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Aerosol over land with MERIS, present and future

Ramon, D. 1 and Santer, R. 2 HYGEOS, France LISE, Université du Littoral, France. Aerosol over land with MERIS, present and future. Where did we start after Salzburg. MERIS level 2 products Reprocessing #2 after MAVT Workshop oct. 2003 recommendations

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Aerosol over land with MERIS, present and future

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  1. Ramon, D.1 and Santer, R.2 HYGEOS, France LISE, Université du Littoral, France Aerosol over land with MERIS, present and future

  2. Where did we start after Salzburg • MERIS level 2 products • Reprocessing #2 after MAVT Workshop oct. 2003 recommendations • Increase aerosol model number (Angstrom coeff. from 0 to 2.5 by step of 0.1) • Extend the aerosol product spatial cover • From Dense Dark Vegetation to Land Aerosol Remote Sensing target

  3. LARS concept • Surface reflectance varies linearly with some spectral index, here ARVI 100x100 RR around Alta Floresta DARVI=0 DARVI=-0.2 DARVI=-0.5

  4. LARS Reflectance for a biome slope Initial DDV Domain Seasonal Initial DDV

  5. Biomes

  6. Biome transition on level 3

  7. Spatially Complete Global Surface Albedos Derived from Terra/MODIS Data • Operational MODIS surface albedo data product (MOD43B3/MCD43B3) • 0.47, 0.56, 0.67, 0.86, 1.24, 1.64, 2.1 µm , 0.3-5.0, 0.7-5.0, 0.3-0.7 µm • 1 km spatial resolution (sinusoidal projection stored as 10° x 10° tiles) • 16-day periodicity (001, 017, …, 353) Michael D. King1, Eric G. Moody1,2, Steven Platnick1, and Crystal Schaaf3 1NASA Goddard Space Flight Center 2L3-Communications GSI 3Boston University

  8. 16 days period starting from julian day r0(l1) 12'x12' box fit goodness of fit

  9. 12' resolution, day 177, slope at 659 nm Black: no fit White: no good fit

  10. 12' resolution, day 177, albedo at 659 nm for ARVI=0.6 0.08 0

  11. C443 1.5 0

  12. C670 1.5 0

  13. New RO_LARS LUTs from MODIS • Aerosol product: AOT_865 and alpha

  14. Remaining issues? • See biome transitions on AOT_865 • Lot of alpha out of range

  15. Flags Clouds(White); water (Black),LARS with good aerosol retrieval(Green); Bad aerosol retrieval (Red) LARS in cloud vicinity(Blue)

  16. AOT_865

  17. RO_LARS_670 DDV albedo (red) corrected LARS albedo (magenta)

  18. Rayleigh corrected reflectance above LARS at 443nm

  19. Rayleigh corrected reflectance above LARS at 670 nm

  20. What aerosol product? RO_AER_440 is correct but improvements are possible RO_AER_670 is questionable Laerosol _440 is OK AOT_440 instead of AOT_865 (no compromise at 670 nm) What about a and the associated Junge size distribution

  21. The 3 possible algorithms • Simultaneous retrieval of AOT and alpha • AOT for model no 36 (a=1) • Use AOT for model no 36 as back up only

  22. Spatial & temporal binning (nov.)

  23. Spatial & temporal binning (sept.)

  24. Conclusion • Separate AOT retrieval and alpha retrieval • Coherence with AOT over water • No real biome transition found, but need to consolidate with L3 • Better cloud rejection at level 2 is mandatory • Less problem with a better surface albedo map !

  25. What next? • How to make a good surface albedo map for dark pixels? • Utility of a level 2 aerosol product? • On a pixel by pixel basis? • A daily level 3 which is not a simple bining • Utility of a daily level 3 aerosol product? • Validation • Atmospheric correction • Upper level

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