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Dataset Title:	Great Lakes Coastal Forecasting System (GLCFS), FORECAST
Institution:	NOAA/GLERL (Dataset ID: GLOS_HURON_2D_NOWCAST)
Information:	Summary \| License \| Metadata \| Background \| Data Access Form

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time (UTC)

ny (count)

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nx (count)

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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:

Web page authors can embed a graph of the latest data in a web page using HTML <img> tags.
Anyone can use ERDDAPs Slide Sorter to build a personal web page that displays graphs with the latest data (or other images or HTML content), each in its own, draggable slide.

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.388538e+9, 1.4700528e+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";
  }
  ny {
    Int16 actual_range 0, 187;
    String ioos_category "Statistics";
    String long_name "NY";
    String units "count";
  }
  nx {
    Int16 actual_range 0, 200;
    String ioos_category "Statistics";
    String long_name "NX";
    String units "count";
  }
  eta {
    Float64 colorBarMaximum 2.0;
    Float64 colorBarMinimum -2.0;
    String ioos_category "Sea Level";
    String long_name "Height Above Model Sea Level";
    Float32 missing_value -99999.0;
    String positive "up";
    String reference "model_sea_level";
    String standard_name "sea_surface_elevation";
    String units "m";
  }
  uc {
    Float64 colorBarMaximum 0.5;
    Float64 colorBarMinimum -0.5;
    String discriminant "normal";
    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";
  }
  vc {
    Float64 colorBarMaximum 0.5;
    Float64 colorBarMinimum -0.5;
    String discriminant "normal";
    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";
  }
  wvh {
    Float64 colorBarMaximum 10.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Surface Waves";
    String long_name "Significant Wave Height";
    Float32 missing_value -99999.0;
    String standard_name "sea_surface_wave_significant_height";
    String units "m";
  }
  wvd {
    Float64 colorBarMaximum 360.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Surface Waves";
    String long_name "Wave Direction";
    Float32 missing_value -99999.0;
    String standard_name "sea_surface_wave_to_direction";
    String units "degrees";
  }
  wvp {
    Float64 colorBarMaximum 20.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Surface Waves";
    String long_name "Wave Period";
    Float32 missing_value -99999.0;
    String standard_name "sea_surface_wave_mean_period";
    String units "s";
  }
  ci {
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Ice Distribution";
    String long_name "Ice concentration";
    Float32 missing_value -99999.0;
    String standard_name "sea_ice";
    String units "percent";
  }
  hi {
    String ioos_category "Ice Distribution";
    String long_name "Ice thickness";
    Float32 missing_value -99999.0;
    String standard_name "ice_cover_thickness";
    String units "m";
  }
  ui {
    Float64 colorBarMaximum 0.1;
    Float64 colorBarMinimum -0.1;
    String ioos_category "Currents";
    String long_name "Zonal Current";
    Float32 missing_value -99999.0;
    String standard_name "eastward_sea_ice_velocity";
    String units "m.s-1";
  }
  vi {
    Float64 colorBarMaximum 0.1;
    Float64 colorBarMinimum -0.1;
    String ioos_category "Currents";
    String long_name "Meridional Current";
    Float32 missing_value -99999.0;
    String standard_name "northward_sea_ice_velocity";
    String units "m.s-1";
  }
  NC_GLOBAL {
    String _CoordSysBuilder "ucar.nc2.internal.dataset.conv.DefaultConventions";
    String author "gregory.lang@noaa.gov";
    String cdm_data_type "Grid";
    String comment1 "Lake Huron  2 km bathymetric grid";
    String comment2 "1-hourly model 2D output starting at validtime plus 1 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 "Wed Jan  1 03:12:42 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 
"Thu Oct  9 09:27:39 2014: ncea -d time,0,0 /mnt/gluster/data/netCDF/glos/2dnowcast/huron//h201400100.out1.nc /mnt/gluster/data/netCDF/glos/2dnowcast/huron/processed//h_2014-01-01-01_2014.001.00.nc
2023-06-10T10:24:25Z (local files)
2023-06-10T10:24:25Z http://erddap.axiomdatascience.com/griddap/GLOS_HURON_2D_NOWCAST.das";
    String infoUrl "???";
    String institution "NOAA/GLERL";
    String keywords "above, circulation, coastal, concentration, cover, cryosphere, current, currents, direction, distribution, Earth Science > Cryosphere > Sea Ice > Sea Ice Motion, Earth Science > Oceans > Ocean Circulation > Ocean Currents, Earth Science > Oceans > Ocean Waves > Significant Wave Height, Earth Science > Oceans > Ocean Waves > Wave Speed/Direction, Earth Science > Oceans > Sea Ice > Sea Ice Motion, Earth Science > Oceans > Sea Surface Topography > Sea Surface Height, eastward, eastward_sea_ice_velocity, eastward_sea_water_velocity, elevation, forecast, forecasting, glcfs, glerl, great, great lakes, height, ice, ice distribution, ice_cover_thickness, lakes, level, mean, meridional, model, motion, noaa, northward, northward_sea_ice_velocity, northward_sea_water_velocity, ocean, oceans, period, sea, sea level, sea_ice, sea_surface_elevation, sea_surface_wave_mean_period, sea_surface_wave_significant_height, sea_surface_wave_to_direction, seawater, significant, speed, surface, surface waves, system, thickness, topography, velocity, water, wave, waves, 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 "GLERL Wave Model-Great Lakes, 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 "2016-08-01T12:00:00Z";
    String time_coverage_start "2014-01-01T01:00:00Z";
    String title "Great Lakes Coastal Forecasting System (GLCFS), FORECAST";
    String validtime "01-JAN-2014 00:00 GMT";
    String validtime_DOY "001, 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.

(easy) You can get data by using the dataset's Data Access Form. It makes the URL for you.
(easy) You can make a graph or map by using the dataset's Make A Graph form. It makes the URL for you.
(not hard) You can bypass the forms and get the data or make a graph or map by generating the URL by hand or with a computer program or script.

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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