Accession Number:

AD1099540

Title:

An Ocean-Colour Time Series for Use in Climate Studies: The Experience of the Ocean-Colour Climate Change Initiative (OC-CCI)

Descriptive Note:

Journal Article - Open Access

Corporate Author:

NAVAL RESEARCH LAB WASHINGTON DC WASHINGTON United States

Personal Author(s):

• Feldman,Gene
• Franz,Bryan A.
• Gould,Richard Jr W.
• Hooker,Stanford B.
• Werdell,Jeremy
• Calton,Ben
• Chuprin,Andrei
• Cipollini,Paolo
• Couto,Andre B.
• Dingle,James
• Doerffer,Roland
• Donlon,Craig
• Dowell,Mark
• Farman,Alex
• Grant,Mike
• Groom,Steve
• Horseman,Andrew
• Martinez-Vicente,Victor
• Mazeran,Constant
• Melin,Frederic

Report Date:

2019-10-03

Pagination or Media Count:

31.0

Abstract:

Ocean colour is recognised as an Essential Climate Variable ECV by the Global Climate Observing System GCOS and spectrally-resolved water-leaving radiances or remote-sensing reflectances in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales their role in marine biogeochemistry the global carbon cycle the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean-colour data is not a trivial task algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data

Descriptors:

• remote sensing
• optical properties
• reflectance
• algorithms
• phytoplankton
• satellite imaging
• chlorophylls
• absorption coefficients
• data sets
• image processing
• oceans
• ecosystems

Subject Categories:

• Biology
• Biological Oceanography

Distribution Statement:

APPROVED FOR PUBLIC RELEASE