Arctic sea ice in CMIP5 climate model projections and their seasonal variability

We combine satellite-derived observations of sea ice concentration, drift, and thickness to provide the first observational decomposition of the dynamic (advection/divergence) and thermodynamic (melt/growth) drivers of wintertime Arctic sea ice volume change. Ten winter growth seasons are analyzed over the CryoSat-2 period between October 2010 and April 2020. Sensitivity to several observational products is performed to provide an estimated uncertainty of the budget calculations. The total thermodynamic ice volume growth and dynamic ice losses are calculated with marked seasonal, inter-annual and regional variations. Ice growth is fastest during Autumn, in the Marginal Seas and over first year ice.&#160;Our budget decomposition methodology can help diagnose the processes confounding climate model predictions of sea ice. We make our product and code available to the community in monthly pan-Arctic netcdft files for the entire October 2010 to April 2020 period.

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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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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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Atmospheric teleconnection processes linking winter air stagnation and haze extremes in China with regional Arctic sea ice decline

10.5194/acp-2019-1023 ◽

2019 ◽

Author(s):

Yufei Zou ◽

Yuhang Wang ◽

Zuowei Xie ◽

Hailong Wang ◽

Philip J. Rasch

Keyword(s):

Sea Ice ◽

Climate Model ◽

Teleconnection Pattern ◽

Arctic Sea Ice ◽

The Arctic ◽

Transient Eddy ◽

Regional Ventilation ◽

Atmospheric Teleconnection ◽

Upper Troposphere ◽

Arctic Sea

Abstract. Recent studies suggested significant impacts of boreal cryosphere changes on wintertime air stagnation and haze pollution extremes in China. However, the underlying mechanism of such a teleconnection relationship remains unclear. Here we used the Whole Atmosphere Community Climate Model (WACCM) to investigate dynamic processes leading to atmospheric circulation and air stagnation responses to Arctic sea ice changes. We conducted four climate sensitivity experiments by perturbing sea ice concentrations (SIC) and corresponding sea surface temperature (SST) in autumn and early winter over the whole Arctic and three sub-regions in the climate model. The results indicate different responses in the general circulation and regional ventilation to the region-specific Arctic changes, with the largest increase of both the probability (by 120 %) and the intensity (by 32 %) of air stagnation extreme events being found in the experiment driven by SIC and SST changes over the Pacific sector of the Arctic (the East Siberian and Chukchi Seas). The increased air stagnation extreme events are mainly driven by an amplified hemispheric-scale atmospheric teleconnection pattern that resembles the negative phase of the Eurasian (EU) pattern. Dynamical diagnostics suggest that convergence of transient eddy forcing in the vicinity of Scandinavia in winter is largely responsible for the amplification of the teleconnection pattern. Transient eddy vorticity fluxes dominate the transient eddy forcing and produce a barotropic anticyclonic anomaly near Scandinavia and wave-train propagation across Eurasia to the downstream regions in East Asia. The piecewise potential vorticity inversion analysis reveals that this long-range atmospheric teleconnection of the Arctic origin takes place primarily in the middle and upper troposphere. The anomalous ridge over East Asia in the middle and upper troposphere worsens regional ventilation conditions by weakening monsoon northwesterlies and enhancing temperature inversion near the surface, leading to more and stronger air stagnation and pollution extremes over eastern China in winter. Ensemble projections based on the state-of-the-art climate models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) corroborate this teleconnection relationship between high-latitude environmental changes and middle-latitude weather extremes, though the tendency and magnitude vary considerably among each participating model.

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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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Mechanisms causing reduced Arctic sea ice loss in a coupled climate model

The Cryosphere Discussions ◽

10.5194/tcd-6-2653-2012 ◽

2012 ◽

Vol 6 (4) ◽

pp. 2653-2687 ◽

Cited By ~ 1

Author(s):

A. E. West ◽

A. B. Keen ◽

H. T. Hewitt

Keyword(s):

Sea Ice ◽

Climate Model ◽

Historical Record ◽

Arctic Sea Ice ◽

The Arctic ◽

Slight Reduction ◽

Coupled Climate Model ◽

Arctic Sea ◽

Ensembles Project ◽

Arctic Sea Ice Loss

Abstract. The fully-coupled climate model HadGEM1 produces one of the most accurate simulations of the historical record of Arctic sea ice seen in the IPCC AR4 multi-model ensemble. In this study, we examine projections of sea ice decline out to 2030, produced by two ensembles of HadGEM1 with natural and anthropogenic forcings included. These ensembles project a significant slowing of the rate of ice loss to occur after 2010, with some integrations even simulating a small increase in ice area. We use an energy budget of the Arctic to examine the causes of this slowdown. A negative feedback effect by which rapid reductions in ice thickness north of Greenland reduce ice export is found to play a major role. A slight reduction in ocean-to-ice heat flux in the relevant period, caused by changes in the MOC and subpolar gyre in some integrations, is also found to play a part. Finally, we assess the likelihood of a slowdown occurring in the real world due to these causes.

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Gridded Arctic sea ice concentration reconstruction for the first half of the 20th century based on different proxy data

10.5194/egusphere-egu21-3106 ◽

2021 ◽

Author(s):

Vladimir Semenov ◽

Tatiana Matveeva

Keyword(s):

Sea Ice ◽

20Th Century ◽

Climate Model ◽

Surface Air Temperature ◽

Arctic Sea Ice ◽

The Arctic ◽

Sea Ice Concentration ◽

The North ◽

Arctic Sea ◽

Ice Concentration

Global warming in the recent decades has been accompanied by a rapid recline of the Arctic sea ice area most pronounced in summer (10% per decade). To understand the relative contribution of external forcing and natural variability to the modern and future sea ice area changes, it is necessary to evaluate a range of long-term variations of the Arctic sea ice area in the period before a significant increase in anthropogenic emissions of greenhouse gases into the atmosphere. Available observational data on the spatiotemporal dynamics of Arctic sea ice until 1950s are characterized by significant gaps and uncertainties. In the recent years, there have appeared several reconstructions of the early 20th century Arctic sea ice area that filled the gaps by analogue methods or utilized combined empirical data and climate model&#8217;s output. All of them resulted in a stronger that earlier believed negative sea ice area anomaly in the 1940s concurrent with the early 20th century warming (ETCW) peak. In this study, we reconstruct the monthly average gridded sea ice concentration (SIC) in the first half of the 20th century using the relationship between the spatiotemporal features of SIC variability, surface air temperature over the Northern Hemisphere extratropical continents, sea surface temperature in the North Atlantic and North Pacific, and sea level pressure. In agreement with a few previous results, our reconstructed data also show a significant negative anomaly of the Arctic sea ice area in the middle of the 20th century, however with some 15% to 30% stronger amplitude, about 1.5 million km2 in September and 0.7 million km2 in March. The reconstruction demonstrates a good agreement with regional Arctic sea ice area data when available and suggests that ETWC in the Arctic has been accompanied by a concurrent sea ice area decline of a magnitude that have been exceeded only in the beginning of the 21st century.

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