Make A Graph

Dataset Title:	CMEMS - CORA: Coriolis Ocean database for ReAnalysis
Institution:	Copernicus Marine Service (CMEMS) (Dataset ID: INSITU_GLO_PHY_TS_OA_MY_013_052)
Information:	Summary \| License \| FGDC \| ISO 19115 \| 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 →

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 -3.129408e+8, 1.6698528e+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";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    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 actual_range -77.01048, 89.89626;
    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 actual_range -180.0, 179.5;
    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;
    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;
  }
  PSAL_ERR {
    Float64 _FillValue 32.767;
    String long_name "Practical salinity Error";
    String units "PSS-78";
    Float64 valid_max 15.0;
    Float64 valid_min 0.0;
  }
  PSAL_PCTVAR {
    Byte _FillValue 127;
    String _Unsigned "false";
    String long_name "Error on salinity  (% variance)";
    String units "percent";
    Byte valid_max 100;
    Byte valid_min 0;
  }
  TEMP {
    Float64 _FillValue 52.767;
    String long_name "sea temperature";
    String SDN "SDN:P01::TEMPPR01";
    String standard_name "sea_water_temperature";
    String units "degree_Celsius";
    Float64 valid_max 40.0;
    Float64 valid_min -3.0;
  }
  TEMP_ERR {
    Float64 _FillValue 32.767;
    String long_name "Temperature Error";
    String units "degree_Celsius";
    Float64 valid_max 20.0;
    Float64 valid_min 0.0;
  }
  TEMP_PCTVAR {
    Byte _FillValue 127;
    String _Unsigned "false";
    String long_name "Error on temperature  (% variance)";
    String units "percent";
    Byte valid_max 100;
    Byte valid_min 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-1.4";
    String conventions "CF-1.6, COARDS, ACDD-1.3";
    String creation_date "20231127T085441L";
    String creator_name "OceanScope";
    String creator_type "Company";
    String creator_url "https://www.ocean-scope.com/";
    String data_doi "https://www.seanoe.org/data/00351/46219/";
    String data_format_original "NetCDF";
    String data_manager "Tanguy Szekely";
    String data_update "2024-02";
    String data_update_frequence "Biannually";
    Float64 Easternmost_Easting 179.5;
    Float64 geospatial_lat_max 89.89626;
    Float64 geospatial_lat_min -77.01048;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 179.5;
    Float64 geospatial_lon_min -180.0;
    Float64 geospatial_lon_resolution 0.5;
    String geospatial_lon_units "degrees_east";
    String history 
"20231127T085441L : Creation
2024-10-09T15:52:08Z (local files)
2024-10-09T15:52:08Z https://erddap.sochic-h2020.eu/erddap/griddap/INSITU_GLO_PHY_TS_OA_MY_013_052.das
2024-11-06T09:26:55Z https://erddap.sochic-h2020.eu/erddap/griddap/INSITU_GLO_PHY_TS_OA_MY_013_052
2024-11-06T09:26:55Z https://er1.s4oceanice.eu/griddap/INSITU_GLO_PHY_TS_OA_MY_013_052.das";
    String infoUrl "https://www.seanoe.org/data/00351/46219/";
    String institution "Copernicus Marine Service (CMEMS)";
    String institution_country "FR";
    String institution_edmo_code "5938";
    String keywords "Earth Science > Oceans > Ocean Temperature > Water Temperature (46206E8C-8Def-406F-9E62-Da4E74633A58), Earth Science > Oceans > Salinity/Density > Salinity (7E95B5Fc-1D58-431A-Af36-948B29Fa870D), Salinity, Water Temperature";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "CC-BY4.0";
    String metadata_url "https://www.seanoe.org/data/00351/46219/";
    String naming_authority "SO-CHIC";
    Float64 Northernmost_Northing 89.89626;
    String owner_name "OceanScope";
    String product_DOI "https://doi.org/10.17882/46219";
    String project_name "CMEMS Ins-TAC";
    String references "https://www.seanoe.org/data/00351/46219/";
    String software_version "POSTOA_main - 7.0";
    String source "Reanalysis";
    String sourceUrl "https://erddap.sochic-h2020.eu/erddap/griddap/INSITU_GLO_PHY_TS_OA_MY_013_052";
    Float64 Southernmost_Northing -77.01048;
    String standard_name_vocabulary "CF Standard Name Table v85";
    String summary 
"The COriolis Ocean Dataset for Reanalysis (hereafter \"CORA\") product is a global dataset of in situ temperature and salinity measurements. The CORA observations comes from many different sources collected by Coriolis data centre in collaboration with the In Situ Thematic Centre of the Copernicus Marine Service (CMEMS INSTAC). The observation integrated in the CORA product have been acquired both by autonomous platforms (Argo profilers, fixed moorings , gliders , drifters, sea mammals) , research or opportunity vessels (CTDs, XBTs, ferrybox). 
From the near real time CMEMS In Situ Thematic Centre product validated on a daily and weekly basis for forecasting purposes, a scientifically validated product is created. It s a \"reference product\" updated on a yearly basis since 2007. This product has been controlled using an objective analysis (statistical tests) method and a visual quality control (QC). This QC procedure has been developed with the main objective to improve the quality of the dataset to the level required by the climate application and the physical ocean re-analysis activities. It provides T and S weekly gridded fields and individual profiles both on their original level with QC flags and interpolated level. The measured parameters, depending on the data source, are : temperature, salinity. The reference level of measurements is immersion (in meters) or pressure (in decibars). 
CORA contains historical profiles extracted from the EN.4 global T&S dataset, World Ocean Atlas, SeaDataNet, ICES and other data aggregators.";
    String time_coverage_end "2022-12-01T00:00:00Z";
    String time_coverage_start "1960-02-01T00:00:00Z";
    String title "CMEMS - CORA: Coriolis Ocean database for ReAnalysis";
    String variables "Time, Depth, Latitude, Longitude, Sea Temperature, Temperature Error, Error on temperature (% variance), Practical Salinity, Practical Salinity Error, Error on Salinity (% variance)";
    Float64 Westernmost_Easting -180.0;
  }
}

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.