Make A Graph

Dataset Title:	AdriaClim RESM - Indicators - NEMO - MHW 2031-2050
Institution:	CMCC (Dataset ID: adriaclim_resm_indicators_mhw_nemo_2050)
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 →

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:
(Documentation / Bypass this form

)

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 2.524608e+9, 2.524608e+9;
    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 units "seconds since 1970-01-01T00:00:00Z";
  }
  latitude {
    UInt32 _ChunkSizes 331;
    String _CoordinateAxisType "Lat";
    Float32 actual_range 39.0, 45.875;
    String axis "Y";
    String cell_methods "x: mean";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    UInt32 _ChunkSizes 432;
    String _CoordinateAxisType "Lon";
    Float32 actual_range 12.0, 20.97917;
    String axis "X";
    String cell_methods "y: mean";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  mhw_mean_number {
    UInt32 _ChunkSizes 331, 432;
    Float64 _FillValue 1.0e+20;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Statistics";
    String long_name "Mean number of MHW per year";
    String standard_name "mhw_mean_number";
    String units "count";
  }
  mhw_mean_number_trend {
    UInt32 _ChunkSizes 331, 432;
    Float64 _FillValue 1.0e+20;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Statistics";
    String long_name "Trend of number of MHW per year";
    String standard_name "mhw_mean_number_trend";
    String units "count";
  }
  mhw_mean_duration {
    UInt32 _ChunkSizes 331, 432;
    Float64 _FillValue 1.0e+20;
    String ioos_category "Time";
    String long_name "Mean duration of MHW per year";
    String standard_name "mhw_mean_duration";
    String units "days";
  }
  mhw_mean_duration_trend {
    UInt32 _ChunkSizes 331, 432;
    Float64 _FillValue 1.0e+20;
    String ioos_category "Time";
    String long_name "Trend of duration of MHW per year";
    String standard_name "mhw_mean_duration_trend";
    String units "days";
  }
  mhw_mean_intensity {
    UInt32 _ChunkSizes 331, 432;
    Float64 _FillValue 1.0e+20;
    Float64 colorBarMaximum 40.0;
    Float64 colorBarMinimum -10.0;
    String ioos_category "Temperature";
    String long_name "Mean max. intensity of MHW per year";
    String standard_name "mhw_mean_intensity";
    String units "degree_C";
  }
  mhw_mean_intensity_trend {
    UInt32 _ChunkSizes 331, 432;
    Float64 _FillValue 1.0e+20;
    Float64 colorBarMaximum 40.0;
    Float64 colorBarMinimum -10.0;
    String ioos_category "Temperature";
    String long_name "Trend of max. intensity of MHW per year";
    String standard_name "mhw_mean_intensity_trend";
    String units "degree_C";
  }
  NC_GLOBAL {
    String adriaclim_dataset "indicator";
    String adriaclim_model "NEMO";
    String adriaclim_scale "adriatic";
    String adriaclim_timeperiod "20y";
    String adriaclim_type "anomaly, trend";
    String CDI "Climate Data Interface version 1.9.8 (https://mpimet.mpg.de/cdi)";
    String cdm_data_type "Grid";
    String CDO "Climate Data Operators version 1.9.8 (https://mpimet.mpg.de/cdo)";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creation_date "2023/03/29 14:40";
    String creator_name "Euro-Mediterranean Centre for Climate Change - CMCC";
    String creator_type "institution";
    String creator_url "https://www.ec.gc.ca/scitech/default.asp?lang=En&n=61B33C26-1#cmc";
    String description "Created with create_MHW_mean_AdriaClim.py using the MHW algorithm described by Hobday et al. (2016) and freely available.";
    Float64 Easternmost_Easting 20.97917;
    Float64 geospatial_lat_max 45.875;
    Float64 geospatial_lat_min 39.0;
    Float64 geospatial_lat_resolution 0.020833333333333332;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 20.97917;
    Float64 geospatial_lon_min 12.0;
    Float64 geospatial_lon_resolution 0.020833341067285384;
    String geospatial_lon_units "degrees_east";
    String history 
"Thu Apr 13 10:41:41 2023: cdo chname,nav_lon,lon,nav_lat,lat mid.nc mid1.nc
Thu Apr 13 10:41:24 2023: ncks -A -v nav_lat lat.nc mid.nc
Thu Apr 13 10:41:14 2023: ncks -A -v nav_lon lon.nc mid.nc
Thu Apr 13 10:40:26 2023: ncks -C -O -x -v lon,lat AdriaClim_NEMO_MHW_METRICS_2031_2050.nc mid.nc
Wed Apr 12 12:59:25 2023: ncrename -O -d x,lon -d y,lat AdriaClim_NEMO_MHW_METRICS_2031_2050.nc
2024-09-18T10:15:08Z (local files)
2024-09-18T10:15:08Z https://erddap-adriaclim.cmcc-opa.eu/griddap/adriaclim_resm_indicators_mhw_nemo_2050.das";
    String history_of_appended_files 
"Thu Apr 13 10:41:24 2023: Appended file lat.nc had following \"history\" attribute:
Fri Sep 30 17:59:47 2022: ncrename -O -d y,lat lat1.nc
Fri Sep 30 17:59:47 2022: ncwa -a x lat.nc lat1.nc
Fri Sep 30 17:59:47 2022: ncks -v nav_lat 1993/ADRIACLIM2_1d_19930101_grid_T.nc lat.nc
Thu Apr 13 10:41:14 2023: Appended file lon.nc had following \"history\" attribute:
Fri Sep 30 17:59:47 2022: ncrename -O -d x,lon lon1.nc
Fri Sep 30 17:59:47 2022: ncwa -a y lon.nc lon1.nc
Fri Sep 30 17:59:47 2022: ncks -v nav_lon 1993/ADRIACLIM2_1d_19930101_grid_T.nc lon.nc
";
    String infoUrl "https://cmcc.it";
    String institution "CMCC";
    String keywords "adriaclim, centre, change, climate, cmcc, data, duration, euro, euro-mediterranean, heat, intensity, marine, max, mean, mediterranean, mhw, mhw_mean_duration, mhw_mean_duration_trend, mhw_mean_intensity, mhw_mean_intensity_trend, mhw_mean_number, mhw_mean_number_trend, number, per, statistics, temperature, time, trend, waves, year";
    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 4.9.3 (Homepage = http://nco.sf.net, Code = https://github.com/nco/nco)";
    Float64 Northernmost_Northing 45.875;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 39.0;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "AdriaClim RESM - Indicators - NEMO - MHW 2031-2050";
    String time_coverage_end "2050-01-01T00:00:00Z";
    String time_coverage_start "2050-01-01T00:00:00Z";
    String title "AdriaClim RESM - Indicators - NEMO - MHW 2031-2050";
    Float64 Westernmost_Easting 12.0;
  }
}

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.