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Dataset Title:	Sea Ice Concentration, NOAA/NSIDC Climate Data Record V5, Southern Hemisphere, 25km, Science Quality, 1978-Present, Daily
Institution:	NSIDC > National Snow and Ice Data Center (Dataset ID: nsidcG02202v5sh1day)
Information:	Summary \| License \| Metadata \| Background \| Data Access Form \| Files

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Y Axis:
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time (UTC)

specify just 1 value →

y (meters)

x (meters)

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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 {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 3.155328e+8, 1.7197056e+9;
    String axis "T";
    String calendar "standard";
    String coverage_content_type "coordinate";
    String ioos_category "Time";
    String long_name "ANSI date";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
    Float64 valid_range 0, 30000;
  }
  y {
    Float64 _FillValue NaN;
    Float64 actual_range -3937500.0, 4337500.0;
    String axis "Y";
    String coverage_content_type "coordinate";
    String ioos_category "Location";
    String long_name "y coordinate of projection";
    String standard_name "projection_y_coordinate";
    String units "meters";
    Float64 valid_range -3950000.0, 4350000.0;
  }
  x {
    Float64 _FillValue NaN;
    Float64 actual_range -3937500.0, 3937500.0;
    String axis "X";
    String coverage_content_type "coordinate";
    String ioos_category "Location";
    String long_name "x coordinate of projection";
    String standard_name "projection_x_coordinate";
    String units "meters";
    Float64 valid_range -3950000.0, 3950000.0;
  }
  cdr_seaice_conc_interp_spatial_flag {
    Byte _FillValue -1;
    String _Unsigned "true";
    Float64 colorBarMaximum 20.0;
    Float64 colorBarMinimum 0.0;
    Byte flag_masks 1, 2, 4, 8, 16;
    String flag_meanings "19v_tb_value_interpolated 19h_tb_value_interpolated 22v_tb_value_interpolated 37v_tb_value_interpolated 37h_tb_value_interpolated";
    String ioos_category "Quality";
    String long_name "NOAA/NSIDC CDR of Passive Microwave Sea Ice Concentration spatial interpolation flags";
    String standard_name "status_flag";
    String units "1";
    Byte valid_range 0, 31;
  }
  cdr_seaice_conc_qa_flag {
    Byte _FillValue -1;
    String _Unsigned "true";
    Float64 colorBarMaximum 80.0;
    Float64 colorBarMinimum 0.0;
    Byte flag_masks 1, 2, 4, 8, 16, 32, 64;
    String flag_meanings "BT_weather_filter_applied NT_weather_filter_applied Land_spillover_filter_applied No_input_data invalid_ice_mask_applied spatial_interpolation_applied temporal_interpolation_applied";
    String ioos_category "Quality";
    String long_name "NOAA/NSIDC CDR of Passive Microwave Sea Ice Concentration QA flags";
    String standard_name "status_flag";
    String units "1";
    Byte valid_range 0, 127;
  }
  cdr_seaice_conc_interp_temporal_flag {
    Byte _FillValue -1;
    String _Unsigned "true";
    Float64 colorBarMaximum 60.0;
    Float64 colorBarMinimum 0.0;
    String comment "Value of 0 indicates no temporal interpolation occurred.  Values greater than 0 and less than or equal to 55 are of the form 'AB' where 'A' indicates the number of days prior to the current day and 'B' indicates the number of days after the current day used to linearly interpolate the data.  If either A or B are zero, the value was extrapolated from that date rather than interpolated.  A value of 255 indicates that temporal interpolation could not be accomplished.";
    String flag_meanings "no_temporal_interp 1_day_after 2_days_after 3_days_after 1_day_prior 1_day_prior_and_1_day_after 1_day_prior_and_2_days_after 1_day_prior_and_3_days_after 1_day_prior_and_4_days_after 1_day_prior_and_5_days_after 2_days_prior 2_days_prior_and_1_day_after 2_days_prior_and_2_days_after 2_days_prior_and_3_days_after 2_days_prior_and_4_days_after 2_days_prior_and_5_days_after 3_days_prior 3_days_prior_and_1_day_after 3_days_prior_and_2_days_after 3_days_prior_and_3_days_after 3_days_prior_and_4_days_after 3_days_prior_and_5_days_after 4_days_prior_and_1_day_after 4_days_prior_and_2_days_after 4_days_prior_and_3_days_after 4_days_prior_and_4_days_after 4_days_prior_and_5_days_after 5_days_prior_and_1_day_after 5_days_prior_and_2_days_after 5_days_prior_and_3_days_after 5_days_prior_and_4_days_after 5_days_prior_and_5_days_after";
    Byte flag_values 0, 1, 2, 3, 10, 11, 12, 13, 14, 15, 20, 21, 22, 23, 24, 25, 30, 31, 32, 33, 34, 35, 41, 42, 43, 44, 45, 51, 52, 53, 54, 55;
    String ioos_category "Quality";
    String long_name "NOAA/NSIDC CDR of Passive Microwave Sea Ice Concentration temporal interpolation flags";
    String standard_name "status_flag";
    String units "1";
    Byte valid_range 0, 55;
  }
  cdr_seaice_conc {
    Float64 _FillValue 2.5500000000000003;
    String ancillary_variables "cdr_seaice_conc_stdev cdr_seaice_conc_qa_flag";
    Float64 colorBarMaximum 1.0;
    Float64 colorBarMinimum 0.0;
    String coverage_content_type "image";
    String ioos_category "Ice Distribution";
    String long_name "NOAA/NSIDC CDR of Passive Microwave Sea Ice Concentration";
    String standard_name "sea_ice_area_fraction";
    String units "1";
    Float64 valid_range 0.0, 1.0;
  }
  cdr_seaice_conc_stdev {
    Float32 _FillValue -1.0;
    Float64 colorBarMaximum 0.1;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Statistics";
    String long_name "NOAA/NSIDC CDR of Passive Microwave Sea Ice Concentration Source Estimated Standard Deviation";
    String units "1";
    Float32 valid_range 0.0, 1.0;
  }
  NC_GLOBAL {
    String _NCProperties "version=2,netcdf=4.8.1,hdf5=1.10.6";
    String acknowledgment "This project was supported in part by a grant from the NOAA Climate Data Record Program. The NASA Team and Bootstrap sea ice concentration algorithms were developed by Donald J. Cavalieri, Josefino C. Comiso, Claire L. Parkinson, and others at the NASA Goddard Space Flight Center in Greenbelt, MD.";
    String cdm_data_type "Grid";
    String cdr_data_type "grid";
    String contributor_name "Walter N. Meier, Florence Fetterer, Ann Windnagel, J. Scott Stewart, Trey Stafford";
    String contributor_role "principal investigator, author, author, software developer, software developer";
    String Conventions "CF-1.11, ACDD-1.3";
    String creator_email "nsidc@nsidc.org";
    String creator_name "NSIDC/NOAA";
    String creator_type "institution";
    String creator_url "https://nsidc.org/";
    String date_created "2024-11-12T08:36:21Z";
    String geospatial_bounds "POLYGON ((-3950000 4350000, 3950000 4350000, 3950000 -3950000, -3950000 -3950000, -3950000 4350000))";
    String geospatial_bounds_crs "EPSG:3412";
    String geospatial_x_resolution "25000 meters";
    String geospatial_x_units "meters";
    String geospatial_y_resolution "25000 meters";
    String geospatial_y_units "meters";
    String grid_mapping_crs_wkt "PROJCS[\"NSIDC Sea Ice Polar Stereographic South\",GEOGCS[\"Unspecified datum based upon the Hughes 1980 ellipsoid\",DATUM[\"Not_specified_based_on_Hughes_1980_ellipsoid\",SPHEROID[\"Hughes 1980\",6378273,298.279411123061,AUTHORITY[\"EPSG\",\"7058\"]],AUTHORITY[\"EPSG\",\"6054\"]],PRIMEM[\"Greenwich\",0,AUTHORITY[\"EPSG\",\"8901\"]],UNIT[\"degree\",0.0174532925199433,AUTHORITY[\"EPSG\",\"9122\"]],AUTHORITY[\"EPSG\",\"4054\"]],PROJECTION[\"Polar_Stereographic\"],PARAMETER[\"latitude_of_origin\",-70],PARAMETER[\"central_meridian\",0],PARAMETER[\"scale_factor\",1],PARAMETER[\"false_easting\",0],PARAMETER[\"false_northing\",0],UNIT[\"metre\",1,AUTHORITY[\"EPSG\",\"9001\"]],AXIS[\"X\",EAST],AXIS[\"Y\",NORTH],AUTHORITY[\"EPSG\",\"3412\"]]";
    Float64 grid_mapping_false_easting 0.0;
    Float64 grid_mapping_false_northing 0.0;
    String grid_mapping_GeoTransform "-3950000 25000 0 4350000 0 -25000";
    Float64 grid_mapping_inverse_flattening 298.279411123064;
    Float64 grid_mapping_latitude_of_projection_origin -90.0;
    String grid_mapping_long_name "NSIDC_SH_PolarStereo_25km";
    Float64 grid_mapping_longitude_of_prime_meridian 0.0;
    String grid_mapping_name "polar_stereographic";
    String grid_mapping_proj4text "+proj=stere +lat_0=-90 +lat_ts=-70 +lon_0=0 +k=1 +x_0=0 +y_0=0 +a=6378273 +b=6356889.449 +units=m +no_defs";
    Float64 grid_mapping_semi_major_axis 6378273.0;
    String grid_mapping_spatial_ref "PROJCS[\"NSIDC Sea Ice Polar Stereographic South\",GEOGCS[\"Unspecified datum based upon the Hughes 1980 ellipsoid\",DATUM[\"Not_specified_based_on_Hughes_1980_ellipsoid\",SPHEROID[\"Hughes 1980\",6378273,298.279411123061,AUTHORITY[\"EPSG\",\"7058\"]],AUTHORITY[\"EPSG\",\"6054\"]],PRIMEM[\"Greenwich\",0,AUTHORITY[\"EPSG\",\"8901\"]],UNIT[\"degree\",0.0174532925199433,AUTHORITY[\"EPSG\",\"9122\"]],AUTHORITY[\"EPSG\",\"4054\"]],PROJECTION[\"Polar_Stereographic\"],PARAMETER[\"latitude_of_origin\",-70],PARAMETER[\"central_meridian\",0],PARAMETER[\"scale_factor\",1],PARAMETER[\"false_easting\",0],PARAMETER[\"false_northing\",0],UNIT[\"metre\",1,AUTHORITY[\"EPSG\",\"9001\"]],AXIS[\"X\",EAST],AXIS[\"Y\",NORTH],AUTHORITY[\"EPSG\",\"3412\"]]";
    String grid_mapping_srid "urn:ogc:def:crs:EPSG::3412";
    Float64 grid_mapping_standard_parallel -70.0;
    Float64 grid_mapping_straight_vertical_longitude_from_pole 0.0;
    String grid_mapping_units "meters";
    String history 
"Generated from https://nsidc.org/data/nsidc-0001
2025-02-14T05:53:02Z (local files)
2025-02-14T05:53:02Z https://polarwatch.noaa.gov/griddap/nsidcG02202v5sh1day.das";
    String id "https://doi.org/10.7265/rjzb-pf78";
    String infoUrl "https://nsidc.org/data/g02202/versions/5";
    String institution "NSIDC > National Snow and Ice Data Center";
    String keywords "Earth Science > Cryosphere > Sea Ice > Sea Ice Concentration, Geographic Region > Polar, Geographic Region > Southern Hemisphere, Ocean > Southern Ocean, Ocean > Southern Ocean > Bellingshausen Sea, Ocean > Southern Ocean > Ross Sea, Ocean > Southern Ocean > Weddell Sea";
    String keywords_vocabulary "NASA Global Change Master Directory (GCMD) Keywords, Version 17.1";
    String license "No constraints on data access or use";
    String metadata_link "https://nsidc.org/data/g02202/versions/5";
    String naming_authority "org.doi.dx";
    String platform "DMSP 5D-3/F17 > Defense Meteorological Satellite Program-F17";
    String processing_level "NOAA Level 3";
    String product_version "v05r00";
    String program "NOAA Climate Data Record Program";
    String proj_crs_code "EPSG:3412";
    String project "NOAA/NSIDC passive microwave sea ice concentration climate data record";
    String references "Comiso, J. C., and F. Nishio. 2008. Trends in the Sea Ice Cover Using Enhanced and Compatible AMSR-E, SSM/I, and SMMR Data. Journal of Geophysical Research 113, C02S07, doi:10.1029/2007JC0043257. ; Comiso, J. C., D. Cavalieri, C. Parkinson, and P. Gloersen. 1997. Passive Microwave Algorithms for Sea Ice Concentrations: A Comparison of Two Techniques. Remote Sensing of the Environment 60(3):357-84. ; Comiso, J. C. 1984. Characteristics of Winter Sea Ice from Satellite Multispectral Microwave Observations. Journal of Geophysical Research 91(C1):975-94. ; Cavalieri, D. J., P. Gloersen, and W. J. Campbell. 1984. Determination of Sea Ice Parameters with the NIMBUS-7 SMMR. Journal of Geophysical Research 89(D4):5355-5369. ; Cavalieri, D. J., C. l. Parkinson, P. Gloersen, J. C. Comiso, and H. J. Zwally. 1999. Deriving Long-term Time Series of Sea Ice Cover from Satellite Passive-Microwave Multisensor Data Sets. Journal of Geophysical Research 104(7): 15,803-15,814 ; Comiso, J.C., R.A. Gersten, L.V. Stock, J. Turner, G.J. Perez, and K. Cho. 2017. Positive Trend in the Antarctic Sea Ice Cover and Associated Changes in Surface Temperature. J. Climate, 30, 2251â€"2267, doi:10.1175/JCLI-D-16-0408.1";
    String sensor "SSMIS > Special Sensor Microwave Imager/Sounder";
    String software_version_id "git@github.com:nsidc/seaice_ecdr.git@093d056580028f123c3a90654c04abf3edea0300";
    String source "Generated from https://nsidc.org/data/nsidc-0001";
    String sourceUrl "(local files)";
    String spatial_resolution "25km";
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "This data set provides a passive microwave sea ice concentration climate data record (CDR) based on gridded brightness temperatures (TBs) from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) and the Defense Meteorological Satellite Program (DMSP) series of passive microwave radiometers: the Special Sensor Microwave Imager (SSM/I) and the Special Sensor Microwave Imager/Sounder (SSMIS). The sea ice concentration CDR is an estimate of sea ice concentration that is produced by combining concentration estimates from two algorithms developed at the NASA Goddard Space Flight Center (GSFC): the NASA Team (NT) algorithm and the Bootstrap (BT) algorithm. The individual algorithms are used to process and combine brightness temperature data at NSIDC. This product is designed to provide a consistent time series of sea ice concentrations (the fraction, or percentage, of ocean area covered by sea ice) from November 1978 to the present, which spans the coverage of several passive microwave instruments. The data are gridded on the NSIDC polar stereographic grid with 25 km x 25 km grid cells and are available in NetCDF file format. Each file contains a variable with the CDR concentration values as well as variables that hold the raw NT and BT processed concentrations for reference. Variables containing standard deviation, quality flags, and projection information are also included. Files that are from 2013 to the present also contain a prototype CDR sea ice concentration based on gridded TBs from the Advanced Microwave Scanning Radiometer 2 (AMSR2) onboard the GCOM-W1 satellite.";
    String time_coverage_duration "P1D";
    String time_coverage_end "2024-06-30T00:00:00Z";
    String time_coverage_resolution "P1D";
    String time_coverage_start "1980-01-01T00:00:00Z";
    String title 
"Sea Ice Concentration, NOAA/NSIDC Climate Data Record V5, Southern Hemisphere, 25km, Science
Quality, 1978-Present, Daily";
  }
}

Using griddap to Request Data and Graphs from Gridded Datasets

griddap lets you request a data subset, graph, or map from a gridded dataset (for example, sea surface temperature data from a satellite), via a specially formed URL. griddap uses the OPeNDAP (external link)

Data Access Protocol (DAP) (external link)

and its projection 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. It makes 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.

griddap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/griddap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/griddap/jplMURSST41.htmlTable?analysed_sst[(2002-06-01T09:00:00Z)][(-89.99):1000:(89.99)][(-179.99):1000:(180.0)]
Thus, the query is often a data variable name (e.g., analysed_sst), followed by [(start):stride:(stop)] (or a shorter variation of that) for each of the variable's dimensions (for example, [time][latitude][longitude]).

For details, see the griddap Documentation.