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Cloud workshop wrap-up OMI science team meeting, 21 June 2006.

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Presentation on theme: "Cloud workshop wrap-up OMI science team meeting, 21 June 2006."— Presentation transcript:

1 Cloud workshop wrap-up OMI science team meeting, 21 June 2006

2 Agenda Presentations incl. questions: 9:00 –10:15 h PK Bhartia: Introduction Sasha Vassilkov: Comparisons of LER/MLER Cloud Pressures with a Model of Mie Scattering Plane-Parallel Cloud Maarten Sneep: Cloud algorithm choices: comparing OMCLDO2 and OMCLDRR Ping Wang: Effects of clouds on detection of tropospheric NO2 Bastiaan van Diedenhoven: Retrieval of cloud parameters from the 477 nm O4 band and UV measurements Nick Krotkov: Altitude resolved AMF in clouds Gordon Labow: INTEX-B data of cloud effect on total ozone Discussion: 10:15 – 10:45 h Conclusions/Recommendations: 10:45 – 11:00 h

3 Summary (1/3) The Mixed-LER cloud model with assumption A c =0.8 gives better Raman cloud retrievals than with assumption A c =0.4. A c =0.4: OMCLDRR STD A c =0.8: OMCLDRR for O3 (A c =0.8 is also used in O2-O2 and Fresco algor.) Comparison Raman – O2-O2 cloud products: - Effective cloud fractions c eff (for A c =0.8) correlate well (0.97), but there is an offset at small c eff, due to different surface albedo assumptions. - Cloud pressures correlate poorly (0.3-0.5) for small c eff, but much better (0.8-0.9) for large c eff. - The cloud pressure difference p O2-O2 - p Raman amounts to 100- 300 hPa, depending on c eff. - The O2-O2 cloud pressure is a consistent function of c eff.

4 Summary (2/3) Correct cloud height is essential for total ozone. But O2-O2 gives generally lower cloud height than Raman and the currently used THIR climatology. So which cloud height is better? Use INTEX-B aircraft validation campaign with ozone lidars. Also spectral radiation experiments are needed to analyse the RT at O3, O2-O2 and Raman wavelengths above, in, and below clouds. Validation of cloud heights with Calipso/Cloudsat.

5 Summary (3/3) For tropospheric NO2 retrieval, the effective cloud fraction is an essential input parameter; here the surface albedo database is an important ingredient, which should be improved in spatial resolution. The geometric cloud fraction can be obtained from combining O2-O2 with UV reflectance; could be used in future algorithm improvements. The altitude-resolved AMF for O3 and NO2 in cloudy scenes can be well approximated by the Mixed-LER model.


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