Pronounced changes in the Arctic environment add a new potential driver of anomalous weather patterns in midlatitudes that affect billions of people. Recent studies of these Arctic/midlatitude weather linkages, however, state inconsistent conclusions. A source of uncertainty arises from the chaotic nature of the atmosphere. Thermodynamic forcing by a rapidly warming Arctic contributes to weather events through changing surface heat fluxes and large-scale temperature and pressure gradients. But internal shifts in atmospheric dynamics—the variability of the location, strength, and character of the jet stream, blocking, and stratospheric polar vortex (SPV)—obscure the direct causes and effects. It is important to understand these associated processes to differentiate Arctic-forced variability from natural variability. For example in early winter, reduced Barents/Kara Seas sea-ice coverage may reinforce existing atmospheric teleconnections between the North Atlantic/Arctic and central Asia, and affect downstream weather in East Asia. Reduced sea ice in the Chukchi Sea can amplify atmospheric ridging of high pressure near Alaska, influencing downstream weather across North America. In late winter southward displacement of the SPV, coupled to the troposphere, leads to weather extremes in Eurasia and North America. Combined tropical and sea ice conditions can modulate the variability of the SPV. Observational evidence for Arctic/midlatitude weather linkages continues to accumulate, along with understanding of connections with pre-existing climate states. Relative to natural atmospheric variability, sea-ice loss alone has played a secondary role in Arctic/midlatitude weather linkages; the full influence of Arctic amplification remains uncertain.

There were two major multiyear, Arctic-wide (60°–90°N) warm anomalies (>0.7°C) in land surface air temperature (LSAT) during the twentieth century, between 1920 and 1950 and again at the end of the century after 1979. Reproducing this decadal and longer variability in coupled general circulation models (GCMs) is a critical test for understanding processes in the Arctic climate system and increasing the confidence in the Intergovernmental Panel on Climate Change (IPCC) model projections. This study evaluated 63 realizations generated by 20 coupled GCMs made available for the IPCC Fourth Assessment for their twentieth-century climate in coupled models (20C3M) and corresponding control runs (PIcntrl). Warm anomalies in the Arctic during the last two decades are reproduced by all ensemble members, with considerable variability in amplitude among models. In contrast, only eight models generated warm anomaly amplitude of at least two-thirds of the observed midcentury warm event in at least one realization, but not its timing. The durations of the midcentury warm events in all the models are decadal, while that of the observed was interdecadal. The variance of the control runs in nine models was comparable with the variance in the observations. The random timing of midcentury warm anomalies in 20C3M simulations and the similar variance of the control runs in about half of the models suggest that the observed midcentury warm period is consistent with intrinsic climate variability. Five models were considered to compare somewhat favorably to Arctic observations in both matching the variance of the observed temperature record in their control runs and representing the decadal mean temperature anomaly amplitude in their 20C3M simulations. Seven additional models could be given further consideration. Results support selecting a subset of GCMs when making predictions for future climate by using performance criteria based on comparison with retrospective data.

Public attention has recently focused on high-impact extreme weather events in midlatitudes that originate in the sub-Arctic. We investigate movements of the stratospheric polar vortex (SPV) and related changes in lower atmospheric circulation during the February-March 2018 “Beast from the East” cold winter event that dramatically affected much of Europe and north-central North America. This study demonstrates that the movement of the SPV is a key linkage in late winter subarctic and northern midlatitude extreme weather events. February–March 2018 saw two types of subarctic-midlatitude weather connections. In the first type, the SPV was displaced from the pole to lower latitudes over North America in February and then was found over northern Siberia in March. Mid-February and mid-March are examples of persistent near vertically aligned geopotential height structures of the atmospheric circulation. These structures over North America and Eurasia advected cold Arctic air southward. The second type of cold surface event was associated with a weak regional SPV and a sudden stratospheric warming event over Europe during the second half of February. These late winter linkage events that arise through dynamic instabilities of the SPV are more common in the last decade, but the potential role of enhanced Arctic amplification is uncertain.

The prospect of an ice-free Arctic in our near future due to the rapid and accelerated Arctic sea ice decline has brought about the urgent need for reliable projections of the first ice-free Arctic summer year (FIASY). Together with up-to-date observations and characterizations of Arctic ice state, they are essential to business strategic planning, climate adaptation, and risk mitigation. In this study, the monthly Arctic sea ice extents from 12 global climate models are utilized to obtain projected FIASYs and their dependency on different emission scenarios, as well as to examine the nature of the ice retreat projections. The average value of model-projected FIASYs is 2054/2042, with a spread of 74/42 years for the medium/high emission scenarios, respectively. The earliest FIASY is projected to occur in year 2023, which may not be realistic, for both scenarios. The sensitivity of individual climate models to scenarios in projecting FIASYs is very model-dependent. The nature of model-projected Arctic sea ice coverage changes is shown to be primarily linear. FIASY values predicted by six commonly used statistical models that were curve-fitted with the first 30 years of climate projections (2006–2035), on other hand, show a preferred range of 2030–2040, with a distinct peak at 2034 for both scenarios, which is more comparable with those from previous studies.

It is widely accepted that Arctic amplification (AA)—enhanced Arctic warming relative to global warming—will increasingly moderate cold-air outbreaks (CAOs) to the midlatitudes. Yet, some recent studies also argue that AA over the last three decades to the rest of the present century may contribute to more frequent severe winter weather including disruptive cold spells. To prepare society for future extremes, it is necessary to resolve whether AA and severe midlatitude winter weather are coincidental or physically linked. Severe winter weather events in the northern continents are often related to a range of stratospheric polar vortex (SPV) configurations and atmospheric blocking, but these dynamical drivers are complex and still not fully understood. Here we review recent research advances and paradigms including a nonlinear theory of atmospheric blocking that helps to explain the location, timing and duration of AA/midlatitude weather connections, studies of the polar vortex’s zonal asymmetric and intra-seasonal variations, its southward migration over continents, and its surface impacts. We highlight novel understanding of SPV variability—polar vortex stretching and a stratosphere–troposphere oscillation—that have remained mostly hidden in the predominant research focus on sudden stratospheric warmings. A physical explanation of the two-way vertical coupling process between the polar vortex and blocking highs, taking into account local surface conditions, remains elusive. We conclude that evidence exists for tropical preconditioning of Arctic-midlatitude climate linkages. Recent research using very large-ensemble climate modelling provides an emerging opportunity to robustly quantify internal atmospheric variability when studying the potential response of midlatitude CAOs to AA and sea-ice loss.