The Met Office Hadley Centre's sea surface temperature data set, HadSST.4.0.1.0 is a monthly global field of SST on a 5° latitude by 5° longitude grid from 1850 to 2018. The data have been adjusted to minimise the effects of changes in instrumentation throughout the record. The data set is presented as a set of interchangeable realisations that capture the temporal and spatial characteristics of the estimated uncertainties in the biases. In addition there are files providing the measurement and sampling uncertainties which must be used in addition to the ensemble to obtain a comprehensive estimate of the uncertainty. The data are not interpolated.

This service is available to all ArcGIS Online users with organizational accounts. For more information on this service, including the terms of use, visit us online at http://goto.arcgisonline.com/earthobs2/REMSS_SeaSurfaceTempSea Surface Temperature is a key climate and weather measurement used for weather prediction, ocean forecasts, tropical cyclone forecasts, and in coastal applications such as fisheries, pollution monitoring and tourism. El Niño and La Niña are two examples of climate events which are forecast through the use of sea surface temperature maps. The Naval Oceanographic Office sea surface temperature dataset is calculated from satellite-based microwave and infrared imagery. These data are optimally interpolated to provide a daily, global map of the midday (12:00 pm) sea surface temperature. Learn more about the source data. Phenomenon Mapped: Sea Surface TemperatureUnits: Degrees CelsiusTime Interval: DailyTime Extent: 2008/04/01 12:00:00 UTC to presentCell Size: 11 kmSource Type: ContinuousPixel Type: Floating PointData Projection: GCS WGS84Mosaic Projection: Web Mercator Auxiliary SphereExtent: Global OceansSource: Naval Oceanographic OfficeUpdate Cycle: SporadicArcGIS Server URL: http://earthobs2.arcgis.com/arcgisTime: This is a time-enabled layer. It shows the average sea surface temperature during the map's time extent, or if time animation is disabled, a time range can be set using the layer's multidimensional settings. The map shows the average of all days in the time extent. Minimum temporal resolution is one day; maximum is one month.What can you do with this layer?Visualization: This layer can be used for visualization online in web maps and in ArcGIS Desktop.Analysis: This layer can be used as an input to geoprocessing tools and model builder. Units are in degrees Celsius, and there is a processing template to convert pixels to Fahrenheit. See this Esri blog post for more information on how to use this layer in your analysis. Do not use this layer for analysis while the Cartographic Renderer processing template is applied.This layer is part of the Living Atlas of the World that provides an easy way to explore the earth observation layers and many other beautiful and authoritative maps on hundreds of topics.

In 2023, the global ocean surface temperature was 0.91 degrees Celsius warmer than the 20th-century average. Oceans are responsible for absorbing over 90 percent of the Earth's excess heat from global warming. Departures from average conditions are called anomalies, and temperature anomalies result from recurring weather patterns or longer-term climate change. While the extent of these temperature anomalies fluctuates annually, an upward trend has been observed over the past several decades.

Effects of climate change

Since the 1980s, every region of the world has consistently recorded increases in average temperatures. These trends coincide with significant growth in the global carbon dioxide emissions, greenhouse gas, and a driver of climate change. As temperatures rise, notable decreases in the extent of arctic sea ice have been recorded.

Outlook

An increase in emissions from the use of fossil fuels is projected for the coming decades. Nevertheless, global investments in clean energy have increased dramatically since the early 2000s.

The dataset contains satellite-derived sea-surface temperature measurements collected by means of the Geostationary Orbiting Environmental Satellite. The data is collected daily, and is available at 2-day intervals at a spatial resolution of 0.05 degrees. The geographic coverage extends for the Pacific region,and the temporal coverage ranges from 2001-present.

The NOAA Ocean Surface Bundle (OSB) Climate Data Record (CDR) consist of three parts: sea surface temperature, near-surface atmospheric properties, and heat fluxes. This portion of the OSB CDR is the NOAA Climate Data Record (CDR) of Sea Surface Temperature - WHOI. The SST data are found through modeling the diurnal variability in combination with AVHRR observations of sea surface temperature. The data cover a time period from January 1988 to present at a 3-hourly, quarter-degree resolution.

The Sea Surface Temperature - WHOI dataset is part of the NOAA Ocean Surface Bundle (OSB) and provides a high quality Climate Data Record (CDR) of sea surface temperature over ice-free oceans. The SST values are found through modeling the diurnal variability in combination with AVHRR observations of sea surface …

This archive covers two high resolution sea surface temperature (SST) analysis products developed using an optimum interpolation (OI) technique. The analyses have a spatial grid resolution of 0.25 degree and temporal resolution of 1 day. One product uses Advanced Very High Resolution Radiometer (AVHRR) infrared satellite data, while the other uses satellite data from both AVHRR and the Advanced Microwave Scanning Radiometer from NASA Earth Observing System (AMSR-E). Both products also use sea-ice data, in situ data from ships and buoys, and include a large-scale adjustment of satellite biases with respect to the in situ data. Two products are needed because of the increase in signal variance from AMSR-E due to its near all-weather coverage. For both products, the results show improved spatial and temporal resolution compared to heritage weekly 1.0 degree OISST analyses from the NWS NCEP. The AVHRR-only product uses Pathfinder AVHRR data, when available, from September 1981 through December 2005, and operational Navy AVHRR data for 2006 onwards. Pathfinder AVHRR was chosen because of good agreement with the in situ data. The combined AMSR-E and AVHRR product begins with the start of AMSR data in June 2002 and ends in October 2011, when the AMSR-E instrument ceased to function properly. In this second product, the primary AVHRR contribution is in regions near land where AMSR-E is not available. However, in cloud-free regions, use of both infrared and microwave instruments reduces systematic biases because the error characteristics are independent. For both products, in areas where sea ice is present, SST is estimated from sea ice fraction datasets from NASA GSFC before 2005 and then from NWS NCEP from 2005 onwards. Preliminary products are produced daily in near real-time (1-day latency) and may be updated in the first few days if critical input data become available after the initial production time. After two weeks, a complete or final product is generated with no additional changes expected. The preliminary products from near real-time data productions began in October 2008 for Version 2.0.

Subskin Sea Surface Temperature derived from the imager SEVIRI on MSG satellites (Meteosat-8 and Meteosat-9). SST is retrieved from SEVIRI infrared channels (10.8 and 12.0 µm) using a nonlinear algorithm and the cloud mask from CM SAF. NWP outputs (temperature and humidity profiles), OSTIA Sea Surface Temperature re-analysis and analysis, together with a radiatiave transfer model (RTTOV), are used to correct the multispectral algorithm for regional and seasonal biases due to changing atmospheric conditions. The product is hourly and remapped onto a regular cylindrical equidistant latitude/longitude grid at 0.05° resolution and extends from 60°S to 60°N and 60°W to 60°E. The product format is compliant with the Data Specification (GDS) version 2 from the Group for High Resolution Sea Surface Temperatures (GHRSST).

Sea surface temperature (SST) plays an important role in a number of ecological processes and can vary over a wide range of time scales, from daily to decadal changes. SST influences primary production, species migration patterns, and coral health. If temperatures are anomalously warm for extended periods of time, drastic changes in the surrounding ecosystem can result, including harmful effects such as coral bleaching. This layer represents the maximum of the monthly mean climatology of SST (degrees Celsius) from 1985-2013. Three SST datasets were combined to provide continuous coverage from 1985-2013. The concatenation applies bias adjustment derived from linear regression to the overlap periods of datasets, with the final representation matching the 0.05-degree (~5-km) near real-time SST product. First, a weekly composite, gap-filled SST dataset from the NOAA Pathfinder v5.2 SST 1/24-degree (~4-km), daily dataset (a NOAA Climate Data Record) for each location was produced following Heron et al. (2010) for January 1985 to December 2012. Next, weekly composite SST data from the NOAA/NESDIS/STAR Blended SST 0.1-degree (~11-km), daily dataset was produced for February 2009 to October 2013. Finally, a weekly composite SST dataset from the NOAA/NESDIS/STAR Blended SST 0.05-degree (~5-km), daily dataset was produced for March 2012 to December 2013. An SST climatology was first calculated by taking the average of the 5-km weekly SST data for each month, and then averaging for all same-months (e.g., January) over the 1985-2013 time period.

From the parent record held in the GCMD:

The data sets in the CDC archive called "Reynolds SST' and "Reconstructed Reynolds SST" were discontinued on 1 April 2003.

A new OI SST data set is available as described here, which includes a new analysis for the historical data and updates into the future. NCEP will not provide new data for the "Reynolds SST" after December 2002 and CDC will remove the "Reynolds SST" data set on 1 April 2003.

TO SEE THE NEW DATASET, PLEASE SEARCH THE GLOBAL CHANGE MASTER DIRECTORY FOR MORE INFORMATION. REFER TO THE METADATA RECORD (LINKED BELOW): REYNOLDS_SST

This metadata record is a modified child record of an original parent record registered at the Global Change Master Directory. (The Entry ID of the parent record is REYNOLDS_SST, and can be found on the GCMD website - see the provided URL). The data described here are a subset of the original dataset. This metadata record has been created for the express use of Australian Government Antarctic Division employees.

Reproduced from: http://www.emc.ncep.noaa.gov/research/cmb/sst_analysis/

Analysis Description and Recent Reanalysis

The optimum interpolation (OI) sea surface temperature (SST) analysis is produced weekly 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 are 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.v2.

The most significant change for the OI.v2 is the improved simulation of SST obs 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.

The data are available in the following formats:

Net CDF Flat binary files Text

This dataset consists of sea surface temperature (SST) measurements collected from a range of instruments, at slightly different depths, at 62 stations during the 28th Atlantic Meridional Transect (AMT28/JR18001) research cruise (September and October 2018) on the RRS James Clark Ross (JCR). The data includes sea surface temperature (SST) measurements collected from a Smartfin (internal and external sensors) at approximately 0.1 m, and SST data at 1 m collected from TidbiT v2 and iButton sensors, which were calibrated to an NPL-traceable Hart Scientific 1504 temperature bridge and Themometrics ES 225 temperature probe. These sensors were mounted to a Simple Oceanographic floating Device (SOD) and deployed for approximately 20 minutes at each station. Additionally, the dataset includes SST skin measurements from an Infrared Sea surface temperature Autonomous Radiometer (ISAR) and SST data at 5 m collected from the ship's underway system using a Seabird SBE38 sensor. Auxiliary environmental data (air temperature, photosynthetically available radiation (PAR), and wind speed) collected from the ship's underway system and from a Gill Windmaster mounted on the foremast of the ship are included. Median and robust standard deviations (SDV) of all variables are provided over the duration of the SOD deployments at each station. The European Space Agency is acknowledged for their funding and contributions to the collection of the ISAR data on AMT28.

This dataset provides global daily sea surface temperature (SST) data from the Group for High Resolution Sea Surface Temperature (GHRSST) multi-product ensemble (GMPE) produced by the European Space Agency SST Climate Change Initiative (ESA SST CCI). The GMPE system was designed to allow users to compare the outputs from different SST analysis systems and understand their similarities and differences. Although originally intended for comparison of near real time data, it has also been used to compare long historical datasets. Note that the dataset provided here is the climate version of the GMPE dataset. An operational version, with different input products and time coverage, also exists but is not distributed by the CDS. The SST analyses ingested into the GMPE system come from the following seven SST products and providers:

ESA SST CCI Analysis version 2.0 ESA SST CCI Analysis version 1.1 Copernicus Marine Environment Monitoring Service (CMEMS) Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) Reprocessing National Centers for Environmental Information (NCEI) Advanced Very High Resolution Radiometer (AVHRR) Optimal Interpolation (OI) Global Blended SST Analysis Canada Meteorological Center (CMC) 0.2-degree Global Foundation SST Analysis Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) Analysis version 2.2.0.0 Japan Meteorological Agency (JMA) Merged satellite and in-situ Data Global Daily SST (MGDSST) Analysis

These products are all spatially complete (through use of infilling or reconstruction techniques) but were originally produced for different purposes and with different user requirements in mind. Therefore, each producer has made different choices on aspects of data production such as which input observations to use and what type of SST to represent. For example, the CMEMS OSTIA, CMC, and MGDSST analyses attempt to represent the foundation SST (water temperature free of diurnal temperature variability) while the ESA SST CCI and HadISST analyses estimate the SST at a standard depth of 20 cm. The AVHRR OI product, on the other hand, is bias-corrected to in situ observations and hence will be representative of their depths. The GMPE dataset provides the median and standard deviation of the input SST products, the differences between each input product and the median, and the horizontal gradients in each of the input SST products as well as the final ensemble product. The HadISST product consists of 10 different realisations, therefore the median and standard deviation are calculated for an ensemble of 16 input fields. All fields are provided on a common 0.25 degree regular latitude-longitude grid and extend from 1 September 1981 to 31 December 2016, although some of the individual input products cover shorter periods. The dataset will not be extended beyond 2016.

Variables in the dataset/application are: Analysed SST, Gradient fields, SST anomaly, SST standard deviation

This ArcGIS image service contains a set of monthly global day-night sea surface temperature averages, derived from the AVHRR Pathfinder Version 5 sea surface temperature cloud screened data set (https://www.ncei.noaa.gov/products/avhrr-pathfinder-sst).This image service layer can be viewed using a map with a time slider.The AVHRR Pathfinder SST data sets provide the longest, most accurate, and highest resolution consistently-reprocessed SST climate data record from the AVHRR sensor series. These data files were produced to facilitate the utilization of high resolution Pathfinder v5.0 sea surface temperature data within geographic information system (GIS) software. These day-night combined monthly and yearly means were produced from cloud-screened day-night monthly full resolution files of Pathfinder SST data from 1985-2009. The data are available for download at https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.nodc:0077816. The original .HDF files are archived at the National Centers for Environmental Information under separate accession numbers. The GeoTIFF SST averages were assigned projection GCS_WGS_1984. In addition, browse images in PNG format with an associated KML file for each year are included with these data as well as detailed metadata.This is a time-enabled image service. Each image's date is stored in the "Date" field, with a format of YYYYMM.Sea surface temperatures are represented using this color scale:

We used NIWA’s sea-surface temperature archive, which is derived from the Advanced Very High Resolution Radiometer (AVHRR) satellite data it receives from the US National Oceanic and Atmospheric Administration. The archive provides high spatial (approximately 1km) and high temporal (approximately six-hourly in cloud-free locations) resolution estimates of sea-surface temperatures over the New Zealand region, dating from January 1993. Uddstrom & Oien (1999) and Uddstrom (2003) describe the methods used to derive and validate the data. Our data extends from about 30°S to 55°S, and from 160°E to 170°W and is grouped into five areas: the exclusive economic zone (EEZ), the Chatham Rise, northern subtropical waters, subantarctic waters, and the Tasman Sea. More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

JPL OurOcean Portal: A daily, global Sea Surface Temperature (SST) data set is produced at 1-km (also known as ultra-high resolution) by the JPL ROMS (Regional Ocean Modeling System) group.

The Sea Surface Temperature dataset in CMAP is the GHRSST Level 4 AVHRR_OI Global Blended Sea Surface Temperature Analysis (GDS version 2) from NCEI. This data product has a 1/4° X 1/4° degree gridded spatial resolution with global ocean coverage at a 1 day temporal interval. The dataset is derived from a combination of multiple AVHRR (Advanced Very High Resolution Radiometer) satellites along with in-situ sst measurements from ship and buoy measurements. These data sources are optimally interpolated to produce a complete smoothed grid.

This description has been reproduced using the following source:

https://doi.org/10.5067/GHAAO-4BC21

The ocean waters surrounding New Zealand vary in temperature from north to south. They interact with heat and moisture in the atmosphere and affect our weather. Sea surface temperature changes with climate drivers such as El Niño, and will change with climate change. The sea surface temperature anomaly provides an indication of the heat change in the ocean. Long-term changes and short-term variability in sea-surface temperatures can affect marine processes, habitats, and species. some species may find it hard to survive in changing environmental conditions. The oceanic sea surface temperature data comes from the NIWA Sea surface temperature Archive (NSA). There are 2 datasets, of NSA Annual means and NSA Annual Anomolies, covering the Tasman, subtropical (STW) and Southern Antarctic (SAW) area and the total area. The data is available from 1993 to 2013 and the unit of measure is degrees celcius. For further information please see: Uddstrom, MJ (2015) Sea Surface Temperature Data and Analysis for the 2015 Synthesis Report. For Ministry for the Environment. Available at https://data.mfe.govt.nz/x/hRbGUJ on the Ministry for the Environment dataservice (https://data.mfe.govt.nz). This dataset relates to the "Sea surface temperature" measure on the Environmental Indicators, Te taiao Aotearoa website.

The AATSR Reprocessing for Climate (ARC) dataset consists of Advanced Along-Track Scanning Radiometer (AATSR) multimission data which has been reprocessed using various algorithms and in-situ contemporaneous measurements, to provide update retrievals of Sea Surface Temperature (SST) and assess their accuracy. This dataset contains version 1.1 of the Level 3 sea surface temperature data product produced by the ARC project team. The main ARC objective was to reduce regional biases in retrieved sea surface temperature (SST) to less than 0.1 K for all global oceans while creating a very homogeneous record with a stability (lack of drift in the observing system and analysis) of 0.05 K decade.

The dataset measures the long-term seasonal means of the sea surface temperature (SST) of ocean surface waters. They are derived from MODIS (aqua) images using NASA's SeaDAS image processing software. The monthly SST images between July 2002 and December 2017 are used to calculate the means of the four austral seasons: winter (June, July, and August), spring (September, October and November), summer (December, January and February) and autumn (March, April and May). The extent of the dataset covers the entire Australian EEZ and surrounding waters (including the southern ocean). The unit of the dataset is Celsius degree.

This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.