of the inversion wavelength, the quality of an inversion result (the concentration of the batter) is judged through inversion errors (the batter concentration difference value after the iterative fitting of the actual measurement spectrum and the simulated spectrum is finished when the least square fitting is carried out) and fitting residual errors (obtained by calculating diagonal elements of a fitting covariance matrix), an optimal inversion waveband (for example, 435-462 nm) is obtained, the concentration of glyoxal in the waveband can be accurately inverted, the influence of sand albedo and liquid water absorption is avoided as much as possible, and meanwhile, the inversion errors and the fitting residual errors are in a reasonable range.
TABLE 1 wavelength sensitivity test area
As shown in fig. 4, the wavelength test results. Each SCD value in the figure is the average of the respective regions. The SCD obtained by inversion varies greatly in different wavelength bands in the same region, indicating that glyoxal is highly sensitive to wavelength. In the central Africa, the North and Central Africa, the fitting error increases significantly when the termination wavelength is below 459.5nm. This may be related to the fact that the strongest absorption peak of glyoxal is located around this wavelength, and therefore the stop wavelength is greater than 459.5nm. When the starting wavelength is greater than 438nm or less than 427nm, the fitting error will increase significantly and the SCD is an exceptionally low value, probably because the absorption of glyoxal is weak in this band and that of other interfering gases, and therefore the starting wavelength should be between 427nm and 438 nm. In sahara desert areas SCD are mostly positive when the starting wavelength is in the range 427nm to 428nm, outside this range SCD are mostly negative, and SCD is close to zero for the ending wavelength in the range 460nm to 463nm, which is relatively close to reality because chopho is not observed in the desert atmosphere under normal conditions. In the ocean, SCD is mostly negative due to interference with liquid water absorption. But still a small zero region can be found with a starting wavelength of 433.5nm to 439nm and an ending wavelength of 462nm to 464.5nm. In summary, the selected wavelength range is 435-462nm. In the frequency band, reliable glyoxal SCD can be obtained except that the fitting error and the fitting residual error are within an acceptable range, and glyoxal information of a desert area and an ocean area can be accurately obtained.
In the scheme for the high-precision inversion of the concentration of the vertical column of glyoxal provided by the embodiment of the invention, fig. 5 shows a distribution diagram of a local area in China of glyoxal obtained by inversion based on the scheme.
On the basis of the inversion scheme, factory source VOC identification can be realized; as shown in fig. 6, after the vertical column concentration of glyoxal is calculated, averaging is performed to a given regular grid (for example, a regular grid of 0.01 ° × 0.01 °) by using a grid point algorithm, random noise is averagely eliminated by using the spatial-temporal distribution result of the vertical column concentration of glyoxal in a long sequence (on the left side of fig. 6), a high-value point source of glyoxal is searched, and then high-resolution satellite images (on the right side of fig. 6) are combined to realize the traceability recognition of VOC emission of a factory.
It should be noted that the concentration of the glyoxal vertical column in the long sequence is the existing information, for example, the pre-calculated concentration of the glyoxal vertical column in the whole world from 2018 to 2020; a high glyoxal value point source is a pixel location point having a higher concentration value than the surrounding area glyoxal, and for example, a high definition condition is generally considered to be greater than 6 x 10 14 molec/cm 2 。
Another embodiment of the present invention further provides a hyperspectral satellite-based global glyoxal concentration remote sensing inversion system, which is mainly used for implementing the method provided in the foregoing embodiment, as shown in fig. 7, the system mainly includes:
the glyoxal inclined column concentration calculating unit is used for fitting the simulated spectrum and the earth albedo spectrum observed by the satellite to obtain the glyoxal inclined column concentration;
a scattering weight calculation unit for calculating a scattering weight using the radiation transmission module for each satellite observation pixel;
the glyoxal vertical shape factor calculation unit is used for calculating the glyoxal vertical shape factor by using the sum of the prior glyoxal profile and the concentration of each layer of profile in a model simulation mode to obtain the glyoxal vertical shape factor of each satellite observation pixel;
the atmospheric quality factor calculation unit is used for calculating the atmospheric quality factor by using the scattering weight of each satellite observation pixel and the vertical shape factor of the glyoxal;
and the vertical column concentration calculation unit of the glyoxal calculates the vertical column concentration of the glyoxal by combining the corrected atmospheric quality factor of the corresponding satellite observation pixel with the inclined column concentration of the glyoxal of the corresponding satellite observation pixel obtained by fitting.
Another embodiment of the present invention further provides a processing apparatus, as shown in fig. 8, which mainly includes: one or more processors; a memory for storing one or more programs; wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the methods provided by the foregoing embodiments.
Further, the processing device further comprises at least one input device and at least one output device; in the processing device, a processor, a memory, an input device and an output device are connected through a bus.
In the embodiment of the present invention, the specific types of the memory, the input device, and the output device are not limited; for example:
the input device can be a touch screen, an image acquisition device, a physical button or a mouse and the like;
the output device may be a display terminal;
the Memory may be a Random Access Memory (RAM) or a non-volatile Memory (non-volatile Memory), such as a disk Memory.
Another embodiment of the present invention further provides a readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the method provided by the foregoing embodiment.
The readable storage medium in the embodiment of the present invention may be provided in the foregoing processing device as a computer readable storage medium, for example, as a memory in the processing device. The readable storage medium may be various media that can store program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disk.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (7)
1. A global glyoxal concentration remote sensing inversion method based on a hyperspectral satellite is characterized by comprising the following steps:
fitting the simulated spectrum and the earth albedo spectrum observed by the satellite to obtain the concentration of the glyoxal inclined column;
calculating a scattering weight for each satellite observation pixel using a radiation transmission module;
calculating a vertical glyoxal shape factor by using the sum of the prior glyoxal profile and the concentration of each layer of profile in a model simulation mode to obtain the vertical glyoxal shape factor of each satellite observation pixel;
calculating an atmospheric quality factor by using the scattering weight of each satellite observation pixel and the vertical shape factor of glyoxal;
calculating the vertical column concentration of glyoxal by combining the corrected atmospheric quality factor of each satellite observation pixel with the glyoxal inclined column concentration of the corresponding satellite observation pixel obtained by fitting;
the method comprises the following steps of selecting an area with a glyoxal concentration value close to 0 as a standard area to perform strip correction, wherein concentration changes of the standard area are caused by differences of satellite detectors, correcting the concentration of the obtained glyoxal inclined column by taking the concentration of the glyoxal inclined column of the standard area as a reference, and the formula is as follows:
SCD i_correction ＝SCD i_original -Mean(SCD i )
wherein, SCD i Glyoxal batter concentration, SCD, representing daily inversion of standard area i_original 、SCD i_correction Each represents the concentration of the glyoxal diagonal column before and after the band correction, i represents the channel of the detector, mean (SCD) i ) As standard region SCD i Average value of (d);
the method comprises the following steps of selecting an optimal inversion waveband in advance, carrying out global glyoxal concentration inversion by using the optimal inversion waveband, wherein the mode of selecting the optimal inversion waveband comprises the following steps: based on the sensitivity test of the inversion wavelength, judging the quality of an inversion result through an inversion error and a fitting residual error, and selecting an optimal inversion waveband according to a judgment result; the inversion error is a glyoxal inclined column concentration difference value obtained after fitting the simulated spectrum and the earth albedo spectrum observed by the satellite, the fitting residual error is obtained through calculation of diagonal elements of a fitted covariance matrix, and the inversion result is the glyoxal inclined column concentration obtained through fitting;
after the vertical column concentration of the glyoxal is calculated, averaging is carried out in a given regular grid through a lattice point algorithm, after averaging is carried out by utilizing the spatial-temporal distribution result of the vertical column concentration of the glyoxal, a high-value point source of the glyoxal is searched, and the traceability identification of the emission of the volatile organic compounds of the atmospheric pollution of the factory is realized by combining with a satellite image.
2. The hyperspectral satellite-based global glyoxal concentration remote sensing inversion method according to claim 1, characterized in that nonlinear least squares iterative fitting is performed on the simulated spectrum and the earth reflected illumination spectrum observed by the satellite to obtain glyoxal inclined column concentration, and the simulated spectrum is represented as:
wherein e represents a natural constant, I s For the constructed simulated spectrum, I 0 Represents the daily solar irradiance spectrum, a represents I 0 Correction factor of X r Representing a Raman spectrum, alpha r Represents X r Fitting coefficient of (C) j Represents the absorption cross section, s, of different trace gases j j The differential inclined column concentration of different trace gases j is shown, one of the concentrations is the concentration of the glyoxal inclined column, S is the slit function of a satellite instrument,
a convolution algorithm;
and
respectively representing stretch and offset polynomials.
3. The remote sensing inversion method for the global glyoxal concentration based on the hyperspectral satellite as claimed in claim 1, wherein when the scattering weight is calculated, if a satellite observation pixel is a pixel not containing cloud, namely a non-cloud scene, a radiation transmission module is used for obtaining the scattering weight W (z) = W clear Said W clear Representing the contribution value of the scattered sunlight of different height layers under the cloud-free condition to the total scattered light intensity received by the satellite detector;
if the satellite observation pixel is a pixel containing cloud, performing cloud correction, and decomposing the scattering weight W (z) into a non-cloud scene and a cloud scene, wherein the scattering weight is calculated as follows:
wherein, C f Represents an effective cloud amount; i is clear And I cloud Representing the intensity of the backscattered radiation, W, of a non-cloudy and cloudy scene, respectively clear And W cloud And the contribution values of the scattered sunlight of different height layers under the conditions of no cloud and cloud to the total scattered light intensity received by the satellite detector are calculated by the radiation transmission module.
4. The hyperspectral satellite-based remote sensing inversion method of global glyoxal concentration according to claim 1 or 3, wherein the calculating scattering weights using the radiation transmission module comprises: calculating a lookup table by using a radiation transmission model, and searching interpolation in the lookup table by using wavelength, cloud amount, cloud pressure, cloud albedo, surface albedo, solar zenith angle, observation zenith angle, surface pressure and CHOCHO profile to obtain scattering weight;
wherein the corrected surface pressure is obtained by terrain correction, the correcting step comprising:
correcting the altitude information of the terrain grid of the satellite, converting the altitude information of the satellite into earth surface pressure through temperature and air pressure information simulated by a model, and applying the earth surface pressure to the calculation of the atmospheric quality factor; the conversion is as follows: the earth surface height information of the satellite is obtained by interpolation h eff Surface temperature T through model simulation surf And surface pressure p GEOS Surface pressure p converted into satellite terrain grid eff The conversion formula is as follows:
wherein h is eff Representing surface height information of the same size as the satellite pixel grid, h GEOS And (b) representing surface height information in accordance with the size of the model mesh, wherein K represents a correction coefficient, K = -g/RΓ, g represents a gravity acceleration, R is a constant in dry air, and Γ represents a temperature decrease rate.
5. A global glyoxal concentration remote sensing inversion system based on a hyperspectral satellite is characterized by comprising:
the glyoxal inclined column concentration calculating unit is used for fitting the simulated spectrum and the earth albedo spectrum observed by the satellite to obtain the glyoxal inclined column concentration;
a scattering weight calculation unit for calculating a scattering weight using the radiation transmission module for each satellite observation pixel;
the glyoxal vertical shape factor calculation unit is used for calculating the glyoxal vertical shape factor by using the sum of the prior glyoxal profile and the concentration of each layer of profile in a model simulation mode to obtain the glyoxal vertical shape factor of each satellite observation pixel;
the atmospheric quality factor calculation unit is used for calculating the atmospheric quality factor by using the scattering weight of each satellite observation pixel and the vertical shape factor of the glyoxal;
the vertical column concentration calculation unit of the glyoxal calculates the vertical column concentration of the glyoxal by combining the corrected atmospheric quality factor of the corresponding satellite observation pixel with the inclined column concentration of the glyoxal of the corresponding satellite observation pixel obtained by fitting;
the method comprises the following steps of selecting an area with a glyoxal concentration value close to 0 as a standard area to carry out strip correction, correcting the glyoxal inclined column concentration by taking the glyoxal inclined column concentration of the standard area as a reference, wherein the concentration change of the standard area is caused by the difference of satellite detectors, and the formula is as follows: SCD i_correction ＝SCD i_original -Mean(SCD i ) (ii) a Wherein, SCD i Glyoxal batter concentration, SCD, representing daily inversion of standard area i_original 、SCD i_correction Each representing the glyoxal diagonal concentration before and after the band correction, i represents the channel of the detector, mean (SCD) i ) As standard region SCD i Average value of (d);
the method comprises the following steps of selecting an optimal inversion waveband in advance, carrying out global glyoxal concentration inversion by using the optimal inversion waveband, wherein the mode of selecting the optimal inversion waveband comprises the following steps: based on the sensitivity test of the inversion wavelength, judging the quality of an inversion result through an inversion error and a fitting residual error, and selecting an optimal inversion waveband according to a judgment result; the inversion error is a glyoxal inclined column concentration difference value obtained after fitting the simulated spectrum and the earth albedo spectrum observed by the satellite, the fitting residual error is obtained through calculation of diagonal elements of a fitted covariance matrix, and the inversion result is the glyoxal inclined column concentration obtained through fitting; after the vertical column concentration of the glyoxal is calculated, averaging is carried out in a given regular grid through a lattice point algorithm, after averaging is carried out by utilizing the spatial-temporal distribution result of the vertical column concentration of the glyoxal, a high-value point source of the glyoxal is searched, and the traceability identification of the emission of the volatile organic compounds of the atmospheric pollution of the factory is realized by combining with a satellite image.
6. A processing apparatus, comprising: one or more processors; a memory for storing one or more programs;
wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-4.
7. A readable storage medium, storing a computer program, characterized in that the computer program, when being executed by a processor, carries out the method according to any one of claims 1 to 4.
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