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Global warming is destabilizing the cryosphere, with consequences for glaciers, permafrost, sea ice and lake ice. Polar lakes have short ice‐free seasons, and small changes in ice cover duration have the potential to provoke alterations to ecosystem structure. However, these lakes are understudied, and the consequences for mixing regimes, thermal structures and biogeochemical processes remain unclear. We measured three annual cycles of dissolved oxygen, temperature and specific conductivity in a lake at ∼83°N to investigate limnological processes and their interannual variability. There were sharp interannual contrasts in lake dynamics, with state shifts in mixing, stratification and oxygen regimes due to air temperature variability and meteorological events. We also observed unusual thermal profiles that were associated with solute gradients. These striking differences underscore the sensitivity of high Arctic lakes to interannual variations in meteorological forcing, and their susceptibility to regime shifts in response to ongoing global change. Plain Language Summary: Lakes are biodiversity refuges, climate regulators and providers of ecosystem services. High Arctic lakes experience brief summer ice‐free periods and their annual dynamics remain largely unexplored despite their location in one of the most rapidly warming regions on Earth. In particular, patterns of thermal structure and oxygen dynamics have rarely been measured. We studied three complete annual cycles in a coastal lake less than 100 km south of the northernmost land on Earth. The observed limnological dynamics highlight the potential for rapid regime shifts in polar lakes and underline their sensitivity to interannual differences in environmental conditions. Key Points: Pronounced shifts in lake oxygen and temperature dynamics occur due to interannual air temperature variation and meteorological episodesDivergent annual trajectories in lake structure and functioning highlight the vulnerability of high Arctic lakes to climate change [ABSTRACT FROM AUTHOR]

We simulated the seasonal temperature evolution in the atmosphere of Antarctica and the Arctic focusing on infrared processes. Contributions by other processes were parametrized and kept fixed throughout the simulations. The model was run for current CO2 and CH4 and for doubled concentrations. For doubling CH4 the warming in Antarctica is restricted to the lowest few hundred meters above the surface while in the Arctic we find a warming in the whole troposphere. We find that the amount of water is the main driver for the differences between both polar regions. When increasing both, CO2 and CH4 from pre‐industrial values to current concentrations, and averaged over the whole troposphere, we find a warming of 0.42 K for the Arctic and a slight cooling of 0.01 K for Antarctica. Our results contribute to the understanding of the lack of warming seen in Antarctica throughout the last decades. Plain Language Summary: In 2015 we have initiated a discussion on a fundamental property of the radiation in the atmosphere over Antarctica: The negative greenhouse effect (Schmithüsen et al., 2015, https://doi.org/10.1002/2015GL066749). A negative greenhouse effect means, the atmosphere emits more radiation to space than it receives from the surface. This results in a cooling somewhere in the Antarctic atmosphere during some months of the year, when increasing CO2. We now simulate how the Antarctic atmospheric temperature responds in all altitude levels to CO2 and CH4 increases, and show this is different from the temperature response in the Arctic. We show for example, that an increase in CH4 cools nearly the whole troposphere, although the response for CH4 is much lower in amplitude than for CO2. We find that the amount of water is the main driver for the differences between both polar regions. Since the amount of water vapor strongly depends on temperature, the colder Antarctic atmosphere responds differently to the Arctic when greenhouse gases increase. Our studies could be one important factor when understanding the lack of warming in Antarctica throughout the last decades. Key Points: We simulate the temperature development in both polar regions in the infrared and find that doubling CO2 and CH4 lead to opposing forcingsThe different amount of water vapor shows to be responsible for the differences in warming/cooling in both polar regionsIn Antarctica doubling CH4 leads to a cooling of almost the whole troposphere, a future increase in H2O could invert this [ABSTRACT FROM AUTHOR]

Since 1980, the Arctic surface has warmed four times faster than the global mean. Enhanced Arctic warming relative to the global average warming is referred to as Arctic Amplification (AA). While AA is a robust feature in climate change simulations, models rarely reproduce the observed magnitude of AA, leading to concerns that models may not accurately capture the response of the Arctic to greenhouse gas emissions. Here, we use CMIP6 data to train a machine learning algorithm to quantify the influence of internal variability in surface air temperature trends over both the Arctic and global domains. Application of this machine learning algorithm to observations reveals that internal variability increases the Arctic warming but slows global warming in recent decades, inflating AA since 1980 by 38% relative to the externally forced AA. Accounting for the role of internal variability reconciles the discrepancy between simulated and observed AA. Plain Language Summary: The Arctic has been warming four times as quickly as the global mean since 1980. This so‐called Arctic Amplification (AA) has unprecedented impacts on Arctic environments and livelihoods. AA is robustly simulated by climate models, but simulations rarely reproduce the observed levels of AA for 1980–2022. This may be due to a model misrepresentation of the Arctic's sensitivity to increasing greenhouse gases. Another possibility is that the large, observed value of AA is inflated by natural fluctuations in the climate system. Here, we use machine learning to quantify the contribution of natural fluctuations to observed AA. We show that natural fluctuations have inflated AA by 38%, and thus reconcile model‐observation differences and suggest that the observed large AA over 1980 to present would not persist into the future. Key Points: Internally generated and externally forced temperature trends over the Arctic and globe can be partitioned using machine learning methodsInternal variability has enhanced Arctic warming while damping global warming over 1980‐2022Accounting for internal variability in observations reconciles discrepancies between simulated and observed Arctic Amplification [ABSTRACT FROM AUTHOR]

Data assimilation of satellite microwave measurements is one of the important keys to improving weather forecasting over the Arctic region. However, the use of surface‐sensitive microwave‐sounding channel measurements for data assimilation or retrieval has been limited, especially during winter, due to the poorly constrained sea ice emissivity. In this study, aiming at more use of those channel measurements in the data assimilation, we propose an explicit method for specifying the surface radiative boundary conditions (namely emissivity and emitting layer temperature of snow and ice). These were explicitly determined with a radiative transfer model for snow and ice and with snow/ice physical parameters (i.e. snow/ice depths and vertical distributions of temperature, density, salinity, and grain size) simulated from the thermodynamically driven snow/ice growth model. We conducted 1D‐Var experiments in order to examine whether this approach can help to use the surface‐sensitive microwave temperature channel measurements over the Arctic sea ice region for data assimilation. Results show that (1) the surface‐sensitive microwave channels can be used in the 1D‐Var retrieval, and (2) the specification of the radiative boundary condition at the surface using the snow/sea ice emission model can significantly improve the atmospheric temperature retrieval, especially in the lower troposphere (500 hPa to surface). The successful retrieval suggests that useful information can be extracted from surface‐sensitive microwave‐sounding channel radiances over sea ice surfaces through the explicit determination of snow/ice emissivity and emitting layer temperature. [ABSTRACT FROM AUTHOR]

Climate change in the Arctic has substantial impacts on human life and ecosystems both within and beyond the Arctic. Our analysis of CMIP6 simulations shows that some climate models project much larger Arctic climate change than other models, including changes in sea ice, ocean mixed layer, air‐sea heat flux, and surface air temperature in wintertime. In particular, dramatic enhancement of Arctic Ocean convection down to a few hundred meters is projected in these models but not in others. Interestingly, these models employ the same ocean model family (NEMO) while the choice of models for the atmosphere and sea ice varies. The magnitude of Arctic climate change is proportional to the strength of the increase in poleward ocean heat transport, which is considerably higher in this group of models. Establishing the plausibility of this group of models with high Arctic climate sensitivity to anthropogenic forcing is imperative given the implied ramifications. Plain Language Summary: Arctic climate is projected to change dramatically in the future based on the latest climate models. However, there is a large discrepancy between these climate models. We find that simulated Arctic climate change tends to be much larger in models using the community ocean model "NEMO" as their ocean component. Future Arctic climate change in winter strongly depends on the strength of the increase in poleward ocean heat transport, which is considerably higher in the NEMO‐family climate models. There are some indications that this group of models can better reproduce the observed winter sea ice decline and mixed layer depth in the Barents Sea in their historical simulations. We suggest that investigating the model physics in the NEMO‐family climate models in comparison with other models may ultimately help to reduce the overall uncertainty in climate change projections. Key Points: Future Arctic climate change in winter strongly depends on the strength of the increase in poleward ocean heat transport (OHT)Arctic climate change in the NEMO‐family climate models is much more pronouncedNEMO‐family climate models have larger increases in poleward OHT [ABSTRACT FROM AUTHOR]

Understanding influence of vegetation on past temperature changes in the Arctic region would help isolate uncertainty and build understanding of its broader climate system, with implications for paleoclimate reconstructions and future climate change. Using an Earth system model EC‐Earth, we conduct a series of simulations to investigate the impact of vegetation‐climate feedback on the Arctic climate during the mid‐Holocene. Results show Arctic greening induced by the warming resulting from stronger orbital forcing, further amplifies the Arctic warming. The increased vegetation contributes 0.33°C of Arctic warming and 0.35 × 106 km2 of Arctic sea ice loss. Increased Arctic vegetation leads to reduced land surface albedo and increased evapotranspiration, both of which cause local warming in spring and summer. The resultant sea ice loss causes warming in the following seasons, with atmospheric circulation anomalies further amplifying the warming. Our results highlight the significant contribution of vegetation‐climate feedback to Arctic climate under natural conditions. Plain Language Summary: Vegetation‐climate feedback is an essential process between the terrestrial biosphere and the atmosphere. Greening of the Arctic can be invoked by increased solar radiation, for example, during the mid‐Holocene (6,000 years ago), or increased greenhouse gas, for example, ongoing global warming. Here we perform simulations of vegetation and climate interactions during the mid‐Holocene and demonstrate the impact of vegetation‐climate feedback on the Arctic climate. We show that compared to the pre‐industrial period (1850 CE), the Arctic region experiences an expansion of vegetation under a warm climate due to increased solar radiation during the mid‐Holocene. The greening leads to reduced land albedo and enhanced evapotranspiration. These changes and resultant sea ice loss, in combination with associated atmospheric circulation changes, further amplify the Arctic warming. These changes alone are responsible for 0.33°C increase in surface air temperature and 0.35 × 106 km2 increase in sea ice loss. Given the facts of observed ongoing Arctic greening in recent decades, our modeling results suggest that the effect of the vegetation‐climate feedback will amplify the future Arctic warming and sea ice loss even more. Key Points: The Earth system model EC‐Earth reproduced the expansion of vegetation in northern high latitudes during the mid‐Holocene compared to the PIThe mid‐Holocene Arctic greening contributes 0.33°C increase in annual Arctic warming and 0.35 × 106 km2 of sea ice lossThe increased evapotranspiration and decreased surface albedo due to the Arctic greening amplify the Arctic warming in the growing season [ABSTRACT FROM AUTHOR]

While the annual mean Arctic Amplification (AA) index varied between two and three during the 1970–2000 period, it reached values exceeding four during the first two decades of the 21st century. The AA did not change in a continuous fashion but rather in two sharp increases around 1986 and 1999. During those steps the mean global surface air temperature trend remained almost constant, while the Arctic trend increased. Although the "best" CMIP6 models reproduce the increasing trend of the AA in 1980s they do not capture the sharply increasing trend of the AA after 1999 including its rapid step‐like increase. We propose that the first sharp AA increase around 1986 is due to external forcing, while the second step close to 1999 is due to internal climate variability, which models cannot reproduce in the observed time. Plain Language Summary: The rate of Arctic warming varied in time, while the rate of global warming was nearly constant over the period 1960–2020. This led to a variable Arctic Amplification (AA) defined as a ratio of the Arctic warming trend to mean global warming trend. In addition, the Arctic experienced sudden changes in the rate of warming with step‐like changes in annual mean Arctic Amplification around the years 1986 and 1999. Climate models do not capture the second observed sharp increase of the AA. We suggest that the first AA increase around 1986 is primarily due to external forcing (increasing concentration of carbon dioxide) while the second sharp increase around 1999 is dominated by internal climate variability which current models cannot capture accurately within the time scale of the physical phenomena. Key Points: Annual mean Arctic Amplification (AA) within the period 1970–2020 changed in steep steps around 1986 and 1999. It reached values over 4.0Even those CMIP6 models best at reproducing the AA did not reproduce the second sudden increase near 1999We conjecture that the first AA sharp increase is due to external forcing, while the second is due to internal climate variability [ABSTRACT FROM AUTHOR]

Arctic sea ice has substantially changed over the past four decades, with a large decrease in sea‐ice area and volume. The exact causes of these changes are not entirely known. In our study, we make use of the Swedish Meteorological and Hydrological Institute Large Ensemble. This ensemble consists of 50 members realized with the EC‐Earth3 global climate model and covers the period 1970‐2100. We apply for the first time the Liang‐Kleeman information flow method to analyze the cause‐effect relationships between Arctic sea ice and its potential drivers. We show that recent and future changes in Arctic sea ice are mainly driven by air and sea‐surface temperatures and ocean heat transport. Conversely, changes in Arctic sea ice also considerably impact temperature and ocean heat transport. Finally, we find a progressive decrease in the influence of sea‐ice area and volume on air temperature and ocean heat transport through the twenty‐first century. Plain Language Summary: The Arctic has been warming at a larger rate than the rest of the world, resulting in a substantial loss of sea ice since the late 1970s. This has had and will continue to have an impact on our climate and societies. The exact causes of the ongoing sea‐ice loss are not entirely known, and understanding them is important in order to better prepare our societies for future climate changes. In our study, we apply a relatively novel approach that quantifies the cause‐effect relationships between Arctic sea ice and its potential drivers. We make use of a large range of model simulations performed with the EC‐Earth3 global climate model covering the period 1970‐2100. We find that air temperature, sea‐surface temperature, and the transport of heat by the ocean are important drivers of the ongoing and future retreat of Arctic sea ice. Conversely, changes in Arctic sea ice also affect the three former quantities. Our study demonstrates the performance of causal inference methods in the quest for a better understanding of relationships between climate variables. The geophysical and climate communities could greatly benefit from using these methods more intensively. Key Points: The Liang‐Kleeman rate of information transfer allows quantification of the directional dependence between Arctic sea ice and its driversRecent and future changes in Arctic sea ice are mainly driven by air and sea‐surface temperatures and ocean heat transportThe influence of Arctic sea ice on air temperature and ocean heat transport progressively decreases through the twenty‐first century [ABSTRACT FROM AUTHOR]

Studies have indicated that marine heatwaves (MHWs) have had severe impacts on the marine ecosystem in the Pacific, Atlantic, and Indian Oceans, but there have been few studies focused on MHWs in the Arctic. On the other hand, amplified rapid warming in the Arctic region makes it a hotspot strategically and economically worldwide. In this study, we documented that the average intensity of MHWs in the Arctic was comparable with that in the other regions of the global oceans. The annual intensity, frequency, duration, and areal coverage of MHWs have increased significantly in recent decades. The increase of the annual duration is mainly owing to the postponed end time, thus the prolonged periods, of the MHW seasons. Our analysis indicates that the increasing trends of the annual intensity, frequency, duration, and areal coverage in the Arctic are closely associated with the increasing surface air temperature and decreasing sea‐ice concentration under the global warming environment. These features are robust across three different sea surface temperature (SST) products and using different MHW criteria. Plain Language Summary: Events of extremely warm waters in the oceans are known as marine heatwaves (MHWs). Past MHW research has used sea surface temperature (SST) to diagnose MHWs and has focused on the tropical and subtropical oceans. The questions we address here are: (a) Are there any MHW events in the Arctic region where SSTs are generally low? and (b) Are the MHWs weaker or stronger in the Arctic than in the other oceans? Our study indicates that: (a) MHWs do exist in the Arctic, (b) their strengths increase with time, and (c) they are stronger than those in the other oceans in the most recent decades. These MHWs may have a strong impact on the Arctic bio‐ecosystem due to their low heat tolerance since the seasonal variation of SST in the Arctic is small. Key Points: The average marine heatwaves (MHWs) in the Arctic are as strong as in the other ocean basins in 1982–2020The annual intensity are stronger in 2000–2020 than in 1982–2000, which is consistent with changes in air temperature, sea‐ice, and cloudThe increase of annual duration is largely associated with the postponed end time of the MHW seasons [ABSTRACT FROM AUTHOR]

Whether sea‐ice loss or lapse‐rate feedback dominates the Arctic amplification (AA) remains an open question. Analysis of data sets based upon observations reveals a 1.11 K per decade surface warming trend in the Arctic (70°–90°N) during 1979–2020 cold season (October–February) that is five times higher than the corresponding global mean. Based on surface energy budget analysis, we show that the largest contribution (∼82%) to this cold season warming trend is attributed to changes in clear‐sky downward longwave radiation. In contrast to that in Arctic summer and over tropics, a reduction in lower‐tropospheric inversions plays a unique role in explaining the reduction of the downward longwave radiation associated with atmospheric nonuniform temperature and corresponding moisture changes. Our analyses also suggest that Arctic lower‐tropospheric stability should be considered in conjunction with sea‐ice decline during the preceding warm season to explain AA. Plain Language Summary: Observations and climate models have consistently shown a stronger surface warming in the Arctic than the global mean, a.k.a. Arctic amplification (AA), which has a strong asymmetry between the cold season and warm season. Previous studies suggested that key contributors to AA are the positive surface‐albedo feedback and lapse‐rate feedback. However, the lapse‐rate feedback itself depends on temperature profiles and sea‐ice loss. Whether sea‐ice loss or lapse‐rate feedback dominates AA remains an open question. Here, by analyzing the latest generation of observationally‐based reanalysis data (1979–2020), we present a unique role of lower‐tropospheric temperature inversion changes in representing the contribution of vertically inhomogeneous atmospheric temperature and associated moisture changes to clear‐sky downward longwave radiation during the cold season. This unique role is not found either in the tropics or during Arctic summertime. We further link the inversion during the cold season to sea‐ice loss during the preceding warm season. These results reinforce previous findings not only that lapse‐rate feedback and sea‐ice loss play a key role in AA but also that lapse‐rate feedback in the cold season is likely a consequence of sea‐ice albedo feedback during the preceding warm season. Key Points: An increase in clear‐sky downward longwave radiation (rldsclr) explains 82% of the recent cold season Arctic surface warming trendReduced low inversion largely explains the Arctic rldsclr reduction due to vertical nonuniform temperature and related moisture changesLapse‐rate feedback in the Arctic cold season is likely a consequence of sea‐ice albedo feedback during the preceding warm season [ABSTRACT FROM AUTHOR]

Whether sea‐ice loss or lapse‐rate feedback dominates the Arctic amplification (AA) remains an open question. Analysis of data sets based upon observations reveals a 1.11 K per decade surface warming trend in the Arctic (70°–90°N) during 1979–2020 cold season (October–February) that is five times higher than the corresponding global mean. Based on surface energy budget analysis, we show that the largest contribution (∼82%) to this cold season warming trend is attributed to changes in clear‐sky downward longwave radiation. In contrast to that in Arctic summer and over tropics, a reduction in lower‐tropospheric inversions plays a unique role in explaining the reduction of the downward longwave radiation associated with atmospheric nonuniform temperature and corresponding moisture changes. Our analyses also suggest that Arctic lower‐tropospheric stability should be considered in conjunction with sea‐ice decline during the preceding warm season to explain AA. Plain Language Summary: Observations and climate models have consistently shown a stronger surface warming in the Arctic than the global mean, a.k.a. Arctic amplification (AA), which has a strong asymmetry between the cold season and warm season. Previous studies suggested that key contributors to AA are the positive surface‐albedo feedback and lapse‐rate feedback. However, the lapse‐rate feedback itself depends on temperature profiles and sea‐ice loss. Whether sea‐ice loss or lapse‐rate feedback dominates AA remains an open question. Here, by analyzing the latest generation of observationally‐based reanalysis data (1979–2020), we present a unique role of lower‐tropospheric temperature inversion changes in representing the contribution of vertically inhomogeneous atmospheric temperature and associated moisture changes to clear‐sky downward longwave radiation during the cold season. This unique role is not found either in the tropics or during Arctic summertime. We further link the inversion during the cold season to sea‐ice loss during the preceding warm season. These results reinforce previous findings not only that lapse‐rate feedback and sea‐ice loss play a key role in AA but also that lapse‐rate feedback in the cold season is likely a consequence of sea‐ice albedo feedback during the preceding warm season. Key Points: An increase in clear‐sky downward longwave radiation (rldsclr) explains 82% of the recent cold season Arctic surface warming trendReduced low inversion largely explains the Arctic rldsclr reduction due to vertical nonuniform temperature and related moisture changesLapse‐rate feedback in the Arctic cold season is likely a consequence of sea‐ice albedo feedback during the preceding warm season [ABSTRACT FROM AUTHOR]

A model study shows that the decline of Arctic sea ice volume (SIV) slows down during 2007–2020 with increasingly warm atmospheric and oceanic conditions. The slowdown of the SIV decline is because the decrease in ice export from the Arctic exceeds the decrease in net ice production within the Arctic. The relatively strong decrease in ice export occurs when the increase in ice motion is lower than the decrease in SIV. The relatively weak decrease in net ice production is due to strong increases in ice growth as thinner ice grows faster than thicker ice under freezing conditions. The ice growth increases are closely correlated with and benefit from increases in open water creation caused by enhanced ice divergence and shear as thinner ice is easier to deform. Plain Language Summary: Results from the Pan‐arctic Ice‐Ocean Modeling and Assimilation System (PIOMAS) show significant decline of Arctic sea ice volume (SIV) in the past decades. However, the SIV decline is slowing down during 2007–2020 with increasingly higher air and ocean temperatures, which is in line with satellite CryoSat‐2 observations of largely stabilized SIV since 2011. The slowdown of the SIV decline is because of relatively strong decreases in ice export from the Arctic and increases in ice growth in the Arctic. The relatively strong increase in ice growth in 2007–2020 is because thinner and less compact ice, which is the norm in recent years, has much higher growth rates than thicker ice under freezing conditions. Thinner ice also moves faster and deforms more, which tends to create more open water to stimulate ice growth in 2007–2020. Thus, the ice export and growth processes play a role in slowing down the SIV decline in recent years and may continue to play that role in the future. Key Points: The decline of Arctic sea ice volume has slowed down in recent years under increasingly warm atmospheric and oceanic conditionsThe slowdown is due to weak ice export and strong ice growth which serve as a negative feedback to retard the ice volume declineIncreases in dynamic open water creation because of an accelerating thin ice cover play a role in stimulating ice growth in recent years [ABSTRACT FROM AUTHOR]

The El Niño Southern Oscillation (ENSO) is a well‐known modulator of global climate and is correlated with observed temperature variations over the Barents‐Kara Sea (BKS). However, the origins and causality of this observed correlation are unclear. Here, we show that historical climate model simulations, on average, fail to reproduce the observed ENSO‐BKS correlation. However, individual realizations do show a relationship as observed. We find that the internal variability of BKS sea ice is the main factor between realizations that reproduce the ENSO‐BKS correlation and those that do not. Furthermore, we find that atmospheric model simulations prescribed with observed sea ice variability reproduce the ENSO‐BKS correlation. We conclude that ENSO‐correlated winter BKS temperature variations are dependent on coincidental sea ice changes. Plain Language Summary: Naturally occurring changes in the tropical Pacific Ocean, for example, the El Niño Southern Oscillation or ENSO, are known to affect weather and climate all across the planet. The influence of ENSO on Europe and North America is relatively well known but if and how ENSO affects Arctic weather and climate is less clear. In this study, we identify a correlation between ENSO and winter temperatures in the Arctic focusing specifically on the Barents and Kara Seas. We then examine a large collection of climate model experiments to see if they reproduce the observed correlation. We find that models, on average, do not. However, a small selection of the model experiments do show a correlation as large or larger than observed. The experiments that do reproduce the observed correlation are those that, by chance, have sea ice variations similar to observed; or are experiments in which sea ice is constrained to perfectly match observations. We conclude that Barents and Kara Sea winter temperature variations are primarily governed by local sea ice changes, which by coincidence, may on occasion correlate with ENSO. Key Points: Observed near‐surface air temperature variations over the Barents‐Kara Sea (BKS) are correlated with El Nino Southern Oscillation (ENSO)Models can reproduce the ENSO‐BKS correlation, but only in realizations that have similar or identical sea ice variations as observedSea ice variations are the proximal cause of ENSO‐correlated BKS temperature changes and may be a manifestation of internal variability [ABSTRACT FROM AUTHOR]

During the early 20th century, the Arctic experienced a period of remarkable warming, often called the early 20th century warming (ETCW). However, the degree of the response to external climate forcing on the Arctic surface air temperature is not well understood. Climate simulations using a state‐of‐the‐art climate model of Meteorological Research Institute (MRI‐ESM2.0) and multimodel analyses were conducted to better understand ETCW. The MRI‐ESM2.0 historical simulations successfully reproduced the observed ETCW and the corresponding decreases in sea ice extent. Detection and attribution experiments using MRI‐ESM2.0 suggest that internal climate variability and external natural forcings by solar and volcanic activities had major influences on the model‐simulated ETCW, rather than external anthropogenic forcings. Multimodel analyses indicate that the Arctic warming trend during 1911–1940 induced by natural forcings is comparable to the unforced multidecadal internal variability, suggesting major contributions of the internal dynamics and natural forcings to ETCW. Plain Language Summary: Instrumental records show that there was significant warming in the Arctic during the first half of the 20th century, known as the early 20th century warming (ETCW). Climate simulations using a state‐of‐the‐art climate model of Meteorological Research Institute (MRI‐ESM2.0) suggest that external natural forcings, i.e., long‐lasting quiet volcanic activity and increased solar activity, influenced the model‐simulated ETCW and associated sea ice decrease. Multimodel analyses indicate the robustness of the MRI‐ESM2.0 results and suggest that the climatic response of Arctic surface air temperature to external natural forcings in the ETCW period is comparable to the unforced multidecadal internal variability of the models, suggesting a major contribution of unforced multidecadal internal variability and natural forcings to ETCW. Key Points: Climate model MRI‐ESM2.0 reproduces the Arctic surface air temperature rising and associated sea ice loss observed in the early 20th centuryMRI‐ESM2.0 results indicate that the natural forcings and the internal variability are main contributors to Arctic warming during 1920–1940Multimodel analyses suggest the Arctic warming response to natural forcings in 1911–1940 is comparable to the unforced internal variability [ABSTRACT FROM AUTHOR]

Recent studies have used satellite data to estimate the response of top‐of‐atmosphere (TOA) radiative fluxes to surface temperature changes in the Arctic. The satellite‐observed radiative response is indicative of Arctic climate sensitivity that determines future Arctic warming. However, it remains ambiguous whether the satellite‐observed radiative response is invariable because the time period covered by satellite data reflects a rapidly changing transient Arctic climate state with considerable sea ice loss. Using NASA's Clouds and Earth's Radiant Energy System (CERES) observations from 2000 to 2018, this study evaluates the invariability of the radiative response by comparing the radiative response of the high sea ice concentration (SIC) period to that of the low SIC period. The results show that the net radiative response remains approximately unchanged regardless of the SIC (−0.19 ± 0.44 and 0.15 ± 0.16 W m−2 K−1 for high and low SIC periods, respectively). In addition, seven of the 11 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) demonstrated that the modeled radiative responses are stable. The ERA‐interim reanalysis estimates show that regionally confined changes in individual radiative feedbacks such as albedo, lapse rate, water vapor, and clouds do not vary considerably. Consequently, we infer that the radiative response in the Arctic may remain stable even under rapid Arctic climate change. Hence, the Arctic climate sensitivity can be quantified with present satellite observations. Key Points: Satellite‐observed radiative response to surface air temperature change remains unchanged under sea ice retreat over the Arctic regionRegionally confined changes in individual radiative feedbacks cannot considerably change the radiative response in the ArcticThe majority of the climate models demonstrated that the Arctic radiative response is insensitive to sea ice loss in the near future [ABSTRACT FROM AUTHOR]

The effect of future Arctic amplification (AA) on the extratropical atmospheric circulation remains unclear in modeling studies. Using a collection of coordinated atmospheric and coupled global climate model perturbation experiments, we find an emergent relationship between the high‐latitude 1,000–500 hPa thickness response and an enhancement of the Siberian High in winter. This wave number‐1‐like sea level pressure anomaly pattern is linked to an equatorward shift of the eddy‐driven jet and a dynamical cooling response in eastern Asia. Additional simulations, where AA is imposed directly into the model domain by nudging, demonstrate how the sea ice forcing is insufficient by itself to capture the vertical extent of the warming and by extension the amplitude of the response in the Siberian High. This study demonstrates the importance of the vertical extent of the tropospheric warming over the polar cap in revealing the "warm Arctic, cold Siberia" anomaly pattern in future projections. Plain Language Summary: Surface air temperature averaged within the Arctic Circle is rising more than twice as fast as the rate of the globally averaged temperature. This is known as "Arctic amplification" and is the result of numerous feedbacks in the Earth system. This warming is not restricted to the surface, as the temperature is also increasing at least to the middle troposphere in the Arctic. The effects of this warming on weather patterns in the midlatitudes remain uncertain in observations and model simulations. In this study, we conduct a series of climate model experiments to better understand how the vertical extent of warming in the Arctic atmosphere connects to a strengthening of the Siberian High in boreal winter. This high‐pressure response leads to colder air temperatures in eastern Asia through advection. We find that climate models prescribed with only Arctic sea ice loss do not fully capture the vertical extent of warming in the atmosphere, and thus underestimate the linkage between projected Arctic amplification and Eurasian climate. Key Points: Climate models forced only by sea ice anomalies do not capture the vertical extent of Arctic warming during winterIncrease in thickness of the winter 1,000–500 hPa layer is linked to a strengthening of the Siberian High and cold anomalies in eastern AsiaRole of the stratosphere is unclear due to large internal variability at future global warming of 2° C above preindustrial levels [ABSTRACT FROM AUTHOR]

Globally, 2017 was one of the three warmest years on record at the surface of the Earth, despite neutral or weak La Niña conditions. Warmth was widespread in the climate system, with ocean heat and atmospheric temperatures also among the top three years. Arctic and Antarctic sea ice extents were below the long‐term average, and a number of months had record low extents. In the UK and Europe there were a number of unusual weather events, and high spring and summer temperatures affected areas of Europe, North Africa and the Middle East. We summarise aspects of global and regional climate in 2017. [ABSTRACT FROM AUTHOR]