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Dataset Title:  SST, GHRSST Blended, MW-IR-OI, Science Quality, Global, 2006-2011 (1 Day
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Institution:  NOAA NMFS SWFSC ERD   (Dataset ID: erdG1ssta1day)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Make a graph
Dimensions ? Start ? Stride ? Stop ?  Size ?    Spacing ?
 time (UTC) ?      1694    1 day 3h 54m 20s (uneven)
  < slider >
 latitude (degrees_north) ?      2048    0.08789062 (even)
  < slider >
 longitude (degrees_east) ?      4096    0.08789065 (even)
  < slider >
Grid Variables (which always also download all of the dimension variables) 
 analyzed_sst (Analyzed Sea Surface Temperature, degree_C) ?
 analysis_error (Estimated Error Standard Deviation of analyzed_sst, degree_C) ?
 mask (Sea/Land/Lake/Ice Field Composite Mask) ?

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 1.1360736e+9, 1.306152e+9;
    String axis "T";
    String calendar "Gregorian";
    String ioos_category "Time";
    String long_name "reference time of sst file";
    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 -89.95605, 89.95605;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range -179.9561, 179.9561;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  analyzed_sst {
    Float32 _FillValue -327.68;
    Float64 colorBarMaximum 32.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Temperature";
    String long_name "Analyzed Sea Surface Temperature";
    String standard_name "sea_surface_temperature";
    String type "foundation";
    String units "degree_C";
    Float32 valid_max 45.0;
    Float32 valid_min -3.0;
  analysis_error {
    Float32 _FillValue -327.68;
    Float64 colorBarMaximum 1.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Temperature";
    String long_name "Estimated Error Standard Deviation of analyzed_sst";
    String units "degree_C";
    Float32 valid_max 2.5;
    Float32 valid_min 0.0;
  mask {
    Byte _FillValue 127;
    String _Unsigned "false";
    Float64 colorBarMaximum 16.0;
    Float64 colorBarMinimum 0.0;
    String flag_meanings "sea land lake ice ir mw bad";
    String flag_values "0b,1b,2b,3b,4b,5b,6";
    String ioos_category "Temperature";
    String long_name "Sea/Land/Lake/Ice Field Composite Mask";
    Byte valid_max 127;
    Byte valid_min -127;
    String cdm_data_type "Grid";
    String contact "";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "";
    String creator_name "NOAA NMFS SWFSC ERD";
    String creator_type "institution";
    String creator_url "";
    String DSD_entry_id "REMSS-L4HRfnd-GLOB-mw_ir_OI";
    Float64 Easternmost_Easting 179.9561;
    Int16 file_quality_index 1;
    String GDS_version_id "GDS-v1.0-rev1.6";
    Float64 geospatial_lat_max 89.95605;
    Float64 geospatial_lat_min -89.95605;
    Float64 geospatial_lat_resolution 0.08789062042012702;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 179.9561;
    Float64 geospatial_lon_min -179.9561;
    Float64 geospatial_lon_resolution 0.08789064713064712;
    String geospatial_lon_units "degrees_east";
    String history 
"Remote Sensing Systems, Inc.
NOAA CoastWatch (West Coast Node)
    String infoUrl "";
    String institution "NOAA NMFS SWFSC ERD";
    String keywords "1-day, analysed, composite, day, deviation, Earth Science > Oceans > Ocean Temperature > Sea Surface Temperature, error, estimated, field, foundation, global, ice, identifier, lake, land, mask, ocean, oceans, remote, sea, sea/land/lake/ice, sea_surface_temperature, sensing, sst, standard, statistics, surface, systems, temperature";
    String keywords_vocabulary "GCMD Science Keywords";
    String license 
"The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.";
    String naming_authority "gov.noaa.pfeg.coastwatch";
    Float64 Northernmost_Northing 89.95605;
    String product_version "v03";
    String publisher_email "";
    String publisher_name "NOAA NMFS SWFSC ERD";
    String publisher_type "institution";
    String publisher_url "";
    String references "";
    String sourceUrl "";
    Float64 Southernmost_Northing -89.95605;
    String spatial_resolution "9 km";
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary 
"THIS DATASET WILL NOT BE UPDATED AFTER 2011-05-23. This dataset was terminated with the demise of the AMSR-E sensor on Aqua. 
Analyzed Foundation, Microwave + InfraRed Optimally Interpolated, Science Quality, Global, Sea Surface Temperature data. The through-cloud capabilities of microwave radiometers provide a valuable picture of global sea surface temperature (SST). To utilize this, scientists at Remote Sensing Systems have calculated a daily, Optimally Interpolated (OI) SST product at quarter degree (~25 kilometer) resolution. This product is ideal for research activities in which a complete, daily SST map is more desirable than one with missing data due to orbital gaps or environmental conditions precluding SST retrieval. Improved global daily NRT SSTs should be useful for a wide range of scientific and operational activities. The addition of SST derived from Infrared (IR) measurements allows higher spatial resolution, and SST near land.  However, IR input is less accurate than MW due to cloud contamination. Blending MW and IR enables greater coverage and higher accuracy than IR only SSTs, but current OI does not completely eliminate cloud contamination inherent to IR SSTs.";
    String time_coverage_end "2011-05-23T12:00:00Z";
    String time_coverage_start "2006-01-01T00:00:00Z";
    String title "SST, GHRSST Blended, MW-IR-OI, Science Quality, Global, 2006-2011 (1 Day Composite)";
    Float64 Westernmost_Easting -179.9561;


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{?query}
For example,[(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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