Data Access Form

Dataset Title:	Data from ICATMAR predictions
Institution:	ICATMAR (Dataset ID: prediccions)
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| Files \| Make a graph

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Dimensions	Size	Spacing
time (UTC)	72	1h 0m 0s (even)

depth (m)	1	(just one value)

latitude (degrees_north)	442	0.01164805 (uneven)

longitude (degrees_east)	442	0.01482961 (even)

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

Eta

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 _FillValue NaN;
    Float64 actual_range 1.7800128e+9, 1.7802684e+9;
    String axis "T";
    String calendar "standard";
    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 0.0, 0.0;
    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 _FillValue NaN;
    Float32 actual_range 38.4573, 43.59409;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 _FillValue NaN;
    Float32 actual_range -0.4525852, 6.087273;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Eta {
    Float32 _FillValue -999.0;
    String ioos_category "Unknown";
    String long_name "Eta";
  }
  S {
    Float32 _FillValue -999.0;
    String ioos_category "Unknown";
    String long_name "S";
  }
  T {
    Float32 _FillValue -999.0;
    String ioos_category "Unknown";
    String long_name "T";
  }
  U {
    Float32 _FillValue -999.0;
    String ioos_category "Unknown";
    String long_name "U";
  }
  V {
    Float32 _FillValue -999.0;
    String ioos_category "Unknown";
    String long_name "V";
  }
  NC_GLOBAL {
    String cdm_data_type "Grid";
    String Conventions "COARDS, CF-1.10, ACDD-1.3";
    Float64 Easternmost_Easting 6.087273;
    Float64 geospatial_lat_max 43.59409;
    Float64 geospatial_lat_min 38.4573;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 6.087273;
    Float64 geospatial_lon_min -0.4525852;
    Float64 geospatial_lon_resolution 0.014829610430839002;
    String geospatial_lon_units "degrees_east";
    String history 
"2026-05-29T18:09:28Z (local files)
2026-05-29T18:09:28Z http://erddap.icatmar.cat/erddap/griddap/prediccions.das";
    String infoUrl "???";
    String institution "ICATMAR";
    String keywords "data, depth, eta, local, source, time, u, v";
    String license 
"This dataset by ICATMAR is licensed under a Creative Commons Attribution 4.0
        International License. You should have received a copy of the license along with this work.
        If not, see https://creativecommons.org/licenses/by/4.0/.";
    String NCO 
"netCDF Operators version 5.0.6 (Homepage = http://nco.sf.net, Code =
                https://github.com/nco/nco)";
    Float64 Northernmost_Northing 43.59409;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 38.4573;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "Data from ICATMAR predictions";
    String testOutOfDate "now-1day";
    String time_coverage_end "2026-05-31T23:00:00Z";
    String time_coverage_start "2026-05-29T00:00:00Z";
    String title "Data from ICATMAR predictions";
    Float64 Westernmost_Easting -0.4525852;
  }
}

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.