Make A Graph

Dataset Title:	CORA: Coriolis Ocean database for ReAnalysis, Temperature and Salinity in the Water Column (1960, 2022)
Institution:	OceanScope (Dataset ID: experiment_emodnet)
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 _FillValue NaN;
    Float64 actual_range 1.0729152e+9, 1.6698528e+9;
    String axis "T";
    String calendar "proleptic_gregorian";
    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";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float32 _FillValue NaN;
    Float32 actual_range 1.0, 2000.0;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
    Float32 valid_max 12000.0;
    Float32 valid_min 0.0;
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.9999492;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
    Float32 valid_max 90.0;
    Float32 valid_min -90.0;
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 _FillValue NaN;
    Float32 actual_range -4.0, 2.0;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
    Float32 valid_max 180.0;
    Float32 valid_min -180.0;
  }
  PSAL {
    Float64 _FillValue 62.767;
    Float64 colorBarMaximum 32.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Salinity";
    String long_name "practical salinity";
    String SDN "SDN:P01::PSLTZZ01";
    String standard_name "sea_water_practical_salinity";
    String units "PSU";
    Float64 valid_max 60.0;
    Float64 valid_min 4.0;
  }
  NC_GLOBAL {
    String analysis_name "OA_CORA5.2_";
    String cdm_data_type "Grid";
    String citation "Szekely et al. 2020, doi: 10.17882/46219";
    String comment "V8.0 reference climatology and analysis parameters";
    String Conventions "CF-1.10, COARDS, ACDD-1.3";
    String creation_date "20231127T085441L";
    String creator_name "OceanScope";
    String creator_url "https://resources.marine.copernicus.eu/product-detail/INSITU_GLO_PHY_TS_OA_MY_013_052/INFORMATION";
    String data_manager "Tanguy Szekely";
    Float64 Easternmost_Easting 2.0;
    Float64 geospatial_lat_max 0.9999492;
    Float64 geospatial_lat_min 0.0;
    Float64 geospatial_lat_resolution 0.4999746;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 2.0;
    Float64 geospatial_lon_min -4.0;
    Float64 geospatial_lon_resolution 0.5;
    String geospatial_lon_units "degrees_east";
    String history 
"20231127T085441L : Creation
2024-08-26T14:18:29Z (local files)
2024-08-26T14:18:29Z https://erddap.emodnet-physics.eu/erddap/griddap/INSITU_GLO_PHY_TS_OA_MY_013_052_PSAL.nc?PSAL%5B(2004-01-01):1:(2022-12-01T00:00:00Z)%5D%5B(1.0):1:(2000.0)%5D%5B(0):1:(0.9999492)%5D%5B(-4):1:(2)%5D
2024-11-21T14:40:39Z (local files)
2024-11-21T14:40:39Z https://erddap.observations.voiceoftheocean.org/griddap/experiment_emodnet.das";
    String infoUrl "https://resources.marine.copernicus.eu/product-detail/INSITU_GLO_PHY_TS_OA_MY_013_052/INFORMATION";
    String institution "OceanScope";
    String keywords "analysis, column, cora, coriolis, data, database, density, depth, earth, Earth Science > Oceans > Ocean Salinity  > Water Salinity, Earth Science > Oceans > Salinity/Density > Salinity, error, latitude, longitude, month, monthly, ocean, oceans, oceanscope, percent, practical, psal, psal_err, psal_pctvar, reanalysis, salinity, science, sea, sea_water_practical_salinity, sea_water_salinity, seawater, temperature, time, variance, water";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "Creative Commons Attribution Share-Alike http://www.opendefinition.org/licenses/cc-by-sa";
    Float64 Northernmost_Northing 0.9999492;
    String owner_name "OceanScope";
    String product_DOI "https://doi.org/10.17882/46219";
    String project_name "CMEMS Ins-TAC";
    String software_version "POSTOA_main - 7.0";
    String source "ISAS-V8";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 0.0;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "CORA: Coriolis Ocean database for ReAnalysis - Temperature and Salinity in the Water Column (1960 - 2022). Global Ocean- Gridded objective analysis fields of temperature and salinity using profiles from the reprocessed in-situ global product CORA (INSITU_GLO_TS_REP_OBSERVATIONS_013_001_b) using the ISAS software. Objective analysis is based on a statistical estimation method that allows presenting a synthesis and a validation of the dataset, providing a validation source for operational models, observing seasonal cycle and inter-annual variability.";
    String time_coverage_end "2022-12-01T00:00:00Z";
    String time_coverage_start "2004-01-01T00:00:00Z";
    String title "CORA: Coriolis Ocean database for ReAnalysis, Temperature and Salinity in the Water Column (1960, 2022)";
    Float64 Westernmost_Easting -4.0;
  }
}

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.