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Arctic amplification (AA)—referring to the enhancement of near-surface air temperature change over the Arctic relative to lower latitudes—is a prominent feature of climate change with important impacts on human and natural systems. In this review, we synthesize current understanding of the underlying physical mechanisms that can give rise to AA. These mechanisms include both local feedbacks and changes in poleward energy transport. Temperature and sea ice-related feedbacks are especially important for AA, since they are significantly more positive over the Arctic than at lower latitudes. Changes in energy transport by the atmosphere and ocean can also contribute to AA. These energy transport changes are tightly coupled with local feedbacks, and thus their respective contributions to AA should not be considered in isolation. It is here emphasized that the feedbacks and energy transport changes that give rise to AA are sensitively dependent on the state of the climate system itself. This implies that changes in the climate state will lead to changes in the strength of AA, with implications for past and future climate change.

Numerous attempts have been made to understand the connection between extreme weather and Arctic amplification (AA), and it is still disputed whether the mechanism is the elongation and deceleration of planetary-scale waves. In this study, we provide further evidence that the Arctic’s rapid warming is influencing extreme precipitation in the Northern Hermisphere based on observation and model outputs, and elucidate the underlying dynamic mechanisms. We find that AA has a significant positive correlation with extreme precipitation, both in the past (1901–2018) and in the future (by 2100). Moreover, observations reveal that, with the enhancement of AA since the mid-1980s, the planetary-scale wave amplitude has increased significantly at 0.66°/decade. This is associated with a negative Northern Hemisphere annular mode and an increased duration of weather patterns, resulting in more extreme precipitation events. Under Shared Socioeconomic Pathways SSP585 scenario, extreme precipitation increases by 8.7% along with wave amplitude increase of 7.9° by 2100.

The 168 year trends of summer (July–September) sea ice area (SIA) variations in six Arctic regions during 1850–2017 are analyzed. SIA has been significantly decreasing in most Arctic regions since 1850. The rate of retreat for the period of 1948–2017 accelerated multi-fold. For the nearly four decades since 1979, most Arctic regions are experiencing the highest reduction rate. Besides the increasing surface air temperature, the key drivers to the accelerated summer Arctic sea ice decline are found to be the combined global warming and the regional Arctic warming exerted simultaneously by the Arctic Oscillation, North Atlantic Oscillation, Atlantic Multidecadal Oscillation and Pacific Decadal Oscillation during the last several decades. The dynamical and thermodynamical warming, driven by the internal variability of the teleconnection patterns, occurred in the last several decades, in particular on the multidecadal timescales. This leads to Arctic amplification that accelerates the positive ice/ocean albedo feedback loop, resulting in accelerating summer sea ice decline.

The rapid polar sea ice retreat and its drivers are challenging and still unresolved questions in climate change research. In particular, the relationship between near-surface wind speed and sea ice extent remains unclear for two main reasons: (1) observed wind speeds over Polar Regions are very sparse, and (2) simulated winds by climate models are dependent on subjective parameterizations of boundary layer stratification, ultimately leading to large uncertainty. Here, we use observation-based data (passive microwave sea ice concentration and six different reanalysis datasets) together with output from 26 climate models (from the CMIP5 archive) to quantify the relationships between near-surface wind speed and sea ice concentration over the past 40 years. We find strong inverse relationships between near-surface wind speed and sea ice concentration that are consistent among the six reanalysis datasets. The poleward wind component is particularly increasing in years of reduced sea ice concentration, which contributes to the enhancement of the atmospheric (surface oceanic) poleward heat flux by up to 24 ± 1% (29 ± 2%) in the Arctic and 37 ± 3% (51 ± 3%) in the Antarctic seas, therefore boosting the impact of polar sea ice loss and contributing to polar amplification of climate warming. In addition, our results show a marginal contribution of the dynamical (pushing/opening/compacting) effects of wind on sea ice compared to the thermodynamic effects which in turn play a lower role than the associated change in local surface Autumn–Winter turbulent and Spring–Summer radiative fluxes. Climate models generally produce similar results but with lower magnitude, and one model even simulates the opposite relationship wind/sea-ice. Given the rapid changes in polar climate and the potential impacts on the mid-latitudes, it is urgent that model developments make use of evidence from satellite observations and reanalysis datasets to reduce uncertainties in the representation of relationships between polar winds and sea ice.

One of the clearest indicators of human-caused climate change is the rapid decline in Arctic sea ice. The summer minimum coverage is now approximately half of its extent only 40 yr ago. Four records in the minimum extent were broken since 2000, the most recent occurring in September 2012. No new records have been set since then, however, owing to an abrupt atmospheric shift during each August/early-September that brought low sea-level pressure, cloudiness, and unfavorable wind conditions for ice reduction. While random variability could be the cause, we identify a recently increased prevalence of a characteristic large-scale atmospheric pattern over the northern hemisphere. This pattern is associated not only with anomalously low pressure over the Arctic during summer, but also with frequent heatwaves over East Asia, Scandinavia, and northern North America, as well as the tendency for a split jet stream over the continents. This jet-stream configuration has been identified as favoring extreme summer weather events in northern mid-latitudes. We propose a mechanism linking these features with diminishing spring snow cover on northern-hemisphere continents that acts as a negative feedback on the loss of Arctic sea ice during summer.

Trends and variations in the amount of cold airmass in the Arctic and the Northern Hemisphere are evaluated for the 60 year period, 1959–2018. The two indicators are (1) polar cold air mass (PCAM), which is the amount of air below a potential temperature threshold, and (2) negative heat content (NHC), which includes a weighting by coldness. Because the metrics of coldness are based on multiple layers in the atmosphere, they provide a more comprehensive framework for assessment of warming than is provided by surface air temperatures alone. The negative trends of PCAM and NHC are stronger (as a % per decade) when the threshold is 245 K rather than 280 K, indicating that the loss of extremely cold air is happening at a faster rate than the loss of moderately cold air. The loss of cold air has accelerated, as the most rapid loss of NHC has occurred in recent decades (1989–2018). The spatial patterns of the trends of PCAM and NHC provide another manifestation of Arctic amplification. Of the various teleconnection indices, the Atlantic Multidecadal Oscillation shows the strongest correlations with the spatially integrated metrics of moderate coldness. Several Pacific indices also correlate significantly with these indicators. However, the amount of extremely cold air mass does not correlate significantly with the indices of internal variability used here. publishedVersion

The Eurasian wheat belt (EWB) spans a region across Eastern Ukraine, Southern Russia, and Northern Kazakhstan; accounting for nearly 15% of global wheat production. We assessed land surface conditions across the EWB during the early growing season (April-May-June; AMJ) leading up to the 2010 Russian heat wave, and over a longer-term period from 2000 to 2010. A substantial reduction in early season values of the normalized difference vegetation index occurred prior to the Russian heat wave, continuing a decadal decline in early season primary production in the region. In 2010, an anomalously cold winter followed by an abrupt shift to a warmer-than-normal early growing season was consistent with a persistently negative phase of the North Atlantic oscillation (NAO). Regression analyses showed that early season vegetation productivity in the EWB is a function of both the winter (December-January-February; DJF) and AMJ phases of the NAO. Land surface anomalies preceding the heat wave were thus consistent with highly negative values of both the DJF NAO and AMJ NAO in 2010.

Despite the on-going global warming, recent winters in Eurasian mid-latitudes were much colder than average. In an attempt to better understand the physical characteristics for cold Eurasian winters, major sources of variability in surface air temperature (SAT) are investigated based on cyclostationary EOF analysis. The two leading modes of SAT variability represent the effect of Arctic amplification (AA) and the Arctic oscillation (AO), respectively. These two modes are distinct in terms of the physical characteristics, including surface energy fluxes and tropospheric circulations, and result in significantly different winter SAT patterns over the Eurasian continent. The AA-related SAT anomalies are dipolar with warm Arctic, centered at the Barents–Kara Seas, and cold East Asia. In contrast, the negative AO-related SAT anomalies are characterized by widespread cold anomalies in Northern Eurasia. Relative importance of the AA and the negative AO contributions to cold Eurasian winters is sensitive to the region of interest.

Recent years (i.e., 2007?2014) have exhibited large declines in snow cover extent (SCE) in the Northern Hemisphere (NH), marked by earlier snowmelt in the springtime. In Northern latitudes, the snow-albedo feedback (SAF) is most pronounced in the spring and may be contributing to these decreasing trends in SCE. Rising surface air temperatures and changes in precipitation patterns could also vary the declining trends in SCE depending on latitude and elevation. Previous trend analyses of NH SCE are extended here to cover the period 1 October 1971 to 30 September 2014 using observed data from the National Oceanic and Atmospheric Administration snow chart climate data record. Trends in snow coverage (significant when p?0.05) with latitude and elevation are investigated using the Mann?Kendall test. Over the 43 year period, strong polar amplification of negative trends in snow cover are observed. The majority of statistically significant negative trends are found in the mid- to high-latitudes, reaching a maximum reduction at 75.5?N. There is also elevation dependence of SCE over time as statistically significant negative trends occur at most elevations, with the strongest observed at 3950 m a.s.l. These significant negative trends exhibited in the mid- to high-latitudes and mid- to high-elevations provide evidence of polar amplification and elevation dependence of trends in snow cover in a warming climate, suggesting a leading role of the SAF on the recent retreat of NH snow cover.

New metrics and evidence are presented that support a linkage between rapid Arctic warming, relative to Northern hemisphere mid-latitudes, and more frequent high-amplitude (wavy) jet-stream configurations that favor persistent weather patterns. We find robust relationships among seasonal and regional patterns of weaker poleward thickness gradients, weaker zonal upper-level winds, and a more meridional flow direction. These results suggest that as the Arctic continues to warm faster than elsewhere in response to rising greenhouse-gas concentrations, the frequency of extreme weather events caused by persistent jet-stream patterns will increase.

There are a number of asymmetries in the surface air temperature response to forcing, including polar amplification and changes to the diurnal and seasonal temperature ranges. We propose that such spatial?temporal signatures of climate change can, in part, be explained by differences in the effective heat capacity of the atmosphere. We have demonstrated that predictions arising from this hypothesis are simultaneously satisfied through the analysis of temperature records from daily to inter-decadal timescales using observational and reanalysis datasets. This mechanism can help to explain why we see the largest temperature trends in the winter months (0.42?K/decade in winter compared to 0.18?K/decade in summer) and why the diurnal temperature range decreases in a warming world, having decreased by ?0.4?K since 1950.

The Earth has warmed in the last century with the most rapid warming occurring near the surface in the Arctic. This Arctic amplification occurs partly because the extra heat is trapped in a thin layer of air near the surface due to the persistent stable-stratification found in this region. The amount of warming depends upon the extent of turbulent mixing in the atmosphere, which is described by the depth of the atmospheric boundary layer (ABL). Global climate models (GCMs) tend to over-estimate the depth of stably-stratified ABLs, and here we show that GCM biases in the ABL depth are strongly correlated with biases in the surface temperature variability. This highlights the need for a better description of the stably-stratified ABL in GCMs in order to constrain the current uncertainty in climate variability and projections of climate change in the surface layer.

Carbon dioxide removal (CDR) from the atmosphere is part of all emission scenarios of the IPCC that limit global warming to below 1.5C. Here, we investigate hysteresis characteristics in 4×pre-industrial atmospheric CO2 concentration scenarios with exponentially increasing and decreasing CO2 using the Bern3D-LPX Earth system model of intermediate complexity. The equilibrium climate sensitivity (ECS) and the rate of CDR are systematically varied. Hysteresis is quantified as the difference in a variable between the up and down pathway at identical cumulative carbon emissions. Typically, hysteresis increases non-linearly with increasing ECS, while its dependency on the CDR rate varies across variables. Large hysteresis is found for global surface air temperature (∆SAT), upper ocean heat content, ocean deoxygenation, and acidification. We find distinct spatial patterns of hysteresis: ∆SAT exhibits strong polar amplification, hysteresis in O2 is both positive and negative depending on the interplay between changes in remineralization of organic matter and ventilation. Due to hysteresis, sustained negative emissions are required to return to and keep a CO2 and warming target, particularly for high climate sensitivities and the large overshoot scenario considered here. Our results suggest, that not emitting carbon in the first place is preferable over carbon dioxide removal, even if technologies would exist to efficiently remove CO2 from the atmosphere and store it away safely.