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Dataset Title:  Daily hindcast of MITgcm-BFM Model simulation of the Northern Adriatic Sea for
the year 2024 (Zonal velocity), produced in the framework of the MER Project.
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Institution:  OGS - Trieste   (Dataset ID: itineris_NAD_MER_daily_zonal_velocity)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
 
Graph Type:  ?
X Axis:  ?
Y Axis:  ?
Color:  ?
 
Dimensions ?    Start ?    Stop ?
time (UTC) ?     specify just 1 value →
    |< - >|
< <
depth (m) ?     specify just 1 value →
    |< -
< <
latitude (degrees_north) ?
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< slider >
longitude (degrees_east) ?
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< slider >
 
Graph Settings
Color Bar:   Continuity:   Scale: 
   Minimum:   Maximum:   N Sections: 
Draw land mask: 
Y Axis Minimum:   Maximum:   
 
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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:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.7041536e+9, 1.7356896e+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";
    String units_long "Seconds Since 1970-01-01";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 actual_range 0.5308958889854694, 271.37629539912086;
    String axis "Z";
    String description "bottom of vertical layers";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range 42.75260517821568, 45.872396844882346;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range 12.106771461596368, 17.934896461596367;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  zonal_velocity {
    UInt32 _ChunkSizes 46, 5, 75, 140;
    Float32 _FillValue 1.0e+20;
    Float64 colorBarMaximum 0.5;
    Float64 colorBarMinimum -0.5;
    String discipline "Physical Oceanography";
    String ecv "ECV - Ocean, Physical: Ocean Currents";
    String ecv_uri "https://gcos.wmo.int/site/global-climate-observing-system-gcos/essential-climate-variables/ocean-currents";
    String ioos_category "Currents";
    Float32 missing_value 1.0e+20;
    String parameter_sdn_name "Northward Sea Water Velocity";
    String parameter_sdn_uri "https://vocab.nerc.ac.uk/collection/P01/current/VOCE/";
    String parameter_sdn_urn "SDN:P01::VOCE";
    String standard_name "northward_sea_water_velocity";
    String unit_sdn_name "Metres per second";
    String unit_sdn_uri "https://vocab.nerc.ac.uk/collection/P06/current/UMETPS/";
    String unit_sdn_urn "urn:sdn:P06::UMETPS";
    String units "m s-1";
  }
  NC_GLOBAL {
    String _NCProperties "version=2,netcdf=4.9.3,hdf5=1.14.6";
    String cdm_data_type "Grid";
    String Conventions "CF-1.10, COARDS, ACDD-1.3";
    String creator_email "squerin@ogs.it";
    String creator_name "Stefano Querin";
    String creator_type "person";
    String creator_url "https://www.ogs.it/it/users/stefano-querin";
    String data_creation "2025-04-07";
    String data_format_original "NetCDF";
    String data_type "Grid";
    String data_update "2026-01-30";
    String data_update_frequence "never";
    String data_version "nan";
    Float64 Easternmost_Easting 17.934896461596367;
    String format "netCDF";
    Float64 geospatial_lat_max 45.872396844882346;
    Float64 geospatial_lat_min 42.75260517821568;
    Float64 geospatial_lat_resolution 0.00520833333333333;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 17.934896461596367;
    Float64 geospatial_lon_min 12.106771461596368;
    Float64 geospatial_lon_resolution 0.005208333333333332;
    String geospatial_lon_units "degrees_east";
    String history 
"2026-09-08T13:56:15Z (local files)
2026-09-08T13:56:15Z http://laguna.ogs.it/griddap/itineris_NAD_MER_daily_zonal_velocity.das";
    String identifier "\"null\"";
    String infoUrl "\"null\"";
    String inspire "Oceanographic geographical features";
    String institution "OGS - Trieste";
    String institution_edmo_code "150";
    String institution_edmo_uri "https://edmo.seadatanet.org/report/150";
    String institution_ror_code "04y4t7k95";
    String institution_ror_uri "https://ror.org/04y4t7k95";
    String keywords "hydrodynamics, MER, MITgcm-BFM, Northern Adriatic Sea";
    String keywords_vocabulary "GCMD Science Keywords,GCOS Essential Climate Variables";
    String license "CC-BY 4.0";
    String license_url "https://creativecommons.org/licenses/by/4.0/";
    String naming_authority "\"null\"";
    Float64 Northernmost_Northing 45.872396844882346;
    String platform_name "MITgcm Model";
    String platform_organization_managing "OGS - Trieste";
    String platform_organization_owning "OGS - Trieste";
    String platform_reference_person "Stefano Querin";
    String project_code "IR0000032";
    String Project_DOI "\"null\"";
    String project_edmerp "\"null\"";
    String project_edmerp_uri "\"null\"";
    String project_id "\"null\"";
    String project_name "\"null\"";
    String project_statement "\"null\"";
    String RI_abstract "The International Centre for Advanced Studies on River-Sea Systems (DANUBIUS-RI) is a distributed research infrastructure building on existing expertise to support interdisciplinary research on large river-sea (RS) systems.";
    String RI_coordin_organization "GeoEcoMar";
    String RI_coordin_organization_edmo_code "850";
    String RI_coordin_organization_edmo_uri "https://edmo.seadatanet.org/report/850";
    String RI_coordinating_person "Adrian Stanica";
    String RI_geographical_coverage "European mainland,Mediterranean Region,Northeast Atlantic Ocean";
    String RI_name "DANUBIUS-RI - International Centre for Advanced Studies on River-Sea Systems";
    String RI_short_name "DANUBIUS-RI";
    String RI_start_date "2016-03-16";
    String source "Model data produced by MITgcm-BFM at OGS - Trieste";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 42.75260517821568;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "OGS_OCE_NAD_MER_ANALYSIS_PHYS: The dataset contains the variables of temperature, salinity and water currents in hindcast mode for the year 2024, covering the Northern Adriatic Sea domain. The data and information were produced in the framework of the MER Project (Investment M2C4 - I3.5 of the PNRR under the NextGenerationEU Programme).";
    String time_coverage_end "2025-01-01T00:00:00Z";
    String time_coverage_start "2024-01-02T00:00:00Z";
    String title "Daily hindcast of MITgcm-BFM Model simulation of the Northern Adriatic Sea for the year 2024 (Zonal velocity), produced in the framework of the MER Project.";
    Float64 Westernmost_Easting 12.106771461596368;
  }
}

 

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.

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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