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Dataset Title:  Chlorophyll a concentration, ESA OC CCI - 8-Day, 1997-2021. v5.0 Subscribe RSS
Institution:  Plymouth Marine Laboratory   (Dataset ID: esa-cci-chla-8d-v5-0)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form
 
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Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 8.733312e+8, 1.6405632e+9;
    String axis "T";
    String ioos_category "Time";
    String long_name "Time";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range -89.97916666666666, 89.97916666666667;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
    Float64 valid_max 89.97916666666667;
    Float64 valid_min -89.97916666666666;
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range 0.020833333333314386, 359.97916666666663;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
    Float64 valid_max 359.97918701171875;
    Float64 valid_min 0.020829999819397926;
  }
  chlor_a {
    Float32 _FillValue NaN;
    String ancillary_variables "chlor_a_log10_rmsd chlor_a_log10_bias";
    Float64 colorBarMaximum 30.0;
    Float64 colorBarMinimum 0.03;
    String colorBarScale "Log";
    String grid_mapping "crs";
    String ioos_category "Ocean Color";
    String long_name "Chlorophyll-a concentration in seawater (not log-transformed), generated by as a blended combination of OCI, OCI2, OC2 and OCx algorithms, depending on water class memberships";
    String parameter_vocab_uri "http://vocab.ndg.nerc.ac.uk/term/P011/current/CHLTVOLU";
    String standard_name "mass_concentration_of_chlorophyll_a_in_sea_water";
    String units "mg m-3";
    String units_nonstandard "mg m^-3";
  }
  MERIS_nobs_sum {
    Float32 _FillValue NaN;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Statistics";
    String long_name "Count of the number of observations from the MERIS sensor contributing to this bin cell";
    Int32 number_of_files_composited 5;
  }
  MODISA_nobs_sum {
    Float32 _FillValue NaN;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Statistics";
    String long_name "Count of the number of observations from the MODIS (Aqua) sensor contributing to this bin cell";
    Int32 number_of_files_composited 5;
  }
  OLCI_nobs_sum {
    Float32 _FillValue NaN;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Statistics";
    String long_name "Count of the number of observations from the OLCI sensor contributing to this bin cell";
    Int32 number_of_files_composited 5;
  }
  SeaWiFS_nobs_sum {
    Float32 _FillValue NaN;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Statistics";
    String long_name "Count of the number of observations from the SeaWiFS (GAC and LAC) sensor contributing to this bin cell";
    Int32 number_of_files_composited 5;
  }
  VIIRS_nobs_sum {
    Float32 _FillValue NaN;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Statistics";
    String long_name "Count of the number of observations from the VIIRS sensor contributing to this bin cell";
    Int32 number_of_files_composited 5;
  }
  chlor_a_log10_bias {
    Float32 _FillValue NaN;
    Float64 colorBarMaximum 0.1;
    Float64 colorBarMinimum -0.1;
    String comment "Uncertainty lookups derived from file: /data/datasets/CCI/v5.0-production/stage09b-uncertainty_tables/chlor_a/cci_chla_bias.dat";
    String grid_mapping "crs";
    String ioos_category "Statistics";
    String long_name "Bias of log10-transformed chlorophyll-a concentration in seawater.";
    String ref "https://esa-oceancolour-cci.org/?q=webfm_send/581";
    String rel "uncertainty";
  }
  chlor_a_log10_rmsd {
    Float32 _FillValue NaN;
    Float64 colorBarMaximum 0.002;
    Float64 colorBarMinimum 0.0;
    String comment "Uncertainty lookups derived from file: /data/datasets/CCI/v5.0-production/stage09b-uncertainty_tables/chlor_a/cci_chla_rmsd.dat";
    String grid_mapping "crs";
    String ioos_category "Statistics";
    String long_name "Root-mean-square-difference of log10-transformed chlorophyll-a concentration in seawater.";
    String ref "https://esa-oceancolour-cci.org/?q=webfm_send/581";
    String rel "uncertainty";
  }
  total_nobs_sum {
    Float32 _FillValue NaN;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Statistics";
    String long_name "Count of the total number of observations contributing to this bin cell";
    Int32 number_of_files_composited 5;
  }
  NC_GLOBAL {
    String _NCProperties "version=1|netcdflibversion=4.4.1.1|hdf5libversion=1.8.20";
    String cdm_data_type "Grid";
    String comment "See summary attribute";
    String Conventions "CF-1.7, COARDS, ACDD-1.3";
    String creation_date "Sun Jan 30 23:33:17 2022";
    String creator_email "help@esa-oceancolour-cci.org";
    String creator_name "Plymouth Marine Laboratory";
    String creator_url "https://esa-oceancolour-cci.org";
    String date_created "2022-01-30T23:33:17Z";
    Float64 Easternmost_Easting 359.97916666666663;
    Float64 geospatial_lat_max 89.97916666666667;
    Float64 geospatial_lat_min -89.97916666666666;
    Float64 geospatial_lat_resolution 0.041666666666666664;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 359.97916666666663;
    Float64 geospatial_lon_min 0.020833333333314386;
    Float64 geospatial_lon_resolution 0.041666666666666664;
    String geospatial_lon_units "degrees_east";
    String git_commit_hash "3fe7e05a781af95661c77063a71600c45ea7ca65";
    String history 
"Thu Feb  3 09:07:07 2022: ncatted -O -a geospatial_lon_max,global,o,f,360.0 ESACCI-OC-L3S-CHLOR_A-MERGED-8D_DAILY_4km_GEO_PML_OCx-20211227-fv5.0-0-360.nc
Thu Feb  3 09:07:07 2022: ncatted -O -a geospatial_lon_min,global,o,f,0.0 ESACCI-OC-L3S-CHLOR_A-MERGED-8D_DAILY_4km_GEO_PML_OCx-20211227-fv5.0-0-360.nc
Thu Feb  3 09:07:07 2022: ncatted -O -a valid_max,lon,o,f,359.9792 ESACCI-OC-L3S-CHLOR_A-MERGED-8D_DAILY_4km_GEO_PML_OCx-20211227-fv5.0-0-360.nc
Thu Feb  3 09:07:07 2022: ncatted -O -a valid_min,lon,o,f,0.02083 ESACCI-OC-L3S-CHLOR_A-MERGED-8D_DAILY_4km_GEO_PML_OCx-20211227-fv5.0-0-360.nc
Thu Feb  3 09:06:51 2022: ncap2 -O -s where(lon<0) lon=lon+360 ESACCI-OC-L3S-CHLOR_A-MERGED-8D_DAILY_4km_GEO_PML_OCx-20211227-fv5.0-0-360.nc ESACCI-OC-L3S-CHLOR_A-MERGED-8D_DAILY_4km_GEO_PML_OCx-20211227-fv5.0-0-360.nc
Thu Feb  3 09:06:33 2022: ncks -O --msa_usr_rdr -d lon,0.0,180.0 -d lon,-180.0,0.0 ESACCI-OC-L3S-CHLOR_A-MERGED-8D_DAILY_4km_GEO_PML_OCx-20211227-fv5.0.nc ESACCI-OC-L3S-CHLOR_A-MERGED-8D_DAILY_4km_GEO_PML_OCx-20211227-fv5.0-0-360.nc
Source data were: ESACCI-OC-L3S-OC_PRODUCTS-MERGED-1D_DAILY_4km_GEO_PML_OCx_QAA-20211227-fv5.0.nc, ESACCI-OC-L3S-OC_PRODUCTS-MERGED-1D_DAILY_4km_GEO_PML_OCx_QAA-20211228-fv5.0.nc, ESACCI-OC-L3S-OC_PRODUCTS-MERGED-1D_DAILY_4km_GEO_PML_OCx_QAA-20211229-fv5.0.nc, ESACCI-OC-L3S-OC_PRODUCTS-MERGED-1D_DAILY_4km_GEO_PML_OCx_QAA-20211230-fv5.0.nc, ESACCI-OC-L3S-OC_PRODUCTS-MERGED-1D_DAILY_4km_GEO_PML_OCx_QAA-20211231-fv5.0.nc; netcdf_compositor_cci composites  Rrs_412, Rrs_443, Rrs_490, Rrs_510, Rrs_560, Rrs_665, water_class1, water_class2, water_class3, water_class4, water_class5, water_class6, water_class7, water_class8, water_class9, water_class10, water_class11, water_class12, water_class13, water_class14, atot_412, atot_443, atot_490, atot_510, atot_560, atot_665, aph_412, aph_443, aph_490, aph_510, aph_560, aph_665, adg_412, adg_443, adg_490, adg_510, adg_560, adg_665, bbp_412, bbp_443, bbp_490, bbp_510, bbp_560, bbp_665, chlor_a, kd_490, Rrs_412_bias, Rrs_443_bias, Rrs_490_bias, Rrs_510_bias, Rrs_560_bias, Rrs_665_bias, chlor_a_log10_bias, aph_412_bias, aph_443_bias, aph_490_bias, aph_510_bias, aph_560_bias, aph_665_bias, adg_412_bias, adg_443_bias, adg_490_bias, adg_510_bias, adg_560_bias, adg_665_bias, kd_490_bias with --mean,  Rrs_412_rmsd, Rrs_443_rmsd, Rrs_490_rmsd, Rrs_510_rmsd, Rrs_560_rmsd, Rrs_665_rmsd, chlor_a_log10_rmsd, aph_412_rmsd, aph_443_rmsd, aph_490_rmsd, aph_510_rmsd, aph_560_rmsd, aph_665_rmsd, adg_412_rmsd, adg_443_rmsd, adg_490_rmsd, adg_510_rmsd, adg_560_rmsd, adg_665_rmsd, kd_490_rmsd with --root-mean-square, and  MODISA_nobs, VIIRS_nobs, OLCI_nobs, MERIS_nobs, SeaWiFS_nobs, total_nobs - with --total
1643586478 Subsetted from standardised_geo/ESACCI-OC-L3S-OC_PRODUCTS-MERGED-8D_DAILY_4km_GEO_PML_OCx_QAA-20211227-fv5.0.nc to only include variables MERIS_nobs_sum,MODISA_nobs_sum,OLCI_nobs_sum,SeaWiFS_nobs_sum,VIIRS_nobs_sum,chlor_a,chlor_a_log10_bias,chlor_a_log10_rmsd,crs,lat,lon,time,total_nobs_sum
2022-06-30T22:46:33Z (local files)
2022-06-30T22:46:33Z https://oceanwatch.pifsc.noaa.gov/griddap/esa-cci-chla-8d-v5-0.das";
    String id "ESACCI-OC-L3S-CHLOR_A-MERGED-8D_DAILY_4km_GEO_PML_OCx-20211227-fv5.0.nc";
    String infoUrl "https://esa-oceancolour-cci.org/";
    String institution "Plymouth Marine Laboratory";
    String keywords "algorithms, aqua, area, array, array-data, bias, bin, blended, cci, cell, chemistry, chlor_a, chlor_a_log10_bias, chlor_a_log10_rmsd, chlorophyll, chlorophyll-a, class, color, colour, combination, comprehensive, concentration, contributing, count, coverage, data, depending, difference, earth, Earth Science > Oceans > Ocean Chemistry > Chlorophyll, esa, field, field-of-view, gac, generated, global, imager, imager/radiometer, imaging, infrared, laboratory, lac, large, local, log, log-transformed, log10, log10-transformed, marine, mass, mass_concentration_of_chlorophyll_a_in_sea_water, mean, memberships, meris, MERIS_nobs_sum, moderate, modis, MODISA_nobs_sum, not, number, observation, observations, oc2, ocean, ocean color, ocean colour, oceans, oci, oci2, ocx, olci, OLCI_nobs_sum, plymouth, product, radiometer, resolution, root, root-mean-square-difference, satellite, science, sea, sea-wide, seawater, seawifs, SeaWiFS_nobs_sum, sensor, spectroradiometer, square, statistics, stewardship, suite, system, time, total, total_nobs_sum, transformed, view, viirs, VIIRS_nobs_sum, visible, water, wide";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "ESA CCI Data Policy: free and open access.  When referencing, please use: Ocean Colour Climate Change Initiative dataset, Version <Version Number>, European Space Agency, available online at https://esa-oceancolour-cci.org.  We would also appreciate being notified of publications so that we can list them on the project website at https://esa-oceancolour-cci.org/?q=publications";
    String naming_authority "uk.ac.pml";
    String NCO "netCDF Operators version 4.7.5 (Homepage = http://nco.sf.net, Code = https://github.com/nco/nco)";
    Int32 nco_openmp_thread_number 1;
    String netcdf_file_type "NETCDF4_CLASSIC";
    Float64 Northernmost_Northing 89.97916666666667;
    String number_of_bands_used_to_classify "4";
    Int32 number_of_files_composited 5;
    String number_of_optical_water_types "14";
    String platform "Orbview-2,Aqua,Envisat,Suomi-NPP, Sentinel-3a";
    String processing_level "Level-3";
    String product_version "5.0";
    String project "Climate Change Initiative - European Space Agency";
    String references "https://esa-oceancolour-cci.org/";
    String sensor "SeaWiFS,MODIS,MERIS,VIIRS,OLCI";
    String sensors_present "MODISA OLCIa VIIRSN";
    String source "NASA SeaWiFS  L1A and L2 R2018.0 LAC and GAC, MODIS-Aqua L1A and L2 R2018.0, MERIS L1B 3rd reprocessing inc OCL corrections, NASA VIIRS L1A and L2 R2018.0, OLCI L1B";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -89.97916666666666;
    String spatial_resolution "4km nominal at equator";
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Data products generated by the Ocean Colour component of the European Space Agency Climate Change Initiative project. These files are 8 day composites of merged sensor (MERIS, Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua, Sea-Wide Field-of-View Sensor (SeaWiFS) Local Area Coverage (LAC) & Global Area Coverage (GAC), Visible and Infrared Imager/Radiometer Suite (VIIRS), OLCI) products.  MODIS Aqua and SeaWiFS were band-shifted and bias-corrected to MERIS bands and values using a temporally and spatially varying scheme based on the overlap years of 2003-2007.  VIIRS was band-shifted and bias-corrected in a second stage against the MODIS Rrs that had already been corrected to MERIS levels, for the overlap period 2012-2013; and at the third stage OLCI was bias corrected against already corrected MODIS, for overlap period 2016-07-01 to 2019-06-30.  VIIRS, MODIS, SeaWiFS and MERIS Rrs were derived from a combination of NASA's l2gen (for basic sensor geometry corrections, etc) and HYGEOS Polymer v4.12 (for atmospheric correction). OLCI Rrs were sourced at L1b (already geometrically corrected) and processed with polymer.  The Rrs were binned to a sinusoidal 4km level-3 grid, and later to 4km geographic projection, by Brockmann Consult's SNAP.  Derived products were generally computed with the standard algorithmsthrough SeaDAS.  QAA IOPs were derived using the standard SeaDAS algorithm but with a modified backscattering table to match that used in the bandshifting.  The final chlorophyll is a combination of OCI, OCI2, OC2 and OCx, depending on the water class memberships.  Uncertainty estimates were added using the fuzzy water classifier and uncertainty estimation algorithm of Tim Moore as documented in Jackson et al (2017). and updated accorsing to Jackson et al. (in prep).";
    String time_coverage_duration "P8D";
    String time_coverage_end "2021-12-27T00:00:00Z";
    String time_coverage_resolution "P8D";
    String time_coverage_start "1997-09-04T00:00:00Z";
    String title "Chlorophyll a concentration, ESA OC CCI - 8-Day, 1997-2021. v5.0";
    String tracking_id "3849ce0e-b92d-4ecb-8465-9bf9a9f885a7";
    Float64 Westernmost_Easting 0.020833333333314386;
  }
}

 

Using griddap to Request Data and Graphs from Gridded Datasets

griddap lets you request a data subset, graph, or map from a gridded dataset (for example, sea surface temperature data from a satellite), via a specially formed URL. griddap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its projection constraints (external link).

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

griddap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/griddap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/griddap/jplMURSST41.htmlTable?analysed_sst[(2015-06-09T09:00:00Z)][(-89.99):1000:(89.99)][(-179.99):1000:(180.0)]
Thus, the query is often a data variable name (e.g., analysed_sst), followed by [(start):stride:(stop)] (or a shorter variation of that) for each of the variable's dimensions (for example, [time][latitude][longitude]).

For details, see the griddap Documentation.


 
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