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Dataset Title:  Sea Ice Surface Elevation from IceBridge ATM LIDAR, Arctic, from 2009 to 2018
Airborne Surveys
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Institution:  NOAA NESDIS STAR   (Dataset ID: noaa_lsa_surface_elevation_icebridge)
Range: longitude = -179.99844 to 179.99477°E, latitude = 67.23399 to 89.99707°N, time = 2009-03-31T12:28:04.781Z to 2018-04-16T16:30:20.114Z
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
 
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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 {
 s {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.238502484781e+9, 1.523896220114e+9;
    String axis "T";
    String comment "Time (seconds since 1970-01-01T00:00:00.000Z), minimum time of all ATM point measurements within 10 across-track grid cells\"";
    String ioos_category "Time";
    String long_name "Time";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01T00:00:00.000Z";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  Along_track_Distance {
    Float32 actual_range 1000.0, 2002000.0;
    String comment "Along-track distance (meters), relative to the beginning of the flight line";
    String ioos_category "Unknown";
    String long_name "Along-track Distance";
    String units "meters";
  }
  Across_Track_Grid_Cell_Number {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 1, 10;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Statistics";
    String long_name "Cross-Track Grid Cell Number";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -179.99844221, 179.9947664;
    String axis "X";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String comment "Longitude (degrees), mean longitude of ATM point measurements within grid cell";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 67.23399119, 89.99707309;
    String axis "Y";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String comment "Latitude (degrees), mean latitude of ATM point measurements within grid cell";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  Elevation {
    Float32 _FillValue NaN;
    Float32 actual_range -16.521, 50.0;
    String comment "Elevation (meters, relative to WGS84 ellipsoid), mean elevation of ATM elevation point measurements within grid cell";
    String ioos_category "Location";
    String long_name "Elevation";
    String units "meters";
  }
  Standard_Deviation {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 4.3024;
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String comment "Standard Deviation (meters), standard deviation of ATM elevation point measurements within grid cell";
    String ioos_category "Statistics";
    String long_name "Standard Deviation";
    String units "meters";
  }
  Num_Pts {
    Float32 actual_range 0.0, 1543.0;
    String comment "Number of ATM point measurements within grid cell";
    String ioos_category "Unknown";
    String long_name "Number of Points";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Other";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String defaultGraphQuery "longitude%2Clatitude%2CElevation%26time%3E%3D2018-04-10T00%3A00%3A00Z%26time%3C%3D2018-04-17T00%3A00%3A00Z%26.draw=markers%26t.marker=6%7C%26.color=0x000000%26.colorBar=KT_amp%7C%7C%7C%7C%7C";
    Float64 Easternmost_Easting 179.9947664;
    Float64 geospatial_lat_max 89.99707309;
    Float64 geospatial_lat_min 67.23399119;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 179.9947664;
    Float64 geospatial_lon_min -179.99844221;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-10-11T14:56:31Z (local files)
2024-10-11T14:56:31Z https://polarwatch.noaa.gov/tabledap/noaa_lsa_surface_elevation_icebridge.das";
    String infoUrl "https://www.star.nesdis.noaa.gov/sod/lsa/SeaIce/SurfaceElevation.php";
    String institution "NOAA NESDIS STAR";
    String keywords "along, along-track, Along_track_Distance, Along_Track_Grid_Cell_Number, cell, data, deviation, distance, elevation, grid, latitude, local, longitude, num, Num_Pts, number, pts, source, standard, Standard_Deviation, statistics, time, time2, track";
    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.";
    Float64 Northernmost_Northing 89.99707309;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 67.23399119;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary 
"This dataset contains the NOAA / NESDIS / STAR / LSA Polar Ocean Data System (PODS) Arctic Gridded Surface Elevation Product. The Gridded Surface Elevation Product is derived from Airborne Topographic Mapper (ATM) lidar elevation data acquired during annual, low-altitude NASA Operation IceBridge airborne surveys over Arctic sea ice. IceBridge ATM data were acquired between March and May, 2009 - 2019. Due to the conical scanning geometry of the ATM lidar, across-track sampling is non-uniform, with sampling density greatest at the swath edges. To account for the variation in sample density, ATM elevation data are gridded (See Figure 1 on Data Product Webpage). Each grid cell has an along-track dimension of 30 m and an across-track dimension that is inversely proportional to the across-track sampling density. The grid configuration optimizes ATM sample density providing high-resolution measurements of elevation while still containing enough point measurements for robust statistical calculations. Citation: Users are asked to cite the following publication whenever these data are used:
            Connor, L., S. Farrell and D. McAdoo (2017), A decadal study of interannual variability in Arctic sea ice freeboard using airborne laser altimetry (2006-2016), presented at the 2017 IGS International Symposium on Polar Ice, Polar Climate, and Polar Change, Boulder, Colorado, 14-19 Aug. 2017.
        Point of Contact: Laurence.Connor@noaa.gov
        Data Product Webpage: https://www.star.nesdis.noaa.gov/sod/lsa/SeaIce/SurfaceElevation.php";
    String time_coverage_end "2018-04-16T16:30:20.114Z";
    String time_coverage_start "2009-03-31T12:28:04.781Z";
    String title "Sea Ice Surface Elevation from IceBridge ATM LIDAR, Arctic, from 2009 to 2018 Airborne Surveys";
    Float64 Westernmost_Easting -179.99844221;
  }
}

 

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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