Frequently Asked Questions

Where to go for further information?

For a detailed description of the OC_CCI products please consult the Product User Guide (PUG) below (oc-cci-pug-v4.1.3.pdf).

There's also been a paper published: An Ocean-Colour Time Series for Use in Climate Studies: The Experience of the Ocean-Colour Climate Change Initiative (OC-CCI) https://www.mdpi.com/1424-8220/19/19/4285

If you encounter any difficulties and would like support then please email: help@esa-oceancolour-cci.org

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Version 4.2 Data Release

The latest version of the OC-CCI dataset is 4.2 that comprises of globally merged MERIS, Aqua-MODIS, SeaWiFS and VIIRS data with associated per-pixel uncertainty information, with the dataset extended to the end of 2019. This is an update of the version 4.0 and 4.1 products that had erroneous data within the Chlorophyll product (for v4.0):

The OC-CCI team noticed that the algorithm blending designed to optimise the chlorophyll-a product across a range of optical environments was corrupted in the operational code, with the consequence that the chlorophyll-a product released as part of OC-CCI v4.0 (released in June 2019) is based uniquely on the OC3 algorithm, rather than on blended algorithms. The chlorophyll-a product (and associated uncertainties) are the only products affected. We have now recomputed the chlorophyll-a product using the blending scheme and are releasing an updated v4.1 dataset. If you were using products such as Rrs, water class memberships or IOPs then the products remain unchanged, compared with v4.0.  Further details are available within http://esa-oceancolour-cci.org/sites/esa-oceancolour-cci.org/files/oc-cci_v4_diffs.pdf

and (for v4.1): Kd used value of bw instead of bbw

When using the OC-CCI data in publications please consider following our citing advice:  https://esa-oceancolour-cci.org/citing-oc-cci

Sinusoidal versus geographic products

The sinusoidal products are produced according to the NASA SeaWiFS binning algorithm (“Level-3 SeaWiFS Data Products: Spatial and Temporal Binning Algorithms" J.W. Campbell, J.M. Blasidell, and M. Darzi, NASA Technical Memorandum 104566, Vol.32.); unlike the original NASA format, all grid cells are retained and those with no valid data contain NetCDF fill values. These products are transformed into regular grid geographic products (8640 by 4320 pixels in size as a Plate Carrée projection), but this can result in Moiré effects i.e. pixels with missing data where the input and output spatial resolutions are similar.

The sinusoidal products should be used in preference, but it’s acknowledged that many software packages cannot deal with this format and need to resample the data to a geographic projection in order to display it.

The PUG provides detailed information on how to read the products and there is also the freely available ESA BEAM VISAT package http://www.brockmann-consult.de/cms/web/beam/

Problems reading the files in Linux ncdump and Matlab ncload

this could be because the OC Climate Change Initiative files are in a compressed version of NetCDF 4. Try reading the 3 examples given in the zip file below, which contains:

  • NetCDF version 3
  • NetCDF version 4
  • NetCDF version 4 with compression (the closest to our dataset)

If you can read the NetCDF 3, but not NetCDF 4 files then the ideal option is to have your machine updated to use the latest NetCDF libraries. If this isn’t possible then an alternative option is to download and build nccopy that can then be used to convert the files from NetCDF 4 to NetCDF 3; they will significantly increase in size as the internal NetCDF compression will no longer be available.

Depth of the satellite Chlorophyll-a concentration data

For satellite derived chlorophyll the depth it pertains to varies with the turbidity and hence is related to the concentration itself; the signal may return from depths as deep as 20+ m in the open ocean to as shallow as 1-2 m in highly productive waters. Also, the signal from the water closer to the surface will have a stronger influence than the signal from greater depths.

It is possible to use the diffuse attenuation coefficient to understand the penetration of light, which is often used when converting in-situ chlorophyll profiles into datasets suitable for satellite algorithm development and validation; e.g. see Sections 2.2.2 and 2.3.2 of http://oceancolor.gsfc.nasa.gov/MEETINGS/OCBAM/docs/werdell_and_bailey_2005_rse.pdf

Data processing in sunglint conditions

Elliptical data gaps within the daily SeaWiFS data.

OC-CCI-v1.0 and v2.0 include elliptical data gaps (also in the NASA daily SeaWiFS Level-3 products) because a HIGLINT flag is applied as a mask at Level-3, which was adopted because the POLYMER atmospheric correction is not currently used for SeaWiFS. The HIGLINT flag started to be used as a mask during the NASA Ocean Color Reprocessing 2009 so that SeaWiFS and MODIS Level-3 data are consistent. Therefore, the original GlobColour (http://www.globcolour.info/) dataset often does not have these gaps because at the time it was produced this flag was not applied as a mask at Level-3; the GlobColour GLOB_4KM/RAN dataset was originally generated in 2008. It has since been reprocessed (2nd reprocessing) and so now also has these gaps.

Processing under sunglint conditions.

POLYMER is capable of retrieving data under sun glint conditions, which substantially increases the spatial coverage of the MERIS retrieved data. However, in OC-CCI-v1.0 and v2.0, POLYMER was not used for the MODIS or SeaWiFS atmospheric correction, and so data gaps due to glint do occur for these sensors. POLYMER is described in the following document http://www.esa-oceancolour-cci.org/?q=webfm_send/179

Error characterisation

The user consultation carried out at the beginning of the Ocean Colour CCI project indicated an overwhelming preference for uncertainty characterisation based on comparison with in situ data. Each of the products, generated from a merged time series of ocean-colour data, has uncertainties (bias and Root Mean Square Difference) assigned to pixels based on the validation of each of the products against corresponding in situ observations. For further details please see the Uncertainty Characterisation Document (UCD) pdf below (oc_cci_-_ucd_-_v12.pdf).

In contrast, GlobColour products have pixel-by-pixel error bars based on a theoretical computation using a Look-Up-Table that uses the value of the variable and observation conditions or the output of the merging model. For further details consult the GlobColour Product User Guide at http://www.globcolour.info/CDR_Docs/GlobCOLOUR_PUG.pdf

Some OC_CCI observations don’t have a corresponding uncertainty.

This is because some pixels do not fit the currently pre-defined water classes, and thus OC-CCI-v1.0 and v2.0 don't currently have a computed uncertainty for them value; despite a product being produced. It’s expected this will be solved in the next data release.

What are the chlor_a_log10_rmsd and chlor_a_log10_bias values?

The Chlorophyll-a data were log transformed prior to the estimation of the uncertainty characteristics, using match-up in situ data, which means that the RMSD and bias are provided for log10(Chlorophyll).

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Ocean Colour CCI chlorophyll product compared to MyOcean and GlobColour

The OC-CCI-v2.0 chlorophyll product (units of mg/m^3) is derived from merged MODIS-Aqua, SeaWiFS and MERIS data; generated in 2015 with the current input dataset versions. The SeaWiFS and MODIS data was processed from Level 1 to 2 within the project, with the NASA standard processing (SeaDAS 7.0), and POLYMER was used for the MERIS atmospheric correction. Then the MODIS and MERIS data were band shifted to the six main SeaWiFS bands and a bias correction applied before merging, after which the OC4v6 chlorophyll algorithm was applied; within Phase 2 of the project a research focus includes improving the products within Case-2 waters.

The MyOcean REP (reprocessed) products use the OC-CCI-v1.0 4km bias-corrected/merged remote-sensing reflectance (Rrs, surface ratio of upwelling radiance emerging from seawater to downwelling radiative flux in air), which is resampled to 1km for the regional datasets and then has the OC4 or OC5 chlorophyll algorithms applied alongside Rrs being made available. See MyOcean Product User Manual http://catalogue.myocean.eu.org/static/resources/myocean/pum/MYO2-OC-PUM-009-ALL-V1.0.pdf

The GlobColour RAN (reanalysis) products are produced by ACRI-ST using the GlobColour processor that merges MODIS-Aqua, SeaWiFS and MERIS; the dataset was originally generated in 2008 and has since been reprocessed (2nd reprocessing). There are several chlorophyll products available:

  • CHL1 merged products that include:
    • GSM derived product based on merged Level 2 data, following the approach proposed by Maritorena and Siegel (2005, RSE);
    • OC4Me algorithm (an inter-calibration is applied to the MODIS-Aqua and SeaWiFS Level 2 chlorophyll products to get MERIS algorithm compatible inputs) with a weighted averaging merging (AVW) method then applied to merge the adjusted MODIS and SeaWiFS products with MERIS data – there is also a simple average (AV) single sensor OC4Me product;
  • CHL2 that’s the MERIS C2R Neural Network algorithm (only available for input MERIS data).

See GlobColour Product User Guide http://www.globcolour.info/CDR_Docs/GlobCOLOUR_PUG.pdf

Downloading and extracting data

Access to several options, including FTP and the Composite Browser, is available via http://www.oceancolour.org/

The data can be directly downloaded from: ftp://oc-cci-data:ELaiWai8ae@oceancolour.org/

FTP server: oceancolour.org
Username: oc-cci-data
Password: ELaiWai8ae

Support is available from help@esa-oceancolour-cci.org

Some people have reported that the Mac FTP client has trouble with files bigger than 4GB. If you look at the monthly composites directory and the files there appear to be around 500-600MB rather than ~4.5GB, you're affected by this problem. If you attempt to download, you'll get ~500MB corrupt files. So you'll need to use an alternative FTP client or the terminal.

If you’re interested in downloading a subset of the dataset then THREDDS provides several options. As an example, the NetCDF subset service allows for a spatial and / or temporal subset to be extracted.

From https://rsg.pml.ac.uk/thredds/catalog-cci.html first choose the temporal composites required (daily, 8day or monthly) and then access Option 5, which is NetcdfSubset. Now choose the products, Latitude / Longitude subset and time subset options. Then press Submit at the bottom of the page.

If you receive an error message then it’s likely you’re trying to download too much data in one block – files cannot be larger than 4GB. The Stride parameter can be set to a value greater than 1 if you only want every nth value.

The output is a single NetCDF file and so this method will become unwieldy for large areas / time periods.If you’d prefer binary or ASCII data then choose Option 1, which is OPeNDAP.

To browse the data in an interactive viewer then the Web GIS Portal (http://www.oceancolour.org/portal/) is an option that can produce plots / graphics of the data as well as also exporting layers. First select the product(s) that you’re interested in, then select ‘Analysis’ that should be in the top right hand corner and choose what you’d like to do.

Data beyond 2013 and the quality of MODIS-Aqua data in 2014

The version 2 dataset release extends the time series to the end of 2013 using just MODIS-Aqua from the end of MERIS onwards. However, the project has decided to omit the 2014 MODIS-Aqua data because of concerns over its quality, and hence ability to consider it within a climate quality dataset.

A recently presented figure (Bryan Franz, NASA) shows a sharp decline in the Chlorophyll-a values related to 2014 radiometry shifting (up in blue, down in green). The aim is for NASA to undertake a MODIS reprocessing, which would aim to correct for the decay, and so the OC-CCI project has decided to wait for that to occur.

Reading the products

The data can be directly read into BEAM (http://earth.esa.int/beam) or SeaDAS (http://seadas.gsfc.nasa.gov/) using the NetCDF-CF import option. Currently (April 2015) BEAM 5.0 will requires an update of the “Level-3 Binning Processor” modules before it is capable of reading the v2.0 sinusoidal product format.

You can also read the products into your favourite language, for example:

  • Python using “netCDF4” that’s available from http://code.google.com/p/netcdf4-python/ or using “pip install netCDF4”
  • R using “ncdf4”, which can be added to your R build using install.packages(‘ncdf4’) and added to your session using library(‘ncdf4’)
  • IDL using the NetCDF library, see the PUG (oc-cci-pug-v2.0.5-min.pdf) below for an example
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Citing OC-CCI information and data products when you use them

All OC-CCI products are free and open. However, we request all users to acknowledge the source of the data, whenever you publish any work based on them.

Acknowledgement:

Please include a general statement acknowledging OC-CCI data and/or assistance in the acknowledgement section of any article.

In addition, please cite the following references, as appropriate:

References:

The correct reference for OC-CCI products is:

Sathyendranath, S, Brewin, RJW, Brockmann, C, Brotas, V, Calton, B, Chuprin, A, Cipollini, P, Couto, AB, Dingle, J, Doerffer, R, Donlon, C, Dowell, M, Farman, A, Grant, M, Groom, S, Horseman, A, Jackson, T, Krasemann, H, Lavender, S, Martinez-Vicente, V, Mazeran, C, Mélin, F, Moore, TS, Müller, D, Regner, P, Roy, S, Steele, CJ, Steinmetz, F, Swinton, J, Taberner, M, Thompson, A, Valente, A, Zühlke, M, Brando, VE, Feng, H, Feldman, G, Franz, BA, Frouin, R, Gould, Jr., RW, Hooker, SB, Kahru, M, Kratzer, S, Mitchell, BG, Muller-Karger, F, Sosik, HM, Voss, KJ, Werdell, J, and Platt, T (2019) An ocean-colour time series for use in climate studies: the experience of the Ocean-Colour Climate Change Initiative (OC-CCI). Sensors: 19, 4285. doi:10.3390/s19194285

In addition, each of the versions of OC-CCI products have their own doi’s. Please provide reference to the appropriate doi’s:

Doi’s for OC-CCI Ocean-Colour products

Version 4.2:

Sathyendranath, S.; Jackson, T.; Brockmann, C.; Brotas, V.; Calton, B.; Chuprin, A.; Clements, O.; Cipollini, P.; Danne, O.; Dingle, J.; Donlon, C.; Grant, M.; Groom, S.; Krasemann, H.; Lavender, S.; Mazeran, C.; Mélin, F.; Moore, T.S.; Müller, D.; Regner, P.; Steinmetz, F.; Steele, C.; Swinton, J.; Valente, A.; Zühlke, M.; Feldman, G.; Franz, B.; Frouin, R.; Werdell, J.; Platt, T. (2020): ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global chlorophyll-a data products gridded on a sinusoidal projection, Version 4.2. Centre for Environmental Data Analysis, date of citation. https://catalogue.ceda.ac.uk/uuid/99348189bd33459cbd597a58c30d8d10

Version 3.1:

Sathyendranath, S.; Grant, M.; Brewin, R.J.W.; Brockmann, C.; Brotas, V.; Chuprin, A.; Doerffer, R.; Dowell, M.; Farman, A.; Groom, S.; Jackson, T.; Krasemann, H.; Lavender, S.; Martinez Vicente, V.; Mazeran, C.; Mélin, F.; Moore, T.S.; Müller, D.; Platt, T.; Regner, P.; Roy, S.; Steinmetz, F.; Swinton, J.; Valente, A.; Zühlke, M.; Antoine, D.; Arnone, R.; Balch, W.M.; Barker, K.; Barlow, R.; Bélanger, S.; Berthon, J.-F.; Beşiktepe, Ş.; Brando, V.E.; Canuti, E.; Chavez, F.; Claustre, H.; Crout, R.; Feldman, G.; Franz, B.; Frouin, R.; García-Soto, C.; Gibb, S.W.; Gould, R.; Hooker, S.; Kahru, M.; Klein, H.; Kratzer, S.; Loisel, H.; McKee, D.; Mitchell, B.G.; Moisan, T.; Muller-Karger, F.; O'Dowd, L.; Ondrusek, M.; Poulton, A.J.; Repecaud, M.; Smyth, T.; Sosik, H.M.; Taberner, M.; Twardowski, M.; Voss, K.; Werdell, J.; Wernand, M.; Zibordi, G. (2018): ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Version 3.1 Data. Centre for Environmental Data Analysis, 04 July 2018. doi:10.5285/9c334fbe6d424a708cf3c4cf0c6a53f5 http://dx.doi.org/10.5285/9c334fbe6d424a708cf3c4cf0c6a53f5


Version 2.0:

Sathyendranath, S, Groom, S, Grant, M, Brewin, RJW, Thompson, A, Chuprin, A, Horseman, A, Jackson, T, Martinez Vicente, V, Platt, T, Brockmann, C, Zühlke, M, Doerffer, R, Valente, A, Brotas, V, Krasemann, H, Müller, D, Dowell, M, Mélin, F, Swinton, J, Farman, A, Lavender, S, Moore, TS, Regner, P, Roy, S, Steinmetz, F, Mazeran, C, Brando, VE, Taberner, M, Antoine, D, Arnone, R, Balch, WM, Barker, K, Barlow, R, Bélanger, S, Berthon, J, Beşiktepe, Ş, Canuti, E, Chavez, F, Claustre, H, Crout, R, Frouin, R, García-Soto, C, Gibb, SW, Gould, R, Hooker, S, Kahru, M, Klein, H, Kratzer, S, Loisel, H, McKee, D, Mitchell, BG, Moisan, T, Feldman, G, Franz, B, Muller-Karger, F, O'Dowd, L, Ondrusek, M, Poulton, AJ, Repecaud, M, Smyth, T, Sosik, HM, Twardowski, M, Voss, K, Werdell, J, Wernand, M, Zibordi, G (2016) ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Version 2.0 Data. Centre for Environmental Data Analysis, 20 December 2016. doi:10.5285/b0d6b9c5-14ba-499f-87c9-66416cd9a1dc http://dx.doi.org/10.5285/b0d6b9c5-14ba-499f-87c9-66416cd9a1dc

Version 1.0:

Sathyendranath, S, Groom, S, Grant, M, Brewin, RJW, Thompson, A, Chuprin, A, Horseman, A, Jackson, T, Martinez Vicente, V, Platt, T, Brockmann, C, Zühlke, M, Doerffer, R, Valente, A, Brotas, V, Krasemann, H, Müller, D, Dowell, M, Mélin, F, Swinton, J, Farman, A, Lavender, S, Moore, TS, Regner, P, Roy, S, Steinmetz, F, Mazeran, C, Brando, VE, Taberner, M, Antoine, D, Arnone, R, Balch, WM, Barker, K, Barlow, R, Bélanger, S, Berthon, J, Beşiktepe, Ş, Canuti, E, Chavez, F, Claustre, H, Crout, R, Frouin, R, García-Soto, C, Gibb, SW, Gould, R, Hooker, S, Kahru, M, Klein, H, Kratzer, S, Loisel, H, McKee, D, Mitchell, BG, Moisan, T, Feldman, G, Franz, B, Muller-Karger, F, O'Dowd, L, Ondrusek, M, Poulton, AJ, Repecaud, M, Smyth, T, Sosik, HM, Twardowski, M, Voss, K, Werdell, J, Wernand, M, Zibordi, G (2016) ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Version 1.0 Data. Centre for Environmental Data Analysis, 20 December 2016. doi:10.5285/E32FEB53-5DB1-44BC-8A09-A6275BA99407. http://dx.doi.org/10.5285/E32FEB53-5DB1-44BC-8A09-A6275BA99407

OC-CCI in situ databases

Version 2:

Valente, A, Sathyendranath, S, Brotas, V, Groom, S, Grant, M, Taberner, M, Antoine, D, Arnone, R, Balch, WM, Barker, K Barlow, R, Bélanger, S, Berthon, J-F,  Besiktepe, S, Borsheim, Y, Bracher, A, Brando, V, Canuti, E, Chavez, F, Cianca, A, Claustre, H, Clementson, L, Crout, R, Frouin, R, García-Soto, C, Gibb, SW, Gould, R, Hooker, SB, Kahru, M, Kampel, M, Klein, H, Kratzer, S, Kudela, R, Ledesma, J, Loisel, H, Matrai, P, McKee, D, Mitchell, BG, Moisan, T, Muller-Karger, F, O’Dowd, L, Ondrusek, M, Platt, T, Poulton, AJ, Repecaud, M, Schroeder, T, Smyth, T, Smythe-Wright, D, Sosik, HM, Twardowski, M, Vellucci, V, Voss, K, Werdell, J, Wernand, M, Wright, S, and Zibordi, G (2019) A compilation of global bio-optical in situ data for ocean-colour satellite applications – version two. Earth Syst. Sci. Data, 11, 1037–1068. https://doi.org/10.5194/essd-11-1037-2019

Version 1:

Valente, A, Sathyendranath, S, Brotas, V, Groom, S, Grant, M, Taberner, M, Antoine, D, Arnone, R, Balch, W, Barker, K, Barlow, R, Bélanger, S, Berthon, JF, Besiktepe, S, Brando, V, Canuti, E, Chavez, F, Claustre, H, Crout, R, Frouin, R, Garcìa-Soto, C, Gibb, SW, Gould, R, Hooker, S, Kahru, M, Klein, H, Kratzer, S, Loisel, H, McKee, D, Mitchell, BG, Moisan, T, Muller-Karger, F., O'Dowd, L, Ondrusek, M, Poulton, A, Repecaud, M, Smyth, T, Sosik, HM, Twardowski, M, Voss, K, Werdell, J, Wernand, M, Zibordi, G (2016) A compilation of global bio-optical in situ data for ocean-colour satellite applications. Earth Syst. Sci. Data, 8, 235–252, 2016www.earth-syst-sci-data.net/8/235/2016/doi:10.5194/essd-8-235-2016