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A near-term (next reprocessing) end-user perspective…

A near-term (next reprocessing) end-user perspective…. A near-term (next reprocessing) end-user perspective…. Near-term products : atot, aphy, adg, bbp, Chl atot is most accurate (essentially sum of aphy and adg, can be done by end-user)

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A near-term (next reprocessing) end-user perspective…

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  1. A near-term (next reprocessing) end-user perspective…

  2. A near-term (next reprocessing) end-user perspective… • Near-term products: atot, aphy, adg, bbp, Chl • atot is most accurate (essentially sum of aphy and adg, can be done by end-user) • aphy, adg, bbp are good for intercomparison with other methods, and in situ data, they provide information on the environment • Chl… just because • Approach: they give the same thing • Easiest for implementation is the simultaneous inversion (GSM-type) • As a consequence, only 1 wavelength is necessary per data product because of prescribed spectral shapes • Uncertainties: for near-term, Globcolor technique • Encompasses all types of errors • Documentation: must come with ATBD

  3. Longer term • Products • Let’s make sure we have a good validation (in situ or match ups) of any new products before making them “operational” • Let’s not lead end-users astray (they can use l2gen or l3gen to get whatever they want anyway). • Uncertainties • Clear need to compare Globecolor vs Wang-Boss approach on selected datasets • We can build piece by piece “the best algorithm”

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