The recent evolution of CO 2 and CH 4 in the mid-troposphere as seen from IASI onboard MetOp-A Cyril Crevoisier, Alain Chédin, Delphine Nobileau, Noëlle A. Scott, Raymond Armante, Laurent Crépeau, Thibaud Thonat and Jérôme Pernin Laboratoire de Météorologie Dynamique, CNRS, IPSL MACC – 3 rd General Assembly Utrecht, 23-27 May 2011 [email protected]
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The recent evolution of CO2 and CH4 in the mid-troposphere as seen from IASI onboard MetOp-A
Cyril Crevoisier, Alain Chédin, Delphine Nobileau, Noëlle A. Scott, Raymond Armante,
Laurent Crépeau, Thibaud Thonat and Jérôme Pernin
Laboratoire de Météorologie Dynamique, CNRS, IPSL
MACC – 3rd General Assembly Utrecht, 23-27 May 2011
The IASI instrument onboard MetOp-A
• IASI provides -8461 spectral channels between 645 and 2760 cm−1 (15.5 - 3.63 µm) -with a spectral resolution of 0.5 cm−1 after apodisation (“Level 1c” spectra) -the spectral sampling interval is 0.25 cm−1.
• Date of launch: 19 October 2006, onboard MetOp-A. • Declared operational in July 2007.
• IASI (Infrared Atmospheric Sounding Interferometer) is a Fourier Transform Spectrometer based on a Michelson Interferometer coupled to an integrated imaging system that measures infrared radiation emitted from the Earth. • It has been developed by CNES, in collaboration with EUMETSAT.
• IASI data are routinely archived at LMD via the Ether Centre for Atmospheric Chemistry Products and Services (http://ether.ipsl.jussieu.fr/), through EUMETCast, the Broadcast System for Environmental Data of EUMETSAT.
The IASI instrument onboard MetOp-A
CO
Sensi>vi>es of IASI channels to atmospheric and surface perturba>ons (simula8ons from LMD 4A radia8ve transfer model, based on the
GEISA spectroscopic database and using the TIGR atmospheric dataset)
Sco$ et Chédin, 1981 hKp://www.novel8s.fr/4AOP/
Jacquinet-‐Husson et al., 2008 hKp://ether.ipsl.jussieu.fr
CO2
H2O
CH4
Chédin et al., 1984 hKp://ara.abct.lmd.polytechnique.fr
O3
T
CO2 (1%) H2O (20%) O3 (10%) CH4 (10%) CO (10%) Tsurf (1 K) T (1K) N2O (2%)
The IASI instrument onboard MetOp-A
CO
Sensi>vi>es of IASI channels to atmospheric and surface perturba>ons (simula8ons from LMD 4A radia8ve transfer model, based on the
GEISA spectroscopic database and using the TIGR atmospheric dataset)
Sco$ et Chédin, 1981 hKp://www.novel8s.fr/4AOP/
Jacquinet-‐Husson et al., 2008 hKp://ether.ipsl.jussieu.fr
CO2
H2O
CH4
Chédin et al., 1984 hKp://ara.abct.lmd.polytechnique.fr
Simultaneous observa8ons: CO2, CH4, CO
O3
T
Retrieval of CO2, CH4 and CO from IASI
-‐Non linear inference scheme based on neural networks [Chédin et al., 2003, Crevoisier et al., 2009a, 2009b].
• We retrieve a mid or upper-‐tropospheric content: in clear sky only (no clouds, no aerosols) -‐ in day and night, over land and over sea
-‐The decorrela8on between T/GHG is easier to do in the tropics. ⇒ beKer precision in the tropical region.
-‐CO2/CH4 and T(p) are in8mately correlated in the IR.
Use of IR (IASI) and MW (AMSU) observa8ons to decorrelate T from gas varia8ons.
• For CO2 (low signal) and for CH4 (interferences from other species), we use:
• For CO, we use couples of IASI channels whose difference is only sensi8ve to the gas [Thonat et al., in prep.].
Pres
sure
(hPa
)
We have now ~3.5 years (July 2007-‐April 2011) of monthly averaged tropospheric CO2, CO and CH4 integrated content from IASI.
1000
100
10 CO2 CH4 CO
Weigh8ng func8ons
Mid-tropospheric CH4 from IASI
CH4 (pp
bv)
la8tude
Month
Zonally averaged tropical distribu>on of mid-‐tropospheric CH4 as retrieved from IASI from July 2007 to Dec. 2010
CH4 geographical distributions - 2009
TM5 simula8ons are constrained by NOAA surface sta8ons and SCIAMACHY and sampled/weighted at IASI resolu8on (courtesy of P. Bergamaschi).
JFM
AMJ
JAS
OND
JFM
AMJ
JAS
OND
IASI! TM5!
Latitudinal gradients of CH4 - 2009
IASI TM5
• Overall good agreement between IASI and TM5
• Strong disagreement between IASI and TM5 in February and March for the three available years partly due to a CH4 plume more spread over Indonesia and West of South America.
• Similar IASI/TM5 variability within each month.
May 2009
Jun. 2009
Jul. 2009
Aug. 2009
Sep. 2009
Oct. 2009
Nov. 2009
Dec. 2009
Jan. 2009
Feb. 2009
Mar. 2009
Apr. 2009
La8tud
e
Monthly variations of CH4 – Surface vs. Mid-tropo. Northern tropics
Southern tropics
0801 0807 0901 0907 1001 1007 1720
1760
1800
1820
1720
1760
1800
1820 CH
4 (pp
bv)
CH4 (pp
bv)
IASI
TM5
GLOBALVIEW-‐CH4
Month
IASI
TM5
GLOBALVIEW-‐CH4
CH4 trend over 2007-2010
• Trend of +10 ppb.yr-‐1 in 2007, which decreases throughout 2008-‐2009 and then becomes nega8ve in 2010.
• Same paKern of precipita8on in tropical wetlands, especially in South America.
IASI Surface (Dlugokencky
et al. 2009)
Year 20N:20S NH SH
2007 9.5 ± 2.8 7.3 ± 1.3 9.2 ± 0.3
2008 6.3 ± 1.7 8.1 ± 1.6*
2009 3.2 ± 2.1
2010 -2.9 ± 3.1
CH4 trend over 2007-2010
• Trend of +10 ppb.yr-‐1 in 2007, which decrease throughout 2008-‐2009 and then becomes nega8ve in 2010.
• Same paKern of precipita8on in tropical wetlands, especially in South America.
IASI Surface (Dlugokencky
et al. 2009)
Year 20N:20S NH SH
2007 9.5 ± 2.8 7.3 ± 1.3 9.2 ± 0.3
2008 6.3 ± 1.7 8.1 ± 1.6*
2009 3.2 ± 2.1
2010 -2.9 ± 3.1
CH4 increase and decrease mostly due to varia8ons in wetland emissions.
2003 2004 2005 2006 2007 2008 2009 2010 2011 2002
ECMWF precipitations in Amazonian wetlands
Impact of fires on CO2
370
380
390
Averaged seasonal cycle (night+day) of CO2 over [0-20N]
Spectral shih of the
instrument
Trend of +2 ppm.yr-‐1 in 2003-‐2010
AIRS
IASI
2003 2004 2005 2006 2007 2008 2009 2010 2011
• Study of the night minus day difference of retrieved CO2
• This diurnal variation is quantitavely linked to fire emissions (Chédin et al., 2005, 2008)
• IASI measures CO2 during day (9h30) and night (21h30)
385
375
MODIS fire pixels count
Jus>ce et al., 2002
Study of fires in Amazonia over 2008-2010
Fire season in Amazonia: July-‐Nov
Diurnal excess of IASI CO2 (ppmv)
2008
2009
2010
Crevoisier et al., in prep.
MODIS fire pixels count
Jus>ce et al., 2002
Study of fires in Amazonia over 2008-2010
Fire season in Amazonia: July-‐Nov
Diurnal excess of IASI CO2 (ppmv)
2008
2009
2010
Impact on CO2 and CO atmospheric distribu>ons of the 2010 severe drought in Amazonia
Monthly burden of IASI CO (ppbv)
Thonat et al., in prep. Crevoisier et al., in prep.
Conclusions
• Observa8ons in the thermal infrared can provide very useful informa8on to complement observa8ons made in the SWIR (GOSAT, OCO-‐2, etc.), and provide a means to study the correla8ons between various gases (eg: CO2 vs. CO, CH4).
• Retrieval over land/sea by night/day of a mid-‐to-‐upper tropospheric content of CO2
and CH4 from coupled IASI/AMSU in clear-‐sky condi8on.
• Precision: ~2.3ppmv / 20 ppbv for a 5ºx5º -‐ 1 month resolu8on.
• Comparison with atmospheric transport models seems promising even if differences need to be explained.
• CH4 fields retrieved from IASI tends to confirm that tropical wetland emissions driven by higher than average precipita8on are one of the main drivers of the 2007-‐2008 increase. The 2010 decrease of methane suggested by IASI is also supported by the drop in precipita8on over this year in wetland tropical region.
• CO2 fields provide informa8on of fire emissions, especially on their diurnal varia8on thanks to the night/day coverage of IASI.
• IASI CH4 fields are delivered to ECMWF and assimilated within IFS (see Richard’s and Anna’s talks)
Greenhouse gases from IASI and follow-ons
TOVS
METOP
AQUA
A-TRAIN
ENVISAT
MetOp-A
GOSAT
IASI on MetOp-‐A, B (2012) and C (2016)
EPS-SG (IASI-NG)
• With the launch of two other successive IASI instruments scheduled for 2012 and 2016, more than 20 years of observa8ons of mid-‐tropospheric CO2, CH4 and CO will be available for climate studies.
Merlin
Microcarb
Flex
CarbonSat
Sentinel 5 OCO-2
• Design of IASI-‐New Genera8on (IASI-‐NG) to be flown onboard EPS-‐SG.
GHG Missions under development 1978 2002 2006 2009 2013 2015 2016 2018 2020
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