CN107505632A - A kind of temperature and pressure profile is with cutting high joint inversion method - Google Patents
A kind of temperature and pressure profile is with cutting high joint inversion method Download PDFInfo
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Abstract
The present invention relates to a kind of temperature and pressure profile and high joint inversion method is cut, by building priori profile, priori covariance matrix, observation covariance matrix；The geography of moonscope is inputted into positive radiative transfer model SCIATRAN with geological information, obtain the weighting function of the analogue value and temperature, with reference to the analogue value, the weighting function of temperature, priori profile, prior variance matrix and observation covariance matrix, temperature profile is obtained based on optimal estimation algorithm；The temperature profile inverting of occultation sensor is realized based on optimal estimation algorithm, and during inverting iteration, uses hydrostatic equilibrium equation, realize pressure and cut high Simultaneous Retrieving, by iteration, temperature profile, pressure profile are finally given, height is cut after correction.
Description
Technical field
The present invention relates to Observation of Occultation technical field, more particularly to a kind of temperature and pressure profile based on occultation sensor is with cutting height
Joint inversion method.
Background technology
Temperature and pressure profile is to carry out atmospheric parameter essential to trace gas inverting, and temperature and pressure parameters precision directly affects
The precision of other Atmospheric components invertings.Effective vertical height of Observation of Occultation is 10-100km, and meteorological data can not provide enough
Valid data, therefore atmospheric temperature and pressure profile need the inverting from the observation data of survey meter to obtain.To infrared channel profit
Use CO2Absorbing path carry out temperature and pressure inverting be conventional way.
For Observation of Occultation, the observation directional information of sensor is vital for inverting, and this is related to biography
Sensor receives the propagation path of radiation.Observation, which is pointed to, is mainly reflected in that the big autogenous cutting of observation path is high, due to air in high level
It is relatively lean, because light refraction caused by gas concentration difference is very weak in observation path, can be ignored, height is cut in observation can
Using moonscope geometry and day relative position information is calculated.But for lower atmosphere layer, gas is dense in observation path
It is obvious to spend graded, light refraction influences substantially on transmission path, and cutting height can not obtain using geological information simple computation is observed
Take, it is necessary to which height will be cut as a unknown number and treat that inverted parameters are fitted acquisition together.
At present, existing infrared occultation sensors A CE-FTS acquisitions temperature and pressure profile is with the method for cutting high profile in the world
The height of cutting of lower floor (below 40Km) is fitted the factor as one, the high method acquisition being fitted using the overall situation is cut to the region,
To upper strata (more than 40km), it is believed that the adjacent difference in height cut between height is accurate, not as the fitting factor.Based on overall situation fitting
Method obtains temperature and pressure profile can not quantitative predication with cutting the mode error of high sequence.At this stage, based on optimal inversion algorithm, tool
Have error can quantitative predication, advantage applied widely, be widely used in infrared facing side detector with terahertz wave band.But
Optimal estimation algorithm occultation sensor temperature and pressure profile and cut high joint inversion, have not been used.
The content of the invention
It is an object of the present invention in place of solving above shortcomings in the prior art.
To achieve the above object, the invention provides a kind of temperature and pressure profile with cutting high joint inversion method, this method includes
Following steps：Build priori profile, priori covariance matrix, observation covariance matrix；The geography of moonscope is believed with geometry
Breath inputs positive radiative transfer model SCIATRAN, the weighting function of the analogue value and temperature is obtained, with reference to the analogue value, the power of temperature
Weight function, priori profile, prior variance matrix and observation covariance matrix, the first temperature exterior feature is obtained based on optimal estimation algorithm
Line；Hydrostatic equilibrium equation is based on according to temperature profile and calculates pressure profile；Hydrostatics is based on according to pressure profile
Equilibrium equation calculates and cuts height；By iterative calculation, second temperature profile, pressure profile are obtained, height is cut after correction.
Preferably, optimization algorithm comprises the following steps：
By the analogue value, the weighting function of temperature, priori profile, prior variance matrix, observation covariance square
Battle array, substitute into below equation：
Wherein, xaRepresent prior estimate,Represent the covariance of prior estimate, KTRepresent the transposition of weighting function, SyRepresent
The covariance of observation error, y represent measured value, and f represents forward model function,Represent the atmospheric parameter of estimation.
Preferably, it is according to the specific formula of hydrostatic equilibrium equation calculating pressure profile
Wherein, z represents Qie Gao；P represents pressure；G represents acceleration of gravity；MrAir relative molecular mass is represented,
During below 80km, constant can be used as；R represents gas constant；T represents temperature.
Preferably, cutting high specific formula according to the calculating of hydrostatic equilibrium equation is
Wherein, z represents Qie Gao；P represents pressure；G represents acceleration of gravity；MrAir relative molecular mass is represented,
During below 80km, constant can be used as；R represents gas constant；T represents temperature.
Preferably, iterative calculation be included in every time obtain temperature profile, pressure profile and Qie Gao after, amendment temperature, pressure,
Recalculate the analogue value, the weighting function of temperature, priori profile, prior variance matrix and observation covariance matrix.
Present invention employs optimal estimation algorithm, the algorithm is widely used, error can quantitative predication, with reference to occultation sensor
Feature, using hydrostatic equilibrium equation, realize pressure and cut high Simultaneous Retrieving, the algorithm may be used on domestic occultation and pass
In the GDHS of sensor.
Brief description of the drawings
Fig. 1 is a kind of temperature and pressure profile provided in an embodiment of the present invention and cuts high joint inversion method schematic diagram；
Fig. 2 is a kind of temperature and pressure provided in an embodiment of the present invention and cuts high joint inversion schematic flow sheet；
Fig. 3 is a kind of temperature retrieval figure provided in an embodiment of the present invention；
Fig. 4 is a kind of difference of temperature retrieval provided in an embodiment of the present invention；
Fig. 5 is a kind of pressure inversion result figure provided in the embodiment of the present invention；
Fig. 6 is a kind of difference chart of percentage comparison of the pressure provided in the embodiment of the present invention；
Fig. 7 is that provided in the embodiment of the present invention a kind of cuts high procreation result and high comparison diagram is cut by official；
Fig. 8 also have for a kind of correction provided in an embodiment of the present invention cut it is high with original cutting high differential chart.
Embodiment
Below by drawings and examples, technical scheme is described in further detail.
Fig. 1 is a kind of temperature and pressure profile provided in an embodiment of the present invention and cuts high joint inversion method schematic diagram；
Fig. 2 is a kind of temperature and pressure provided in an embodiment of the present invention and cuts high joint inversion schematic flow sheet；
As depicted in figs. 1 and 2, this inversion method comprises the following steps that：
Step S101：Build priori profile, priori covariance matrix, observation covariance matrix；
Specifically, the priori profile using MLS v4.22 levels product structure in of the invention needed for optimal estimation algorithm, when
Between span be 2005-2015, and the data are done with 5 ° of latitude, the monthly average of 30 ° of grid of longitude.Seen when in use according to satellite
The time latitude and longitude information matching priori of survey.Priori covariance matrix is the result counted to priori profile.Priori
The dimension of profile is xa(k, 1), wherein k are the air number of plies.The dimension of priori covariance matrix is
Observation error covariance matrix is a diagonal matrix, and its nonzero element (diagonal entry) represents observation error, non-
Diagonal entry is that zero to represent observation noise unrelated with passage, is independent to each passage.To occultation sensor, observation error
Influenceed by passage signal to noise ratio.In fact, SyTotal system noise should be included, off diagonal element is not all zero.In reality
Off diagonal element is set to zero in, is to handle one kind of problem reduction.The dimension for observing covariance matrix is Sy(m,
M), wherein m represents port number.
Step S102：The geography of moonscope is inputted into positive radiative transfer model SCIATRAN with geological information, obtained
The weighting function of the analogue value and temperature, with reference to the analogue value, the weighting function of temperature, priori profile, prior variance matrix and observation
Covariance matrix, the first temperature profile is obtained based on optimal estimation algorithm.
Further specifically, it is as follows to solve detailed process by step S102：
The transmitance observation of actual measurement is represented by
Y=f (x, b)+∈y (1.1)
F represents forward model function, and x represents real temperature profile, and b is model parameter, ∈yFor observation error.Utilize
The radiation value of forward model simulation is represented by：
WithRepresent the atmospheric parameter and model parameter of estimation.For parameterInverting, be represented by：
xaPrior estimate is represented, I represents reverse pattern function, and c represents other data (such as initial iterative value).Cost function
It is represented by：
Represent the covariance of prior estimate, SyRepresent the covariance of observation error.Make cost function minimum, even equation
(1.4) first derivative is 0, is represented by：
Wherein K is weighting function
The solution of formula (1.5) is：
When formula (1.7) is that moderately non-linear and initial estimate is near true solution, Newton iteration method solution can be used,
As shown in formula (1.8)：
The covariance of solution is represented by：
It is when initial estimate is far from actual value, steepest descent method can be used, make iteration convergence to optimal solution：
γ represents iteration step length.Levenberg-Marquardt can combine Newton iteration method with steepest descent method
As shown in formula (1.11)：
γ depends on the iteration performance of function, as φ (x(i+1)) ＞ φ (x(i)) when, increase γ values, otherwise reduce.D is represented
Scaling matrices, generally value be
By the priori in step S101, geography and the geological information of moonscope input positive radiative transfer model
SCIATRAN, it can obtain the analogue value (transmitance)With the weighting function K of temperature, with reference to step S101 priori profile, priori
Covariance matrix, covariance matrix is observed, formula (1.7) (1.9) is brought into, obtainsAs required temperature profile can be asked
Iteration 1 time temperature profile (i.e. the first temperature profile) and its covariance matrix.
Step S103：Hydrostatic equilibrium equation is based on according to temperature profile and calculates pressure profile；
Step S104：The calculating of hydrostatic equilibrium equation is based on according to pressure profile and cuts height；
Step S103 and the specific solution procedurees of step S104 are as follows：
Assuming that air meets hydrostatic equilibrium condition, according to hydrostatics side into ideal atmosphere state side
Journey, temperature, pressure, following relation be present between height and atmospheric density
Wherein z represents Qie Gao；P represents pressure；G represents acceleration of gravity；MrAir relative molecular mass is represented, in 80km
It is that can be used as constant below；R represents gas constant；T represents temperature, and above formula is integrated
Wherein g is latitude and the function of height, can be expressed as：
WhereinRepresent latitude,Represent the acceleration of gravity on sea level, ReffRepresent and cut effectively the half of the eminence earth
Footpath.
The pressure profile that can be asked by formula (1.13), and new pressure profile is write back into priori, pass through formula
(1.14) can try to achieve it is adjacent cut high difference in height, obtain new height of cutting, and write back forward model cuts high setting.
Step S105：By iterative calculation, second temperature profile, pressure profile are obtained, height is cut after correction.
Specifically, iterative step S102-104, meet cycling condition, obtained temperature profile is replaced into priori profile, obtained
The pressure arrived, temperature and Qie Gao replace the pressure in SCIATRAN, temperature and Qie Gao, are unsatisfactory for iterated conditional, jump out, obtainThe final temperature profile of as required temperature profile (i.e. second temperature profile), obtained pressure profile and cuts height i.e.
For final pressure profile and Qie Gao.
Wherein, cycling condition is：If iterations is less than 3 times and can meet that threshold condition can be jumped out, if 3 take second place
Do not reach set threshold condition also afterwards, jump out yet.
Wherein, threshold condition is | Tranobser-Transimu| ＜ 0.00001
Wherein, TranobserWith TransimuObservation spectrum transmitance and simulated spectra transmitance are represented respectively
Fig. 3 is a kind of temperature retrieval figure provided in an embodiment of the present invention；
Fig. 4 is a kind of difference of temperature retrieval provided in an embodiment of the present invention；
Fig. 5 is a kind of pressure inversion result figure provided in the embodiment of the present invention；
Fig. 6 is a kind of difference chart of percentage comparison of the pressure provided in the embodiment of the present invention；
Fig. 7 is that high comparison diagram is cut by a kind of high inversion result and the official of cutting provided in the embodiment of the present invention；
Fig. 8 also have for a kind of correction provided in an embodiment of the present invention cut it is high with original cutting high differential chart.
With the 1 scape observation spectrum sr38154 (2010-09-13,63 ° of N of latitude, 287 ° of longitude) of ACE-FTS occultation sensors
Exemplified by, illustrate said process, and inversion result and official products are compared.Its flow chart as indicated with 2, as a result such as Fig. 3-8 institutes
Show：
Wherein Fig. 3, represents the inversion result of this paper algorithms with circle solid line, band × number used for this paper inversion algorithms
Priori profile, the result provided for ACE-FTS with ☆.Fig. 4 is the result and official products' result of this paper inversion algorithm
Difference (retrive-ACE_FTS).By contrast as can be seen that in below 70km, both relative temperature differences within 2K,
Both significant differences at 70-80km, generally relative temperature difference is between ± 5K.
Fig. 5 is contrast of the pressure with official's result of this paper algorithm invertings, and wherein band zero is inversion result, and band ☆ is ACE-
The result that FTS is provided, Fig. 6 are both relative errors, as can be seen that existing in more than 15Km, both relative errors from figure
Within ± 20%.
Fig. 7 is the contrast for cutting height and official's result of this paper algorithm invertings, and wherein band zero is inversion result, and band ☆ is
The result that ACE-FTS is provided, Fig. 8 are both relative errors, as can be seen that both relative errors are with height from figure
Increase and increase, final relative error is between ± 1.5km.
Embodiment above, the purpose of the present invention, technical scheme and beneficial effect are carried out further in detail
Illustrate, should be understood that the embodiment that these are only the present invention, the protection model being not intended to limit the present invention
Enclose, within the spirit and principles of the invention, any modification, equivalent substitution and improvements done etc., should be included in the present invention
Protection domain within.
Claims (5)
1. a kind of temperature and pressure profile is with cutting high joint inversion method, it is characterised in that comprises the following steps：
Build priori profile, priori covariance matrix, observation covariance matrix；
The geography of moonscope is inputted into positive radiative transfer model SCIATRAN with geological information, obtains the analogue value and temperature
Weighting function, with reference to the analogue value, the weighting function of temperature, priori profile, prior variance matrix and covariance matrix is observed,
First temperature profile is obtained based on optimal estimation algorithm；
Hydrostatic equilibrium equation is based on according to temperature profile and calculates pressure profile；
The calculating of hydrostatic equilibrium equation is based on according to pressure profile and cuts height；
By iterative calculation, second temperature profile, pressure profile are obtained, height is cut after correction.
2. according to the method for claim 1, it is characterised in that the optimal estimation algorithm comprises the following steps：
By the analogue value, the weighting function of temperature, priori profile, prior variance matrix, observation covariance matrix, substitute into following public
Formula：
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Wherein, xaRepresent prior estimate,Represent the covariance of prior estimate, KTRepresent the transposition of the weighting function of temperature, SyGeneration
The covariance of table observation error, y represent measured value, and f represents forward model function,Represent the atmospheric parameter of estimation.
3. according to the method for claim 1, it is characterised in that described that hydrostatic equilibrium side is based on according to temperature profile
Journey calculate pressure profile specific formula be
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Wherein, z represents Qie Gao；P represents pressure；G represents acceleration of gravity；MrAir relative molecular mass is represented, in below 80km
When, constant can be used as；R represents gas constant；T represents temperature.
4. according to the method for claim 1, it is characterised in that described that hydrostatic equilibrium side is based on according to pressure profile
Journey calculating cuts high specific formula and is
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Wherein, z represents Qie Gao；P represents pressure；G represents acceleration of gravity；MrAir relative molecular mass is represented, in below 80km
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5. the method described in claim 1, it is characterised in that the iterative calculation is included in obtains temperature profile, pressure every time
After profile and Qie Gao, amendment temperature, pressure, the analogue value, the weighting function of temperature, priori profile are recalculated.
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| CN111504937A (en) * | 2020-04-28 | 2020-08-07 | 南通大学 | Method for correcting low-layer cut height of infrared occultation sensor based on non-absorption spectrum |
| CN113128058A (en) * | 2021-04-22 | 2021-07-16 | 中国科学院空天信息创新研究院 | Temperature profile inversion method and device, readable storage medium and electronic equipment |
| CN113239505A (en) * | 2020-11-27 | 2021-08-10 | 北京航空航天大学 | Atmospheric trace gas inversion method based on improved optimal estimation |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110275182A (en) * | 2019-06-25 | 2019-09-24 | 中国科学院国家空间科学中心 | A kind of near space atmospheric temperature and pressure profile detection system |
| CN110275182B (en) * | 2019-06-25 | 2021-05-18 | 中国科学院国家空间科学中心 | Near space atmospheric temperature and pressure profile detection system |
| CN111504937A (en) * | 2020-04-28 | 2020-08-07 | 南通大学 | Method for correcting low-layer cut height of infrared occultation sensor based on non-absorption spectrum |
| CN111504937B (en) * | 2020-04-28 | 2022-06-03 | 南通大学 | Method for correcting low-layer cut height of infrared occultation sensor based on non-absorption spectrum |
| CN113239505A (en) * | 2020-11-27 | 2021-08-10 | 北京航空航天大学 | Atmospheric trace gas inversion method based on improved optimal estimation |
| CN113239505B (en) * | 2020-11-27 | 2023-01-24 | 北京航空航天大学 | Atmospheric trace gas inversion method based on improved optimal estimation |
| CN113128058A (en) * | 2021-04-22 | 2021-07-16 | 中国科学院空天信息创新研究院 | Temperature profile inversion method and device, readable storage medium and electronic equipment |
| CN113702298A (en) * | 2021-08-25 | 2021-11-26 | 中国科学院合肥物质科学研究院 | Method, system and equipment for correcting cut-to-height of edge scattered radiation |
| CN113702298B (en) * | 2021-08-25 | 2023-11-17 | 中国科学院合肥物质科学研究院 | Method, system and equipment for correcting critical edge scattered radiation height cutting |
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