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Arctic sea ice has been retreating at fast pace over the last decades, with potential impacts on the weather and climate at mid and high latitudes, as well as the biosphere and society. The current sea-ice loss is driven by both atmospheric and oceanic processes. One of these key processes, the influence of ocean heat transport on Arctic sea ice, is one of the least understood due to the greater inaccessibility of the ocean compared to the atmosphere. Recent observational and modeling studies show that the poleward Atlantic and Pacific Ocean heat transports can have a strong influence on Arctic sea ice. In turn, the changing sea ice may also affect ocean heat transport, but this effect has been less investigated so far. In this review, we provide a synthesis of the main studies that have analyzed the interactions between ocean heat transport and Arctic sea ice, focusing on the most recent analyses. We make use of observations and model results, as they are both complementary, in order to better understand these interactions. We show that our understanding in sea ice - ocean heat transport relationships has improved during recent years. The Barents Sea is the Arctic region where the influence of ocean heat transport on sea ice has been the largest in the past years, explaining the large number of studies focusing on this specific region. The Pacific Ocean heat transport also constitutes a key driver in the recent Arctic sea-ice changes, thus its contribution needs to be taken into account. Although under-studied, the impact of sea-ice changes on ocean heat transport, via changes in ocean temperature and circulation, is also important to consider. Further analyses are needed to improve our understanding of these relationships using observations and climate models.

The concept of feedback is key in assessing whether a perturbation to a system is amplified or damped by mechanisms internal to the system. In polar regions, climate dynamics are controlled by both radiative and non-radiative interactions between the atmosphere, ocean, sea ice, ice sheets and land surfaces. Precisely quantifying polar feedbacks is required for a process-oriented evaluation of climate models, a clear understanding of the processes responsible for polar climate changes, and a reduction in uncertainty associated with model projections. This quantification can be performed using a simple and consistent approach that is valid for a wide range of feedbacks, offering the opportunity for more systematic feedback analyses and a better understanding of polar climate changes. Estimating the magnitude of radiative and non-radiative feedbacks is key for understanding the climate dynamics of polar regions. Here the authors propose an inclusive methodology to quantify the influence of all those feedbacks, stimulating more systematic analyses in observational and model ensembles.

Arctic sea ice has been retreating at an accelerating pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) and select models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to lower Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of future Arctic sea-ice loss when including all CMIP6 models.

One of the clearest manifestations of ongoing global climate change is the dramatic retreat and thinning of the Arctic sea-ice cover1. While all state-of-the-art climate models consistently reproduce the sign of these changes, they largely disagree on their magnitude1–4, the reasons for which remain contentious3,5–7. As such, consensual methods to reduce uncertainty in projections are lacking7. Here, using the CMIP5 ensemble, we propose a process-oriented approach to revisit this issue. We show that intermodel differences in sea-ice loss and, more generally, in simulated sea-ice variability, can be traced to differences in the simulation of seasonal growth and melt. The way these processes are simulated is relatively independent of the complexity of the sea-ice model used, but rather a strong function of the background thickness. The larger role played by thermodynamic processes as sea ice thins8,9 further suggests that the recent10 and projected11 reductions in sea-ice thickness induce a transition of the Arctic towards a state with enhanced volume seasonality but reduced interannual volume variability and persistence, before summer ice-free conditions eventually occur. These results prompt modelling groups to focus their priorities on the reduction of sea-ice thickness biases.

The sea-ice cover in the Barents and Kara Seas (BKS) displays pronounced interannual variability. Both atmospheric and oceanic drivers have been found to influence sea-ice variability, but their relative strength and regional importance remain under debate. Here, we use the Liang-Kleeman information flow method to quantify the causal influence of oceanic and atmospheric drivers on the annual sea-ice cover in the BKS in the Community Earth System Model large ensemble and reanalysis. We find that atmospheric drivers dominate in the northern part, ocean heat transport dominates in the central and northeastern part, and local sea-surface temperature dominates in the southern part. Furthermore, the large-scale atmospheric circulation over the Nordic Seas drives ocean heat transport into the Barents Sea, which then influences sea ice. Under future sea-ice retreat, the atmospheric drivers are expected to become more important.

Arctic sea-ice extent has strongly decreased since the beginning of satellite observations in the late 1970s. While several drivers are known to be implicated, their respective contribution is not fully understood. Here, we apply the Liang-Kleeman information flow method to five different large ensembles from the Coupled Model Intercomparison Project Phase 6 (CMIP6) over the 1970-2060 period to investigate the extent to which fluctuations in winter sea-ice volume, air temperature and ocean heat transport drive changes in subsequent summer Arctic sea-ice extent. This allows us to go beyond classical correlation analyses. Results show that air temperature is the most important controlling factor of summer sea-ice extent at interannual time scale, and that winter sea-ice volume and Atlantic Ocean heat transport play a secondary role. If we replace air temperature by net shortwave and downward longwave radiations, we find that the sum of influences from both radiations is almost similar to the air temperature influence, with the longwave radiation being dominant in driving changes in summer sea-ice extent. Finally, we find that the influence of air temperature is more prominent during periods of large sea-ice reduction and that this temperature influence has overall increased since 1970.

The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of Earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility. It consists of (1) an easy-to-install, well-documented Python package providing the core functionalities (ESMValCore) that performs common preprocessing operations and (2) a diagnostic part that includes tailored diagnostics and performance metrics for specific scientific applications. Here we describe large-scale diagnostics of the second major release of the tool that supports the evaluation of ESMs participating in CMIP Phase 6 (CMIP6). ESMValTool v2.0 includes a large collection of diagnostics and performance metrics for atmospheric, oceanic, and terrestrial variables for the mean state, trends, and variability. ESMValTool v2.0 also successfully reproduces figures from the evaluation and projections chapters of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) and incorporates updates from targeted analysis packages, such as the NCAR Climate Variability Diagnostics Package for the evaluation of modes of variability, the Thermodynamic Diagnostic Tool (TheDiaTo) to evaluate the energetics of the climate system, as well as parts of AutoAssess that contains a mix of top–down performance metrics. The tool has been fully integrated into the Earth System Grid Federation (ESGF) infrastructure at the Deutsches Klimarechenzentrum (DKRZ) to provide evaluation results from CMIP6 model simulations shortly after the output is published to the CMIP archive. A result browser has been implemented that enables advanced monitoring of the evaluation results by a broad user community at much faster timescales than what was possible in CMIP5.

Arctic sea-ice area and volume have substantially decreased since the beginning of the satellite era. Concurrently, the poleward heat transport from the North Atlantic Ocean into the Arctic has increased, partly contributing to the loss of sea ice. Increasing the horizontal resolution of general circulation models (GCMs) improves their ability to represent the complex interplay of processes at high latitudes. Here, we investigate the impact of model resolution on Arctic sea ice and Atlantic Ocean heat transport (OHT) by using five different state-of-the-art coupled GCMs (12 model configurations in total) that include dynamic representations of the ocean, atmosphere and sea ice. The models participate in the High Resolution Model Intercomparison Project (HighResMIP) of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Model results over the period 1950–2014 are compared to different observational datasets. In the models studied, a finer ocean resolution drives lower Arctic sea-ice area and volume and generally enhances Atlantic OHT. The representation of ocean surface characteristics, such as sea-surface temperature (SST) and velocity, is greatly improved by using a finer ocean resolution. This study highlights a clear anticorrelation at interannual time scales between Arctic sea ice (area and volume) and Atlantic OHT north of 60 ∘ N in the models studied. However, the strength of this relationship is not systematically impacted by model resolution. The higher the latitude to compute OHT, the stronger the relationship between sea-ice area/volume and OHT. Sea ice in the Barents/Kara and Greenland–Iceland–Norwegian (GIN) Seas is more strongly connected to Atlantic OHT than other Arctic seas.

A multimodel, multiresolution ensemble using Coupled Model Intercomparison Project Phase 6 (CMIP6) High Resolution Model Intercomparison Project (HighResMIP) coupled experiments is used to assess the performance of key aspects of the North Atlantic circulation. The Atlantic Meridional Overturning Circulation (AMOC), and related heat transport, tends to become stronger as ocean model resolution is enhanced, better agreeing with observations at 26.5°N. However, for most models the circulation remains too shallow compared to observations and has a smaller temperature contrast between the northward and southward limbs of the AMOC. These biases cause the northward heat transport to be systematically too low for a given overturning strength. The higher‐resolution models also tend to have too much deep mixing in the subpolar gyre. In the period 2015–2050 the overturning circulation tends to decline more rapidly in the higher‐resolution models, which is related to both the mean state and to the subpolar gyre contribution to deep water formation. The main part of the decline comes from the Florida Current component of the circulation. Such large declines in AMOC are not seen in the models with resolutions more typically used for climate studies, suggesting an enhanced risk for Northern Hemisphere climate change. However, only a small number of different ocean models are included in the study. Plain Language Summary The ocean circulation in the North Atlantic is important for Northern Hemisphere climate, and hence, it is important to assess the risk of changes caused by climate change. In this work we use seven different global coupled climate models to simulate the period 1950–2050, using different horizontal grid spacings of the ocean (and atmosphere) models. We find that, when assessed against observations at 26.5°N in the Atlantic, the higher‐resolution models tend to perform better, though this is not so obviously the case at higher latitudes. In the future projections to 2050, the higher‐resolution models typically have a larger reduction in their ocean circulation compared to the lower‐resolution models, with potential implications for climate risk and impacts. Key Points The Atlantic Meridional Overturning Circulation and northward heat transport typically increase in strength at higher horizontal model resolution The Atlantic Meridional Overturning Circulation in most of the higher‐resolution models declines more quickly in the future projections The results suggest that to fully assess the risk of changes to Atlantic Ocean circulation requires use of higher‐resolution models

We use an ensemble of models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) to analyse the number of days with extreme winter precipitation over Northern Europe and its relationship to the North Atlantic Oscillation (NAO), for the historical period 1950–2014 and two future 21st-century scenarios. Here we find that over Northern Europe, the models project twice more extreme precipitation days by the end of the 21st century under the high-emission scenario compared to the historical period. We also find a weakening of the NAO variability in the second half of the 21st century in the high greenhouse gas emission scenario compared to the historical period, as well as an increasing correlation between extreme winter precipitation events and the NAO index in both future scenarios. Models with a projected decrease in the NAO variability across the 21st century show a positive trend in the number of days with extreme winter precipitation over Northern Europe. These results highlight the role played by NAO in modulating extreme winter precipitation events.