Impact of floe size distribution on seasonal fragmentation and melt of Arctic sea ice

Abstract. Recent years have seen a rapid reduction in the summer Arctic sea ice extent. To both understand this trend and project the future evolution of the summer Arctic sea ice, a better understanding of the physical processes that drive the seasonal loss of sea ice is required. The marginal ice zone, here defined as regions with between 15 and 80 % sea ice cover, is the region separating pack ice from open ocean. Accurate modelling of this region is important to understand the dominant mechanisms involved in seasonal sea ice loss. Evolution of the marginal ice zone is determined by complex interactions between the atmosphere, sea ice, ocean, and ocean surface waves. Therefore, this region presents a significant modelling challenge. Sea ice floes span a range of sizes but climate sea ice models assume they adopt a constant size. Floe size influences the lateral melt rate of sea ice and momentum transfer between atmosphere, sea ice, and ocean, all important processes within the marginal ice zone. In this study, the floe size distribution is represented as a truncated power law defined by three key parameters: minimum floe size, maximum floe size, and power law exponent. This distribution is implemented within a sea ice model coupled to a prognostic ocean mixed layer model. We present results to show that the use of a power law derived floe size distribution has a spatially and temporally dependent impact on the sea ice, in particular increasing the role of the marginal ice zone in seasonal sea ice loss. This feature is important in correcting existing biases within sea ice models. In addition, we show a much stronger model sensitivity to floe size distribution parameters than other parameters used to calculate lateral melt, justifying the focus on floe size distribution in model development. It is finally concluded that the model approach presented here is a flexible tool for assessing the importance of a floe size distribution in the evolution of sea ice and is suitable for applications where a simple but realistic floe size distribution model is required.

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Impact of sea ice floe size distribution on seasonal fragmentation and melt of Arctic sea ice

The Cryosphere ◽

10.5194/tc-14-403-2020 ◽

2020 ◽

Vol 14 (2) ◽

pp. 403-428 ◽

Cited By ~ 4

Author(s):

Adam W. Bateson ◽

Daniel L. Feltham ◽

David Schröder ◽

Lucia Hosekova ◽

Jeff K. Ridley ◽

...

Keyword(s):

Sea Ice ◽

Size Distribution ◽

Power Law ◽

Climate Models ◽

Ice Cover ◽

Arctic Sea Ice ◽

Arctic Sea ◽

Marginal Ice Zone ◽

Break Up ◽

The Impact

Abstract. Recent years have seen a rapid reduction in the summer Arctic sea ice extent. To both understand this trend and project the future evolution of the summer Arctic sea ice, a better understanding of the physical processes that drive the seasonal loss of sea ice is required. The marginal ice zone, here defined as regions with between 15 % and 80 % sea ice cover, is the region separating pack ice from the open ocean. Accurate modelling of this region is important to understand the dominant mechanisms involved in seasonal sea ice loss. Evolution of the marginal ice zone is determined by complex interactions between the atmosphere, sea ice, ocean, and ocean surface waves. Therefore, this region presents a significant modelling challenge. Sea ice floes span a range of sizes but sea ice models within climate models assume they adopt a constant size. Floe size influences the lateral melt rate of sea ice and momentum transfer between atmosphere, sea ice, and ocean, all important processes within the marginal ice zone. In this study, the floe size distribution is represented as a power law defined by an upper floe size cut-off, lower floe size cut-off, and power-law exponent. This distribution is also defined by a new tracer that varies in response to lateral melting, wave-induced break-up, freezing conditions, and advection. This distribution is implemented within a sea ice model coupled to a prognostic ocean mixed-layer model. We present results to show that the use of a power-law floe size distribution has a spatially and temporally dependent impact on the sea ice, in particular increasing the role of the marginal ice zone in seasonal sea ice loss. This feature is important in correcting existing biases within sea ice models. In addition, we show a much stronger model sensitivity to floe size distribution parameters than other parameters used to calculate lateral melt, justifying the focus on floe size distribution in model development. We also find that the attenuation rate of waves propagating under the sea ice cover modulates the impact of wave break-up on the floe size distribution. It is finally concluded that the model approach presented here is a flexible tool for assessing the importance of a floe size distribution in the evolution of sea ice and is a useful stepping stone for future development of floe size modelling.

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Modeling the seasonal evolution of the Arctic sea ice floe size distribution

Elem Sci Anth ◽

10.12952/journal.elementa.000126 ◽

2016 ◽

Vol 4 ◽

Cited By ~ 9

Author(s):

Jinlun Zhang ◽

Harry Stern ◽

Byongjun Hwang ◽

Axel Schweiger ◽

Michael Steele ◽

...

Keyword(s):

Sea Ice ◽

Size Distribution ◽

Power Law ◽

Annual Cycle ◽

Arctic Sea Ice ◽

The Arctic ◽

Ice Thickness ◽

First Year ◽

Seasonal Evolution ◽

Marginal Ice Zone

Abstract To better simulate the seasonal evolution of sea ice in the Arctic, with particular attention to the marginal ice zone, a sea ice model of the distribution of ice thickness, floe size, and enthalpy was implemented into the Pan-arctic Ice–Ocean Modeling and Assimilation System (PIOMAS). Theories on floe size distribution (FSD) and ice thickness distribution (ITD) were coupled in order to explicitly simulate multicategory FSD and ITD distributions simultaneously. The expanded PIOMAS was then used to estimate the seasonal evolution of the Arctic FSD in 2014 when FSD observations are available for model calibration and validation. Results indicate that the simulated FSD, commonly described equivalently as cumulative floe number distribution (CFND), generally follows a power law across space and time and agrees with the CFND observations derived from TerraSAR-X satellite images. The simulated power-law exponents also correlate with those derived using MODIS images, with a low mean bias of –2%. In the marginal ice zone, the modeled CFND shows a large number of small floes in winter because of stronger winds acting on thin, weak first-year ice in the ice edge region. In mid-spring and summer, the CFND resembles an upper truncated power law, with the largest floes mostly broken into smaller ones; however, the number of small floes is lower than in winter because floes of small sizes or first-year ice are easily melted away. In the ice pack interior there are fewer floes in late fall and winter than in summer because many of the floes are “welded” together into larger floes in freezing conditions, leading to a relatively flat CFND with low power-law exponents. The simulated mean floe size averaged over all ice-covered areas shows a clear annual cycle, large in winter and smaller in summer. However, there is no obvious annual cycle of mean floe size averaged over the marginal ice zone. The incorporation of FSD into PIOMAS results in reduced ice thickness, mainly in the marginal ice zone, which improves the simulation of ice extent and yields an earlier ice retreat.

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Arctic Sea Ice Retreat in 2007 Follows Thinning Trend

Journal of Climate ◽

10.1175/2008jcli2521.1 ◽

2009 ◽

Vol 22 (1) ◽

pp. 165-176 ◽

Cited By ~ 143

Author(s):

R. W. Lindsay ◽

J. Zhang ◽

A. Schweiger ◽

M. Steele ◽

H. Stern

Keyword(s):

Sea Ice ◽

Arctic Ocean ◽

Ocean Model ◽

Arctic Sea Ice ◽

The Arctic ◽

Ice Thickness ◽

Sea Ice Extent ◽

Pacific Side ◽

Arctic Sea ◽

The Arctic Ocean

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.

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Sources of multi-decadal variability in Arctic sea ice extent

Environmental Research Letters ◽

10.1088/1748-9326/7/3/034011 ◽

2012 ◽

Vol 7 (3) ◽

pp. 034011 ◽

Cited By ~ 75

Author(s):

J J Day ◽

J C Hargreaves ◽

J D Annan ◽

A Abe-Ouchi

Keyword(s):

Sea Ice ◽

Decadal Variability ◽

Arctic Sea Ice ◽

Sea Ice Extent ◽

Arctic Sea ◽

Arctic Sea Ice Extent

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Late-Twentieth-Century Simulation of Arctic Sea Ice and Ocean Properties in the CCSM4

Journal of Climate ◽

10.1175/jcli-d-11-00201.1 ◽

2012 ◽

Vol 25 (5) ◽

pp. 1431-1452 ◽

Cited By ~ 82

Author(s):

Alexandra Jahn ◽

Kara Sterling ◽

Marika M. Holland ◽

Jennifer E. Kay ◽

James A. Maslanik ◽

...

Keyword(s):

Twentieth Century ◽

Sea Ice ◽

Internal Variability ◽

Ice Cover ◽

Arctic Sea Ice ◽

The Arctic ◽

Motion Field ◽

Sea Ice Extent ◽

Arctic Sea ◽

Ensemble Mean

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.

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Mechanisms for and Predictability of a Drastic Reduction in the Arctic Sea Ice: APPOSITE Data with Climate Model MIROC

Journal of Climate ◽

10.1175/jcli-d-18-0195.1 ◽

2019 ◽

Vol 32 (5) ◽

pp. 1361-1380 ◽

Cited By ~ 3

Author(s):

J. Ono ◽

H. Tatebe ◽

Y. Komuro

Keyword(s):

Sea Ice ◽

Climate Model ◽

Arctic Sea Ice ◽

The Arctic ◽

Ensemble Prediction ◽

Forecast Errors ◽

Drastic Reduction ◽

Sea Ice Concentration ◽

Sea Ice Extent ◽

Arctic Sea

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.

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Record high Pacific Arctic seawater temperatures and delayed sea ice advance in response to episodic atmospheric blocking

Scientific Reports ◽

10.1038/s41598-020-77488-y ◽

2020 ◽

Vol 10 (1) ◽

Cited By ~ 1

Author(s):

Tsubasa Kodaira ◽

Takuji Waseda ◽

Takehiko Nose ◽

Jun Inoue

Keyword(s):

Sea Ice ◽

Arctic Region ◽

Arctic Sea Ice ◽

Sea Surface ◽

The Arctic ◽

Atmospheric Blocking ◽

Sea Ice Extent ◽

The Pacific ◽

Arctic Sea ◽

Highly Correlated

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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How much should we believe correlations between Arctic cyclones and sea ice extent?

10.5194/tc-2017-140 ◽

2017 ◽

Author(s):

Jamie G. L. Rae ◽

Alexander D. Todd ◽

Edward W. Blockley ◽

Jeff K. Ridley

Keyword(s):

Sea Ice ◽

Climate Model ◽

Arctic Sea Ice ◽

Reanalysis Dataset ◽

Sea Ice Extent ◽

Sea Level Pressure ◽

Temporal Sampling ◽

Time Period ◽

Arctic Sea ◽

Short Time

Abstract. This paper presents an analysis of Arctic summer cyclones in a climate model and in a reanalysis dataset. A cyclone identification and tracking algorithm is run for output from model simulations at two resolutions, and for the reanalysis, using two different tracking variables (mean sea-level pressure and 850 hPa vorticity) for identification of the cyclones. Correlations between characteristics of the cyclones and September Arctic sea ice extent are investigated, and the influence of the tracking variable, the spatial resolution of the model, and spatial and temporal sampling, on the correlations is explored. We conclude that the correlations obtained depend on all of these factors, and that care should be taken when interpreting the results of such analyses, especially when the focus is on one reanalysis, or output from one model, analysed with a single tracking variable for a short time period.

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Modeled Arctic sea ice evolution through 2300 in CMIP5 extended RCPs

The Cryosphere Discussions ◽

10.5194/tcd-8-1383-2014 ◽

2014 ◽

Vol 8 (1) ◽

pp. 1383-1406 ◽

Cited By ~ 1

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.

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Changes of the Arctic marginal ice zone during the satellite era

The Cryosphere ◽

10.5194/tc-14-1971-2020 ◽

2020 ◽

Vol 14 (6) ◽

pp. 1971-1984 ◽

Cited By ~ 1

Author(s):

Rebecca J. Rolph ◽

Daniel L. Feltham ◽

David Schröder

Keyword(s):

Sea Ice ◽

Arctic Sea Ice ◽

Satellite Observations ◽

The Arctic ◽

Upper And Lower Bounds ◽

Sea Ice Concentration ◽

Sea Ice Extent ◽

Ice Concentration ◽

Marginal Ice Zone ◽

Definition Of

Abstract. Many studies have shown a decrease in Arctic sea ice extent. It does not logically follow, however, that the extent of the marginal ice zone (MIZ), here defined as the area of the ocean with ice concentrations from 15 % to 80 %, is also changing. Changes in the MIZ extent has implications for the level of atmospheric and ocean heat and gas exchange in the area of partially ice-covered ocean and for the extent of habitat for organisms that rely on the MIZ, from primary producers like sea ice algae to seals and birds. Here, we present, for the first time, an analysis of satellite observations of pan-Arctic averaged MIZ extent. We find no trend in the MIZ extent over the last 40 years from observations. Our results indicate that the constancy of the MIZ extent is the result of an observed increase in width of the MIZ being compensated for by a decrease in the perimeter of the MIZ as it moves further north. We present simulations from a coupled sea ice–ocean mixed layer model using a prognostic floe size distribution, which we find is consistent with, but poorly constrained by, existing satellite observations of pan-Arctic MIZ extent. We provide seasonal upper and lower bounds on MIZ extent based on the four satellite-derived sea ice concentration datasets used. We find a large and significant increase (>50 %) in the August and September MIZ fraction (MIZ extent divided by sea ice extent) for the Bootstrap and OSI-450 observational datasets, which can be attributed to the reduction in total sea ice extent. Given the results of this study, we suggest that references to “rapid changes” in the MIZ should remain cautious and provide a specific and clear definition of both the MIZ itself and also the property of the MIZ that is changing.

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