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Dataset Title:  NWA MODIS-AQUA CHL_POLY4 2023-07-31 Subscribe RSS
Institution:  dfo_bio   (Dataset ID: bio_remote_sensing_modis_aqua_chl_poly4)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
 
Graph Type:  ?
X Axis:  ?
Y Axis:  ?
Color:  ?
 
Dimensions ?    Start ?    Stop ?
time (UTC) ?     specify just 1 value →
    |< - >|
< <
latitude (degrees_north) ?
    +
    -
< slider >
longitude (degrees_east) ?
    +
    -
< slider >
 
Graph Settings
Color Bar:   Continuity:   Scale: 
   Minimum:   Maximum:   N Sections: 
Draw land mask: 
Y Axis Minimum:   Maximum:   
 
(Please be patient. It may take a while to get the data.)
 
Optional:
Then set the File Type: (File Type information)
and
or view the URL:
(Documentation / Bypass this form ? )
    Click on the map to specify a new center point. ?
Zoom:
[The graph you specified. Please be patient.]

 

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 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.
2024-06-23T17:21:14Z (local files)
2024-06-23T17:21:14Z https://cioosatlantic.ca/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.

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.


 
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