Make A Graph

Dataset Title:	RV Sikuliaq : Nitrate SUNA_V2-1999 : Absorbance at 350 nm : 600 s binned
Institution:	UAF (Dataset ID: absorbance350_unitless_nitrat001999_600sbin)
Information:	Summary \| License \| Metadata \| Background \| Data Access Form

To work correctly, this web page requires that JavaScript be enabled in your browser. Please:
1) Enable JavaScript in your browser:
      • Chrome: "Settings : Advanced : Privacy and security : Site Settings : JavaScript"
      • Firefox: (it should be always on!)"
      • Opera: "Settings : Websites : JavaScript"
      • Safari: "Safari : Preferences : Security : Enable JavaScript"
2) Reload this web page.

Graph Type:

X Axis:

Y Axis:

Color:

Constraints	Optional Constraint #1		Optional Constraint #2

Server-side Functions

distinct()

Hover here to see a list of options. Click on an option to select it.

Graph Settings

Marker Type:

Size:

Color:

Color Bar:

Continuity:

Scale:

Minimum:

Maximum:

N Sections:

Y Axis Minimum:

Maximum:

(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:

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 {
 s {
  time {
    String _CoordinateAxisType "Time";
    String axis "T";
    String ioos_category "Time";
    String long_name "Time";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  spot_time {
    String ioos_category "Time";
    String long_name "Spot Time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  spot_value {
    String ioos_category "Statistics";
    String long_name "Absorbance At 350 Nm Spot_Value";
    String short_name "absorbance_350_spot_value";
    String special_notes "Binning type: linear";
    String standard_name "x_spot_value";
    String units "unitless";
  }
  mean {
    String ioos_category "Statistics";
    String long_name "Absorbance At 350 Nm Mean";
    String short_name "absorbance_350_mean";
    String special_notes "Binning type: linear";
    String standard_name "x_mean";
    String units "unitless";
  }
  stddev {
    String ioos_category "Statistics";
    String long_name "Absorbance At 350 Nm Stddev";
    String short_name "absorbance_350_stddev";
    String special_notes "Binning type: linear";
    String standard_name "x_stddev";
    String units "unitless";
  }
  minimum {
    String ioos_category "Statistics";
    String long_name "Absorbance At 350 Nm Minimum";
    String short_name "absorbance_350_minimum";
    String special_notes "Binning type: linear";
    String standard_name "x_minimum";
    String units "unitless";
  }
  maximum {
    String ioos_category "Statistics";
    String long_name "Absorbance At 350 Nm Maximum";
    String short_name "absorbance_350_maximum";
    String special_notes "Binning type: linear";
    String standard_name "x_maximum";
    String units "unitless";
  }
  median {
    String ioos_category "Statistics";
    String long_name "Absorbance At 350 Nm Median";
    String short_name "absorbance_350_median";
    String special_notes "Binning type: linear";
    String standard_name "x_median";
    String units "unitless";
  }
  num_values {
    String ioos_category "Statistics";
    String long_name "Absorbance At 350 Nm Num_Values";
    String short_name "absorbance_350_num_values";
    String special_notes "Binning type: linear";
    String standard_name "x_num_values";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Other";
    String contributor_name "RV Sikuliaq";
    String contributor_role "Data collector";
    String creator_name "CORIOLIX, RDESC, RCRV Project, Oregon State University";
    String creator_url "http://ceoas.oregonstate.edu";
    String history 
"2026-05-02T14:11:51Z (source database)
2026-05-02T14:11:51Z https://coriolix.sikuliaq.alaska.edu/tabledap/absorbance350_unitless_nitrat001999_600sbin.das";
    String infoUrl "https://www.uaf.edu/cfos/sikuliaq/";
    String institution "UAF";
    String keywords "atmosphere, data, observations, ocean";
    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 "(source database)";
    String standard_name_vocabulary "CF standard name";
    String summary 
"Absorbance at 350 nm 600 s binned time series data.
Vessel: RV Sikuliaq. Sensor Model: Satlantic {Sea-Bird} Submersible Ultraviolet Nitrate Analyser V2 (SUNA V2) nutrient analyser series
Sensor S/N: NTR-1999
Sensor Location Onboard: Main Lab / Wet Wall
Sensor Description: Sea-Bird Submersible Ultraviolet Nitrate Analyzer (SUNA) is a real time, chemical free sensor for measuring nitrate concentration in seawater. The instrument is programmed to output full ASCII frames.
Parameter Description: Measurement of Absorbance at 350nm, outside of the wavelength integration range, this value is used to assess the impact of colored dissolved organic matter (CDOM) on the sample. When values are greater than 1.3 A.U. CDOM may affect the light availability to take this measurement accurately.";
    String title "RV Sikuliaq : Nitrate SUNA_V2-1999 : Absorbance at 350 nm : 600 s binned";
  }
}

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.

(easy) You can get data by using the dataset's Data Access Form or Subset form. They make 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.

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.

ERDDAP, Version 2.23
Disclaimers | Privacy Policy | Contact