ERDDAP > griddap > Data Access Form

Dataset Title:	Sea Surface Temperature, NOAA geopolar blended - Monthly, 2002-Present (2017 Reanalysis)
Institution:	Office of Satellite Products and Operations   (Dataset ID: goes-poes-monthly-ghrsst-RAN)
Information:	Summary | License | FGDC | ISO 19115 | Metadata | Background | Make a graph

 

Dimensions	Start	Stride	Stop	Size	Spacing
time (UTC)				236	31 days 14h 5m 37s (uneven)
latitude (degrees_north)				3600	0.05 (even)
longitude (degrees_east)				7200	0.05 (even)

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

analysed_sst (analysed sea surface temperature, degree_K)

sea_ice_fraction (1)

File type: (more info) .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 (lat lon data only; lon 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,lat,lon,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 lat lon data; lon must be all below or all above 180). .kml - View a Google Earth .kml file (for lat, lon 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).

(Documentation / Bypass this form)
 
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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.0312272e+9, 1.6725744e+9;
    String axis "T";
    String calendar "Gregorian";
    String comment "Nominal time of Level 4 analysis";
    String ioos_category "Time";
    String long_name "reference time of sst field";
    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";
    Float32 actual_range -89.975, 89.975;
    String axis "Y";
    String comment "equirectangular projection";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
    Float32 valid_max 90.0;
    Float32 valid_min -90.0;
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range 0.025, 359.975;
    String axis "X";
    String comment "equirectangular projection";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
    Float32 valid_max 360.0;
    Float32 valid_min 0.0;
  }
  analysed_sst {
    Float32 _FillValue NaN;
    Float64 colorBarMaximum 305.0;
    Float64 colorBarMinimum 273.0;
    String comment "nighttime analysed SST for each ocean grid point";
    String ioos_category "Temperature";
    String long_name "analysed sea surface temperature";
    String references "Fieguth,P.W. et al. \"Mapping Mediterranean altimeter data with a multiresolution optimal interpolation algorithm\", J. Atmos. Ocean Tech, 15 (2): 535-546, 1998.     Fieguth, P. Multiply-Rooted Multiscale Models for Large-Scale Estimation, IEEE Image Processing, 10(11), 1676-1686, 2001.     Khellah, F., P.W. Fieguth, M.J. Murray and M.R. Allen, \"Statistical Processing of Large Image Sequences\", IEEE Transactions on Geoscience and Remote Sensing, 12 (1), 80-93, 2005.";
    String source "OSPO-ACSPO_VIIRS, OSPO-ACSPO_METOPB_FRAC, OSPO-GOES16_SST_L3,OSPO-GOES15_SST_L3, OSPO-METEOSAT11_SST_L3, OSPO-HIMA8_SST_L3";
    String standard_name "sea_surface_foundation_temperature";
    String units "degree_K";
    Float32 valid_max 4000.0;
    Float32 valid_min -200.0;
  }
  sea_ice_fraction {
    Float32 _FillValue NaN;
    Float64 colorBarMaximum 1.0;
    Float64 colorBarMinimum 0.0;
    String comment " Percentage of ice";
    String ioos_category "Ice Distribution";
    String long_name "sea ice fraction";
    String source "NCEP 1/12th degree ice mask";
    String standard_name "sea_ice_area_fraction";
    String units "1";
    Float32 valid_max 100.0;
    Float32 valid_min 0.0;
  }
  NC_GLOBAL {
    String acknowledgement "NOAA/NESDIS";
    String cdm_data_type "Grid";
    String comment "The Geo-Polar Blended Sea Surface Temperature (SST) Analysis combines multi-satellite retrievals of sea surface temperature into a single analysis of SST. This analysis includes only nighttime data.";
    String Conventions "CF-1.6, Unidata Observation Dataset v1.0, COARDS, ACDD-1.3";
    String creator_email "john.sapper@noaa.gov";
    String creator_name "Office of Satellite Products and Operations";
    String creator_type "group";
    String creator_url "www.osdpd.nesdis.noaa.gov";
    String date_created "2018-12-26T10:43:22Z";
    Float64 Easternmost_Easting 359.975;
    String gds_version_id "2.0";
    Float64 geospatial_lat_max 89.975;
    Float64 geospatial_lat_min -89.975;
    Float64 geospatial_lat_resolution 0.049999999999999996;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 359.975;
    Float64 geospatial_lon_min 0.025;
    Float64 geospatial_lon_resolution 0.05000000000000001;
    String geospatial_lon_units "degrees_east";
    String history 
"Sat Mar 25 05:41:18 2023: ncea -v analysed_sst,sea_ice_fraction /mnt/r01/data/goes-poes_ghrsst/daily/20230101000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230102000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230103000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230104000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230105000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230106000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230107000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230108000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230109000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230110000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230111000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230112000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230113000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230114000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230115000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230116000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230117000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230118000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230119000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230120000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230121000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230122000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230123000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230124000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230125000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230126000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230127000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230128000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230129000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230130000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc /mnt/r01/data/goes-poes_ghrsst/daily/20230131000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc 202301-gp-monthly.nc
Mon Jan  2 02:05:25 2023: ncatted -O -a easternmost_longitude,global,o,f,360.0 20230101000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc
Mon Jan  2 02:05:25 2023: ncatted -O -a westernmost_longitude,global,o,f,0.0 20230101000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc
Mon Jan  2 02:05:25 2023: ncatted -O -a valid_max,lon,o,f,360.0 20230101000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc
Mon Jan  2 02:05:25 2023: ncatted -O -a valid_min,lon,o,f,0.0 20230101000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc
Mon Jan  2 02:05:17 2023: ncap2 -O -s where(lon<0) lon=lon+360 20230101000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc 20230101000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc
Mon Jan  2 02:05:08 2023: ncks -O --msa_usr_rdr -d lon,0.0,180.0 -d lon,-180.0,0.0 20230101000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0.nc 20230101000000-OSPO-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc
NESDIS geo-SST L1 to L2 processor, NESDIS Advanced Clear-Sky Processor for Oceans (ACSPO), NESDIS Geo-Polar 1/20th degree Blended SST Analysis
2023-03-26T21:49:27Z (local files)
2023-03-26T21:49:27Z https://oceanwatch.pifsc.noaa.gov/erddap/griddap/goes-poes-monthly-ghrsst-RAN.das";
    String id "Geo_Polar_Blended_Night-OSPO-L4-GLOB-v1.0";
    String infoUrl "https://podaac.jpl.nasa.gov/dataset/Geo_Polar_Blended_Night-OSPO-L4-GLOB-v1.0";
    String institution "Office of Satellite Products and Operations";
    String keywords "analysed, analysed_sst, area, blended, cryosphere, data, distribution, earth, Earth Science > Cryosphere > Sea Ice > Ice Extent, Earth Science > Oceans > Ocean Temperature > Sea Surface Temperature, Earth Science > Oceans > Sea Ice > Ice Extent, extent, foundation, fraction, global, ice, ice distribution, infrared, input, night, ocean, oceans, office, only, operations, over, products, satellite, science, sea, sea_ice_area_fraction, sea_ice_fraction, sea_surface_foundation_temperature, sst, surface, temperature, time, using";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "GHRSST protocol describes data use as free and open";
    String metadata_link "https://podaac.jpl.nasa.gov/ws/metadata/dataset?format=iso&shortName=Geo_Polar_Blended_Night-OSPO-L4-GLOB-v1.0";
    String naming_authority "org.ghrsst";
    String NCO "netCDF Operators version 4.7.5 (Homepage = http://nco.sf.net, Code = https://github.com/nco/nco)";
    Int32 nco_openmp_thread_number 1;
    Float64 Northernmost_Northing 89.975;
    String platform "Suomi NPP, MetOp-B, GOESE (GOES-16), GOESW (GOES-15), Meteosat-11, Meteosat-08, Himawari-9";
    String processing_level "L4";
    String product_version "1.0";
    String project "Group for High Resolution Sea Surface Temperature";
    String publisher_email "ghrsst-po@nceo.ac.uk";
    String publisher_name "The GHRSST Project Office";
    String publisher_type "group";
    String publisher_url "https://www.ghrsst.org";
    String references "Fieguth,P.W. et al. \"Mapping Mediterranean altimeter data with a multiresolution optimal interpolation algorithm\", J. Atmos. Ocean Tech, 15 (2): 535-546, 1998.     Fieguth, P. Multiply-Rooted Multiscale Models for Large-Scale Estimation, IEEE Image Processing, 10(11), 1676-1686, 2001.     Khellah, F., P.W. Fieguth, M.J. Murray and M.R. Allen, \"Statistical Processing of Large Image Sequences\", IEEE Transactions on Geoscience and Remote Sensing, 12 (1), 80-93, 2005.";
    String sensor "VIIRS, AVHRR, ABI, Imager, SEVIRI, SEVIRI, AHI";
    String source "OSPO-ACSPO_VIIRS, OSPO-ACSPO_METOPB_FRAC, OSPO-GOES16_SST_L3, OSPO-GOES15_SST_L3, OSPO-METEOSAT11_SST_L3, OSPO-HIMA8_SST_L3";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -89.975;
    String spatial_resolution "0.05 degree";
    String standard_name_vocabulary "CF Standard Name Table v29";
    String summary "Monthly composite of analysed blended sea surface temperature over the global ocean using night only input data. An SST estimation scheme which combines multi-satellite retrievals of sea surface temperature datasets available from polar orbiters, geostationary InfraRed (IR) and microwave sensors into a single global analysis. This global SST analysis provides a daily gap free map of the foundation sea surface temperature at 0.05º spatial resolution. The monthly composites were generated from daily files by OceanWatch Central Pacific";
    String time_coverage_end "2023-01-01T12:00:00Z";
    String time_coverage_start "2002-09-05T12:00:00Z";
    String title "Sea Surface Temperature, NOAA geopolar blended - Monthly, 2002-Present (2017 Reanalysis)";
    Float64 Westernmost_Easting 0.025;
  }
}

 

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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[(2015-06-09T09:00:00Z)][(-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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