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Dataset Title:  Multi-scale High Resolution (MUR) SST Analysis, SST Anomaly, fv04.2, Global, 0.
25°, 2002-present
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Institution:  Jet Propulsion Laboratory   (Dataset ID: jplMURSST42)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
 
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Y Axis:  ?
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time (UTC) ?     specify just 1 value →
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longitude (degrees_east) ?
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Color Bar:   Continuity:   Scale: 
   Minimum:   Maximum:   N Sections: 
Draw land mask: 
Y Axis Minimum:   Maximum:   
 
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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 1.0308708e+9, 1.7086788e+9;
    String axis "T";
    String comment "Nominal time of analyzed fields";
    String coverage_content_type "coordinate";
    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 -89.875, 89.875;
    String axis "Y";
    String comment "geolocations inherited from the input data without correction";
    String coverage_content_type "coordinate";
    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 -179.875, 179.875;
    String axis "X";
    String comment "geolocations inherited from the input data without correction";
    String coverage_content_type "coordinate";
    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;
  }
  analysed_sst {
    Float64 _FillValue -7.768000000000001;
    Float64 colorBarMaximum 32.0;
    Float64 colorBarMinimum 0.0;
    String comment "\"Final\" version using Multi-Resolution Variational Analysis (MRVA) method for interpolation";
    String coverage_content_type "physicalMeasurement";
    String ioos_category "Temperature";
    String long_name "analysed sea surface temperature";
    String source "MODIS_T-JPL, MODIS_A-JPL, AMSR2-REMSS, AVHRRMTB_G-NAVO, iQUAM-NOAA/NESDIS, Ice_Conc-OSISAF";
    String standard_name "sea_surface_foundation_temperature";
    String units "degree_C";
    Float64 valid_max 57.767;
    Float64 valid_min -7.767000000000003;
  }
  analysis_error {
    Float64 _FillValue -327.68;
    Float64 colorBarMaximum 5.0;
    Float64 colorBarMinimum 0.0;
    String comment "uncertainty in \"analysed_sst\"";
    String coverage_content_type "qualityInformation";
    String ioos_category "Statistics";
    String long_name "estimated error standard deviation of analysed_sst";
    String units "degree_C";
    Float64 valid_max 327.67;
    Float64 valid_min 0.0;
  }
  mask {
    Byte _FillValue -128;
    String _Unsigned "false";
    Float64 colorBarMaximum 20.0;
    Float64 colorBarMinimum 0.0;
    String comment "flag interpretation as integer values:  1=water, 2=land, 5=lake, 9=water with ice in the grid, 13=lake with ice in the grid, 17=river";
    String coverage_content_type "referenceInformation";
    Byte flag_masks 1, 2, 4, 8, 16;
    String flag_meanings "water land optional_lake_surface sea_ice optional_river_surface";
    String ioos_category "Identifier";
    String long_name "sea/land field composite mask";
    String source "GMT \"grdlandmask\", ice flag from sea_ice_fraction data";
    String standard_name "land_binary_mask";
    Byte valid_max 31;
    Byte valid_min 1;
  }
  sea_ice_fraction {
    Float64 _FillValue -1.28;
    Float64 colorBarMaximum 1.0;
    Float64 colorBarMinimum 0.0;
    String comment "ice fraction is a dimensionless quantity between 0 and 1; it has been interpolated by a nearest neighbor approach; EUMETSAT OSI-SAF files used: ice_conc_nh_polstere-100_multi_202402161200.nc, ice_conc_sh_polstere-100_multi_202402161200.nc.";
    String coverage_content_type "auxiliaryInformation";
    String ioos_category "Ice Distribution";
    String long_name "sea ice area fraction";
    String source "EUMETSAT OSI-SAF, copyright EUMETSAT";
    String standard_name "sea_ice_area_fraction";
    Float64 valid_max 1.0;
    Float64 valid_min 0.0;
  }
  sst_anomaly {
    Float64 _FillValue -32.768;
    Float64 colorBarMaximum 3.0;
    Float64 colorBarMinimum -3.0;
    String comment "anomaly reference to the day-of-year average between 2003 and 2014";
    String coverage_content_type "auxiliaryInformation";
    String ioos_category "Temperature";
    String long_name "SST anomaly from a seasonal SST climatology based on the MUR data over 2003-2014 period";
    String standard_name "surface_temperature_anomaly";
    String units "kelvin";
    Float64 valid_max 32.767;
    Float64 valid_min -32.767;
  }
  NC_GLOBAL {
    String _NCProperties "version=2,netcdf=4.7.4,hdf5=1.8.12";
    String acknowledgement "Please acknowledge the use of these data with the following statement:  These data were provided by JPL under support by NASA MEaSUREs and COVERAGE programs.";
    String cdm_data_type "Grid";
    String comment "MUR = \"Multi-scale Ultra-high Resolution\"";
    String Conventions "CF-1.10, ACDD-1.3, COARDS";
    String creator_email "ghrsst@podaac.jpl.nasa.gov";
    String creator_institution "Jet Propulsion Laboratory";
    String creator_name "JPL MUR SST project";
    String creator_type "group";
    String creator_url "https://podaac.jpl.nasa.gov/dataset/MUR-JPL-L4-GLOB-v4.1";
    String date_created "2024-02-25";
    Float64 Easternmost_Easting 179.875;
    String gds_version_id "2.0";
    Float64 geospatial_lat_max 89.875;
    Float64 geospatial_lat_min -89.875;
    Float64 geospatial_lat_resolution 0.25;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 179.875;
    Float64 geospatial_lon_min -179.875;
    Float64 geospatial_lon_resolution 0.25;
    String geospatial_lon_units "degrees_east";
    String history 
"created at nominal 4-day latency; replaced nrt (1-day latency) version.
2024-02-25T09:09:22Z (local files)
2024-02-25T09:09:22Z http://coastwatch.pfeg.noaa.gov/griddap/jplMURSST42.das";
    String id "MUR25-JPL-L4-GLOB-v04.2";
    String infoUrl "https://podaac.jpl.nasa.gov/ws/metadata/dataset/?format=iso&shortName=MUR25-JPL-L4-GLOB-v04.2";
    String institution "Jet Propulsion Laboratory";
    String instrument "MODIS, AMSR2, AVHRR, in-situ";
    String keywords "0.25-degree, 2003-2014, analysed, analysed_sst, analysis_error, anomaly, area, based, binary, climatology, composite, cryosphere, daily, data, day, degree, deviation, distribution, earth, Earth Science > Cryosphere > Sea Ice > Ice Extent, Earth Science > Land Surface > Land Temperature > Land Surface Temperature, Earth Science > Oceans > Ocean Temperature > Sea Surface Temperature, Earth Science > Oceans > Sea Ice > Ice Extent, error, estimated, extent, field, final, foundation, fraction, high, ice, ice distribution, identifier, jet, jpl, laboratory, land, land_binary_mask, mask, multi, multi-scale, mur, ocean, oceans, over, period, product, propulsion, resolution, scale, science, sea, sea/land, sea_ice_area_fraction, sea_ice_fraction, sea_surface_foundation_temperature, seasonal, sst, sst_anomaly, standard, statistics, surface, surface_temperature_anomaly, temperature, time, ultra, ultra-high";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "These data are available free of charge under data policy of JPL PO.DAAC.";
    String metadata_link "https://podaac.jpl.nasa.gov/ws/metadata/dataset/?format=iso&shortName=MUR25-JPL-L4-GLOB-v04.2";
    String naming_authority "org.ghrsst";
    Float64 Northernmost_Northing 89.875;
    String platform "Terra, Aqua, GCOM-W, MetOp-B, Buoys/Ships";
    String processing_level "L4";
    String product_version "04.2";
    String program "NASA Earth Science Data and Information System (ESDIS)";
    String project "NASA MEaSUREs and COVERAGE";
    String publisher_email "gpc@ghrsst.org";
    String publisher_name "GHRSST Project Office";
    String publisher_type "group";
    String publisher_url "https://www.ghrsst.org";
    String references "Chin et al. (2017) \"Remote Sensing of Environment\", volulme 200, pages 154-169.  https://dx.doi.org/10.1016/j.rse.2017.07.029";
    String sensor "MODIS, AMSR2, AVHRR, in-situ";
    String source "MODIS_T-JPL, MODIS_A-JPL, AMSR2-REMSS, AVHRRMTB_G-NAVO, iQUAM-NOAA/NESDIS, Ice_Conc-OSISAF";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -89.875;
    String spatial_resolution "0.25 degrees";
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "A low-resolution version of the Multi-scale Ultra-high Resolution (MUR) Sea Surface Temperature (SST) analysis, a merged, multi-sensor L4 Foundation SST analysis product from Jet Propulsion Laboratory (JPL).";
    String testOutOfDate "now-3days";
    String time_coverage_end "2024-02-23T09:00:00Z";
    String time_coverage_resolution "P1D";
    String time_coverage_start "2002-09-01T09:00:00Z";
    String title "Multi-scale High Resolution (MUR) SST Analysis, SST Anomaly, fv04.2, Global, 0.25°, 2002-present";
    Float64 Westernmost_Easting -179.875;
  }
}

 

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[(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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