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Dataset Title:  GLCFS, Lake Erie, Forecast, 2D (Lake Erie, 2D, Best Time Series) [nsigma] Subscribe RSS
Institution:  NOAA/GLERL   (Dataset ID: glos_tds_3f0b_1285_0cf8)
Information:  Summary ? | License ? | Metadata | Background (external link) | Data Access Form
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nsigma (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:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  nsigma {
    Int32 actual_range 0, 19;
    String ioos_category "Unknown";
    String long_name "Nsigma";
    String units "count";
  sigma {
    String _CoordinateAxisType "GeoZ";
    String _CoordinateTransformType "Vertical";
    String _CoordinateZisPositive "down";
    String axis "Z";
    String formula_terms "sigma: sigma eta: eta depth: depth";
    String ioos_category "Location";
    String long_name "Sigma Stretched Vertical Coordinate at Nodes";
    String positive "down";
    String standard_name "ocean_sigma_coordinate";
    String units "1";
    String _CoordSysBuilder "ucar.nc2.dataset.conv.CF1Convention";
    String author "";
    String cdm_data_type "Grid";
    String comment1 "Lake Erie  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 contributor_name "GLOS DMAC, GLERL";
    String contributor_role "distributor, producer";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    String creation_date "Thu Mar  1 13:40:01 2018 GMT";
    String creator_email "";
    String creator_name "Dr. Dave Schwab";
    String creator_type "person";
    String creator_url "";
    String data_source "NDFD";
    String disclaimer "";
    String history 
"FMRC Best Dataset
    String id "glos.glcfs.erie.fcfmrc-2d.Lake_Erie_-_2D_best.ncd";
    String infoUrl "";
    String institution "NOAA/GLERL";
    String keywords "best, best time series, coastal, coordinate, data, density, earth, Earth Science > Oceans > Salinity/Density > Density, environmental, erie, forecast, forecasting, glcfs, glerl, glos, great, great lakes, laboratory, lake, lakes, noaa, nodes, nsigma, observing, ocean, ocean_sigma_coordinate, oceans, research, salinity, science, series, sigma, stretched, system, time, time series, vertical";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "No usage restrictions";
    String location "Proto fmrc:Lake_Erie_-_2D";
    String metadata_link "";
    String model "GLERL Wave Model-Great Lakes, Princeton Ocean Model-Great Lakes";
    String naming_authority "GLOS";
    String publisher_email "";
    String publisher_name "GLOS DMAC";
    String publisher_type "institution";
    String publisher_url "";
    String references "";
    String sourceUrl "";
    String standard_name_vocabulary "CF Standard Name Table v29";
    String summary "GLCFS - Lake Erie - Forecast - 2D. Best time series, taking the data from the most recent run available. Great Lakes Coastal Forecasting System. Lake Erie  2 km bathymetric grid. 1-hourly model 2D output starting at validtime plus 1 hr. Generated 2x per day following the 0,12 Z Forecast runs";
    String title "GLCFS, Lake Erie, Forecast, 2D (Lake Erie, 2D, Best Time Series) [nsigma]";
    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.

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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