NOAA NCEP Optimum Interpolation Sea Surface Temperature Analysis
d277000
The NOAA National Center for Environmental Prediction (NCEP) optimum interpolation (OI) sea surface temperature (SST) analysis is produced weekly and monthly on a one-degree grid. The analysis uses in situ and satellite SSTs plus SSTs simulated by sea ice cover. Before the analysis is computed, the satellite data is adjusted for biases using the method of Reynolds (1988) and Reynolds and Marsico (1993). A description of the OI analysis can be found in Reynolds and Smith (1994). The bias correction improves the large scale accuracy of the OI. In November 2001, the OI fields were recomputed for late 1981 onward. The new version will be referred to as OI Version 2, and the most significant change is the improved simulation of SST from sea ice data following a technique developed at the UK Met Office. This change has reduced biases in the OI SST at higher latitudes. Also, the update and extension of COADS has provided us with improved ship data coverage through 1997, reducing the residual satellite biases in otherwise data sparse regions. For more details, see Reynolds, et al. (2002).
dataset
https://rda.ucar.edu/datasets/d277000/
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https://rda.ucar.edu/datasets/d277000/dataaccess/
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oceans
dataset
revision
2014-10-16
GRIDDING METHODS
revision
2024-12-17
EARTH SCIENCE > OCEANS > SEA ICE > SEA ICE CONCENTRATION
EARTH SCIENCE > OCEANS > OCEAN TEMPERATURE > SEA SURFACE TEMPERATURE
revision
2024-12-17
-180
180
90
-90
1981-10-29T00:00:00Z
2023-02-01T00:00:00Z
publication
1986-03-04
weekly
Creative Commons Attribution 4.0 International License
None
UCAR/NCAR - Research Data Archive
National Center for Atmospheric Research
CISL/DECS
P.O. Box 3000
Boulder
80307
U.S.A.
720-937-8442
303-497-1291
pointOfContact
NCAR Research Data Archive
National Center for Atmospheric Research
CISL/DECS
P.O. Box 3000
Boulder
80307
U.S.A.
303-497-1291
name: NCAR Research Data Archive
description: The Research Data Archive (RDA), managed by the Data Engineering and Curation Section (DECS) of the Computational and Information Systems Laboratory (CISL) at NCAR, contains a large and diverse collection of meteorological and oceanographic observations, operational and reanalysis model outputs, and remote sensing datasets to support atmospheric and geosciences research, along with ancillary datasets, such as topography/bathymetry, vegetation, and land use.
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2024-12-31T16:05:01Z