This is the preliminary, near real time version of the related dataset "ncdcOisst21Agg", which has the final version of these files, which are released about 2 weeks after these NRT files. NOAA/National Centers for Environmental Information (NCEI) 1/4 Degree Daily Optimum Interpolation Sea Surface Temperature (OISST) Analysis, Version 2.1 - Inter. NOAAs 1/4-degree Daily Optimum Interpolation Sea Surface Temperature (OISST) (sometimes referred to as Reynolds SST, which however also refers to earlier products at different resolution), currently available as version v02r01, is created by interpolating and extrapolating SST observations from different sources, resulting in a smoothed complete field. The sources of data are satellite (Advanced Very High Resolution Radiometer (AVHRR)) and in situ platforms (i.e., ships and buoys), and the specific datasets employed may change over time. At the marginal ice zone, sea ice concentrations are used to generate proxy SSTs. A preliminary version of this file is produced in near-real time (1-day latency), and then replaced with a final version after 2 weeks. Note that this is the AVHRR-ONLY DOISST, available from Oct 1981, but there is a companion DOISST product that includes microwave satellite data, available from June 2002

The NOAA 1/4 degree daily Optimum Interpolation Sea Surface Temperature (OISST) provides complete ocean temperature fields constructed by combining bias-adjusted observations from different platforms (satellite, ships, buoys) on a regular global grid, with gaps filled in by interpolation. Satellite data from the Advanced Very High Resolution Radiometer (AVHRR) provides the …

A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced as a retrospective dataset (four day latency) and near-real-time dataset (one day latency) at the JPL Physical Oceanography DAAC using wavelets as basis functions in an optimal interpolation approach on a global 0.01 degree grid. The version 4 Multiscale Ultrahigh Resolution (MUR) L4 analysis is based upon nighttime GHRSST L2P skin and subskin SST observations from several instruments including the NASA Advanced Microwave Scanning Radiometer-EOS (AMSR-E), the JAXA Advanced Microwave Scanning Radiometer 2 on GCOM-W1, the Moderate Resolution Imaging Spectroradiometers (MODIS) on the NASA Aqua and Terra platforms, the US Navy microwave WindSat radiometer, the Advanced Very High Resolution Radiometer (AVHRR) on several NOAA satellites, and in situ SST observations from the NOAA iQuam project. The ice concentration data are from the archives at the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) High Latitude Processing Center and are also used for an improved SST parameterization for the high-latitudes. The dataset also contains additional variables for some granules including a SST anomaly derived from a MUR climatology and the temporal distance to the nearest IR measurement for each pixel.This dataset is funded by the NASA MEaSUREs program ( http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects ), and created by a team led by Dr. Toshio M. Chin from JPL. It adheres to the GHRSST Data Processing Specification (GDS) version 2 format specifications. Use the file global metadata "history:" attribute to determine if a granule is near-realtime or retrospective.

The Regional Ocean Forecast System (ROFS) has been developed jointly by the Ocean Modeling Branch of the National Weather Service's Environmental Modeling Center, the National Ocean Service's Coast Survey Development Lab, Princeton University, and Naval Oceanographic Office (NAVOCEANO). ROFS is based on a hydrodynamic, three-dimensional ocean circulation model (Princeton Ocean Model) which simulates temperature, salinity, surface elevation, and currents for a region off the U.S. East Coast from ~30 to 47N and out to 50W. The model is driven at the ocean surface boundary by heat, moisture, and momentum fluxes provided by NCEP's Eta mesoscale atmospheric forecast model. The ocean model is driven along its open (that is, southern and eastern) boundaries by climatological estimates of temperature, salinity, and transport. The spatial resolution of the model varies from approximately 20km offshore to about 10km nearshore. The coastal boundary corresponds to the location of the 10m isobath. In the vertical, an 18-layer sigma (terrain-following) coordinate system is used with at least half the layers concentrated in the upper 100m. Tidal forcing is included in the model.

At 24-hour intervals, Gulf Stream north-wall-location data and satellite altimeter data are assimilated with an OI-based algorithm from Princeton University. Gulf Stream location data are provided by NAVOCEANO and sea surface height anomalies (SSHAs) derived from satellite altimeter data are provided by the NOAA Laboratory for Satellite Altimetry. These data are input for correction of the model's sea surface height field and assimilation into the subsurface temperature and salinity fields using correlation functions statistically derived from the model itself. Gulf Stream location data for the current day and TOPEX data from the prior 10-day orbital cycle, are used in this analysis step, which provides the input fields for the second analysis step.

Sea surface temperature (SST) data from in-situ and satellite observing platforms are assimilated into the updated fields from the first data assimilation step, in a nowcast/data assimilation cycle producing initial conditions for the 48-h forecast. In-situ observations are from fixed and drifting buoys, C-MAN stations, and ships. Remotely sensed observations are MCSST retrievals from the AVHRR sensor onboard the NOAA polar orbiting satellites. Surface atmospheric forcing is obtained from 3-hourly analyses of the NCEP's Eta Data Assimilation System (EDAS).

The forecast cycle generates regional ocean forecasts out to 48 hours. Surface forcing is obtained from the 3-hourly surface fields from NCEP's Eta mesoscale atmospheric prediction model. [This abstract was obtained from the ROFS website at http://polar.wwb.noaa.gov/cofs/Description.html#OM on June 23, 2004.]

Accurate estimates of ocean circulation are essential for hindcasting and predicting the transport of the pollutants, assessing their environmental impacts, and managing response efforts. A standard method for improving ocean simulations and predictions is data assimilation, which combines observations and dynamical models to obtain more accurate estimates. This dataset represents such a combined estimate and was generated from a data-assimilative circulation model (horizontal resolution ~5 km) of the Gulf of Mexico (GOM). The circulation model is a configuration of the Regional Ocean Modelling System (ROMS, http://myroms.org) for the entire GOM, initialized on 1 April 2010 and run until 1 October 2010. Satellite and float data were assimilated using a localized Ensemble Kalman Filter (EnKF). Observations assimilated into the model include Sea Level Anomaly (SLA) from AVISO (Archiving Validation and Interpretation of Satellite Oceanographic Data, http://www.aviso.oceanobs.com/), 1/4° SST from the AVHRR (Advanced Very High-Resolution Radiometer, http://marine.copernicus.eu/), and temperature and salinity profiles from Shay et al., 2011. Daily ensemble means model outputs of sea surface height (SSH), temperature, salinity and velocity fields during April to September 2010 are generated and archived in this dataset. This dataset consists of four NetCDF files containing the model physical daily assembles, a model grid file, and the model's 7-years mean SSH (considered as the model’s mean dynamic topography) that was added to the satellite Sea Level Anomaly for assimilation and comparison. This dataset supports the publication (submitted to Journal of Geophysical Research: Oceans). Yu, L., Fennel, K., Wang, B., Laurent, A., Thompson, K. and Shay, L. EnKF-based data assimilation improves simulated circulation in the Gulf of Mexico but does it benefit the simulation of deep-water oil plumes?

The EUMETSAT OSI-SAF NAR SST products are SST fields derived from NOAA/AVHRR data and available over 6 pre-defined zones, 4 times per day. After acquisition and calibration at CMS, the NOAA/AVHRR data are re-mapped onto a stereopolar grid to produce mosaics of consecutive orbits over Europe and the Near Atlantic at a 2 km resolution. Mosaics are made over a "Rectification Grand Domaine" area (RGD). For re-mapped grid points observed by more than one overpass, the smallest satellite zenith angle data are selected. In the normal conditions when two satellites are operational, four mosaics per day are produced for all the AVHRR channels. SSTs are then calculated from these data. Six zones are then extracted . They are 1024 * 1024 pixels in size to offer the users (presumably interested by local phenomena) the possibility of handling a restricted volume of data. Note that SSTs are calculated over the entire RGD, but only the predefined zones are delivered as NAR products.The operational CMS AVHRR cloud mask in use is based on a multi-spectral thresholding algorithm (Derrien and Le Gleau 1999). Some refinements specific to the marine conditions have been introduced including Use of fine scale climatology and a fine gradiant climatology to assist in the detection of clouds in areas characterised by strong thermal gradients. SSTs are derived from the 11 and 12 micron brightness temperatures (T11 and T12) . The NOAA /AVHRR has three IR channels : channel 3 (3.6-3.8 micron), channel 4 (10.2-11.2 micron) and channel 5 (11.5-12.5 micron) which provide IR data at 1-km spatial resolution at the satellite subpoint (Kidwell, 1997). NOAA-14 and NOAA-16 have similar characteristics, but with distinct radiometer filter functions that necessitate distinct algorithm coefficients. The algorithms coefficients are derived from multilinear regression on a simulation database . At night the use of the 3.7 channel in a triple window algorithm improves the SST retrieval performances under high water vapor content conditions. The expected accuracy is defined as the expected bias and standard deviation of the primary calculations against drifting buoy measurements determined on a monthly or yearly basis. The following performance evaluation was derived from a detailed validation of NOAA/AVHRR derived SSTs (Brisson et al 2001). Bias: Apart for the first 2 months after the launch of a new satellite, the monthly biases should remain within +/-0.4 K by night. By day local biases of several K are possible because of shallow diurnal heating. Standard deviation: see table below: low-cloud cases (cloud coverage less than 10% of the validation box) have been separated from all cases (cloud coverage less than 60%). The "expected maximum standard deviation" or the expected maximum biases are the maximum values that can be observed under normal conditions. When these values are overpassed, some anomaly may have occurred and the problem must be identified. Standard deviation Table Yearly, all Monthly, all Yearly, low-cloud Monthly, lowcloud 0.7 0.8 0.6 0.7 Physical definition subskin SST : Comparable to in situ (buoy) measurements at night. Relation to bulk SST: equivalent to bulk SST by night. By day, a bias of several Kelvin may be found under favorable diurnal heating conditions, Relation to skin SST: By day and by night the subskin SST is convertible to skin temperature by subtracting 0.2K. Units and range Units: Centi-Kelvins When using GRIB format, a scaling factor of 100 must be applied. No lower limit is imposed on the SST calculations, providing the sea is ice free. The expected range is thus from about -3 degC till 35 degC, corresponding to actual values of 27000 to 30800. Unprocessed data (for whatever reason) show a negative value (-32768) in HDF format, or is flagged as missing in GRIB section3. Origin SST calculated from the IR channel data of the NOAA/AVHRR re-mapped onto a stereopolar grid at 2 km resolution. SST are extracted over 6 pre-

The Regional Ocean Forecast System (ROFS) has been developed jointly by the Ocean Modeling Branch of the National Weather Service's Environmental Modeling Center, the National Ocean Service's Coast Survey Development Lab, Princeton University, and Naval Oceanographic Office (NAVOCEANO). ROFS is based on a hydrodynamic, three-dimensional ocean circulation model (Princeton Ocean Model) which simulates temperature, salinity, surface elevation, and currents for a region off the U.S. East Coast from ~30 to 47N and out to 50W. The model is driven at the ocean surface boundary by heat, moisture, and momentum fluxes provided by NCEP's Eta mesoscale atmospheric forecast model. The ocean model is driven along its open (that is, southern and eastern) boundaries by climatological estimates of temperature, salinity, and transport. The spatial resolution of the model varies from approximately 20km offshore to about 10km nearshore. The coastal boundary corresponds to the location of the 10m isobath. In the vertical, an 18-layer sigma (terrain-following) coordinate system is used with at least half the layers concentrated in the upper 100m. Tidal forcing is included in the model.

At 24-hour intervals, Gulf Stream north-wall-location data and satellite altimeter data are assimilated with an OI-based algorithm from Princeton University. Gulf Stream location data are provided by NAVOCEANO and sea surface height anomalies (SSHAs) derived from satellite altimeter data are provided by the NOAA Laboratory for Satellite Altimetry. These data are input for correction of the model's sea surface height field and assimilation into the subsurface temperature and salinity fields using correlation functions statistically derived from the model itself. Gulf Stream location data for the current day and TOPEX data from the prior 10-day orbital cycle, are used in this analysis step, which provides the input fields for the second analysis step.

Sea surface temperature (SST) data from in-situ and satellite observing platforms are assimilated into the updated fields from the first data assimilation step, in a nowcast/data assimilation cycle producing initial conditions for the 48-h forecast. In-situ observations are from fixed and drifting buoys, C-MAN stations, and ships. Remotely sensed observations are MCSST retrievals from the AVHRR sensor onboard the NOAA polar orbiting satellites. Surface atmospheric forcing is obtained from 3-hourly analyses of the NCEP's Eta Data Assimilation System (EDAS).

The forecast cycle generates regional ocean forecasts out to 48 hours. Surface forcing is obtained from the 3-hourly surface fields from NCEP's Eta mesoscale atmospheric prediction model. [This abstract was obtained from the ROFS website at http://polar.wwb.noaa.gov/cofs/Description.html#OM on June 23, 2004.]