Estimating long-term modifications of the sea surface temperature (SST) is crucial for evaluating the current state of the oceans and to correctly assess the impact of climate change at regional scales. In this work, we analyze SST variations within the Mediterranean Sea and the adjacent Northeastern Atlantic box (west of the Strait of Gibraltar) over the last 37 years, by using a satellite-based dataset from the Copernicus Marine Environment Monitoring Service (CMEMS). We found a mean warming trend of $0.041\pm 0.006$ ${}^{\circ }$ C/year over the whole Mediterranean Sea from 1982 to 2018. The trend has an uneven spatial pattern, with values increasing from $0.036\pm 0.006$ ${}^{\circ }$ C/year in the western basin to $0.048\pm 0.006$ ${}^{\circ }$ C/year in the Levantine–Aegean basin. The Northeastern Atlantic box and the Mediterranean show a similar trend until the late 1990s. Afterwards, the Mediterranean SST continues to increase, whereas the Northeastern Atlantic box shows no significant trend, until ~2015. The observed change in the Mediterranean Sea affects not only the mean trend but also the amplitude of the Mediterranean seasonal signal, with consistent relative increase and decrease of summer and winter mean values, respectively, over the period considered. The analysis of SST changes occurred during the “satellite era” is further complemented by reconstructions also based on direct in situ SST measurements, i.e., the Extended Reconstructed SST (ERSST) and the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST), which go back to the 19th century. The analysis of these longer time series, covering the last 165 years, indicates that the increasing Mediterranean trend, observed during the CMEMS operational period, is consistent with the Atlantic Multidecadal Oscillation (AMO), as it closely follows the last increasing period of AMO. This coincidence occurs at least until 2007, when the apparent onset of the decreasing phase of AMO is not seen in the Mediterranean SST evolution.

A joint effort between the Copernicus Climate Change Service (C3S) and the Group for High Resolution Sea Surface Temperature (GHRSST) has been dedicated to an intercomparison study of eight global gap-free sea surface temperature (SST) products to assess their accurate representation of the SST relevant to climate analysis. In general, all SST products show consistent spatial patterns and temporal variability during the overlapping time period (2003–18). The main differences between each product are located in the western boundary current and Antarctic Circumpolar Current regions. Linear trends display consistent SST spatial patterns among all products and exhibit a strong warming trend from 2012 to 2018 with the Pacific Ocean basin as the main contributor. The SST discrepancy between all SST products is very small compared to the significant warming trend. Spatial power spectral density shows that the interpolation into 1° spatial resolution has negligible impacts on our results. The global mean SST time series reveals larger differences among all SST products during the early period of the satellite era (1982–2002) when there were fewer observations, indicating that the observation frequency is the main constraint of the SST climatology. The maturity matrix scores, which present the maturity of each product in terms of documentation, storage, and dissemination but not the scientific quality, demonstrate that ESA-CCI and OSTIA SST are well documented for users’ convenience. Improvements could be made for MGDSST and BoM SST. Finally, we have recommended that these SST products can be used for fundamental climate applications and climate studies (e.g., El Niño).

Sea level has risen significantly in the recent decades and is expected to rise further based on recent climate projections. Ocean reanalyses that synthetize information from observing networks, dynamical ocean general circulation models, and atmospheric forcing data offer an attractive way to evaluate sea level trend and variability and partition the causes of such sea level changes at both global and regional scales. Here, we review recent utilization of reanalyses for steric sea level trend investigations. State-of-the-science ocean reanalysis products are then used to further infer steric sea level changes. In particular, we used an ensemble of centennial reanalyses at moderate spatial resolution (between 0.5 × 0.5 and 1 × 1 degree) and an ensemble of eddy-permitting reanalyses to quantify the trends and their uncertainty over the last century and the last two decades, respectively. All the datasets showed good performance in reproducing sea level changes. Centennial reanalyses reveal a 1900–2010 trend of steric sea level equal to 0.47 ± 0.04 mm year⁻¹, in agreement with previous studies, with unprecedented rise since the mid-1990s. During the altimetry era, the latest vintage of reanalyses is shown to outperform the previous ones in terms of skill scores against the independent satellite data. They consistently reproduce global and regional upper ocean steric expansion and the association with climate variability, such as ENSO. However, the mass contribution to the global mean sea level rise is varying with products and its representability needs to be improved, as well as the contribution of deep and abyssal waters to the steric sea level rise. Similarly, high-resolution regional reanalyses for the European seas provide valuable information on sea level trends, their patterns, and their causes.

The impact of stochastic physics on El Niño Southern Oscillation (ENSO) is investigated in the EC-Earth coupled climate model. By comparing an ensemble of three members of control historical simulations with three ensemble members that include stochastics physics in the atmosphere, we find that in EC-Earth the implementation of stochastic physics improves the excessively weak representation of ENSO. Specifically, the amplitude of both El Niño and, to a lesser extent, La Niña increases. Stochastic physics also ameliorates the temporal variability of ENSO at interannual time scales, demonstrated by the emergence of peaks in the power spectrum with periods of 5–7 years and 3–4 years. Based on the analogy with the behaviour of an idealized delayed oscillator model (DO) with stochastic noise, we find that when the atmosphere–ocean coupling is small (large) the amplitude of ENSO increases (decreases) following an amplification of the noise amplitude. The underestimated ENSO variability in the EC-Earth control runs and the associated amplification due to stochastic physics could be therefore consistent with an excessively weak atmosphere–ocean coupling. The activation of stochastic physics in the atmosphere increases westerly wind burst (WWB) occurrences (i.e. amplification of noise amplitude) that could trigger more and stronger El Niño events (i.e. increase of ENSO oscillation) in the coupled EC-Earth model. Further analysis of the mean state bias of EC-Earth suggests that a cold sea surface temperature (SST) and dry precipitation bias in the central tropical Pacific together with a warm SST and wet precipitation bias in the western tropical Pacific are responsible for the coupled feedback bias (weak coupling) in the tropical Pacific that is related to the weak ENSO simulation. The same analysis of the ENSO behaviour is carried out in a future scenario experiment (RCP8.5 forcing), highlighting that in a coupled model with an extreme warm SST, characterized by a strong coupling, the effect of stochastic physics on the ENSO representation is opposite. This corroborates the hypothesis that the mean state bias of the tropical Pacific region is the main reason for the ENSO representation deficiency in EC-Earth.

More than 90% of excess energy trapped by greenhouse gases is accumulated in the oceans. Ocean heat content (OHC) and its changes are therefore fundamental metrics to monitor climate change. However, due to sparse observation sampling before the 1950s, accurate observation‐based estimations only exist for the second half of the 20th century. A 16‐member ensemble of historical ocean reanalyses is used for the first time to compile a unique estimate of 20th century oceanic warming rates. The reanalyses combine dynamical ocean general circulation models with historical observations and observation‐based atmospheric forcing. Ocean heat content tendencies (OHCT) from the multireanalysis ensemble (MRE) agree well with independent estimates of ocean heat content, and show a coherent evolution with records of Earth's energy imbalance from atmospheric reanalyses and atmospheric CO₂concentration at a range of timescales. OHCT from reanalyses proves to be a more effective climate change proxy, that is, more closely related to independent climate indexes, than observed surface warming tendencies that contain high‐frequency variability not related to the climate change signature, or historical coupled model simulations, which neglect interannual fluctuations. The ensemble mean estimate of the century‐long ocean warming rate is 0.26 ± 0.08 W m⁻². The warming rate of 0.84 ± 0.21 W m⁻²estimated from 1993 onwards is unprecedented. The global decadal warming rate is persistently positive from about 1925 onwards, except for two neutral periods. The Indian Ocean exhibits the highest relative contribution to centennial heat accumulation, while the Atlantic Ocean plays an increasingly prominent role, especially during the 1995–2004 decade. These findings are in agreement with previous studies.