ERDDAP > griddap > Data Access Form

Dataset Title:	OCEAN:ICE - European circumpolar sea ice production fluxes
Institution:	Alfred-Wegener-Institut Helmholtz-Zentrum Für Polar- Und Meeresforschung (AWI)   (Dataset ID: EU_circumpolar_seaice_prod_fluxes_1992_2023)
Information:	Summary | License | FGDC | ISO 19115 | Metadata | Background | Files | Make a graph

 

Dimensions	Start	Stride	Stop	Size	Spacing
time (UTC)				384	30 days 10h 27m 53s (uneven)
latitude (degrees_north)				664	12.51885 (even)
longitude (degrees_east)				632	12.51981 (even)

Grid Variables (which always also download all of the dimension variables)

sea_ice_production (m/month)

File type: (more information) .asc - View OPeNDAP-style ISO-8859-1 comma-separated text. .csv - Download a ISO-8859-1 comma-separated text table (line 1: names; line 2: units; ISO 8601 times). .csvp - Download a ISO-8859-1 .csv file with line 1: name (units). Times are ISO 8601 strings. .csv0 - Download a ISO-8859-1 .csv file without column names or units. Times are ISO 8601 strings. .das - View the dataset's metadata via an ISO-8859-1 OPeNDAP Dataset Attribute Structure (DAS). .dds - View the dataset's structure via an ISO-8859-1 OPeNDAP Dataset Descriptor Structure (DDS). .dods - OPeNDAP clients use this to download the data in the DODS binary format. .esriAscii - Download an ISO-8859-1 ESRI ASCII file (latitude longitude data only; longitude must be all below or all above 180). .fgdc - View the dataset's UTF-8 FGDC .xml metadata. .graph - View a Make A Graph web page. .help - View a web page with a description of griddap. .html - View an OPeNDAP-style HTML Data Access Form. .htmlTable - View a UTF-8 .html web page with the data in a table. Times are ISO 8601 strings. .iso19115 - View the dataset's ISO 19115-2/19139 UTF-8 .xml metadata. .itx - Download an ISO-8859-1 Igor Text File. Each axis variable and each data variable becomes a wave. .json - View a table-like UTF-8 JSON file (missing value = 'null'; times are ISO 8601 strings). .jsonlCSV1 - View a UTF-8 JSON Lines CSV file with column names on line 1 (mv = 'null'; times are ISO 8601 strings). .jsonlCSV - View a UTF-8 JSON Lines CSV file without column names (mv = 'null'; times are ISO 8601 strings). .jsonlKVP - View a UTF-8 JSON Lines file with Key:Value pairs (missing value = 'null'; times are ISO 8601 strings). .mat - Download a MATLAB binary file. .nc - Download a NetCDF-3 binary file with COARDS/CF/ACDD metadata. .ncHeader - View the UTF-8 header (the metadata) for the NetCDF-3 .nc file. .ncml - View the dataset's structure and metadata as a UTF-8 NCML .xml file. .nccsv - Download a NetCDF-3-like 7-bit ASCII NCCSV .csv file with COARDS/CF/ACDD metadata. .nccsvMetadata - View the dataset's metadata as the top half of a 7-bit ASCII NCCSV .csv file. .ncoJson - Download a UTF-8 NCO lvl=2 JSON file with COARDS/CF/ACDD metadata. .odvTxt - Download time,latitude,longitude,otherVariables as an ODV Generic Spreadsheet File (.txt). .timeGaps - View a UTF-8 list of gaps in the time values which are larger than the median gap. .tsv - Download a ISO-8859-1 tab-separated text table (line 1: names; line 2: units; ISO 8601 times). .tsvp - Download a ISO-8859-1 .tsv file with line 1: name (units). Times are ISO 8601 strings. .tsv0 - Download a ISO-8859-1 .tsv file without column names or units. Times are ISO 8601 strings. .wav - Download a .wav audio file. All columns must be numeric and of the same type. .xhtml - View a UTF-8 XHTML (XML) file with the data in a table. Times are ISO 8601 strings. .geotif - View a grayscale GeoTIFF .tif file (for latitude longitude data; longitude must be all below or all above 180). .kml - View a Google Earth .kml file (for latitude, longitude data only). .smallPdf - View a small .pdf image file with a graph or map. .pdf - View a standard, medium-sized .pdf image file with a graph or map. .largePdf - View a large .pdf image file with a graph or map. .smallPng - View a small .png image file with a graph or map. .png - View a standard, medium-sized .png image file with a graph or map. .largePng - View a large .png image file with a graph or map. .transparentPng - View a .png image file (just the data, without axes, landmask, or legend).

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 6.96816e+8, 1.7039808e+9;
    String axis "T";
    String calendar "proleptic_gregorian";
    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";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range -3950.0, 4350.0;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String source_name "y";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range -3950.0, 3950.0;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String source_name "x";
    String standard_name "longitude";
    String units "degrees_east";
  }
  sea_ice_production {
    Float32 _FillValue NaN;
    String ioos_category "Ice Distribution";
    String long_name "Sea ice production";
    Float32 missing_value NaN;
    String standard_name "sea_ice_production";
    String units "m/month";
  }
  NC_GLOBAL {
    String acknowledgements 
"EU OCEAN:ICE Deliverable D1.4 (June 2024)
Gridded European circumpolar sea ice production fluxes
OCEAN:ICE is co-funded by the European Union, Horizon Europe Funding Programme for research and innovation under grant agreement Nr. 101060452 and by UK Research and Innovation";
    String CDI "Climate Data Interface version 2.3.0 (https://mpimet.mpg.de/cdi)";
    String cdm_data_type "Grid";
    String CDO "Climate Data Operators version 2.3.0 (https://mpimet.mpg.de/cdo)";
    String citation "Kaleschke, L. (2024). EU project OCEAN:ICE Deliverable: D1.4 Gridded European circumpolar sea ice production fluxes [Data set]. Zenodo. https://doi.org/10.5281/zenodo.11652686";
    String contributors_name "Kaleschke, Lars";
    String contributors_orcid "https://orcid.org/0000-0001-7086-3299";
    String Conventions "CF-1.10, COARDS, ACDD-1.3";
    String conventions "CF-1.6";
    String creator_name "Kaleschke, Lars";
    String creator_type "Person";
    String data_creation "2024.07.31";
    String data_doi "https://zenodo.org/records/11652686";
    String data_format_original "netCDF";
    String Description "OCEAN:ICE - European circumpolar sea ice production fluxes";
    Float64 Easternmost_Easting 3950.0;
    Float64 geospatial_lat_max 4350.0;
    Float64 geospatial_lat_min -3950.0;
    Float64 geospatial_lat_resolution 12.518853695324283;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 3950.0;
    Float64 geospatial_lon_min -3950.0;
    Float64 geospatial_lon_resolution 12.519809825673534;
    String geospatial_lon_units "degrees_east";
    String grid "EPSG:3412 # NSIDC Polar Stereographic for South";
    String history 
"Thu Apr 18 20:46:13 2024: cdo -f nc2 mergetime SIP_199201.nc SIP_199202.nc SIP_199203.nc SIP_199204.nc SIP_199205.nc SIP_199206.nc SIP_199207.nc SIP_199208.nc SIP_199209.nc SIP_199210.nc SIP_199211.nc SIP_199212.nc SIP_199301.nc SIP_199302.nc SIP_199303.nc SIP_199304.nc SIP_199305.nc SIP_199306.nc SIP_199307.nc SIP_199308.nc SIP_199309.nc SIP_199310.nc SIP_199311.nc SIP_199312.nc SIP_199401.nc SIP_199402.nc SIP_199403.nc SIP_199404.nc SIP_199405.nc SIP_199406.nc SIP_199407.nc SIP_199408.nc SIP_199409.nc SIP_199410.nc SIP_199411.nc SIP_199412.nc SIP_199501.nc SIP_199502.nc SIP_199503.nc SIP_199504.nc SIP_199505.nc SIP_199506.nc SIP_199507.nc SIP_199508.nc SIP_199509.nc SIP_199510.nc SIP_199511.nc SIP_199512.nc SIP_199601.nc SIP_199602.nc SIP_199603.nc SIP_199604.nc SIP_199605.nc SIP_199606.nc SIP_199607.nc SIP_199608.nc SIP_199609.nc SIP_199610.nc SIP_199611.nc SIP_199612.nc SIP_199701.nc SIP_199702.nc SIP_199703.nc SIP_199704.nc SIP_199705.nc SIP_199706.nc SIP_199707.nc SIP_199708.nc SIP_199709.nc SIP_199710.nc SIP_199711.nc SIP_199712.nc SIP_199801.nc SIP_199802.nc SIP_199803.nc SIP_199804.nc SIP_199805.nc SIP_199806.nc SIP_199807.nc SIP_199808.nc SIP_199809.nc SIP_199810.nc SIP_199811.nc SIP_199812.nc SIP_199901.nc SIP_199902.nc SIP_199903.nc SIP_199904.nc SIP_199905.nc SIP_199906.nc SIP_199907.nc SIP_199908.nc SIP_199909.nc SIP_199910.nc SIP_199911.nc SIP_199912.nc SIP_200001.nc SIP_200002.nc SIP_200003.nc SIP_200004.nc SIP_200005.nc SIP_200006.nc SIP_200007.nc SIP_200008.nc SIP_200009.nc SIP_200010.nc SIP_200011.nc SIP_200012.nc SIP_200101.nc SIP_200102.nc SIP_200103.nc SIP_200104.nc SIP_200105.nc SIP_200106.nc SIP_200107.nc SIP_200108.nc SIP_200109.nc SIP_200110.nc SIP_200111.nc SIP_200112.nc SIP_200201.nc SIP_200202.nc SIP_200203.nc SIP_200204.nc SIP_200205.nc SIP_200206.nc SIP_200207.nc SIP_200208.nc SIP_200209.nc SIP_200210.nc SIP_200211.nc SIP_200212.nc SIP_200301.nc SIP_200302.nc SIP_200303.nc SIP_200304.nc SIP_200305.nc SIP_200306.nc SIP_200307.nc SIP_200308.nc SIP_200309.nc SIP_200310.nc SIP_200311.nc SIP_200312.nc SIP_200401.nc SIP_200402.nc SIP_200403.nc SIP_200404.nc SIP_200405.nc SIP_200406.nc SIP_200407.nc SIP_200408.nc SIP_200409.nc SIP_200410.nc SIP_200411.nc SIP_200412.nc SIP_200501.nc SIP_200502.nc SIP_200503.nc SIP_200504.nc SIP_200505.nc SIP_200506.nc SIP_200507.nc SIP_200508.nc SIP_200509.nc SIP_200510.nc SIP_200511.nc SIP_200512.nc SIP_200601.nc SIP_200602.nc SIP_200603.nc SIP_200604.nc SIP_200605.nc SIP_200606.nc SIP_200607.nc SIP_200608.nc SIP_200609.nc SIP_200610.nc SIP_200611.nc SIP_200612.nc SIP_200701.nc SIP_200702.nc SIP_200703.nc SIP_200704.nc SIP_200705.nc SIP_200706.nc SIP_200707.nc SIP_200708.nc SIP_200709.nc SIP_200710.nc SIP_200711.nc SIP_200712.nc SIP_200801.nc SIP_200802.nc SIP_200803.nc SIP_200804.nc SIP_200805.nc SIP_200806.nc SIP_200807.nc SIP_200808.nc SIP_200809.nc SIP_200810.nc SIP_200811.nc SIP_200812.nc SIP_200901.nc SIP_200902.nc SIP_200903.nc SIP_200904.nc SIP_200905.nc SIP_200906.nc SIP_200907.nc SIP_200908.nc SIP_200909.nc SIP_200910.nc SIP_200911.nc SIP_200912.nc SIP_201001.nc SIP_201002.nc SIP_201003.nc SIP_201004.nc SIP_201005.nc SIP_201006.nc SIP_201007.nc SIP_201008.nc SIP_201009.nc SIP_201010.nc SIP_201011.nc SIP_201012.nc SIP_201101.nc SIP_201102.nc SIP_201103.nc SIP_201104.nc SIP_201105.nc SIP_201106.nc SIP_201107.nc SIP_201108.nc SIP_201109.nc SIP_201110.nc SIP_201111.nc SIP_201112.nc SIP_201201.nc SIP_201202.nc SIP_201203.nc SIP_201204.nc SIP_201205.nc SIP_201206.nc SIP_201207.nc SIP_201208.nc SIP_201209.nc SIP_201210.nc SIP_201211.nc SIP_201212.nc SIP_201301.nc SIP_201302.nc SIP_201303.nc SIP_201304.nc SIP_201305.nc SIP_201306.nc SIP_201307.nc SIP_201308.nc SIP_201309.nc SIP_201310.nc SIP_201311.nc SIP_201312.nc SIP_201401.nc SIP_201402.nc SIP_201403.nc SIP_201404.nc SIP_201405.nc SIP_201406.nc SIP_201407.nc SIP_201408.nc SIP_201409.nc SIP_201410.nc SIP_201411.nc SIP_201412.nc SIP_201501.nc SIP_201502.nc SIP_201503.nc SIP_201504.nc SIP_201505.nc SIP_201506.nc SIP_201507.nc SIP_201508.nc SIP_201509.nc SIP_201510.nc SIP_201511.nc SIP_201512.nc SIP_201601.nc SIP_201602.nc SIP_201603.nc SIP_201604.nc SIP_201605.nc SIP_201606.nc SIP_201607.nc SIP_201608.nc SIP_201609.nc SIP_201610.nc SIP_201611.nc SIP_201612.nc SIP_201701.nc SIP_201702.nc SIP_201703.nc SIP_201704.nc SIP_201705.nc SIP_201706.nc SIP_201707.nc SIP_201708.nc SIP_201709.nc SIP_201710.nc SIP_201711.nc SIP_201712.nc SIP_201801.nc SIP_201802.nc SIP_201803.nc SIP_201804.nc SIP_201805.nc SIP_201806.nc SIP_201807.nc SIP_201808.nc SIP_201809.nc SIP_201810.nc SIP_201811.nc SIP_201812.nc SIP_201901.nc SIP_201902.nc SIP_201903.nc SIP_201904.nc SIP_201905.nc SIP_201906.nc SIP_201907.nc SIP_201908.nc SIP_201909.nc SIP_201910.nc SIP_201911.nc SIP_201912.nc SIP_202001.nc SIP_202002.nc SIP_202003.nc SIP_202004.nc SIP_202005.nc SIP_202006.nc SIP_202007.nc SIP_202008.nc SIP_202009.nc SIP_202010.nc SIP_202011.nc SIP_202012.nc SIP_202101.nc SIP_202102.nc SIP_202103.nc SIP_202104.nc SIP_202105.nc SIP_202106.nc SIP_202107.nc SIP_202108.nc SIP_202109.nc SIP_202110.nc SIP_202111.nc SIP_202112.nc SIP_202201.nc SIP_202202.nc SIP_202203.nc SIP_202204.nc SIP_202205.nc SIP_202206.nc SIP_202207.nc SIP_202208.nc SIP_202209.nc SIP_202210.nc SIP_202211.nc SIP_202212.nc SIP_202301.nc SIP_202302.nc SIP_202303.nc SIP_202304.nc SIP_202305.nc SIP_202306.nc SIP_202307.nc SIP_202308.nc SIP_202309.nc SIP_202310.nc SIP_202311.nc SIP_202312.nc ../1992_2023.nc
2024-11-06T09:25:27Z (local files)
2024-11-06T09:25:27Z https://er1.s4oceanice.eu/erddap/griddap/EU_circumpolar_seaice_prod_fluxes_1992_2023.das";
    String infoUrl "https://gitlab.awi.de/ocean-ice/deliverable";
    String institution "Alfred-Wegener-Institut Helmholtz-Zentrum Für Polar- Und Meeresforschung (AWI)";
    String institution_country "DE";
    String institution_edmo_code "1368";
    String keywords "Earth Science > Climate Indicators > Cryospheric Indicators > Sea Ice Concentration, EARTH SCIENCE SERVICES > ENVIRONMENTAL ADVISORIES > MARINE ADVISORIES > SEA ICE, sea ice concentration, sea ice production";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "CC-BY4.0";
    String metadata_url "https://zenodo.org/records/12166097";
    String naming_authority "OCEAN:ICE";
    String netCDF_created_by "Lars.Kaleschke@AWI.de";
    Float64 Northernmost_Northing 4350.0;
    String references "ASI SSM/I sea ice concentration data used as input are available at IFREMER/CERSAT ftp://ftp.ifremer.fr/ifremer/cersat/products/gridded/psi-concentration ECMWF ERA5 hourly data on single levels from 1940 to present https://doi.org/10.24381/cds.adbb2d47";
    String source "Reanalysis";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -3950.0;
    String spatial_resolution "12.5 km";
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "This dataset on sea ice production (SIP) in Antarctic coastal polynyas offers crucial insights into these regions' roles in sea ice and dense water formation. Using Earth Observation data and atmospheric reanalysis, the dataset employs a heat budget method to estimate SIP. It incorporates sea ice concentration (SIC) from passive microwave sensors and near-surface wind speed and surface air temperature from ECMWF ERA5 reanalysis. Comparative analysis with previous studies confirms the dataset's accuracy in depicting spatial patterns and the magnitude of ice production, though some variations exist across larger polynyas. While simplifications may increase uncertainties in absolute SIP values, this dataset is a valuable resource for understanding the dynamics and variability of Antarctic polynya SIP from 1992 to 2023.";
    String time_coverage_end "2023-12-31T00:00:00Z";
    String time_coverage_resolution "monthly";
    String time_coverage_start "1992-01-31T00:00:00Z";
    String time_resolution "monthly";
    String title "OCEAN:ICE - European circumpolar sea ice production fluxes";
    String variables "Latitude, Longitude, Sea Ice Production";
    Float64 Westernmost_Easting -3950.0;
  }
}

 

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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 Data Access Protocol (DAP) and its projection constraints.

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.

 

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