scholarly journals An Internal Atmospheric Process Determining Summertime Arctic Sea Ice Melting in the Next Three Decades: Lessons Learned from Five Large Ensembles and Multiple CMIP5 Climate Simulations

2020 ◽  
Vol 33 (17) ◽  
pp. 7431-7454 ◽  
Author(s):  
Dániel Topál ◽  
Qinghua Ding ◽  
Jonathan Mitchell ◽  
Ian Baxter ◽  
Mátyás Herein ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
Lessons Learned ◽  
The Arctic ◽  
Cmip5 Models ◽  
Ice Melting ◽  
Decadal Time Scale ◽  
Atmospheric Process ◽  
Sst Variability ◽  
Arctic Sea

AbstractArctic sea ice melting processes in summer due to internal atmospheric variability have recently received considerable attention. A regional barotropic atmospheric process over Greenland and the Arctic Ocean in summer (June–August), featuring either a year-to-year change or a low-frequency trend toward geopotential height rise, has been identified as an essential contributor to September sea ice loss, in both observations and the CESM1 Large Ensemble (CESM-LE) of simulations. This local melting is further found to be sensitive to remote sea surface temperature (SST) variability in the east-central tropical Pacific Ocean. Here, we utilize five available large “initial condition” Earth system model ensembles and 31 CMIP5 models’ preindustrial control simulations to show that the same atmospheric process, resembling the observed one and the one found in the CESM-LE, also dominates internal sea ice variability in summer on interannual to interdecadal time scales in preindustrial, historical, and future scenarios, regardless of the modeling environment. However, all models exhibit limitations in replicating the magnitude of the observed local atmosphere–sea ice coupling and its sensitivity to remote tropical SST variability in the past four decades. These biases call for caution in the interpretation of existing models’ simulations and fresh thinking about models’ credibility in simulating interactions of sea ice variability with the Arctic and global climate systems. Further efforts toward identifying the causes of these model limitations may provide implications for alleviating the biases and improving interannual- and decadal-time-scale sea ice prediction and future sea ice projection.

An Internal Atmospheric Process Determining Summertime Arctic Sea Ice Melting in the Next Three Decades: Lessons Learnt from 5 Large Ensembles and CMIP5 Simulations

2020 ◽  
Author(s):  
Daniel Topal ◽  
Qinghua Ding ◽  
Jonathan Mitchell ◽  
Ian Baxter ◽  
Mátyás Herein ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Cmip5 Models ◽  
Ice Melting ◽  
Surface Cooling ◽  
Atmospheric Process ◽  
Sst Variability ◽  
Arctic Sea ◽  
Large Ensembles

<p>Arctic sea ice melting processes in summer due to internal atmospheric variability have recently received considerable attention. A regional barotropic atmospheric process over Greenland and the Arctic Ocean in summer (June-July-August), featuring either a year-to-year change or a low-frequency trend toward geopotential height rise, has been identified as an essential contributor to September sea ice loss, in both observations and the CESM1 Large Ensemble (CESM-LE) of simulations [1-2]. This local melting is further found to be sensitive to remote sea surface temperature (SST) variability in the East Central Pacific [3]. Here, we utilize five available single-model large ensembles and 31 CMIP5 models’ pre-industrial control simulations to show that the same atmospheric process, resembling the observed one and the one found in the CESM-LE, also dominates internal sea ice variability on interannual to interdecadal time scales in pre-industrial, historical and future scenarios, regardless of the modeling environment. However, all models exhibit limitations in replicating the correct magnitude of the observed local atmosphere-sea ice coupling and its sensitivity to remote tropical SST variability. These biases cast a shadow over models’ credibility in simulating interactions of sea ice variability with the Arctic and global climate systems. Further efforts toward identifying possible causes of these model limitations may provide profound implications for alleviating the biases and improving interannual and decadal time scale sea ice prediction and future sea ice projection.</p><p> </p><p>[1] Ding, Q., and Coauthors, (2017): Influence of high-latitude atmospheric circulation changes on summertime Arctic sea ice. Nat. Climate Change, <strong>7</strong>, 289-295.</p><p>[2] Ding, Q., and Coauthors, (2019): Fingerprints of internal drivers of Arctic sea ice loss in observations and model simulations. Nat. Geosci., <strong>12</strong>, 28–33.</p><p>[3] Baxter, I., and Coauthors, (2019): How tropical Pacific surface cooling contributed to accelerated sea ice melt from 2007 to 2012 as ice is thinned by anthropogenic forcing. J. Climate, <strong>32</strong>, 8583–8602 https://doi.org/10.1175/JCLI-D-18-0783.1 </p>

scholarly journals The role of moisture transport for precipitation in the inter-annual and inter-daily fluctuations of the Arctic sea ice extension

2019 ◽  
Vol 10 (1) ◽  
pp. 121-133 ◽  
Author(s):  
Luis Gimeno-Sotelo ◽  
Raquel Nieto ◽  
Marta Vázquez ◽  
Luis Gimeno
Keyword(s):  
Sea Ice ◽  
Moisture Transport ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Melting ◽  
Sea Ice Extent ◽  
Moisture Sources ◽  
Arctic Sea

Abstract. By considering the moisture transport for precipitation (MTP) for a target region to be the moisture that arrives in this region from its major moisture sources and which then results in precipitation in that region, we explore (i) whether the MTP from the main moisture sources for the Arctic region is linked with inter-annual fluctuations in the extent of Arctic sea ice superimposed on its decline and (ii) the role of extreme MTP events in the inter-daily change in the Arctic sea ice extent (SIE) when extreme MTP simultaneously arrives from the four main moisture regions that supply it. The results suggest (1) that ice melting at the scale of inter-annual fluctuations against the trend is favoured by an increase in moisture transport in summer, autumn, and winter and a decrease in spring and, (2) on a daily basis, extreme humidity transport increases the formation of ice in winter and decreases it in spring, summer, and autumn; in these three seasons extreme humidity transport therefore contributes to Arctic sea ice melting. These patterns differ sharply from that linked to the decline on a long-range scale, especially in summer when the opposite trend applies, as ice melt is favoured by a decrease in moisture transport for this season at this scale.

scholarly journals The role of moisture transport for precipitation on the interannual and inter-daily fluctuations of the arctic sea ice extension

2018 ◽  
Author(s):  
Luis Gimeno-Sotelo ◽  
Raquel Nieto ◽  
Marta Vázquez ◽  
Luis Gimeno
Keyword(s):  
Sea Ice ◽  
Moisture Transport ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Melting ◽  
Sea Ice Extent ◽  
Moisture Sources ◽  
Arctic Sea ◽  
Interannual Fluctuations

Abstract. By considering the moisture transport for precipitation (MTP) for a target region to be the moisture that arrives in this region from its major moisture sources and which then results in precipitation in that region, we explore i) whether the MTP from the main moisture sources for the Arctic region is linked with interannual fluctuations in the extent of Arctic Sea ice superimposed on its decline and ii) the role of extreme MTP events in the inter-daily change of the Arctic Sea Ice Extent (SIE) when extreme MTP simultaneously arrives from the four main moisture regions that supply it. The results suggest 1) that ice-melting at the scale of interannual fluctuations against the trend is favoured by an increase in moisture transport in summer, autumn, and winter, and a decrease in spring and, 2) on a daily basis, extreme humidity transport increases the formation of ice in winter and decreases it in spring, summer and autumn; in these 3 seasons it therefore contributes to Arctic Sea Ice Melting. These patterns differ sharply from that linked to the decline, especially in summer when the opposite trend applies.

scholarly journals Arctic sea ice area in CMIP3 and CMIP5 climate model ensembles – variability and change

2015 ◽  
Vol 9 (1) ◽  
pp. 1077-1131 ◽  
Author(s):  
V. A. Semenov ◽  
T. Martin ◽  
L. K. Behrens ◽  
M. Latif
Keyword(s):  
Sea Ice ◽  
21St Century ◽  
Seasonal Cycle ◽  
Climate Models ◽  
Barents Sea ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Cmip5 Models ◽  
The Barents Sea ◽  
Arctic Sea

Abstract. The shrinking Arctic sea ice cover observed during the last decades is probably the clearest manifestation of ongoing climate change. While climate models in general reproduce the sea ice retreat in the Arctic during the 20th century and simulate further sea ice area loss during the 21st century in response to anthropogenic forcing, the models suffer from large biases and the model results exhibit considerable spread. The last generation of climate models from World Climate Research Programme Coupled Model Intercomparison Project Phase 5 (CMIP5), when compared to the previous CMIP3 model ensemble and considering the whole Arctic, were found to be more consistent with the observed changes in sea ice extent during the recent decades. Some CMIP5 models project strongly accelerated (non-linear) sea ice loss during the first half of the 21st century. Here, complementary to previous studies, we compare results from CMIP3 and CMIP5 with respect to regional Arctic sea ice change. We focus on September and March sea ice. Sea ice area (SIA) variability, sea ice concentration (SIC) variability, and characteristics of the SIA seasonal cycle and interannual variability have been analysed for the whole Arctic, termed Entire Arctic, Central Arctic and Barents Sea. Further, the sensitivity of SIA changes to changes in Northern Hemisphere (NH) averaged temperature is investigated and several important dynamical links between SIA and natural climate variability involving the Atlantic Meridional Overturning Circulation (AMOC), North Atlantic Oscillation (NAO) and sea level pressure gradient (SLPG) in the western Barents Sea opening serving as an index of oceanic inflow to the Barents Sea are studied. The CMIP3 and CMIP5 models not only simulate a coherent decline of the Arctic SIA but also depict consistent changes in the SIA seasonal cycle and in the aforementioned dynamical links. The spatial patterns of SIC variability improve in the CMIP5 ensemble, particularly in summer. Both CMIP ensembles depict a significant link between the SIA and NH temperature changes. Our analysis suggests that, on average, the sensitivity of SIA to external forcing is enhanced in the CMIP5 models. The Arctic SIA variability response to anthropogenic forcing is different in CMIP3 and CMIP5. While the CMIP3 models simulate increased variability in March and September, the CMIP5 ensemble shows the opposite tendency. A noticeable improvement in the simulation of summer SIA by the CMIP5 models is often accompanied by worse results for winter SIA characteristics. The relation between SIA and mean AMOC changes is opposite in September and March, with March SIA changes being positively correlated with AMOC slowing. Finally, both CMIP ensembles demonstrate an ability to capture, at least qualitatively, important dynamical links of SIA to decadal variability of the AMOC, NAO and SLPG. SIA in the Barents Sea is strongly overestimated by the majority of the CMIP3 and CMIP5 models, and projected SIA changes are characterized by a large spread giving rise to high uncertainty.

scholarly journals Assessment of Arctic sea ice simulations in CMIP5 models

2018 ◽  
Author(s):  
Liping Wu ◽  
Xiao-Yi Yang ◽  
Jianyu Hu
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Model Performance ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Cmip5 Models ◽  
Late 20Th Century ◽  
Arctic Sea ◽  
Potential Factors

Abstract. The Arctic sea ice cover has experienced an unprecedented decline since the late 20th century. As a result, the feedback of sea ice anomalies to atmospheric circulation has been increasingly evidenced. While the climate models almost consistently reproduce the downward trend of sea ice cover, great dispersion between them still exists. To evaluate the model performance in simulating Arctic sea ice and its potential role in climate change, we constructed a reasonable metric by synthesizing the linear trends and anomalies of the sea ice. We particularly focus on the Barents and Kara seas, where the sea ice anomalies have the greatest potential to feedback the atmosphere. Models can be grouped into three categories according to this criterion. The strong contrast among the multi-model ensemble means in different groups demonstrates the robustness and rationality of this method. The potential factors accounting for the different performance of climate models are further explored. The result shows that the model performance depends more on the ozone datasets prescribed by model rather than on the chemistry representation of ozone.

scholarly journals Nonuniform Contribution of Internal Variability to Recent Arctic Sea Ice Loss

2019 ◽  
Vol 32 (13) ◽  
pp. 4039-4053 ◽  
Author(s):  
Mark England ◽  
Alexandra Jahn ◽  
Lorenzo Polvani
Keyword(s):  
Sea Ice ◽  
Barents Sea ◽  
Late Summer ◽  
Internal Variability ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Cmip5 Models ◽  
East Siberian Sea ◽  
Arctic Sea

Abstract Over the last half century, the Arctic sea ice cover has declined dramatically. Current estimates suggest that, for the Arctic as a whole, nearly one-half of the observed loss of summer sea ice cover is not due to anthropogenic forcing but rather is due to internal variability. Using the 40 members of the Community Earth System Model Large Ensemble (CESM-LE), our analysis provides the first regional assessment of the role of internal variability on the observed sea ice loss. The CESM-LE is one of the best available models for such an analysis, because it performs better than other CMIP5 models for many metrics of importance. Our study reveals that the local contribution of internal variability has a large range and strongly depends on the month and region in question. We find that the pattern of internal variability is highly nonuniform over the Arctic, with internal variability accounting for less than 10% of late summer (August–September) East Siberian Sea sea ice loss but more than 60% of the Kara Sea sea ice loss. In contrast, spring (April–May) sea ice loss, notably in the Barents Sea, has so far been dominated by internal variability.

scholarly journals Persistent Freshening of the Arctic Ocean and Changes in the North Atlantic Salinity Caused by Arctic Sea Ice Decline

2021 ◽  
Author(s):  
Hui Li ◽  
Alexey Fedorov
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
North Atlantic ◽  
Arctic Sea Ice ◽  
Meridional Overturning Circulation ◽  
The Arctic ◽  
Global Ocean ◽  
Ice Melting ◽  
Sea Ice Decline ◽  
Arctic Sea

Abstract Arctic sea ice has been declining over past several decades with the largest ice loss occurring in summer. This implies a strengthening of the sea ice seasonal cycle. Here, we examine global ocean salinity response to such changes of Arctic sea ice using simulations wherein we impose a radiative heat imbalance at the sea ice surface, inducing a sea ice decline comparable to the observed. The imposed perturbation leads to enhanced seasonal melting and a rapid retreat of Arctic sea ice within the first 5-10 years. We then observe a gradual freshening of the upper Arctic ocean that continues for about a century. The freshening is most pronounced within the central Arctic, including the Beaufort gyre, and is attributed to excess surface freshwater associated with the stronger seasonal sea ice melting, as well as a greater upper-ocean freshwater storage due to changes in ocean circulation. The freshening of the Nordic Seas can also occur via a distillation-like process in which denser saline waters with increased salinity are exported to the subtropical/tropical North Atlantic by meridional overturning circulation. Thus, enhanced seasonal sea ice melting in a warmer climate can lead to a persistent Arctic freshening with large impacts on the global salinity distribution.

scholarly journals Arctic Sea Ice Growth in Response to Synoptic- and Large-Scale Atmospheric Forcing from CMIP5 Models

2020 ◽  
Vol 33 (14) ◽  
pp. 6083-6099
Author(s):  
Lei Cai ◽  
Vladimir A. Alexeev ◽  
John E. Walsh
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Cmip5 Models ◽  
Atmospheric Forcing ◽  
Large Scale Circulation ◽  
Ice Growth ◽  
Circulation Patterns ◽  
Arctic Sea

AbstractWe explore the response of wintertime Arctic sea ice growth to strong cyclones and to large-scale circulation patterns on the daily scale using Earth system model output in phase 5 of the Coupled Model Intercomparison Project (CMIP5). A combined metrics ranking method selects three CMIP5 models that are successful in reproducing the wintertime Arctic dipole (AD) pattern. A cyclone identification method is applied to select strong cyclones in two subregions in the North Atlantic to examine their different impacts on sea ice growth. The total change of sea ice growth rate (SGR) is split into those respectively driven by the dynamic and thermodynamic atmospheric forcing. Three models reproduce the downward longwave radiation anomalies that generally match thermodynamic SGR anomalies in response to both strong cyclones and large-scale circulation patterns. For large-scale circulation patterns, the negative AD outweighs the positive Arctic Oscillation in thermodynamically inhibiting SGR in both impact area and magnitude. Despite the disagreement on the spatial distribution, the three CMIP5 models agree on the weaker response of dynamic SGR than thermodynamic SGR. As the Arctic warms, the thinner sea ice results in more ice production and smaller spatial heterogeneity of thickness, dampening the SGR response to the dynamic forcing. The higher temperature increases the specific heat of sea ice, thus dampening the SGR response to the thermodynamic forcing. In this way, the atmospheric forcing is projected to contribute less to change daily SGR in the future climate.

scholarly journals Arctic sea-ice-free season projected to extend into autumn

2019 ◽  
Vol 13 (1) ◽  
pp. 79-96 ◽  
Author(s):  
Marion Lebrun ◽  
Martin Vancoppenolle ◽  
Gurvan Madec ◽  
François Massonnet
Keyword(s):  
Sea Ice ◽  
Growth Period ◽  
Basic Feature ◽  
Ocean Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Cmip5 Models ◽  
Ice Growth ◽  
Arctic Sea

Abstract. The recent Arctic sea ice reduction comes with an increase in the ice-free season duration, with comparable contributions of earlier ice retreat and later advance. CMIP5 models all project that the trend towards later advance should progressively exceed and ultimately double the trend towards earlier retreat, causing the ice-free season to shift into autumn. We show that such a shift is a basic feature of the thermodynamic response of seasonal ice to warming. The detailed analysis of an idealised thermodynamic ice–ocean model stresses the role of two seasonal amplifying feedbacks. The summer feedback generates a 1.6-day-later advance in response to a 1-day-earlier retreat. The underlying physics are the property of the upper ocean to absorb solar radiation more efficiently than it can release heat right before ice advance. The winter feedback is comparatively weak, prompting a 0.3-day-earlier retreat in response to a 1-day shift towards later advance. This is because a shorter growth season implies thinner ice, which subsequently melts away faster. However, the winter feedback is dampened by the relatively long ice growth period and by the inverse relationship between ice growth rate and thickness. At inter-annual timescales, the thermodynamic response of ice seasonality to warming is obscured by inter-annual variability. Nevertheless, in the long term, because all feedback mechanisms relate to basic and stable elements of the Arctic climate system, there is little inter-model uncertainty on the projected long-term shift into autumn of the ice-free season.

scholarly journals Large-Scale Atmospheric Warming in Winter and the Arctic Sea Ice Retreat

2016 ◽  
Vol 29 (8) ◽  
pp. 2869-2888 ◽  
Author(s):  
Srdjan Dobricic ◽  
Elisabetta Vignati ◽  
Simone Russo
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Large Scale ◽  
Southern Oscillation ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Melting ◽  
Near Surface ◽  
Arctic Sea

Abstract The ongoing shrinkage of the Arctic sea ice cover is likely linked to the global temperature rise, the pronounced warming in the Arctic, and possibly weather anomalies in the midlatitudes. By evaluating independent components of global atmospheric energy anomalies in winters from 1980 to 2015, the study finds the link between the sea ice melting in the Arctic and the combination of only three well-known atmospheric oscillation patterns approximating observed spatial variations of near-surface temperature trends in winter. The three patterns are the North Atlantic Oscillation (NAO), Scandinavian blocking (SB), and El Niño–Southern Oscillation (ENSO). The first two are directly related to the ongoing sea ice cover shrinkage in the Barents Sea and the hemispheric increase of near-surface temperature. By independent dynamical processes they connect the sea ice melting and related atmospheric perturbations in the Arctic either with the negative phase of the NAO or the negative trend of atmospheric temperatures over the tropical Pacific. The study further shows that the ongoing sea ice melting may often imply the formation of large-scale circulation patterns bringing the recent trend of colder winters in densely populated areas like Europe and North America.

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