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.
Methodology for indicator calculation
This methodology is extracted from Copernicus Climate Change Service (C3S web).
This indicator primarily uses information from the HadISST1, HadSST4, Extended Reconstruction Sea Surface Temperature version 5 (ERSSTv5) and European Space Agency Sea Surface Temperature Climate Change Initiative (ESA CCI/C3S SST Climate Data Record v2.1) Analysis data sets.
Anomalies are calculated relative to a 1991–2020 average. For the satellite data (ESA CCI/C3S SST), the anomalies are calculated daily based on a daily climatology computed from a five-day mean centered on each day. For the in situ datasets, anomalies are calculated on a monthly basis by subtracting the 1991–2020 mean anomaly (relative to the original baseline used by the dataset) for each month. Daily anomalies were aggregated to monthly anomalies, and the monthly anomalies were aggregated to annual anomalies giving each month an equal weight.
Area-averaged anomalies were calculated using an area-weighted average of non-missing grid cells within the chosen region. A grid cell was assumed to be within a region if its center was within the region. Ocean area in the in situ products was estimated based on the high-resolution C3S satellite product, assigning 100% ocean area to grid cells populated in the satellite product and 100% land area to grid cells that are missing in that product. A 10-year rolling mean centered on right edge of the window is applied to the annual times series.
Due to lack of observations during some periods of 19th century and first half of 20th, Black Sea is only represented from the 1950s onward.
Uncertainty information in large scale aggregates is not available for the L4 satellite data, so uncertainties in this product were not computed.
Uncertainties in the HadSST4 product were calculated following Kennedy et al. (2019). Correlated uncertainties were assumed to be correlated within a year and uncorrelated between years where appropriate. Uncertainties were not calculated for the ERSSTv5 and HadISST1 datasets. No uncertainty information is available for HadISST1. Pre-computed uncertainties in the ERSSTv5 data are available for the global mean but not for the European seas and other regional SST averages. Uncertainty in ERSSTv5 is represented by an ensemble, but the ensemble is not regularly updated. Final uncertainty (shown in figure) is based on maximum and minimum values of HadISST1, ERSSTv5 and higher and lower boundaries of HadSST4.
The areas used for the regional seas are the following:
· Europe: 35°-70°N, 25°W-40°E
· Baltic Sea: 52.5°-67.5°N, 8.5°-30.5°E
· Black Sea: 39.5°-48.5°N, 27.5°W-42.5°E
· Mediterranean: 30.5°-46.5°N, 6.5°W-38.5°E
Methodology for gap filling
In February 2021, the European Commission adopted a new EU strategy for adaptation to climate change . The new strategy sets out how the European Union can adapt to the unavoidable impacts of climate change and become climate resilient by 2050. It has four principle objectives: to make adaptation smarter, swifter and more systemic, and to step up international action on adaptation to climate change. The strategy builds on the 2018 evaluation of the 2013 EU adaptation strategy accompanied by a Commission staff working document . An open public consultation was conducted in preparation for the new strategy between May and August 2020.
No targets have been specified.
Data sets uncertainty
Systematic observations of SST began around 1850. More recently, manual measurements have been complemented by satellite-based observations that have a high degree of temporal resolution and wide geographical coverage, and by measurements from drifting buoys and Argo floats that automatically measure temperature and salinity below the ocean surface.
No uncertainty has been specified.