Rapid Arctic Sea Ice Loss on the Synoptic Time Scale and Related Atmospheric Circulation Anomalies

AbstractLarge sea ice loss on the synoptic time scale is examined in various subregions in the Arctic as well as at the pan-Arctic scale. It is found that the frequency of large daily sea ice loss (LDSIL) days is significantly correlated with the September sea ice extent over the Beaufort–Chukchi–Siberian Seas, the Laptev–Kara Seas, the central Arctic, and the all-Arctic regions, indicating a link between the synoptic sea ice variability and the interannual variability of the annual minimum sea ice extent. A composite analysis reveals dipoles of anomalous cyclones and anticyclones associated with LDSIL days. Different from the well-known Arctic dipole pattern, the east–west dipoles are found over the corresponding regions of LDSIL in the Arctic marginal seas and are associated with the increasing occurrence of Rossby wave breaking and atmospheric rivers. The anticyclones of the dipoles are persistent and quasi-stationary, reminiscent of blocking. The anomalous poleward flow between the cyclone and the anticyclone enhances the poleward transport of heat and water vapor in the lower troposphere. Although enhanced downward shortwave radiation, associated with reduced cloud fraction, is found in some regions, it is not collocated with the regions of LDSIL. In contrast, enhanced downward longwave radiation owing to increasing column water vapor shows good spatial correspondence with LDSIL, indicating the importance of atmospheric rivers in LDSIL events. Lead/lag composites with respect to the onset of LDSIL episodes reveal precursor wave trains spanning the midlatitudes. The wave trains have predominantly zonal energy propagation in the midlatitudes and do not show a clear link to tropical or subtropical forcing.

Download Full-text

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.

Download Full-text

Sea-ice induced growth decline in Arctic shrubs

Biology Letters ◽

10.1098/rsbl.2017.0122 ◽

2017 ◽

Vol 13 (8) ◽

pp. 20170122 ◽

Cited By ~ 6

Author(s):

Mads Forchhammer

Keyword(s):

Sea Ice ◽

Ring Width ◽

Plant Productivity ◽

Climatic Conditions ◽

Arctic Sea Ice ◽

Annual Growth ◽

The Arctic ◽

Growth Time ◽

Sea Ice Extent ◽

Negative Effect

Measures of increased tundra plant productivity have been associated with the accelerating retreat of the Arctic sea-ice. Emerging studies document opposite effects, advocating for a more complex relationship between the shrinking sea-ice and terrestrial plant productivity. I introduce an autoregressive plant growth model integrating effects of biological and climatic conditions for analysing individual ring-width growth time series. Using 128 specimens of Salix arctica , S. glauca and Betula nana sampled across Greenland to Svalbard, an overall negative effect of the retreating June sea-ice extent was found on the annual growth. The negative effect of the retreating June sea-ice was observed for younger individuals with large annual growth allocations and with little or no trade-off between previous and current year's growth.

Download Full-text

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.

Download Full-text

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.

Download Full-text

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.

Download Full-text

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.

Download Full-text

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.

Download Full-text

Large-scale Arctic sea ice motion from Sentinel-1 and the RADARSAT Constellation Mission

10.5194/egusphere-egu21-514 ◽

2021 ◽

Author(s):

Stephen Howell ◽

Mike Brady ◽

Alexander Komarov

Keyword(s):

Sea Ice ◽

Spatial Resolution ◽

Temporal Resolution ◽

Large Scale ◽

Arctic Sea Ice ◽

The Arctic ◽

High Temporal Resolution ◽

Sar Images ◽

Sea Ice Extent ◽

Arctic Sea

<p>As the Arctic&#8217;s sea ice extent continues to decline, remote sensing observations are becoming even more vital for the monitoring and understanding of this process.&#160; Recently, the sea ice community has entered a new era of synthetic aperture radar (SAR) satellites operating at C-band with the launch of Sentinel-1A in 2014, Sentinel-1B in 2016 and the RADARSAT Constellation Mission (RCM) in 2019. These missions represent a collection of 5 spaceborne SAR sensors that together can routinely cover Arctic sea ice with a high spatial resolution (20-90 m) but also with a high temporal resolution (1-7 days) typically associated with passive microwave sensors. Here, we used ~28,000 SAR image pairs from Sentinel-1AB together with ~15,000 SAR images pairs from RCM to generate high spatiotemporal large-scale sea ice motion products across the pan-Arctic domain for 2020. The combined Sentinel-1AB and RCM sea ice motion product provides almost complete 7-day coverage over the entire pan-Arctic domain that also includes the pole-hole. Compared to the National Snow and Ice Data Center (NSIDC) Polar Pathfinder and Ocean and Sea Ice-Satellite Application Facility (OSI-SAF) sea ice motion products, ice speed was found to be faster with the Senintel-1AB and RCM product which is attributed to the higher spatial resolution of SAR imagery. More sea ice motion vectors were detected from the Sentinel-1AB and RCM product in during the summer months and within the narrow channels and inlets compared to the NSIDC Polar Pathfinder and OSI-SAF sea ice motion products. Overall, our results demonstrate that sea ice geophysical variables across the pan-Arctic domain can now be retrieved from multi-sensor SAR images at both high spatial and temporal resolution.</p>

Download Full-text

Regional September Sea Ice Forecasting with Complex Networks and Gaussian Processes

Weather and Forecasting ◽

10.1175/waf-d-19-0107.1 ◽

2020 ◽

Vol 35 (3) ◽

pp. 793-806

Author(s):

William Gregory ◽

Michel Tsamados ◽

Julienne Stroeve ◽

Peter Sollich

Keyword(s):

Sea Ice ◽

Time Series Data ◽

Gaussian Process Regression ◽

Forecast Model ◽

Arctic Sea Ice ◽

The Arctic ◽

Series Data ◽

Lead Times ◽

Sea Ice Concentration ◽

Sea Ice Extent

Abstract Reliable predictions of the Arctic sea ice cover are becoming of paramount importance for Arctic communities and industry stakeholders. In this study pan-Arctic and regional September mean sea ice extents are forecast with lead times of up to 3 months using a complex network statistical approach. This method exploits relationships within climate time series data by constructing regions of spatiotemporal homogeneity (i.e., nodes), and subsequently deriving teleconnection links between them. Here the nodes and links of the networks are generated from monthly mean sea ice concentration fields in June, July, and August; hence, individual networks are constructed for each respective month. Network information is then utilized within a linear Gaussian process regression forecast model, a Bayesian inference technique, in order to generate predictions of sea ice extent. Pan-Arctic forecasts capture a significant amount of the variability in the satellite observations of September sea ice extent, with detrended predictive skills of 0.53, 0.62, and 0.81 at 3-, 2-, and 1-month lead times, respectively. Regional forecasts are also performed for nine Arctic regions. On average, the highest predictive skill is achieved in the Canadian Archipelago, Beaufort, Chukchi, East Siberian, Laptev, and Kara Seas, although the ability to accurately predict many of these regions appears to be changing over time.

Download Full-text

Arctic seabirds and shrinking sea ice: egg analyses reveal the importance of ice-derived resources

Scientific Reports ◽

10.1038/s41598-019-51788-4 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 2

Author(s):

Fanny Cusset ◽

Jérôme Fort ◽

Mark Mallory ◽

Birgit Braune ◽

Philippe Massicotte ◽

...

Keyword(s):

Sea Ice ◽

Marine Species ◽

Arctic Sea Ice ◽

The Arctic ◽

Sea Ice Extent ◽

Climate Shifts ◽

Investment In Reproduction ◽

Ice Conditions ◽

Arctic Seabirds ◽

Energetic Composition

Abstract In the Arctic, sea-ice plays a central role in the functioning of marine food webs and its rapid shrinking has large effects on the biota. It is thus crucial to assess the importance of sea-ice and ice-derived resources to Arctic marine species. Here, we used a multi-biomarker approach combining Highly Branched Isoprenoids (HBIs) with δ13C and δ15N to evaluate how much Arctic seabirds rely on sea-ice derived resources during the pre-laying period, and if changes in sea-ice extent and duration affect their investment in reproduction. Eggs of thick-billed murres (Uria lomvia) and northern fulmars (Fulmarus glacialis) were collected in the Canadian Arctic during four years of highly contrasting ice conditions, and analysed for HBIs, isotopic (carbon and nitrogen) and energetic composition. Murres heavily relied on ice-associated prey, and sea-ice was beneficial for this species which produced larger and more energy-dense eggs during icier years. In contrast, fulmars did not exhibit any clear association with sympagic communities and were not impacted by changes in sea ice. Murres, like other species more constrained in their response to sea-ice variations, therefore appear more sensitive to changes and may become the losers of future climate shifts in the Arctic, unlike more resilient species such as fulmars.

Download Full-text