NOAA ERDDAP
Easier access to scientific data
   
Brought to you by NOAA NMFS SWFSC ERD    

ERDDAP > griddap > Make A Graph ?

Dataset Title:  Great Lakes Coastal Forecasting System (GLCFS), FORECAST Subscribe RSS
Institution:  NOAA/GLERL   (Dataset ID: GLOS_ONTARIO_3D_FORECAST)
Information:  Summary ? | License ? | Metadata | Background (external link) | Data Access Form
 
Graph Type:  ?
X Axis:  ?
Y Axis:  ?
Color:  ?
 
Dimensions ?    Start ?    Stop ?
time (UTC) ?
    << - +
    -
< slider >
nsigma (count) ?     specify just 1 value →
    << -
< <
ny (count) ?     specify just 1 value →
    << -
< <
nx (count) ?     specify just 1 value →
    << -
< <
 
Graph Settings
Marker Type:   Size: 
Color: 
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.)
 
Optional:
Then set the File Type: (File Type information)
and
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 1.3885452e+9, 1.5043104e+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";
  }
  nsigma {
    Int16 actual_range 0, 18;
    String ioos_category "Unknown";
    String long_name "Nsigma";
    String units "count";
  }
  ny {
    Int16 actual_range 0, 24;
    String ioos_category "Statistics";
    String long_name "NY";
    String units "count";
  }
  nx {
    Int16 actual_range 0, 60;
    String ioos_category "Statistics";
    String long_name "NX";
    String units "count";
  }
  temp {
    Float64 colorBarMaximum 32.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Temperature";
    String long_name "Temperature";
    Float32 missing_value -99999.0;
    String standard_name "sea_water_temperature";
    String units "degree_Celsius";
  }
  u {
    Float64 colorBarMaximum 0.5;
    Float64 colorBarMinimum -0.5;
    String ioos_category "Currents";
    String long_name "Zonal Current";
    Float32 missing_value -99999.0;
    String standard_name "eastward_sea_water_velocity";
    String units "m.s-1";
  }
  v {
    Float64 colorBarMaximum 0.5;
    Float64 colorBarMinimum -0.5;
    String ioos_category "Currents";
    String long_name "Meridional Current";
    Float32 missing_value -99999.0;
    String standard_name "northward_sea_water_velocity";
    String units "m.s-1";
  }
  NC_GLOBAL {
    String _CoordSysBuilder "ucar.nc2.dataset.conv.DefaultConvention";
    String author "gregory.lang@noaa.gov";
    String cdm_data_type "Grid";
    String comment1 "Lake Ontario  5 km bathymetric grid";
    String comment2 "3-hourly model 3D output starting at validtime plus 3 hr";
    String comment3 "Generated 2x per day following the 0,12 Z Forecast runs";
    String Conventions "COARDS, CF-1.6, Unidata Dataset Discovery v1.0";
    String creation_date "Thu Aug  7 01:37:48 2014 GMT";
    String creator_email "gregory.lang@noaa.gov";
    String creator_name "NOAA/GLERL";
    String disclaimer "https://www.glerl.noaa.gov/home/notice.html";
    String history 
"Fri Oct  3 19:42:01 2014: ncea -d time,3,3 /mnt/gluster/data/netCDF/glos/3dforecast/ontario//o201421900.out3.nc /mnt/gluster/data/netCDF/glos/3dforecast/ontario/processed//o_2014-08-07-12_2014.219.00.nc
2018-10-17T05:38:50Z (local files)
2018-10-17T05:38:50Z http://erddap.axiomdatascience.com/griddap/GLOS_ONTARIO_3D_FORECAST.das";
    String infoUrl "???";
    String institution "NOAA/GLERL";
    String keywords "circulation, coastal, current, currents, Earth Science > Oceans > Ocean Circulation > Ocean Currents, Earth Science > Oceans > Ocean Temperature > Water Temperature, eastward, eastward_sea_water_velocity, forecast, forecasting, glcfs, glerl, great, great lakes, lakes, meridional, noaa, northward, northward_sea_water_velocity, ocean, oceans, sea, sea_water_temperature, seawater, system, temperature, velocity, water, zonal";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.glerl.noaa.gov/home/notice.html";
    String Metadata_Conventions "COARDS, CF-1.6, Unidata Dataset Discovery v1.0";
    String model "Princeton Ocean Model-Great Lakes";
    Int32 nco_openmp_thread_number 1;
    String references "https://www.glerl.noaa.gov/glcfs/";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF-12";
    String summary "Great Lakes Coastal Forecasting System (GLCFS), FORECAST";
    String time_coverage_end "2017-09-02T00:00:00Z";
    String time_coverage_start "2014-01-01T03:00:00Z";
    String title "Great Lakes Coastal Forecasting System (GLCFS), FORECAST";
    String validtime "07-AUG-2014 00:00 GMT";
    String validtime_DOY "219, 2014 00:00 GMT";
  }
}

 

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.


 
ERDDAP, Version 1.82_axiom-r1
Disclaimers | Privacy Policy | Contact