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Dataset Title:  Great Lakes GLSEA & NIC Ice. NOAA/GLERL/COASTWATCH data from a local source. Subscribe RSS
Institution:  NOAA/GLERL/COASTWATCH   (Dataset ID: test_greg)
Information:  Summary ? | License ? | Metadata | Background (external link) | Data Access Form
Graph Type:  ?
X Axis:  ?
Y Axis:  ?
Color:  ?
Dimensions ?    Start ?    Stop ?
time (UTC) ?
    << - +
    - >>
< slider >
nx (count) ?     specify just 1 value →
    << -
< <
ny (count) ?     specify just 1 value →
    << -
< <
Graph Settings
Marker Type:   Size: 
Color Bar:   Continuity:   Scale: 
   Minimum:   Maximum:   N Sections: 
Y Axis Minimum:   Maximum:   Ascending: 
(Please be patient. It may take a while to get the data.)
Then set the File Type: (File Type information)
or view the URL:
(Documentation / Bypass this form ? )
    Time range:    <<    -              
[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 1.5147648e+9, 1.5462144e+9;
    String axis "T";
    String base_date "1970,1,1,0";
    String ioos_category "Time";
    String long_name "UTC";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  nx {
    Int16 actual_range 0, 1023;
    String ioos_category "Statistics";
    String long_name "NX";
    String units "count";
  ny {
    Int16 actual_range 0, 1023;
    String ioos_category "Statistics";
    String long_name "NY";
    String units "count";
  temp {
    Float64 colorBarMaximum 32.0;
    Float64 colorBarMinimum 0.0;
    String comment "negative values indicate ice fraction (0-1)";
    String ioos_category "Temperature";
    String long_name "Temperature";
    Float32 missing_value -99999.0;
    String standard_name "sea_water_temperature";
    String units "degree_C";
    String author "";
    String cdm_data_type "Grid";
    String comment "Great Lakes GLSEA & NIC Ice";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creation_date "Mon Feb 11 13:59:20 2019 GMT";
    String creator_email "";
    String creator_name "Gregory Lang";
    String creator_type "person";
    String creator_url "";
    String disclaimer "";
    String history 
"2019-04-23T02:52:37Z (local files)
    String infoUrl "";
    String institution "NOAA/GLERL/COASTWATCH";
    String keywords "coastwatch, data, earth, Earth Science > Oceans > Ocean Temperature > Water Temperature, environmental, glerl, glsea, great, great lakes, ice, laboratory, lakes, local, nic, noaa, ocean, oceans, research, science, sea, sea_water_temperature, seawater, source, temperature, time, water";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "";
    String references "";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v29";
    String summary "Great Lakes GLSEA & NIC Ice. NOAA/GLERL/COASTWATCH data from a local source.";
    String time_coverage_end "2018-12-31T00:00:00Z";
    String time_coverage_start "2018-01-01T00:00:00Z";
    String title "Great Lakes GLSEA & NIC Ice. NOAA/GLERL/COASTWATCH data from a local source.";


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{?query}
For example,[(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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