Make A Graph

Dataset Title:	Test Black Sea biogeochemical model output: zooplankton
Institution:	METU-IMS (Dataset ID: BlackSea_BGC_model_zooplankton)
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 →

depth (m)

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 {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.4516496e+9, 1.452168e+9;
    String axis "T";
    String calendar "gregorian";
    String ioos_category "Time";
    String long_name "Time axis";
    String source_name "time_counter";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float32 actual_range 2.499249, 2244.475;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String source_name "deptht";
    String standard_name "depth";
    String units "m";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 40.6, 47.1052;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String source_name "y";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range 27.2, 42.2954;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String source_name "x";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Gelatinous_carnivores_carbon {
    Float32 _FillValue -2.0e+20;
    String cell_methods "time: mean (interval: 360 s)";
    String interval_operation "360 s";
    String interval_write "1 d";
    String ioos_category "Zooplankton Abundance";
    String long_name "gelatinous_carnivores carbon";
    Float32 missing_value -2.0e+20;
    String online_operation "average";
    String units "mg C/m^3";
  }
  Mesozooplankton_carbon {
    Float32 _FillValue -2.0e+20;
    String cell_methods "time: mean (interval: 360 s)";
    String interval_operation "360 s";
    String interval_write "1 d";
    String ioos_category "Zooplankton Abundance";
    String long_name "mesozooplankton carbon";
    Float32 missing_value -2.0e+20;
    String online_operation "average";
    String units "mg C/m^3";
  }
  Microzooplankton_carbon {
    Float32 _FillValue -2.0e+20;
    String cell_methods "time: mean (interval: 360 s)";
    String interval_operation "360 s";
    String interval_write "1 d";
    String ioos_category "Zooplankton Abundance";
    String long_name "microzooplankton carbon";
    Float32 missing_value -2.0e+20;
    String online_operation "average";
    String units "mg C/m^3";
  }
  Microzooplankton_nitrogen {
    Float32 _FillValue -2.0e+20;
    String cell_methods "time: mean (interval: 360 s)";
    String interval_operation "360 s";
    String interval_write "1 d";
    String ioos_category "Dissolved Nutrients";
    String long_name "microzooplankton nitrogen";
    Float32 missing_value -2.0e+20;
    String online_operation "average";
    String units "MMol' 'N/M^3";
  }
  Microzooplankton_phosphorus {
    Float32 _FillValue -2.0e+20;
    String cell_methods "time: mean (interval: 360 s)";
    String interval_operation "360 s";
    String interval_write "1 d";
    String ioos_category "Dissolved Nutrients";
    String long_name "microzooplankton phosphorus";
    Float32 missing_value -2.0e+20;
    String online_operation "average";
    String units "MMol' 'P/M^3";
  }
  Nanoflagellates_carbon {
    Float32 _FillValue -2.0e+20;
    String cell_methods "time: mean (interval: 360 s)";
    String interval_operation "360 s";
    String interval_write "1 d";
    String ioos_category "Zooplankton Abundance";
    String long_name "nanoflagellates carbon";
    Float32 missing_value -2.0e+20;
    String online_operation "average";
    String units "mg C/m^3";
  }
  Nanoflagellates_nitrogen {
    Float32 _FillValue -2.0e+20;
    String cell_methods "time: mean (interval: 360 s)";
    String interval_operation "360 s";
    String interval_write "1 d";
    String ioos_category "Dissolved Nutrients";
    String long_name "nanoflagellates nitrogen";
    Float32 missing_value -2.0e+20;
    String online_operation "average";
    String units "MMol' 'N/M^3";
  }
  Nanoflagellates_phosphorus {
    Float32 _FillValue -2.0e+20;
    String cell_methods "time: mean (interval: 360 s)";
    String interval_operation "360 s";
    String interval_write "1 d";
    String ioos_category "Dissolved Nutrients";
    String long_name "nanoflagellates phosphorus";
    Float32 missing_value -2.0e+20;
    String online_operation "average";
    String units "MMol' 'P/M^3";
  }
  NC_GLOBAL {
    String CDI "Climate Data Interface version 1.9.8 (https://mpimet.mpg.de/cdi)";
    String cdm_data_type "Grid";
    String CDO "Climate Data Operators version 1.9.8 (https://mpimet.mpg.de/cdo)";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    String defaultGraphQuery "Gelatinous_carnivores_carbon[last][0][0:last][0:last]";
    String description "BGC zooplanktons";
    Float64 Easternmost_Easting 42.2954;
    String file_name "BlackSea_1d_20160101_20160331_bgc_zoos.nc";
    Float64 geospatial_lat_max 47.1052;
    Float64 geospatial_lat_min 40.6;
    Float64 geospatial_lat_resolution 0.02780000000000001;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 42.2954;
    Float64 geospatial_lon_min 27.2;
    Float64 geospatial_lon_resolution 0.027800000000000002;
    String geospatial_lon_units "degrees_east";
    String history 
"Wed Feb 08 13:35:04 2023: cdo -L -z zip_9 -seltimestep,1,7 /nas/acar/DOORS_examples/BlackSea_1d_20160101_20160331_bgc_zoos.nc BlackSea_1d_20160101_20160105_bgc_file3.nc
2024-09-16T19:31:54Z (local files)
2024-09-16T19:31:54Z http://erddap.bridgeblacksea.org:8080/griddap/BlackSea_BGC_model_zooplankton.das";
    Int32 ibegin 1;
    String infoUrl "http://bridgeblacksea.org";
    String institution "METU-IMS";
    Int32 jbegin 1;
    String keywords "carbon, carnivores, gelatinous, mesozooplankton, microzooplankton, nanoflagellates, nitrogen, phosphorus, zooplankton";
    String license "The standard license for all data should be described here!!";
    String name "BlackSea_1d_20160101_20160331";
    Int32 ni 544;
    Int32 nj 2;
    Float64 Northernmost_Northing 47.1052;
    String production "An IPSL model";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 40.6;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "BGC zooplanktons.";
    String time_coverage_end "2016-01-07T12:00:00Z";
    String time_coverage_start "2016-01-01T12:00:00Z";
    String TimeStamp "02/05/2022 14:30:23 +0300";
    String timeStamp "2022-May-01 15:38:51 +03";
    String title "Test Black Sea biogeochemical model output: zooplankton";
    Float64 Westernmost_Easting 27.2;
  }
}

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.