midtropospheric co concentration derived from infrared and...
TRANSCRIPT
ITSC XVIAngra dos Reis, 7-13 May 2008
Cyril Crevoisier, Alain Chédin, Noëlle A. Scott, Gaelle Dufour, Raymond Armante and Virginie Capelle
Midtropospheric CO2 Concentration derived from infrared and microwave sounders.
Application to the TOVS, AIRS/AMSU, and IASI/AMSU instruments.
Laboratoire de Météorologie Dynamique, CNRS, IPSL, Palaiseau
CO2 from infrared/microwave sounders
Since 2006
IASI/AMSUESA/MetOp
AIRS/AMSUNASA/AquaSince 2002
NOAA10TOVS
NOAAkATOVS
1987-1991 1999-2005
19/15
7.30
19/4
7.30
AquaAIRS/AMSU
MetOpIASI/AMSU
Time coverage May 2002-… Oct. 2006-…
Spectral resolution
0.5 - 2 cm-1 0.5 cm-1
(apodized)# IR/MWchannels
2378/15(324/15)
8461/15(421/15)
Local time 1.30 9.30
NOAA10/HIRS/MSU1987-1991
NOAAk/HIRS/AMSU1999-2005
CO2 seasonal cycle - Northern tropics [0-20°N]
NOAA10TOVS
NOAA15ATOVS*
AquaAIRS/AMSU
MetOpIASI/AMSU
87 91 01 03 0793 95 97 99 0589340350360370380
•NOAA10: Chédin et al., JGR, 2003, 2008.
•AIRS: Crevoisier et al., GRL, 2004.
•NOAA15: Very preliminary results…
CO2 seasonal cycle - Northern tropics [0-20°N]
NOAA10TOVS
NOAA15ATOVS*
AquaAIRS/AMSU
MetOpIASI/AMSU
87 91 01 03 0793 95 97 99 0589340350360370380
Difference between7.30 am/pm observations
Diurnal Tropospheric Excess of CO2due to biomass burning emissions
See Poster B12 [Chédin et al.]
Spectrum and sensitivity to atmospheric components
QuickTime™ and aTIFF (LZW) decompressor
are needed to see this picture.
CO2 (1%)H2O (20%)O3 (20%)CH4 (20%)CO (40%)N2O (2%)Surface
Sensitivity of IASI TB to variations of atmospheric and surface variables (simulations with the 4A RT model)
T Bpe
rt -T B
ref(K
)
10 μm 6 μm 4 μm15 μm
wavenumber (cm-1)
CO2
CO
CH4
surface
H2O
O3
N2O
1 % of CO2 variation → 0.04% of TB variation3ppmv → 0.3 K
The full information contained in the channels is needed to extract the CO2 signal!
Spectrum and sensitivity to atmospheric components
QuickTime™ and aTIFF (LZW) decompressor
are needed to see this picture.
CO2 (1%)H2O (20%)O3 (20%)CH4 (20%)CO (40%)N2O (2%)Surface
Sensitivity of IASI TB to variations of atmospheric and surface variables (simulations with the 4A RT model)
T Bpe
rt -T B
ref(K
)
10 μm 6 μm 4 μm15 μm
wavenumber (cm-1)
CO2
CO
CH4
surface
H2O
O3
N2O
1 % of CO2 variation → 0.04% of TB variation3ppmv → 0.3 K
The full information contained in the channels is needed to extract the CO2 signal!
Spectrum and sensitivity to atmospheric components
CO2 (1%)H2O (20%)O3 (20%) Surf. emissivity (5%)
CO (40%)Surface T (1%)
Sensitivity of AIRS and IASI channels in the two CO2 bands(simulations with the 4A RT model)
AIRS
wavenumber (cm-1)
CO2
CO noiseH2OO3CO2noise
1.51
0.50
-0.5
1.51
0.50
T Bpe
rt -T B
ref(K
)-0.5
670 690 710 730 750 2220 2260 2300 2340 2380
IASI
4 μm15 μm
650
surface T
At 4 μm: Non-LTE
Only nightime retrieval
T JacobianCO2 Jacobian
O3 Jacobian
Jacobians of two “CO2” AIRS channels
Channel 80 - 15μm Channel 261 - 4μm
Spectrum and sensitivity to atmospheric components
10
100
1000
1
0.1
•Channels at 4μm peak lower in the atmosphere.
Jacobians of two “CO2” AIRS channelsand AMSU weighting functions
Channel 80 - 15μm Channel 264 - 4μm
AMSU 7AMSU 6
AMSU 8
AMSU 10
Spectrum and sensitivity to atmospheric components
T JacobianCO2 Jacobian
O3 Jacobian
10
100
1000
1
0.1
AMSU 9
•Channels at 4μm peak lower in the atmosphere.
•AMSU channels bring the information on temperature.
CO2 channel selection•Aqua AIRS/AMSU:
-15 AIRS channels (8 in the 15 μm band - 7 in the 4 μm band).-2 AMSU channels (6 and 8).
•MetOp IASI/AMSU:-14 IASI channels (all in the 15 μm band).-3 AMSU channels (6, 7, and 8).
IASI - CO2 channel selection
-0.05
0
0.05
0.1
0.15
0.2
0.25
1 2 3 4 5 6 7 8 9 10 11 12 13 14
Sen
siti
vit
y (
K) CH4 4%
CO 20%
N2O 1%
O3 20%
CO2 1%
H2O 20%
AMSU 6
AMSU 8
AMSU 7
IASI CO2 JacobiansIASI sensitivity (K)
CO2 (1%) H2O (20%) O3 (20%) 10
100
1000
0.05
0
-0.05
0.1
0.15
0.2
0.25
The level1b validation suite at LMD
ECMWF
FTP « Clean »Radio-
soundings
L1B Satellite
Data(1979-2006)
RT model(Stransac, 4A)
Fixed CO2=372 ppmv
See Poster B10 [Armante et al.]
Radiative biasesbetween calculated and observed BT
Colocation of radiosoundings/re-analyses ERA40 with IR/MW observations
Space and Time
Colocation(100 Km, 3h)
Quality control of the Radiosoundings
Inter/extrapolationUGAMP climatology
Radio-soundings
/Reanalysis(ERA-40)
- Radiosoundings «ERA40 »(23 Go from 1979 to 2007 )-Re-analyses ERA-40 (79 Mo / day, 2 days /month)
Example IASI/AMSU (MetOp)Satellite data :14 orbits/day 900 Mo/day; 421 IR, 15 MW
AIRS Radiative biases: Monthly evolution (5 years over the tropics)
~60 situations/month over sea~30 situations/month over land
03 04 05 06 07 08-0.2
0
0.2
0.4
0.6
0.8
03 04 05 06 07 08
03 04 05 06 07 08
0.6
0.8
1
1.2
1.4
1.6
0.3
0.5
0.7
0.9
1.1
1.3
Cal
c.-O
bs. (
K) AIRS 80 (15 μm) AIRS 264 (4 μm)
AMSU 6
AIRS Radiative biases: Monthly evolution (5 years over the tropics)
“CO2” slopes (mean over 5 years):AIRS 80: 2.16 ppmv.yr-1
AIRS 264: 2.39 ppmv.yr-1
Mauna Loa: 2.05 ppmv.yr-1
~60 situations/month over sea~30 situations/month over land
03 04 05 06 07 08-0.2
0
0.2
0.4
0.6
0.8
03 04 05 06 07 08
03 04 05 06 07 08
0.6
0.8
1
1.2
1.4
1.6
0.3
0.5
0.7
0.9
1.1
1.3
Cal
c.-O
bs. (
K) AIRS 80 (15 μm) AIRS 264 (4 μm)
AMSU 6
A stand-alone approach
General features of the CO2 retrieval scheme :non-linear regressions
qCO2
Training of Neural Networks
Non-linear inference scheme
calc-obsbias removal
« clear sky »detection
Off-line
•Simultaneous use of IR and MW channels to decorrelate T/CO2.
IASI AMSU
•Retrieval limited to the tropical region.
Training data set (TIGR)
Selection of a set of CO2channels
[Chédin et al., JGR, 2003; Crevoisier et al., GRL, 2004]
Evaluation of the inference scheme characteristics
Pre
ssur
e (h
Pa)
We retrieve a mid-to-upper tropospheric integrated content of CO2.
5-15 km
10
100
1000
Mean CO2 averaging kernel over TIGR atmospheric dataset for nadir observation
AIRS/AMSUNOAA15IASI/AMSU
CO2 distribution from AIRS and IASI - Monthly average
Evaluation of IASI CO2
•Aircraft [Matsueda et al.]-8-10 km
•IASI CO2-integrated content 5-15 km
-1-2 points/month-until March. 2007
-period: July 2007-March 2008-monthly mean
JAL commercial airliners between Australia and Japan
10
100
1000
IASI CO2 weighting function
altitude of the aircraft
Seasonal cycle
Detrended CO2 seasonal cycle as observed in situ by JAL aircraft for 2003-2006
CO
2(p
pmv)
Apr Jun Aug Oct Dec Feb
-2
-1
0
1
2
Seasonal cycle
Apr Jun Aug Dec Feb
-2
-1
0
1
2
Detrended CO2 seasonal cycle as observed in situ by JAL aircraft for 2003-2006
CO
2(p
pmv)
Oct
IASI(07/07-08/03)
Latitudinal variationCO2 latitudinal variation in July
2006
2003
20052004
1 ppmv
2007
JAL aircraft (10 km)
IASI (5-15 km)
30N
-25N
25N
-20N
20N
-15N
15N
-10N
10N
-05N
05N
-EQ
EQ
-05S
05S
-10S
10S
-15S
15S
-20S
20S
-25S
Conclusions
The full information contained in the channels is needed (that excludes using PCA-like data).
•We retrieve a mid-to-upper tropospheric integrated content of CO2 from simultaneous IR/MW observations (TOVS, ATOVS, AIRS/AMSU, IASI/AMSU).
•The CO2 signal is very low:
-Reducing radiometric noise is as important as improving spectral resolution.
-A “good” AMSU instrument is important.
•Good agreement of CO2 distribution between IASI and AIRS but lower variability/uncertainty with IASI:
•General good agreement with in-situ observation in terms of seasonal cycle and latitudinal gradients.