Human-induced warming is amplified in the Arctic, but its causes and consequences are not precisely known. Here, we review scientific advances facilitated by the Polar Amplification Model Intercomparison Project. Surface heat flux changes and feedbacks triggered by sea-ice loss are critical to explain the magnitude and seasonality of Arctic amplification. Tropospheric responses to Arctic sea-ice loss that are robust across models and separable from internal variability have been revealed, including local warming and moistening, equatorward shifts of the jet stream and storm track in the North Atlantic, and fewer and milder cold extremes over North America. Whilst generally small compared to simulated internal variability, the response to Arctic sea-ice loss comprises a non-negligible contribution to projected climate change. For example, Arctic sea-ice loss is essential to explain projected North Atlantic jet trends and their uncertainty. Model diversity in the simulated responses has provided pathways to observationally constrain the real-world response. The Polar Amplification Model Intercomparison Project reveals robust jet stream and storm track responses to Arctic sea-ice loss that are separable from internal variability, and the model diversity provides pathways to constrain the real-world response

It is well established that internal variability arising spontaneously from the chaotic nature of the climate system can amplify or obscure anthropogenically-forced signals, especially at near-term and at regional scale in the extratropics. In this talk, we focus on Northern Europe (NEU) winter climate changes over the 2020-2040 period and propose a set of internal variability storylines (IVS) to tackle related uncertainties. IVS are built from the combined evolution of the North Atlantic Oscillation (NAO) and the Atlantic Meridional Overturning Circulation (AMOC) diagnosed as drivers of variability for temperature over NEU. We first show, based on a large ensemble of historical-scenario simulations from CNRM-CM6-1, that, depending on the near-term [AMOC-NAO] doublet evolution, anthropogenically-forced changes can be either considerably amplified with much warmer-wetter mean conditions, almost doubled, or considerably masked with marginal warming and unchanged mean precipitation with respect to present day. We then provide evidence for the robustness of our results by using large-ensembles from several models which ultimately allows assessing the full range of uncertainties for near-term climate change. We finally use the 2010 severe winter case as an illustrative example of the added-value in expressing climate change knowledge in a conditional form through IVS to plan at best climate-related risks and local adaptation strategies at near term. Reframing the uncertain climate outcomes into the physical science space through IVS grapples the complexity of regional situations; it is also informative to more efficiently communicate towards the general public as well as for climate literacy in general.

Abstract The CNRM‐Cerfacs Climate Prediction System (C3PS) is a new research modeling tool for performing climate reanalyzes and seasonal‐to‐multiannual predictions for a wide array of Earth system variables. C3PS is based on the CNRM‐ESM2‐1 model including interactive aerosols and stratospheric chemistry schemes as well as terrestrial and marine biogeochemistry enabling a comprehensive representation of the global carbon cycle. C3PS operates through a seamless coupled initialization for the atmosphere, land, ocean, sea ice and biogeochemistry components that allows a continuum of predictions across seasonal to multiannual time‐scales. C3PS has also contributed to the Decadal Climate Prediction Project (DCPP‐A) as part of the sixth Coupled Model Intercomparison Project (CMIP6). Here we describe the main characteristics of this novel Earth system‐based prediction platform, including the methodological steps for obtaining initial states to produce forecasts. We evaluate the entire C3PS initialization procedure with the most up‐to‐date observations and reanalyzes over 1960–2021, and we discuss the overall performance of the system in the light of the lessons learned from previous and actual prediction platforms. Regarding the forecast skill, C3PS exhibits comparable seasonal predictive skill to other systems. At the multiannual scale, C3PS shows significant predictive skill in surface temperature during the first 2 years after initialization in several regions of the world. C3PS also exhibits potential predictive skill in Net primary production (NPP) and carbon fluxes several years in advance. This expands the possibility of applications of forecasting systems, such as the possibility of performing multiannual predictions of marine ecosystems and carbon cycle.

Internal variability arising from the inherently chaotic nature of the climate system has amplified or obscured human-caused changes, especially at regional scales in the extratropics, where its contribution to climate variability is the largest. It is virtually certain that this will continue in the near-term. We here focus on the Northern Europe region, whose variability is largely controlled by the North Atlantic Oscillation (NAO) and the Atlantic Meridional Overturning Circulation (AMOC) through remote dynamical and thermodynamic processes, and introduce the concept of internal variability storylines (IVS) to explore, understand, and quantify the role of the two combined drivers of internal variability in the modulation of the anthropogenic warming by 2040 in winter. Based on a large ensemble of historical-scenario simulations, we show that the high-impact IVS, characterised by weak AMOC decline and a decadal shift of the NAO toward dominant positive phase, leads faster to warmer-wetter conditions independently of actual and future greenhouse gases emissions. By contrast, amplified AMOC reduction and more recurrent negative NAO can considerably damp both warming and wettening at near-term. In the latter IVS, we provide evidence that winter-severe conditions similar to those in 2010, that had been responsible for widespread socio-economic disruptions, remain almost as likely to occur by 2040. Reframing the uncertain climate outcomes into the physical science space in a conditional form through the prism of IVS makes climate information relevant for accurate risk assessments and adaptation planning.

This study investigates the differences in atmospheric responses to Arctic sea ice anomalies between simulations from six (atmospheric-only) models contributing to the Polar Amplification Model Intercomparison Project and one long control simulation (piControl from CMIP6) from the same six (coupled) models. We perform a composite analysis between years of low and high Arctic sea ice extent in the piControl and consider four different types of experiment in the PAMIP where only the sea ice concentration is changed (pdSST-futArcSIC, pdSST-futBKSeasSIC, pdSST-futOkhotskSIC and pdSST-pdArcSIC) to examine the associated atmospheric circulation changes owing to an Arctic sea ice loss. A negative change in the North Atlantic Oscillation (NAO) pattern emerges in winter, linked to the so-called stratospheric pathway, and is mainly due to the sea ice anomaly in the Barents-Kara Seas. The results in the PAMIP experiments support these findings, except that the intensity is lower than in the piControl composite analysis. This work highlights that the atmospheric circulation responses to Arctic sea ice loss in a long control simulation (CMIP6) show similarities with the responses of a coordinated set of numerical model experiments with prescribed sea ice (PAMIP). However, the atmospheric responses in the numerical models with prescribed sea ice display weaker changes than in CMIP6. The role of the atmosphere-ocean coupling and of the initial sea ice condition could be the main reasons for this difference in intensity.

Abstract. The atmospheric circulation response to Arctic sea ice loss may differ depending on the region of sea ice loss but also on the methodology used to study this impact. Examining the different possible atmospheric circulation responses to sea ice loss is essential, as the Arctic sea ice is not melting uniformly. In this study, we examine the atmospheric response in winter to regional sea ice loss using two different approaches across seven climate models. The sea ice anomaly areas are the pan-Arctic, the Barents-Kara Seas only, and the Sea of Okhotsk only. The first approach involves sensitivity experiments performed within the Polar Amplification Model Intercomparison Project (PAMIP), while the second approach entails a composite analysis in long pre-industrial control simulations from CMIP6. Our results reveal that both approaches lead to consistent atmospheric circulation responses to pan-Arctic sea ice loss, characterized by a negative phase in the North Atlantic Oscillation and a weakening of the stratospheric polar vortex. Similar responses to BK sea ice loss are simulated, albeit with more spread in the PAMIP experiments. The responses to Okhotsk sea ice loss differ and are uncertain in both approaches. Furthermore, larger changes are detected in the composite analysis than in the sensitivity experiments, likely due to a different background state and the presence of confounding factors in the composite analysis. We also find that the atmosphere-ocean coupling does not imply larger circulation changes or a better representation of the eddy momentum feedback in the climate response. These results highlight that sea ice loss in sensitivity experiments yields a weaker atmospheric circulation response compared to the pre-industrial simulations in CMIP6 where the sea ice loss is governed by internal climate variability. A quantification of the role played by factors related to sea ice loss that amplifies the response should be further investigated.

The pattern and magnitude of the Atlantic meridional overturning circulation (AMOC) in response to an increase in atmospheric carbon dioxide (CO2) concentration greatly differ across climate models in particular due to differ-ences in the representation of oceanic processes. Here, we investigate the response of the AMOC to an idealized climate change scenario, along with the drivers of this response, in the three configurations of a coupled climate model suite with varying resolutions in the ocean (1 & DEG;, 0.25 & DEG;, 0.10 & DEG;). In response to the CO2 increase, the AMOC shows a reduction of similar magnitude in the low and high resolutions, while a muted response is found in the medium resolution. A decomposition of the AMOC into its geostrophic and residual components reveals that most of the AMOC reduction is due to a weakening of the geostrophic streamfunction driven by temperature anomalies, partly opposed by a strengthening of the geostrophic streamfunction driven by salinity anomalies. Changes in the AMOC due to the mesoscale eddy streamfunction contribute to 13% and 17% of the AMOC decline in the low and high resolutions, respectively, but induce very little change in the medium resolution. The similar response of the AMOC strength in the low and high resolutions hides important differ-ences in the contribution and pattern of the geostrophic and eddy streamfunctions. The lack of sensitivity of the medium resolution to the CO2 forcing is due to a weak connection between the deep water formation regions in the northern sub-polar gyre and the Deep Western Boundary Current.

The mid-latitude climate responses to Arctic sea ice loss remain unclear, partly because the atmospheric responses depend sensitively to the location of sea ice anomalies. Evaluating the role of regional Arctic sea ice extent anomalies is therefore essential to appreciate the extent of atmospheric responses. We investigated these responses but also the atmospheric precursors to regional Arctic sea ice extent anomalies in long pre-industrial control simulations from 36 CMIP6 climate models. This study examines changes in various atmospheric variables at different lead and lag times by performing a composite analysis between years of low and high sea ice extents in different Arctic seas. Stronger and more statistically significant relationships are found when the atmosphere leads to changes in sea ice than in the reverse direction, suggesting that in the CMIP6 models the atmosphere drives the sea ice rather than the opposite. The atmospheric circulation is found to be relatively insensitive to regional sea ice anomalies except in the Barents–Kara (BAKA) Seas, where the negative anomalies are followed by a robust negative winter North Atlantic Oscillation (NAO)-like pattern. Consistent with the so-called stratospheric pathway, a weakening of the stratospheric polar vortex (SPV) is simulated 1 month prior to the NAO change and can be partially explained by the sea ice anomaly in BAKA in preceding months. The magnitude of this weakening in models depends on other factors, such as the Siberian snow cover, the El Niño–Southern oscillation, and the quasi-biennial oscillation. Moreover, the SPV and the NAO index responses scale approximately linearly with the magnitude of the BAKA sea ice anomaly. These results highlight the inter-model consistency of the role played by the BAKA sea ice extent anomaly for the atmospheric responses under pre-industrial conditions. In upcoming work, the sea ice loss in this region should therefore primarily be considered, but under future conditions.

The retreat of Arctic sea ice is frequently considered to be a possible driver of changes in climate extremes in the Arctic and possibly down to mid-latitudes. However, it remains unclear how the atmosphere will respond to a near-total retreat of summer Arctic sea ice, a reality that might occur in the foreseeable future. This study explores this question by conducting sensitivity experiments with two global coupled climate models run at two different horizontal resolutions to investigate the change in temperature and precipitation extremes during summer over peripheral Arctic regions following a sudden reduction in summer Arctic sea ice cover. An increase in frequency and persistence of maximum surface air temperature is found in all peripheral Arctic regions during the summer, when sea ice loss occurs. For each 1×106 km2 of Arctic sea ice extent reduction, the absolute frequency of days exceeding the surface air temperature of the climatological 90th percentile increases by ∼ 4 % over the Svalbard area, and the duration of warm spells increases by ∼ 1 d per month over the same region. Furthermore, we find that the 10th percentile of surface daily air temperature increases more than the 90th percentile, leading to a weakened diurnal cycle of surface air temperature. Finally, an increase in extreme precipitation, which is less robust than the increase in extreme temperatures, is found in all regions in summer. These findings suggest that a sudden retreat of summer Arctic sea ice clearly impacts the extremes in maximum surface air temperature and precipitation over the peripheral Arctic regions with the largest influence over inhabited islands such as Svalbard or northern Canada. Nonetheless, even with a large sea ice reduction in regions close to the North Pole, the local precipitation response is relatively small compared to internal climate variability.

The possibility that Arctic sea ice loss weakens mid-latitude westerlies, promoting more severe cold winters, has sparked more than a decade of scientific debate, with apparent support from observations but inconclusive modelling evidence. Here we show that sixteen models contributing to the Polar Amplification Model Intercomparison Project simulate a weakening of mid-latitude westerlies in response to projected Arctic sea ice loss. We develop an emergent constraint based on eddy feedback, which is 1.2 to 3 times too weak in the models, suggesting that the real-world weakening lies towards the higher end of the model simulations. Still, the modelled response to Arctic sea ice loss is weak: the North Atlantic Oscillation response is similar in magnitude and offsets the projected response to increased greenhouse gases, but would only account for around 10% of variations in individual years. We further find that relationships between Arctic sea ice and atmospheric circulation have weakened recently in observations and are no longer inconsistent with those in models.

Air-sea interaction processes over the Gulf Stream have received particular attention over the last decade. It has been shown that sea surface temperature (SST) gradients over the Gulf Stream can alter the near surface wind divergence through changes in the marine atmospheric boundary layer (MABL). Two mechanisms have been proposed to explain the response: the Vertical Mixing Mechanism (VMM) and the Pressure Adjustment Mechanism (PAM). However, their respective contribution is still under debate. It has been argued that the synoptic perturbations over the Gulf Stream can provide more insight on the MABL response to SST fronts. We analyze the VMM and PAM under different atmospheric conditions obtained from a classification method based on the deciles of the statistical distribution of winter turbulent heat fluxes over the Gulf Stream. Lowest deciles are associated with weak air-sea interactions and anticyclonic atmospheric circulation over the Gulf Stream, whereas highest deciles are related to strong air-sea interactions and a cyclonic circulation. Our analysis includes the low and high-resolution versions of the ARPEGEv6 atmospheric model forced by observed SST, and the recently released ERA5 global reanalysis. We find that the occurrence of anticyclonic and cyclonic perturbations associated with different anomalous wind regimes can locally modulate the activation of the VMM and the PAM. In particular, the PAM is predominant in anticyclonic conditions, whereas both mechanisms are equally present in most of the cyclonic conditions. Our results highlight the role of the atmospheric circulation and associated anomalous winds in the location, strength and occurrence of both mechanisms.

Previous climate model studies have shown that Arctic sea ice decline can solely affect weather and climate at lower latitudes during the cold season. However, the mechanisms beneath this linkage are poorly understood. Whether sea ice loss have had an influence on the lower latitudes climate over the past decades is also uncertain (Barnes and Screen 2015). The goal of this work is to better understand the relative contributions of dyncamical and thermodynamical changes in the atmospheric response to Arctic sea ice loss, which have been suggested to oppose each other (Screen 2017). We conducted two sets of sensitivity transient experiments that allow to isolate the effect of Arctic sea ice decline on the mid-latitudes from other climate forcings, using the climate model CNRM-CM6 (Voldoire et al. 2019) in a coupled configuration or with an atmosphere-only. The first set of experiments, that is part of the European H2020 PRIMAVERA project, consists of a 100-member ensemble in which sea ice albedo is reduced to the ocean value (PERT) in the fully coupled CNRM-CM6, and which is compared to a 1950 control run (CTL) (Haarsma et al. 2016). This yields idealised ice-free conditions in summer and a more moderate sea ice reduction during the following months. The second set of experiments, that is part of the CMIP6 Polar Amplification Model Intercomparison Project (PAMIP, Smith et al. 2019), consists of a 300-member ensemble in which the atmospheric component of CNRM-CM6 is forced by sea ice anomalies associated with a future 2°C warming (FUT) and present day sea surface temperatures (SSTs). These are compared to experiments in which the atmosphere is forced by present-day sea ice conditions (PD) and the same SSTs. To extract the dynamical component of the response in the two sets of experiments, we use a dynamical adjustment method (Deser et al. 2016) based on a regional reconstruction of circulation analogs. We focus on three mid-latitudes regions in which a significant near-surface temperature response has been identified, namely North America, Europe and central Asia. We show that the cooling occurring over central Asia in both sets of experiments is dynamically-induced through an intensification of the Siberian High, and that opposed temperature responses over North America between the two sets of experiments could be explained by opposed dynamical components occurring in response to the imposed Arctic sea ice decline. Finally, we discuss whether different dynamical and thermodynamical contributions in the PAMIP multi-model experiments could explain the multi-model differences in the atmospheric response to sea ice loss.

The Northern Hemisphere transient atmospheric response to Arctic sea decline is investigated in autumn and winter, using sensitivity experiments performed with the CNRMCM6-1 high-top climate model. Arctic sea ice albedo is reduced to the ocean value, yielding ice-free conditions during summer and a more moderate sea ice reduction during the following months. A strong ampli_cation of temperatures over the Arctic is induced by sea ice loss, with values reaching up to 25°C near the surface in autumn. Signi_cant surface temperature anomalies are also found over the mid-latitudes, with a warming reaching 1°C over North America and Europe, and a cooling reaching 1°C over central Asia. Using a dynamical adjustment method based on a regional reconstruction of circulation analogs, we show that the warming over North America and Europe can be explained both by changes in the atmospheric circulation and by the advection of warmer oceanic air by the climatological ow. In contrast, we demonstrate that the sea-ice induced cooling over central Asia is solely due to dynamical changes, involving an intensi_cation of the Siberian High and a cyclonic anomaly over the Sea of Okhotsk. In the troposphere, the abrupt Arctic sea ice decline favours a narrowing of the subtropical jet stream and a slight weakening of the lower part of the polar vortex that is explained by a weak enhancement of upward wave activity toward the stratosphere. We further show that reduced Arctic sea ice in our experiments is mainly associated with less severe cold extremes in the mid-latitudes.

Atlantic multidecadal variability (AMV) has been linked to the observed slowdown of global warming over 1998–2012 through its impact on the tropical Pacific. Given the global importance of tropical Pacific variability, better understanding this Atlantic–Pacific teleconnection is key for improving climate predictions, but the robustness and strength of this link are uncertain. Analyzing a multi-model set of sensitivity experiments, we find that models differ by a factor of 10 in simulating the amplitude of the Equatorial Pacific cooling response to observed AMV warming. The inter-model spread is mainly driven by different amounts of moist static energy injection from the tropical Atlantic surface into the upper troposphere. We reduce this inter-model uncertainty by analytically correcting models for their mean precipitation biases and we quantify that, following an observed 0.26 °C AMV warming, the equatorial Pacific cools by 0.11 °C with an inter-model standard deviation of 0.03 °C.

The retreat of Arctic sea ice for the last four decades is a primary manifestation of the climate system response to increasing atmospheric greenhouse gas concentrations. This retreat is frequently considered as a possible driver of atmospheric circulation anomalies at mid-latitudes. However, the year-to-year evolution of the Arctic sea ice cover is also characterized by significant fluctuations attributed to internal climate variability. It is unclear how the atmosphere will respond to a near-total retreat of summer Arctic sea ice, a reality that might occur in the foreseeable future. This study uses sensitivity experiments with higher and lower horizontal resolution configurations of three global coupled climate models to investigate the local and remote atmospheric responses to a reduction in Arctic sea ice cover during the preceding summer. Recognizing that these responses likely depend on the model itself and on its horizontal resolution, and that the model’s internally-generated climate variability may obscure the atmospheric response, we design a protocol to compare each source separately. After imposing a 15-month albedo perturbation resulting in a sudden summer Arctic sea ice loss, the remote mid-latitude climate response has a very low signal-to-noise ratio such that internal climate variability dominates the uncertainty of the response, regardless of the atmospheric variable. Indeed, more than 28, 165 and 210 members are needed to detect a robust response in surface air temperature, precipitation and sea level pressure to sea ice loss in Europe, respectively. Finally, we find that horizontal resolution plays a secondary role in the uncertainty of the atmospheric response to substantial perturbation of Arctic sea ice. These findings suggest that even with higher resolution model configurations, it is important to have large ensemble sizes to increase the signal to noise ratio for the mid-latitude atmospheric response to sea ice changes.

Despite ever-increasing anthropogenic forcing due to continuing GHG emissions, a slowdown in the rate of global warming has been monitored in the early 2000s and has been mostly attributed to the effect of internal climate variability. The weight of internal variability with respect to external forcing increases at regional scale and it is crucial to understand and quantify its role in future climate outcomes. In this study, we assess the near-term climate change over Europe by contrasting a suite of large ensemble of socio-economic pathways (SSP) projections conducted over 2020-2039, with historical simulations over 1995-2014 used as reference. The uncertainty associated with future anthropogenic forcing is taken into account by analysing 4 SSP projections (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5), while the one associated with internal variability is assessed through the large ensembles of 30 members. Projections averaged over 4 SSP give a mean warming of +1.1°C over Northern Europe in Dec-Feb winter, as quantified by the difference between 20-yr averages over 2020-2039 compared to present-day (1995-2014). Since the signal (related to the forced response) to noise (related to internal variability) is small in all scenarios, ranging from 0.2 for SSP3-7.0 to 0.5 for SSP5-8.5, the 4 near-term ensembles are combined to create a super ensemble of 120 members to further evaluate the role of internal variability, whose likely range, defined by the 5th and 95th percentiles, is equal to 3.0°C for the region of interest. We apply the so-called storyline paradigm and find 4 families of future outcome, each family corresponding to a couple of given phases of the two main drivers of internal variability for Northern Europe winter temperature, namely the Atlantic meridional overturning circulation (AMOC) and the north Atlantic oscillation (NAO). More than a statistical classification, these storylines provide physically consistent future outcomes. The storyline characterised by stronger AMOC and positive NAO leads to the strongest warming, +2.3°C (+1.7 to +3.0), and has a large increase in precipitation, +10% (+5.2 to +16), compared to the storyline where AMOC is reduced and the NAO negative, leading to +0.19°C (-0.46 to +0.86) and +1.9% (-3.3 to +11) for temperature and precipitation only. Regarding temperature extremes, we show, regardless of the scenario, a clear decrease in the probability of extremely cold days in the near-term, and a statistically significant increase in the frequency of extremely warm days that is expected to double. There is, however, a larger dependence of extremes to the storyline family. In particular, the probability of occurrence of exceptionally warm days, defined by the 99th percentile level, is 4 times more likely in the combined AMOC and NAO positive phases storylines, while it is almost null for the counterpart one. We show here evidence that the storyline approach is a clear added-value to understand the role of internal variability in future climate and that it provides actionable information to users in presence of related irreducible variability uncertainties.

L'Arctique est la région du globe qui s'est réchauffée le plus vite au cours des trente dernières années, avec une augmentation de la température de surface environ deux fois plus rapide que pour la moyenne globale. Le déclin de la banquise arctique observé depuis le début de l'ère satellitaire et attribué principalement à l'augmentation de la concentration des gaz à effet de serre aurait joué un rôle important dans cette amplification des températures au pôle. Cette fonte importante des glaces arctiques, qui devrait s'accélérer dans les décennies à venir, pourrait modifier les vents en haute altitude et potentiellement avoir un impact sur le climat des moyennes latitudes. L'étendue de la banquise arctique varie considérablement d'une saison à l'autre, d'une année à l'autre, d'une décennie à l'autre. Améliorer notre capacité à prévoir ces variations nécessite de comprendre, observer et modéliser les interactions entre la banquise et les autres composantes du système Terre, telles que l'océan, l'atmosphère ou la biosphère, à différentes échelles de temps. La réalisation de prévisions saisonnières de la banquise arctique est très récente comparée aux prévisions du temps ou aux prévisions saisonnières de paramètres météorologiques (température, précipitation). Les résultats ayant émergé au cours des dix dernières années mettent en évidence l'importance des observations de l'épaisseur de la glace de mer pour prévoir l'évolution de la banquise estivale plusieurs mois à l'avance. Surface temperatures over the Arctic region have been increasing twice as fast as global mean temperatures, a phenomenon known as arctic amplification. One main contributor to this polar warming is the large decline of Arctic sea ice observed since the beginning of satellite observations, which has been attributed to the increase of greenhouse gases. The acceleration of Arctic sea ice loss that is projected for the coming decades could modify the upper level atmospheric circulation yielding climate impacts up to the mid-latitudes. There is considerable variability in the spatial extent of ice cover on seasonal, interannual and decadal time scales. Better understanding, observing and modelling the interactions between sea ice and the other components of the climate system is key for improved predictions of Arctic sea ice in the future. Running operational-like seasonal predictions of Arctic sea ice is a quite recent effort compared to weather predictions or seasonal predictions of atmospheric fields like temperature or precipitation. Recent results stress the importance of sea ice thickness observations to improve seasonal predictions of Arctic sea ice conditions during summer.

This work aims to clarify the relation between the Atlantic meridional overturning circulation (AMOC) and the thermal wind. We derive a new and generic dynamical AMOC decomposition that expresses the thermal wind transport as a simple vertical integral function of eastern minus western boundary densities. This allows us to express density anomalies at any depth as a geostrophic transport in Sverdrups (1 Sv ≡ 106 m3 s−1) per meter and to predict that density anomalies around the depth of maximum overturning induce most AMOC transport. We then apply this formalism to identify the dynamical drivers of the centennial AMOC variability in the CNRM-CM6 climate model. The dynamical reconstruction and specifically the thermal wind component explain over 80% of the low-frequency AMOC variance at all latitudes, which is therefore almost exclusively driven by density anomalies at both zonal boundaries. This transport variability is dominated by density anomalies between depths of 500 and 1500 m, in agreement with theoretical predictions. At those depths, southward-propagating western boundary temperature anomalies induce the centennial geostrophic AMOC transport variability in the North Atlantic. They are originated along the western boundary of the subpolar gyre through the Labrador Sea deep convection and the Davis Strait overflow.

Observed September Arctic sea ice has declined sharply over the satellite era. While most climate models forced by observed external forcing simulate a decline, few show trends matching the observations, suggesting either model deficiencies or significant contributions from internal variability. Using a set of perturbed climate model experiments, we provide evidence that atmospheric teleconnections associated with the Atlantic multidecadal variability (AMV) can drive low-frequency Arctic sea ice fluctuations. Even without AMV-related changes in ocean heat transport, AMV-like surface temperature anomalies lead to adjustments in atmospheric circulation patterns that produce similar Arctic sea ice changes in three different climate models. Positive AMV anomalies induce a decrease in the frequency of winter polar anticyclones, which is reflected both in the sea level pressure as a weakening of the Beaufort Sea high and in the surface temperature as warm anomalies in response to increased low-cloud cover. Positive AMV anomalies are also shown to favor an increased prevalence of an Arctic dipole–like sea level pressure pattern in late winter/early spring. The resulting anomalous winds drive anomalous ice motions (dynamic effect). Combined with the reduced winter sea ice formation (thermodynamic effect), the Arctic sea ice becomes thinner, younger, and more prone to melt in summer. Following a phase shift to positive AMV, the resulting atmospheric teleconnections can lead to a decadal ice thinning trend in the Arctic Ocean on the order of 8%–16% of the reconstructed long-term trend, and a decadal trend (decline) in September Arctic sea ice area of up to 21% of the observed long-term trend.