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Dataset Title:  SDC_GlobalOcean_Climatology_TS_V1_2 Subscribe RSS
Institution:  SeaDataNet   (Dataset ID: SDC_GLO_CLIM_TS_V1_2)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form
 
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) ?
    +
    -
< slider >
longitude (degrees_east) ?
    +
    -
< slider >
 
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:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.2636e+9, 1.2924576e+9;
    String axis "T";
    String calendar "standard";
    String climatology "climatology_bounds";
    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";
    Int16 actual_range 0, 36;
    String axis "Z";
    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 -80.0, 80.0;
    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 -180.0, 179.75;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Temperature {
    Float32 _FillValue 9.96921e+36;
    String cell_methods "time: mean within years time: mean over years";
    Float64 colorBarMaximum 32.0;
    Float64 colorBarMinimum 0.0;
    String long_name "sea water temperature";
    Float32 missing_value 9.96921e+36;
    String standard_name "sea_water_temperature";
    String units "degree_C";
  }
  Temperature_L1 {
    Float32 _FillValue 9.96921e+36;
    Float64 colorBarMaximum 5.0;
    Float64 colorBarMinimum 0.0;
    String long_name "sea water temperature masked using relative error threshold 0.3";
    Float32 missing_value 9.96921e+36;
    String standard_name "sea_water_temperature";
    String units "degree_C";
  }
  Temperature_L2 {
    Float32 _FillValue 9.96921e+36;
    Float64 colorBarMaximum 5.0;
    Float64 colorBarMinimum 0.0;
    String long_name "sea water temperature masked using relative error threshold 0.5";
    Float32 missing_value 9.96921e+36;
    String standard_name "sea_water_temperature";
    String units "degree_C";
  }
  Temperature_relerr {
    Float32 _FillValue 9.96921e+36;
    Float64 colorBarMaximum 0.1;
    Float64 colorBarMinimum 0.0;
    String long_name "Relative error of sea water temperature";
    Float32 missing_value 9.96921e+36;
    String units "1";
    Float32 valid_max 1.0;
    Float32 valid_min 0.0;
  }
  Salinity {
    Float32 _FillValue 9.96921e+36;
    String cell_methods "time: mean within years time: mean over years";
    Float64 colorBarMaximum 37.0;
    Float64 colorBarMinimum 32.0;
    String long_name "sea water salinity";
    Float32 missing_value 9.96921e+36;
    String standard_name "sea_water_practical_salinity";
    String units "PSU";
  }
  Salinity_L1 {
    Float32 _FillValue 9.96921e+36;
    Float64 colorBarMaximum 1.0;
    Float64 colorBarMinimum 0.0;
    String long_name "sea water salinity masked using relative error threshold 0.3";
    Float32 missing_value 9.96921e+36;
    String standard_name "sea_water_practical_salinity";
    String units "PSU";
  }
  Salinity_L2 {
    Float32 _FillValue 9.96921e+36;
    Float64 colorBarMaximum 1.0;
    Float64 colorBarMinimum 0.0;
    String long_name "sea water salinity masked using relative error threshold 0.5";
    Float32 missing_value 9.96921e+36;
    String standard_name "sea_water_practical_salinity";
    String units "PSU";
  }
  Salinity_relerr {
    Float32 _FillValue 9.96921e+36;
    Float64 colorBarMaximum 0.1;
    Float64 colorBarMinimum 0.0;
    String long_name "Relative error of sea water salinity";
    Float32 missing_value 9.96921e+36;
    String units "1";
    Float32 valid_max 1.0;
    Float32 valid_min 0.0;
  }
  NC_GLOBAL {
    String abstract "SDC_GLO_CLIM_T_2003-2017_025_September_V1_2 product contains Temperature Climatologies for Global Ocean for period 2003-2017.  The climatic fields were computed from World Ocean Database 2013 data set. The computation was done with the DIVAnd (Data-Interpolating Variational Analysis), version 2.3.1";
    String acknowledgement "EC H2020 grant #730960 SeaDataCloud";
    String area_keywords "World";
    String area_keywords_urn "SDN:C19::SVX00025";
    String Author_e_mail "kanwal.shahzadi@studio.unibo.it";
    String bathymetry_source "The GEBCO Digital Atlas published by the British Oceanographic Data Centre on behalf of IOC and IHO, 2003";
    String cdm_data_type "Grid";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    String creator_name "University of Bologna";
    String creator_type "institution";
    String creator_url "https://dx.doi.org/doi_of_doc";
    String data_access "http://sdn.oceanbrowser.net/data/SeaDataCloud-domains";
    String date "2019-06-11T00:02:34";
    String documentation "https://dx.doi.org/doi_of_doc";
    String doi "http://dx.doix.org/10.12770/f632d0d4-3373-43a4-a6be-d2109ebe0177";
    Float64 Easternmost_Easting 179.75;
    String file_name "/Volumes/LaCie/DataOutput/CLIMATOLOGIES_JUNE_2019/SDC_GLO_CLIM_T_V1_2_2003_2017_025/September/DIVA_Output/SDC_GLO_CLIM_T_V1_2_2003_2017_025_September_1.nc";
    Float64 geospatial_lat_max 80.0;
    Float64 geospatial_lat_min -80.0;
    Float64 geospatial_lat_resolution 0.25;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 179.75;
    Float64 geospatial_lon_min -180.0;
    Float64 geospatial_lon_resolution 0.25;
    String geospatial_lon_units "degrees_east";
    String history 
"Wed Jul  3 10:35:06 2019: ncatted -a history,global,d,, /Volumes/DataBackup/DataOutput/SDC_GLO_CLIM_TS_V1/UNIBO_SEXTANT_OUTPUT/SDC_GLO_CLIM_T_V1_2_2003_2017_025//SDC_GLO_CLIM_T_V1_2_2003_2017_025_September.nc
2024-03-29T08:33:02Z (local files)
2024-03-29T08:33:02Z https://erddap.ifremer.fr/griddap/SDC_GLO_CLIM_TS_V1_2.das";
    String infoUrl "https://dx.doi.org/doi_of_doc";
    String institution "SeaDataNet";
    String institution_urn "SDN:EDMO::4969";
    String keywords "analysis, bologna, data, database, depth, diva, earth, Earth Science > Oceans > Ocean Temperature > Water Temperature, error, masked, ocean, oceans, relative, science, sea, sea_water_temperature, seawater, temperature, Temperature_L1, Temperature_L2, Temperature_relerr, threshold, time, university, using, water, wod, world";
    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.";
    Int32 nco_openmp_thread_number 1;
    Float64 Northernmost_Northing 80.0;
    String parameter_keyword "ITS-90 water temperature";
    String parameter_keyword_urn "SDN:P35::WATERTEMP";
    String product_code "SDC_GLO_CLIM_T_2003_2017_025_September";
    String product_id "73606c5a-8bcb-11e9-288e-5b579837f948";
    String product_version "1.0";
    String production "University of Bologna, Bologna, Italy";
    String project "SeaDataCloud";
    String search_keywords "Temperature of the water column";
    String search_keywords_urn "SDN:P02::TEMP";
    String source "Observational data from World Ocean Database 2013";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -80.0;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "SDC_GLO_CLIM_T_2003-2017_025_January_V1_2 product contains Temperature Climatologies for Global Ocean for period 2003-2017. The climatic fields were computed from World Ocean Database 2013 data set. The computation was done with the DIVAnd (Data-Interpolating Variational Analysis), version 2.3.1";
    String time_coverage_end "2010-12-16T00:00:00Z";
    String time_coverage_start "2010-01-16T00:00:00Z";
    String title "SDC_GlobalOcean_Climatology_TS_V1_2";
    String WEB_visualisation "http://sdn.oceanbrowser.net/web-vis/";
    Float64 Westernmost_Easting -180.0;
  }
}

 

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.

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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