scholarly journals The effect of decreasing seasonal sea-ice cover on the winter Bering Sea pollock fishery

2012 ◽  
Vol 69 (7) ◽  
pp. 1148-1159 ◽  
Author(s):  
Lisa Pfeiffer ◽  
Alan C. Haynie
Keyword(s):  
Sea Ice ◽  
Bering Sea ◽  
Climate Models ◽  
Global Climate ◽  
Ice Cover ◽  
Global Climate Models ◽  
Retrospective Data ◽  
Sea Ice Extent ◽  
Fishing Season ◽  
Eastern Bering Sea

Abstract Pfeiffer, L., and Haynie, A. C. 2012. The effect of decreasing seasonal sea-ice cover on the winter Bering Sea pollock fishery. – ICES Journal of Marine Science, 69: . The winter fishing season for eastern Bering Sea pollock (Theragra chalcogramma) is during the period of maximum seasonal sea-ice extent, but harvesters avoid fishing in ice-covered waters. Global climate models predict a 40% reduction in winter ice cover by 2050, with potential implications for the costs incurred by vessels travelling to and around their fishing grounds and the value of their catch. Additionally, it may open entirely new areas to fishing. Using retrospective data from 1999 to 2009, a period of extensive annual climate variation, the variation in important characteristics of the fishery is analysed. When ice is present, it restricts a portion of the fishing grounds, but in general, ice-restricted areas have lower expected profits at the time of restriction than the areas left open. Some areas show a change in effort in warm years relative to cold, but the global redistribution of effort attributable to ice cover is small. This is largely because the winter fishery is driven by the pursuit of roe-bearing fish whose spawning location is stable in the southern part of the fishing grounds.

scholarly journals Modeled Arctic sea ice evolution through 2300 in CMIP5 extended RCPs

2014 ◽  
Vol 8 (1) ◽  
pp. 1383-1406 ◽  
Author(s):  
P. J. Hezel ◽  
T. Fichefet ◽  
F. Massonnet
Keyword(s):  
Sea Ice ◽  
Radiative Forcing ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Arctic Sea Ice Extent

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.

scholarly journals Pan-Arctic and Regional Sea Ice Predictability: Initialization Month Dependence

2014 ◽  
Vol 27 (12) ◽  
pp. 4371-4390 ◽  
Author(s):  
J. J. Day ◽  
S. Tietsche ◽  
E. Hawkins
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Regional Analysis ◽  
Early Summer ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
Sea Ice Extent ◽  
The North ◽  
Arctic Sea

Abstract Seasonal-to-interannual predictions of Arctic sea ice may be important for Arctic communities and industries alike. Previous studies have suggested that Arctic sea ice is potentially predictable but that the skill of predictions of the September extent minimum, initialized in early summer, may be low. The authors demonstrate that a melt season “predictability barrier” and two predictability reemergence mechanisms, suggested by a previous study, are robust features of five global climate models. Analysis of idealized predictions with one of these models [Hadley Centre Global Environment Model, version 1.2 (HadGEM1.2)], initialized in January, May and July, demonstrates that this predictability barrier exists in initialized forecasts as well. As a result, the skill of sea ice extent and volume forecasts are strongly start date dependent and those that are initialized in May lose skill much faster than those initialized in January or July. Thus, in an operational setting, initializing predictions of extent and volume in July has strong advantages for the prediction of the September minimum when compared to predictions initialized in May. Furthermore, a regional analysis of sea ice predictability indicates that extent is predictable for longer in the seasonal ice zones of the North Atlantic and North Pacific than in the regions dominated by perennial ice in the central Arctic and marginal seas. In a number of the Eurasian shelf seas, which are important for Arctic shipping, only the forecasts initialized in July have continuous skill during the first summer. In contrast, predictability of ice volume persists for over 2 yr in the central Arctic but less in other regions.

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>

scholarly journals Future Arctic marine access: analysis and evaluation of observations, models, and projections of sea ice

2012 ◽  
Vol 6 (5) ◽  
pp. 3963-3998 ◽  
Author(s):  
T. S. Rogers ◽  
J. E. Walsh ◽  
T. S. Rupp ◽  
L. W. Brigham ◽  
M. Sfraga
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Model Performance ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Sea Ice Extent ◽  
State And Local

Abstract. There is an emerging need for regional applications of sea ice projections to provide more accuracy and greater detail to scientists, national, state and local planners, and other stakeholders. The present study offers a prototype for a comprehensive, interdisciplinary study to bridge observational data, climate model simulations, and user needs. The study's first component is an observationally-based evaluation of Arctic sea ice trends during 1980–2008, with an emphasis on seasonal and regional differences relative to the overall pan-Arctic trend. Regional sea ice los has varied, with a significantly larger decline of winter maximum (January–March) extent in the Atlantic region than in other sectors. A lead-lag regression analysis of Atlantic sea ice extent and ocean temperatures indicates that reduced sea ice extent is associated with increased Atlantic Ocean temperatures. Correlations between the two variables are greater when ocean temperatures lag rather than lead sea ice. The performance of 13 global climate models is evaluated using three metrics to compare sea ice simulations with the observed record. We rank models over the pan-Arctic domain and regional quadrants, and synthesize model performance across several different studies. The best performing models project reduced ice cover across key access routes in the Arctic through 2100, with a lengthening of seasons for marine operations by 1–3 months. This assessment suggests that the Northwest and Northeast Passages hold potential for enhanced marine access to the Arctic in the future, including shipping and resource development opportunities.

scholarly journals Mid-Holocene Antarctic sea-ice increase driven by marine ice sheet retreat

2020 ◽  
Author(s):  
Kate E. Ashley ◽  
James A. Bendle ◽  
Robert McKay ◽  
Johan Etourneau ◽  
Francis J. Jimenez-Espejo ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Feedback Mechanism ◽  
Global Climate Models ◽  
Ice Shelf ◽  
Sea Ice Extent ◽  
Glacial Meltwater ◽  
Ice Shelves ◽  
Antarctic Sea Ice

Abstract. Over recent decades Antarctic sea-ice extent has increased, alongside widespread ice shelf thinning and freshening of waters along the Antarctic margin. In contrast, Earth system models generally simulate a decrease in sea ice. Circulation of water masses beneath large cavity ice shelves is not included in current models and may be a driver of this phenomena. We examine a Holocene sediment core off East Antarctica that records the Neoglacial transition, the last major baseline shift of Antarctic sea-ice, and part of a late-Holocene global cooling trend. We provide a multi-proxy record of Holocene glacial meltwater input, sediment transport and sea-ice variability which includes. Our record, supported by high-resolution ocean modelling, shows that a rapid Antarctic sea-ice increase occurred against a backdrop of increasing glacial meltwater input and gradual climate warming. We suggest that mid-Holocene ice shelf cavity expansion led to supercooling of surface waters and sea-ice growth which slowed basal ice shelf melting. Incorporating this feedback mechanism into global climate models will be important for future projections of Antarctic changes.

scholarly journals Albedo parametrization and reversibility of sea ice decay

2012 ◽  
Vol 19 (1) ◽  
pp. 81-94 ◽  
Author(s):  
M. Müller-Stoffels ◽  
R. Wackerbauer
Keyword(s):  
Surface Energy ◽  
Sea Ice ◽  
Radiative Forcing ◽  
Climate Models ◽  
Global Climate ◽  
Open Water ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
Surface Energy Budget

Abstract. The Arctic's sea ice cover has been receding rapidly in recent years, and global climate models typically predict a further decline over the next century. It is an open question whether a possible loss of Arctic sea ice is reversible. We study the stability of Arctic model sea ice in a conceptual, two-dimensional energy-based regular network model of the ice-ocean layer that considers ARM's longwave radiative budget data and SHEBA albedo measurements. Seasonal ice cover, perennial ice and perennial open water are asymptotic states accessible by the model. We show that the shape of albedo parameterization near the melting temperature differentiates between reversible continuous sea ice decrease under atmospheric forcing and hysteresis behavior. Fixed points induced solely by the surface energy budget are essential for understanding the interaction of surface energy with the radiative forcing and the underlying body of ice/water, particularly close to a bifurcation point. Future studies will explore ice edge stability and reversibility in this lattice model, generalized to a latitudinal transect with spatiotemporal lateral atmospheric heat transfer and high spatial resolution.

scholarly journals Wave-triggered breakup in the marginal ice zone generates lognormal floe size distributions

2021 ◽  
Author(s):  
Nicolas Guillaume Alexandre Mokus ◽  
Fabien Montiel
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Harmonic Wave ◽  
Statistical Significance ◽  
Wave Spectrum ◽  
Ocean Waves ◽  
Ice Cover ◽  
Global Climate Models ◽  
Ice Breakup

Abstract. Fragmentation of the sea ice cover by ocean waves is an important mechanism impacting ice evolution. Fractured ice is more sensitive to melt, leading to a local reduction in ice concentration, facilitating wave propagation. A positive feedback loop, accelerating sea ice retreat, is then introduced. Despite recent efforts to incorporate this process and the resulting floe size distribution (FSD) into the sea ice components of global climate models (GCM), the physics governing ice breakup under wave action remains poorly understood, and its parametrisation highly simplified. We propose a two-dimensional numerical model of wave-induced sea ice breakup to estimate the FSD resulting from repeated fracture events. This model, based on linear water wave theory and viscoelastic sea ice rheology, solves for the scattering of an incoming time-harmonic wave by the ice cover and derives the corresponding strain field. Fracture occurs when the strain exceeds an empirical threshold. The geometry is then updated for the next iteration of the breakup procedure. The resulting FSD is analysed for both monochromatic and polychromatic forcings. For the latter results, FSDs obtained for discrete frequencies are combined appropriately following a prescribed wave spectrum. We find that under realistic wave forcing, lognormal FSDs emerge consistently in a large variety of model configurations. Care is taken to evaluate the statistical significance of this finding. This result contrasts with the power-law FSD behaviour often assumed by modellers. We discuss the properties of these modelled distributions, with respect to the ice rheological properties and the forcing waves. The projected output will be used to improve empirical parametrisations used to couple sea ice and ocean waves GCM components.

scholarly journals Future Arctic marine access: analysis and evaluation of observations, models, and projections of sea ice

2013 ◽  
Vol 7 (1) ◽  
pp. 321-332 ◽  
Author(s):  
T. S. Rogers ◽  
J. E. Walsh ◽  
T. S. Rupp ◽  
L. W. Brigham ◽  
M. Sfraga
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Model Performance ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Sea Ice Extent ◽  
State And Local

Abstract. There is an emerging need for regional applications of sea ice projections to provide more accuracy and greater detail to scientists, national, state and local planners, and other stakeholders. The present study offers a prototype for a comprehensive, interdisciplinary study to bridge observational data, climate model simulations, and user needs. The study's first component is an observationally based evaluation of Arctic sea ice trends during 1980–2008, with an emphasis on seasonal and regional differences relative to the overall pan-Arctic trend. Regional sea ice loss has varied, with a significantly larger decline of winter maximum (January–March) extent in the Atlantic region than in other sectors. A lead–lag regression analysis of Atlantic sea ice extent and ocean temperatures indicates that reduced sea ice extent is associated with increased Atlantic Ocean temperatures. Correlations between the two variables are greater when ocean temperatures lag rather than lead sea ice. The performance of 13 global climate models is evaluated using three metrics to compare sea ice simulations with the observed record. We rank models over the pan-Arctic domain and regional quadrants and synthesize model performance across several different studies. The best performing models project reduced ice cover across key access routes in the Arctic through 2100, with a lengthening of seasons for marine operations by 1–3 months. This assessment suggests that the Northwest and Northeast Passages hold potential for enhanced marine access to the Arctic in the future, including shipping and resource development opportunities.

scholarly journals Modeled Arctic sea ice evolution through 2300 in CMIP5 extended RCPs

2014 ◽  
Vol 8 (4) ◽  
pp. 1195-1204 ◽  
Author(s):  
P. J. Hezel ◽  
T. Fichefet ◽  
F. Massonnet
Keyword(s):  
Sea Ice ◽  
Radiative Forcing ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Arctic Sea Ice Extent

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.

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

2020 ◽  
Author(s):  
Glenn Rudebusch ◽  
Francis Diebold
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
Economic Consequences ◽  
Sea Ice Extent ◽  
Wide Range ◽  
Arctic Sea

<p>The downward trend in the amount of Arctic sea ice is a key factor determining the pace and intensity of future global climate change. Diminished sea ice also has a wide range of other environmental and economic consequences. 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 carbon emissions. Our long-range statistical projections also deliver probability assessments of the timing of an ice-free Arctic. These results indicate almost a 60 percent chance of an effectively ice-free Arctic Ocean during some summer in the 2030s -- much earlier than the average projection from global climate models.</p>

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