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Dataset Title:  Lake Michigan, Nowcast, 3D, All Years, Lake Michigan, Nowcast, 3D, All Years,
Best Time Series [time][ny][nx], 2006-2018
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Institution:  NOAA/GLERL   (Dataset ID: glos_tds_9f37_5b0b_ab8b)
Information:  Summary ? | License ? | Metadata | Background (external link) | Data Access Form
Graph Type:  ?
X Axis:  ?
Y Axis:  ?
Color:  ?
Dimensions ?    Start ?    Stop ?
time (UTC) ?
    << - +
< slider >
ny (count) ?     specify just 1 value →
    << -
< <
nx (count) ?     specify just 1 value →
    << -
< <
Graph Settings
Marker Type:   Size: 
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.)
Then set the File Type: (File Type information)
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 1.1360844e+9, 1.5320448e+9;
    String axis "T";
    String calendar "proleptic_gregorian";
    String ioos_category "Time";
    String long_name "Forecast time for ForecastModelRunCollection";
    Float64 missing_value NaN;
    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, 250;
    String ioos_category "Statistics";
    String long_name "NY";
    String units "count";
  nx {
    Int16 actual_range 0, 130;
    String ioos_category "Statistics";
    String long_name "NX";
    String units "count";
  eta {
    String ioos_category "Unknown";
    String long_name "Eta";
    String units "m";
    String _CoordSysBuilder "ucar.nc2.dataset.conv.CF1Convention";
    String author "";
    String cdm_data_type "Grid";
    String comment1 "Lake Michigan  2 km bathymetric grid";
    String comment2 "3-hourly model 3D output starting at validtime plus 3 hr";
    String comment3 "Generated 4x per day following the 0,6,12,18 Z Nowcast runs";
    String contributor_name "GLOS DMAC, GLERL";
    String contributor_role "distributor, producer";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    String creation_date "Mon Jun 11 18:15:48 2018 GMT";
    String creator_email "";
    String creator_name "Dr. Dave Schwab";
    String creator_type "person";
    String creator_url "";
    String disclaimer "";
    String history 
"Mon Jun 11 18:16:56 2018: ncks -O --deflate=1 tmp/m201810100.out3.nc4 tmp/
Mon Jun 11 18:16:44 2018: ncks -O --fl_fmt=netcdf4_classic nc_files/ tmp/m201810100.out3.nc4 ;
FMRC Best Dataset
    String id "glos/glcfs/archiveall/michigan/ncfmrc-3d/Lake_Michigan_-_Nowcast_-_3D_-_All_Years_best.ncd";
    String infoUrl "";
    String institution "NOAA/GLERL";
    String keywords "all, best, best time series, coastal, data, environmental, eta, forecasting, glcfs, glerl, glos, great, great lakes, laboratory, lake, lakes, michigan, noaa, nowcast, observing, research, series, system, time, time series, years";
    String license "No usage restrictions";
    String location "Proto fmrc:Lake_Michigan_-_Nowcast_-_3D_-_All_Years";
    String metadata_link "";
    String model "Princeton Ocean Model-Great Lakes";
    String naming_authority "GLOS";
    String NCO "4.3.7";
    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 v55";
    String summary "GLCFS - Lake Michigan - Nowcast - 3D. Best time series, taking the data from the most recent run available. Great Lakes Coastal Forecasting System. Lake Michigan  2 km bathymetric grid. 3-hourly model 3D output starting at validtime plus 3 hr. Generated 4x per day following the 0,6,12,18 Z Nowcast runs";
    String time_coverage_end "2018-07-20T00:00:00Z";
    String time_coverage_start "2006-01-01T03:00:00Z";
    String title "Lake Michigan, Nowcast, 3D, All Years, Lake Michigan, Nowcast, 3D, All Years, Best Time Series [time][ny][nx], 2006-2018";
    String validtime "01-JAN-2013 00:00 GMT";
    String validtime_DOY "001, 2013 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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