scholarly journals Arctic Sea Ice Retreat in 2007 Follows Thinning Trend

2009 ◽  
Vol 22 (1) ◽  
pp. 165-176 ◽  
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.

scholarly journals The effect of Arctic sea-ice extent on the absorbed (net) solar flux at the surface, based on ISCCP-D2 cloud data for 1983–2007

2010 ◽  
Vol 10 (2) ◽  
pp. 777-787 ◽  
Author(s):  
C. Matsoukas ◽  
N. Hatzianastassiou ◽  
A. Fotiadi ◽  
K. G. Pavlakis ◽  
I. Vardavas
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Cloud Amount ◽  
Arctic Sea Ice ◽  
Solar Flux ◽  
The Arctic ◽  
Transfer Model ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
The Arctic Ocean

Abstract. We estimate the effect of the Arctic sea ice on the absorbed (net) solar flux using a radiative transfer model. Ice and cloud input data to the model come from satellite observations, processed by the International Satellite Cloud Climatology Project (ISCCP) and span the period July 1983–June 2007. The sea-ice effect on the solar radiation fluctuates seasonally with the solar flux and decreases interannually in synchronisation with the decreasing sea-ice extent. A disappearance of the Arctic ice cap during the sunlit period of the year would radically reduce the local albedo and cause an annually averaged 19.7 W m−2 increase in absorbed solar flux at the Arctic Ocean surface, or equivalently an annually averaged 0.55 W m−2 increase on the planetary scale. In the clear-sky scenario these numbers increase to 34.9 and 0.97 W m−2, respectively. A meltdown only in September, with all other months unaffected, increases the Arctic annually averaged solar absorption by 0.32 W m−2. We examined the net solar flux trends for the Arctic Ocean and found that the areas absorbing the solar flux more rapidly are the North Chukchi and Kara Seas, Baffin and Hudson Bays, and Davis Strait. The sensitivity of the Arctic absorbed solar flux on sea-ice extent and cloud amount was assessed. Although sea ice and cloud affect jointly the solar flux, we found little evidence of strong non-linearities.

scholarly journals The Arctic sea ice cover of 2016: a year of record-low highs and higher-than-expected lows

2018 ◽  
Vol 12 (2) ◽  
pp. 433-452 ◽  
Author(s):  
Alek A. Petty ◽  
Julienne C. Stroeve ◽  
Paul R. Holland ◽  
Linette N. Boisvert ◽  
Angela C. Bliss ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
North Atlantic ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Atlantic Sector ◽  
Arctic Sea ◽  
The Arctic Ocean

Abstract. The Arctic sea ice cover of 2016 was highly noteworthy, as it featured record low monthly sea ice extents at the start of the year but a summer (September) extent that was higher than expected by most seasonal forecasts. Here we explore the 2016 Arctic sea ice state in terms of its monthly sea ice cover, placing this in the context of the sea ice conditions observed since 2000. We demonstrate the sensitivity of monthly Arctic sea ice extent and area estimates, in terms of their magnitude and annual rankings, to the ice concentration input data (using two widely used datasets) and to the averaging methodology used to convert concentration to extent (daily or monthly extent calculations). We use estimates of sea ice area over sea ice extent to analyse the relative “compactness” of the Arctic sea ice cover, highlighting anomalously low compactness in the summer of 2016 which contributed to the higher-than-expected September ice extent. Two cyclones that entered the Arctic Ocean during August appear to have driven this low-concentration/compactness ice cover but were not sufficient to cause more widespread melt-out and a new record-low September ice extent. We use concentration budgets to explore the regions and processes (thermodynamics/dynamics) contributing to the monthly 2016 extent/area estimates highlighting, amongst other things, rapid ice intensification across the central eastern Arctic through September. Two different products show significant early melt onset across the Arctic Ocean in 2016, including record-early melt onset in the North Atlantic sector of the Arctic. Our results also show record-late 2016 freeze-up in the central Arctic, North Atlantic and the Alaskan Arctic sector in particular, associated with strong sea surface temperature anomalies that appeared shortly after the 2016 minimum (October onwards). We explore the implications of this low summer ice compactness for seasonal forecasting, suggesting that sea ice area could be a more reliable metric to forecast in this more seasonal, “New Arctic”, sea ice regime.

scholarly journals Arctic Sea Ice and Freshwater Changes Driven by the Atmospheric Leading Mode in a Coupled Sea Ice–Ocean Model

2003 ◽  
Vol 16 (13) ◽  
pp. 2159-2177 ◽  
Author(s):  
Xiangdong Zhang ◽  
Moto Ikeda ◽  
John E. Walsh
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Ocean Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Siberian River ◽  
The North ◽  
New Findings ◽  
Arctic Sea ◽  
The Arctic Ocean

Abstract Observational and modeling studies have indicated recent large changes of sea ice and hydrographic properties in the Arctic Ocean. However, the observational database is sufficiently sparse that the mechanisms responsible for the recent changes are not fully understood. A coupled Arctic ocean–sea ice model forced by output from the NCEP–NCAR reanalysis is employed to investigate the role that the leading atmospheric mode has played in the recent changes of the Arctic Ocean. A modified Arctic Oscillation (AO) index is derived for the region poleward of 62.5°N in order to avoid ambiguities in the distinction between the conventional AO and the North Atlantic Oscillation index. The model results indicate that the AO is the driver of many of the changes manifested in the recent observations. The model shows reductions of Arctic sea ice area and volume by 3.2% and 8.8%, respectively, when the AO changes from its negative to its positive phase. Concurrently, freshwater storage decreases by about 2%, while the sea ice and freshwater exports via Fram Strait increase substantially. The changes of sea ice and freshwater storage are strikingly asymmetric between the east and the west Arctic. Notable new findings include 1) the interaction of the dynamic and thermodynamic responses in the sense that changes of sea ice growth and melt are driven by, and feed back negatively to, the dynamically (transport) driven changes of sea ice volume; and 2) the compatibility of the associated freshwater changes with recently observed changes in the salinity of the upper Arctic Ocean, thereby explaining the observed salinity variations by a mechanism that is distinct from, but complementary to, the altered circulation of Siberian river water. In addition, the enhanced freshwater export could be a contributing factor to the increased salinity in the Arctic Ocean. The results of the simulations indicate that Arctic sea ice and freshwater distributions change substantially if one phase of the AO predominates over a decadal timescale. However, such results are based on an idealization of the real-world situation, in which the pattern of forcing varies interannually and the number of positive-AO years varies among decades.

scholarly journals Arctic sea-ice extent and its effect on the absorbed (net) solar flux at the surface, based on ISCCP-D2 cloud data for 1983–2007

2009 ◽  
Vol 9 (5) ◽  
pp. 21041-21072
Author(s):  
C. Matsoukas ◽  
N. Hatzianastassiou ◽  
A. Fotiadi ◽  
K. G. Pavlakis ◽  
I. Vardavas
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Cloud Amount ◽  
Arctic Sea Ice ◽  
Solar Flux ◽  
The Arctic ◽  
Transfer Model ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
The Arctic Ocean

Abstract. We estimate the effect of the Arctic sea ice on the absorbed (net) solar flux using a radiation transfer model. Ice and cloud input data to the model come from satellite observations, processed by the International Satellite Cloud Climatology Project (ISCCP) and span the period July 1983–June 2007. The sea-ice effect on the solar radiation fluctuates seasonally with the solar flux and decreases interannually in synchronisation with the decreasing sea-ice extent. A disappearance of the Arctic ice cap during the sunlit period of the year would radically reduce the local albedo and cause a 19.7 W m−2 increase in absorbed solar flux at the Arctic Ocean surface, or equivalently a 0.55 W m−2 increase on the planetary scale. In the clear-sky scenario these numbers increase to 34.9 and 0.97 W m−2, respectively. A meltdown only in September, with all other months unaffected, increases the Arctic annually averaged solar absorption by 0.32 W m−2. We examined the net solar flux trends for the Arctic Ocean and found that the areas absorbing the solar flux more rapidly are the North Chukchi and Kara Seas, Buffin and Hudson Bays, and Davis Strait. The sensitivity of the Arctic absorbed solar flux on sea-ice extent and cloud amount was assessed. Although sea ice and cloud affect jointly the solar flux, we found little evidence of strong non-linearities.

scholarly journals The Arctic sea ice cover of 2016: A year of record low highs and higher than expected lows

2017 ◽  
Author(s):  
Alek A. Petty ◽  
Julienne C. Stroeve ◽  
Paul R. Holland ◽  
Linette N. Boisvert ◽  
Angela C. Bliss ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
North Atlantic ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
The Arctic Ocean ◽  
Arctic Sea Ice Extent

Abstract. 2016 was an interesting year in the Arctic, with record low sea ice at the start of the year, but a summer (September) Arctic sea ice extent that was higher than expected by most seasonal forecasts. Here we explore the 2016 Arctic sea ice state in terms of its monthly sea ice cover, placing this in context of the sea ice conditions observed since 2000. We demonstrate the sensitivity of monthly Arctic sea ice extent and area estimates, in terms of their magnitude and annual rankings, to the ice concentration input data (using two widely used datasets) and to the methodology used to convert concentration to extent (daily or monthly extent calculations). We use estimates of sea ice area to analyse the relative 'compactness' of the Arctic sea ice cover, highlighting anomalously low compactness in the summer of 2016 which contributed to the higher than expected September ice extent. Two cyclones that entered the Arctic Ocean during August appear to have driven this low concentration/compactness ice cover, but were not sufficient to cause more widespread melt out and a new record low September ice extent. We use concentration budgets to explore the regions and processes (thermodynamics/dynamics) contributing to the monthly 2016 extent/area estimates highlighting, amongst other things, rapid ice intensification across the central eastern Arctic through September. Two different products show significant early melt onset across the Arctic Ocean in 2016, including record early melt onset in the North Atlantic sector of the Arctic. Our results also show record late 2016 freeze up in the Central Arctic, North Atlantic. and the Alaskan Arctic sector in particular, associated with strong sea surface temperature anomalies that appeared shortly after the 2016 minimum (October onwards). We explore the implications of this low summer ice compactness for seasonal forecasting, suggesting that sea ice area could be a more reliable metric to forecast in this more seasonal, 'New Arctic', sea ice regime.

scholarly journals Intensification of the Atlantic Water Supply to the Arctic Ocean Through Fram Strait Induced by Arctic Sea Ice Decline

2020 ◽  
Vol 47 (3) ◽  
Author(s):  
Qiang Wang ◽  
Claudia Wekerle ◽  
Xuezhu Wang ◽  
Sergey Danilov ◽  
Nikolay Koldunov ◽  
...  
Keyword(s):  
Sea Ice ◽  
Water Supply ◽  
Arctic Ocean ◽  
Atlantic Water ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Fram Strait ◽  
Sea Ice Decline ◽  
Arctic Sea ◽  
The Arctic Ocean

scholarly journals Impact of Variable Atmospheric and Oceanic Form Drag on Simulations of Arctic Sea Ice*

2014 ◽  
Vol 44 (5) ◽  
pp. 1329-1353 ◽  
Author(s):  
Michel Tsamados ◽  
Daniel L. Feltham ◽  
David Schroeder ◽  
Daniela Flocco ◽  
Sinead L. Farrell ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Form Drag ◽  
Drag Coefficients ◽  
Arctic Sea ◽  
The Arctic Ocean ◽  
Range Of Values

Abstract Over Arctic sea ice, pressure ridges and floe and melt pond edges all introduce discrete obstructions to the flow of air or water past the ice and are a source of form drag. In current climate models form drag is only accounted for by tuning the air–ice and ice–ocean drag coefficients, that is, by effectively altering the roughness length in a surface drag parameterization. The existing approach of the skin drag parameter tuning is poorly constrained by observations and fails to describe correctly the physics associated with the air–ice and ocean–ice drag. Here, the authors combine recent theoretical developments to deduce the total neutral form drag coefficients from properties of the ice cover such as ice concentration, vertical extent and area of the ridges, freeboard and floe draft, and the size of floes and melt ponds. The drag coefficients are incorporated into the Los Alamos Sea Ice Model (CICE) and show the influence of the new drag parameterization on the motion and state of the ice cover, with the most noticeable being a depletion of sea ice over the west boundary of the Arctic Ocean and over the Beaufort Sea. The new parameterization allows the drag coefficients to be coupled to the sea ice state and therefore to evolve spatially and temporally. It is found that the range of values predicted for the drag coefficients agree with the range of values measured in several regions of the Arctic. Finally, the implications of the new form drag formulation for the spinup or spindown of the Arctic Ocean are discussed.

scholarly journals Natural variability of the Arctic Ocean sea ice during the present interglacial

2020 ◽  
Vol 117 (42) ◽  
pp. 26069-26075
Author(s):  
Anne de Vernal ◽  
Claude Hillaire-Marcel ◽  
Cynthia Le Duc ◽  
Philippe Roberge ◽  
Camille Brice ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Natural Variability ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Lomonosov Ridge ◽  
Arctic Sea ◽  
The Arctic Ocean ◽  
Open Question ◽  
The Impact

The impact of the ongoing anthropogenic warming on the Arctic Ocean sea ice is ascertained and closely monitored. However, its long-term fate remains an open question as its natural variability on centennial to millennial timescales is not well documented. Here, we use marine sedimentary records to reconstruct Arctic sea-ice fluctuations. Cores collected along the Lomonosov Ridge that extends across the Arctic Ocean from northern Greenland to the Laptev Sea were radiocarbon dated and analyzed for their micropaleontological and palynological contents, both bearing information on the past sea-ice cover. Results demonstrate that multiyear pack ice remained a robust feature of the western and central Lomonosov Ridge and that perennial sea ice remained present throughout the present interglacial, even during the climate optimum of the middle Holocene that globally peaked ∼6,500 y ago. In contradistinction, the southeastern Lomonosov Ridge area experienced seasonally sea-ice-free conditions, at least, sporadically, until about 4,000 y ago. They were marked by relatively high phytoplanktonic productivity and organic carbon fluxes at the seafloor resulting in low biogenic carbonate preservation. These results point to contrasted west–east surface ocean conditions in the Arctic Ocean, not unlike those of the Arctic dipole linked to the recent loss of Arctic sea ice. Hence, our data suggest that seasonally ice-free conditions in the southeastern Arctic Ocean with a dominant Arctic dipolar pattern, may be a recurrent feature under “warm world” climate.

scholarly journals Nudging the Arctic Ocean to Quantify Sea Ice Feedbacks

2019 ◽  
Vol 32 (8) ◽  
pp. 2381-2395
Author(s):  
Evelien Dekker ◽  
Richard Bintanja ◽  
Camiel Severijns
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Climate Sensitivity ◽  
Surface Albedo ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Response ◽  
Arctic Sea ◽  
The Arctic Ocean

AbstractWith Arctic summer sea ice potentially disappearing halfway through this century, the surface albedo and insulating effects of Arctic sea ice will decrease considerably. The ongoing Arctic sea ice retreat also affects the strength of the Planck, lapse rate, cloud, and surface albedo feedbacks together with changes in the heat exchange between the ocean and the atmosphere, but their combined effect on climate sensitivity has not been quantified. This study presents an estimate of all Arctic sea ice related climate feedbacks combined. We use a new method to keep Arctic sea ice at its present-day (PD) distribution under a changing climate in a 50-yr CO2 doubling simulation, using a fully coupled global climate model (EC-Earth, version 2.3). We nudge the Arctic Ocean to the (monthly dependent) year 2000 mean temperature and minimum salinity fields on a mask representing PD sea ice cover. We are able to preserve about 95% of the PD mean March and 77% of the September PD Arctic sea ice extent by applying this method. Using simulations with and without nudging, we estimate the climate response associated with Arctic sea ice changes. The Arctic sea ice feedback globally equals 0.28 ± 0.15 W m−2 K−1. The total sea ice feedback thus amplifies the climate response for a doubling of CO2, in line with earlier findings. Our estimate of the Arctic sea ice feedback agrees reasonably well with earlier CMIP5 global climate feedback estimates and shows that the Arctic sea ice exerts a considerable effect on the Arctic and global climate sensitivity.

Winter Arctic sea ice bottom evolution detected by thermistor string-based ice mass balance buoys (SIMBA)

2020 ◽  
Author(s):  
Bin Cheng ◽  
Timo Vihma ◽  
Zeling Liao ◽  
Ruibo Lei ◽  
Mario Hoppmann ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Mass Balance ◽  
Arctic Sea Ice ◽  
Heating Element ◽  
The Arctic ◽  
Ice Thickness ◽  
The Arctic Ocean ◽  
Ice Mass Balance ◽  
Snow And Ice

<p>A thermistor-string-based Snow and Ice Mass Balance Array (SIMBA) has been developed in recent years and used for monitoring snow and ice mass balance in the Arctic Ocean. SIMBA measures vertical environment temperature (ET) profiles through the air-snow-sea ice-ocean column using a thermistor string (5 m long, sensor spacing 2cm). Each thermistor sensor equipped with a small identical heating element. A small voltage was applied to the heating element so that the heat energy liberated in the vicinity of each sensor is the same. The heating time intervals lasted 60 s and 120 s, respectively. The heating temperatures (HT) after these two intervals were recorded. The ET was measured 4 times a day and once per day for the HT.</p><p>A total 15 SIMBA buoys have been deployed in the Arctic Ocean during the Chinese National Arctic Research Expedition (CHINARE) 2018 and the Nansen and Amundsen Basins Observational System (NABOS) 2018 field expeditions in late autumn. We applied a recently developed SIMBA algorithm to retrieve snow and ice thickness using SIMBA ET and HT temperature data. We focus particularly on sea ice bottom evolution during Arctic winter.</p><p>In mid-September 2018, 5 SIMBA buoys were deployed in the East Siberian Sea (NABOS2018) where snow was in practical zero cm and ice thickness ranged between 1.8 m – 2.6 m. By the end of May, those SIMBA buoys were drifted in the central Arctic where snow and ice thicknesses were around 0.05m - 0.2m and 2.6m – 3.2m, respectively. For those 10 SIMBA buoys deployed by the CHINARE2018 in the Chukchi Sea and Canadian Basin, the initial snow and ice thickness were ranged between 0.05m – 0.1cm and 1.5m – 2.5m, respectively.  By the end of May, those SIMBA buoys were drifted toward the north of Greenland where snow and ice thicknesses were around 0.2m - 0.3m and 2.0m – 3.5m, respectively. The ice bottom evolution derived by SIMBA algorithm agrees well with SIMBA HT identified ice-ocean interfaces. We also perform a preliminary investigation of sea ice bottom evolution measured by several SIMBA buoys deployed during the MOSAiC leg1 field campaign in winter 2019/2020.  </p>

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