scholarly journals Impact of Reduced Arctic Sea Ice on Northern Hemisphere Climate and Weather in Autumn and Winter

2021 ◽  
pp. 1-61
Author(s):  
Svenya Chripko ◽  
Rym Msadek ◽  
Emilia Sanchez-Gomez ◽  
Laurent Terray ◽  
Laurent Bessières ◽  
...  
Keyword(s):  
North America ◽  
Sea Ice ◽  
Central Asia ◽  
Northern Hemisphere ◽  
Climate Model ◽  
Polar Vortex ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Arctic Sea ◽  
Autumn And Winter

AbstractThe Northern Hemisphere transient atmospheric response to Arctic sea decline is investigated in autumn and winter, using sensitivity experiments performed with the CNRMCM6-1 high-top climate model. Arctic sea ice albedo is reduced to the ocean value, yielding ice-free conditions during summer and a more moderate sea ice reduction during the following months. A strong ampli_cation of temperatures over the Arctic is induced by sea ice loss, with values reaching up to 25°C near the surface in autumn. Signi_cant surface temperature anomalies are also found over the mid-latitudes, with a warming reaching 1°C over North America and Europe, and a cooling reaching 1°C over central Asia. Using a dynamical adjustment method based on a regional reconstruction of circulation analogs, we show that the warming over North America and Europe can be explained both by changes in the atmospheric circulation and by the advection of warmer oceanic air by the climatological ow. In contrast, we demonstrate that the sea-ice induced cooling over central Asia is solely due to dynamical changes, involving an intensi_cation of the Siberian High and a cyclonic anomaly over the Sea of Okhotsk. In the troposphere, the abrupt Arctic sea ice decline favours a narrowing of the subtropical jet stream and a slight weakening of the lower part of the polar vortex that is explained by a weak enhancement of upward wave activity toward the stratosphere. We further show that reduced Arctic sea ice in our experiments is mainly associated with less severe cold extremes in the mid-latitudes.

scholarly journals Dynamical and thermodynamical contributions to the mid-latitude atmospheric response to Arctic sea ice decline

2021 ◽  
Author(s):  
Svenya Chripko ◽  
Rym Msadek ◽  
Emilia Sanchez-Gomez ◽  
Laurent Terray ◽  
Laurent Bessières ◽  
...  
Keyword(s):  
North America ◽  
Sea Ice ◽  
Central Asia ◽  
Climate Model ◽  
Temperature Response ◽  
Arctic Sea Ice ◽  
Atmospheric Response ◽  
Near Surface ◽  
Sea Ice Decline ◽  
Arctic Sea

<p>Previous climate model studies have shown that Arctic sea ice decline can solely affect weather and climate at lower latitudes during the cold season. However, the mechanisms beneath this linkage are poorly understood. Whether sea ice loss have had an influence on the lower latitudes climate over the past decades is also uncertain (Barnes and Screen 2015). The goal of this work is to better understand the relative contributions of dyncamical and thermodynamical changes in the atmospheric response to Arctic sea ice loss, which have been suggested to oppose each other (Screen 2017). We conducted two sets of sensitivity transient experiments that allow to isolate the effect of Arctic sea ice decline on the mid-latitudes from other climate forcings, using the climate model CNRM-CM6 (Voldoire et al. 2019) in a coupled configuration or with an atmosphere-only. The first set of experiments, that is part of the European H2020 PRIMAVERA project, consists of a 100-member ensemble in which sea ice albedo is reduced to the ocean value (PERT) in the fully coupled CNRM-CM6, and which is compared to a 1950 control run (CTL) (Haarsma et al. 2016). This yields idealised ice-free conditions in summer and a more moderate sea ice reduction during the following months. The second set of experiments, that is part of the CMIP6 Polar Amplification Model Intercomparison Project (PAMIP, Smith et al. 2019), consists of a 300-member ensemble in which the atmospheric component of CNRM-CM6 is forced by sea ice anomalies associated with a future 2°C warming (FUT) and present day sea surface temperatures (SSTs). These are compared to experiments in which the atmosphere is forced by present-day sea ice conditions (PD) and the same SSTs. To extract the dynamical component of the response in the two sets of experiments, we use a dynamical adjustment method (Deser et al. 2016) based on a regional reconstruction of circulation analogs. We focus on three mid-latitudes regions in which a significant near-surface temperature response has been identified, namely North America, Europe and central Asia. We show that the cooling occurring over central Asia in both sets of experiments is dynamically-induced through an intensification of the Siberian High, and that opposed temperature responses over North America between the two sets of experiments could be explained by opposed dynamical components occurring in response to the imposed Arctic sea ice decline. Finally, we discuss whether different dynamical and thermodynamical contributions in the PAMIP multi-model experiments could explain the multi-model differences in the atmospheric response to sea ice loss.</p>

Assessing the climate response to regional sea ice change across all Arctic regions.

2020 ◽  
Author(s):  
Xavier Levine ◽  
Ivana Cvijanovic ◽  
Pablo Ortega ◽  
Markus Donat
Keyword(s):  
Climate Change ◽  
North America ◽  
Sea Ice ◽  
Northern Hemisphere ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Response ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss

<p>Climate models predict that sea ice cover will shrink--even disappear-- in most regions of the Arctic basin by the end of the century, triggering local and remote responses in the surface climate via atmospheric and oceanic circulation changes. In particular, it has been suggested that seasonal anomalies over Europe and North America in recent years could have been caused by record low Arctic sea ice cover. Despite an intense research effort toward quantifying its effect, the contribution of regional sea ice loss to climate change and its mechanisms of action remain controversial. </p><p>In this study, we prescribe sea ice loss in individual sectors of the Arctic within a climate model, and study its effect on climatic anomalies in the Northern Hemisphere. Using the EC-EARTH3.3 model in its atmospheric-only and fully coupled configuration, and following the PAMIP protocol, sea ice cover is set to either its present day state, or a hypothetical future distribution of reduced sea ice cover in the Arctic. This pan-Arctic sea ice loss experiment is then complemented by 8 regional sea ice loss experiments.</p><p>Comparing those experiments, we assess the contribution of sea ice loss in each region of the Arctic to climate change over Europe, Siberia and North America. We find that sea ice loss in some sectors of the Arctic appears to matter more for Northern Hemisphere climate change than others, even after normalizing for differences in surface cover. Furthermore, the climatic effect of regional sea ice loss is compared to that of a pan-Arctic sea ice loss, whose associated climate anomalies are found to be strikingly different from that expected from a simple linear response to regional sea ice loss. We propose a mechanism for this nonlinear climate response to regional sea ice loss, which considers regional differences in the strength of the thermal inversion over the Arctic, as well as the relative proximity of each Arctic region to features critical for stationary wave genesis (e.g. the Tibetan plateau).</p>

Mechanisms for and Predictability of a Drastic Reduction in the Arctic Sea Ice: APPOSITE Data with Climate Model MIROC

2019 ◽  
Vol 32 (5) ◽  
pp. 1361-1380 ◽  
Author(s):  
J. Ono ◽  
H. Tatebe ◽  
Y. Komuro
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ensemble Prediction ◽  
Forecast Errors ◽  
Drastic Reduction ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
Arctic Sea

Abstract The mechanisms for and predictability of a drastic reduction in the Arctic sea ice extent (SIE) are investigated using the Model for Interdisciplinary Research on Climate (MIROC) version 5.2. Here, a control (CTRL) with forcing fixed at year 2000 levels and perfect-model ensemble prediction (PRED) experiments are conducted. In CTRL, three (model years 51, 56, and 57) drastic SIE reductions occur during a 200-yr-long integration. In year 56, the sea ice moves offshore in association with a positive phase of the summer Arctic dipole anomaly (ADA) index and melts due to heat input through the increased open water area, and the SIE drastically decreases. This provides the preconditioning for the lowest SIE in year 57 when the Arctic Ocean interior is in a warm state and the spring sea ice volume has a large negative anomaly due to drastic ice reduction in the previous year. Although the ADA is one of the key mechanisms behind sea ice reduction, it does not always cause a drastic reduction. Our analysis suggests that wind direction favoring offshore ice motion is a more important factor for drastic ice reduction events. In years experiencing drastic ice reduction events, the September SIE can be skillfully predicted in PRED started from July, but not from April. This is because the forecast errors for the July sea level pressure and those for the sea ice concentration and sea ice thickness along the ice edge are large in PRED started from April.

scholarly journals Atmospheric teleconnection processes linking winter air stagnation and haze extremes in China with regional Arctic sea ice decline

2019 ◽  
Author(s):  
Yufei Zou ◽  
Yuhang Wang ◽  
Zuowei Xie ◽  
Hailong Wang ◽  
Philip J. Rasch
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Teleconnection Pattern ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Transient Eddy ◽  
Regional Ventilation ◽  
Atmospheric Teleconnection ◽  
Upper Troposphere ◽  
Arctic Sea

Abstract. Recent studies suggested significant impacts of boreal cryosphere changes on wintertime air stagnation and haze pollution extremes in China. However, the underlying mechanism of such a teleconnection relationship remains unclear. Here we used the Whole Atmosphere Community Climate Model (WACCM) to investigate dynamic processes leading to atmospheric circulation and air stagnation responses to Arctic sea ice changes. We conducted four climate sensitivity experiments by perturbing sea ice concentrations (SIC) and corresponding sea surface temperature (SST) in autumn and early winter over the whole Arctic and three sub-regions in the climate model. The results indicate different responses in the general circulation and regional ventilation to the region-specific Arctic changes, with the largest increase of both the probability (by 120 %) and the intensity (by 32 %) of air stagnation extreme events being found in the experiment driven by SIC and SST changes over the Pacific sector of the Arctic (the East Siberian and Chukchi Seas). The increased air stagnation extreme events are mainly driven by an amplified hemispheric-scale atmospheric teleconnection pattern that resembles the negative phase of the Eurasian (EU) pattern. Dynamical diagnostics suggest that convergence of transient eddy forcing in the vicinity of Scandinavia in winter is largely responsible for the amplification of the teleconnection pattern. Transient eddy vorticity fluxes dominate the transient eddy forcing and produce a barotropic anticyclonic anomaly near Scandinavia and wave-train propagation across Eurasia to the downstream regions in East Asia. The piecewise potential vorticity inversion analysis reveals that this long-range atmospheric teleconnection of the Arctic origin takes place primarily in the middle and upper troposphere. The anomalous ridge over East Asia in the middle and upper troposphere worsens regional ventilation conditions by weakening monsoon northwesterlies and enhancing temperature inversion near the surface, leading to more and stronger air stagnation and pollution extremes over eastern China in winter. Ensemble projections based on the state-of-the-art climate models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) corroborate this teleconnection relationship between high-latitude environmental changes and middle-latitude weather extremes, though the tendency and magnitude vary considerably among each participating model.

scholarly journals Mechanisms causing reduced Arctic sea ice loss in a coupled climate model

2012 ◽  
Vol 6 (4) ◽  
pp. 2653-2687 ◽  
Author(s):  
A. E. West ◽  
A. B. Keen ◽  
H. T. Hewitt
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Historical Record ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Slight Reduction ◽  
Coupled Climate Model ◽  
Arctic Sea ◽  
Ensembles Project ◽  
Arctic Sea Ice Loss

Abstract. The fully-coupled climate model HadGEM1 produces one of the most accurate simulations of the historical record of Arctic sea ice seen in the IPCC AR4 multi-model ensemble. In this study, we examine projections of sea ice decline out to 2030, produced by two ensembles of HadGEM1 with natural and anthropogenic forcings included. These ensembles project a significant slowing of the rate of ice loss to occur after 2010, with some integrations even simulating a small increase in ice area. We use an energy budget of the Arctic to examine the causes of this slowdown. A negative feedback effect by which rapid reductions in ice thickness north of Greenland reduce ice export is found to play a major role. A slight reduction in ocean-to-ice heat flux in the relevant period, caused by changes in the MOC and subpolar gyre in some integrations, is also found to play a part. Finally, we assess the likelihood of a slowdown occurring in the real world due to these causes.

Gridded Arctic sea ice concentration reconstruction for the first half of the 20th century based on different proxy data

2021 ◽  
Author(s):  
Vladimir Semenov ◽  
Tatiana Matveeva
Keyword(s):  
Sea Ice ◽  
20Th Century ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
The North ◽  
Arctic Sea ◽  
Ice Concentration

<p>Global warming in the recent decades has been accompanied by a rapid recline of the Arctic sea ice area most pronounced in summer (10% per decade). To understand the relative contribution of external forcing and natural variability to the modern and future sea ice area changes, it is necessary to evaluate a range of long-term variations of the Arctic sea ice area in the period before a significant increase in anthropogenic emissions of greenhouse gases into the atmosphere. Available observational data on the spatiotemporal dynamics of Arctic sea ice until 1950s are characterized by significant gaps and uncertainties. In the recent years, there have appeared several reconstructions of the early 20<sup>th</sup> century Arctic sea ice area that filled the gaps by analogue methods or utilized combined empirical data and climate model’s output. All of them resulted in a stronger that earlier believed negative sea ice area anomaly in the 1940s concurrent with the early 20<sup>th</sup> century warming (ETCW) peak. In this study, we reconstruct the monthly average gridded sea ice concentration (SIC) in the first half of the 20th century using the relationship between the spatiotemporal features of SIC variability, surface air temperature over the Northern Hemisphere extratropical continents, sea surface temperature in the North Atlantic and North Pacific, and sea level pressure. In agreement with a few previous results, our reconstructed data also show a significant negative anomaly of the Arctic sea ice area in the middle of the 20th century, however with some 15% to 30% stronger amplitude, about 1.5 million km<sup>2</sup> in September and 0.7 million km<sup>2</sup> in March. The reconstruction demonstrates a good agreement with regional Arctic sea ice area data when available and suggests that ETWC in the Arctic has been accompanied by a concurrent sea ice area decline of a magnitude that have been exceeded only in the beginning of the 21<sup>st</sup> century.</p>

scholarly journals Mid-Holocene Northern Hemisphere warming driven by Arctic amplification

2019 ◽  
Vol 5 (12) ◽  
pp. eaax8203 ◽  
Author(s):  
Hyo-Seok Park ◽  
Seong-Joong Kim ◽  
Andrew L. Stewart ◽  
Seok-Woo Son ◽  
Kyong-Hwan Seo
Keyword(s):  
Sea Ice ◽  
Northern Hemisphere ◽  
High Latitude ◽  
Climate Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Arctic Amplification ◽  
The Holocene ◽  
Holocene Thermal Maximum ◽  
Thermal Maximum

The Holocene thermal maximum was characterized by strong summer solar heating that substantially increased the summertime temperature relative to preindustrial climate. However, the summer warming was compensated by weaker winter insolation, and the annual mean temperature of the Holocene thermal maximum remains ambiguous. Using multimodel mid-Holocene simulations, we show that the annual mean Northern Hemisphere temperature is strongly correlated with the degree of Arctic amplification and sea ice loss. Additional model experiments show that the summer Arctic sea ice loss persists into winter and increases the mid- and high-latitude temperatures. These results are evaluated against four proxy datasets to verify that the annual mean northern high-latitude temperature during the mid-Holocene was warmer than the preindustrial climate, because of the seasonally rectified temperature increase driven by the Arctic amplification. This study offers a resolution to the “Holocene temperature conundrum”, a well-known discrepancy between paleo-proxies and climate model simulations of Holocene thermal maximum.

Arctic Sea Ice Reemergence: The Role of Large-Scale Oceanic and Atmospheric Variability*

2015 ◽  
Vol 28 (14) ◽  
pp. 5477-5509 ◽  
Author(s):  
Mitchell Bushuk ◽  
Dimitrios Giannakis ◽  
Andrew J. Majda
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Arctic Sea ◽  
Spring Sea Ice ◽  
Phase Relationships

Abstract Arctic sea ice reemergence is a phenomenon in which spring sea ice anomalies are positively correlated with fall anomalies, despite a loss of correlation over the intervening summer months. This work employs a novel data analysis algorithm for high-dimensional multivariate datasets, coupled nonlinear Laplacian spectral analysis (NLSA), to investigate the regional and temporal aspects of this reemergence phenomenon. Coupled NLSA modes of variability of sea ice concentration (SIC), sea surface temperature (SST), and sea level pressure (SLP) are studied in the Arctic sector of a comprehensive climate model and in observations. It is found that low-dimensional families of NLSA modes are able to efficiently reproduce the prominent lagged correlation features of the raw sea ice data. In both the model and observations, these families provide an SST–sea ice reemergence mechanism, in which melt season (spring) sea ice anomalies are imprinted as SST anomalies and stored over the summer months, allowing for sea ice anomalies of the same sign to reappear in the growth season (fall). The ice anomalies of each family exhibit clear phase relationships between the Barents–Kara Seas, the Labrador Sea, and the Bering Sea, three regions that compose the majority of Arctic sea ice variability. These regional phase relationships in sea ice have a natural explanation via the SLP patterns of each family, which closely resemble the Arctic Oscillation and the Arctic dipole anomaly. These SLP patterns, along with their associated geostrophic winds and surface air temperature advection, provide a large-scale teleconnection between different regions of sea ice variability. Moreover, the SLP patterns suggest another plausible ice reemergence mechanism, via their winter-to-winter regime persistence.

scholarly journals An inter-comparison of the mass budget of the Arctic sea ice in CMIP6 models

2020 ◽  
Author(s):  
Ann Keen ◽  
Ed Blockley ◽  
David Bailey ◽  
Jens Boldingh Debernard ◽  
Mitchell Bushuk ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Formation ◽  
Mass Budget ◽  
Ice Growth ◽  
Arctic Sea ◽  
Basal Melting

Abstract. We compare the mass budget of the Arctic sea ice for 14 models submitted to the latest Climate Model Inter-comparison Project (CMIP6), using new diagnostics that have not been available for previous model inter-comparisons. Using these diagnostics allows us to look beyond the standard metrics of ice cover and thickness, to compare the processes of sea ice growth and loss in climate models in a more detailed way than has previously been possible. For the 1960–89 multi-model mean, the dominant processes causing annual ice growth are basal growth and frazil ice formation, which both occur during the winter. The main processes by which ice is lost are basal melting, top melting and advection of ice out of the Arctic. The first two processes occur in summer, while the latter process is present all year. The sea-ice budgets for individual models are strikingly similar overall in terms of the major processes causing ice growth and loss, and in terms of the time of year during which each process is important. However, there are also some key differences between the models. The relative amounts of frazil and basal ice formation varies between the models. This is, to some extent at least, attributable to exactly how the frazil growth is formulated within each model. There are also differences in the relative amounts of top and basal melting. As the ice cover and mass decline during the 21st century, we see a shift in the timing of the top and basal melting in the multi-model mean, with more melt occurring earlier in the year, and less melt later in the summer. The amount of basal growth in the autumn reduces, but the amount of basal growth later in the winter increases due to the ice being thinner. Overall, extra ice loss in May–June and reduced ice growth in October-November is partially offset by reduced ice melt in August and increased ice growth in January–February. For the individual models, changes in the budget components vary considerably in terms of magnitude and timing of change. However, when the evolving budget terms are considered as a function of the changing ice state itself, behaviours common to all the models emerge, suggesting that the sea ice components of the models are fundamentally responding in a broadly consistent way to the warming climate. Additional results from a forced ocean-ice model show that although atmospheric forcing is crucial for the sea ice mass budget, the sea ice physics also plays an important role.

scholarly journals Simulation of observed climate changes in 1850–2014 with climate model INM-CM5

2018 ◽  
Vol 9 (4) ◽  
pp. 1235-1242 ◽  
Author(s):  
Evgeny Volodin ◽  
Andrey Gritsun
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Climate Changes ◽  
Climate Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ocean Heat Uptake ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss ◽  
Global Mean

Abstract. Climate changes observed in 1850–2014 are modeled and studied on the basis of seven historical runs with the climate model INM-CM5 under the scenario proposed for the Coupled Model Intercomparison Project Phase 6 (CMIP6). In all runs global mean surface temperature rises by 0.8 K at the end of the experiment (2014) in agreement with the observations. Periods of fast warming in 1920–1940 and 1980–2000 as well as its slowdown in 1950–1975 and 2000–2014 are correctly reproduced by the ensemble mean. The notable change here with respect to the CMIP5 results is the correct reproduction of the slowdown in global warming in 2000–2014 that we attribute to a change in ocean heat uptake and a more accurate description of the total solar irradiance in the CMIP6 protocol. The model is able to reproduce the correct behavior of global mean temperature in 1980–2014 despite incorrect phases of the Atlantic Multidecadal Oscillation and Pacific Decadal Oscillation indices in the majority of experiments. The Arctic sea ice loss in recent decades is reasonably close to the observations in just one model run; the model underestimates Arctic sea ice loss by a factor of 2.5. The spatial pattern of the model mean surface temperature trend during the last 30 years looks close to the one for the ERA-Interim reanalysis. The model correctly estimates the magnitude of stratospheric cooling.

Sign in / Sign up

Export Citation Format

Share Document