1. Retrieval of Methane Distributions from IASI
Waterfall, R. Siddans, B. Kerridge, G. Miles, B. Latter
Rutherford Appleton Laboratory
Acknowledgements: NCEO Atmospheric Composition Theme

2. Why measure methane with IASI?
Important for its role in atmospheric chemistry and as a greenhouse gas
Concentrations are increasing with time (but not consistently)
Uncertainties in the global methane budget
Satellite measurements available (tropospheric methane):
mid-IR (IASI, TES, AIRS)
near-IR (GOSAT, SCIAMACHY)
Advantages/disadvantages of IASI
Global day/night coverage
Different sensitivity
Long time series of planned instruments (monitoring of trends)

3. IASI CH4 retrieval scheme
Retrieval Technique:
Optimal estimation
Radiative Transfer model:
RTTOV (with customised coefficients)
Spectral range:
cm-1
(cf. Razavi et al, ACP 2009)
Retrieval species:
CH4, N2O, H2O (log vmr)
HDO scaling factor, surface temperature
Measurement noise:
Derived from spectral fits (dependent on scene radiance)
Apriori + covariance matrix
Fixed apriori profile (no latitude dependence)
Covariance: ~ 10% error in troposphere, increased in stratosphere, with 6km correlation length
Background profiles
Temperature, and apriori surface temperature, H2O from ECMWF

4. Vertical sensitivity Example real averaging kernels
Retrieve methane on a fixed pressure grid (~0,6,12,16,20... km)
Principal sensitivity is in mid to upper troposphere
Limited sensitivity at the surface (dependent on air-surface temperature contrast) T
Example real averaging kernels
Simulated averaging kernels
Averaging kernels:
x = vmr
1km retrieval grid, 6km correlation length
Averaging kernels:
x = ln(vmr)
Latitude

5. Expected methane precision (fractional error) Retrieved/apriori error
Retrieval error
Retrieved/apriori error
Latitude
Latitude
Apriori error values: 10% in troposphere, higher in stratosphere
Significant improvement over apriori in mid and upper tropospheric layers

6. Version 1 of methane data
23rd August 2009
Day
4 continuous months of data (August – November 2009), April 2009, August 2008
Profile retrieval
=> Column averaged mixing ratios
Xch4 averaging kernel
XCH4 /ppmv
Night
‘least cloudy’ out of every 4 pixels
Nb. retrieval very sensitive to cloud

7. Monthly mean column averaged mixing ratios gridded 1x1 degree bins
September 2009
Day
Monthly mean column averaged mixing ratios
gridded 1x1 degree bins
Nb. Apriori data is a constant profile => N-S gradient comes completely from IASI
Xch4 (ppmv)
Night
© 2010 RAL Space

8. DAY
Possible reasons for day/night difference:
Difference in sensitivity
Problem with apriori
CH4 apriori has a low bias, inconsistent with apriori error
Different cloud sensitivity
NIGHT

9. NCEO Model + satellite comparisons: Aug 2009
Aug 2009, bias:
IASI (night)
GEOSCHEM (U. Edinburgh)
TOMCAT (U. Leeds)
Xch4 (ppmv)
:…..
GOSAT (U. Leicester)

10. Monthly mean data, 1x1°bins
April 2009
August 2009
November 2009
IASI (night time only data)
Xch4 (ppmv)
GOSAT
GOSAT data produced by R. Parker, U. Leicester, see poster by Byckling et al.

11. Monthly mean data on retrieval levels
August 2009
DAY
ppmv
ppmv
Column averaged mixing ratio
178 hPa
422 hPa
NIGHT

12. Are these distributions reasonable?
300 hPa
IASI night: 422 hPa
MACC Reanalysis data
500 hPa
ppmv
August 2009
Plots from MACC website.

13. Cloud effects on the retrieval data
Real retrievals show a tail of high methane retrievals believed to be due to cloud
Simulations based on AVHRR-3 data indicate that the apparent methane is expected to increase with increasing cloud top height and optical depth
Multiple scattering simulations based on more complicated (realistic) cloud distribution also show higher methane values due to increasing cloud amount
Will be hard to filter out as even small amounts of cloud can cause slightly increased radiances.
Retrieval of cloud top height/cloud fraction may improve retrievals in many cases.

14. IASI cloud sensitivity - AVHRR/3
ORAC
Cloud height / km
CH4 enhancement
Estimated Relative error on CH4 column
LUT of retrieval simulations of error due to cloud on IASI CH4 column averaged vmr
Cloud optical depth
Cloud Altitude / km

15. Summary and Future Plans
A scheme for retrieving methane profiles from IASI has been developed at RAL.
Version 1 global distributions of methane are now available for: August-November 2009, April 2009, August 2008
Agreement with many features seen in models / GOSAT
Current version has some issues related to cloud contamination and certain land types
Simulations show cloud can introduce a high bias to the IASI data
Further simulations are planned to assess the impact of other important error sources
Future versions will include improved handling of clouds and improved apriori data