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Dataset Title:  Daily Chl of NEMO_MED12-Eco3M simulation by Guyennon et al. (2015) Subscribe RSS
Institution:  MIO UMR7294 CNRS / OSU Pytheas   (Dataset ID: simu_guyennon_daily_chl)
Information:  Summary ? | License ? | 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 →
    |< -
< <
y (count) ?
    +
    -
< slider >
x (count) ?
    +
    -
< 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 {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 9.46728e+8, 9.518256e+8;
    String axis "T";
    String calendar "gregorian";
    String ioos_category "Time";
    String long_name "Time axis";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String title "Time";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float32 actual_range 0.4940254, 318.1274;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String title "deptht";
    String units "m";
    Float32 valid_max 5727.9165;
    Float32 valid_min 0.49402538;
  }
  y {
    Int16 actual_range 0, 263;
    String ioos_category "Location";
    String long_name "Y";
    String units "count";
  }
  x {
    Int16 actual_range 0, 566;
    String ioos_category "Location";
    String long_name "X";
    String units "count";
  }
  Chltot {
    Float32 _FillValue 9.96921e+36;
    Float32 interval_operation 1200.0;
    Float32 interval_write 86400.0;
    String ioos_category "Unknown";
    String long_name "Chltot";
    String online_operation "ave(X)";
    String standard_name "chltot";
  }
  nav_lon {
    String ioos_category "Location";
    String long_name "Longitude";
    String nav_model "Default grid";
    String standard_name "longitude";
    Float32 valid_max 36.234074;
    Float32 valid_min -11.069905;
  }
  nav_lat {
    String ioos_category "Location";
    String long_name "Latitude";
    String nav_model "Default grid";
    String standard_name "latitude";
    Float32 valid_max 46.186768;
    Float32 valid_min 30.02892;
  }
  NC_GLOBAL {
    String cdm_data_type "Grid";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    String file_name "/workgpfs/rech/ron/rron962/chlt200002/Chlt_2000_02.nc";
    String history 
"Fri Nov 21 15:35:37 2014: ncks -O -d deptht,0,28 -v Chltot Chlt_2000_02.nc Chlt_2000_02_extr.nc
2024-12-07T09:15:40Z (local files)
2024-12-07T09:15:40Z http://erddap.osupytheas.fr/griddap/simu_guyennon_daily_chl.das";
    String infoUrl "http://www.biogeosciences.net/12/7025/2015/";
    String institution "MIO UMR7294 CNRS / OSU Pytheas";
    String keywords "bloom, Eco3M, NEMO-MED12, surface chlorophyll";
    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 "4.4.2";
    String production "An IPSL model";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v29";
    String summary "Daily Chl of NEMO_MED12-Eco3M simulation by Guyennon et al. (2015)";
    String time_coverage_end "2000-02-29T12:00:00Z";
    String time_coverage_start "2000-01-01T12:00:00Z";
    String TimeStamp "2014-JUN-06 06:54:12 GMT+0200";
    String title "Daily Chl of NEMO_MED12-Eco3M simulation by Guyennon et al. (2015)";
  }
}

 

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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