Data Access Form

Dataset Title:	EMODnet Physics - Arctic Sea Surface Temperature Climatology (1900-2014) - GridSeriesObservation - based on the SeaDataNet aggregated dataset
Institution:	Institute of Marine Research, Norwegian Marine Data Centre (Dataset ID: EP_TDS_SDN_TEMP_XX_GR_CLI_ARCTIC)
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| Files \| Make a graph

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Dimensions	Size	Spacing
time (UTC)	12	30 days 8h 43m 38s (uneven)

depth (m)	25	-72.91667 (uneven)

latitude (degrees_north)	171	0.1 (even)

longitude (degrees_east)	526	0.2 (even)

Grid Variables (which always also download all of the dimension variables)

Temperature (degree_C)

Temperature_err (Error standard deviation of Temperature, degree_C)

Temperature_L1 (Temperature masked using relative error threshold 0.3, degree_C)

Temperature_L2 (Temperature masked using relative error threshold 0.5, degree_C)

Temperature_relerr (Relative error of Temperature)

databins (Logarithm10 of number of data in bins)

outlbins (Logarithm10 of number of outliers data in bins)

CLfield (Correlation length field)

File type: (more information)

(Documentation / Bypass this form)

(Please be patient. It may take a while to get the data.)

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range -4.089312e+8, -3.800736e+8;
    String axis "T";
    String climatology "climatology_bounds";
    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 0.0, 1750.0;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 65.0, 82.0;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range -40.0, 65.0;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Temperature {
    Float32 _FillValue -9999.0;
    String cell_methods "time: mean (this month data from all years)";
    String long_name "Temperature";
    Float32 missing_value -9999.0;
    String units "degree_C";
    Float32 valid_max 15.0;
    Float32 valid_min -8.0;
  }
  Temperature_err {
    Float32 _FillValue -9999.0;
    String long_name "Error standard deviation of Temperature";
    Float32 missing_value -9999.0;
    String units "degree_C";
    Float32 valid_max 3.1;
    Float32 valid_min 0.0;
  }
  Temperature_L1 {
    Float32 _FillValue -9999.0;
    String long_name "Temperature masked using relative error threshold 0.3";
    Float32 missing_value -9999.0;
    String units "degree_C";
    Float32 valid_max 15.0;
    Float32 valid_min -8.0;
  }
  Temperature_L2 {
    Float32 _FillValue -9999.0;
    String long_name "Temperature masked using relative error threshold 0.5";
    Float32 missing_value -9999.0;
    String units "degree_C";
    Float32 valid_max 15.0;
    Float32 valid_min -8.0;
  }
  Temperature_relerr {
    Float32 _FillValue -9999.0;
    String long_name "Relative error of Temperature";
    Float32 missing_value -9999.0;
    Float32 valid_max 1.0;
    Float32 valid_min 0.0;
  }
  databins {
    Float32 _FillValue -9999.0;
    String long_name "Logarithm10 of number of data in bins";
    Float32 missing_value -9999.0;
    Float32 valid_max 3.4;
    Float32 valid_min 0.0;
  }
  outlbins {
    Float32 _FillValue -9999.0;
    String long_name "Logarithm10 of number of outliers data in bins";
    Float32 missing_value -9999.0;
    Float32 valid_max -9999.0;
    Float32 valid_min 0.0;
  }
  CLfield {
    Float32 _FillValue -9999.0;
    String long_name "Correlation length field";
    Float32 missing_value -9999.0;
    Float32 valid_max 3.5;
    Float32 valid_min 0.0;
  }
  NC_GLOBAL {
    String Author_e_mail "Helge.Sagen@imr.no";
    String cdm_data_type "Grid";
    String comment "No comment";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    String creator_name "Institute of Marine Research, Norwegian Marine Data Centre";
    String data_access "GHER OPENDAB: http://gher-diva.phys.ulg.ac.be/data/";
    String date "2015-09-17 07:37:05.00";
    Float64 Easternmost_Easting 65.0;
    String file_name "../output/3Danalysis/Temperature.19002014.4Danl.nc";
    Float64 geospatial_lat_max 82.0;
    Float64 geospatial_lat_min 65.0;
    Float64 geospatial_lat_resolution 0.1;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 65.0;
    Float64 geospatial_lon_min -40.0;
    Float64 geospatial_lon_resolution 0.2;
    String geospatial_lon_units "degrees_east";
    String history 
"Data from SeaDataNetArcticProductV1.1
2025-10-29T18:29:36Z (local files)
2025-10-29T18:29:36Z http://erddap.emodnet-physics.eu/erddap/griddap/EP_TDS_SDN_TEMP_XX_GR_CLI_ARCTIC.das";
    String infoUrl "https://www.seadatanet.org/";
    String institution "Institute of Marine Research, Norwegian Marine Data Centre";
    String keywords "analysis, bins, centre, CLfield, correlation, data, databins, degrees, depth, deviation, diva, error, field, institute, length, logarithm10, marine, masked, norwegian, number, outlbins, outliers, relative, research, standard, temperature, Temperature_err, Temperature_L1, Temperature_L2, Temperature_relerr, threshold, time, using, year";
    String license "Creative Commons Attribution Share-Alike http://www.opendefinition.org/licenses/cc-by-sa";
    Float64 Northernmost_Northing 82.0;
    String product_id "0effef69-c932-47d7-8f2f-9d51d249f796";
    String production "Diva group. E-mails : Helge.Sagen@imr.no ; Oivind.Oestensen@imr.no";
    String project "SeaDataNetII: https://www.seadatanet.org/";
    String source "Data from SeaDataNetArcticProductV1.1";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 65.0;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "No comment. Institute of Marine Research, Norwegian Marine Data Centre data from a local source.";
    String time_coverage_end "1957-12-16T00:00:00Z";
    String time_coverage_start "1957-01-16T00:00:00Z";
    String title "EMODnet Physics - Arctic Sea Surface Temperature Climatology (1900-2014) - GridSeriesObservation - based on the SeaDataNet aggregated dataset";
    String WEB_visualisation "http://gher-diva.phys.ulg.ac.be/web-vis/clim.html";
    Float64 Westernmost_Easting -40.0;
  }
}

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.

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