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AO 160 – OZVAL

AO 160 – OZVAL V alidation of ENVISAT ozone products through assimilation in the MSDOL model: First results obtained with GOMOS. Authors: B. Théodore and the OZVAL team. Objectives. Data assimilation for ENVISAT stratospheric ozone measurements using the MSDOL model

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AO 160 – OZVAL

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  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. 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 MSDOL

  5. 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). Data pre-processing

  6. Data selection: the good…

  7. Data selection: the bad…

  8. Data selection: the ugly !

  9. A first glance at the Southern hemisphere in September

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

  11. Difference between an analyse and the free running model

  12. Sequence of ozone fields at 31.4 hPa

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

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

  15. An assimilation diagnostic: the quantity .

  16. OmF vs.OmA

  17. Time evolution of the OmF

  18. Time evolution of the OmF/OmA

  19. Assimilation with (better) data selection

  20. Diagnostics

  21. Time evolution of the OmF/OmA

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

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

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