1. C. Sweeney 1, A. Karion, D.W.Guenther 1, S. E. Wolter 1, D. Neff 1, P.M. Lang 2, M.J. Heller 1, T. Conway 2, E.J. Dlugokencky 2, P. Novelli 2, L. Bruhwiler 2, A. Hirsch 1, A. Jacobson 1, J. Miller 1 G. Petron 1, S. Montzka 2 and K.A. Masarie 2 1 CIRES, University of Colorado, Boulder, CO 2 NOAA/ESRL, Boulder, CO NOAA/ESRL Carbon Cycle Group aircraft profile measurements – Non CO 2 gases

3. Aircraft Data SF 6 CO N2ON2O CO 2 CH 4

4. Making Annual Climatology Original dataOriginal data – detrended Making an Annual Climatology

5. CO 2

6. West  East Transect HAA THD NHA OIL West coast sites lagged by one month West coast show well mixed throughout column relative to east coast CAR

7. CO 2

8. The Arctic Footprint Boundary LayerFree Troposphere Courtesy of Adam Hirsch

9. Arctic CO 2 /CH 4 Correlation Residual of profile means show extremely good correlations in Arctic.

10. CH 4

11. Boundary Layer Free Troposphere HAA NHA SCA CMA Boundary Layer Enhancement of CH 4 Significant enhancement in the boundary layer suggesting a year round flux

12. N2ON2O

13. Midwest Sites THD NHA CAR Midwest enhancement of N 2 O Significant enhancement of N 2 O in boundary layer in croplands of the Midwestern US Courtesy of Eric Kort (GEIA N2O fluxes)

14. CO

15. CH 4

16. Arctic CO 2 /CO Correlation Residual s of profile means for CO 2 and CO correlates well suggesting that large scale transport is driving winter time high. PFA

17. Free Troposphere Boundary Layer HAA CAR NHA OIL NHA OIL Boundary layer CO

18. SF 6

19. CO N2ON2O CO 2 NHA HFM

20. What do we do with the data?

21. Kriging interpolation – 850 mbar Crovoisier et al., in review

22. Direct Carbon Budgeting Approach Surface CO 2 fluxes (F surf ) Out Exchanges with the upper atmosphere (convection, advection) h Observations aircrafts + towers. ? Edges Convection Volume Crovoisier et al., 2006

23. Crovoisier et al., in review

24. Surface flux  acting on transport (A)  Concentration Forward Model Regression of data c onto basis set A. Inverse Model Measurement Background

25. Forward Model A Transport  Flux Foot print – one month Flux prior (GEIA) = C ’ Concentration anomally Courtesy of Eric Kort

26. Regions Obs. (Flasks/profiles) Particle concentration (BL)  Regions = C’pC’p [CH 4 ]Flux AIAI Regions Foot print – one month Courtesy of Eric Kort Flux prior (GEIA)

27. Inversion Model for aircraft profiles using a LPDM Advantage: 1. Monthly fluxes for each region 2.Ability to use sparse measurement field by treating each profile as an independent observation assuming that monthly fluxes have not changed over the last 5 years. 3.Evaluate spatial distribution of fluxes (region to region) Disadvantage 1.Requires a background concentration 2.It will be tricky to define regions that are truly independent. 3.Number of regions will be limited by the limited number of profiles per month (10 profiles x 18 sites)

28. Conclusions The last 5 years of aircraft profiles not only tell us about transport but suggest distribution of many sources/sinks for CO 2, CO, SF 6, N 2 O and CH 4. The aircraft profiles offer an independent estimate of regional scale fluxes. This is a new dataset which needs to be exercised by good science!