Insights for the Future of Arctic Sea Ice from the CMIP6 lig127k Experiment

Author(s):  
Esther C. Brady ◽  
Bette L. Otto-Bliesner ◽  
Masa Kageyama ◽  

<p>New to CMIP6 is the Tier 1 lig127k experiment, designed to address the climate responses to stronger orbital forcing than the midHolocene experiment, using the same state-of-the-art models and following a common experimental protocol. We present a multi-model ensemble of 17 climate models, all of which (except for two) have also completed the CMIP6 DECK experiments, looking at the lig127k Arctic’s responses across models and the relationships with each model’s Equilibrium Climate Sensitivity (ECS), preindustrial sea ice thickness and 127ka temperature anomalies.</p><p>Boreal insolation anomalies at 127 ka enhance the seasonal cycle of Arctic sea ice, though with notable differences among the models. The consensus from the lig127k sea ice distributions is a reduced minimum (August-September) summer sea ice extent in the Arctic as compared to the piControl simulations. Sea ice remains above 15% concentrations over the central Arctic Ocean in all but one of the lig127k simulations. More than half of the models simulate a retreat of the Arctic minimum ice edge similar to the average of the last 2 decades. The lig127k minimum Arctic sea ice area anomalies show a strong negative correlation with the Arctic (60-90°N) annual surface temperature anomalies but only a weak correlation with the corresponding June-July-August (JJA) temperature anomalies. Memory in the ocean and cryosphere provide feedbacks to maintain larger positive temperature anomalies, December-January-February (DJF) and annually, in the Arctic than in JJA. The models contributing to the lig127k ensemble have an ECS varying from 2.1 to 5.3°C. There is a notable relationship between the ECS and simulation of lig127k minimum Arctic sea ice area.  With very limited Arctic sea ice proxies for 127 ka, and with evolving interpretation of the relationships of these proxies with sea ice coverage, it is still difficult to rule out the high or low values of ECS from the proxy data.</p>

2014 ◽  
Vol 8 (1) ◽  
pp. 1383-1406 ◽  
Author(s):  
P. J. Hezel ◽  
T. Fichefet ◽  
F. Massonnet

Abstract. Almost all global climate models and Earth system models that participated in the Coupled Model Intercomparison Project 5 (CMIP5) show strong declines in Arctic sea ice extent and volume under the highest forcing scenario of the Radiative Concentration Pathways (RCPs) through 2100, including a transition from perennial to seasonal ice cover. Extended RCP simulations through 2300 were completed for a~subset of models, and here we examine the time evolution of Arctic sea ice in these simulations. In RCP2.6, the summer Arctic sea ice extent increases compared to its minimum following the peak radiative forcing in 2044 in all 9 models. RCP4.5 demonstrates continued summer Arctic sea ice decline due to continued warming on longer time scales. These two scenarios imply that summer sea ice extent could begin to recover if and when radiative forcing from greenhouse gas concentrations were to decrease. In RCP8.5 the Arctic Ocean reaches annually ice-free conditions in 7 of 9 models. The ensemble of simulations completed under the extended RCPs provide insight into the global temperature increase at which sea ice disappears in the Arctic and reversibility of declines in seasonal sea ice extent.


2021 ◽  
Author(s):  
Stephanie Hay ◽  
Paul Kusnher

<p>Antarctic sea ice has gradually increased in extent over the forty-year-long satellite record, in contrast with the clear decrease in sea-ice extent seen in the Arctic over the same time period. However, state-of-the-art climate models ubiquitously project Antarctic sea-ice to decrease over the coming century, much as they do for Arctic sea-ice. Several recent years have also seen record low Antarctic sea-ice. It is therefore of interest to understand what the climate response to Antarctic sea-ice loss will be. </p><p>We have carried out new fully coupled climate model simulations to assess the response to sea-ice loss in either hemisphere separately or coincidentally under different albedo parameter settings to determine the relative importance of each. By perturbing the albedo of the snow overlying the sea ice and the albedo of the bare sea ice, we obtain a suite of simulations to assess the linearity and additivity of sea-ice loss. We find the response to sea-ice loss in each hemisphere exhibits a high degree of additivity, and can simply be decomposed into responses due to loss in each hemisphere separately. We find that the response to Antarctic sea-ice loss exceeds that of Arctic sea-ice loss in the tropics, and that Antarctic sea-ice loss leads to statistically significant Arctic warming, while the opposite is not true.</p><p>With these new simulations and one in which CO<sub>2</sub> is instantaneously doubled , we can further characterize the response to sea-ice loss from each hemisphere using an extension to classical pattern scaling that includes three controlling parameters. This allows us to simultaneously compute the sensitivity patterns to Arctic sea-ice loss, Antarctic sea-ice loss, and to tropical warming. The statistically significant response to Antarctic sea-ice loss in the Northern Hemisphere extratropics is found to be mediated by tropical warming and small amounts of Arctic sea-ice loss.</p>


2010 ◽  
Vol 56 (200) ◽  
pp. 1115-1121 ◽  
Author(s):  
Vladimir M. Kattsov ◽  
Vladimir E. Ryabinin ◽  
James E. Overland ◽  
Mark C. Serreze ◽  
Martin Visbeck ◽  
...  

AbstractOver the period of modern satellite observations, Arctic sea-ice extent at the end of the melt season (September) has declined at a rate of >11% per decade, and there is evidence that the rate of decline has accelerated during the last decade. While climate models project further decreases in sea- ice mass and extent through the 21st century, the model ensemble mean trend over the period of instrumental records is smaller than observed. Possible reasons for the apparent discrepancy between observations and model simulations include observational uncertainties, vigorous unforced climate variability in the high latitudes, and limitations and shortcomings of the models stemming in particular from gaps in understanding physical process. The economic significance of a seasonally sea-ice-free future Arctic, the increased connectivity of a warmer Arctic with changes in global climate, and large uncertainties in magnitude and timing of these impacts make the problem of rapid sea-ice loss in the Arctic a grand challenge of climate science. Meaningful prediction/projection of the Arctic sea-ice conditions for the coming decades and beyond requires determining priorities for observations and model development, evaluation of the ability of climate models to reproduce the observed sea-ice behavior as a part of the broader climate system, improved attribution of the causes of Arctic sea-ice change, and improved understanding of the predictability of sea-ice conditions on seasonal through centennial timescales in the wider context of the polar climate predictability.


2021 ◽  
Vol 34 (9) ◽  
pp. 3609-3627
Author(s):  
Zili Shen ◽  
Anmin Duan ◽  
Dongliang Li ◽  
Jinxiao Li

AbstractThe capability of 36 models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6) and their 24 CMIP5 counterparts in simulating the mean state and variability of Arctic sea ice cover for the period 1979–2014 is evaluated. In addition, a sea ice cover performance score for each CMIP5 and CMIP6 model is provided that can be used to reduce the spread in sea ice projections through applying weighted averages based on the ability of models to reproduce the historical sea ice state. Results show that the seasonal cycle of the Arctic sea ice extent (SIE) in the multimodel ensemble (MME) mean of the CMIP6 simulations agrees well with observations, with a MME mean error of less than 15% in any given month relative to the observations. CMIP6 has a smaller intermodel spread in climatological SIE values during summer months than its CMIP5 counterpart. In terms of the monthly SIE trends, the CMIP6 MME mean shows a substantial reduction in the positive bias relative to the observations compared with that of CMIP5. The spread of September SIE trends is very large, not only across different models but also across different ensemble members of the same model, indicating a strong influence of internal variability on SIE evolution. Based on the assumptions that the simulations of CMIP6 models are from the same distribution and that models have no bias in response to external forcing, we can infer that internal variability contributes to approximately 22% ± 5% of the September SIE trend over the period 1979–2014.


2014 ◽  
Vol 8 (4) ◽  
pp. 1195-1204 ◽  
Author(s):  
P. J. Hezel ◽  
T. Fichefet ◽  
F. Massonnet

Abstract. Almost all global climate models and Earth system models that participated in the Coupled Model Intercomparison Project 5 (CMIP5) show strong declines in Arctic sea ice extent and volume under the highest forcing scenario of the representative concentration pathways (RCPs) through 2100, including a transition from perennial to seasonal ice cover. Extended RCP simulations through 2300 were completed for a~subset of models, and here we examine the time evolution of Arctic sea ice in these simulations. In RCP2.6, the summer Arctic sea ice extent increases compared to its minimum following the peak radiative forcing in 2044 in all nine models. RCP4.5 demonstrates continued summer Arctic sea ice decline after the forcing stabilizes due to continued warming on longer timescales. Based on the analysis of these two scenarios, we suggest that Arctic summer sea ice extent could begin to recover if and when radiative forcing from greenhouse gas concentrations were to decrease. In RCP8.5 the Arctic Ocean reaches annually ice-free conditions in seven of nine models. The ensemble of simulations completed under the extended RCPs provide insight into the global temperature increase at which sea ice disappears in the Arctic and the reversibility of declines in seasonal sea ice extent.


2021 ◽  
Vol 2 (1) ◽  
Author(s):  
David Docquier ◽  
Torben Koenigk

AbstractArctic sea ice has been retreating at an accelerating pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) and select models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to lower Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of future Arctic sea-ice loss when including all CMIP6 models.


2009 ◽  
Vol 22 (1) ◽  
pp. 165-176 ◽  
Author(s):  
R. W. Lindsay ◽  
J. Zhang ◽  
A. Schweiger ◽  
M. Steele ◽  
H. Stern

Abstract The minimum of Arctic sea ice extent in the summer of 2007 was unprecedented in the historical record. A coupled ice–ocean model is used to determine the state of the ice and ocean over the past 29 yr to investigate the causes of this ice extent minimum within a historical perspective. It is found that even though the 2007 ice extent was strongly anomalous, the loss in total ice mass was not. Rather, the 2007 ice mass loss is largely consistent with a steady decrease in ice thickness that began in 1987. Since then, the simulated mean September ice thickness within the Arctic Ocean has declined from 3.7 to 2.6 m at a rate of −0.57 m decade−1. Both the area coverage of thin ice at the beginning of the melt season and the total volume of ice lost in the summer have been steadily increasing. The combined impact of these two trends caused a large reduction in the September mean ice concentration in the Arctic Ocean. This created conditions during the summer of 2007 that allowed persistent winds to push the remaining ice from the Pacific side to the Atlantic side of the basin and more than usual into the Greenland Sea. This exposed large areas of open water, resulting in the record ice extent anomaly.


2012 ◽  
Vol 25 (5) ◽  
pp. 1431-1452 ◽  
Author(s):  
Alexandra Jahn ◽  
Kara Sterling ◽  
Marika M. Holland ◽  
Jennifer E. Kay ◽  
James A. Maslanik ◽  
...  

To establish how well the new Community Climate System Model, version 4 (CCSM4) simulates the properties of the Arctic sea ice and ocean, results from six CCSM4 twentieth-century ensemble simulations are compared here with the available data. It is found that the CCSM4 simulations capture most of the important climatological features of the Arctic sea ice and ocean state well, among them the sea ice thickness distribution, fraction of multiyear sea ice, and sea ice edge. The strongest bias exists in the simulated spring-to-fall sea ice motion field, the location of the Beaufort Gyre, and the temperature of the deep Arctic Ocean (below 250 m), which are caused by deficiencies in the simulation of the Arctic sea level pressure field and the lack of deep-water formation on the Arctic shelves. The observed decrease in the sea ice extent and the multiyear ice cover is well captured by the CCSM4. It is important to note, however, that the temporal evolution of the simulated Arctic sea ice cover over the satellite era is strongly influenced by internal variability. For example, while one ensemble member shows an even larger decrease in the sea ice extent over 1981–2005 than that observed, two ensemble members show no statistically significant trend over the same period. It is therefore important to compare the observed sea ice extent trend not just with the ensemble mean or a multimodel ensemble mean, but also with individual ensemble members, because of the strong imprint of internal variability on these relatively short trends.


2019 ◽  
Vol 32 (5) ◽  
pp. 1361-1380 ◽  
Author(s):  
J. Ono ◽  
H. Tatebe ◽  
Y. Komuro

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.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Tsubasa Kodaira ◽  
Takuji Waseda ◽  
Takehiko Nose ◽  
Jun Inoue

AbstractArctic sea ice is rapidly decreasing during the recent period of global warming. One of the significant factors of the Arctic sea ice loss is oceanic heat transport from lower latitudes. For months of sea ice formation, the variations in the sea surface temperature over the Pacific Arctic region were highly correlated with the Pacific Decadal Oscillation (PDO). However, the seasonal sea surface temperatures recorded their highest values in autumn 2018 when the PDO index was neutral. It is shown that the anomalous warm seawater was a rapid ocean response to the southerly winds associated with episodic atmospheric blocking over the Bering Sea in September 2018. This warm seawater was directly observed by the R/V Mirai Arctic Expedition in November 2018 to significantly delay the southward sea ice advance. If the atmospheric blocking forms during the PDO positive phase in the future, the annual maximum Arctic sea ice extent could be dramatically reduced.


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