ERDDAP > tabledap > Data Access Form

Dataset Title:	2 days 1.1 km resolution forecast over Liguria - Animation of waves
Institution:	UNIGE-DICCA   (Dataset ID: unige-dicca_waves_animation)
Information:	Summary | License | Metadata | Background | Subset | Files | Make a graph

 

Variable	Optional Constraint #1		Optional Constraint #2		Minimum    or a List of Values	Maximum
url	!= =~ <= >= = < >		!= =~ <= >= = < >
time (UTC)	!= =~ <= >= = < >		!= =~ <= >= = < >		2026-01-20T00:00:00Z	2026-04-05T00:00:00Z
name (File Name)	!= =~ <= >= = < >		!= =~ <= >= = < >
lastModified (UTC)	!= =~ <= >= = < >		!= =~ <= >= = < >		2026-01-20T13:55:50Z	2026-04-03T00:01:36Z
size (bytes)	!= =~ <= >= = < >		!= =~ <= >= = < >		2.316727E7	2.4993862E7
fileType	!= =~ <= >= = < >		!= =~ <= >= = < >		".json"

 

Server-side Functions

distinct()

orderBy orderByDescending orderByClosest orderByCount orderByLimit orderByMax orderByMin orderByMinMax orderByMean orderBySum (" url time name lastModified size fileType url time name lastModified size fileType url time name lastModified size fileType url time name lastModified size fileType url time name lastModified size fileType ")

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. .dataTable - A JSON file formatted for use with the Google Visualization client library (Google Charts). .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. .esriCsv - Download a ISO_8859_1 .csv file for ESRI's ArcGIS 9.x and below (separate date and time columns). .fgdc - View the dataset's UTF-8 FGDC .xml metadata. .geoJson - Download longitude,latitude,otherColumns data as a UTF-8 GeoJSON .json file. .graph - View a Make A Graph web page. .help - View a web page with a description of tabledap. .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 response column 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 flat, table-like, NetCDF-3 binary file with COARDS/CF/ACDD metadata. .ncHeader - View the UTF-8 header (the metadata) for the NetCDF-3 .nc file. .ncCF - Download a NetCDF-3 CF Discrete Sampling Geometries file (Contiguous Ragged Array). .ncCFHeader - View the UTF-8 header (the metadata) for the .ncCF file. .ncCFMA - Download a NetCDF-3 CF Discrete Sampling Geometries file (Multidimensional Array). .ncCFMAHeader - View the UTF-8 header (the metadata) for the .ncCFMA 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 longitude,latitude,time,otherColumns as an ISO-8859-1 ODV Generic Spreadsheet File (.txt). .parquet - Download as a parquet file. Metadata contains column names ("column_names") and units ("column_units"). .parquetWMeta - Download as a parquet file with detailed metadata. .subset - View an HTML form which uses faceted search to simplify picking subsets of the data. .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. .kml - View a .kml file, suitable for Google Earth. .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 )
 
Submit (Please be patient. It may take a while to get the data.)

 

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  url {
    String ioos_category "Identifier";
    String long_name "URL";
  }
  time {
    String _CoordinateAxisType "Time";
    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 time_precision "1970-01-01 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  name {
    String ioos_category "Identifier";
    String long_name "File Name";
  }
  lastModified {
    String ioos_category "Time";
    String long_name "Last Modified";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  size {
    String ioos_category "Other";
    String long_name "Size";
    String units "bytes";
  }
  fileType {
    String ioos_category "Identifier";
    String long_name "File Type";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Grid";
    String contributors_email "meteocean.unige@gmail.com";
    String contributors_name "MeteOcean research group";
    String contributors_role "Research management";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "francesco.ferrari@unige.it";
    String creator_name "Ferrari, Francesco";
    String creator_orcid "0000-0002-8752-993X";
    String creator_type "person";
    String creator_url "https://forecast.meteocean.science";
    String data_format_original "grib2";
    String data_version "3.9.1";
    String documentation "https://s4raise.it/dssmare/distributed_monitoring_system/, https://s4raise.it/dssmare/metocean_models/, https://raise-spoke3.s4raise.it/project01";
    String geospatial_lat_units "degrees_north";
    String geospatial_lon_units "degrees_east";
    String history 
"2026-04-03T04:27:37Z (local files)
2026-04-03T04:27:37Z https://erddap.s4raise.it/erddap/tabledap/unige-dicca_waves_animation.html";
    String infoUrl "https://www.raiseliguria.it/spoke-3/";
    String inspire "Oceanographic geographical features";
    String institution "UNIGE-DICCA";
    String institution_country "IT";
    String keywords "Atmospheric data, high resolution forecast, Liguria";
    String keywords_vocabulary "GCMD Science Keywords";
    String language "XML";
    String license "CC-BY 4.0";
    String maintainer "ETT S.p.A.";
    String model_realtime "true";
    String naming_authority "RAISE, Sindbad 2.0";
    String owner "UNIGE-DICCA";
    String owner_url "https://meteocean.science/";
    String project_code "RAISE, Sindbad 2.0";
    String project_name "Robotics and AI for Socio-economic Empowerment, Servizi per la Navigazione e Attività Marittime";
    String project_statement "RAISE: Robotics and AI for Socio-economic Empowerment is an innovation ecosystem funded by the Ministry of University and Research under the National Recovery and Resilience Plan (NRRP, Mission 4, Component 2, Investment 1.5). Sindbad 2.0: Servizi per la Navigazione e Attività Marittime (Services for Navigation and Maritime Activities)";
    String project_url "https://www.raiseliguria.it/, https://www.sindbad-liguria.it/";
    String publisher "ETT S.p.A.";
    String source "WRF simulations initialized with GFS global model simulation";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v70";
    String subsetVariables "fileType";
    String summary "Hourly 3-dimensional atmospheric gridded data, with a temporal coverage of 48 hours. Data cover Central and Eastern Liguria - Animation of waves";
    String theme_eu_data "http://publications.europa.eu/resource/authority/data-theme/ENVI";
    String theme_eurovoc "http://publications.europa.eu/resource/authority/eurovoc/100224";
    String title "2 days 1.1 km resolution forecast over Liguria - Animation of waves";
    String visibility "public";
  }
}

 

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Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP Data Access Protocol (DAP) and its selection 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 or Subset form. They make 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.

Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.

 

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