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Dataset Title:  Sea Ice Surface Roughness from IceBridge ATM LIDAR, Arctic, 10km, from 2009 to
2018 Airborne Surveys
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Institution:  NOAA NESDIS STAR   (Dataset ID: noaa_lsa_surface_roughness_icebridge)
Range: longitude = -179.84143 to 179.83208°E, latitude = 67.27581 to 89.97597°N, time = 2009-03-31T12:28:41Z to 2018-04-16T16:30:01Z
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 1.238502521e+9, 1.523896201e+9;
    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 time_precision "1970-01-01T00:00:00Z";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range 67.27580708, 89.975968808;
    String axis "Y";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String comment "The average latitude of measurements in the 10km segment";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range -179.841429911, 179.832076042;
    String axis "X";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String comment "The average longitude of measurements in the 10km segment";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Mean_surface_roughness {
    Float32 actual_range 0.02, 0.77;
    String comment "Arithmetic mean of all surface roughness measurements in 10km segment";
    String ioos_category "Surface Waves";
    String long_name "Mean Surface Roughness";
    String units "Meters";
  }
  Maximum_surface_roughness {
    Float32 actual_range 0.04, 3.71;
    String comment "Maximum value of surface roughness in 10km segment";
    String ioos_category "Surface Waves";
    String long_name "Maximum Surface Roughness";
    String units "Meters";
  }
  Surface_roughness_5th_percentile {
    Float32 actual_range 0.0, 0.48;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String comment "5th percentile height of all surface roughness measurements in 10km segment";
    String ioos_category "Surface Waves";
    String long_name "Surface Roughness 5th Percentile";
    String units "Meters";
  }
  Surface_roughness_25th_percentile {
    Float32 actual_range 0.01, 0.63;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String comment "25th percentile height of all surface roughness measurements in 10km segment";
    String ioos_category "Surface Waves";
    String long_name "Surface Roughness 25th Percentile";
    String units "Meters";
  }
  Surface_roughness_75th_percentile {
    Float32 actual_range 0.03, 0.91;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String comment "75th percentile height of all surface roughness measurements in 10km segment";
    String ioos_category "Surface Waves";
    String long_name "Surface Roughness 75th Percentile";
    String units "Meters";
  }
  Surface_roughness_95th_percentile {
    Float32 actual_range 0.03, 1.17;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String comment "95th percentile height of all surface roughness measurements in 10km segment";
    String ioos_category "Surface Waves";
    String long_name "Surface Roughness 95th Percentile";
    String units "Meters";
  }
  Surface_roughness_99th_percentile {
    Float32 actual_range 0.03, 1.75;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String comment "99th percentile height of all surface roughness measurements in 10km segment";
    String ioos_category "Surface Waves";
    String long_name "Surface Roughness 99th Percentile";
    String units "Meters";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Point";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_name "NOAA";
    String creator_type "institution";
    String creator_url "https://star.nesdis.noaa.gov/socd/lsa";
    String defaultGraphQuery "time%2CSurface_roughness_99th_percentile%2C&time>=2018-04-10T00%3A00%3A00Z&time%3C%3D2018-04-17T00%3A00%3A00Z&.draw=markers&.marker=5%7C5&.color=0x000000";
    Float64 Easternmost_Easting 179.832076042;
    String featureType "Point";
    Float64 geospatial_lat_max 89.975968808;
    Float64 geospatial_lat_min 67.27580708;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 179.832076042;
    Float64 geospatial_lon_min -179.841429911;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-10-11T13:46:43Z (local files)
2024-10-11T13:46:43Z https://polarwatch.noaa.gov/tabledap/noaa_lsa_surface_roughness_icebridge.das";
    String infoUrl "https://star.nesdis.noaa.gov/socd/lsa/SeaIce/SeaIceSurfaceRoughness.php";
    String institution "NOAA NESDIS STAR";
    String keywords "Earth Science > Climate Indicators > Cryospheric Indicators, Earth Science > Climate Indicators > Cryospheric Indicators > Sea Ice Elevation, Earth Science > Cryosphere > Sea Ice, Earth Science > Cryosphere > Sea Ice> Sea Ice Elevation, Surface Roughness";
    String keywords_vocabulary "GCMD Science Keywords";
    String license 
"Users are free to use the information hosted on this site in their research, provided credit  is given to the NOAA National Environmental Satellite, Data, and Information Service (NESDIS) Center for Satellite Applications and Research (STAR) Laboratory for Satellite Altimetry (LSA).

            Data and images displayed on NOAA/NESDIS/STAR sites are provided for experimental use only and are not official operational NOAA products. More information is available at: http://www.star.nesdis.noaa.gov/star/productdisclaimer.php

            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 89.975968808;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 67.27580708;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary 
"This data file contains the NOAA / NESDIS / STAR / LSA Polar Ocean Data System (PODS) Arctic Surface Roughness Product. The Arctic Surface Roughness 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 sea ice surface roughness while still containing enough point measurements for robust statistical calculations. Statistics are computed on the distribution of sea ice surface roughness for 10 km along-track segments, for each aircraft flight line.

            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";
    String time_coverage_end "2018-04-16T16:30:01Z";
    String time_coverage_start "2009-03-31T12:28:41Z";
    String title "Sea Ice Surface Roughness from IceBridge ATM LIDAR, Arctic, 10km, from 2009 to 2018 Airborne Surveys";
    Float64 Westernmost_Easting -179.841429911;
  }
}

 

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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