On the Potential for Abrupt Arctic Winter Sea Ice Loss

Abstract The authors examine the transition from a seasonally ice-covered Arctic to an Arctic Ocean that is sea ice free all year round under increasing atmospheric CO2 levels. It is shown that in comprehensive climate models, such loss of Arctic winter sea ice area is faster than the preceding loss of summer sea ice area for the same rate of warming. In two of the models, several million square kilometers of winter sea ice are lost within only one decade. It is shown that neither surface albedo nor cloud feedbacks can explain the rapid winter ice loss in the climate model MPI-ESM by suppressing both feedbacks in the model. The authors argue that the large sensitivity of winter sea ice area in the models is caused by the asymmetry between melting and freezing: an ice-free summer requires the complete melt of even the thickest sea ice, which is why the perennial ice coverage decreases only gradually as more and more of the thinner ice melts away. In winter, however, sea ice areal coverage remains high as long as sea ice still forms, and then drops to zero wherever the ocean warms sufficiently to no longer form ice during winter. The loss of basinwide Arctic winter sea ice area, however, is still gradual in most models since the threshold mechanism proposed here is reversible and not associated with the existence of multiple steady states. As this occurs in every model analyzed here and is independent of any specific parameterization, it is likely to be relevant in the real world.

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Consistent Changes in the Sea Ice Seasonal Cycle in Response to Global Warming

Journal of Climate ◽

10.1175/2011jcli4051.1 ◽

2011 ◽

Vol 24 (20) ◽

pp. 5325-5335 ◽

Cited By ~ 31

Author(s):

Ian Eisenman ◽

Tapio Schneider ◽

David S. Battisti ◽

Cecilia M. Bitz

Keyword(s):

Sea Ice ◽

Northern Hemisphere ◽

Surface Albedo ◽

Climate Models ◽

Climate Model ◽

Ice Cover ◽

Climate Forcing ◽

Sea Ice Extent ◽

Ice Retreat ◽

Sea Ice Retreat

Abstract The Northern Hemisphere sea ice cover has diminished rapidly in recent years and is projected to continue to diminish in the future. The year-to-year retreat of Northern Hemisphere sea ice extent is faster in summer than winter, which has been identified as one of the most striking features of satellite observations as well as of state-of-the-art climate model projections. This is typically understood to imply that the sea ice cover is most sensitive to climate forcing in summertime, and previous studies have explained this by calling on factors such as the surface albedo feedback. In the Southern Hemisphere, however, it is the wintertime sea ice extent that retreats fastest in climate model projections. Here, it is shown that the interhemispheric differences in the model projections can be attributed to differences in coastline geometry, which constrain where sea ice can occur. After accounting for coastline geometry, it is found that the sea ice changes simulated in both hemispheres in most climate models are consistent with sea ice retreat being fastest in winter in the absence of landmasses. These results demonstrate that, despite the widely differing rates of ice retreat among climate model projections, the seasonal structure of the sea ice retreat is robust among the models and is uniform in both hemispheres.

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Observations and Simulations of Meteorological Conditions over Arctic Thick Sea Ice in Late Winter during the Transarktika 2019 Expedition

Atmosphere ◽

10.3390/atmos12020174 ◽

2021 ◽

Vol 12 (2) ◽

pp. 174

Author(s):

Günther Heinemann ◽

Sascha Willmes ◽

Lukas Schefczyk ◽

Alexander Makshtas ◽

Vasilii Kustov ◽

...

Keyword(s):

Sea Ice ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Open Water ◽

The Arctic ◽

Late Winter ◽

Good Representation ◽

Hourly Temperature ◽

Ice Model

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.

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

Climate ◽

10.3390/cli8010015 ◽

2020 ◽

Vol 8 (1) ◽

pp. 15 ◽

Cited By ~ 1

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.

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Achieving realistic Arctic-midlatitude teleconnections in a climate model through stochastic process representation

10.5194/wcd-2021-61 ◽

2021 ◽

Author(s):

Kristian Strommen ◽

Stephan Juricke

Keyword(s):

Sea Ice ◽

Climate Models ◽

Climate Model ◽

Arctic Sea Ice ◽

Stochastic Perturbations ◽

Model Studies ◽

Process Representation ◽

Arctic Sea ◽

Ocean Atmosphere ◽

Winter Circulation

Abstract. The extent to which interannual variability in Arctic sea ice influences the midlatitude circulation has been extensively debated. While observational data supports the existence of a teleconnection between November sea ice in the Barents-Kara region and the subsequent winter circulation, climate models do not consistently reproduce such a link, with only very weak inter-model consensus. We show, using the EC-Earth3 climate model, that while a deterministic ensemble of coupled simulations shows no evidence of such a teleconnection, the inclusion of stochastic parameterizations to the ocean and sea ice component of EC-Earth3 results in the emergence of a robust teleconnection comparable in magnitude to that observed. We show that this can be accounted for entirely by an improved ice-ocean-atmosphere coupling due to the stochastic perturbations. In particular, the inconsistent signal in existing climate model studies may be due to model biases in surface coupling, with stochastic parameterizations being one possible remedy.

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Influence of Ocean and Atmosphere Components on Simulated Climate Sensitivities

Journal of Climate ◽

10.1175/jcli-d-12-00121.1 ◽

2013 ◽

Vol 26 (1) ◽

pp. 231-245 ◽

Cited By ~ 27

Author(s):

Michael Winton ◽

Alistair Adcroft ◽

Stephen M. Griffies ◽

Robert W. Hallberg ◽

Larry W. Horowitz ◽

...

Keyword(s):

Sea Ice ◽

Climate Models ◽

Climate Model ◽

Model Simulation ◽

Coupled Model ◽

Ocean Model ◽

Historical Simulation ◽

Model Version ◽

Salinity Response ◽

The Impact

Abstract The influence of alternative ocean and atmosphere subcomponents on climate model simulation of transient sensitivities is examined by comparing three GFDL climate models used for phase 5 of the Coupled Model Intercomparison Project (CMIP5). The base model ESM2M is closely related to GFDL’s CMIP3 climate model version 2.1 (CM2.1), and makes use of a depth coordinate ocean component. The second model, ESM2G, is identical to ESM2M but makes use of an isopycnal coordinate ocean model. The authors compare the impact of this “ocean swap” with an “atmosphere swap” that produces the GFDL Climate Model version 3 (CM3) by replacing the AM2 atmospheric component with AM3 while retaining a depth coordinate ocean model. The atmosphere swap is found to have much larger influence on sensitivities of global surface temperature and Northern Hemisphere sea ice cover. The atmosphere swap also introduces a multidecadal response time scale through its indirect influence on heat uptake. Despite significant differences in their interior ocean mean states, the ESM2M and ESM2G simulations of these metrics of climate change are very similar, except for an enhanced high-latitude salinity response accompanied by temporarily advancing sea ice in ESM2G. In the ESM2G historical simulation this behavior results in the establishment of a strong halocline in the subpolar North Atlantic during the early twentieth century and an associated cooling, which are counter to observations in that region. The Atlantic meridional overturning declines comparably in all three models.

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Dust Aerosol Important for Snowball Earth Deglaciation

Journal of Climate ◽

10.1175/2010jcli3378.1 ◽

2010 ◽

Vol 23 (15) ◽

pp. 4121-4132 ◽

Cited By ~ 26

Author(s):

Dorian S. Abbot ◽

Itay Halevy

Keyword(s):

Climate Models ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Atmospheric Model ◽

Dust Aerosol ◽

Snowball Earth ◽

Dust Aerosols ◽

Co2 Levels ◽

The Impact

Abstract Most previous global climate model simulations could only produce the termination of Snowball Earth episodes at CO2 partial pressures of several tenths of a bar, which is roughly an order of magnitude higher than recent estimates of CO2 levels during and shortly after Snowball events. These simulations have neglected the impact of dust aerosols on radiative transfer, which is an assumption of potentially grave importance. In this paper it is argued, using the Dust Entrainment and Deposition (DEAD) box model driven by GCM results, that atmospheric dust aerosol concentrations may have been one to two orders of magnitude higher during a Snowball Earth event than today. It is furthermore asserted on the basis of calculations using NCAR’s Single Column Atmospheric Model (SCAM)—a radiative–convective model with sophisticated aerosol, cloud, and radiative parameterizations—that when the surface albedo is high, such increases in dust aerosol loading can produce several times more surface warming than an increase in the partial pressure of CO2 from 10−4 to 10−1 bar. Therefore the conclusion is reached that including dust aerosols in simulations may reconcile the CO2 levels required for Snowball termination in climate models with observations.

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Effect of prescribed sea surface conditions on the modern and future Antarctic surface climate simulated by the ARPEGE atmosphere general circulation model

The Cryosphere ◽

10.5194/tc-13-3023-2019 ◽

2019 ◽

Vol 13 (11) ◽

pp. 3023-3043

Author(s):

Julien Beaumet ◽

Michel Déqué ◽

Gerhard Krinner ◽

Cécile Agosta ◽

Antoinette Alias

Keyword(s):

Sea Ice ◽

General Circulation ◽

Climate Models ◽

Climate Model ◽

Atmospheric Model ◽

Sea Surface ◽

Coupled Climate Model ◽

Surface Climate ◽

Late 21St Century ◽

The Antarctic

Abstract. Owing to increase in snowfall, the Antarctic Ice Sheet surface mass balance is expected to increase by the end of the current century. Assuming no associated response of ice dynamics, this will be a negative contribution to sea-level rise. However, the assessment of these changes using dynamical downscaling of coupled climate model projections still bears considerable uncertainties due to poorly represented high-southern-latitude atmospheric circulation and sea surface conditions (SSCs), that is sea surface temperature and sea ice concentration. This study evaluates the Antarctic surface climate simulated using a global high-resolution atmospheric model and assesses the effects on the simulated Antarctic surface climate of two different SSC data sets obtained from two coupled climate model projections. The two coupled models from which SSCs are taken, MIROC-ESM and NorESM1-M, simulate future Antarctic sea ice trends at the opposite ends of the CMIP5 RCP8.5 projection range. The atmospheric model ARPEGE is used with a stretched grid configuration in order to achieve an average horizontal resolution of 35 km over Antarctica. Over the 1981–2010 period, ARPEGE is driven by the SSCs from MIROC-ESM, NorESM1-M and CMIP5 historical runs and by observed SSCs. These three simulations are evaluated against the ERA-Interim reanalyses for atmospheric general circulation as well as the MAR regional climate model and in situ observations for surface climate. For the late 21st century, SSCs from the same coupled climate models forced by the RCP8.5 emission scenario are used both directly and bias-corrected with an anomaly method which consists in adding the future climate anomaly from coupled model projections to the observed SSCs with taking into account the quantile distribution of these anomalies. We evaluate the effects of driving the atmospheric model by the bias-corrected instead of the original SSCs. For the simulation using SSCs from NorESM1-M, no significantly different climate change signals over Antarctica as a whole are found when bias-corrected SSCs are used. For the simulation driven by MIROC-ESM SSCs, a significant additional increase in precipitation and in winter temperatures for the Antarctic Ice Sheet is obtained when using bias-corrected SSCs. For the range of Antarctic warming found (+3 to +4 K), we confirm that snowfall increase will largely outweigh increases in melt and rainfall. Using the end members of sea ice trends from the CMIP5 RCP8.5 projections, the difference in warming obtained (∼ 1 K) is much smaller than the spread of the CMIP5 Antarctic warming projections. This confirms that the errors in representing the Southern Hemisphere atmospheric circulation in climate models are also determinant for the diversity of their projected late 21st century Antarctic climate change.

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

The Cryosphere ◽

10.5194/tc-10-1631-2016 ◽

2016 ◽

Vol 10 (4) ◽

pp. 1631-1645 ◽

Cited By ~ 11

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.

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Surface Albedo of the Antarctic Sea Ice Zone

Journal of Climate ◽

10.1175/jcli3489.1 ◽

2005 ◽

Vol 18 (17) ◽

pp. 3606-3622 ◽

Cited By ~ 124

Author(s):

Richard E. Brandt ◽

Stephen G. Warren ◽

Anthony P. Worby ◽

Thomas C. Grenfell

Keyword(s):

Sea Ice ◽

Surface Albedo ◽

Near Infrared ◽

Field Experiments ◽

Climate Models ◽

Solar Spectrum ◽

Open Water ◽

Visual Observation ◽

Antarctic Sea Ice ◽

The Antarctic

Abstract In three ship-based field experiments, spectral albedos were measured at ultraviolet, visible, and near-infrared wavelengths for open water, grease ice, nilas, young “grey” ice, young grey-white ice, and first-year ice, both with and without snow cover. From the spectral measurements, broadband albedos are computed for clear and cloudy sky, for the total solar spectrum as well as for visible and near-infrared bands used in climate models, and for Advanced Very High Resolution Radiometer (AVHRR) solar channels. The all-wave albedos vary from 0.07 for open water to 0.87 for thick snow-covered ice under cloud. The frequency distribution of ice types and snow coverage in all seasons is available from the project on Antarctic Sea Ice Processes and Climate (ASPeCt). The ASPeCt dataset contains routine hourly visual observations of sea ice from research and supply ships of several nations using a standard protocol. Ten thousand of these observations, separated by a minimum of 6 nautical miles along voyage tracks, are used together with the measured albedos for each ice type to assign an albedo to each visual observation, resulting in “ice-only” albedos as a function of latitude for each of five longitudinal sectors around Antarctica, for each of the four seasons. These ice albedos are combined with 13 yr of ice concentration estimates from satellite passive microwave measurements to obtain the geographical and seasonal variation of average surface albedo. Most of the Antarctic sea ice is snow covered, even in summer, so the main determinant of area-averaged albedo is the fraction of open water within the pack.

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20th-century sea-ice variations from observational data

Annals of Glaciology ◽

10.3189/172756401781818671 ◽

2001 ◽

Vol 33 ◽

pp. 444-448 ◽

Cited By ~ 99

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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