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Dataset Title:  CORA: Coriolis Ocean database for ReAnalysis - Temperature and Salinity in the
Water Column (1960 - 2022)
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Institution:  OceanScope   (Dataset ID: INSITU_GLO_PHY_TS_OA_MY_013_052_TEMP)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
 
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) ?
    +
    -
< slider >
longitude (degrees_east) ?
    +
    -
< slider >
 
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:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range -3.156192e+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;
  }
  TEMP {
    Float64 _FillValue 52.767;
    Float64 colorBarMaximum 32.0;
    Float64 colorBarMinimum 0.0;
    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;
    Float64 colorBarMaximum 5.0;
    Float64 colorBarMinimum 0.0;
    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";
    Float64 colorBarMaximum 5.0;
    Float64 colorBarMinimum 0.0;
    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-1.6, COARDS, ACDD-1.3";
    String creation_date "20230926T220219L";
    String data_manager "Tanguy Szekely";
    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 
"20230926T220219L : Creation
2024-02-29T08:29:55Z (local files)
2024-02-29T08:29:55Z https://erddap.emodnet-physics.eu/griddap/INSITU_GLO_PHY_TS_OA_MY_013_052_TEMP.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, data, depth, earth, Earth Science > Oceans > Ocean Salinity  > Water Salinity, error, latitude, longitude, month, monthly, ocean, oceans, oceanscope, percent, PSAL, PSAL_ERR, PSAL_PCTVAR, salinity, science, sea, sea_water_salinity, seawater, 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 89.89626;
    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 -77.01048;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "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 "1960-01-01T00:00:00Z";
    String title "CORA: Coriolis Ocean database for ReAnalysis - Temperature and Salinity in the Water Column (1960 - 2022)";
    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.

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.


 
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