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Dataset Title:	Northwest Atlantic per-pixel spring bloom metrics derived from OC-CCI POLY4 satellite Chlorophyll-a, 1998-present
Institution:	dfo_bio (Dataset ID: bio_remote_sensing_occci_nwa_poly4_spring_bloom)
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| Data Access Form \| Files

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Graph Type:
X Axis:
Y Axis:
Color:

Dimensions

Start

Stop

time (UTC)

specify just 1 value →

latitude (degrees_north)

longitude (degrees_east)

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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:

Web page authors can embed a graph of the latest data in a web page using HTML <img> tags.
Anyone can use ERDDAPs Slide Sorter to build a personal web page that displays graphs with the latest data (or other images or HTML content), each in its own, draggable slide.

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 8.836128e+8, 1.7040672e+9;
    String axis "T";
    String calendar "standard";
    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 39.020833333333336, 65.97916666666667;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range -75.97916666666667, -42.020833333333336;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  t_start {
    Float32 _FillValue NaN;
    Float64 colorBarMaximum 200.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Ocean Color";
    String long_name "Day of year of the start of the spring phytoplankton bloom";
    Float32 valid_max 176.0;
    Float32 valid_min 1.0;
  }
  t_duration {
    Float32 _FillValue NaN;
    Float64 colorBarMaximum 250.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Ocean Color";
    String long_name "Duration of the spring phytoplankton bloom";
    String units "days";
    Float32 valid_max 220.0;
    Float32 valid_min 1.0;
  }
  amplitude_real {
    Float32 _FillValue NaN;
    Float64 colorBarMaximum 150.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Ocean Color";
    String long_name "Maximum concentration during the spring phytoplankton bloom period";
    String units "mg/m3";
    Float32 valid_max 100.0;
    Float32 valid_min 0.0;
  }
  magnitude_real {
    Float32 _FillValue NaN;
    Float64 colorBarMaximum 30.0;
    Float64 colorBarMinimum 0.03;
    String colorBarScale "Log";
    String ioos_category "Ocean Color";
    String long_name "Total chlorophyll-a produced during the spring phytoplankton bloom period";
    String units "days*mg/m3";
    Float32 valid_max 22000.0;
    Float32 valid_min 0.0;
  }
  annual_mean {
    Float32 _FillValue NaN;
    Float64 colorBarMaximum 30.0;
    Float64 colorBarMinimum 0.03;
    String colorBarScale "Log";
    String ioos_category "Ocean Color";
    String long_name "Average chlorophyll-a over the year";
    String standard_name "mass_concentration_of_chlorophyll_a_in_sea_water";
    String units "mg/m3";
    Float32 valid_max 100.0;
    Float32 valid_min 0.0;
  }
  NRMSE_bloom {
    Float32 _FillValue NaN;
    Float64 colorBarMaximum 0.1;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Ocean Color";
    String long_name "Root mean square error between the fitted Gaussian and real chl-a values during the bloom period, normalized to amplitude_real";
    String units "mg/m3";
    Float32 valid_max 1.0;
    Float32 valid_min 0.0;
  }
  percent_dineof {
    Float32 _FillValue NaN;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Ocean Color";
    String long_name "Percentage of days with pixel values estimated using DINEOF";
    Float32 valid_max 100.0;
    Float32 valid_min 0.0;
  }
  NC_GLOBAL {
    String cdm_data_type "Grid";
    String Conventions "CF-1.10, COARDS, ACDD-1.3";
    String creator_email "Stephanie.Clay@dfo-mpo.gc.ca";
    String creator_group "SOPhyE (Satellite Ocean colour and Phytoplankton Ecology group), Ocean Monitoring and Modelling Section";
    String creator_name "Stephanie Clay";
    String creator_type "person";
    String creator_url "https://bio-rsg.github.io/";
    String date_created "2025-08-31T11:52:23Z";
    Float64 Easternmost_Easting -42.020833333333336;
    String geographic_crs_epsg_code "EPSG:4326";
    Float64 geospatial_lat_max 65.97916666666667;
    Float64 geospatial_lat_min 39.020833333333336;
    Float64 geospatial_lat_resolution 0.04166666666666667;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -42.020833333333336;
    Float64 geospatial_lon_min -75.97916666666667;
    Float64 geospatial_lon_resolution 0.04166666666666667;
    String geospatial_lon_units "degrees_east";
    String history 
"Created with map_and_write_to_netcdf.R. Input data were 4km-resolution spring bloom metrics and annual average chlorophyll-a (chl-a) concentration per bin. Bloom metrics for each bin and year were derived from a shifted gaussian curve fitted to the time series of daily logged chl-a data within that bin. Chl-a data were taken from the POLY4 chl-a dataset which was generated using remote sensing reflectances (Rrs) from the OC-CCI multisensor product (www.oceancolour.org) and regionally-tuned coefficients, and subsequently gap-filled using DINEOF (https://github.com/aida-alvera/DINEOF).
2025-09-03T16:04:58Z (local files)
2025-09-03T16:04:58Z https://cioosatlantic.ca/griddap/bio_remote_sensing_occci_nwa_poly4_spring_bloom.das";
    String infoUrl "https://bio-rsg.github.io/";
    String institution "dfo_bio";
    String keywords "agencies, agencies-non-us, amplitude, amplitude_real, annual_mean, average, based, between, bio, bloom, ca/dfo/bio, canada, chemistry, chl, chl-a, chlorophyll, chlorophyll-a, color, concentration, data, day, days, department, dfo, dineof, duration, during, earth, Earth Science > Oceans > Ocean Chemistry > Chlorophyll, Earth Science > Oceans > Ocean Chemistry > Pigments > Chlorophyll, Earth Science > Oceans > Ocean Optics > Chlorophyll > Chlorophyll Concentration, error, estimated, fisheries, fitted, gaussian, government, latitude, longitude, magnitude_real, mass, mass_concentration_of_chlorophyll_a_in_sea_water, maximum, mean, metrics, non, normalized, NRMSE_bloom, nwa, observation, occci, ocean, ocean color, oceans, optics, over, percent_dineof, percentage, period, phytoplankton, pigments, pixel, platforms, Platforms > Space-based Platforms > Earth Observation Satellites >, produced, providers, Providers > GOVERNMENT AGENCIES-NON-US > CANADA > CA/DFO/BIO, real, root, satellites, science, sea, seawater, space, space-based, spring, square, start, t_duration, t_start, time, total, using, values, water, with, year";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://creativecommons.org/licenses/by/4.0/";
    String map_projection "Equidistant Cylindrical (Plate Carrée)";
    String mission "Multiple missions";
    Float64 Northernmost_Northing 65.97916666666667;
    String platform "Multiple platforms";
    String POLY4_coefficients "0.59779,-3.15824,-0.80348,0.93129,0.78322";
    String processing_level "L4 Mapped";
    String product_name "gaussian_fit_metrics_2010.nc";
    String projected_crs_epsg_code "EPSG:4087";
    String references "doi:10.3390/s19194285; https://catalogue.ceda.ac.uk/uuid/690fdf8f229c4d04a2aa68de67beb733; doi:10.3390/rs11222609; Layton, C., Devred, E., DeTracey B.. 2022. A comparison of phytoplankton spring bloom fitting methods using MODIS satellite-derived chlorophyll-a concentration for the Maritimes region. Can. Tech. Rep. Hydrogr. Ocean Sci. 340: vii + 22 p.; Stephanie Clay, Chantelle Layton, & Emmanuel Devred. (2021). BIO-RSG/PhytoFit: First release (v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.4770754; doi:10.1016/j.ocemod.2004.08.001";
    String region "Northwest Atlantic";
    String reprocessing "v6.0";
    String sensor "Multiple sensors";
    String source "Spring bloom metrics and annual average chlorophyll-a (chl-a) derived from DINEOF-filled POLY4 chl-a. POLY4 chl-a were created using remote sensing reflectance (Rrs) data from the OC-CCI multisensor product, which were generated by the Plymouth Marine Laboratory (PML) as part of the European Space Agency (ESA) climate change initiative (www.oceancolour.org).";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 39.020833333333336;
    String spatial_resolution "4.64km at equator";
    String standard_name_vocabulary "CF Standard Name Table v79";
    String summary "NWA OCCCI spring bloom metrics 2024";
    String temporal_range "year";
    Int32 time 2010;
    String time_coverage_end "2024-01-01T00:00:00Z";
    String time_coverage_start "1998-01-01T00:00:00Z";
    String title "Northwest Atlantic per-pixel spring bloom metrics derived from OC-CCI POLY4 satellite Chlorophyll-a, 1998-present";
    String tools "https://github.com/BIO-RSG/oceancolouR";
    Float64 Westernmost_Easting -75.97916666666667;
  }
}

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.

(easy) You can get data by using the dataset's Data Access Form. It makes the URL for you.
(easy) You can make a graph or map by using the dataset's Make A Graph form. It makes the URL for you.
(not hard) You can bypass the forms and get the data or make a graph or map by generating the URL by hand or with a computer program or script.

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[(2002-06-01T09:00:00Z)][(-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.