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Transcript DLR.de • Chart 1 > 13th International HITRAN Conference > J.

DLR.de β€’ Chart 1
> 13th International HITRAN Conference > J. Loos β€’ New multispectrum fitting software used at DLR > June 24, 2014
New multispectrum fitting software used at DLR
for analysis of laboratory Fourier-Transform
molecular spectra
Joep Loos, Manfred Birk, Georg Wagner
German Aerospace Center, Remote Sensing Technology Institute
DLR.de β€’ Chart 2
> 13th International HITRAN Conference > J. Loos β€’ New multispectrum fitting software used at DLR > June 24, 2014
Absorption cross sections or line-by-line data?
293 K
273 K
253 K
233 K
203 K
-ln(t) x T / p
400
200
0
802.5
803.0
803.5
804.0
804.5
Wavenumber/cm-1
𝛼=
𝑑 = exp βˆ’π›Ό 𝑇, 𝑃, 𝜎 βˆ™ 𝑙 βˆ™ 𝑁
𝑆𝑖 βˆ™ 𝑓 𝑇, 𝑃, 𝜎, 𝑝𝑖
𝑖
β€’
β€’
β€’
β€’
High measurement effort
Higher resolution necessary
Low analysis effort
Only interpolation
 e.g. HFCs, CFCs
β€’
β€’
β€’
β€’
β€’
Baseline less critical
Less measurements needed
Extrapolation possible (to some extent)
Low line density
Error parametrization accessible
 e.g. CO, NO, H2O
DLR.de β€’ Chart 3
> 13th International HITRAN Conference > J. Loos β€’ New multispectrum fitting software used at DLR > June 24, 2014
Why multispectral fitting?
β€žClassicalβ€œ analysis:
single spectrum fitting
Multispectral analysis
FitMAS, LINEFIT, tool by MB/GW, …
𝑆 = 𝑆𝑖
𝑏𝐿𝑖,π‘π‘Žπ‘™π‘ = 𝛾𝐹 βˆ™ 𝑝𝑖 βˆ™
𝑇0
𝑇𝑖
𝑛
𝑆, 𝛾𝐹 , 𝑛
β€’
β€’
β€’
β€’
Computationally inexpensive
Quality assessment
accessible:
Chi-Test, filecuts
Test of data reduction model
possible
Error covariances lost
𝑆1
𝑏𝐿1
𝑇𝑖 = 𝑓 𝑆, 𝛾𝐹 , 𝑛 , 𝑝𝑖 , 𝑇𝑖
𝑆2
𝑏𝐿2
𝑆, 𝛾𝐹 , 𝑛
β€’
β€’
𝑆3
𝑏𝐿3
β€’
β€’
β€’
Computationally extensive
Quality assessment difficult:
only spectral residuals
Data reduction model has to
be known
decorrelates various
parameters
opaque and blended lines can
be fitted
DLR.de β€’ Chart 4
> 13th International HITRAN Conference > J. Loos β€’ New multispectrum fitting software used at DLR > June 24, 2014
Multispectrum vs single spectrum fitting
β€’ Single spectrum fitting + consecutive data reduction = sound method for generation of
spectroscopic data
β€’ Complexity and computation time requirements restrict multispectral fit to small spectral
intervals
β€’ Temperature and number density fit requires large spectral range  restricted to single
spectrum fits
β€’ Multispectrum fit yields higher precision in many cases
β€’ Multispectrum fit can give higher accuracy in some cases
β€’ Multispectrum fit enables fitting of parameters not accessible to single spectral analysis
e.g. speed-dependence
 Fusion of multispectrum and single spectrum fit to combine advantages
DLR.de β€’ Chart 5
> 13th International HITRAN Conference > J. Loos β€’ New multispectrum fitting software used at DLR > June 24, 2014
What can the new software do?
β€’ Line models
β€’
β€’
β€’
β€’
β€’
Filecut
Voigt
Speed-dependent Voigt (C. Boone)
Speed-dependent Galatry + LM (F. Hase)
pCqSDHC + LM (Ngo, Tran)
Humlicek by Kuntz & Ruyten for Boone and Tran
β€’ Versatile interactive mode
β€’ Choice of line model, fitparameters
β€’ ILS, calibration factors, baseline, channelling, …
β€’ Automatic mode
β€’ Microwindow-, spectra-, fitparameter selection (Voigt)
β€’ Chi-test of spectral residuals
β€’ Residua analysis similar to MIPAS/ENVISAT REC analsis
by Anu Dudhia planned
β€’ Single spectrum fitting
cor𝑖𝑗 =
β€’ Temperature/number density fit
β€’ Filecuts (results of single-spectra-fits vs. ms-fit)
𝐽𝑇 π‘Šπ½
𝐽𝑇 π‘Šπ½
𝐴 = 𝐽𝑇 π‘Šπ½
βˆ’1
β€’ Identification of systematic spectrum-specific errors
β€’ Identification/prevention of correlation between fitted parameters
β€’ Identification of source of information
C𝑝,𝑠 = 𝑁 βˆ™
π‘–βˆˆπ‘ 
𝑖𝑖
𝑖𝑗
𝐽𝑇 π‘Šπ½
𝐽𝑇 π‘Š
𝐴𝑝,𝑖
max𝑖 𝐴𝑝,𝑖
𝑗𝑗
DLR.de β€’ Chart 6
> 13th International HITRAN Conference > J. Loos β€’ New multispectrum fitting software used at DLR > June 24, 2014
How does it look like?
DLR.de β€’ Chart 7
> 13th International HITRAN Conference > J. Loos β€’ New multispectrum fitting software used at DLR > June 24, 2014
transmittance
Example: Speed-dependent analysis of H2O n2 band
1,0
0,8
0,6
0,4
0,2
0,0
pure
-2
1.2e21 m
pure
-2
6.1e21 m
pure
-2
1.1e23 m
pure
-2
5.2e23 m
pure
-2
4.3e23 m
pure
-2
2.1e24 m
pure
-2
3.0e22 m
pure
-2
2.5e24 m
pure
-2
1.0e25 m
1000.6 mb
-2
2.2e22 m
501.8 mb
-2
1.1e22 m
400.3 mb
-2
1.3e24 m
399.9 mb
-2
2.6e24 m
199.4 mb
-2
1.1e22 m
199.4 mb
-2
4.6e22 m
200.7 mb
-2
1.0e23 m
200.7 mb
-2
3.9e23 m
200.4 mb
-2
1.3e24 m
199.6 mb
-2
2.6e24 m
100.0 mb
-2
1.3e24 m
100.6 mb
-2
2.6e24 m
50.4 mb
-2
3.9e23 m
50.4 mb
-2
2.1e24 m
50.5 mb
-2
1.3e24 m
49.8 mb
-2
2.5e24 m
Voigt
transmittance
SDV
1,0
0,8
0,6
0,4
0,2
0,0
Voigt
transmittance
SDV
1,0
0,8
0,6
0,4
0,2
0,0
Voigt
transmittance
SDV
1,0
0,8
0,6
0,4
0,2
0,0
residual water
Voigt
transmittance
SDV
1,0
0,8
0,6
0,4
0,2
0,0
pressure- or
column density error
Voigt
SDV
1287,3
1287,4
1287,5
-1
wavenumber [cm ]
1287,3
1287,4
1287,5
-1
wavenumber [cm ]
1287,3
1287,4
1287,5
-1
wavenumber [cm ]
1287,3
1287,4
1287,5
-1
wavenumber [cm ]
1287,3
1287,4
1287,5
-1
wavenumber [cm ]
DLR.de β€’ Chart 8
> 13th International HITRAN Conference > J. Loos β€’ New multispectrum fitting software used at DLR > June 24, 2014
Example: Speed-dependent analysis of H2O n2 band
guide to the eye
(3rd order polynomial)
6
4
2
guide to the eye
(3rd order polynomial)
0,24
2,SDV / SDV
(SDV- Hit12) / Hit12 [%]
8
0,20
0,16
0,12
0,08
0
0,02
0,04
0,06
0,08
-1
-1
Hit12 [cm atm ]
0,10
0,02
0,04
0,06
0,08
-1
-1
SDV [cm atm ]
β€’ Voigt: w-shaped residuals for non-opaque lines
β€’ Voigt: line-wing residuals for opaque lines
β€’ Fitted broadening parameters systemitically larger when fitted with SDV
 Opaque lines are modelled too narrow
β€’ Influence of narrowing larger when broadening parameter lower (higher J)
0,10
DLR.de β€’ Chart 9
> 13th International HITRAN Conference > J. Loos β€’ New multispectrum fitting software used at DLR > June 24, 2014
Example: Line mixing of N2O n3 band
103.7 mb,
205.9 mb;
498.2 mb;
1000.2 mb
103.7 mb,
0,5
0,0
0,5
0.049 %
0.053 %
0.036 %
Voigt - profile:
0,4
0,0
-0,4
0,4
0,0
-0,4
0,4
0,0
-0,4
0,4
0,0
-0,4
0,4
0,0
-0,4
0,4
0,0
-0,4
0,4
0,0
-0,4
0,4
0,0
-0,4
0.074 %
0.086 %
0.081 %
2210
2220
2230
-1
wavenumber (cm )
2240
2250

0.061 %
0.049 %
0.053 %
0.036 %
Voigt - profile:

0.076 %
2200
(obs - calc) * 100
0.061 %
2190
qSDV+LM - profile:

(obs - calc) * 100
(obs - calc) * 100
(obs - calc) * 100
0,4
0,0
-0,4
0,4
0,0
-0,4
0,4
0,0
-0,4
0,4
0,0
-0,4
1000.2 mb
0,0
qSDV+LM - profile:
0,4
0,0
-0,4
0,4
0,0
-0,4
0,4
0,0
-0,4
0,4
0,0
-0,4
498.2 mb;
1,0
transmittance
transmittance
1,0
205.9 mb;

0.076 %
0.074 %
0.086 %
0.081 %
2240,4
2240,8
2241,2
2241,6
-1
wavenumber (cm )
2242,0
DLR.de β€’ Chart 10
> 13th International HITRAN Conference > J. Loos β€’ New multispectrum fitting software used at DLR > June 24, 2014
Example: Line mixing of N2O n3 band
0,03
qSDV+LM
fit to qSDV+LM
Voigt
(0 - 0,HIT) / 0,HIT
0,09
-1
-1
0 (cm atm )
0,10
0,08
0,02
0,01
qSDV+LM
Voigt
0,00
0,07
-40
-30
-20
-10
0
10
20
30
40
0,0
0,5
1,0
1,5
2,0
m
3,5
0,020
qSDV+LM
fit
4,0
4,5
5,0
qSDV+LM
polyn. fit
0,015
0,010
0,010
0,005
-1
Y0 (atm )
-1
-1
3,0
opacity
0,012
2 (cm atm )
2,5
0,008
0,000
-0,005
-0,010
0,006
-0,015
-0,020
0,004
-40
-30
-20
-10
0
m
10
20
30
40
-40
-30
-20
-10
0
m
10
20
30
40
DLR.de β€’ Chart 11
> 13th International HITRAN Conference > J. Loos β€’ New multispectrum fitting software used at DLR > June 24, 2014
Concluding remarks
β€’ Multispectral analysis essential when using line profiles of high complexity and various
parameters
β€’ IDL fitting tool combining advantages of single and multispectrum fit has been developed
β€’ Several line models
β€’ Interactive and automatic mode
β€’ Additional information for quality assessment
(parameter correlation matrix, information content, filecuts)
β€’ H2O n2 band reanalyzed
β€’ Speed-dependence of broadening parameter has to be considered
β€’ Opaque and non-opaque lines fitted simultaneously
β€’ Systematically larger broadening parameters than HITRAN
β€’ N2O n3 band
β€’ High SNR measurements
β€’ Speed-dependence and line mixing have to be considered