Chlorophyll Reprocessed¶
| Dataset Name | Sensor | Make | Spatial Resolution | Temporal Resolution | Start Date | End Date |
|---|---|---|---|---|---|---|
| Chlorophyll Reprocessed |  |
Observation | 25km X 25km | 8 Days | 1998-01-01 | 2018-06-26 |
Dataset Description¶
The Chlorophyll_REP dataset in CMAP is a global 25km X 25km 8 day averaged product, with a temporal coverage from 1998-01-01 through 2018-06-26. This product is a satellite derived chl_a estimate for the global ocean, provided by the Ocean Colour Thematic Center at the Copernicus Marine environment monitoring service ([CMEMS](http://marine.copernicus.eu/)) The dataset is generated from ESA and NASA satellite missions, specifically from SeaWiFS, MODIS-Squa, MERIS, VIIRSN and OLCI-S3A. This level 4 dataset was created by linking multiple satellite ocean color observations into a gridded space-time interpolated cloud free dataset. In-situ and multi-mission validation and QA details can be found on page 15 of the Ocean Colour Production Center [Quality Information Document](http://resources.marine.copernicus.eu/documents/QUID/CMEMS-OC-QUID-009-030-032-033-037-081-082-083-085-086-098.pdf).
In 2018, CMEMES adopted a re-processing of SeaWifs, MODIS-Aqua, VIIRS-N data. In addition to this, the chlorophyll retrieval algorithm was switched to the Hu/CI algorithm for oligotrophic waters and the OC5 algorithm for coastal areas. These algorithmic changes not only improve chlorophyll detection rates, but also bring CMEMS inline with other NASA Ocean Color product processing techniques. Details on the ocean color algorithms can be found [here](https://oceancolor.gsfc.nasa.gov/atbd/chlor_a/).
The CMEMS internal name for this dataset is: OCEANCOLOUR_GLO_CHL_L4_REP_OBSERVATIONS_009_082.
Table of Variables¶
How to Acknowledge¶
Data provided by: E.U. Copernicus Marine Service Information
Volpe, G., S. Colella, V. Forneris, C. Tronconi, and R. Santoleri: The Mediterranean Ocean Colour Observing System – system development and product validation. Ocean Sci., 8, 869–883, 2012.
Volpe, G., R. Santoleri, V. Vellucci, M. Ribera d’Alcala, S. Marullo and F. D’Ortenzio: The colour of the Mediterranean Sea: Global versus regional bio-optical algorithms evaluation and im- plication for satellite chlorophyll estimates, Remote Sens. Envi- ron., 107, 625–638, 2007
Berthon, J.-F., Zibordi, G.: Bio-optical relationships for the northern Adriatic Sea. Int. J. Remote Sens., 25, 1527-1532, 2004
Beckers, J. M. and Rixen, M.: EOF calculations and data filling from incomplete oceanographic datasets, J. Atmos. Ocean. Tech., 20, 1839–1856, 2003
Pitarch, J., Volpe, G., Colella, S., Krasemann, H., and Santoleri, R.: Remote sensing of chlorophyll in the Baltic Sea at basin scale from 1997 to 2012 using merged multi-sensor data, Ocean Sci., 12, 379-389, 10.5194/os-12-379-2016, 2016.
Volpe, G., Colella, S., Brando, V., Forneris, V., La Padula, F., Di Cicco, A., Sammartino, M., Bracaglia, M., Artuso, F., and Santoleri, R.: The Mediterranean Ocean Colour Level 3 Operational Multi-Sensor Processing, Ocean Sci. Discuss., https://doi.org/10.5194/os2018-73, in review, 2018
Di Cicco A, Sammartino M, Marullo S and Santoleri R (2017) Regional Empirical Algorithms for an Improved Identification of Phytoplankton Functional Types and Size Classes in the Mediterranean Sea Using Satellite Data. Front. Mar. Sci. 4:126. doi: 10.3389/fmars.2017.00126
Zibordi G., F. Mélin, J.-F. Berthon, and M. Talone, “In situ autonomous optical radiometry measurements for satellite ocean color validation in the western black sea,” Ocean Science, vol. 11, no. 2, pp. 275–286, 2015. [Online]. Available: https://www.ocean-sci.net/11/275/2015/
Kajiyama T., D. D’Alimonte, and G. Zibordi, “Algorithms merging for the determination of Chlorophyll-a concentration in the Black Sea,” IEEE Geoscience and Remote Sensing Letters, 2018. [Online]. Available: https://- www.doi.org/¬10.1109/¬LGRS.2018.2883539
Updates of Saulquin, B., Gohin, F., and Garrello, R. (2010) Regional Objective Analysis for Merging High-Resolution MERIS, MODIS/Aqua, and SeaWiFS Chlorophyll-a Data from 1998 to 2008 on the European Atlantic Shelf. IEEE Trans. Geosc. and Remote Sensing.
Maritorena, S., O. Hembise Fanton d’Andon, A. Mangin & D.A. Siegel. 2010. Merged Ocean Color Data Products Using a Bio-Optical Model: Characteristics, Benefits and Issues. Remote Sensing of Environment. Fanton d’Andon O.H., D. Antoine, A. Mangin, S. Maritorena, D. Durand, Y. Pradhan, S. Lavender, A. Morel, J. Demaria, G. Barrot (2008)
Morel, A., Huot, Y., Gentili, B., Werdell, P.J., Hooker, S.B. and B.A. Franz (2007). Examining the consistency of products derived from various ocean color sensors in open ocean (Case 1) waters in the perspective of a multi-sensor approach. Remote Sensing of Environment, 111, 69-88, doi:10.1016/j.rse.2007.03.012
Gohin, F.: Annual cycles of chlorophyll-a, non-algal suspended particulate matter, and turbidity observed from space and in-situ in coastal waters, Ocean Sci., 7, 705-732, doi:10.5194/os-7-705-2011, 2011.
Saulquin, B., Gohin, F, Odile Fanton d’Andon Interpolated fields of satellitederived multi-algorithm chlorophyll-a estimates at Global and European scales in the frame of the European Copernicus-Marine