The latest version of the Met Office Hadley Centre's sea surface temperature dataset, HadSST.4.2.0.0 is a monthly global field of SST on a 5° latitude by 5° longitude grid from 1850 to the present day. The data have been adjusted to minimise the effects of changes in instrumentation throughout the record. The dataset 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.

The NOAA Global Surface Temperature Dataset (NOAAGlobalTemp) is a monthly global merged land-ocean surface temperature analysis product that is derived from two independent analyses. The first is the Extended Reconstructed Sea Surface Temperature (ERSST) analysis and the second is a land surface air temperature (LSAT) analysis that uses the Global Historical Climatology Network - Monthly (GHCN-M) temperature database. The NOAAGlobalTemp data set contains global surface temperatures in gridded (5° × 5°) and monthly resolution time series (from 1850 to present time) data files. The product is used in climate monitoring assessments of near-surface temperatures on a global scale. This version, v6.0, an updated version to the current operational release v5.1, is implemented by an Artificial Neural Network method to improve the surface temperature reconstruction over the land.

The NOAA Extended Reconstructed Sea Surface Temperature (ERSST) dataset is a global monthly sea surface temperature dataset derived from the International Comprehensive Ocean-Atmosphere Dataset (ICOADS). It is produced on a 2 x 2 degree grid with spatial completeness enhanced using statistical methods. This monthly analysis begins in January 1854 continuing to the present and includes anomalies computed with respect to a 1971-2000 monthly climatology. Version 5 (v5) is the newest version of ERSST. Major revisions for v5 include: 1) using unadjusted first-guess instead of adjusted first-guess in QC, 2) using latest International Comprehensive Ocean Atmosphere Data Set (ICOADS) Release 3.0 (R3.0) over 1854-2015 instead of R2.5 over 1854-2007, 3) using Argo temperature above 5 meter depth that has not been used in previous version ERSST and other SST analysis, 4) using latest UK Met Office HadISST2 ice concentration over 1870-2015 instead of HadISST1 ice concentration over 1870-2010, 5) removing damping in high latitudes north of 60 degrees North and south of 50 degrees South in Empirical Orthogonal Teleconnection (EOT) Functions, 6) adding 10 more EOT modes in the Arctic, 7) reducing spatial filtering in training EOTs, and 8) revising ship SST bias correction relative to nighttime marine air temperature (NMAT) to the one relative to buoy SST observations. Other features remain same as in the previous ERSST version 4. The data are written to monthly netCDF files following CF Metadata Conventions.

The Met Office Hadley Centre's sea ice and sea surface temperature (SST) data set, HadISST1 is a unique combination of monthly globally-complete fields of SST and sea ice concentration on a 1 degree latitude-longitude grid from 1870 to date.

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 standard deviation of SST (degrees Celsius) of the weekly time series from 2000-2013. 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. The standard deviation of the long-term mean SST was calculated by taking the standard deviation over all weekly data from 2000-2013 for each pixel.

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.

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 input SST data sets are derived from the Global High-Resolution Sea Surface Temperature (SST) Pilot Project (GHRSST-PP). For details, see https://podaac.jpl.nasa.gov/dataset/JPL_OUROCEAN-L4UHfnd-GLOB-G1SST . This dataset is part of the Multi-sensor Improved Sea Surface Temperatures (MISST) project, which is part of the Group for High-Resolution Sea Surface Temperature (GHRSST) project. DISCONTINUED - The creators of the jplG1SST dataset stopped production in late Oct 2017. There are more recent files available from JPL, but they are flawed so they are not included in the dataset at ERD. You might consider using the similar jplMURSST41 dataset, https://coastwatch.pfeg.noaa.gov/erddap/search/index.html?searchFor=jplMURSST41 which has the additional advantage of offering related climatology and anomaly datasets.

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.

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 (PO.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.

This dataset contains daily-averaged ocean potential temperature and salinity interpolated to a regular 0.5-degree grid from the ECCO Version 4 revision 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g.,research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.

The Smith & Reynolds Extended Reconstructed Sea Surface Temperature (ERSST) Level 4 dataset provides a historical reconstruction of monthly global ocean surface temperatures and temperature anomalies over a 2 degree spatial grid since 1854 from in-situ observations based on a consistent statistical methodology that accounts for uneven sampling distributions over time and related observational biases. Version 4 of this dataset implements release 2.5 of ICOADS (International Comprehensive Ocean-Atmosphere Data Set) and is supplemented by monthly GTS (Global Telecommunications Ship and buoy) system data. As for the prior ERSST version, v4 implements Empirical Orthogonal Teleconnection analysis (EOT) but with an improved tuning method for sparsely sampled regions and periods. ERSST anomalies are computed with respect to a 1971-2000 monthly climatology. The version 4 has been improved from previous version 3b. Major revisions include updated and substantially more complete input data from the ICOADS release 2.5, revised EOTs and EOT acceptance criterion, updated SST quality control procedures, revised SST anomaly evaluation methods, updated bias adjustments of ship SSTs using the Hadley Centre Nighttime Marine Air Temperature dataset version 2 (HadNMAT2), and buoy SST bias adjustment not previously made in v3b. The ERSST v4 in netCDF format contains extended reconstructed sea surface temperature, SST anomaly, and associated estimated SST error standard deviation fields, incompliance with CF1.6 standard metadata.

This map features daily sea surface temperature from 2008 to present in degrees Celsius (⁰C) at 25 km resolution. Sea 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.

This dataset provides global sea surface temperatures (SST) from Sea and Land Surface Temperature Radiometers (SLSTR), presented on the native geometry of observation, and spanning 2016 to 2021.

The SST CCI SLSTR product contains two different SST estimates. The first is the skin temperature of the water at the time it was observed. The second is an estimate of the temperature at 20 cm depth at either 1030h or 2230h local time, which closely approximates the daily mean SST. Each SST value has an associated total uncertainty estimate, and uncertainty estimates for various contributions to that total.

The dataset has been produced as part of the version 3 Climate Data Record (CDR) produced by the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project (ESA SST_cci). The CDR accurately maps the surface temperature of the global oceans over the period 1980 to 2021 using observations from many satellites, with a high degree of independence from in situ measurements. The data provide independently quantified SSTs to a quality suitable for climate research.

Data are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/

When citing this dataset please also cite the associated data paper:

Embury, O., Merchant, C.J., Good, S.A., Rayner, N.A., Høyer, J.L., Atkinson, C., Block, T., Alerskans, E., Pearson, K.J., Worsfold, M., McCarroll, N., Donlon, C. Satellite-based time-series of sea-surface temperature since 1980 for climate applications. Scientific Data 11, 326 (2024). https://doi.org/10.1038/s41597-024-03147-w

The surface temperature of the world's oceans reached new record levels in the first months of 2024, continuing the trend started in April 2023. As of August 6, 2024, the global sea surface temperature reached 20.98 degrees Celsius, an increase of 0.76 degrees compared to the 1982-2010 average. Overall, 2024 was a year of record temperatures on land and in the sea, with a temperature anomaly of 1.29 degrees with respect to the 20th century average. As of September 2025, temperatures this year remain lower than 2024 temperatures.

This dataset contains monthly 1 degree averages of sea surface temperature data in Obs4MIPS format, from the European Space Agency (ESA)'s Climate Change Initiatve (CCI) Sea Surface Temperature (SST) v2.1 analysis.

The data covers the period from 1981-2017, with the data from 1981 to 2016 coming from the Sea Surface Temperature (SST) project of the ESA CCI project. The data for 2017 were generated using the same approach but under funding from the Copernicus Climate Change Service (C3S).

This particular product has been generated for inclusion in Obs4MIPs (Observations for Model Intercomparisons Project), which is an activity to make observational products more accessible for climate model intercomparisons.

Data are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/

When citing this dataset please also cite the associated data paper: Merchant, C.J., Embury, O., Bulgin, C.E., Block T., Corlett, G.K., Fiedler, E., Good, S.A., Mittaz, J., Rayner, N.A., Berry, D., Eastwood, S., Taylor, M., Tsushima, Y., Waterfall, A., Wilson, R., Donlon, C. Satellite-based time-series of sea-surface temperature since 1981 for climate applications, Scientific Data 6:223 (2019). http://doi.org/10.1038/s41597-019-0236-x

The COBE-SST is a gridded 1x1 resolution SST monitoring dataset. It is used as input for the JMA Climate Data Assimilation System (JCDAS) and the Japanese 25-year Re-analyses (JRA-25 and JRA-55). It is also used as input for the ensemble prediction systems used in seasonal forecasts. It starts in 1891 and extends to near present.

Retirement Notice: This item is in mature support as of April 2024 and will be retired in December 2026. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.Sea 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: Daily Time 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 OfficeArcGIS Server URL: https://earthobs2.arcgis.com/arcgis Time: 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. Do not use this layer for analysis while the Cartographic Renderer processing template is applied.

A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced daily on an operational basis at the UK Met Office using optimal interpolation (OI) on a global 0.054 degree grid. The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) analysis uses satellite data from sensors that include the Advanced Very High Resolution Radiometer (AVHRR), the Advanced Along Track Scanning Radiometer (AATSR), the Spinning Enhanced Visible and Infrared Imager (SEVIRI), the Advanced Microwave Scanning Radiometer-EOS (AMSRE), the Tropical Rainfall Measuring Mission Microwave Imager (TMI), and in situ data from drifting and moored buoys. This analysis has a highly smoothed SST field and was specifically produced to support SST data assimilation into Numerical Weather Prediction (NWP) models.

The NOAA/ NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the NOAA -7, -9, -11, -14, -16 and -17 polar orbiting satellites. Daily, 8-day and monthly averaged data for both the ascending pass (daytime) and descending pass (nighttime) are available on equal-angle grids of 8192 pixels/360 degrees (nominally referred to as the 4km resolution, 4096 pixels/360 degrees (nominally referred to as the 9km resolution), 2048 pixels/360 degrees (nominally referred to as the 18km resolution), and 720 pixels/360 degrees (nominally referred to as the 54km resolution or 0.5 degree resolution).The monthly averaged daytime data was converted to an ESRI GRID format and the 12 monthly grid files were combined into one annual grid with a attribute field for each month.