GlobColour: A ten-year time series of global Ocean Colour Products
Odile Fanton d'Andon(1), Samantha Lavender(2,3), Antoine Mangin(1), David Antoine(4), Stephane Maritorena(5), Dominique Durand(6), André Morel(4), Gilbert Barrot(1), Julien Demaria(1), Kai Sorensen(7), Ralf Quast(8), Helge Witt(9), Christophe Lerebourg(1) and Simon Pinnock(10)
(1) ACRI-ST, 260 Route du Pin Montard, F-06904 Sophia Antipolis, France
(2) University of Plymouth, Portland Square A403, Drake Circus, Plymouth, Devon, PL4 8AA, United Kingdom
(3) ARGANS Limited, Tamar Science Park, 1 Davy Road, Derriford, Plymouth, Devon, PL6 8BX, United Kingdom
(4) Laboratoire d'Océanographie de Villefranche, Quai de La Darse, BP 8, 06238 Villefranche sur Mer Cedex, France
(5) University of California at Santa Barbara, 6841 Ellison Hall, Santa Barbara, CA 93106-3060, United States
(6) NIVA, Nordnesboder 5, PoBox 2026, N-5817 Bergen, Norwa, Norway
(7) NIVA, Gaustadalléen 21, NO-0349 OSLO, Norway
(8) Brockmann Consult, Max-Plank-Str 2, D-21502 Geesthacht, Germany
(9) DLR Remote Sensing Technology Inst, Rutherfordstr. 2, 12489 Berlin, Germany
(10) ESA, via Galileo Galilei, Casella Postale 64, 00044 Frascati, Italy
The GlobColour project has been initiated and funded by the ESA Data User Element Programme to develop a satellite based ocean colour data service to support global carbon-cycle research and operational oceanography. It aims to satisfy the scientific requirement for a long (10+ year) time-series of consistently calibrated global ocean colour information with the best possible spatial coverage. In order to cover the long time span necessary for climate monitoring purposes, the required ocean colour data set can only be built by merging together observations made with different satellite systems.
To that purpose, MERIS products are merged with MODIS and SeaWiFS and a Full Data Set (FPS) covering 10 years of observation is available to the scientific community (www.globcolour.info) and in particular to the key users of the project: IOCCP, IOCCG and UKMO. Prior to the delivery, a very thorough calibration and validation exercise covering the entire spatial and temporal extent of the data set has been performed.
This exercise provided a deep understanding of the different input data streams, and led to the prototyping of three different merging methods: simple averaging, error-weighted averaging and an advanced retrieval based on fitting an in-water bio-optical model to the merged set of observed normalised water-leaving radiances (nLw’s). This third technique is also being utilised by the NASA Ocean Color Time-Series Project, and is termed GSM because it originates from the Garver et al. (1997) bio-optical model (Maritorena & Siegel, 2005). Error statistics from the initial sensor characterisation are also used as an input to both the weighted averaging and GSM merging methods, and propagate through the merging process to provide error estimates on the output merged products. These error estimates are a key component of GlobColour as they are invaluable to the users; particularly the modellers who need them in order to assimilate the ocean colour data into their ocean simulations.
The service is distributing global data sets of chlorophyll-a concentration, normalised water-leaving radiances, diffuse attenuation coefficient, coloured dissolved and detrital organic materials, total suspended matter or particulate backscattering coefficient, turbidity index, cloud fraction and quality indicators. In the future this will feed into the Marine Core Services and utilise Sentinel-3.
Key steps, findings, achievements and long term vision of GlobColour will be presented at the 2nd MERIS-(A)ATSR workshop.
IOCCG Report No. 4, Guide to the creation and use of ocean-colour, Level-3, binned data products, D. Antoine (ed.), 2004. http://www.ioccg.org/reports_ioccg.html
IOCCG (2006). Ocean Colour Data Merging. Gregg, W.W. (ed.), Reports of the International Ocean-Colour Coordinating Group, No. 5, IOCCG.
Maritorena, S. and Siegel, D.A. 2005. Consistent Merging of Satellite Ocean Colour Data Sets Using a Bio-Optical Model. Remote Sensing of Environment, 94, 4, 429-440.
Keywords: ESA European
Space Agency - Agence spatiale europeenne,
observation de la terre, earth observation,
satellite remote sensing,
teledetection, geophysique, altimetrie, radar,
chimique atmospherique, geophysics, altimetry, radar,