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Arctic amplification (AA), referring to the phenomenon of amplified warming in the Arctic compared to the warming in the rest of the globe, is generally attributed to the increasing concentrations of carbon dioxide (CO₂) in the atmosphere. However, little attention has been paid to the mechanisms and quantitative variations of AA under decreasing levels of CO₂, when cooling where the Arctic region is considerably larger than over the rest of the planet. Analyzing climate model experiments forced with a wide range of CO₂concentrations (from 1/8× to 8×CO₂, with respect to preindustrial levels), we show that AA indeed occurs under decreasing CO₂concentrations, and it is stronger than AA under increasing CO₂concentrations. Feedback analysis reveals that the Planck, lapse-rate, and albedo feedbacks are the main contributors to producing AAs forced by CO₂increase and decrease, but the stronger lapse-rate feedback associated with decreasing CO₂level gives rise to stronger AA. We further find that the increasing CO₂concentrations delay the peak month of AA from November to December or January, depending on the forcing strength. In contrast, decreasing CO₂levels cannot shift the peak of AA earlier than October, as a consequence of the maximum sea-ice increase in September which is independent of forcing strength. Such seasonality changes are also presented in the lapse-rate feedback, but do not appear in other feedbacks nor in the atmospheric and oceanic heat transport processeses. Our results highlight the strongly asymmetric responses of AA, as evidenced by the different changes in its intensity and seasonality, to the increasing and decreasing CO₂concentrations. These findings have significant implications for understanding how carbon removal could impact the Arctic climate, ecosystems, and socio-economic activities.

Arctic amplification (AA), defined as the enhanced warming of the Arctic compared to the global average, is a robust feature of historical observations and simulations of future climate. Despite many studies investigating AA mechanisms, their relative importance remains contested. In this study, we examine the different timescales of these mechanisms to improve our understanding of AA’s fundamental causes. We use the Community Earth System Model v1, Large Ensemble configuration (CESM-LE), to generate large ensembles of 2 years simulations subjected to an instantaneous quadrupling of CO₂. We show that AA emerges almost immediately (within days) following CO₂increase and before any significant loss of Arctic sea ice has occurred. Through a detailed energy budget analysis of the atmospheric column, we determine the time-varying contributions of AA mechanisms over the simulation period. Additionally, we examine the dependence of these mechanisms on the season of CO₂quadrupling. We find that the surface heat uptake resulting from the different latent heat flux anomalies between the Arctic and global average, driven by the CO₂forcing, is the most important AA contributor on short (<1 month) timescales when CO₂is increased in January, followed by the lapse rate feedback. The latent heat flux anomaly remains the dominant AA mechanism when CO₂is increased in July and is joined by the surface albedo feedback, although AA takes longer to develop. Other feedbacks and energy transports become relevant on longer (>1 month) timescales. Our results confirm that AA is an inherently fast atmospheric response to radiative forcing and reveal a new AA mechanism.

Over recent decades, the Southern Ocean (SO) has experienced multi‐decadal surface cooling despite global warming. Earlier studies have proposed that recent SO cooling has been caused by the strengthening of surface westerlies associated with a positive trend of the Southern Annular Mode (SAM) forced by ozone depletion. Here we revisit this hypothesis by examining the relationships between the SAM, zonal winds and SO sea‐surface temperature (SST). Applying a low‐frequency component analysis to observations, we show that while positive SAM anomalies can induce SST cooling as previously found, this seasonal‐to‐interannual modulation makes only a small contribution to the observed long‐term SO cooling. Global climate models well capture the observed interannual SAM‐SST relationship, and yet generally fail to simulate the observed multi‐decadal SO cooling. The forced SAM trend in recent decades is thus unlikely the main cause of the observed SO cooling, pointing to a limited role of the Antarctic ozone hole.

Weather regimes defined through cluster analysis concisely categorize the anomalous regional circulation pattern on any given day. Owing to their persistence and low dimensionality, regimes are increasingly used in subseasonal-to-seasonal prediction and in analysis of climate variability and change. However, a limitation of existing regime classifications for North America is their seasonal dependence, with most existing studies defining regimes for winter only. Here, we normalize the seasonal cycle in daily geopotential height variance and use empirical orthogonal function analysis combined withk-means clustering to define a new set of year-round North American weather regimes: the Pacific Trough, Pacific Ridge, Alaskan Ridge, and Greenland High regimes. We additionally define a “No Regime” state to represent conditions close to climatology. To demonstrate the robustness of the classification, a thorough assessment of the sensitivity of the clustering solution to various methodological choices is provided. The median persistence of all four regimes, obtained without imposing a persistence criterion, is found to be one week, approximately 3 times longer than the median persistence of the No Regime state. Regime-associated temperature and precipitation anomalies are reported, together with the relationship between the regimes and modes of climate variability. We also quantify historical trends in the frequency of the regimes since 1979, finding a decrease in the annual frequency of the Pacific Trough regime and an increase in the summertime frequency of the Greenland High regime. This study serves as a foundation for the future use of these regimes in a variety of weather and climate applications.

Volcanic super-eruptions have been theorized to cause severe global cooling, with the 74 kya Toba eruption purported to have driven humanity to near-extinction. However, this eruption left little physical evidence of its severity and models diverge greatly on the magnitude of post-eruption cooling. A key factor controlling the super-eruption climate response is the size of volcanic sulfate aerosol, a quantity that left no physical record and is poorly constrained by models. Here we show that this knowledge gap severely limits confidence in model-based estimates of super-volcanic cooling, and accounts for much of the disagreement among prior studies. By simulating super-eruptions over a range of aerosol sizes, we obtain global mean responses varying from extreme cooling all the way to the previously unexplored scenario of widespread warming. We also use an interactive aerosol model to evaluate the scaling between injected sulfur mass and aerosol size. Combining our model results with the available paleoclimate constraints applicable to large eruptions, we estimate that global volcanic cooling is unlikely to exceed 1.5°C no matter how massive the stratospheric injection. Super-eruptions, we conclude, may be incapable of altering global temperatures substantially more than the largest Common Era eruptions. This lack of exceptional cooling could explain why no single super-eruption event has resulted in firm evidence of widespread catastrophe for humans or ecosystems.

Observational records of meteorological and chemical variables are imprinted by an unknown combination of anthropogenic activity, natural forcings, and internal variability. With a 15-member initial-condition ensemble generated from the CESM2-WACCM6 chemistry-climate model for 1950–2014, we extract signals of anthropogenic (‘forced’) change from the noise of internally arising climate variability on observed tropospheric ozone trends. Positive trends in free tropospheric ozone measured at long-term surface observatories, by commercial aircraft, and retrieved from satellite instruments generally fall within the ensemble range. CESM2-WACCM6 tropospheric ozone trends are also bracketed by those in a larger ensemble constructed from five additional chemistry-climate models. Comparison of the multi-model ensemble with observed tropospheric column ozone trends in the northern tropics implies an underestimate in regional precursor emission growth over recent decades. Positive tropospheric ozone trends clearly emerge from 1950 to 2014, exceeding 0.2 DU yr⁻¹at 20–40 N in all CESM2-WACCM6 ensemble members. Tropospheric ozone observations are often only available for recent decades, and we show that even a two-decade record length is insufficient to eliminate the role of internal variability, which can produce regional tropospheric ozone trends oppositely signed from ensemble mean (forced) changes. By identifying regions and seasons with strong anthropogenic change signals relative to internal variability, initial-condition ensembles can guide future observing systems seeking to detect anthropogenic change. For example, analysis of the CESM2-WACCM6 ensemble reveals year-round upper tropospheric ozone increases from 1995 to 2014, largest at 30 S–40 N during boreal summer. Lower tropospheric ozone increases most strongly in the winter hemisphere, and internal variability leads to trends of opposite sign (ensemble overlaps zero) north of 40 N during boreal summer. This decoupling of ozone trends in the upper and lower troposphere suggests a growing prominence for tropospheric ozone as a greenhouse gas despite regional efforts to abate warm season ground-level ozone.

The enhanced warming of the Arctic, relative to other parts of the Earth, a phenomenon known as Arctic amplification, is one of the most striking features of climate change, and has important climatic impacts for the entire Northern Hemisphere. Several mechanisms are believed to be responsible for Arctic amplification; however, a quantitative understanding of their relative importance is still missing. Here, using ensembles of model integrations, we quantify the contribution of ocean coupling, both its thermodynamic and dynamic components, to Arctic amplification over the 20th and 21st centuries. We show that ocean coupling accounts for ~80% of the amplification by 2100. In particular, we show that thermodynamic coupling is responsible for future amplification and sea-ice loss as it overcomes the effect of dynamic coupling which reduces the amplification and sea-ice loss by ~35%. Our results demonstrate the utility of targeted numerical experiments to quantify the role of specific mechanisms in Arctic amplification, for better constraining climate projections.

Effective climate sensitivity (EffCS), commonly estimated from model simulations with abrupt 4×CO₂for 150 years, has been shown to depend on the CO₂forcing level. To understand this dependency systematically, we performed a series of simulations with a range of abrupt CO₂forcing in two climate models. Our results indicate that normalized EffCS values in these simulations are a non‐monotonic function of the CO₂forcing, decreasing between 3× and 4×CO₂in CESM1‐LE (2× and 3×CO₂in GISS‐E2.1‐G) and increasing at higher CO₂levels. The minimum EffCS value, caused by anomalously negative radiative feedbacks, arises mainly from sea‐surface temperature (SST) relative cooling in the tropical and subtropical North Atlantic. This cooling is associated with the formation of the North Atlantic Warming Hole and Atlantic Meridional Overturning Circulation collapse under CO₂forcing. Our findings imply that understanding changes in North Atlantic SST patterns is important for constraining near‐future and equilibrium global warming.

This study investigates the stratospheric response to Arctic sea ice loss and subsequent near-surface impacts by analyzing 200-member coupled experiments using the Whole Atmosphere Community Climate Model version 6 (WACCM6) with preindustrial, present-day, and future sea ice conditions specified following the protocol of the Polar Amplification Model Intercomparison Project. The stratospheric polar vortex weakens significantly in response to the prescribed sea ice loss, with a larger response to greater ice loss (i.e., future minus preindustrial) than to smaller ice loss (i.e., future minus present-day). Following the weakening of the stratospheric circulation in early boreal winter, the coupled stratosphere–troposphere response to ice loss strengthens in late winter and early spring, projecting onto a negative North Atlantic Oscillation–like pattern in the lower troposphere. To investigate whether the stratospheric response to sea ice loss and subsequent surface impacts depend on the background oceanic state, ensemble members are initialized by a combination of varying phases of Atlantic multidecadal variability (AMV) and interdecadal Pacific variability (IPV). Different AMV and IPV states combined, indeed, can modulate the stratosphere–troposphere responses to sea ice loss, particularly in the North Atlantic sector. Similar experiments with another climate model show that, although strong sea ice forcing also leads to tighter stratosphere–troposphere coupling than weak sea ice forcing, the timing of the response differs from that in WACCM6. Our findings suggest that Arctic sea ice loss can affect the stratospheric circulation and subsequent tropospheric variability on seasonal time scales, but modulation by the background oceanic state and model dependence need to be taken into account.

How do ocean initial states impact historical and future climate projections in Earth system models? To answer this question, we use the 50-member Canadian Earth System Model (CanESM2) large ensemble, in which individual ensemble members are initialized using a combination of different oceanic initial states and atmospheric microperturbations. We show that global ocean heat content anomalies associated with the different ocean initial states, particularly differences in deep ocean heat content due to ocean drift, persist from initialization at year 1950 through the end of the simulations at year 2100. We also find that these anomalies most readily impact surface climate over the Southern Ocean. Differences in ocean initial states affect Southern Ocean surface climate because persistent deep ocean temperature anomalies upwell along sloping isopycnal surfaces that delineate neighboring branches of the upper and lower cells of the global meridional overturning circulation. As a result, up to a quarter of the ensemble variance in Southern Ocean turbulent heat fluxes, heat uptake, and surface temperature trends can be traced to variance in the ocean initial state, notably deep ocean temperature differences of order 0.1 K due to model drift. Such a discernible impact of varying ocean initial conditions on ensemble variance over the Southern Ocean is evident throughout the full 150 simulation years of the ensemble, even though upper ocean temperature anomalies due to varying ocean initial conditions rapidly dissipate over the first two decades of model integration over much of the rest of the globe.