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External Data Spec

HadSST.4.0.1.0

External Data Spec Published 05 Nov 2019
1 min read
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 date. 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. The data set initially runs from 1850 to presnet with regular monthly updates.
information.png Provider:
Met Office Hadley Centre observations datasets
information.png Dataset URL:
https://www.metoffice.gov.uk/hadobs/hadsst4/data/download.html
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Brief description of the data

The SST data are taken from release 3.0.0 of the International Comprehensive Ocean-Atmosphere Data Set, ICOADS (external web page), from 1850 to 2014 and from ICOADS release 3.0.1 from 2015 onwards. From January 2016, these are supplemented by drifting buoy observations "Generated using E.U. Copernicus Marine Service Information" from CMEMS (Copernicus Marine Environment Monitoring Service). HadSST.4.0.1.0 is produced by taking in situ measurements of SST from ships and buoys, rejecting measurements that fail quality checks, converting the measurements to anomalies by subtracting climatological values from the measurements, and calculating a robust average of the resulting anomalies on a 5° by 5° degree monthly grid. After gridding the anomalies, bias adjustments are applied to reduce the effects of changes in SST measuring practices. The uncertainties arising from under-sampling and measurement error have been calculated for the gridded monthly data as have the uncertainties on the bias adjustments following the procedures described in the paper.

 

Previous description for version HadSST.4.0.0.0:

HadSST.4.0.0.0 is the Met Office Hadley Centre Sea-surface temperature anomaly data set. Anomalies are expressed relative to the 1961-1990 average. The data have been adjusted to minimize the effect of systematic errors associated with instrumentation changes and are representative of SST measured at a depth of 20 cm. The data set is presented on an equirectangular 5°latitude by 5° longitude monthly grid from January 1850 to December 2018.

Uncertainty in the data is presented using a combined approach. Uncertainty in the bias adjustments is presented as an ensemble of interchangeable realisations. Uncertainty arising from local measurement errors and local sampling errors are presented as gridded fields. Uncertainties associated with correlated measurement errors are presented as error-covariance matrices. These can be combined to give uncertainty estimates for derived quantities such as the global mean temperature. HadSST.4.0.0.0 is based on ICOADS release 3.0.0 (1850-2014, [2]) and ICOADS release 3.0.1 (2015-present). In addition it uses drifting buoy observations from CMEMS.

Related content

Produced figures

Figure Temporal development of the number of species of each biogeographical affinity group (top) and of the ratio between Lusitanian and Boreal species with sea surface temperature by marine region (bottom) The charts show: - Top figures: the temporal development in the number of species of each biogeographical affinity group (Atlantic, Boreal, Lusitania and Unknown) by marine region (Greater North Sea, Baltic Sea, Celtic Seas and Bay of Biscay and the Iberian Coast). - Bottom figures: the temporal development of the ratio between Lusitanian and Boreal species and sea surface temperature by marine region to investigate correlations.
Figure Decadal average sea surface temperature anomaly in different European seas (1870 to 2020) Time series of sea surface temperature anomalies (°C), referenced to the average temperature between 1981 and 2010, in each of the European seas and in the Global Ocean. Data sources: SST datasets from the Met Office (HadISST1, HadSST.4.0.0.0 and OSTIA), the US National Ocean and Atmosphere Administration (ERSSTv5), ESA SST CCI analysis version 2.1.
Figure
Archived
Decadal average sea surface temperature anomaly in different European seas (1870 to 2018) The figure shows global and regionally averaged sea surface temperatures anomalies relative to a 1981-2010 baseline. The solid lines show satellite-based series, combining SST CCI (Sea Surface Temperature Climate Change Initiative) Analysis data (to 2016) with the OSTIA (Operational Sea Surface Temperature and Sea Ice Analysis) near real-time updated data (to 2018). The shaded area in each plot indicates the upper and lower uncertainty range of the long-term evolution of the regional averages based on three global data sets (HadSST.4.0.0.0, ERSSTv5 and HadISST).
Figure
Archived
Decadal average sea surface temperature anomaly in different European seas The figure shows decadal global and regionally averaged sea-surface temperature anomalies relative to a 1981-2010 baseline. The solid line shows a satellite-based series combining the SST CCI analysis (to 2016) with the OSTIA near-real time updates (to 2018). The shaded area in each plot indicates the upper and lower uncertainty range of the long-term evolution of the regional averages based on three global data sets (HadSST.4.0.0.0, ERSSTv5 and HadISST).

Used in indicators

Indicator Specification European sea surface temperature This indicator monitors trends in average SST anomalies in Europe’s regional seas and in the global ocean. Care must be taken when comparing the results reported here with previous versions of the indicator, as differences can arise from the choice of underlying data sets. SST is an important physical characteristic of the oceans. It varies naturally with latitude, being warmest at the equator and coldest in the Arctic and Antarctic regions. As the oceans absorb more heat, SST will increase (and heat will be redistributed to deeper water layers). Increases in the mean SST are also accompanied by increases in the frequency and intensity of marine heatwaves (that is, when the daily SST exceeds a locally and seasonally defined threshold). Increases in SST can lead to an increase in atmospheric water vapour over the oceans, influencing entire weather systems. The North Atlantic Ocean plays a key role in the regulation of climate over the European continent by transporting heat northwards and redistributing energy from the atmosphere to the deep parts of the ocean. The Gulf Stream and its extensions, the North Atlantic Current and Drift, partly determine weather patterns over the European continent, including precipitation and wind regimes. One of the most visible physical ramifications of increased temperature in the oceans is a reduction in the area of sea ice coverage in the Arctic polar region. Temperature is a determining factor for the metabolism of species, and thus for their distribution and phenology, such as the timing of seasonal migrations, spawning events and peak abundances (e.g. plankton bloom events). There is an accumulating body of evidence suggesting that many marine species and habitats, such as cetaceans in the North Atlantic Ocean, are highly sensitive to changes in SST. Increased temperature may also increase stratification of the water column. Such changes can significantly reduce vertical nutrient fluxes in the water column, thereby negatively influencing primary production and phytoplankton community structure. Further changes in SST could have widespread effects on marine species and cause the reconfiguration of marine ecosystems (Gilbert et al., 2014; Baker-Austin et al., 2016; Collins et al., 2019).
Indicator Specification
Archived
Sea surface temperature This indicator monitors trends in average SST anomalies in Europe’s regional seas and in the global ocean.

Permalinks

For references, please go to https://www.eea.europa.eu/data-and-maps/data/external/hadsst-4-global-sea-surface or scan the QR code.

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