Data Access Form

Dataset Title:	NWA MODIS-AQUA CHL_POLY4 2023-07-31
Institution:	dfo_bio (Dataset ID: bio_remote_sensing_modis_aqua_chl_poly4)
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| Files \| Make a graph

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Dimensions	Size	Spacing
time (UTC)	7670	1 day 0h 5m 15s (uneven)

latitude (degrees_north)	1032	-0.04166667 (even)

longitude (degrees_east)	1272	0.04166667 (even)

Grid Variables (which always also download all of the dimension variables)

chlor_a (mg m-3)

File type: (more information)

(Documentation / Bypass this form)

(Please be patient. It may take a while to get the data.)

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.0257408e+9, 1.6907616e+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 39.020833333333336, 81.97916666666667;
    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 -94.97916666666667, -42.020833333333336;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  chlor_a {
    Float32 _FillValue NaN;
    Float64 colorBarMaximum 30.0;
    Float64 colorBarMinimum 0.03;
    String colorBarScale "Log";
    String ioos_category "Ocean Color";
    String long_name "Chlorophyll-a Concentration (POLY4v2 model with coefficients optimized to MODIS-AQUA and Northwest Atlantic)";
    String standard_name "mass_concentration_of_chlorophyll_a_in_sea_water";
    String units "mg m-3";
    Float32 valid_max 100.0;
    Float32 valid_min 0.0;
  }
  NC_GLOBAL {
    String cdm_data_type "Grid";
    String Conventions "CF-1.6, 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 "2024-02-26T13:42:26Z";
    Float64 Easternmost_Easting -42.020833333333336;
    String geographic_crs_epsg_code "EPSG:4326";
    Float64 geospatial_lat_max 81.97916666666667;
    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 -94.97916666666667;
    Float64 geospatial_lon_resolution 0.04166666666666667;
    String geospatial_lon_units "degrees_east";
    String history 
"Created with make_mapped_netcdf.R. Input data are 4km-resolution level-3 binned remote sensing reflectances (Rrs) from NASA OBPG, subset to the region of interest and used in conjunction with the most recent set of regionally-tuned parameters to generate the level-3 binned product. The data is then mapped using a Plate Carrée projection and an area-weighted mean for pixels with multiple overlapping bins.
2024-12-21T18:42:00Z (local files)
2024-12-21T18:42:00Z https://cioosatlantic.ca/erddap/griddap/bio_remote_sensing_modis_aqua_chl_poly4.das";
    String infoUrl "https://bio-rsg.github.io/";
    String institution "dfo_bio";
    String keywords "agencies, agencies-non-us, aqua, atlantic, based, bio, ca/dfo/bio, canada, chemistry, chl, chlor_a, chlorophyll, chlorophyll-a, coefficients, color, concentration, data, department, dfo, earth, Earth Science > Oceans > Ocean Chemistry > Chlorophyll, Earth Science > Oceans > Ocean Chemistry > Pigments > Chlorophyll, Earth Science > Oceans > Ocean Optics > Chlorophyll > Chlorophyll Concentration, fisheries, government, imaging, latitude, longitude, mass, mass_concentration_of_chlorophyll_a_in_sea_water, model, moderate, modis, modis-aqua, non, northwest, nwa, observation, ocean, ocean color, oceans, optics, optimized, pigments, platforms, Platforms > Space-based Platforms > Earth Observation Satellites > Aqua, poly4, poly4v2, providers, Providers > GOVERNMENT AGENCIES-NON-US > CANADA > CA/DFO/BIO, resolution, satellites, science, sea, seawater, space, space-based, spectroradiometer, time, water, with";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://creativecommons.org/licenses/by/4.0/";
    String map_projection "Equidistant Cylindrical (Plate Carrée)";
    String mission "AQUA";
    Float64 Northernmost_Northing 81.97916666666667;
    String platform "AQUA";
    String POLY4v2_coefficients "0.49318,-3.86911,-0.83267,1.19094,0.9436";
    String processing_level "L3 Mapped";
    String product_name "AQUA_MODIS.20230731.L3b.DAY.CHL_POLY4.NWA.mapped.nc";
    String projected_crs_epsg_code "EPSG:4087";
    String references "Clay, S.; Peña, A.; DeTracey, B.; Devred, E. Evaluation of Satellite-Based Algorithms to Retrieve Chlorophyll-a Concentration in the Canadian Atlantic and Pacific Oceans. Remote Sens. 2019, 11, 2609.";
    String region "Northwest Atlantic";
    String reprocessing "R2022.0";
    String sensor "MODIS";
    String source "POLY4v2 chlorophyll-a generated using remote sensing reflectance (Rrs) data from NASA Ocean Biology Processing Group (OBPG, https://oceancolor.gsfc.nasa.gov)";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 39.020833333333336;
    String spatial_resolution "4.64 km at equator";
    String standard_name_vocabulary "CF Standard Name Table v79";
    String summary "NWA Moderate Resolution Imaging Spectroradiometer (MODIS)-AQUA CHL_POLY4";
    String temporal_range "day";
    String time "2023-07-31";
    String time_coverage_end "2023-07-31T00:00:00Z";
    String time_coverage_start "2002-07-04T00:00:00Z";
    String title "NWA MODIS-AQUA CHL_POLY4 2023-07-31";
    String tools "https://github.com/BIO-RSG/oceancolouR";
    Float64 Westernmost_Easting -94.97916666666667;
  }
}

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.