Make A Graph

Dataset Title:	VIIRS Suomi NPP 8-Day 750 m Composite Northwest Atlantic Water Mass Calculations
Institution:	University of Delaware (Dataset ID: VIIRS_NWATL_8day_watermass)
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| Data Access Form

To work correctly, this web page requires that JavaScript be enabled in your browser. Please:
1) Enable JavaScript in your browser:
      • Chrome: "Settings : Advanced : Privacy and security : Site Settings : JavaScript"
      • Firefox: (it should be always on!)"
      • Opera: "Settings : Websites : JavaScript"
      • Safari: "Safari : Preferences : Security : Enable JavaScript"
2) Reload this web page.

Graph Type:
X Axis:
Y Axis:
Color:

Dimensions

Start

Stop

time (UTC)

specify just 1 value →

latitude (degrees_north)

longitude (degrees_east)

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:

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 {
    UInt32 _ChunkSizes 1024;
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.483315199e+9, 1.514764799e+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 16.007999420166016, 52.0;
    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 -100.0, -50.0099983215332;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  sst {
    UInt32 _ChunkSizes 1, 900, 1000;
    Float32 _FillValue -999.0;
    Float64 colorBarMaximum 32.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Temperature";
    String long_name "Sea Surface Temperature";
    String standard_name "sea_surface_temperature";
    String units "degree_C";
  }
  chl_oc3 {
    UInt32 _ChunkSizes 1, 900, 1000;
    Float32 _FillValue -999.0;
    Float64 colorBarMaximum 30.0;
    Float64 colorBarMinimum 0.03;
    String colorBarScale "Log";
    String ioos_category "Ocean Color";
    String long_name "Chlorophyll Concentration, OC3 Algorithm";
    String standard_name "concentration_of_chlorophyll_in_sea_water";
    String units "mg m^-3";
  }
  Rrs_443 {
    UInt32 _ChunkSizes 1, 900, 1000;
    Float32 _FillValue -999.0;
    String ioos_category "Optical Properties";
    String long_name "Remote sensing reflectance at 443 nm";
    String units "sr^-1";
  }
  Rrs_551 {
    UInt32 _ChunkSizes 1, 900, 1000;
    Float32 _FillValue -999.0;
    String ioos_category "Optical Properties";
    String long_name "Remote sensing reflectance at 551 nm";
    String units "sr^-1";
  }
  M_WK {
    UInt32 _ChunkSizes 1, 900, 1000;
    Int32 _FillValue -999;
    String ioos_category "Unknown";
    String long_name "Water Mass Classifications using Wards and Kmeans clustering after Oliver and Irwin 2008";
  }
  M_WK_G {
    UInt32 _ChunkSizes 1, 900, 1000;
    Float32 _FillValue -999.0;
    String ioos_category "Unknown";
    String long_name "Gradient Strengths Across Water Mass Classifications using Wards and Kmeans clustering after Oliver and Irwin 2008";
  }
  NC_GLOBAL {
    String cdm_data_type "Grid";
    String Conventions "COARDS, CF-1.10, ACDD-1.3";
    Float64 Easternmost_Easting -50.0099983215332;
    Float64 geospatial_lat_max 52.0;
    Float64 geospatial_lat_min 16.007999420166016;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -50.0099983215332;
    Float64 geospatial_lon_min -100.0;
    String geospatial_lon_units "degrees_east";
    String history 
"2025-11-28T06:41:55Z (local files)
2025-11-28T06:41:55Z http://basin.ceoe.udel.edu/griddap/VIIRS_NWATL_8day_watermass.das";
    String infoUrl "http://orb.ceoe.udel.edu/";
    String institution "University of Delaware";
    String keywords "across, after, algorithm, chemistry, chl_oc3, chlorophyll, classifications, clustering, color, concentration, concentration_of_chlorophyll_in_sea_water, data, earth, Earth Science > Oceans > Ocean Chemistry > Chlorophyll, Earth Science > Oceans > Ocean Temperature > Sea Surface Temperature, gradient, irwin, kmeans, local, M_WK, M_WK_G, mass, oc3, ocean, ocean color, oceans, oliver, optical, optical properties, properties, reflectance, remote, Rrs_443, Rrs_551, science, sea, sea_surface_temperature, seawater, sensing, source, sst, strengths, surface, temperature, time, using, wards, water";
    String keywords_vocabulary "GCMD Science Keywords";
    String license 
"The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.";
    Float64 Northernmost_Northing 52.0;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 16.007999420166016;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "VIIRS Suomi NPP 8-Day 750 m Composite Northwest Atlantic Water Mass Calculations";
    String time_coverage_end "2017-12-31T23:59:59Z";
    String time_coverage_start "2017-01-01T23:59:59Z";
    String title "VIIRS Suomi NPP 8-Day 750 m Composite Northwest Atlantic Water Mass Calculations";
    Float64 Westernmost_Easting -100.0;
  }
}

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.