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Over the past decades, Arctic climate has exhibited significant changes characterized by strong pan-Arctic warming and a large-scale wind shift trending toward an anticyclonic anomaly centered over Greenland and the Arctic Ocean. Recent work has suggested that this wind change is able to warm the Arctic atmosphere and melt sea ice through dynamically driven warming, moistening, and ice drift effects. However, previous examination of this linkage lacks a capability to fully consider the complex nature of the sea ice response to the wind change. In this study, we perform a more rigorous test of this idea by using a coupled high-resolution modeling framework with observed winds nudged over the Arctic that allows for a comparison of these wind-induced effects with observations and simulated effects forced by anthropogenic forcing. Our nudging simulation can well capture observed variability of atmospheric temperature, sea ice, and the radiation balance during the Arctic summer and appears to simulate around 30% of Arctic warming and sea ice melting over the whole period (1979–2020) and more than 50% over the period 2000–12, which is the fastest Arctic warming decade in the satellite era. In particular, in the summer of 2020, a similar wind pattern reemerged to induce the second-lowest sea ice extent since 1979, suggesting that large-scale wind changes in the Arctic are essential in shaping Arctic climate on interannual and interdecadal time scales and may be critical to determine Arctic climate variability in the coming decades. Significance Statement: This work conducts a set of new CESM1 nudging simulations to quantify the impact of the observed evolution of large-scale high-latitude atmospheric winds on Arctic climate variability over the past four decades. Variations in climate parameters, including sea ice, radiation, and atmospheric temperatures are well replicated in the model when observed winds are imposed in the Arctic. By investigating simulated sea ice melting processes in the simulation, we illustrate and estimate how large-scale winds in the Arctic help melt sea ice in summer. The nudging method has the potential to make Arctic climate attribution more tangible and to unravel the important physical processes underlying recent abrupt climate change in the Arctic. [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]

A global problem facing humanity today is the changing planetary climate. The Earth's northern regions play an important role in processes that affect the environment on a global scale and serve as indicators of global natural changes, especially climate change. The currently observed climate changes in the Arctic, such as rising air temperature, shrinking ice cover, increased river runoff, and permafrost degradation, have already shown that the Arctic is experiencing the greatest changes in comparison with other regions of the Earth. The response of the Arctic to all climatic change occurring on the planet is the strongest. The strong and rapid changes in the Arctic climate in recent years require comprehensive studies of their causes with assessment of the role of natural and anthropogenic factors. This paper analyzes the temporal changes in a number of Arctic climate indicators based on its main components (air temperature and oscillations in the atmospheric circulation, ocean waters, and ice cover extent) at time intervals of the 20th century, the period of anthropogenic impact on the climate, the last 2000 years, and the Holocene period, as well as the role of solar activity (cyclical changes and insolation) in climate change on the Earth. Trends in the variation in natural climate indicators are traced. Problems of prime importance for an understanding of the nature of current climate change and the main physical processes responsible for these changes are discussed. The goal of the study is to summarize the current understanding of Arctic climate change. [ABSTRACT FROM AUTHOR]

Marine cold‐air outbreaks (MCAOs) create conditions for hazardous maritime mesocyclones (polar lows) posing risks to marine infrastructure. For marine management, skilful predictions of MCAOs would be highly beneficial. For this reason, we investigate (a) the ability of a seasonal prediction system to predict MCAOs and (b) the possibilities to improve predictions through large‐scale causal drivers. Our results show that the seasonal ensemble predictions have high prediction skill for MCAOs over the Nordic Seas for about 20 days starting from November initial conditions. To study causal drivers of MCAOs, we utilize a causal effect network approach applied to the atmospheric reanalysis ERA‐Interim and identify local sea surface temperature and atmospheric circulation patterns over Scandinavia as valuable predictors. Prediction skill for MCAOs is further improved up to 40 days by including MCAO predictors in the analysis. [ABSTRACT FROM AUTHOR]

Daily surface air temperature from ERA-Interim reanalysis is used to study the cold and warm anomalies observed in December–February 1979–2017 over three regions of North Eurasia. The air temperature anomalies were selected that exceeded the standard deviation in the absolute magnitude and persisted 7 days and longer. The anomalies were analyzed in terms of the frequency of occurrence, strength, persistence, extension and the integral index of severity. The reproducibility of the statistical characteristics of the anomalies was also considered using ensemble simulations with the MGO atmospheric general circulation model and prescribed boundary conditions from observation for the period 1979–2017. The observed and simulated trends of the anomaly characteristics over the whole period and their link to the surface air temperature anomalies in the Barents and Kara seas were also discussed. It was shown that the most significant cold anomalies have been observed in Western Siberia since the beginning of the 21st century, when positive winter temperature anomalies were recorded over the Barents and Kara seas. [ABSTRACT FROM AUTHOR]

A coordinated set of large ensemble atmosphere‐only simulations is used to investigate the impacts of observed Arctic sea ice‐driven variability (SIDV) on the atmospheric circulation during 1979–2014. The experimental protocol permits separating Arctic SIDV from internal variability and variability driven by other forcings including sea surface temperature and greenhouse gases. The geographic pattern of SIDV is consistent across seven participating models, but its magnitude strongly depends on ensemble size. Based on 130 members, winter SIDV is ~0.18 hPa2 for Arctic‐averaged sea level pressure (~1.5% of the total variance), and ~0.35 K2 for surface air temperature (~21%) at interannual and longer timescales. The results suggest that more than 100 (40) members are needed to separate Arctic SIDV from other components for dynamical (thermodynamical) variables, and insufficient ensemble size always leads to overestimation of SIDV. Nevertheless, SIDV is 0.75–1.5 times as large as the variability driven by other forcings over northern Eurasia and Arctic. Plain Language Summary: Changing Arctic sea ice conditions since the late 1970s have exerted profound impacts on environment and ecosystem at the high latitudes and have been suggested to affect midlatitude weather and climate, although this topic has been controversial. In order to improve our understanding on how Arctic sea ice changes influence local and remote weather and climate, a coordinated set of experiments has been performed using various state‐of‐the‐art atmosphere‐only models to study the linkages between the Arctic climate change and lower latitudes. This study uses seven models following a common experimental protocol to investigate the atmospheric circulation changes forced by Arctic sea ice variability. The protocol allows the Arctic sea ice‐driven variability (SIDV) to be singled out. In boreal winter, the Arctic SIDV is ~0.18 hPa2 and accounts for only ~1.5% of the total variance for sea level pressure, while it is ~0.35 K2 and accounts for ~21% for surface air temperature. The results also suggest that using insufficient ensembles always leads to an overestimation of SIDV, and more than 100 and 40 ensemble members are needed for sea level pressure and surface air temperature within the Arctic, respectively, to separate the SIDV from the variability due to other factors, primarily the atmospheric internal variability. Key Points: Arctic sea ice variations drive ~1.5% of boreal winter Arctic SLP variance during 1979–2014 in coordinated 130‐member AGCM experimentsAn accurate quantification of the impacts of Arctic sea ice‐driven SLP variability requires an ensemble size greater than 100 membersInsufficient ensemble size always leads to an overestimation of the Arctic sea ice‐driven variance within and outside Arctic [ABSTRACT FROM AUTHOR]