1. (Towards) anthropogenic CO2 emissions through inverse modelling
Frédéric Chevallier
LSCE, France
The PIs of the TCCON,
as listed on

2. (Towards) anthropogenic CO2 emissions through inverse modelling
Frédéric Chevallier
LSCE, France
The PIs of the TCCON,
as listed on

3. Outline On the maturity of CO2 inverse modeling
Development of CO2 observation systems about the anthropogenic emissions

4. CO2 observations Surface air-sample measurements
Retrievals of CO2 partial column
Satellites: AIRS, IASI, TES, …
[not demonstrated with real data]
Retrievals of CO2 total column
Satellites: SCIAMACHY, GOSAT
Surface: TCCON
Aircrafts

5. Atmospheric inverse modeling
Infer carbon surface fluxes from their measured impact on carbon concentrations
CO2 surface fluxes
Observations

6. Atmospheric inverse modeling
Infer carbon surface fluxes from their measured impact on carbon concentrations
Technology borrowed from Numerical Weather Prediction data assimilation systems
CO2 surface fluxes
Observations

7. Atmospheric inversions
Pros
Directly provides uncertainty estimates
Exhaustive, effective and not-intrusive approach
NRT possible
Refines prior inventories – ultimate estimation
Cons
Heavy, sophisticated numerical technology
Potentially expensive network deployment
Shall involve prior information
Involves chemistry-transport models
Sectorization not straightforward

8. Are inversion statistics reliable?
In its most rigorous form, the inversion problem is expressed by Bayes’ theorem
The output of an inversion is not a deterministic field but a multidimensional probability density function
How reliable are the second order moments of the pdf (variances and covariances)?

9. TCCON inversion vs. air-sample inversion
Aggregation of weekly/3.75ox2.5o results at the annual sub-continental scale
WDCGG, NOAA,
RAMCES, CarboEurope
databases
Chevallier et al., submitted to GRL

10. Evaluating inversion error statistics at local scale
Use air-sample inversion
Compare with y = TCCON measurements at 14 stations
E[ ( Hxb – y ) ( Hxb – y )T ] = HBHT+R
E[ ( Hxa – y ) ( Hxa – y )T ] = HAHT+R

11. Zooming
CO2 inversion is a mature field, even though all scientific questions have not been answered
Increase the resolution
of the inverse systems
of the observation systems

12. Mesoscale inverse modelling
Europe at 50km resolution using the CHIMERE model
Summer 2006
15 CO2 stations of the CarboEurope-Integrated Project
Comparison with spatial averages of gap-filled CarboEurope flux measurements L4 product
Broquet et al. 2011
Obs.
Inversion
Prior

13. Towards the inversion of the anthropogenic component (1/2)
Development of regional networks in Paris, Los Angeles, Indianapolis, …
Indianapolis-Flux
CO2-MegaParis
Davis et al., 2010

14. Towards the inversion of the anthropogenic component (2/2)
Development of regional networks in Paris, Los Angeles, Indianapolis, …
Strategies
Add expert knowledge: prescribe some of the space-time pattern of the anthropogenic emissions and adjust a few degrees of freedom only
Aggregation errors to be taken into account
Add measurements: tracers of anthropogenic emissions (CO, NOx, 14CO2, …) together with CO2
Model errors (chemistry) to be taken into account

15. Imaging the anthropogenic plumes from space (1/2)
CarbonSat is a satellite project which is being developed by ESA, as a candidate for the Earth Explorer Opportunity Mission to be launched in 2018 earliest
Measures the atmospheric concentrations of CO2 and CH4 with high spatial resolution (2 x 2 km2) and good spatial coverage (500 km swath width)
Focus on hot-spot sources, like power plants
Could be operated as a constellation

16. Imaging the anthropogenic plumes from space (2/2)
Accurate wind knowledge is key to the success of the mission

17. Towards anthropogenic CO2 emissions through inverse modelling
What EO/GMES techniques have been used to verify emissions inventories?
CO2 inverse modelling systems are being developed for this purpose
What key data is needed for this verification?
Dense observations around the target regions, of CO2 and of tracers of anthropogenic activity
What are the levels of uncertainty in datasets?
Depends on observation density - can be properly estimated
What future developments/enhancements are possible?
The main developments expected are on the observation side
Can EO/GMES techniques replace traditional emissions inventory estimates (which use statistical data)?
Inverse modelling refines prior inventories but do not replace them

18. Thank you for your attention