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Dataset Title:  NOAA - Optimum Interpolation (OI) Sea Surface Temperature (SST) V2 High
Resolution Dataset
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Institution:  National Oceanic and Atmospheric Administration (NOAA)   (Dataset ID: NOAA_OISST_v2)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Make a graph
 
Dimensions ? Start ? Stride ? Stop ?  Size ?    Spacing ?
 time (UTC) ?      518    30 days 10h 29m 29s (uneven)
  < slider >
 latitude (degrees_north) ?      720    0.25 (even)
  < slider >
 longitude (degrees_east) ?      1440    0.25 (even)
  < slider >
 
Grid Variables (which always also download all of the dimension variables) 
 sst (Monthly Mean of Sea Surface Temperature, degree_C) ?

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 {
    UInt32 _ChunkSizes 512;
    String _CoordinateAxisType "Time";
    Float64 actual_range 3.681504e+8, 1.7277408e+9;
    String avg_period "0000-01-00 00:00:00";
    String axis "T";
    String calendar "gregorian";
    String delta_t "0000-01-00 00:00:00";
    String ioos_category "Time";
    String long_name "Time";
    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 ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range 0.125, 359.875;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  sst {
    UInt32 _ChunkSizes 1, 720, 1440;
    Float32 actual_range -1.8, 32.14;
    Float64 colorBarMaximum 32.0;
    Float64 colorBarMinimum 0.0;
    String level_desc "Surface";
    String long_name "Monthly Mean of Sea Surface Temperature";
    Float32 missing_value -9.96921e+36;
    String parent_stat "Individual Observations";
    Float32 precision 2.0;
    String standard_name "sea_surface_temperature";
    String statistic "Monthly Mean";
    String units "degree_C";
    Float32 valid_range -3.0, 45.0;
    String var_desc "Sea Surface Temperature";
  }
  NC_GLOBAL {
    String _NCProperties "version=2,netcdf=4.7.0,hdf5=1.10.5,";
    String cdm_data_type "Grid";
    String citation "Huang, B., C. Liu, V. Banzon, E. Freeman, G. Graham, B. Hankins, T. Smith, and H.-M. Zhang, 2021: Improvements of the Daily Optimum Interpolation Sea Surface Temperature (DOISST) Version 2.1, Journal of Climate, 34, 2923-2939. doi: 10.1175/JCLI-D-20-0166.1. Accessed via [project] on YYYY-MM-DD.";
    String comment 
"Data described in  Reynolds, R.W., N.A. Rayner, T.M.
Smith, D.C. Stokes, and W. Wang, 2002: An Improved In Situ and Satellite
SST Analysis for Climate, J. Climate";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    String creator_email "ncei.info@noaa.gov";
    String creator_name "National Centers for Environmental Information (NCEI)";
    String creator_type "Organisation";
    String creator_url "https://www.ncep.noaa.gov/";
    String data_doi "https://journals.ametsoc.org/view/journals/clim/34/8/JCLI-D-20-0166.1.xml";
    String data_update_frequence "Daily";
    String dataset_title "NOAA Daily Optimum Interpolation Sea Surface Temperature";
    Float64 Easternmost_Easting 359.875;
    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 359.875;
    Float64 geospatial_lon_min 0.125;
    Float64 geospatial_lon_resolution 0.25;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-11-21T11:00:52Z http://psl.noaa.gov/thredds/dodsC/Datasets/noaa.oisst.v2.highres/sst.mon.mean.nc
2024-11-21T11:00:52Z https://erddap.sochic-h2020.eu/erddap/griddap/NOAA_OISST_v2.das";
    String infoUrl "https://psl.noaa.gov/thredds/catalog/Datasets/noaa.oisst.v2.highres/catalog.html";
    String institution "National Oceanic and Atmospheric Administration (NOAA)";
    String institution_country "US";
    String institution_edmo_code "5759";
    String keywords "Earth Science > Oceans > Ocean Temperature > Sea Surface Temperature (Bd24A9A9-7D52-4C29-B2A0-6Cefd216Ae78), Sea Surface Temperature";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "CC-BY4.0";
    String naming_authority "SO-CHIC";
    Float64 Northernmost_Northing 89.875;
    String platform_id_orig "netCDF";
    String platform_type "drifting subsurface profiling float, drifting surface float, ship, satellite";
    String references "https://psl.noaa.gov/data/gridded/data.noaa.oisst.v2.highres.html";
    String source "satellite observations, in situ observations";
    String sourceUrl "http://psl.noaa.gov/thredds/dodsC/Datasets/noaa.oisst.v2.highres/sst.mon.mean.nc";
    Float64 Southernmost_Northing -89.875;
    String standard_name_vocabulary "CF Standard Name Table v85";
    String summary "The NOAA 1/4° Daily Optimum Interpolation Sea Surface Temperature (OISST) is a long term Climate Data Record that incorporates observations from different platforms (satellites, ships, buoys and Argo floats) into a regular global grid. The dataset is interpolated to fill gaps on the grid and create a spatially complete map of sea surface temperature. Satellite and ship observations are referenced to buoys to compensate for platform differences and sensor biases. OISST belongs to a family of products that are sometimes referred to as \"Reynolds SST\" for Richard W. Reynolds, a NOAA scientist who worked to improve the accuracy of the SST analyses by optimizing the advantages of in situ (ship and buoy) and satellite data. Older Reynolds SST products have been retired, except for the 1° weekly OISST. The dataset was developed using a methodology that includes bias adjustment of satellite and ship observations (referenced to buoys) to compensate for platform differences and sensor biases. This proved critical during the Mt. Pinatubo eruption in 1991, when the widespread presence of volcanic aerosols resulted in infrared satellite temperatures that were much cooler than actual ocean temperatures (Reynolds 1993).";
    String time_coverage_end "2024-10-01T00:00:00Z";
    String time_coverage_start "1981-09-01T00:00:00Z";
    String title "NOAA - Optimum Interpolation (OI) Sea Surface Temperature (SST) V2 High Resolution Dataset";
    String variables "time, latitude, longitude, sst";
    String version "Version 2.1";
    Float64 Westernmost_Easting 0.125;
  }
}

 

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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