Consistency and discrepancy in the atmospheric response to Arctic sea-ice loss across climate models

2018 ◽  
Vol 11 (3) ◽  
pp. 155-163 ◽  
Author(s):  
James A. Screen ◽  
Clara Deser ◽  
Doug M. Smith ◽  
Xiangdong Zhang ◽  
Russell Blackport ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Arctic Sea Ice ◽  
Atmospheric Response ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss

scholarly journals Reassessing Sea Ice Drift and Its Relationship to Long‐Term Arctic Sea Ice Loss in Coupled Climate Models

2018 ◽  
Vol 123 (6) ◽  
pp. 4338-4359 ◽  
Author(s):  
Neil F. Tandon ◽  
Paul J. Kushner ◽  
David Docquier ◽  
Justin J. Wettstein ◽  
Camille Li
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Arctic Sea Ice ◽  
Coupled Climate Models ◽  
Ice Drift ◽  
Arctic Sea ◽  
Sea Ice Drift ◽  
Arctic Sea Ice Loss

scholarly journals Statistical indicators of Arctic sea-ice stability – prospects and limitations

2016 ◽  
Vol 10 (4) ◽  
pp. 1631-1645 ◽  
Author(s):  
Sebastian Bathiany ◽  
Bregje van der Bolt ◽  
Mark S. Williamson ◽  
Timothy M. Lenton ◽  
Marten Scheffer ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Arctic Sea Ice ◽  
Ice Coverage ◽  
Arctic Sea ◽  
Complex Models ◽  
Large Heat ◽  
Annual Time Series ◽  
Arctic Sea Ice Loss ◽  
The Relationship

Abstract. We examine the relationship between the mean and the variability of Arctic sea-ice coverage and volume in a large range of climates from globally ice-covered to globally ice-free conditions. Using a hierarchy of two column models and several comprehensive Earth system models, we consolidate the results of earlier studies and show that mechanisms found in simple models also dominate the interannual variability of Arctic sea ice in complex models. In contrast to predictions based on very idealised dynamical systems, we find a consistent and robust decrease of variance and autocorrelation of sea-ice volume before summer sea ice is lost. We attribute this to the fact that thinner ice can adjust more quickly to perturbations. Thereafter, the autocorrelation increases, mainly because it becomes dominated by the ocean water's large heat capacity when the ice-free season becomes longer. We show that these changes are robust to the nature and origin of climate variability in the models and do not depend on whether Arctic sea-ice loss occurs abruptly or irreversibly. We also show that our climate is changing too rapidly to detect reliable changes in autocorrelation of annual time series. Based on these results, the prospects of detecting statistical early warning signals before an abrupt sea-ice loss at a "tipping point" seem very limited. However, the robust relation between state and variability can be useful to build simple stochastic climate models and to make inferences about past and future sea-ice variability from only short observations or reconstructions.

scholarly journals Are 100 ensemble members enough to capture the remote atmospheric response to +2°C Arctic sea ice loss ?

2021 ◽  
pp. 1-54
Author(s):  
Y. Peings ◽  
Z. Labe ◽  
G. Magnusdottir
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Internal Variability ◽  
General Circulation Models ◽  
Arctic Sea Ice ◽  
Model Assessment ◽  
Atmospheric Response ◽  
Arctic Sea ◽  
Ocean Atmosphere ◽  
Arctic Sea Ice Loss

AbstractThis study presents results from the Polar Amplification Multimodel Intercomparison Project (PAMIP) single-year time-slice experiments that aim to isolate the atmospheric response to Arctic sea ice loss at global warming levels of +2°C. Using two General Circulation Models (GCMs), the ensemble size is increased up to 300 ensemble members, beyond the recommended 100 members. After partitioning the response in groups of 100-ensemble members, the reproducibility of the results is evaluated, with a focus on the response of the mid-latitude jet streams in the North Atlantic and North Pacific. Both atmosphere-only and coupled ocean-atmosphere PAMIP experiments are analyzed. Substantial differences in the mid-latitude response are found among the different experiment subsets, suggesting that 100-member ensembles are still significantly influenced by internal variability, which can mislead conclusions. Despite an overall stronger response, the coupled ocean-atmosphere runs exhibit greater spread due to additional ENSO-related internal variability when the ocean is interactive. The lack of consistency in the response is true for anomalies that are statistically significant according to Student’s-t and False Discovery Rate tests. This is problematic for the multi-model assessment of the response, as some of the spread may be attributed to different model sensitivities while it is due to internal variability. We propose a method to overcome this consistency issue, that allows for more robust conclusions when only 100 ensemble members are used.

Role of the internal climate variability in the atmospheric response to a sudden summer Arctic sea ice loss

2021 ◽  
Author(s):  
Steve Delhaye ◽  
Thierry Fichefet ◽  
François Massonnet ◽  
David Docquier ◽  
Christopher Roberts ◽  
...  
Keyword(s):  
Climate Variability ◽  
Sea Ice ◽  
Signal To Noise Ratio ◽  
Horizontal Resolution ◽  
Arctic Sea Ice ◽  
Atmospheric Response ◽  
Signal To Noise ◽  
Internal Climate Variability ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss

<p>The retreat of Arctic sea ice for the last four decades is a primary manifestation of the climate system response to increasing atmospheric greenhouse gas concentrations. This retreat is frequently considered as a possible driver of atmospheric circulation anomalies at mid-latitudes. However, the year-to-year evolution of the Arctic sea ice cover is also characterized by significant fluctuations attributed to internal climate variability. It is unclear how the atmosphere will respond to a near-total retreat of summer Arctic sea ice, a reality that might occur in the foreseeable future. This study uses sensitivity experiments  with higher and lower horizontal resolution configurations of three global coupled climate models to investigate the local and remote atmospheric responses to a reduction in Arctic sea ice cover during the preceding summer. Recognizing that these responses likely depend on the model itself and on its horizontal resolution, and that the model’s internally-generated climate variability may obscure the atmospheric response, we design a protocol to compare each source separately. After imposing a 15-month albedo perturbation resulting in a sudden summer Arctic sea ice loss, the remote mid-latitude climate response has a very low signal-to-noise ratio such that internal climate variability dominates the uncertainty of the response, regardless of the atmospheric variable. Indeed, more than 28, 165 and 210 members are needed to detect a robust response in surface air temperature, precipitation and sea level pressure to sea ice loss in Europe, respectively. Finally, we find that horizontal resolution plays a secondary role in the uncertainty of the atmospheric response to substantial perturbation of Arctic sea ice. These findings suggest that even with higher resolution model configurations, it is important to have large ensemble sizes to increase the signal to noise ratio for the mid-latitude atmospheric response to sea ice changes.</p>

The relative roles of Arctic and Antarctic sea-ice loss in the response to greenhouse warming

2021 ◽  
Author(s):  
Stephanie Hay ◽  
Paul Kusnher
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
Arctic Sea ◽  
Climate Model Simulations ◽  
Arctic Sea Ice Loss

<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>

scholarly journals The Effect of QBO Phase on the Atmospheric Response to Projected Arctic Sea Ice Loss in Early Winter

2019 ◽  
Vol 46 (13) ◽  
pp. 7663-7671 ◽  
Author(s):  
Zachary Labe ◽  
Yannick Peings ◽  
Gudrun Magnusdottir
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
Atmospheric Response ◽  
Early Winter ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss

scholarly journals Atmospheric response in summer linked to recent Arctic sea ice loss

2015 ◽  
Vol 141 (691) ◽  
pp. 2070-2076 ◽  
Author(s):  
R. E. Petrie ◽  
L. C. Shaffrey ◽  
R. T. Sutton
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
Atmospheric Response ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss

scholarly journals Probability Assessments of an Ice-Free Arctic: Comparing Statistical and Climate Model Projections

2021 ◽  
Author(s):  
Glenn Rudebusch ◽  
Francis Diebold
Keyword(s):  
Sea Ice ◽  
Carbon Emissions ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss

<p>Based on several decades of satellite data, we provide statistical forecasts of Arctic sea ice extent during the rest of this century. The best fitting statistical model indicates that overall sea ice coverage is declining at an increasing rate. By contrast, average projections from the CMIP5 global climate models foresee a gradual slowing of Arctic sea ice loss even in scenarios with high amounts of carbon emissions. Our long-range statistical projections also deliver <em>probability</em> assessments of the timing of an ice-free Arctic. These results indicate almost a 60 percent chance of an effectively ice-free Arctic Ocean sometime during the 2030s—much earlier than the average projection from the global climate models. Our results are also consistent with projections from bivariate regressions of sea ice extent and carbon emissions. </p>

Model and state dependence of the atmospheric response to Arctic sea-ice loss

2020 ◽  
Author(s):  
Amber Walsh ◽  
James Screen ◽  
Adam Scaife ◽  
Doug Smith ◽  
Rosie Eade
Keyword(s):  
Sea Ice ◽  
Polar Vortex ◽  
Horizontal Resolution ◽  
Arctic Sea Ice ◽  
Atmospheric Response ◽  
Model Resolution ◽  
Quasi Biennial Oscillation ◽  
Stratospheric Polar Vortex ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss

<p>The climate response to Arctic sea-ice loss is highly uncertain. There exists considerable disagreement between observational and modelling studies, and between models, for reasons that remain poorly understood. To make progress, the Polar Amplification Model Intercomparison Project (PAMIP) was designed to provide coordinated experiments, with consistent sea-ice loss applied in multiple models. Results from the PAMIP are presented, focussing on the robustness of the atmospheric response to Arctic sea-ice loss across models and, within individual models, the dependence of the response on the mean state.</p><p>In the troposphere, the mid-latitude jet is either weakened and/or shifted towards the equator in all models, albeit with varying magnitudes. We hypothesise that the magnitude of the jet response is sensitive to the atmospheric model resolution. To test this, and to more broadly identify the aspects of the atmospheric response that are sensitive to model resolution, we compare like-for-like experiments with two versions of the HadGEM3 model at low (N96) and high (N216) horizontal resolution.</p><p>The stratospheric polar vortex response to Arctic sea-ice loss is not consistent between models, and appears to be influenced by both the size of the ensemble for each model and the phase of the Quasi-Biennial Oscillation (QBO). The possible modulating effect of the QBO is further explored using new simulations with background atmospheric states representing the easterly and westerly QBO phases.</p><p>A surprising early result from the PAMIP simulations were sizeable changes in the Southern Hemisphere in response to Arctic sea-ice loss and significant changes in the Northern Hemisphere in response to Antarctic sea-ice loss, even in atmosphere-only model experiments. The robustness of such apparent interhemispheric connections across models, ensemble sizes and mean states is investigated.</p><p> </p><p> </p><p> </p>

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