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Comparison of NO 2 profiles derived from MAX-DOAS measurements and model simulations

Comparison of NO 2 profiles derived from MAX-DOAS measurements and model simulations. Folkard Wittrock, Katrijn Cl é mer and the NO 2 profiling team. Objectives of the Bremen workshop in November. To present the „state of the art“ in tropospheric profiling of NO 2 (and other trace gases)

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Comparison of NO 2 profiles derived from MAX-DOAS measurements and model simulations

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  1. Comparison of NO2 profiles derived from MAX-DOAS measurements and model simulations Folkard Wittrock, Katrijn Clémerand the NO2 profiling team EOS-AURA Science Team Meeting14-17 September 2009, Leiden

  2. Objectives of the Bremen workshop in November • To present the „state of the art“ in tropospheric profiling of NO2 (and other trace gases) • To identify advantages but also limitations of the different methods • To collect ideas how to improve the methods and how to move on in the future e.g. harmonize MAXDOAS instruments and retrievals

  3. MAXDOAS vs. in situ BIRA MAXDOAS VMR surface layer compared to EMPA in situ courtesy: Katrijn Clémer, BIRA

  4. MAXDOAS vs. in situ VMR surface layer compared to Bremen in situ In situ BREAM GL

  5. NO2 Profile Comparison 25 June 23 June • first comparisons sometimes o.k., sometimes not • challenge is to identify what causes the differences-> model study

  6. Simulation study • IASB-BIRA has provided modeled NO2 slant columns for UV and visible, using • 8 different NO2 scenarios (profiles) • 2 aerosol loadings (AOD 0.14 and 0.54 for 477 nm) • aerosol information based on CIMEL data from Cabauw • HG phasefunction with asymmetry factor of 0.67 • Simulations for June 24, 2009 in Cabauw • 10 Elevation Angles (1,2,4,5,6,8,10,15,30,89) • SCD error based on real DOAS fit errors plus Gaussian noise • Calculations with LIDORT

  7. Simulation study Fixed settingsfor OE retrievalalgorithms • 0 to 4 km • Apriori 1 ppb atthesurface, 0.01 ppb atthe top • Sa 100% • 2 retrievals per situationandwavelength • Height grid 50 and 200m -> In total 64 retrievals • In total 5 groups (BIRA, MPI, NIWA, iup Bremen, WSU) havecalculateddata (4 OE, one „simple“ least squaresmethod, onlyoneresultforeachsituation)

  8. Simulation study

  9. Simulation study Bremen retrieval of block profile for low aerosol (UV)

  10. Simulation study Bremen retrieval of block profile for high aerosol (UV)

  11. Simulation study Exponential low pollution, low aerosol

  12. Simulation study Exponential high pollution, low aerosol

  13. Simulation study Block low pollution, low aerosol

  14. Simulation study Block high pollution, low aerosol

  15. Simulation study Very shallow layer, low aerosol

  16. Simulation study Less shallow layer, low aerosol

  17. Simulation study Uplifted layer, low pollution, low aerosol

  18. Simulation study Uplifted layer, high pollution, low aerosol

  19. Simulation study Exponential low pollution, high aerosol

  20. Simulation study Exponential high pollution, high aerosol

  21. Simulation study Block low pollution, high aerosol

  22. Simulation study Block high pollution, high aerosol

  23. Simulation study Very shallow layer, high aerosol

  24. Simulation study Less shallow layer, high aerosol

  25. Simulation study Uplifted layer, low pollution, high aerosol

  26. Simulation study Uplifted layer, high pollution, high aerosol

  27. Simulation study

  28. Simulation study

  29. Simulation study

  30. Conclusions • OE retrieval methods agree quite well to each other,… but not always to „reality“ • VC usually captured well also for difficult conditions • Viewing directions towards sun and for high SZA difficult to retrieve • Best settings for OE still open: • Finer grid gives more details, but tends to more oscillations -> Elena has the solution? • UV retrieval seems to be more stable • Is OE the best method for MAXDOAS retrievals?

  31. Outlook • Waiting formoregroupstocontribute (e.g. JAMSTEC on simulateddata, MPI on real data), same deadlineasforaerosols -> Mid April Profiling paper: • NO2profileintercomparisonfocusing on MAXDOAS capabilitiesandusing LIDAR and in situ ascomplementarydatasets (CWG: F. Wittrock, K. Clemer, H. Irie, S. Beirle?)Drafttobewritten in April 2010 before EGU

  32. Empa sees ca. 10 % more NO2 In situ instruments Comparison of Bremen in situ Instrument with Empa and RIVM (at ground level) Bremen - EMPA Slope : 1.11 Correlation : 0.993 Bremen – RIVM Slope : 0.985 Correlation : 0.992 • BLC instruments agree quite well

  33. In situ instruments • deviation between surface in-situ and 200 m in-situ gives information on boundary layer mixing

  34. In situ instruments • NO2 often not well mixed even in the lowest 200 m

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