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Dataset Title:  Sea Surface Temperature, NOAA geopolar blended - Cumulative mean 2003-
2017 (2017 Reanalysis)
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Institution:  Office of Satellite Products and Operations   (Dataset ID: goes-poes-ghrsst-RAN-2003-2017-clim)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Make a graph
 
Dimensions ? Start ? Stride ? Stop ?  Size ?    Spacing ?
 time (UTC) ?      1    (just one value)
  < slider >
 latitude (degrees_north) ?      3600    0.05 (even)
  < slider >
 longitude (degrees_east) ?      7200    0.05 (even)
  < slider >
 
Grid Variables (which always also download all of the dimension variables) 
 analysed_sst (analysed sea surface temperature, degree_K) ?

File type: (more information)

(Documentation / Bypass this form) ?
 
(Please be patient. It may take a while to get the data.)


 

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.043064e+9, 1.043064e+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 "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.     Maturi, E., A. Harris, J. Mittaz, J. Sapper, G. Wick, X. Zhu, P. Dash, P. Koner, \"A New High-Resolution Sea Surface Temperature Blended Analysis\", Bulleting of the American Meteorological Society, 98 (5), 1015-1026, 2017.";
    String source "STAR-ACSPO_GAC, STAR-ACSPO_H-8, STAR-Geo_SST, UKMO-OSTIA";
    String standard_name "sea_surface_foundation_temperature";
    String units "degree_K";
    Float32 valid_max 4000.0;
    Float32 valid_min -200.0;
  }
  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";
    String Conventions "CF-1.6, Unidata Observation Dataset v1.0, COARDS, ACDD-1.3";
    String creator_email "andy.harris@noaa.gov";
    String creator_name "Satellite Applications and Research";
    String creator_url "www.star.nesdis.noaa.gov";
    String date_created "2017-06-22T21:31:01Z";
    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 
"Tue Feb  5 12:05:35 2019: ncatted -O -a easternmost_longitude,global,o,f,360.0 /mnt/r01/data/goes-poes_ghrsst/daily/20030120000000-STAR-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc
Tue Feb  5 12:05:35 2019: ncatted -O -a westernmost_longitude,global,o,f,0.0 /mnt/r01/data/goes-poes_ghrsst/daily/20030120000000-STAR-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc
Tue Feb  5 12:05:35 2019: ncatted -O -a valid_max,lon,o,f,360.0 /mnt/r01/data/goes-poes_ghrsst/daily/20030120000000-STAR-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc
Tue Feb  5 12:05:35 2019: ncatted -O -a valid_min,lon,o,f,0.0 /mnt/r01/data/goes-poes_ghrsst/daily/20030120000000-STAR-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc
Tue Dec 18 16:28:39 2018: ncap2 -O -s where(lon<0) lon=lon+360 20030120000000-STAR-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc 20030120000000-STAR-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc
Tue Dec 18 16:28:37 2018: ncks -O --msa_usr_rdr -d lon,0.0,180.0 -d lon,-180.0,0.0 20030120000000-STAR-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0.nc 20030120000000-STAR-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0-0-360.nc
Fri Oct 19 11:15:57 2018: ncatted -a add_offset,analysed_sst,o,f,273.15 20030120000000-STAR-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0.nc
Fri Oct 19 11:14:00 2018: ncatted -a add_offset,analysis_error,o,f,0. 20030120000000-STAR-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0.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
2024-04-27T00:10:57Z (local files)
2024-04-27T00:10:57Z https://oceanwatch.pifsc.noaa.gov/erddap/griddap/goes-poes-ghrsst-RAN-2003-2017-clim.das";
    String id "Geo_Polar_Blended_Night-STAR-L4-GLOB-v1.0";
    String infoUrl "https://podaac.jpl.nasa.gov/dataset/Geo_Polar_Blended_Night-STAR-L4-GLOB-v1.0";
    String institution "Office of Satellite Products and Operations";
    String keywords "analysed, analysed_sst, blended, data, earth, Earth Science > Oceans > Ocean Temperature > Sea Surface Temperature, foundation, global, infrared, ocean, oceans, office, operations, over, products, satellite, science, sea, sea_surface_foundation_temperature, sst, surface, temperature, time";
    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-STAR-L4-GLOB-v1.0";
    String naming_authority "org.ghrsst";
    String NCO "4.3.7";
    Int32 nco_openmp_thread_number 1;
    Float64 Northernmost_Northing 89.975;
    String platform "NOAA-16, NOAA-17, NOAA-18, NOAA-19, MetOpA, Himawari-8, GOES10, GOES11, GOES12, GOES13, GOES15, MTSAT1R, MTSAT2";
    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.     Maturi, E., A. Harris, J. Mittaz, J. Sapper, G. Wick, X. Zhu, P. Dash, P. Koner, \"A New High-Resolution Sea Surface Temperature Blended Analysis\", Bulleting of the American Meteorological Society, 98 (5), 1015-1026, 2017.";
    String sensor "AVHRR_GAC, AHI, GOES_Imager, JAMI";
    String source "STAR-ACSPO_GAC, STAR-ACSPO_H-8, STAR-Geo_SST, UKMO-OSTIA";
    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 "Analysed blended sea surface temperature over the global ocean. 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 ananlysis provide a daily gap free map of the foundation sea surface temperature at 0.05o spatial resolution.";
    String time_coverage_end "2003-01-20T12:00:00Z";
    String time_coverage_start "2003-01-20T12:00:00Z";
    String title "Sea Surface Temperature, NOAA geopolar blended - Cumulative mean 2003-2017 (2017 Reanalysis)";
    Float64 Westernmost_Easting 0.025;
  }
}

 

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.

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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