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Dataset Title:  Lake Ontario Average Water Level. (1992-2020) Subscribe RSS
Institution:  Yuanyuan Jia, CK Shum, DGS, SES, OSU/ Philip Chu, GLERL NOAA   (Dataset ID: LO_average_water_level)
Range: time = 1992-05-01T00:00:00Z to 2020-03-02T00:00:00Z
Information:  Summary ? | License ? | Metadata | Background (external link) | Data Access Form | Files
 
Graph Type:  ?
X Axis: 
Y Axis: 
Color: 
-1 +1
 
Constraints ? Optional
Constraint #1 ?
Optional
Constraint #2 ?
       
       
       
       
       
 
Server-side Functions ?
 distinct() ?
? (" ")
 
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 {
 s {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 7.046784e+8, 1.5831072e+9;
    String axis "T";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Time";
    String long_name "time: serial date numbers";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  h1 {
    Float64 actual_range 74.40103849937175, 76.11351074349597;
    String ioos_category "Sea Level";
    String long_name "water level above IGLD85";
    String standard_name "water level above igld85";
    String units "meters";
  }
  std1 {
    Float64 actual_range 0.0, 0.20053895534907953;
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Statistics";
    String long_name "standard deviation of h1";
    String standard_name "standard deviation of h1";
    String units "meters";
  }
  h2 {
    Float64 actual_range 74.41757287197817, 76.11629754152281;
    String ioos_category "Sea Level";
    String long_name "water level above IGLD85 after correction";
    String standard_name "water level above igld85 after correction";
    String units "meters";
  }
  std2 {
    Float64 actual_range 0.0, 0.19860326942280793;
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Statistics";
    String long_name "standard deviation of h2";
    String standard_name "standard deviation of h2";
    String units "meters";
  }
 }
  NC_GLOBAL {
    String acknowledgements "Yuanyuan Jia, CK Shum, DGS, SES, OSU/ Philip Chu, GLERL NOAA";
    String cdm_data_type "Other";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    String creator_email "cw.glerl@noaa.gov";
    String creator_name "Yuanyuan Jia, CK Shum, DGS, SES, OSU/ Philip Chu, GLERL NOAA";
    String creator_type "institution";
    String creator_url "https://coastwatch.glerl.noaa.gov/";
    String history 
"2021-12-03T03:16:56Z (local files)
2021-12-03T03:16:56Z http://coastwatch.glerl.noaa.gov/tabledap/LO_average_water_level.das";
    String infoUrl "https://coastwatch.glerl.noaa.gov/";
    String institution "Yuanyuan Jia, CK Shum, DGS, SES, OSU/ Philip Chu, GLERL NOAA";
    String keywords "1992-2020, above, after, average, chu, correction, data, deviation, dgs, environmental, erie, glerl, great, igld85, jia, laboratory, lake, lakes, level, noaa, oregon, osu, philip, research, sea, sea level, seawater, ses, shum, standard, standard deviation of h1, standard deviation of h2, state, statistics, std1, std2, time2, university, water, water level above igld85, water level above igld85 after correction, yuanyuan";
    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.";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v29";
    String summary "Lake Ontario Average Water Level. (1992-2020)";
    String time_coverage_end "2020-03-02T00:00:00Z";
    String time_coverage_start "1992-05-01T00:00:00Z";
    String title "Lake Ontario Average Water Level. (1992-2020)";
  }
}

 

Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its selection 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.

Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.


 
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