CN103955607B - A kind of method for improving short-wave infrared satellite carbon dioxide inversion speed - Google Patents
A kind of method for improving short-wave infrared satellite carbon dioxide inversion speed Download PDFInfo
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Abstract
The invention discloses a kind of method for improving short-wave infrared satellite carbon dioxide inversion speed, the method comprising the steps of：S1. the priori profile database based on carbon dioxide, the carbon dioxide priori covariance matrix that geography network is formatted is calculated；S2. the method for interference is successively forced to calculate the weighting function of gas concentration lwevel；S3. carbon dioxide concentration value is iterated to calculate by optimum inversion method, and the gas concentration lwevel data input radiative transfer model of renewal, forward direction is calculated into the moonscope analogue value；S4. moonscope analogue value calculation cost functional value is utilized, if cost function reduces, inverting terminates；Otherwise, reduce iteration factor value, continue iteration.The present invention is using the mode of the iteration step length factor is increased, and the problem of overcoming the iteration step length occurred during short wavelength-NIR wave band carbon dioxide satellite remote sensing optimal inversion too small, realizes that gas concentration lwevel inverting provides effective technical method for fast and stable.
Description
Technical field
The present invention relates to satellite atmosphere remote sensing technology field, more particularly to short wavelength-NIR wave band carbon dioxide satellite remote sensing
Optimum inversion method.
Background technology
IPCC thinks, since a nearly century the rapid rising of atmospheric carbon dioxide concentration result in global warming,
The concentration and its spatial distribution of carbon dioxide are one of main uncertain factors during Global climate change is assessed.Due to titanium dioxide
The main source of carbon, which is converged, concentrates on surface layer, so the distribution of surface air gas concentration lwevel turns into study hotspot.Tradition
Ground based observa tion network point distribution is sparse, and it, which observes data, can not meet application demand, and satellite remote sensing technology can then make up foundation points
Observe the defects of data are limited.The U.S. in 20th century the seventies devise at first due to atmospheric remote sensing detection satellite sensor
HIRS, it is mainly used in carbon dioxide and steam in atmospheric sounding, the temperature profile of inverting air in early days.The sensor main of early stage will
Using the thermal radiation information of air, the heat radiation data of satellite sensor record are insensitive to surface layer state parameter, bag
The surface layer amount of state information contained is seldom.Ultraviolet-visible light-short wavelength-NIR remote sensing mode can then make up thermal infrared is distant
This defect of sense, what satellite sensor received is the solar radiation by earth surface reflection in the wavelength band, contains near-earth
Atmosphere state parameter information.Current existing greenhouse gases short wavelength-NIR Satellite Remote Sensing, includes and is taken on ENVISAT
The SCIAMACHY observation data of load, the TANSO-FTS sensors observation data that Japanese GOSAT is carried.With high spectrum point
The carbon dioxide near infrared range remote sensing satellite of resolution can provide the observation data of thousands of passages, contain the profile letter of carbon dioxide
Breath, how effectively accurately it is numerous observation data in calculate extraction carbon dioxide concentration informationsThis is that carbon dioxide satellite is distant
Feel the core of inverting work sutdy.
Atmospheric radiation transmission belongs to the first quasi-nonlinear Fredholm equations, so two based on radiative transfer model
Carbonoxide inversion problem is ill posed, and this causes common method of value solving to fail.The physical retrieval method of atmospheric outline,
It can unify in theory under the framework of Optimum Theory, optimize unified during iterative formula is studied as trace gas inverting
Form of presentation, by build object function and select optimizing strategy thinking, use carbon dioxide priori profile data, weight
Function, priori covariance matrix, observation error covariance matrix, the actual observed value etc. of satellite carbon dioxide channel, with iteration
Form progressively inverting obtains true solution.In near-infrared carbon dioxide satellite remote sensing, optimum estimation inversion method titanium dioxide is utilized
During carbon, influenceed, often occurred due to initially guessing value profile from actual value by priori initial value and priori covariance matrix
It is too remote and iteration step length is smaller causes iteration not restrain.Now, by optimize iterative formula in increase a step-length because
Son, and the variation tendency of the cost function value according to definition, the value of real-time update step factor, can quickly realize carbon dioxide
Retrieving concentration iteration convergence provides technical support.
The content of the invention
The invention provides iteration step length factor optimization method in a kind of short-wave infrared satellite carbon dioxide inverting, to solve
Technical problem be：A kind of side for increasing the iteration step length factor and real-time update iteration factor value into optimal inversion is provided
Method, as the technological means for realizing short wavelength-NIR band satellite remote sensing carbon dioxide fast inversion problem.
Include in short-wave infrared satellite data carbon dioxide inverting of the present invention the step of iteration step length factor optimization method：
S1, the titanium dioxide formatted using the carbon dioxide priori profile data simulated from atmospheric model, calculating geography network
Carbon priori covariance matrix；
S2, by the carbon dioxide priori profile data input into radiative transfer model, it is saturating that air flood is calculated
Rate initial value is crossed, calculates the weight letter of every layer of profile gas concentration lwevel with forward model based on the method for successively forcing to disturb
Number, obtains weighting function matrix；
When S3, first time iteration, the input of carbon dioxide priori value is being selected from the carbon dioxide priori profile data just
To model, the initial value of the iteration step length factor is set, if non-first time iteration, with the step factor value in last iteration, is read
Enter satellite carbon dioxide channel actual observed value, using optimizing iterative model iterative calculation carbon dioxide concentration value, and by institute
State carbon dioxide concentration value and input the forward model, calculate the moonscope analogue value；
S4, utilize the moonscope analogue value described in step S3, calculation cost functional value；If the cost function value is in error
Within threshold value, then inverting terminates, and carbon dioxide concentration value described in step S3 is inversion result；Otherwise iteration is continued；For the first time
During iteration, compare the cost function value being calculated with the moonscope analogue value and calculated with the carbon dioxide priori value
Obtained cost function value；If non-first time iteration, compare the cost function value being calculated after this and last iteration；If
The cost function value calculated after current iteration is relatively reduced, then inverting terminates；When continuing iteration, reduce step factor value, return
Step S3.
Successively forcing the method for interference described in step S2 in the method for the invention is：To the first layer of carbon dioxide profile
Concentration data number increases a certain proportion of variable, is then enter into the radiative transfer model, positive again to calculate air
Flood transmitance updated value, with reference to the air flood transmitance updated value and the air flood transmitance initial value, obtain
The weighting function of first layer gas concentration lwevel；Into carbon dioxide profile, the concentration of other layers increases variable successively, calculates
The weighting function of every layer of gas concentration lwevel into profile.
Iterative model is optimized described in step S3 in the method for the invention is：
In formula 1, α is the iteration step length factor；X is carbon dioxide concentration value；Sa represents priori covariance matrix；Se is observed
Error co-variance matrix；XaExpression initially guesses value；I represents ith iteration；KiIt is weighting function matrix；F represents forward model；Y
Represent the actual observed value of satellite carbon dioxide channel.F (X) represents that positive mox models calculate the moonscope analogue value.
The cost function value described in step S4 of the present invention, it is calculated moonscope analogue value F (Xi+1) with
The actual observed value Y calculation cost functional values of satellite carbon dioxide channel.Preferably, the satellite carbon dioxide channel is actual sees
Measured value is GOSAT satellite TANSO-FTS Band2 L1b spoke brightness datas.
It is optimal that the mode that utilization provided by the invention increases the iteration step length factor improves short wavelength-NIR wave band carbon dioxide
Change iterative inversion form, and the value of the cost function value variation tendency real-time update iteration step length factor according to definition, to utilize
GOSAT satellite TANSO-FTS Band2 L1b spoke brightness data fast inversion gas concentration lwevels, there is provided effective technology
Means.
Brief description of the drawings
Fig. 1 is short-wave infrared satellite data carbon dioxide inversion method flow chart
Specific embodiment
A kind of short-wave infrared satellite carbon dioxide inversion method proposed by the present invention, described in detail with reference to drawings and Examples
It is as follows.
As shown in figure 1, sought according to the iteration step length factor in a kind of short-wave infrared satellite data carbon dioxide inverting of the present invention
Excellent method and step includes：
S1, the titanium dioxide formatted using the carbon dioxide priori profile data simulated from atmospheric model, calculating geography network
Carbon priori covariance matrix；
S2, by carbon dioxide profile data input into radiative transfer model, based on successively force interference method utilize
Forward model calculates the weight of every layer of profile gas concentration lwevel；
Needed in S3, first time iteration select the iteration step length factor initial value 4, other when using in last iteration
Step factor, GOSAT satellite TANSO-FTS Band2 L1b spoke brightness datas are read in, calculate carbon dioxide in current iteration
Concentration value, and the gas concentration lwevel data input radiative transfer model of renewal, forward direction are calculated into the moonscope analogue value；
S4, the moonscope analogue value obtained in being walked using S3, calculate the cost function defined in optimum estimation method
Value；If cost function, within error threshold, inverting terminates, the gas concentration lwevel calculated in S3 is final inverting knot
Fruit；Otherwise continue.The moonscope analogue value obtained in being walked using S3, the cost function value defined in inverting is calculated, for the first time
During iteration, compare the situation of change of the cost function value with being calculated during input carbon dioxide priori value；Other when compare with it is upper
The situation of change of cost function value in secondary iteration；If this cost function calculated is relatively reduced, current iteration terminates；
Otherwise, iteration step length factor values halve, and return to S3 steps.
Wherein, step S1 further comprises：
S1.1, using atmospheric model, the dense carbon dioxide degrees of data in the specified time section of simulated production moonscope region
Product, i.e., described priori profile data, the product are to be distributed with the geographic grid of certain time resolution ratio and spatial resolution
Data；
S1.2, the gas concentration lwevel geographic grid distributed data for simulating to obtain using atmospheric model, utilize matrix operation
Obtain the priori covariance matrix for the carbon dioxide profile that geography network is formatted.
Wherein, step S2 further comprises：
S2.1, by carbon dioxide profile data input into radiative transfer model, forward direction be calculated air flood transmission
The initial value of rate, transmitance are represented by
Wherein, k be carbon dioxide molecule for absorption coefficient, ρ is the concentration of carbon dioxide, and z is air height.
S2.2, after total atmospheric spectral transmittance is obtained, increase to the first layer concentration data number of carbon dioxide profile certain
The variable △ ρ of ratio, radiative transfer model is then inputted, forward direction calculates flood transmitance, the flood calculated with reference to S2.1
The weighting function of first layer gas concentration lwevel is calculated in transmitance；
S2.3, into carbon dioxide profile, the concentration of other layers increases variable successively, and every layer of dioxy in profile is calculated
Change the weighting function of concentration of carbon, form weighting function matrix.
Wherein, step S3 further comprises：
S3.1, based on optimum estimation inversion method principle, introduce iteration step length factor-alpha, the form of iteration is changed into：
In formula 1, Sa represents priori covariance matrix；Se observation error covariance matrixes；XaExpression initially guesses value；I tables
Show ith iteration；KiIt is weighting function matrix；F represents forward model；Y represents the actual sight of GOSAT satellite carbon dioxide channels
Measured value.
When S3.2, first time iteration, step factor selects certain initial value；Other when, select last iteration in
Step factor value；GOSAT satellite TANSO-FTS Band2 L1b spoke brightness datas are read in, utilize revised iteration in S3.1
Form, the value X of calculatingi+1；
S3.3, by Xi+1Input radiation mode, forward direction calculate moonscope analogue value F (Xi+1)。
Wherein, step S4 further comprises：
S4.1, utilize the moonscope analogue value F (X being calculated in S3.3i+1), the actual observed value with GOSAT satellites
Y calculation cost functional values；Cost function calculation form is as follows：
Moonscope analogue value convergence actual observed value is wished herein, therefore calculates distance therebetween.Formula 3 is two
Mahalanobis distance expression formula between person.On having a diversified forms apart from the selection of calculation, mahalanobis distance be it is presently most used away from
From expression way.
If within error threshold, iteration terminates for S4.2, cost function, the gas concentration lwevel calculated in S3.2 is
Inversion result；Otherwise iteration is continued.During first time iteration, compare the cost function value of S4.1 calculating and utilize carbon dioxide priori
The cost function value that value is calculated；If non-first time iteration, compare and calculated in the cost function and last iteration of S4.1 calculating
Obtained cost function；If this cost function calculated is relatively reduced, iteration terminates；Continue iteration when, iteration step length because
Subvalue halves, and returns to S3 steps.
Embodiment of above is merely to illustrate the present invention, and not limitation of the present invention, about the common of technical field
Technical staff, without departing from the spirit and scope of the present invention, it can also make a variety of changes and modification, thus it is all
Equivalent technical scheme falls within scope of the invention, and scope of patent protection of the invention should be defined by the claims.
Claims (1)
- A kind of 1. method for improving short-wave infrared satellite carbon dioxide inversion speed, it is characterised in that comprise the following steps：S1, using the carbon dioxide priori profile data simulated from atmospheric model, it is first to calculate the carbon dioxide that geography network is formatted Test covariance matrix；S2, by the carbon dioxide priori profile data input into the forward model of radiative transfer model, air is calculated Flood transmitance initial value, the power of every layer of profile gas concentration lwevel is calculated with forward model based on the method for successively forcing to disturb Weight function, forms weighting function matrix；When S3, first time iteration, carbon dioxide priori value is selected from priori profile data and inputs the forward model, setting changes For the initial value of step factor, if non-first time iteration, with the step factor value in last iteration, satellite carbon dioxide is read in Passage actual observed value, using the concentration value for optimizing iterative model and calculating current iteration carbon dioxide, and by the titanium dioxide Concentration of carbon value inputs the forward model, calculates the moonscope analogue value；It is described optimization iterative model be：<mrow> <msub> <mi>X</mi> <mrow> <mi>i</mi> <mo>+</mo> <mn>1</mn> </mrow> </msub> <mo>=</mo> <msub> <mi>X</mi> <mi>i</mi> </msub> <mo>+</mo> <mi>&alpha;</mi> <msup> <mrow> <mo>&lsqb;</mo> <msubsup> <mi>S</mi> <mi>a</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mo>+</mo> <msubsup> <mi>K</mi> <mi>i</mi> <mi>T</mi> </msubsup> <mo>&CenterDot;</mo> <msubsup> <mi>S</mi> <mi>e</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mo>&CenterDot;</mo> <msub> <mi>K</mi> <mi>i</mi> </msub> <mo>&rsqb;</mo> </mrow> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>*</mo> <mo>{</mo> <msubsup> <mi>K</mi> <mi>i</mi> <mi>T</mi> </msubsup> <mo>&CenterDot;</mo> <msubsup> <mi>S</mi> <mi>e</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mo>&lsqb;</mo> <mi>Y</mi> <mo>-</mo> <mi>F</mi> <mrow> <mo>(</mo> <mi>X</mi> <mo>)</mo> </mrow> <mo>&rsqb;</mo> <mo>-</mo> <msubsup> <mi>S</mi> <mi>a</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mo>&lsqb;</mo> <msub> <mi>X</mi> <mi>i</mi> </msub> <mo>-</mo> <msub> <mi>X</mi> <mi>a</mi> </msub> <mo>&rsqb;</mo> <mo>}</mo> </mrow>Wherein, α is the iteration step length factor；X is carbon dioxide concentration value；Sa represents priori covariance matrix；Se observation errors are assisted Variance matrix；XaExpression initially guesses value；I represents ith iteration；KiIt is weighting function；F represents forward model；Y represents satellite two Carbonoxide passage actual observed value.F (X) represents positive and calculates the moonscope analogue value；S4, utilize the moonscope analogue value described in step S3, calculation cost functional value；If the cost function value is in error threshold Within, then inverting terminates, and carbon dioxide concentration value described in step S3 is inversion result；Otherwise iteration is continued；First time iteration When, compare the cost function value being calculated with the moonscope analogue value and obtained with the carbon dioxide calculation of initial value Cost function value；If non-first time iteration, compare the cost function value being calculated after this and last iteration；If this The cost function value calculated after iteration is relatively reduced, then current iteration terminates；When continuing iteration, iteration step length factor values halve, Return to step S3；It is described successively force interference method be：Increase a certain proportion of change to the first layer concentration data number of carbon dioxide profile Amount, is then enter into the radiative transfer model, positive again to calculate air flood transmitance updated value, with reference to described big Gas flood transmitance updated value and the air flood transmitance initial value, obtain the weight letter of first layer gas concentration lwevel Number；Successively into carbon dioxide profile other layers concentration increase variable, every layer of gas concentration lwevel is calculated in profile Weighting function；The initial value of the air flood transmitance is：<mrow> <msub> <mi>&tau;</mi> <mi>v</mi> </msub> <mo>=</mo> <mi>exp</mi> <mrow> <mo>(</mo> <mo>-</mo> <msubsup> <mo>&Integral;</mo> <mn>0</mn> <mi>Z</mi> </msubsup> <msub> <mi>k</mi> <mi>v</mi> </msub> <mi>&rho;</mi> <mi>d</mi> <mi>z</mi> <mo>)</mo> </mrow> </mrow>Wherein, k be carbon dioxide molecule for absorption coefficient, ρ is the concentration of carbon dioxide, and z is air height；Horse of the cost function between the moonscope analogue value and the satellite carbon dioxide channel actual observed value Formula distance, i.e.,：<mrow> <mi>J</mi> <mrow> <mo>(</mo> <mi>X</mi> <mo>)</mo> </mrow> <mo>=</mo> <msup> <mrow> <mo>(</mo> <mi>Y</mi> <mo>-</mo> <mi>F</mi> <mo>(</mo> <mi>X</mi> <mo>)</mo> <mo>)</mo> </mrow> <mi>T</mi> </msup> <mo>&CenterDot;</mo> <msubsup> <mi>S</mi> <mi>e</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mo>&CenterDot;</mo> <mrow> <mo>(</mo> <mi>Y</mi> <mo>-</mo> <mi>F</mi> <mo>(</mo> <mi>X</mi> <mo>)</mo> <mo>)</mo> </mrow> <mo>+</mo> <msup> <mrow> <mo>(</mo> <msub> <mi>X</mi> <mi>a</mi> </msub> <mo>-</mo> <mi>X</mi> <mo>)</mo> </mrow> <mi>T</mi> </msup> <mo>&CenterDot;</mo> <msubsup> <mi>S</mi> <mi>a</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mo>&CenterDot;</mo> <mrow> <mo>(</mo> <msub> <mi>X</mi> <mi>a</mi> </msub> <mo>-</mo> <mi>X</mi> <mo>)</mo> </mrow> </mrow>Wherein, X is carbon dioxide concentration value；Sa represents priori covariance matrix；Se observation error covariance matrixes；XaRepresent just Beginning guesses value；I represents ith iteration；Y represents satellite carbon dioxide channel actual observed value.F (X) represents that the positive satellite that calculates is seen Survey the analogue value；The satellite carbon dioxide channel actual observed value is GOSAT satellite TANSO-FTS Band2 L1b spoke brightness datas.
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| CN107561557B (en) * | 2017-08-18 | 2020-04-28 | 中国科学院遥感与数字地球研究所 | Atmospheric composition retrieval method for occultation detector |
| CN110196239B (en) * | 2019-06-12 | 2020-09-29 | 中国科学院南京地理与湖泊研究所 | Spectrum remote sensing inversion method for phytoplankton absorption coefficient of turbid water body |
| CN111579494B (en) * | 2020-05-29 | 2022-12-13 | 中国科学院合肥物质科学研究院 | Atmospheric CO with synchronous correction effect of chlorophyll fluorescence and aerosol 2 Satellite remote sensing observation inversion method |
| CN114112935A (en) * | 2021-11-22 | 2022-03-01 | 中国科学技术大学 | Real-time inversion method and device for vertical distribution of atmospheric pollutants, computer equipment and storage medium |
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