1. AO 160 – OZVAL
Validation of ENVISAT ozone products through assimilation in the MSDOL model: First results obtained with GOMOS
Authors: B. Théodore and the OZVAL team

2. Objectives
Data assimilation for ENVISAT stratospheric ozone measurements using the MSDOL model
Daily delivery of ozone profiles over selected stations at synoptic hours
Daily maps of assimilated ozone field at synoptic hours

3. Comparison of GOMOS profiles with assimilated SMR data

4. MSDOL CTM driven by analysed ECMWF wind fields
Resolution: 2.5°x2.5°, 36 pressure levels between 240 to 0.3 hPa (10 to 62 km)
33 chemical species computed, semi-lagrangian transport
Sequential assimilation of O3 profiles

5. Data pre-processing
Read Level2 products from their native format;
Select useable data ;
Convert concentrations to mixing ratios using ECMWF temperature ;
Compute matrix H : each selected point is located on the model grid and the interplation coefficients are computed ;
Save these informations in a file (one file per profile).

7. Data selection: the good…

8. Data selection: the bad…

9. Data selection: the ugly !

10. A first glance at the Southern hemisphere in September

11. Ozone field at 31.4 hPa on Sep. 24th

12. Difference between an analyse and the free running model

13. Sequence of ozone fields at 31.4 hPa

15. Comparison with an ozone sounding at Marambio (64.23°S, 56.72°W)

16. Comparison with Lidar profiles at Lauder (45.05°S, 169.68°E)

17. An assimilation diagnostic: the quantity .

18. OmF vs.OmA

19. Time evolution of the OmF

20. Time evolution of the OmF/OmA

21. Assimilation with (better) data selection

22. Diagnostics

23. Time evolution of the OmF/OmA

25. Conclusions
GOMOS profiles exhibit large oscillations
Error bars in GOMOS products are unreliable
Careful data selection allows good assimilation results for ozone

26. Perspectives
assimilation of GOMOS data over upcoming validation campaigns
Assimilation of GOMOS “line densities” could help dealing with the “strong oscillations” problem