Ramon d 1 and santer r 2 hygeos france lise universit du littoral france
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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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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

    • 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


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


LARS Reflectance for a biome

slope

Initial DDV

Domain

Seasonal

Initial DDV


Biomes


Biome transition on level 3


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


16 days period starting from julian day

r0(l1)

12'x12' box fit

goodness of fit


12' resolution, day 177, slope at 659 nm

Black: no fit

White: no good fit


12' resolution, day 177, albedo at 659 nm for ARVI=0.6

0.08

0


C443

1.5

0


C670

1.5

0


  • New RO_LARS LUTs from MODIS

  • Aerosol product: AOT_865 and alpha


Remaining issues?

  • See biome transitions on AOT_865

  • Lot of alpha out of range


Flags

Clouds(White); water (Black),LARS with good aerosol retrieval(Green);

Bad aerosol retrieval (Red) LARS in cloud vicinity(Blue)


AOT_865


RO_LARS_670

DDV albedo (red) corrected LARS albedo (magenta)


Rayleigh corrected reflectance above LARS at 443nm


Rayleigh corrected reflectance above LARS at 670 nm


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


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


Spatial & temporal binning (nov.)


Spatial & temporal binning (sept.)


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 !


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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