Make A Graph

Dataset Title:	venezia_adriaclim_CMEMS-Reanalysis_1994-2019max
Institution:	ISMAR-CNR, Venice, Italy (Dataset ID: AdriaClim_Veneto_1994-2019_REA_d-max)
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| Data Access Form \| Files

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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)

longitude (degrees_east)

Graph Settings
Color Bar:	Continuity:	Scale:
Minimum:	Maximum:	N Sections:
Draw land mask:
Y Axis Minimum:	Maximum:

(Please be patient. It may take a while to get the data.)

Optional:
Then set the File Type: (File Type information)
and

or view the URL:
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)

Click on the map to specify a new center point.

Zoom:

[The graph you specified. Please be patient.]

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.

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 7.574238e+8, 1.577772e+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 actual_range 10000.0, 10000.0;
    String axis "Z";
    String description "bottom of vertical layers";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String source_name "level";
    String standard_name "depth";
    String units "m";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 45.05, 45.59;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range 12.14, 12.68;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  u_velocity {
    Float32 _FillValue -999.0;
    String cell_methods "time: maximum";
    Float64 colorBarMaximum 0.5;
    Float64 colorBarMinimum -0.5;
    String long_name "Eastward Sea Water Velocity";
    Float32 missing_value -999.0;
    String standard_name "eastward_sea_water_velocity";
    String units "m s-1";
  }
  v_velocity {
    Float32 _FillValue -999.0;
    String cell_methods "time: maximum";
    Float64 colorBarMaximum 0.5;
    Float64 colorBarMinimum -0.5;
    String long_name "Northward Sea Water Velocity";
    Float32 missing_value -999.0;
    String standard_name "northward_sea_water_velocity";
    String units "m s-1";
  }
  salinity {
    Float32 _FillValue -999.0;
    String cell_methods "time: maximum";
    Float64 colorBarMaximum 37.0;
    Float64 colorBarMinimum 32.0;
    String long_name "Sea Water Practical Salinity";
    Float32 missing_value -999.0;
    String standard_name "sea_water_practical_salinity";
    String units "PSU";
  }
  temperature {
    Float32 _FillValue -999.0;
    String cell_methods "time: maximum";
    Float64 colorBarMaximum 32.0;
    Float64 colorBarMinimum 0.0;
    String long_name "Sea Water Temperature";
    Float32 missing_value -999.0;
    String standard_name "sea_water_temperature";
    String units "degree_C";
  }
  mean_wave_period {
    Float32 _FillValue -999.0;
    String cell_methods "time: maximum";
    Float64 colorBarMaximum 20.0;
    Float64 colorBarMinimum 0.0;
    String long_name "Mean Wave Period";
    Float32 missing_value -999.0;
    String standard_name "sea_surface_swell_wave_period";
    String units "s";
  }
  sign_wave_height {
    Float32 _FillValue -999.0;
    String cell_methods "time: maximum";
    Float64 colorBarMaximum 10.0;
    Float64 colorBarMinimum 0.0;
    String long_name "Significant Wave Height";
    Float32 missing_value -999.0;
    String standard_name "sea_surface_wave_significant_height";
    String units "m";
  }
  wave_direction {
    Float32 _FillValue -999.0;
    String cell_methods "time: maximum";
    Float64 colorBarMaximum 360.0;
    Float64 colorBarMinimum 0.0;
    String long_name "Mean Wave Direction";
    Float32 missing_value -999.0;
    String standard_name "sea_surface_wave_to_direction";
    String units "deg";
  }
  NC_GLOBAL {
    String CDI "Climate Data Interface version 1.9.10 (https://mpimet.mpg.de/cdi)";
    String cdm_data_type "Grid";
    String CDO "Climate Data Operators version 1.9.10 (https://mpimet.mpg.de/cdo)";
    String comment "Data restriction: for academic research use only";
    String contact "email: georg.umgiesser@ismar.cnr.it";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    String creator_email "georg.umgiesser@ismar.cnr.it";
    String creator_name "Georg Umgiesser";
    String creator_type "person";
    Float64 Easternmost_Easting 12.68;
    String frequency "day";
    Float64 geospatial_lat_max 45.59;
    Float64 geospatial_lat_min 45.05;
    Float64 geospatial_lat_resolution 0.020000000000000233;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 12.68;
    Float64 geospatial_lon_min 12.14;
    Float64 geospatial_lon_resolution 0.01999999999999997;
    String geospatial_lon_units "degrees_east";
    String history 
"Fri Sep 30 10:44:22 2022: cdo -O mergetime 1994_all_d-max.nc 1995_all_d-max.nc 1996_all_d-max.nc 1997_all_d-max.nc 1998_all_d-max.nc 1999_all_d-max.nc 2000_all_d-max.nc 2001_all_d-max.nc 2002_all_d-max.nc 2003_all_d-max.nc 2004_all_d-max.nc 2005_all_d-max.nc 2006_all_d-max.nc 2007_all_d-max.nc 2008_all_d-max.nc 2009_all_d-max.nc 2010_all_d-max.nc 2011_all_d-max.nc 2012_all_d-max.nc 2013_all_d-max.nc 2014_all_d-max.nc 2015_all_d-max.nc 2016_all_d-max.nc 2017_all_d-max.nc 2018_all_d-max.nc 2019_all_d-max.nc AdriaClim_Veneto_1994-2019_REA_d-max.nc
Thu Sep 29 12:29:33 2022: cdo daymax all.nc 1994_all_d-max.nc
Thu Sep 29 12:29:29 2022: cdo merge hydro.nc ts.nc wave.nc all.nc
Thu Sep 29 12:26:20 2022: ncks -C -x -v total_depth out.nc hydro.nc
created on 2022-09-29 12:25:33 MET
2024-11-10T02:13:45Z (local files)
2024-11-10T02:13:45Z http://erddap.ve.ismar.cnr.it/griddap/AdriaClim_Veneto_1994-2019_REA_d-max.das";
    String infoUrl "???";
    String institution "ISMAR-CNR, Venice, Italy";
    String keywords "adriaclim, circulation, cmems, cmems-reanalysis, cnr, council, currents, data, density, direction, earth, Earth Science > Oceans > Ocean Circulation > Ocean Currents, Earth Science > Oceans > Ocean Temperature > Water Temperature, Earth Science > Oceans > Ocean Waves > Significant Wave Height, Earth Science > Oceans > Ocean Waves > Swells, Earth Science > Oceans > Ocean Waves > Wave Period, Earth Science > Oceans > Ocean Waves > Wave Speed/Direction, Earth Science > Oceans > Salinity/Density > Salinity, eastward, eastward_sea_water_velocity, height, ismar, ismar-cnr, italy, level, mean, mean_wave_period, national, northward, northward_sea_water_velocity, ocean, oceans, period, practical, reanalysis, research, salinity, science, sea, sea_surface_swell_wave_period, sea_surface_wave_significant_height, sea_surface_wave_to_direction, sea_water_practical_salinity, sea_water_temperature, seawater, sign_wave_height, significant, speed, surface, swell, swells, temperature, time, u_velocity, v_velocity, velocity, venezia, venice, water, wave, wave_direction, waves";
    String keywords_vocabulary "GCMD Science Keywords";
    String license 
"The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.";
    String NCO "netCDF Operators version 4.9.7 (Homepage = http://nco.sf.net, Code = https://github.com/nco/nco)";
    Float64 Northernmost_Northing 45.59;
    String references "Model info: http://www.ismar.cnr.it/shyfem";
    String source "Model data produced by SHYFEM at ISMAR-CNR";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 45.05;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "Data restriction: for academic research use only";
    String time_coverage_end "2019-12-31T06:00:00Z";
    String time_coverage_start "1994-01-01T11:30:00Z";
    String title "venezia_adriaclim_CMEMS-Reanalysis_1994-2019max";
    Float64 Westernmost_Easting 12.14;
  }
}

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.