1. Estimation of daily CO 2 fluxes over Europe by inversion of atmospheric continuous data C. Carouge and P. Peylin ; P. Bousquet ; P. Ciais ; P. Rayner Laboratoire des Sciences du Climat et de l’Environnement Acknowledgement : all experimentalists from Aerocarb project

2. high spatial resol. Model daily time step inversion How to assimilate daily measurements ? Schauinsland CO2 (ppm)

3. Period : 1 year = 2001 Observations : 10 European stations, daily averaged data Transport model : LMDZ, zoom over Europe Fluxes : - Europe & North east Atlantic : each pixel / daily - Elsewhere : subcontinental regions / monthly Prior : Fluxes : optimised monthly fluxes Errors : 1 GtC/year over Europe 0.5 GtC/year over north east Atlantic tiny on other regions Correlations : spatial and temporal variable correlations between European pixels Inversion setup

4. AEROCARB data base : http://www.aerocarb.cnrs-gif.fr/database.html Continuous sites Continuous European measurement sites

5. Period : 1 year = 2001 Observations : 10 European stations, daily averaged data Transport model : LMDZ, zoom over Europe Fluxes : - Europe & North east Atlantic : each pixel / daily - Elsewhere : subcontinental regions / monthly Prior : Fluxes : optimised monthly fluxes Errors : 1 GtC/year over Europe 0.5 GtC/year over north east Atlantic tiny on other regions Correlations : spatial and temporal variable correlations between European pixels Inversion setup

6. Transport model Nudged on ECMWF winds 192 x 146 and 19 vertical levels - 0.5 x 0.5 degrees in the zoom - 4 x 4 degrees at the lowest resolution

7. Period : 1 year = 2001 Observations : 10 European stations, daily averaged data Transport model : LMDZ, zoom over Europe Fluxes : - Europe & North east Atlantic : each pixel / daily - Elsewhere : subcontinental regions / monthly Prior : Fluxes : pre-optimised monthly fluxes Errors : 1 GtC/year over Europe 0.5 GtC/year over north east Atlantic tiny on other regions Correlations : spatial and temporal correlations between European / N.Atlantic pixels Inversion setup

8. Spatial and temporal correlations Based on correlation lengths : Distance(i,j) : distance in space or time between 2 fluxes i, j L spatial : 500 - 800 km L temporal : 5 – 15 days

9. Technical aspects : Synthesis inversion to get posterior errors : Sequential approach with overlap : 11 * 2 months inversions Still 7000*60 unknowns covariance matrix of ~ 400,000 x 400,000 !! Use “retro-plume approach” (~ adjoint) to get daily response functions for all pixels Huge memory size problems ! Two steps inversion : - 1 st : standard monthly Fluxes + Globalview data - 2 nd : daily fluxes using the 1 st step estimated fluxes..

10. FIRST RESULTS ( Still preliminary)

11. Two different inversions 10 sites : Cabauw tower at 120m and 200m Data : full daily mean Data-error : stdev of hourly measurements Time correlation length : 5 days Spatial correlation lengths : 500/800 Km for land/ocean 9 sites : Cabauw tower at 200 m + data-error x 3 in winter Data : daytime-only mean Time correlation : 15 days First inversion Updated inversion

12. Fit to the stations : Westerland Posterior Prior Observations + error bars 16/0122/0327/053/0822/1015/12 (Days)

13. 16/0122/0327/053/0822/1015/12 Fit to the stations : Monte Cimone PosteriorPrior Observations + error bars (Days)

14. Need to use different levels depending on the season Aerocarb project : Forward simulation with REMOD model “Proper” vertical level (appropriated in winter) Diurnal cycle At Monte-Cimone

15. Fit to the stations : Schauinsland PosteriorPrior Observations + error bars 16/0122/03 27/05 3/0822/1015/12 (Days)

16. Fit to the stations : Cabauw (200 m) PosteriorPrior Observations + error bars 16/0122/03 27/05 3/0822/1015/12 (Days)

17. May November Flux correction : posterior - prior -250 -160 -70 20 110 200 (gC / m 2 / month) First inversion Updated inversion

18. Total flux over Europe fluxes (gC/day) 16/01 15/12 (Days) 30/06 08/04 02/10 First inversionUpdated inversion

19. 30 25 20 15 10 5 0 16/01 22/03 27/05 3/08 22/10 15/12 (Days) Error Reduction Error Reduction (%) LANDOCEAN First inversion Updated inversion

20. Error Reduction for « small » regions

21. Posterior - Prior (GtC/m²/month) Error Reduction (%) Correlation = 2000 km -25050100 0618301224 Impact of spatial correlation length Correlation = 300 km

22. Conclusions … First daily inversion over a full year with real continuous data and flux error correlations ! Spatial / Temporal patterns of fluxes critically depend on flux error correlations & error observations ! Flux corrections are still a bit high… … and Perspectives Comparaison with flux tower data / Bio. model Define spatial correlations from biogeochemical model Use improved prior fossil emissions Use new LMDz version with 38 vertical levels Integrated carbon assimilation system

23. Contributions

24. 16/0122/03 27/05 3/0822/1015/12 (Days) 16/0122/03 27/05 3/0822/1015/12 (Days) 30 25 20 15 10 5 0 16/01 22/03 27/053/08 22/10 15/12 (Days) LANDOCEAN Error reduction (%) Total fluxes and error reduction European NEPNorth east Atlantic flux Posterior flux Prior flux

25. -20160 0 80 gC/m²/month Prior Fluxes