Chlorophyll algorithms for ocean color sensors - OC4, OC5 & OC6.
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O'Reilly, John E.
Werdell, P. Jeremy
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A high degree of consistency and comparability among chlorophyll algorithms is necessary to meet the goals of merging data from concurrent overlapping ocean color missions for increased coverage of the global ocean and to extend existing time series to encompass data from recently launched missions and those planned for the near future, such as PACE, OLCI, HawkEye, EnMAP and SABIA-MAR. To accomplish these goals, we developed 65 empirical ocean color (OC) chlorophyll algorithms for 25 satellite instruments using the largest available and most globally representative database of coincident in situ chlorophyll a and remote sensing reflectances. Excellent internal consistency was achieved across these OC ‘Version -7’ algorithms, as demonstrated by a median regression slope and coefficient of determination (R2) of 0.985 and 0.859, respectively, among 903 pairwise comparisons of OC-modeled chlorophyll. SeaWiFS and MODIS-Aqua satellite-to-in situ match-up results indicated equivalent.....
JournalRemote Sensing of Environment
Sustainable Development Goals (SDG)14.A
Essential Ocean Variables (EOV)Ocean colour
Maturity LevelTRL 8 Actual system completed and "mission qualified" through test and demonstration in an operational environment (ground or space)
Best Practice TypeManual (incl. handbook, guide, cookbook etc)
CitationO'Reilly, J.E. and Werdell, P.J. (2019) Chlorophyll algorithms for ocean color sensors - OC4, OC5 & OC6. Remote Sensing of Environment, 229, pp.32-47. DOI: https://doi.org/10.1016/j.rse.2019.04.021.
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