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Abstract
The loss of Arctic sea ice is already having profound environmental, societal, and ecological impacts locally. A highly uncertain area of scientific research, however, is whether such Arctic change has a tangible effect on weather and climate at lower latitudes. There is emerging evidence that the geographical location of sea ice loss is critically important in determining the large-scale atmospheric circulation response and associated midlatitude impacts. However, such regional dependencies have not been explored in a thorough and systematic manner. To make progress on this issue, this study analyzes ensemble simulations with an atmospheric general circulation model prescribed with sea ice loss separately in nine regions of the Arctic, to elucidate the distinct responses to regional sea ice loss. The results suggest that in some regions, sea ice loss triggers large-scale dynamical responses, whereas in other regions sea ice loss induces only local thermodynamical changes. Sea ice loss in the Barents–Kara Seas is unique in driving a weakening of the stratospheric polar vortex, followed in time by a tropospheric circulation response that resembles the North Atlantic Oscillation. For October–March, the largest spatial-scale responses are driven by sea ice loss in the Barents–Kara Seas and the Sea of Okhotsk; however, different regions assume greater importance in other seasons. The atmosphere responds very differently to regional sea ice losses than to pan-Arctic sea ice loss, and the response to pan-Arctic sea ice loss cannot be obtained by the linear addition of the responses to regional sea ice losses. The results imply that diversity in past studies of the simulated response to Arctic sea ice loss can be partly explained by the different spatial patterns of sea ice loss imposed.
Abstract
The loss of Arctic sea ice is already having profound environmental, societal, and ecological impacts locally. A highly uncertain area of scientific research, however, is whether such Arctic change has a tangible effect on weather and climate at lower latitudes. There is emerging evidence that the geographical location of sea ice loss is critically important in determining the large-scale atmospheric circulation response and associated midlatitude impacts. However, such regional dependencies have not been explored in a thorough and systematic manner. To make progress on this issue, this study analyzes ensemble simulations with an atmospheric general circulation model prescribed with sea ice loss separately in nine regions of the Arctic, to elucidate the distinct responses to regional sea ice loss. The results suggest that in some regions, sea ice loss triggers large-scale dynamical responses, whereas in other regions sea ice loss induces only local thermodynamical changes. Sea ice loss in the Barents–Kara Seas is unique in driving a weakening of the stratospheric polar vortex, followed in time by a tropospheric circulation response that resembles the North Atlantic Oscillation. For October–March, the largest spatial-scale responses are driven by sea ice loss in the Barents–Kara Seas and the Sea of Okhotsk; however, different regions assume greater importance in other seasons. The atmosphere responds very differently to regional sea ice losses than to pan-Arctic sea ice loss, and the response to pan-Arctic sea ice loss cannot be obtained by the linear addition of the responses to regional sea ice losses. The results imply that diversity in past studies of the simulated response to Arctic sea ice loss can be partly explained by the different spatial patterns of sea ice loss imposed.
Abstract
Disentangling the contribution of changing Arctic sea ice to midlatitude winter climate variability remains challenging because of the large internal climate variability in midlatitudes, difficulties separating cause from effect, methodological differences, and uncertainty around whether models adequately simulate connections between Arctic sea ice and midlatitude climate. We use regression analysis to quantify the links between Arctic sea ice and midlatitude winter climate in observations and large initial-condition ensembles of multiple climate models, in both coupled configurations and so-called Atmospheric Model Intercomparison Project (AMIP) configurations, where observed sea ice and/or sea surface temperatures are prescribed. The coupled models capture the observed links in interannual variability between winter Barents–Kara sea ice and Eurasian surface temperature, and between winter Chukchi–Bering sea ice and North American surface temperature. The coupled models also capture the delayed connection between reduced November–December Barents–Kara sea ice, a weakened winter stratospheric polar vortex, and a shift toward the negative phase of the North Atlantic Oscillation in late winter, although this downward impact is weaker than observed. The strength and sign of the connections both vary considerably between individual 35-yr-long ensemble members, highlighting the need for large ensembles to separate robust connections from internal variability. All the aforementioned links are either absent or are substantially weaker in the AMIP experiments prescribed with only observed sea ice variability. We conclude that the causal effects of sea ice variability on midlatitude winter climate are much weaker than suggested by statistical associations, evident in observations and coupled models, because the statistics are inflated by the effects of atmospheric circulation variability on sea ice.
Abstract
Disentangling the contribution of changing Arctic sea ice to midlatitude winter climate variability remains challenging because of the large internal climate variability in midlatitudes, difficulties separating cause from effect, methodological differences, and uncertainty around whether models adequately simulate connections between Arctic sea ice and midlatitude climate. We use regression analysis to quantify the links between Arctic sea ice and midlatitude winter climate in observations and large initial-condition ensembles of multiple climate models, in both coupled configurations and so-called Atmospheric Model Intercomparison Project (AMIP) configurations, where observed sea ice and/or sea surface temperatures are prescribed. The coupled models capture the observed links in interannual variability between winter Barents–Kara sea ice and Eurasian surface temperature, and between winter Chukchi–Bering sea ice and North American surface temperature. The coupled models also capture the delayed connection between reduced November–December Barents–Kara sea ice, a weakened winter stratospheric polar vortex, and a shift toward the negative phase of the North Atlantic Oscillation in late winter, although this downward impact is weaker than observed. The strength and sign of the connections both vary considerably between individual 35-yr-long ensemble members, highlighting the need for large ensembles to separate robust connections from internal variability. All the aforementioned links are either absent or are substantially weaker in the AMIP experiments prescribed with only observed sea ice variability. We conclude that the causal effects of sea ice variability on midlatitude winter climate are much weaker than suggested by statistical associations, evident in observations and coupled models, because the statistics are inflated by the effects of atmospheric circulation variability on sea ice.
Abstract
Atmospheric reanalyses can be useful tools for examining climate variability and change; however, they must be used cautiously because of time-varying biases that can induce artificial trends. This study explicitly documents a discontinuity in the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) that leads to significantly exaggerated warming in the Arctic mid- to lower troposphere, and demonstrates that the continuing use of ERA-40 to study Arctic temperature trends is problematic. The discontinuity occurs in 1997 in response to refined processing of satellite radiances prior to their assimilation into the reanalysis model. It is clearly apparent in comparisons of ERA-40 output against satellite-derived air temperatures, in situ observations, and alternative reanalyses. Decadal or multidecadal Arctic temperature trends calculated over periods that include 1997 are highly inaccurate, particularly below 600 hPa. It is shown that ERA-40 is poorly suited to studying Arctic temperature trends and their vertical profile, and conclusions based upon them must be viewed with extreme caution. Consequently, its future use for this purpose is discouraged. In the context of the wider scientific debate on the suitability of reanalyses for trend analyses, the results show that a series of alternative reanalyses are in broad-scale agreement with observations. Thus, the authors encourage their discerning use instead of ERA-40 for examining Arctic climate change while also reaffirming the importance of verifying reanalyses with observations whenever possible.
Abstract
Atmospheric reanalyses can be useful tools for examining climate variability and change; however, they must be used cautiously because of time-varying biases that can induce artificial trends. This study explicitly documents a discontinuity in the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) that leads to significantly exaggerated warming in the Arctic mid- to lower troposphere, and demonstrates that the continuing use of ERA-40 to study Arctic temperature trends is problematic. The discontinuity occurs in 1997 in response to refined processing of satellite radiances prior to their assimilation into the reanalysis model. It is clearly apparent in comparisons of ERA-40 output against satellite-derived air temperatures, in situ observations, and alternative reanalyses. Decadal or multidecadal Arctic temperature trends calculated over periods that include 1997 are highly inaccurate, particularly below 600 hPa. It is shown that ERA-40 is poorly suited to studying Arctic temperature trends and their vertical profile, and conclusions based upon them must be viewed with extreme caution. Consequently, its future use for this purpose is discouraged. In the context of the wider scientific debate on the suitability of reanalyses for trend analyses, the results show that a series of alternative reanalyses are in broad-scale agreement with observations. Thus, the authors encourage their discerning use instead of ERA-40 for examining Arctic climate change while also reaffirming the importance of verifying reanalyses with observations whenever possible.
Abstract
In early January 2014, an Arctic air outbreak brought extreme cold and heavy snowfall to central and eastern North America, causing widespread disruption and monetary losses. The media extensively reported the cold snap, including debate on whether human-induced climate change was partly responsible. Related to this, one particular hypothesis garnered considerable attention: that rapid Arctic sea ice loss may be increasing the risk of cold extremes in the midlatitudes. Here we use large ensembles of model simulations to explore how the risk of North American daily cold extremes is anticipated to change in the future, in response to increases in greenhouse gases and the component of that response solely due to Arctic sea ice loss. Specifically, we examine the changing probability of daily cold extremes as (un)common as the 7 January 2014 event. Projected increases in greenhouse gases decrease the likelihood of North American cold extremes in the future. Days as cold or colder than 7 January 2014 are still projected to occur in the mid-twenty-first century (2030–49), albeit less frequently than in the late twentieth century (1980–99). However, such events will cease to occur by the late twenty-first century (2080–99), assuming greenhouse gas emissions continue unabated. Continued Arctic sea ice loss is a major driver of decreased—not increased—North America cold extremes. Projected Arctic sea ice loss alone reduces the odds of such an event by one-quarter to one-third by the mid-twenty-first century, and to zero (or near zero) by the late twenty-first century.
Abstract
In early January 2014, an Arctic air outbreak brought extreme cold and heavy snowfall to central and eastern North America, causing widespread disruption and monetary losses. The media extensively reported the cold snap, including debate on whether human-induced climate change was partly responsible. Related to this, one particular hypothesis garnered considerable attention: that rapid Arctic sea ice loss may be increasing the risk of cold extremes in the midlatitudes. Here we use large ensembles of model simulations to explore how the risk of North American daily cold extremes is anticipated to change in the future, in response to increases in greenhouse gases and the component of that response solely due to Arctic sea ice loss. Specifically, we examine the changing probability of daily cold extremes as (un)common as the 7 January 2014 event. Projected increases in greenhouse gases decrease the likelihood of North American cold extremes in the future. Days as cold or colder than 7 January 2014 are still projected to occur in the mid-twenty-first century (2030–49), albeit less frequently than in the late twentieth century (1980–99). However, such events will cease to occur by the late twenty-first century (2080–99), assuming greenhouse gas emissions continue unabated. Continued Arctic sea ice loss is a major driver of decreased—not increased—North America cold extremes. Projected Arctic sea ice loss alone reduces the odds of such an event by one-quarter to one-third by the mid-twenty-first century, and to zero (or near zero) by the late twenty-first century.
Abstract
A sequence of extreme cold events occurred across Eurasia and North America during winter 2020/21. Here, we explore the causes and associated mechanisms for the extremely cold temperatures using both observations and large-ensemble simulations. Experiments were conducted with observed ocean surface boundary conditions prescribed globally, and regionally to discern the specific influence of Arctic, tropical Pacific, and North Pacific drivers. Increased likelihood of daily cold extremes in mid-December to mid-January are found in Eurasian midlatitudes in response to reduced Arctic sea ice. Tropical sea surface temperature anomalies, more specifically the La Niña pattern, increased probability of extreme cold over high-latitude Eurasia in early January to early February. Both reduced Arctic sea ice and La Niña increased the probability of daily cold extremes over western North America in late January to late February. We conclude that a combination of reduced Arctic sea ice, La Niña, and a sudden stratospheric warming in January 2021 were factors in the February 2021 extreme cold wave that caused huge societal disruptions in Texas and the southern Great Plains. Although the magnitude of the simulated cold extremes are relatively small when compared with observed anomalies, the Arctic and Pacific Ocean surface conditions in winter 2020/21 increased the probability of cold days as cold or colder than observed by approximately 17%–43%.
Abstract
A sequence of extreme cold events occurred across Eurasia and North America during winter 2020/21. Here, we explore the causes and associated mechanisms for the extremely cold temperatures using both observations and large-ensemble simulations. Experiments were conducted with observed ocean surface boundary conditions prescribed globally, and regionally to discern the specific influence of Arctic, tropical Pacific, and North Pacific drivers. Increased likelihood of daily cold extremes in mid-December to mid-January are found in Eurasian midlatitudes in response to reduced Arctic sea ice. Tropical sea surface temperature anomalies, more specifically the La Niña pattern, increased probability of extreme cold over high-latitude Eurasia in early January to early February. Both reduced Arctic sea ice and La Niña increased the probability of daily cold extremes over western North America in late January to late February. We conclude that a combination of reduced Arctic sea ice, La Niña, and a sudden stratospheric warming in January 2021 were factors in the February 2021 extreme cold wave that caused huge societal disruptions in Texas and the southern Great Plains. Although the magnitude of the simulated cold extremes are relatively small when compared with observed anomalies, the Arctic and Pacific Ocean surface conditions in winter 2020/21 increased the probability of cold days as cold or colder than observed by approximately 17%–43%.
Abstract
Connections across seasons in atmospheric circulation and sea ice have long been sought to advance seasonal prediction. This study presents a link between the springtime stratosphere and Arctic sea ice in summer through autumn. The polar stratospheric vortex dominates the winter stratosphere before breaking down each spring, which is called the stratospheric final warming, as solar radiation returns to the pole. Interannual variability of this breakdown is dynamically driven, leading to different springtime tropospheric and surface circulation patterns. To examine the different impacts of delayed and early final warmings, a multimodel composite was generated from selected CMIP5 models. Additionally, regressions were performed on JRA-55 against an index of springtime polar vortex strength. In both the multimodel composites and reanalysis regressions, significant anomalies in sea ice thickness persist several months following an anomalous timing of the final warming. A later final warming or stronger springtime polar stratospheric vortex leads to negative sea ice thickness anomalies in the East Siberian Sea and positive anomalies in the Beaufort Sea in comparison with an earlier final warming or weaker polar vortex. The spring polar stratospheric vortex is related to spring polar surface circulation patterns. The winds associated with this pattern induce anomalous sea ice motion, moving ice from the East Siberian Sea toward the Beaufort Sea. Reduced sea ice in the East Siberian Sea is linked to anomalous warmth over this region in autumn. Our results suggest that the timing of the stratospheric final warming exerts an influence on the tropospheric circulation and sea ice through autumn, which has implications for seasonal climate prediction.
Abstract
Connections across seasons in atmospheric circulation and sea ice have long been sought to advance seasonal prediction. This study presents a link between the springtime stratosphere and Arctic sea ice in summer through autumn. The polar stratospheric vortex dominates the winter stratosphere before breaking down each spring, which is called the stratospheric final warming, as solar radiation returns to the pole. Interannual variability of this breakdown is dynamically driven, leading to different springtime tropospheric and surface circulation patterns. To examine the different impacts of delayed and early final warmings, a multimodel composite was generated from selected CMIP5 models. Additionally, regressions were performed on JRA-55 against an index of springtime polar vortex strength. In both the multimodel composites and reanalysis regressions, significant anomalies in sea ice thickness persist several months following an anomalous timing of the final warming. A later final warming or stronger springtime polar stratospheric vortex leads to negative sea ice thickness anomalies in the East Siberian Sea and positive anomalies in the Beaufort Sea in comparison with an earlier final warming or weaker polar vortex. The spring polar stratospheric vortex is related to spring polar surface circulation patterns. The winds associated with this pattern induce anomalous sea ice motion, moving ice from the East Siberian Sea toward the Beaufort Sea. Reduced sea ice in the East Siberian Sea is linked to anomalous warmth over this region in autumn. Our results suggest that the timing of the stratospheric final warming exerts an influence on the tropospheric circulation and sea ice through autumn, which has implications for seasonal climate prediction.
Abstract
The Arctic is warming faster than the global average. This disproportionate warming—known as Arctic amplification—has caused significant local changes to the Arctic system and more uncertain remote changes across the Northern Hemisphere midlatitudes. Here, an atmospheric general circulation model (AGCM) is used to test the sensitivity of the atmospheric and surface response to Arctic sea ice loss to the phase of the Atlantic multidecadal oscillation (AMO), which varies on (multi-) decadal time scales. Four experiments are performed, combining low and high sea ice states with global sea surface temperature (SST) anomalies associated with opposite phases of the AMO. A trough–ridge–trough response to wintertime sea ice loss is seen in the Pacific–North American sector in the negative phase of the AMO. The authors propose that this is a consequence of an increased meridional temperature gradient in response to sea ice loss, just south of the climatological maximum, in the midlatitudes of the central North Pacific. This causes a southward shift in the North Pacific storm track, which strengthens the Aleutian low with circulation anomalies propagating into North America. While the climate response to sea ice loss is sensitive to AMO-related SST anomalies in the North Pacific, there is little sensitivity to larger-magnitude SST anomalies in the North Atlantic. With background ocean–atmosphere states persisting for a number of years, there is the potential to improve predictions of the impacts of Arctic sea ice loss on decadal time scales.
Abstract
The Arctic is warming faster than the global average. This disproportionate warming—known as Arctic amplification—has caused significant local changes to the Arctic system and more uncertain remote changes across the Northern Hemisphere midlatitudes. Here, an atmospheric general circulation model (AGCM) is used to test the sensitivity of the atmospheric and surface response to Arctic sea ice loss to the phase of the Atlantic multidecadal oscillation (AMO), which varies on (multi-) decadal time scales. Four experiments are performed, combining low and high sea ice states with global sea surface temperature (SST) anomalies associated with opposite phases of the AMO. A trough–ridge–trough response to wintertime sea ice loss is seen in the Pacific–North American sector in the negative phase of the AMO. The authors propose that this is a consequence of an increased meridional temperature gradient in response to sea ice loss, just south of the climatological maximum, in the midlatitudes of the central North Pacific. This causes a southward shift in the North Pacific storm track, which strengthens the Aleutian low with circulation anomalies propagating into North America. While the climate response to sea ice loss is sensitive to AMO-related SST anomalies in the North Pacific, there is little sensitivity to larger-magnitude SST anomalies in the North Atlantic. With background ocean–atmosphere states persisting for a number of years, there is the potential to improve predictions of the impacts of Arctic sea ice loss on decadal time scales.
Abstract
Arctic sea ice is declining at an increasing rate with potentially important repercussions. To understand better the atmospheric changes that may have occurred in response to Arctic sea ice loss, this study presents results from atmospheric general circulation model (AGCM) experiments in which the only time-varying forcings prescribed were observed variations in Arctic sea ice and accompanying changes in Arctic sea surface temperatures from 1979 to 2009. Two independent AGCMs are utilized in order to assess the robustness of the response across different models. The results suggest that the atmospheric impacts of Arctic sea ice loss have been manifested most strongly within the maritime and coastal Arctic and in the lowermost atmosphere. Sea ice loss has driven increased energy transfer from the ocean to the atmosphere, enhanced warming and moistening of the lower troposphere, decreased the strength of the surface temperature inversion, and increased lower-tropospheric thickness; all of these changes are most pronounced in autumn and early winter (September–December). The early winter (November–December) atmospheric circulation response resembles the negative phase of the North Atlantic Oscillation (NAO); however, the NAO-type response is quite weak and is often masked by intrinsic (unforced) atmospheric variability. Some evidence of a late winter (March–April) polar stratospheric cooling response to sea ice loss is also found, which may have important implications for polar stratospheric ozone concentrations. The attribution and quantification of other aspects of the possible atmospheric response are hindered by model sensitivities and large intrinsic variability. The potential remote responses to Arctic sea ice change are currently hard to confirm and remain uncertain.
Abstract
Arctic sea ice is declining at an increasing rate with potentially important repercussions. To understand better the atmospheric changes that may have occurred in response to Arctic sea ice loss, this study presents results from atmospheric general circulation model (AGCM) experiments in which the only time-varying forcings prescribed were observed variations in Arctic sea ice and accompanying changes in Arctic sea surface temperatures from 1979 to 2009. Two independent AGCMs are utilized in order to assess the robustness of the response across different models. The results suggest that the atmospheric impacts of Arctic sea ice loss have been manifested most strongly within the maritime and coastal Arctic and in the lowermost atmosphere. Sea ice loss has driven increased energy transfer from the ocean to the atmosphere, enhanced warming and moistening of the lower troposphere, decreased the strength of the surface temperature inversion, and increased lower-tropospheric thickness; all of these changes are most pronounced in autumn and early winter (September–December). The early winter (November–December) atmospheric circulation response resembles the negative phase of the North Atlantic Oscillation (NAO); however, the NAO-type response is quite weak and is often masked by intrinsic (unforced) atmospheric variability. Some evidence of a late winter (March–April) polar stratospheric cooling response to sea ice loss is also found, which may have important implications for polar stratospheric ozone concentrations. The attribution and quantification of other aspects of the possible atmospheric response are hindered by model sensitivities and large intrinsic variability. The potential remote responses to Arctic sea ice change are currently hard to confirm and remain uncertain.
Abstract
Cold winters over Eurasia often coincide with warm winters in the Arctic, which has become known as the “Warm Arctic-Cold Eurasia” pattern. The extent to which this observed correlation is indicative of a causal response to sea-ice loss is debated. Here, using large multi-model ensembles of coordinated experiments, we find that the Eurasian temperature response to Arctic sea-ice loss is weak compared to internal variability, and is not robust across climate models. We show that Eurasian cooling is driven by tropospheric and stratospheric circulation changes in response to sea-ice loss, but is counteracted by tropospheric thermodynamical warming, as the local warming induced by sea-ice loss spreads into the midlatitudes by eddy advection. Although opposing effects of thermodynamical warming and dynamical cooling are found robustly across different models or different sea ice perturbations, their net effect varies in sign and magnitude across the models, resulting in diverse model temperature response over Eurasia. Both the contributions from tropospheric dynamics and thermodynamics show substantial inter-model spread. Although some of this spread in the Eurasian winter temperature response to sea-ice loss may stem from model uncertainty, even with several hundred ensemble members, it is challenging to isolate model differences in the forced response from internal variability.
Abstract
Cold winters over Eurasia often coincide with warm winters in the Arctic, which has become known as the “Warm Arctic-Cold Eurasia” pattern. The extent to which this observed correlation is indicative of a causal response to sea-ice loss is debated. Here, using large multi-model ensembles of coordinated experiments, we find that the Eurasian temperature response to Arctic sea-ice loss is weak compared to internal variability, and is not robust across climate models. We show that Eurasian cooling is driven by tropospheric and stratospheric circulation changes in response to sea-ice loss, but is counteracted by tropospheric thermodynamical warming, as the local warming induced by sea-ice loss spreads into the midlatitudes by eddy advection. Although opposing effects of thermodynamical warming and dynamical cooling are found robustly across different models or different sea ice perturbations, their net effect varies in sign and magnitude across the models, resulting in diverse model temperature response over Eurasia. Both the contributions from tropospheric dynamics and thermodynamics show substantial inter-model spread. Although some of this spread in the Eurasian winter temperature response to sea-ice loss may stem from model uncertainty, even with several hundred ensemble members, it is challenging to isolate model differences in the forced response from internal variability.
