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Dataset Title:  Analysed blended SST over the global ocean using night only input data Subscribe RSS
Institution:  Office of Satellite Products and Operations   (Dataset ID: nasa_jpl_1a3a_c9d5_2366)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form
 
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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 {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.4017104e+9, 1.4563152e+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 -179.975, 179.975;
    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 180.0;
    Float32 valid_min -180.0;
  }
  analysis_error {
    Float32 _FillValue -54.53;
    Float64 colorBarMaximum 5.0;
    Float64 colorBarMinimum 0.0;
    String comment "Estimate of internal analysis accuracy";
    String ioos_category "Statistics";
    String long_name "estimated error standard deviation of analysed_sst";
    String units "degree_C";
    Float32 valid_max 278.15;
    Float32 valid_min 273.15;
  }
  mask {
    Byte _FillValue 0;
    String _Unsigned "false";
    Float64 colorBarMaximum 5.0;
    Float64 colorBarMinimum 0.0;
    String comment "b0: 1=grid cell is water, b1: 1=grid cell is land, b2: 1=grid cell is ice";
    String flag_meanings "water land ice";
    Byte flag_values 1, 2, 4;
    String ioos_category "Ice Distribution";
    String long_name "sea/land/ice bit mask";
    String source "NCEP 1/12th degree ice mask, OSTIA land mask";
    String standard_name "sea_land_ice_bit_mask";
    Byte valid_max 4;
    Byte valid_min 1;
  }
  sea_ice_fraction {
    Float32 _FillValue -1.28;
    Float64 colorBarMaximum 100.0;
    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 1.0;
    Float32 valid_min 0.0;
  }
  analysed_sst {
    Float32 _FillValue -327.68;
    Float64 colorBarMaximum 32.0;
    Float64 colorBarMinimum 0.0;
    String comment "nighttime analysed SST for each ocean grid point";
    String ioos_category "Temperature";
    String long_name "analysed sea surface temperature";
    String reference "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-GOES13_SST_L3,OSPO-GOES15_SST_L3, OSPO-METEOSAT10_SST_L3, OSPO-MTSAT2_SST_L3";
    String standard_name "sea_surface_foundation_temperature";
    String units "degree_C";
    Float32 valid_max 34.999992;
    Float32 valid_min -2.0000062;
  }
  NC_GLOBAL {
    String acknowledgment "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_url "www.osdpd.nesdis.noaa.gov";
    String date_created "2015-02-01T13:22:35Z";
    Float64 Easternmost_Easting 179.975;
    Float64 file_quality_level 0.0;
    String Geo_Polar_Blended_Night_OSPO_L4_GLOB_v1_0_Documentation "https://podaac.jpl.nasa.gov/dataset/Geo_Polar_Blended_Night-OSPO-L4-GLOB-v1.0";
    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 179.975;
    Float64 geospatial_lon_min -179.975;
    Float64 geospatial_lon_resolution 0.049999999999999996;
    String geospatial_lon_units "degrees_east";
    String history 
"NESDIS geo-SST L1 to L2 processor, NESDIS Advanced Clear-Sky Processor for Oceans (ACSPO), NESDIS Geo-Polar 1/20th degree Blended SST Analysis
2018-07-17T04:07:16Z https://thredds.jpl.nasa.gov/thredds/dodsC/OceanTemperature/Geo_Polar_Blended_Night-OSPO-L4-GLOB-v1.0.nc
2018-07-17T04:07:16Z http://upwell.pfeg.noaa.gov/griddap/nasa_jpl_1a3a_c9d5_2366.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, analysis_error, area, bit, blended, cryosphere, data, deviation, distribution, Earth Science > Cryosphere > Sea Ice > Ice Extent, Earth Science > Oceans > Ocean Temperature > Sea Surface Temperature, Earth Science > Oceans > Sea Ice > Ice Extent, error, estimated, extent, foundation, fraction, global, ice, ice distribution, infrared, input, land, mask, night, noaa, ocean, oceans, office, only, operations, osdpd, ospo, over, product, products, satellite, sea, sea/land/ice, sea_ice_area_fraction, sea_ice_fraction, sea_land_ice_bit_mask, sea_surface_foundation_temperature, sst, standard, statistics, 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 netcdf_version_id "4.1.2";
    Float64 Northernmost_Northing 89.975;
    String platform "Suomi NPP  MetOpB GOESE (GOES-13) GOESW (GOES-15) mtsat-2;";
    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_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_FRAC, GOES_Imager, GOES_Imager, JAMI";
    String source "OSPO-ACSPO_VIIRS, OSPO-ACSPO_METOPB_FRAC, OSPO-GOES13_SST_L3, OSPO-GOES15_SST_L3, OSPO-METEOSAT10_SST_L3, OSPO-MTSAT2_SST_L3";
    String sourceUrl "https://thredds.jpl.nasa.gov/thredds/dodsC/OceanTemperature/Geo_Polar_Blended_Night-OSPO-L4-GLOB-v1.0.nc";
    Float64 Southernmost_Northing -89.975;
    String spatial_resolution "0.05 degree";
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "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 ananlysis provide a daily gap free map of the foundation sea surface temperature at 0.05o spatial resolution. (Geo Polar Blended Night-Office of Satellite and Product Operations (OSPO)-L4-GLOB-v1.0)";
    String time_coverage_end "2016-02-24T12:00:00Z";
    String time_coverage_start "2014-06-02T12:00:00Z";
    String title "Analysed blended SST over the global ocean using night only input data";
    String uuid "95a73067-8e61-4a70-9c12-2c3cbc14f901";
    Float64 Westernmost_Easting -179.975;
  }
}

 

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://upwell.pfeg.noaa.gov/erddap/griddap/datasetID.fileType{?query}
For example,
https://upwell.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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