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ERDDAP > griddap > Make A Graph ?

Dataset Title:  Top Dataset, monolevel, air.2m.day.ltm (Daily NARR) [time][y][x], 0001 Subscribe RSS
Institution:  National Centers for Environmental Prediction   (Dataset ID: noaa_esrl_a5d8_2155_b839)
Information:  Summary ? | License ? | Metadata | Background (external link) | Data Access Form
 
Graph Type:  ?
X Axis:  ?
Y Axis:  ?
Color:  ?
 
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time (UTC) ?     specify just 1 value →
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x (m) ?
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   Minimum:   Maximum:   N Sections: 
Y Axis Minimum:   Maximum:   Ascending: 
 
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    [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 -6.21357696e+10, -6.210432e+10;
    String avg_period "0000-00-01 00:00:00";
    String axis "T";
    String coordinate_defines "start";
    String delta_t "0000-00-01 00:00:00";
    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";
  }
  y {
    Float32 actual_range 0.0, 8959788.0;
    String ioos_category "Location";
    String long_name "northward distance from southwest corner of domain in projection coordinates";
    String standard_name "projection_y_coordinate";
    String units "m";
  }
  x {
    Float32 actual_range 0.0, 1.129712e+7;
    String ioos_category "Location";
    String long_name "eastward distance from southwest corner of domain in projection coordinates";
    String standard_name "projection_x_coordinate";
    String units "m";
  }
  air {
    Float32 actual_range 235.3173, 309.4929;
    String cell_methods "time: mean (of 8 3-hourly values in one day)";
    Float64 colorBarMaximum 313.0;
    Float64 colorBarMinimum 263.0;
    Int32 GRIB_id 11;
    String GRIB_name "TMP";
    String grid_mapping "Lambert_Conformal";
    String ioos_category "Temperature";
    String level_desc "2 m";
    String long_name "Daily Air Temperature at 2 m";
    Float32 missing_value -9.96921e+36;
    String parent_stat "Individual Obs";
    Float32 precision 0.003799786;
    String standard_name "air_temperature";
    String statistic "Mean";
    String units "K";
    Float32 valid_range 151.0, 400.0;
    String var_desc "Air temperature";
  }
  NC_GLOBAL {
    String cdm_data_type "Grid";
    Float64 centerlat 50.0;
    Float64 centerlon -107.0;
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    String creator_name "NOAA NCEP";
    String creator_type "institution";
    String creator_url "http://www.ncep.noaa.gov/";
    String dataset_title "NCEP North American Regional Reanalysis (NARR)";
    String history 
"Fri Jul 15 08:54:37 2016: ncrename -v time_bnds,climatological_bnds /Datasets/NARR/Derived/monolevel/air.2m.day.ltm.nc
created 2005 by Jeff Whitaker
2018-08-21T02:06:49Z https://www.esrl.noaa.gov/psd/thredds/dodsC/Datasets/NARR/Derived/monolevel/air.2m.day.ltm.nc
2018-08-21T02:06:49Z http://upwell.pfeg.noaa.gov/griddap/noaa_esrl_a5d8_2155_b839.das";
    String id "Datasets/NARR/Derived/monolevel/air.2m.day.ltm.nchttps://www.esrl.noaa.gov/psd/thredds/dodsC/Datasets/NARR/Derived/monolevel/air.2m.day.ltm.nc";
    String infoUrl "https://www.esrl.noaa.gov/psd/data/gridded/data.narr.html";
    String institution "National Centers for Environmental Prediction";
    String keywords "air, air.2m.day.ltm, air_temperature, atmosphere, atmospheric, centers, daily, data, dataset, day, earth, Earth Science > Atmosphere > Atmospheric Temperature > Air Temperature, Earth Science > Atmosphere > Atmospheric Temperature > Surface Air Temperature, environmental, monolevel, narr, national, prediction, science, surface, temperature, time, top";
    String keywords_vocabulary "GCMD Science Keywords";
    Float32 latcorners 1.000001, 0.897945, 46.3544, 46.63433;
    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.";
    Float32 loncorners -145.5, -68.32005, -2.569891, 148.6418;
    String platform "Model";
    String references "https://www.esrl.noaa.gov/psd/data/gridded/data.narr.html";
    String source "http://www.emc.ncep.noaa.gov/mmb/rreanl/index.html";
    String sourceUrl "https://www.esrl.noaa.gov/psd/thredds/dodsC/Datasets/NARR/Derived/monolevel/air.2m.day.ltm.nc";
    String standard_name_vocabulary "CF Standard Name Table v55";
    Float64 standardpar1 50.0;
    Float64 standardpar2 50.000001;
    String stream "s4";
    String summary "Daily NARR (Top Dataset, monolevel, air.2m.day.ltm)";
    String time_coverage_end "0001-12-31T00:00:00Z";
    String time_coverage_start "0001-01-01T00:00:00Z";
    String title "Top Dataset, monolevel, air.2m.day.ltm (Daily NARR) [time][y][x], 0001";
  }
}

 

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://upwell.pfeg.noaa.gov/erddap/griddap/datasetID.fileType{?query}
For example,
https://upwell.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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