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ERDDAP > griddap > Make A Graph ?

Dataset Title:  Sea Ice Lat-Lon Grid, OSI SAF EUMETSAT, Antarctic, Polar Stereographic, 10km Subscribe RSS
Institution:  EUMETSAT OSI SAF   (Dataset ID: eumetsat_osisaf_grid_sh_ps)
Information:  Summary ? | License ? | Metadata | Background (external link) | Data Access Form
 
Graph Type:  ?
X Axis:  ?
Y Axis:  ?
Color:  ?
 
Dimensions ?    Start ?    Stop ?
yc (km) ?
    +
    -
< slider >
xc (km) ?
    |< - +
    - + >|
< slider >
 
Graph Settings
Color Bar:   Continuity:   Scale: 
   Minimum:   Maximum:   N Sections: 
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 ? )
    [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 {
  yc {
    Float64 actual_range -3945.0, 4345.0;
    String axis "Y";
    String ioos_category "Location";
    String long_name "y coordinate in Cartesian system";
    String standard_name "projection_y_coordinate";
    String units "km";
  }
  xc {
    Float64 actual_range -3945.0, 3945.0;
    String axis "X";
    String ioos_category "Location";
    String long_name "x coordinate in Cartesian system";
    String standard_name "projection_x_coordinate";
    String units "km";
  }
  lat {
    Float64 colorBarMaximum 0.0;
    Float64 colorBarMinimum -90.0;
    String ioos_category "Location";
    String long_name "latitude coordinate";
    String standard_name "latitude";
    String units "degrees_north";
  }
  lon {
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String ioos_category "Location";
    String long_name "longitude coordinate";
    String standard_name "longitude";
    String units "degrees_east";
  }
  NC_GLOBAL {
    String abstract "The daily analysis of sea ice concentration is obtained from operation satellite images of the polar regions. It is based on atmospherically corrected signal and a carefully selected sea ice concentration algorithm. This product is freely available from the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF).";
    String activity_type "Space borne instrument";
    String area "Southern Hemisphere";
    String cdm_data_type "Grid";
    String contact "osisaf-manager@met.no";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    String copyright_statement "Copyright 2021 EUMETSAT";
    String creator_email "osisaf-manager@met.no";
    String creator_name "EUMETSAT";
    String creator_type "institution";
    String creator_url "https://www.eumetsat.int/website/home/index.html";
    String defaultGraphQuery "lat%5B%285845.0%29%3A%28-5345.0%29%5D%5B%28-3845.0%29%3A%283745.0%29%5D%26.draw%3Dsurface%26.vars%3Dxc%257Cyc%257Clat%26.colorBar%3DKT_gray";
    String distribution_statement "Free";
    String gcmd_keywords 
"Cryosphere > Sea Ice > Sea Ice Concentration
Oceans > Sea Ice > Sea Ice Concentration
Geographic Region > Southern Hemisphere
Vertical Location > Sea Surface
EUMETSAT/OSISAF > Satellite Application Facility on Ocean and Sea Ice, European Organisation for the Exploitation of Meteorological Satellites";
    String history 
"2021-11-14 creation
2021-12-09T06:50:59Z https://thredds.met.no/thredds/dodsC/osisaf/met.no/ice/conc_sh_pol_agg
2021-12-09T06:50:59Z https://polarwatch.noaa.gov/griddap/eumetsat_osisaf_grid_sh_ps.das";
    String infoUrl "https://thredds.met.no/thredds/dodsC/osisaf/met.no/ice/conc_sh_pol_agg.html";
    String institution "EUMETSAT OSI SAF";
    String instrument_type "Multi-sensor analysis";
    String keywords "agg, analysis, application, climate, conc, concentration, coordinate, daily, data, day, eumetsat, european, exploitation, facility, ice, laboratory, latitude, longitude, meteorological, meteorology, ocean, oceanographic, oceanography, organisation, osi, osisaf, pol, proudman, remote sensing, saf, satellite, satellites, sea, sea ice, sea ice concentration";
    String license "Free";
    String netcdf_version "3.6.3";
    String PI_name "Rasmus Tonboe";
    String platform_name "Multi-sensor analysis";
    String product_id "OSI-401";
    String product_name "osi_saf_ice_conc";
    String product_status "operational";
    String product_version "4.0";
    String project_name "EUMETSAT OSI SAF";
    String references 
"Product User Manual for OSI SAF Global Sea Ice Concentration, 
Rasmus Tonboe et al. (editor)
 v1.4, May 2017
 http://www.osi-saf.org";
    String software_version "1.3";
    String sourceUrl "https://thredds.met.no/thredds/dodsC/osisaf/met.no/ice/conc_sh_pol_agg";
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "The daily analysis of sea ice concentration is obtained from operation satellite images of the polar regions. It is based on atmospherically corrected signal and a carefully selected sea ice concentration algorithm. This product is freely available from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSI SAF).";
    String title "Sea Ice Lat-Lon Grid, OSI SAF EUMETSAT, Antarctic, Polar Stereographic, 10km";
    String topiccategory "Oceans Climatology Meteorology Atmosphere";
  }
}

 

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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