ERDDAP > griddap > Data Access Form

Dataset Title:	NAUTILOS - SOMA hourly averaged 2D fields forecast (HOURLY SURFACE 2km best) [ time], 2022-present - UAlg
Institution:	UAlg   (Dataset ID: hydroSOMA_model_hourly_surf_2km_3_ualg)
Information:	Summary | License | Metadata | Background | Make a graph

 

Dimensions	Start	Stride	Stop	Size	Spacing
time (UTC)				21384	1h 0m 0s (even)

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

time_run (run times for coordinate = time, seconds since 1970-01-01T00:00:00Z)

time_offset (seconds since 1970-01-01T00:00:00Z)

File type: (more information) .asc - View OPeNDAP-style ISO-8859-1 comma-separated text. .csv - Download a ISO-8859-1 comma-separated text table (line 1: names; line 2: units; ISO 8601 times). .csvp - Download a ISO-8859-1 .csv file with line 1: name (units). Times are ISO 8601 strings. .csv0 - Download a ISO-8859-1 .csv file without column names or units. Times are ISO 8601 strings. .das - View the dataset's metadata via an ISO-8859-1 OPeNDAP Dataset Attribute Structure (DAS). .dds - View the dataset's structure via an ISO-8859-1 OPeNDAP Dataset Descriptor Structure (DDS). .dods - OPeNDAP clients use this to download the data in the DODS binary format. .esriAscii - Download an ISO-8859-1 ESRI ASCII file (latitude longitude data only; longitude must be all below or all above 180). .fgdc - View the dataset's UTF-8 FGDC .xml metadata. .graph - View a Make A Graph web page. .help - View a web page with a description of griddap. .html - View an OPeNDAP-style HTML Data Access Form. .htmlTable - View a UTF-8 .html web page with the data in a table. Times are ISO 8601 strings. .iso19115 - View the dataset's ISO 19115-2/19139 UTF-8 .xml metadata. .itx - Download an ISO-8859-1 Igor Text File. Each axis variable and each data variable becomes a wave. .json - View a table-like UTF-8 JSON file (missing value = 'null'; times are ISO 8601 strings). .jsonlCSV1 - View a UTF-8 JSON Lines CSV file with column names on line 1 (mv = 'null'; times are ISO 8601 strings). .jsonlCSV - View a UTF-8 JSON Lines CSV file without column names (mv = 'null'; times are ISO 8601 strings). .jsonlKVP - View a UTF-8 JSON Lines file with Key:Value pairs (missing value = 'null'; times are ISO 8601 strings). .mat - Download a MATLAB binary file. .nc - Download a NetCDF-3 binary file with COARDS/CF/ACDD metadata. .ncHeader - View the UTF-8 header (the metadata) for the NetCDF-3 .nc file. .ncml - View the dataset's structure and metadata as a UTF-8 NCML .xml file. .nccsv - Download a NetCDF-3-like 7-bit ASCII NCCSV .csv file with COARDS/CF/ACDD metadata. .nccsvMetadata - View the dataset's metadata as the top half of a 7-bit ASCII NCCSV .csv file. .ncoJson - Download a UTF-8 NCO lvl=2 JSON file with COARDS/CF/ACDD metadata. .odvTxt - Download time,latitude,longitude,otherVariables as an ODV Generic Spreadsheet File (.txt). .timeGaps - View a UTF-8 list of gaps in the time values which are larger than the median gap. .tsv - Download a ISO-8859-1 tab-separated text table (line 1: names; line 2: units; ISO 8601 times). .tsvp - Download a ISO-8859-1 .tsv file with line 1: name (units). Times are ISO 8601 strings. .tsv0 - Download a ISO-8859-1 .tsv file without column names or units. Times are ISO 8601 strings. .wav - Download a .wav audio file. All columns must be numeric and of the same type. .xhtml - View a UTF-8 XHTML (XML) file with the data in a table. Times are ISO 8601 strings. .geotif - View a grayscale GeoTIFF .tif file (for latitude longitude data; longitude must be all below or all above 180). .kml - View a Google Earth .kml file (for latitude, longitude data only). .smallPdf - View a small .pdf image file with a graph or map. .pdf - View a standard, medium-sized .pdf image file with a graph or map. .largePdf - View a large .pdf image file with a graph or map. .smallPng - View a small .png image file with a graph or map. .png - View a standard, medium-sized .png image file with a graph or map. .largePng - View a large .png image file with a graph or map. .transparentPng - View a .png image file (just the data, without axes, landmask, or legend).

(Documentation / Bypass this form)
 
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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.6723584e+9, 1.7493372e+9;
    String axis "T";
    String calendar "proleptic_gregorian";
    String ioos_category "Time";
    String long_name "Forecast time for ForecastModelRunCollection";
    Float64 missing_value NaN;
    String parameter_sdn_name "Elapsed time";
    String parameter_sdn_uri "https://vocab.nerc.ac.uk/collection/P01/current/ELTMZZZZ/";
    String parameter_sdn_urn "SDN:P01::ELTMZZZZ";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String unit_sdn_name "Seconds";
    String unit_sdn_uri "https://vocab.nerc.ac.uk/collection/P06/current/UTBB/";
    String unit_sdn_urn "SDN:P06::UTBB";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  time_run {
    String _CoordinateAxisType "RunTime";
    String calendar "proleptic_gregorian";
    String ioos_category "Time";
    String long_name "run times for coordinate = time";
    String parameter_sdn_name "Elapsed time";
    String parameter_sdn_uri "https://vocab.nerc.ac.uk/collection/P01/current/ELTMZZZZ/";
    String parameter_sdn_urn "SDN:P01::ELTMZZZZ";
    String standard_name "forecast_reference_time";
    String time_origin "01-JAN-1970 00:00:00";
    String unit_sdn_name "Seconds";
    String unit_sdn_uri "https://vocab.nerc.ac.uk/collection/P06/current/UTBB/";
    String unit_sdn_urn "SDN:P06::UTBB";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  time_offset {
    String _CoordinateAxisType "TimeOffset";
    String calendar "proleptic_gregorian";
    String ioos_category "Time";
    String long_name "offset hour from start of run for coordinate = time";
    String parameter_sdn_name "Elapsed time";
    String parameter_sdn_uri "https://vocab.nerc.ac.uk/collection/P01/current/ELTMZZZZ/";
    String parameter_sdn_urn "SDN:P01::ELTMZZZZ";
    String standard_name "forecast_period";
    String time_origin "01-JAN-1970 00:00:00";
    String unit_sdn_name "Seconds";
    String unit_sdn_uri "https://vocab.nerc.ac.uk/collection/P06/current/UTBB/";
    String unit_sdn_urn "SDN:P06::UTBB";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  NC_GLOBAL {
    String _CoordSysBuilder "ucar.nc2.dataset.conv.CF1Convention";
    String area "South Portugal";
    String cdm_data_type "Grid";
    String contact "https://www.cima.ualg.pt/en/contactos";
    String Conventions "CF-1.10, COARDS, ACDD-1.3";
    String creator_name "UAlg Centre for Marine and Environmental Research";
    String creator_type "institution";
    String creator_url "https://soma.ualg.pt";
    String history 
"FMRC Best Dataset
2025-06-07T05:07:27Z https://cima-somathredds.ualg.pt/thredds/dodsC/soma-fes14/hourly-surf_2km/HOURLY_SURFACE_2km_best.ncd
2025-06-07T05:07:27Z https://data-nautilos-h2020.eu/erddap/griddap/hydroSOMA_model_hourly_surf_2km_3_ualg.das";
    String infoUrl "https://soma.ualg.pt";
    String inspire "Oceanographic geographical features";
    String institution "UAlg";
    String institution_country "PT";
    String institution_edmo_code "5675";
    String keywords "2km, averaged, best, centre, coordinate, data, environmental, fields, forecast, forecast_period, forecast_reference_time, hour, hourly, marine, offset, period, reference, research, run, soma, start, surface, time, time_offset, time_run, times, ualg";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "CC-BY 4.0";
    String location "Proto fmrc:SOMA-SURF_2km";
    String naming_authority "NAUTILOS";
    String project_code "NAUTILOS";
    String Project_DOI "https://doi.org/10.3030/101000825";
    String project_edmerp "13720";
    String project_id "101000825";
    String project_name "New Approach to Underwater Technologies for Innovative, Low-cost Ocean obServation";
    String project_statement "This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 101000825 (NAUTILOS). This output reflects only the author's view and the European Union cannot be held responsible for any use that may be made of the information contained therein";
    String references "https://soma.ualg.pt";
    String sourceUrl "https://cima-somathredds.ualg.pt/thredds/dodsC/soma-fes14/hourly-surf_2km/HOURLY_SURFACE_2km_best.ncd";
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "SOMA hourly averaged 2D fields forecast (HOURLY SURFACE 2km best)";
    String testOutOfDate "now+1day";
    String time_coverage_end "2025-06-07T23:00:00Z";
    String time_coverage_start "2022-12-30T00:00:00Z";
    String title "NAUTILOS - SOMA hourly averaged 2D fields forecast (HOURLY SURFACE 2km best) [time], 2022-present - UAlg";
    String variables "run times for coordinate, offset hour from start of run for coordinate";
  }
}

 

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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 Data Access Protocol (DAP) and its projection constraints.

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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