ERDDAP > tabledap > Make A Graph

Dataset Title:	AI-based particle dispersion model
Institution:	UNIGE-DICCA   (Dataset ID: unige-dicca_dispersion_forecast_ai)
Range:	longitude = 9.174013 to 9.238991°E, latitude = 44.29473 to 44.345406°N, depth = 0.0 to 0.0m, time = 2026-03-03T12:00:00Z to 2026-03-03T17:00:00Z
Information:	Summary | License | FGDC | ISO 19115 | Metadata | Background | Data Access Form | Files

 

Graph Type:  lines linesAndMarkers markers sticks vectors X Axis:  time latitude longitude particle_count mass status_codes age density spill_num surface_concentration depth id viscosity Y Axis:  time latitude longitude particle_count mass status_codes age density spill_num surface_concentration depth id viscosity Color:  time latitude longitude particle_count mass status_codes age density spill_num surface_concentration depth id viscosity   Constraints Optional Constraint #1 Optional Constraint #2 time latitude longitude particle_count mass status_codes age density spill_num surface_concentration depth id viscosity     != =~ <= >= = < >     != =~ <= >= = < > time latitude longitude particle_count mass status_codes age density spill_num surface_concentration depth id viscosity     != =~ <= >= = < >     != =~ <= >= = < > time latitude longitude particle_count mass status_codes age density spill_num surface_concentration depth id viscosity     != =~ <= >= = < >     != =~ <= >= = < > time latitude longitude particle_count mass status_codes age density spill_num surface_concentration depth id viscosity     != =~ <= >= = < >     != =~ <= >= = < > time latitude longitude particle_count mass status_codes age density spill_num surface_concentration depth id viscosity     != =~ <= >= = < >     != =~ <= >= = < >   Server-side Functions  distinct() orderBy orderByDescending orderByClosest orderByCount orderByLimit orderByMax orderByMin orderByMinMax orderByMean orderBySum (" time latitude longitude particle_count mass status_codes age density spill_num surface_concentration depth id viscosity time latitude longitude particle_count mass status_codes age density spill_num surface_concentration depth id viscosity time latitude longitude particle_count mass status_codes age density spill_num surface_concentration depth id viscosity time latitude longitude particle_count mass status_codes age density spill_num surface_concentration depth id viscosity ")   Graph Settings Marker Type:  None Plus X Dot Square Filled Square Circle Filled Circle Up Triangle Filled Up Triangle Borderless Filled Square Borderless Filled Circle Borderless Filled Up Triangle  Size:  3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Color:  Color Bar:  BlackBlueWhite BlackGreenWhite BlackRedWhite BlackWhite BlueWhiteRed BlueWideWhiteRed LightRainbow Ocean OceanDepth Rainbow Rainbow2 Rainfall ReverseRainbow RedWhiteBlue RedWhiteBlue2 RedWideWhiteBlue Spectrum Topography TopographyDepth WhiteBlueBlack WhiteGreenBlack WhiteRedBlack WhiteBlack YellowRed KT_algae KT_amp KT_balance KT_curl KT_deep KT_delta KT_dense KT_gray KT_haline KT_ice KT_matter KT_oxy KT_phase KT_solar KT_speed KT_tempo KT_thermal KT_turbid EK80  Continuity:  Continuous Discrete  Scale:  Linear Log    Minimum:   Maximum:   N Sections:  2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 Draw land mask:  under over outline off Y Axis Minimum:   Maximum:    Ascending Descending Linear Log   Redraw the Graph (Please be patient. It may take a while to get the data.)   Optional: Then set the File Type: .asc .csv .csvp .csv0 .dataTable .das .dds .dods .esriCsv .fgdc .geoJson .graph .help .html .htmlTable .iso19115 .itx .json .jsonlCSV1 .jsonlCSV .jsonlKVP .mat .nc .ncHeader .ncCF .ncCFHeader .ncCFMA .ncCFMAHeader .nccsv .nccsvMetadata .ncoJson .odvTxt .parquet .parquetWMeta .subset .tsv .tsvp .tsv0 .wav .xhtml .kml .smallPdf .pdf .largePdf .smallPng .png .largePng .transparentPng (File Type information) and or view the URL: (Documentation / Bypass this form )

Click on the map to specify a new center point. Zoom:  Time range:  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 second(s) minute(s) hour(s) day(s) month(s) year(s)

 

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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:

• Web page authors can embed a graph of the latest data in a web page using HTML <img> tags.
• Anyone can use ERDDAPs Slide Sorter to build a personal web page that displays graphs with the latest data (or other images or HTML content), each in its own, draggable slide.
   

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.7725392e+9, 1.7725572e+9;
    String axis "T";
    String calendar "gregorian";
    String comment "unspecified time zone";
    String ioos_category "Time";
    String long_name "time since the beginning of the simulation";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 44.294729650873045, 44.3454048953903;
    String axis "Y";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String ioos_category "Location";
    String long_name "latitude of the particle";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range 9.174013206017287, 9.238991143743347;
    String axis "X";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String ioos_category "Location";
    String long_name "longitude of the particle";
    String standard_name "longitude";
    String units "degrees_east";
  }
  particle_count {
    Int32 _FillValue 2147483647;
    Int32 actual_range 1000, 1000;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String long_name "number of particles in a given timestep";
    String ragged_row_count "particle count at nth timestep";
    String units "1";
  }
  mass {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 0.0;
    String long_name "mass of particle";
    String units "kilograms";
  }
  status_codes {
    Int16 _FillValue 32767;
    Int16 actual_range 2, 2;
    Float64 colorBarMaximum 40.0;
    Float64 colorBarMinimum 0.0;
    String flag_meanings "0:not_released 2:in_water 3:on_land 7:off_maps 10:evaporated 12:to_be_removed 32:on_tideflat";
    Float64 flag_values 0, 2, 3, 7, 10, 12, 32;
    String long_name "particle status code";
  }
  age {
    Float64 _FillValue 9223372036854775807;
    Float64 actual_range 0, 300;
    String long_name "age of particle from time of release";
    String units "minutes";
  }
  density {
    Float64 _FillValue NaN;
    Float64 actual_range 1000.0, 1000.0;
    Float64 colorBarMaximum 200.0;
    Float64 colorBarMinimum 0.0;
    String long_name "emulsion density at end of timestep";
    String units "kg/m^3";
  }
  spill_num {
    UInt16 _FillValue 65535;
    UInt16 actual_range 0, 0;
    String long_name "spill to which the particle belongs";
    String spills_map "0: Surface Point or Line Release,";
  }
  surface_concentration {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 0.003485418847258934;
    String long_name "surface concentration of oil";
    String units "g m-2";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 0.0;
    String axis "Z";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String ioos_category "Location";
    String long_name "particle depth below sea surface";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  id {
    UInt32 _FillValue 999;
    UInt32 actual_range 0, 998;
    String long_name "particle ID";
  }
  viscosity {
    Float64 _FillValue NaN;
    Float64 actual_range 1.0e+12, 1.0e+12;
    String long_name "emulsion viscosity at end of timestep";
    String units "m^2/sec";
  }
 }
  NC_GLOBAL {
    String acquisition_mode "real time";
    String cdm_data_type "Point";
    String comment "Particle output from the NOAA PyGnome model";
    String contributors_email "andrea.mazzino@unige.it; povero@unige.it";
    String contributors_name "Mazzino, Andrea; Povero, Paolo";
    String contributors_orcid "0000-0001-8342-9897; 0000-0003-0170-2891";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creation_date "2026-03-03T12:17:56";
    String creator_email "mattia.cavaiola@gmail.com";
    String creator_name "Cavaiola, Mattia";
    String creator_orcid "0000-0002-1316-9484";
    String creator_type "person";
    String creator_url "https://forecast.meteocean.science";
    String data_doi "10.5281/zenodo.18935380";
    String data_format_original "netCDF";
    String data_version "1";
    String documentation "https://s4raise.it/dssmare/warning_zooplankton/, https://raise-spoke3.s4raise.it/project01https://raise-spoke3.s4raise.it/project11";
    Float64 Easternmost_Easting 9.238991143743347;
    String feature_type "particle_trajectory";
    String featureType "Point";
    Float64 geospatial_lat_max 44.3454048953903;
    Float64 geospatial_lat_min 44.294729650873045;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 9.238991143743347;
    Float64 geospatial_lon_min 9.174013206017287;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 0.0;
    Float64 geospatial_vertical_min 0.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"PyGnome version 1.1.19
2026-04-03T04:29:07Z (local files)
2026-04-03T04:29:07Z https://erddap.s4raise.it/tabledap/unige-dicca_dispersion_forecast_ai.das";
    String infoUrl "https://www.raiseliguria.it/spoke-3/";
    String inspire "Oceanographic geographical features";
    String institution "UNIGE-DICCA";
    String keywords "Surface Currents (b3647731-a71a-4af4-bfa2-e53b61efafeb)";
    String keywords_vocabulary "GCMD Science Keywords";
    String language "XML";
    String license "CC-BY 4.0";
    String maintainer "ETT S.p.A.";
    String naming_authority "RAISE";
    Float64 Northernmost_Northing 44.3454048953903;
    String owner "UNIGE-DICCA";
    String owner_url "https://meteocean.science/";
    String project_code "RAISE";
    String project_id "ECS00000035";
    String project_name "Robotics and AI for Socio-economic Empowerment";
    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)";
    String project_url "https://www.raiseliguria.it/";
    String publisher "ETT S.p.A.";
    String references "TBD";
    String source "Model developed within RAISE Spoke 3 project based on Neural Network and GNOME models";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 44.294729650873045;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "The particle dispersion model used is Gnome. To drive the dispersion simulations, a neural network is first employed to model the sea current for the next six hours, using the wind and current data from the previous six hours as input. The current signal forecasted by the neural network is then used as a forcing input for Gnome to model the particle dispersion.";
    String testOutOfDate "now-1day";
    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 time_coverage_end "2026-03-03T17:00:00Z";
    String time_coverage_start "2026-03-03T12:00:00Z";
    String title "AI-based particle dispersion model";
    String visibility "public";
    Float64 Westernmost_Easting 9.174013206017287;
  }
}

 

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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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