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Dataset Title:  adriaclim_CNR-Veneto_MHW_2020.nc Subscribe RSS
Institution:  ISMAR-CNR, Venice, Italy   (Dataset ID: Adriaclim_CNR_Veneto_MHW2020)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
 
Dimensions ? Start ? Stride ? Stop ?  Size ?    Spacing ?
 latitude (degrees_north) ?      45    0.01 (even)
  < slider >
 longitude (degrees_east) ?      44    0.01 (even)
  < slider >
 
Grid Variables (which always also download all of the dimension variables) 
 cum_mhw_int (Cumulative MHW intensity over a year, deg. C x days) ?

File type: (more information)

(Documentation / Bypass this form) ?
 
(Please be patient. It may take a while to get the data.)


 

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 45.13, 45.57;
    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, 12.57;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  cum_mhw_int {
    Float32 _FillValue -999.0;
    Float64 colorBarMaximum 130.0;
    Float64 colorBarMinimum 0.0;
    String long_name "Cumulative MHW intensity over a year";
    String standard_name "cumulative_mhw_intensity";
    String units "deg. C x days";
  }
  NC_GLOBAL {
    String _NCProperties "version=2,netcdf=4.7.3,hdf5=1.10.4";
    String cdm_data_type "Grid";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    String creator_email "christian.ferrarin@cnr.it";
    String creator_name "Christian Ferrarin";
    String creator_type "person";
    Float64 Easternmost_Easting 12.57;
    Float64 geospatial_lat_max 45.57;
    Float64 geospatial_lat_min 45.13;
    Float64 geospatial_lat_resolution 0.009999999999999948;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 12.57;
    Float64 geospatial_lon_min 12.14;
    Float64 geospatial_lon_resolution 0.009999999999999993;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-11-21T12:10:14Z (local files)
2024-11-21T12:10:14Z http://erddap.ve.ismar.cnr.it/erddap/griddap/Adriaclim_CNR_Veneto_MHW2020.das";
    String infoUrl "https://www.ismar.cnr.it";
    String institution "ISMAR-CNR, Venice, Italy";
    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.";
    Float64 Northernmost_Northing 45.57;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 45.13;
    String summary "Data restriction: for academic research use only";
    String title "adriaclim_CNR-Veneto_MHW_2020.nc";
    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.

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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