Campaign: The European Service for Ocean Colour (GlobColour) is an ESA Data User Element Project (http://www.globcolour.info/). GlobColour aims to satisfy the scientific requirement for a long time-series (since 1997) of consistently calibrated global ocean color information with the best possible spatial coverage.
Ocean color is an "essential climate variable" needed to support the carbon cycle monitoring requirements of the UNFCCC (United Nations Framework Convention on Climate Change). In order to cover the long time span necessary for climate monitoring purposes, the required ocean color data set can only be built by merging together observations made with different satellite systems (SeaWiFS, MODIS and MERIS).
The GlobColour service distributes global data sets of chlorophyll concentration, water leaving radiances, diffuse attenuation coefficient, coloured dissolved and detrital organic materials, total suspended matter or particulate backscattering coefficient, turbidity index, cloud fraction, quality indicators. Distribution of other products is upcoming (e.g., transparency, heated marine layer), or considered. The global Earth domain is covered with focus on local DDS areas (Diagnostic Data Sets areas) for qualification and validation purpose.
The products are generated on a daily, weekly (8-day), and monthly basis, on a Grid/Projection of 4.63 km equal area bins on an integerised sinusoidal grid. The GlobColour products have undergone an extensive validation based on a validation protocol derived from the SIMBIOS protocol. The GlobColour products have been derived with the GSM model and algorithm, developed by ICESS (Maritorena S. and D.A. Siegel. 2005).
Local copy of part of ESA data of GlobColour project for internal KlimaCampus use: product chlorophyll-a, weighted, monthly means in 1 degree (index 100) and 0.25 degree (index 25) resolutions.
The GlobColour service distributes global daily, 8-day and monthly data sets at 4.6 km resolution for, chlorophyll-a concentration, normalised water-leaving radiances (412, 443, 490, 510, 531, 555 and 620 nm, 670, 681 and 709 nm), diffuse attenuation coefficient, coloured dissolved and detrital organic materials, total suspended matter or particulate backscattering coefficient, turbidity index, cloud fraction and quality indicators. Error statistics from the initial sensor characterisation are used as an input to the merging methods and propagate through the merging process to provide error estimates for 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 ocean simulations. See the Product User Guide (PUG) for further details on the GlobColour products: http://www.globcolour.info/CDR_Docs/GlobCOLOUR_PUG.pdf .
CHL1 is the chlorophyll-a concentration (mg/m3) for case 1 water. As this concentration is computed using a different formulation for each instrument (MERIS, MODIS and SeaWiFS), the quantities read from the level 2 products are intrinsically different. Seceral PPS products are generated, using different averaging formulations starting from single-instument chlorophyll-a concentrations and using the GSM model.
As consistent as the sensors are (SeaWiFS, MODIS and MERIS). In terms of chlorophyll-a (Chl), the statistics for the GSM Chl are a little better than ...
Description
As consistent as the sensors are (SeaWiFS, MODIS and MERIS). In terms of chlorophyll-a (Chl), the statistics for the GSM Chl are a little better than those for the product from the weighted average. The time series of the chlorophyll anomalies, however, are closer to previously published data sets (i.e., Behrenfeld et al, 2006) for the weighted average chlorophyll. The merged product has not degraded the situation as compared to each of the 3 single-sensors' data set. Further information: http://www.globcolour.info/validation/report/GlobCOLOUR_FVR_v1.1.pdf .
[1] DOIMaritorena, Stéphane; Siegel, David A. (2005). Consistent merging of satellite ocean color data sets using a bio-optical model. doi:10.1016/j.rse.2004.08.014