Arctic Sea Ice Loss Research Articles

Stronger Arctic amplification from ozone-depleting substances than from carbon dioxide

Arctic amplification (AA)—the greater warming of the Arctic near-surface temperature relative to its global mean value—is a prominent feature of the climate response to increasing greenhouse gases. Recent work has revealed the importance of ozone-depleting substances (ODS) in contributing to Arctic warming and sea-ice loss. Here, using ensembles of climate model integrations, we expand on that work and directly contrast Arctic warming from ODS to that from carbon dioxide (CO2), over the 1955–2005 period when ODS loading peaked. We find that the Arctic warming and sea-ice loss from ODS are slightly more than half (52%–59%) those from CO2. We further show that the strength of AA for ODS is 1.44 times larger than that for CO2, and that this mainly stems from more positive Planck, albedo, lapse-rate, and cloud feedbacks. Our results suggest that AA would be considerably stronger than presently observed had the Montreal Protocol not been signed.

The Predictability of Ocean Environments that Contributed to the 2020/21 Extreme Cold Events in China: 2020/21 La Niña and 2020 Arctic Sea Ice Loss

Several consecutive extreme cold events impacted China during the first half of winter 2020/21, breaking the low-temperature records in many cities. How to make accurate climate predictions of extreme cold events is still an urgent issue. The synergistic effect of the warm Arctic and cold tropical Pacific has been demonstrated to intensify the intrusions of cold air from polar regions into middle-high latitudes, further influencing the cold conditions in China. However, climate models failed to predict these two ocean environments at expected lead times. Most seasonal climate forecasts only predicted the 2020/21 La Niña after the signal had already become apparent and significantly underestimated the observed Arctic sea ice loss in autumn 2020 with a 1–2 month advancement. In this work, the corresponding physical factors that may help improve the accuracy of seasonal climate predictions are further explored. For the 2020/21 La Niña prediction, through sensitivity experiments involving different atmospheric–oceanic initial conditions, the predominant southeasterly wind anomalies over the equatorial Pacific in spring of 2020 are diagnosed to play an irreplaceable role in triggering this cold event. A reasonable inclusion of atmospheric surface winds into the initialization will help the model predict La Niña development from the early spring of 2020. For predicting the Arctic sea ice loss in autumn 2020, an anomalously cyclonic circulation from the central Arctic Ocean predicted by the model, which swept abnormally hot air over Siberia into the Arctic Ocean, is recognized as an important contributor to successfully predicting the minimum Arctic sea ice extent.

New Mechanisms of Polar Amplification Triggered by the Arctic Sea Ice Loss

The effect of positive feedbacks is associated with the phenomenon of the so-called Polar amplification, due to which an increase of the surface air temperature in the Arctic in recent decades was approximately 2.5 times higher than in the other latitudinal zones. Reduction of the Arctic sea ice acted as a “trigger” that provided an intensification of feedbacks, which were either not manifested at all or were ineffective under the conditions of the prevalence of thick consolidated ice. In addition to the well-known and described in the literature feedbacks that are acting in high latitudes, two new mechanisms are introduced: “seasonal memory” in the ice cover properties and “atlantifi- cation”. It has been shown that these mechanisms contribute to the further reduction of the Arctic sea ice. In the East-Atlantic sector of the Arctic Ocean both mechanisms operate in concert, enhancing the end result. According to climate scenarios, Arctic warming is projected to intensify in the coming decades, causing changes in various environments. It can be expected that an important role in this will be played by positive feedbacks that provide the Polar amplification in modern conditions, when the Arctic climate system is in an unstable transitional state.

Arctic Sea Ice Loss and Eurasian Cooling in Winter 2020-21

Arctic Sea Ice Loss and Eurasian Cooling in Winter 2020-21

Recognising our community as we head towards JEB's centenary in 2023.

Recognising our community as we head towards JEB's centenary in 2023.

Nordic Seas Heat Loss, Atlantic Inflow, and Arctic Sea Ice Cover Over the Last Century

AbstractPoleward ocean heat transport is a key process in the earth system. We detail and review the northward Atlantic Water (AW) flow, Arctic Ocean heat transport, and heat loss to the atmosphere since 1900 in relation to sea ice cover. Our synthesis is largely based on a sea ice‐ocean model forced by a reanalysis atmosphere (1900–2018) corroborated by a comprehensive hydrographic database (1950–), AW inflow observations (1996–), and other long‐term time series of sea ice extent (1900–), glacier retreat (1984–), and Barents Sea hydrography (1900–). The Arctic Ocean, including the Nordic and Barents Seas, has warmed since the 1970s. This warming is congruent with increased ocean heat transport and sea ice loss and has contributed to the retreat of marine‐terminating glaciers on Greenland. Heat loss to the atmosphere is largest in the Nordic Seas (60% of total) with large variability linked to the frequency of Cold Air Outbreaks and cyclones in the region, but there is no long‐term statistically significant trend. Heat loss from the Barents Sea (∼30%) and Arctic seas farther north (∼10%) is overall smaller, but exhibit large positive trends. The AW inflow, total heat loss to the atmosphere, and dense outflow have all increased since 1900. These are consistently related through theoretical scaling, but the AW inflow increase is also wind‐driven. The Arctic Ocean CO2 uptake has increased by ∼30% over the last century—consistent with Arctic sea ice loss allowing stronger air‐sea interaction and is ∼8% of the global uptake.

Slow-down in summer warming over Greenland in the past decade linked to central Pacific El Ni\xf1o

Greenland warming and ice loss have slowed down since the early 2010s, in contrast to the rest of the Arctic region. Both natural variability and anthropogenic forcing contribute to recent Greenland warming by reducing cloud cover and surface albedo, yet most climate models are unable to reasonably simulate the unforced natural variability. Here we show that a simplified atmospheric circulation model successfully simulates an atmospheric teleconnection from the tropics towards Greenland, which accounts for Greenland cooling through an intensified cyclonic circulation. Synthesis from observational analysis and model experiments indicate that over the last decade, more central Pacific El Niño events than canonical El Niño events have generated the atmospheric teleconnection by shifting the tropical rainfall zone poleward, which led to an intensified cyclonic circulation over Greenland. The intensified cyclonic circulation further extends into the Arctic Ocean in observations, whereas the model does not show a direct remote forcing from the tropics, implying the contribution of an indirect atmospheric forcing. We conclude that the frequent occurrence of central Pacific El Niño events has played a key role in the slow-down of Greenland warming and possibly Arctic sea-ice loss.

New climate models reveal faster and larger increases in Arctic precipitation than previously projected

As the Arctic continues to warm faster than the rest of the planet, evidence mounts that the region is experiencing unprecedented environmental change. The hydrological cycle is projected to intensify throughout the twenty-first century, with increased evaporation from expanding open water areas and more precipitation. The latest projections from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) point to more rapid Arctic warming and sea-ice loss by the year 2100 than in previous projections, and consequently, larger and faster changes in the hydrological cycle. Arctic precipitation (rainfall) increases more rapidly in CMIP6 than in CMIP5 due to greater global warming and poleward moisture transport, greater Arctic amplification and sea-ice loss and increased sensitivity of precipitation to Arctic warming. The transition from a snow- to rain-dominated Arctic in the summer and autumn is projected to occur decades earlier and at a lower level of global warming, potentially under 1.5 °C, with profound climatic, ecosystem and socio-economic impacts.

Marine Heatwaves in Siberian Arctic Seas and Adjacent Region

We used a satellite-derived global daily sea surface temperature (SST) dataset with resolution 0.25 × 0.25∘ to analyze interannual changes in the Arctic Shelf seas from 2000 to 2020 and to reveal extreme events in SST distribution. Results show that the second decade of the 21st century for the Siberian Arctic seas turned significantly warmer than the first decade, and the increase in SST in the Arctic seas could be considered in terms of marine heatwaves. Analyzing the spatial distribution of heatwaves and their characteristics, we showed that from 2018 to 2020, the surface warming extended to the northern deep-water region of the Laptev Sea 75∘ to 81∘N. To reveal the most important forcing for the northward extension of the marine heatwaves, we used three-dimensional numerical modeling of the Arctic Ocean based on a sea-ice and ocean model forced by the NCEP/NCAR Reanalysis. The simulation of the Arctic Ocean variability from 2000 to 2020 showed marine heatwaves and their increasing intensity in the northern region of the Kara and Laptev seas, closely connected to the disappearance of ice cover. A series of numerical experiments on the sensitivity of the model showed that the main factors affecting the Arctic sea-ice loss and the formation of anomalous temperature north of the Siberian Arctic seas are equally the thermal and dynamic effects of the atmosphere. Numerical modeling allows us to examine the impact of other physical mechanisms as well. Among them were the state of the ocean and winter sea ice, the formation of fast ice polynias and riverine heat influx.

The January 2021 Sudden Stratospheric Warming and Its Prediction in Subseasonal to Seasonal Models

AbstractUsing reanalysis, observations, and subseasonal to seasonal (S2S) forecasts, the most recent sudden stratospheric warming (SSW) in January 2021 and its predictability are explored. Previous work has shown that SSWs can be forecasted at relatively long lead time if favorable conditions are present. However, favorable conditions were not present for this most recent SSW, which occurred under the tropical westerly quasi‐biennial oscillation (QBO) and weak convection over tropical Pacific. In mid‐December 2020 and early January 2021, the Ural ridge and East Asian trough were anomalously strong, corresponding to enhanced climatological wavenumber 2. In late December 2020 and mid‐January 2021, negative (positive) height anomalies over the North Pacific (Atlantic) enhanced the climatological wavenumber 1. Alternate wave pulses by the wavenumber 1 and 2 finally led to the SSW onset and the long lifetime of the January 2021 SSW. As the composite for QBO westerlies displays a strengthened stratospheric polar vortex, the weak vortex in January 2020 was not attributed to this tropical forcing. Therefore, the predictability for the occurrence of the January 2021 SSW is not beyond two weeks with the required hit ratio >50%. Splitting of the vortex adds further difficulty to the prediction of this event. The cold anomalies over North Eurasia initiated one to two weeks before the SSW onset were likely due to the SSW precursors, which then persisted until mid‐January 2021 as the SSW signal began to propagate downward. However, the persistent cold anomalies can only be forecasted in SSW‐hit members and SSW‐hit S2S models. The observed Arctic sea ice loss is unlikely to extend the predictability of this event in S2S models.

Atmospheric River Response to Arctic Sea Ice Loss in the Polar Amplification Model Intercomparison Project

AbstractThe atmospheric river (AR) response to Arctic sea ice loss in the Northern hemisphere winter is investigated using simulations from the Polar Amplification Model Intercomparison Project. Results have shown that the midlatitude responses are dominated by dynamic effects. Poleward of around , the dynamic and thermodynamic effects cancel each other, resulting in relatively small responses. The response uncertainty can be characterized by leading uncertainty modes, with the responses over the Pacific and Atlantic projecting onto the northeastward extension and equatorward shift mode, respectively. In addition, the responses seem to be mean state‐dependent: under the same forcing, models with more poleward‐located climatological ARs tend to show stronger equatorward shifts over the Atlantic; over the Pacific, models with more westward‐located climatological AR core tend to show stronger northeastward extensions. These relationships highlight the importance of improving the AR climatology representation on reducing the response uncertainty to Arctic sea ice loss.

Quantifying the role of ocean coupling in Arctic amplification and sea-ice loss over the 21st century

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.

In Support of a Renewable Energy and Materials Economy: A Global Green New Deal That Includes Arctic Sea Ice Triage and Carbon Cycle Restoration

A Global Green New Deal (GGND)—that includes Arctic sea ice climate triage and carbon cycle climate restoration, and that, following Eisenberger (2020), would move us toward a renewable energy and materials economy (REME)—is necessary to turn our current civilization and species-threatening climate crises into an opportunity to stabilize our planet’s climate and advance to a new, more equitable and prosperous stage of human development. Imminent, potentially catastrophic, global climate impacts of Arctic sea ice loss, the first global climate “tipping point,” are reviewed, and practical and efficient potential climate triage methods for avoiding this are summarized. Longer-term carbon dioxide removal (CDR) and carbon capture, sequestration, and use (CCSU) methods, that would move us toward long-term carbon cycle climate restoration, are presented. A general reframing of climate policy and specific GGND policy proposals—that include Arctic sea ice climate triage and carbon cycle climate restoration that would rapidly move us toward a REME and avoid increasingly catastrophic climate impacts—are proposed. JEL Classification: Q53, Q54, Q55, Q56, Q58

A mechanism of spring Barents Sea ice effect on the extreme summer droughts in northeastern China

The frequency of extreme drought events in northeastern China (NEC) has increased since the 2000s, and such a decadal anomalous trend may lead to significant stress on agriculture and economic development. The correlation between Arctic sea ice loss in spring and extreme summer droughts over NEC was investigated. The results show that the loss of sea ice over the Barents Sea in spring is associated with extreme droughts and positive height anomalies over NEC in summer. The physical processes include two pathways. First, sea ice loss from the Barents Sea to the Kara Sea results in reducing baroclinicity over the ice loss region but increasing baroclinicity over the ice melting region, which is favorable to the wave ridge over northern Europe and negative-phase Summer North Atlantic Oscillation (SNAO). One wave train originates from negative-phase SNAO over North Atlantic–Europe and spreads to central Europe, central Asia, and NEC. Second, another wave motion flux originates from the Barents–Kara Sea propagating eastward, and then disperses southward to NEC. Both wave trains lead to anomalous anticyclonic circulation and westward subtropical high, which favors descending motion and less water vapor flux, thereby contributing to extreme drought.

An ice‐free Arctic: what could it mean for European weather?

An ice‐free Arctic: what could it mean for European weather?

Interdecadal Linkage Between the Winter Northern Hemisphere Climate and Arctic Sea Ice of Diverse Location and Seasonality

During the past few decades, Arctic sea-ice has declined rapidly in both autumn and winter, which is likely to link extreme weather and climate events across the Northern Hemisphere midlatitudes. Here, we use reanalysis data to investigate the possible linkage between mid–high-latitude atmospheric circulation and Arctic sea-ice loss in different geographical locations and seasons and associated impacts on wintertime climate on interdecadal timescales. Four critical sea-ice subregions are analyzed in this study—namely, the Pan-Arctic, Barents–Kara–Laptev Seas (BKL), East Siberia–Chukchi–Beaufort Seas (EsCB), and Bering Sea (Ber). Results suggest that interdecadal reduction of autumn sea-ice, irrespective of geographical location, is dynamically associated with the negative phase of the North Atlantic Oscillation (NAO) in the subsequent winter via stratospheric pathways. Specifically, autumn sea-ice loss appears to cause a weakened stratospheric polar vortex that propagates to the troposphere in the ensuing months, leading to lower surface air temperature and a deficit in precipitation over Siberia and northeastern North America. Meanwhile, an anomalous cyclone over Europe favors excessive precipitation over southern Europe. For wintertime sea-ice loss in the Pan-Arctic and BKL, a weak positive NAO phase, with a dipole pressure pattern over Greenland–northeastern North America and North Atlantic, and a shrunken Siberian high over Eurasia are observed over mid–high-latitudes. The former results in excessive precipitation over northwestern and southeastern North America, whilst the latter leads to less precipitation and mild winter over Siberia. In contrast, Ber sea-ice loss is associated with a circumglobal wave train downstream of the Bering Sea, leading to extensive warming over Eurasia. The anomalous dipole cyclone and anticyclone over the Bering Sea transport more Pacific and Arctic water vapor to North America, and the anomalous cyclone over the Barents Sea results in abundant precipitation in Siberia. Such midlatitude anomaly is dynamically linked to winter sea-ice loss, mainly through tropospheric rather than stratospheric pathways. These results have important implications for future seasonal and interdecadal forecasts in the context of ongoing sea-ice decline.

Sea ice reduction drives genetic differentiation among Barents Sea polar bears.

Loss of Arctic sea ice owing to climate change is predicted to reduce both genetic diversity and gene flow in ice-dependent species, with potentially negative consequences for their long-term viability. Here, we tested for the population-genetic impacts of reduced sea ice cover on the polar bear (Ursus maritimus) sampled across two decades (1995–2016) from the Svalbard Archipelago, Norway, an area that is affected by rapid sea ice loss in the Arctic Barents Sea. We analysed genetic variation at 22 microsatellite loci for 626 polar bears from four sampling areas within the archipelago. Our results revealed a 3–10% loss of genetic diversity across the study period, accompanied by a near 200% increase in genetic differentiation across regions. These effects may best be explained by a decrease in gene flow caused by habitat fragmentation owing to the loss of sea ice coverage, resulting in increased inbreeding of local polar bears within the focal sampling areas in the Svalbard Archipelago. This study illustrates the importance of genetic monitoring for developing adaptive management strategies for polar bears and other ice-dependent species.

The Emergence and Transient Nature of Arctic Amplification in Coupled Climate Models

Under rising atmospheric greenhouse gas concentrations, the Arctic exhibits amplified warming relative to the globe. This Arctic amplification is a defining feature of global warming. However, the Arctic is also home to large internal variability, which can make the detection of a forced climate response difficult. Here we use results from seven model large ensembles, which have different rates of Arctic warming and sea ice loss, to assess the time of emergence of anthropogenically-forced Arctic amplification. We find that this time of emergence occurs at the turn of the century in all models, ranging across the models by a decade from 1994–2005. We also assess transient changes in this amplified signal across the 21st century and beyond. Over the 21st century, the projections indicate that the maximum Arctic warming will transition from fall to winter due to sea ice reductions that extend further into the fall. Additionally, the magnitude of the annual amplification signal declines over the 21st century associated in part with a weakening albedo feedback strength. In a simulation that extends to the 23rd century, we find that as sea ice cover is completely lost, there is little further reduction in the surface albedo and Arctic amplification saturates at a level that is reduced from its 21st century value.

Inter-model spread in the wintertime Arctic amplification in the CMIP6 models and the important role of internal climate variability

We study the characteristics of wintertime Arctic amplification (AA) and the inter-model spread in model output from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and the Community Earth System Model Large Ensemble Project (CESM-LE). The CMIP6 models exhibit a large spread in AA intensity (as measured by an AA index, ranging from about −0.2 to about 1.1 °C/decade in the Historical simulations) and in its spatial/vertical structure (no AA to AA extending to upper-troposphere). A large model spread in Arctic sea-ice trends (from about −3.1 to about 0.3 %/decade) is also found. Intra-model spread in the ensemble simulations of six selected CMIP6 models, which we interpret as a measure of internal climate variability, is similarly large. We further find that CMIP6 model integrations where AA extends to the upper-troposphere, show weaker warming in the midlatitudes. The observed recent midlatitude cooling trends are generally not seen in the one-realization CMIP6 models but are seen in some ensemble members in the CMIP6 ensemble simulations; They are likely not a response to Arctic sea ice decline according to our analysis and are more likely caused by internal climate variability. By comparing the CMIP6 inter-model spread to the intra-model spread in the six selected CMIP6 ensembles and CESM-LE simulations, we argue that a large part of the CMIP6 inter-model spread in AA index, surface air temperature (SAT) trends and Arctic sea ice trends can be attributed to internal climate variability: about 67% for AA index, 58% for Arctic SAT and 22% for Arctic sea-ice. However, the inferred internal climate variability has been relatively stable in the recent several decades, while the inter-model spread in Arctic temperature trends and particularly Arctic sea-ice trends has been increasing in the CMIP6 models. This highlights the importance of constraining CMIP6 model discrepancies in simulating recent climate variations, which will potentially benefit the future multimodel climate projections. • There is a large spread in CMIP6 models in simulating the recent wintertime Arctic amplification. • Internal climate variability can account for a large part of the CMIP6 model spread. • The influences of Arctic sea ice loss on Eurasian temperature as hypothesized in existing studies are not found based on CMIP6 models/ensembles. • Full-AA is associated with weaker warming trends in midlatitudes compared to surface-only AA.

Intraseasonal contributions of Arctic sea-ice loss and Pacific decadal oscillation to a century cold event during early 2020/21 winter

Intraseasonal contributions of Arctic sea-ice loss and Pacific decadal oscillation to a century cold event during early 2020/21 winter