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 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 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 Observation-based selection of climate models projects Arctic ice-free summers around 2035

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
David Docquier ◽  
Torben Koenigk
Keyword(s):  
Model Selection ◽  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Arctic Sea ◽  
Area And Volume

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.

Constraining Neoproterozoic subtropical low-level clouds to assess the plausibility of near-Snowball Earth states

2021 ◽  
Author(s):  
Christoph Braun ◽  
Aiko Voigt ◽  
Johannes Hörner ◽  
Joaquim G. Pinto
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Mixed Phase ◽  
Snowball Earth ◽  
Stable Range ◽  
Climate Regime ◽  
Low Level ◽  
Mixed Phase Clouds

<p>Stable waterbelt climate states with close to global ice cover challenge the classical Snowball Earth hypothesis because they provide a robust explanation for the survival of advanced marine species during the Neoproterozoic glaciations (1000 – 541 Million years ago). Whether Earth’s climate stabilizes in a waterbelt state or rushes towards a Snowball state is determined by the magnitude of the ice-albedo feedback in the subtropics, where dark, bare sea ice instead of snow-covered sea ice prevails. For a given bare sea-ice albedo, the subtropical ice-albedo feedback and thus the stable range of the waterbelt climate regime is sensitive to the albedo over ice-free ocean, which is largely determined by shortwave cloud-radiative effects (CRE). In the present-day climate, CRE are known to dominate the spread of climate sensitivity across global climate models. We here study the impact of uncertainty associated with CRE on the existence of geologically relevant waterbelt climate regimes using two global climate models and an idealized energy balance model. We find that the stable range of the waterbelt climate regime is very sensitive to the abundance of subtropical low-level mixed-phase clouds. If subtropical cloud cover is low, climate sensitivity becomes so high as to inhibit stable waterbelt states.</p><p>The treatment of mixed-phase clouds is highly uncertain in global climate models. Therefore we aim to constrain the uncertainty associated with their CRE by means of a hierarchy of global and regional simulations that span horizontal grid resolutions from 160 km to 300m, and in particular include large eddy simulations of subtropical mixed-phase clouds located over a low-latitude ice edge. In the cold waterbelt climate subtropical CRE arise from convective events caused by strong meridional temperature gradients and stratocumulus decks located in areas of large-scale descending motion. We identify the latter to dominate subtropical CRE and therefore focus our large eddy simulations on subtropical stratocumulus clouds. By conducting simulations with two extreme scenarios for the abundance of atmospheric mineral dust, which serves as ice-nucleating particles and therefore can control mixed-phase cloud physics, we aim to estimate the possible spread of CRE associated with subtropical mixed-phase clouds. From this estimate we may assess whether Neoproterozoic low-level cloud abundance may have been high enough to sustain a stable waterbelt climate regime.</p>

scholarly journals What Do Global Climate Models Tell Us about Future Arctic Sea Ice Coverage Changes?

Climate ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 15 ◽  
Author(s):  
Ge Peng ◽  
Jessica L. Matthews ◽  
Muyin Wang ◽  
Russell Vose ◽  
Liqiang Sun
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Adaptation ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
Climate Projections ◽  
Emission Scenarios ◽  
Ice Coverage ◽  
Arctic Sea

The prospect of an ice-free Arctic in our near future due to the rapid and accelerated Arctic sea ice decline has brought about the urgent need for reliable projections of the first ice-free Arctic summer year (FIASY). Together with up-to-date observations and characterizations of Arctic ice state, they are essential to business strategic planning, climate adaptation, and risk mitigation. In this study, the monthly Arctic sea ice extents from 12 global climate models are utilized to obtain projected FIASYs and their dependency on different emission scenarios, as well as to examine the nature of the ice retreat projections. The average value of model-projected FIASYs is 2054/2042, with a spread of 74/42 years for the medium/high emission scenarios, respectively. The earliest FIASY is projected to occur in year 2023, which may not be realistic, for both scenarios. The sensitivity of individual climate models to scenarios in projecting FIASYs is very model-dependent. The nature of model-projected Arctic sea ice coverage changes is shown to be primarily linear. FIASY values predicted by six commonly used statistical models that were curve-fitted with the first 30 years of climate projections (2006–2035), on other hand, show a preferred range of 2030–2040, with a distinct peak at 2034 for both scenarios, which is more comparable with those from previous studies.

scholarly journals Seasonal to interannual Arctic sea ice predictability in current global climate models

2014 ◽  
Vol 41 (3) ◽  
pp. 1035-1043 ◽  
Author(s):  
S. Tietsche ◽  
J. J. Day ◽  
V. Guemas ◽  
W. J. Hurlin ◽  
S. P. E. Keeley ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
Arctic Sea

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 Northern Hemisphere sea ice simulations by global climate models

2003 ◽  
Vol 22 (1) ◽  
pp. 75-82 ◽  
Author(s):  
John E. Walsh ◽  
Michael S. Timlin
Keyword(s):  
Sea Ice ◽  
Northern Hemisphere ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models

scholarly journals 20th-century sea-ice variations from observational data

2001 ◽  
Vol 33 ◽  
pp. 444-448 ◽  
Author(s):  
John E. Walsh ◽  
William L. Chapman
Keyword(s):  
Sea Ice ◽  
20Th Century ◽  
North Atlantic ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Empirical Orthogonal Functions ◽  
Global Climate Models ◽  
The Past ◽  
Ice Coverage

AbstractIn order to extend diagnoses of recent sea-ice variations beyond the past few decades, a century-scale digital dataset of Arctic sea-ice coverage has been compiled. For recent decades, the compilation utilizes satellite-derived hemispheric datasets. Regional datasets based primarily on ship reports and aerial reconnaissance are the primary inputs for the earlier part of the 20th century. While the various datasets contain some discrepancies, they capture the same general variations during their period of overlap. The outstanding feature of the time series of total hemispheric ice extent is a decrease that has accelerated during the past several decades. The decrease is greatest in summer and weakest in winter, contrary to the seasonality of the greenhouse changes projected by most global climate models. The primary spatial modes of sea-ice variability diagnosed in terms of empirical orthogonal functions, also show a strong seasonality. The first winter mode is dominated by an opposition of anomalies in the western and eastern North Atlantic, corresponding to the well-documented North Atlantic Oscillation. The primary summer mode depicts an anomaly of the same sign over nearly the entire Arctic and captures the recent trend of sea-ice coverage.

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