1. Modelling Atmospheric CO2 Vertical Profiles TRANSCOM PARIS 2005 Christopher Pickett – Heaps  PhD Student (Univ. of Melbourne, AUS)  Supervisor:Dr. Peter Rayner  Currently studying at the LSCE

2. Thank You To…  Individuals Dr. Peter Rayner (Supervisor) Dr. Rachel Law (CSIRO) Dr. Philippe Ciais & others (LSCE)  Organisations CSIRO Atmospheric Research LSCE, CEA University of Melbourne

3. Aircraft Campaign/MissionAuthor(s) and/or Data ProvidersPeriod PROFILES Cape Grim Aerial Profile Archive GASLAB, CSIRO 1991 - 2000 Orleans Aerial Profile ArchiveLSCE, CEA1997 - Present CMDL Aerial Profile ArchivesP. Tans, CMDL/NOAA1992 - 2002 CAR, FTL, HAA, HFM, LEF, PFA, RTA, SAN TROPOSPHERIC Bible (A, B, C)Machida et al.1998, 1999, 2000 JAL (Japan/Aus)Matsueda & Inoue1993 - 2003 PEM-WEST A dc8Newell et al. 19961991 PEM-WEST B dc8Hoell et al., 19971994 PEM-TROPICS AHoell et al., 19991996 PEM-TROPICS BRaper et al., 20011999 TRACE AAndrae et al. 19961992 TRACE PJacob et al., 20032001 CARIBICBrenninkmeijer et al., 19991997 - 2001 STRATOSPHERIC ASHOEJPL, NASA1994 POLARISJPL, NASA1997 SOLVEJPL, NASA2000 STRATJPL, NASA1996 DATA PROVIDERS!!!

4. Why model CO2 vertical profiles?  Inversion validation  Satellite Validation  Potential use of profile data in atmospheric inversions

5. Inversion Procedure…  Use of data from 77 obs. stations Not gap filled (from GLOBALVIEW)  Use of prior estimates

6. Inversion Procedure…  Monthly fluxes 1989 – 2002 (14 yrs)  High spatial resolution:136 regions –92 land regions 44 ocean regions  One yr of response f’ns from 97-98 winds  15 ‘Sampled Inversions’ removing 20 stations from the network

7. Forward Model Procedure…  CSIRO CCAM model  Flux fields from each inversion inserted into the CCAM model Resolution200km by 18 lvls Time-step1hr Nudged by NCEP data(Inter-annual) Model operates within a Cubic-Conformal grid Advection scheme: NON LINEAR! –Semi-Lagranian horiz. advection with bi-cubic interpolation of fields –‘Non-negative constraint’ used for trace gas advection (Bermejo & Staniforth, 1992) and an ‘a posteriori conservation scheme’ is applied –Vertical advection uses a TDV scheme (Thuburn, 1993)

8. Forward model procedure…  Model sampled at appropriate point in time and space  Produces model data directly comparable to: Surface station monthly obs. data Vertical profile data

9. Model results at the surface (Examples)…

10. Model results at the surface (sampled inversions)…

11. Solutions to improve model fit…  Iteration procedure  Solve for flux estimate adjustments and adjust original CO2 flux estimates  Re-run forward model with adjusted flux field

12. Iteration results at the surface (examples)…

13. Solutions to improve model fit…  Sample inversion variability to characterise non-linearity

14. Profile fit examples (CGO)

15. Profile RMS Time Series (CGO) Mean RMS: 0.45ppm

16. Profile Bias (mean residual) Time Series (CGO)

17. What is causing errors in the model profiles?  Non-Linearity Issue  Profiles an instantaneous measurement Fluxes are monthly  High degree of ‘scatter’ in observed profile  Biomass burning events  Transport

18. Future plans…  Analyse sampled inversion flux estimates  Similar model comparison with LMDz  Use of profiles to estimate carbon flux  Proposed inter-comparison project Stay tuned!!!