Make A Graph

Dataset Title:	INCOIS ARGO 10 Day data Kessler-McCreary Methodology
Institution:	INCOIS (Dataset ID: incois_argo_10day_McCreary)
Information:	Summary \| License \| Metadata \| Background \| Data Access Form

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Graph Type:
X Axis:
Y Axis:
Color:

Dimensions

Start

Stop

time (UTC)

specify just 1 value →

ZAX (METERS)

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 9.790848e+8, 1.7329248e+9;
    String axis "T";
    String calendar "standard";
    String ioos_category "Time";
    String long_name "TAXIS";
    String source_name "TAXIS";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  ZAX {
    Float64 actual_range 5.0, 2000.0;
    String axis "Z";
    String ioos_category "Location";
    String point_spacing "uneven";
    String units "METERS";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range -29.5, 29.5;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String source_name "YAXIS";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range 30.5, 119.5;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String source_name "XAXIS";
    String standard_name "longitude";
    String units "degrees_east";
  }
  S_ANALYZED {
    Float32 _FillValue 9999.0;
    Float64 colorBarMaximum 37.0;
    Float64 colorBarMinimum 32.0;
    String history "From Sal.grd";
    String ioos_category "Salinity";
    String long_name "Objectively Analyzed Salinity";
    Float32 missing_value 9999.0;
    String standard_name "sea_water_practical_salinity";
    String units "PSU";
  }
  S_MEAN {
    Float32 _FillValue 9999.0;
    Float64 colorBarMaximum 37.0;
    Float64 colorBarMinimum 32.0;
    String history "From Sal.grd";
    String ioos_category "Salinity";
    String long_name "Statistical Mean Salinity";
    Float32 missing_value 9999.0;
    String standard_name "sea_water_practical_salinity";
    String units "PSU";
  }
  S_STDEV {
    Float32 _FillValue 9999.0;
    Float64 colorBarMaximum 1.0;
    Float64 colorBarMinimum 0.0;
    String history "From Sal.grd";
    String ioos_category "Statistics";
    String long_name "Salinity Standard Deviation wrt analyzed mean";
    Float32 missing_value 9999.0;
    String units "psu";
  }
  S_RMSE {
    Float32 _FillValue 9999.0;
    Float64 colorBarMaximum 37.0;
    Float64 colorBarMinimum 32.0;
    String history "From Sal.grd";
    String ioos_category "Salinity";
    String long_name "Salinity RMSE wrt analyzed mean";
    Float32 missing_value 9999.0;
    String standard_name "sea_water_practical_salinity";
    String units "PSU";
  }
  S_ROIOBS {
    Float32 _FillValue 9999.0;
    Float64 colorBarMaximum 37.0;
    Float64 colorBarMinimum 32.0;
    String history "From Sal.grd";
    String ioos_category "Salinity";
    String long_name "No of Salinity values with in ROI";
    Float32 missing_value 9999.0;
    String standard_name "sea_water_practical_salinity";
    String units "PSU";
  }
  S_BOXOBS {
    Float32 _FillValue 9999.0;
    Float64 colorBarMaximum 37.0;
    Float64 colorBarMinimum 32.0;
    String history "From Sal.grd";
    String ioos_category "Salinity";
    String long_name "No of Salinity values with in 1x1 box";
    Float32 missing_value 9999.0;
    String standard_name "sea_water_practical_salinity";
    String units "PSU";
  }
  T_ANALYZED {
    Float32 _FillValue 9999.0;
    String history "From Tmp.grd";
    String ioos_category "Temperature";
    String long_name "Objectively Analyzed Temperature";
    Float32 missing_value 9999.0;
    String units "degs";
  }
  T_MEAN {
    Float32 _FillValue 9999.0;
    String history "From Tmp.grd";
    String ioos_category "Temperature";
    String long_name "Statistical Mean Temperature";
    Float32 missing_value 9999.0;
    String units "degs";
  }
  T_STDEV {
    Float32 _FillValue 9999.0;
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String history "From Tmp.grd";
    String ioos_category "Statistics";
    String long_name "Temperature Standard Deviation wrt analyzed mean";
    Float32 missing_value 9999.0;
    String units "degs";
  }
  T_RMSE {
    Float32 _FillValue 9999.0;
    String history "From Tmp.grd";
    String ioos_category "Temperature";
    String long_name "Temperature RMSE wrt analyzed mean";
    Float32 missing_value 9999.0;
    String units "degs";
  }
  T_ROIOBS {
    Float32 _FillValue 9999.0;
    String history "From Tmp.grd";
    String ioos_category "Temperature";
    String long_name "No of Temperature values with in ROI";
    Float32 missing_value 9999.0;
  }
  T_BOXOBS {
    Float32 _FillValue 9999.0;
    String history "From Tmp.grd";
    String ioos_category "Temperature";
    String long_name "No of Temperature values with in 1x1 box";
    Float32 missing_value 9999.0;
  }
  NC_GLOBAL {
    String CDI "Climate Data Interface version 2.1.0 (https://mpimet.mpg.de/cdi)";
    String cdm_data_type "Grid";
    String CDO "Climate Data Operators version 2.1.0 (https://mpimet.mpg.de/cdo)";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    Float64 Easternmost_Easting 119.5;
    Float64 geospatial_lat_max 29.5;
    Float64 geospatial_lat_min -29.5;
    Float64 geospatial_lat_resolution 1.0;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 119.5;
    Float64 geospatial_lon_min 30.5;
    Float64 geospatial_lon_resolution 1.0;
    String geospatial_lon_units "degrees_east";
    String history 
"Tue Dec 31 13:53:10 2024: cdo merge MackessWithStats_Sal10dys.nc MackessWithStats_Tmp10dys.nc argo_10d.nc
FERRET V6.7  27-Dec-24
2025-01-16T12:55:08Z (local files)
2025-01-16T12:55:08Z https://erddap.incois.gov.in/griddap/incois_argo_10day_McCreary.das";
    String infoUrl "???";
    String institution "INCOIS";
    String keywords "S_ANALYZED, S_BOXOBS, S_MEAN, S_RMSE, S_ROIOBS, S_STDEV, T_ANALYZED, T_BOXOBS, T_MEAN, T_RMSE, T_ROIOBS, T_STDEV, TAXIS, XAXIS, YAXIS, ZAX";
    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 29.5;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -29.5;
    String standard_name_vocabulary "CF Standard Name Table v29";
    String summary "INCOIS ARGO 10 Day data Kessler-McCreary Methodology";
    String time_coverage_end "2024-11-30T00:00:00Z";
    String time_coverage_start "2001-01-10T00:00:00Z";
    String title "INCOIS ARGO 10 Day data Kessler-McCreary Methodology";
    Float64 Westernmost_Easting 30.5;
  }
}

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.