Make A Graph

Dataset Title:	SCAR Iceberg Database
Institution:	Norwegian Polar Data Centre (Dataset ID: NPI_Iceberg_database)
Range:	longitude = -179.9833 to 179.9833°E, latitude = -78.4833 to -26.2833°N, time = 1977-01-05T21:00Z to 2010-03-11T06:00Z
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| Data Access Form \| Files

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Constraints	Optional Constraint #1		Optional Constraint #2

Server-side Functions

distinct()

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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 {
 s {
  Cruise_ID {
    Int32 actual_range 101, 990008;
    String long_name "Cruise-ID";
  }
  Vessel {
    String long_name "Vessel";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 2.21346e+8, 1.2682872e+9;
    String axis "T";
    String ioos_category "Time";
    String long_name "Obs Date";
    String source_name "Obs_Date";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01T00:00Z";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range -78.4833, -26.2833;
    String axis "Y";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range -179.9833, 179.9833;
    String axis "X";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Ice_conc {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 0, 20;
    String long_name "Ice Conc";
  }
  RV {
    String long_name "RV";
  }
  Total {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 1500;
    String long_name "Total";
  }
  no10_50 {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 800;
    String long_name "No10-50";
  }
  no50_200 {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 740;
    String long_name "No50-200";
  }
  no200_500 {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 150;
    String long_name "No200-500";
  }
  no500_1000 {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 0, 80;
    String long_name "No500-1000";
  }
  gt1000 {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 0, 40;
    String long_name "GT1000";
  }
  Freeboard {
    Int16 _FillValue 32767;
    Int16 actual_range 3, 6000;
    String long_name "Freeboard";
  }
  Length {
    Int32 _FillValue 2147483647;
    Int32 actual_range 1, 110000;
    String long_name "Length";
  }
  Width {
    Int32 _FillValue 2147483647;
    Int32 actual_range 2, 80000;
    String long_name "Width";
  }
  Dim_as_average {
    String long_name "Dim As Average";
  }
  View_radius {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 1, 48;
    String long_name "View Radius";
  }
  comments {
    String long_name "Comments";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Other";
    String citation "Orheim, O., Giles, B., Moholdt, G., Jacka, J., Bj:Ã¸rdal, A. (2021). The SCAR International Iceberg Database [Data set]. Norwegian Polar Institute. https://doi.org/10.21334/npolar.2021.e4b9a604";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_name "Norwegian Polar Data Centre";
    Float64 Easternmost_Easting 179.9833;
    Float64 geospatial_lat_max -26.2833;
    Float64 geospatial_lat_min -78.4833;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 179.9833;
    Float64 geospatial_lon_min -179.9833;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-05-20T11:40:38Z https://data.npolar.no/dataset/e4b9a604-1b64-4890-9f21-56b5589807c4
2024-05-20T11:40:38Z https://erddap.sochic-h2020.eu/tabledap/NPI_Iceberg_database.das";
    String infoUrl "https://data.npolar.no/dataset/e4b9a604-1b64-4890-9f21-56b5589807c4";
    String institution "Norwegian Polar Data Centre";
    String keywords "ice, Ice_conc, Iceberg, polar, width";
    String license "Creative Commons Attribution Share-Alike http://www.opendefinition.org/licenses/cc-by-sa";
    Float64 Northernmost_Northing -26.2833;
    String sourceUrl "https://data.npolar.no/dataset/e4b9a604-1b64-4890-9f21-56b5589807c4";
    Float64 Southernmost_Northing -78.4833;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary 
"In the period between the austral summers of 1982/83 to 1997/98, iceberg observations were recorded by most research vessels cruising Antarctic waters, under an international programme for systematic collection of Antarctic iceberg data initiated by The Norwegian Polar Institute (NPI) in 1981 with the endorsement of the Scientific Committee on Antarctic Research (SCAR). The resulting database contains records of 320 493 iceberg positions from 26 601 individual observations. Of these, 259 479 icebergs have been classified by size into five different length categories: 10-50, 50- 200, 200-500, 500-1000 and bigger than 1000 m. The database also includes 8061 additional iceberg observations collected by the Australian National Antarctic Research Expeditions ships from 1984 (AAD), operating in the 50-150Â° E longitude sector. Some of these have been classified by slightly different size categories.
The dataset is described in detail in the attached data report, with an overview of the contents of the database and their potential use, the data quality and quality control process, and some concluding remarks on iceberg occurrence and distribution around Antarctica; drift patterns, dissolution rates, calving rates and their contribution to the mass balance of Antarctica.";
    String time_coverage_end "2010-03-11T06:00Z";
    String time_coverage_start "1977-01-05T21:00Z";
    String title "SCAR Iceberg Database";
    Float64 Westernmost_Easting -179.9833;
  }
}

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.

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