Predicting the Timing and Duration of Arctic Sea Ice and Its Implications on Future Drilling Seasons in the Chukchi Sea and Beaufort Sea

2016 ◽  
Author(s):  
Jill F. Hasling
Keyword(s):  
Sea Ice ◽  
Chukchi Sea ◽  
Beaufort Sea ◽  
Arctic Sea Ice ◽  
Arctic Sea

scholarly journals Winter-to-summer transition of Arctic sea ice breakup and floe size distribution in the Beaufort Sea

Elem Sci Anth ◽  
2017 ◽  
Vol 5 (0) ◽  
pp. 40 ◽  
Author(s):  
Byongjun Hwang ◽  
Jeremy Wilkinson ◽  
Edward Maksym ◽  
Hans C. Graber ◽  
Axel Schweiger ◽  
...  
Keyword(s):  
Sea Ice ◽  
Size Distribution ◽  
Beaufort Sea ◽  
Arctic Sea Ice ◽  
Ice Breakup ◽  
Arctic Sea

scholarly journals Effects of Arctic sea ice in autumn on extreme cold events over the Tibetan Plateau in the following winter: possible mechanisms

2021 ◽  
Author(s):  
Miao Bi ◽  
Qingquan Li ◽  
Song Yang ◽  
Dong Guo ◽  
Xinyong Shen ◽  
...  
Keyword(s):  
Sea Ice ◽  
Wave Train ◽  
Beaufort Sea ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
The Tibetan Plateau ◽  
The North ◽  
Arctic Sea ◽  
Cold Events ◽  
Extreme Cold

AbstractExtreme cold events (ECEs) on the Tibetan Plateau (TP) exert serious impacts on agriculture and animal husbandry and are important drivers of ecological and environmental changes. We investigate the temporal and spatial characteristics of the ECEs on the TP and the possible effects of Arctic sea ice. The daily observed minimum air temperature at 73 meteorological stations on the TP during 1980–2018 and the BCC_AGCM3_MR model are used. Our results show that the main mode of winter ECEs over the TP exhibits the same spatial variation and interannual variability across the whole region and is affected by two wave trains originating from the Arctic. The southern wave train is controlled by the sea ice in the Beaufort Sea. It initiates in the Norwegian Sea, and then passes through the North Atlantic Ocean, the Arabian Sea, and the Bay of Bengal along the subtropical westerly jet stream. It enters the TP from the south and brings warm, humid air from the oceans. By contrast, the northern wave train is controlled by the sea ice in the Laptev Sea. It originates from the Barents and Kara seas, passes through Lake Baikal, and enters the TP from the north, bringing dry and cold air. A decrease in the sea ice in the Beaufort Sea causes positive potential height anomalies in the Arctic. This change enhances the pressure gradient between the Artic and the mid-latitudes, leading to westerly winds in the northern TP, which block the intrusion of cold air into the south. By contrast, a decrease in the sea ice in the Laptev Sea causes negative potential height anomalies in the Artic. This change reduces the pressure gradient between the Artic and the mid-latitudes, leading to easterly winds to the north of the TP, which favors the southward intrusion of cold polar air. A continuous decrease in the amount of sea ice in the Beaufort Sea would reduce the frequency of ECEs over the TP and further aggravate TP warming in winter.

scholarly journals Exploring the utility of quantitative network design in evaluating Arctic sea-ice thickness sampling strategies

2015 ◽  
Vol 9 (2) ◽  
pp. 1735-1768 ◽  
Author(s):  
T. Kaminski ◽  
F. Kauker ◽  
H. Eicken ◽  
M. Karcher
Keyword(s):  
Sea Ice ◽  
Network Design ◽  
Chukchi Sea ◽  
Software Tool ◽  
Severity Index ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Target Area ◽  
Sea Ice Thickness ◽  
Arctic Sea

Abstract. We present a quantitative network design (QND) study of the Arctic sea ice-ocean system using a software tool that can evaluate hypothetical observational networks in a variational data assimilation system. For a demonstration, we evaluate two idealised flight transects derived from NASA's Operation IceBridge airborne ice surveys in terms of their potential to improve ten-day to five-month sea-ice forecasts. As target regions for the forecasts we select the Chukchi Sea, an area particularly relevant for maritime traffic and offshore resource exploration, as well as two areas related to the Barnett Ice Severity Index (BSI), a standard measure of shipping conditions along the Alaskan coast that is routinely issued by ice services. Our analysis quantifies the benefits of sampling upstream of the target area and of reducing the sampling uncertainty. We demonstrate how observations of sea-ice and snow thickness can constrain ice and snow variables in a target region and quantify the complementarity of combining two flight transects. We further quantify the benefit of improved atmospheric forecasts and a well-calibrated model.

scholarly journals Exploring the utility of quantitative network design in evaluating Arctic sea ice thickness sampling strategies

2015 ◽  
Vol 9 (4) ◽  
pp. 1721-1733 ◽  
Author(s):  
T. Kaminski ◽  
F. Kauker ◽  
H. Eicken ◽  
M. Karcher
Keyword(s):  
Sea Ice ◽  
Network Design ◽  
Chukchi Sea ◽  
Software Tool ◽  
Severity Index ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Target Area ◽  
Sea Ice Thickness ◽  
Arctic Sea

Abstract. We present a quantitative network design (QND) study of the Arctic sea ice–ocean system using a software tool that can evaluate hypothetical observational networks in a variational data assimilation system. For a demonstration, we evaluate two idealised flight transects derived from NASA's Operation IceBridge airborne ice surveys in terms of their potential to improve 10-day to 5-month sea ice forecasts. As target regions for the forecasts we select the Chukchi Sea, an area particularly relevant for maritime traffic and offshore resource exploration, as well as two areas related to the Barnett ice severity index (BSI), a standard measure of shipping conditions along the Alaskan coast that is routinely issued by ice services. Our analysis quantifies the benefits of sampling upstream of the target area and of reducing the sampling uncertainty. We demonstrate how observations of sea ice and snow thickness can constrain ice and snow variables in a target region and quantify the complementarity of combining two flight transects. We further quantify the benefit of improved atmospheric forecasts and a well-calibrated model.

Regional differences in processes controlling Arctic sea ice floe size distribution in Chukchi Sea, East Siberian and Fram Strait during pre-ponding season

2020 ◽  
Author(s):  
Yanan Wang ◽  
Byongjun Hwang ◽  
Rajlaxmi Basu ◽  
Jinchang Ren
Keyword(s):  
Sea Ice ◽  
Size Distribution ◽  
Regional Difference ◽  
Chukchi Sea ◽  
Arctic Sea Ice ◽  
Fram Strait ◽  
East Siberian Sea ◽  
Arctic Sea ◽  
Before And After ◽  
Western Arctic

<p>The floe size distribution (FSD) is important to the physical and biological processes in the marginal ice zone (MIZ). The FSD is controlled by ice advection, thermodynamics (lateral melting), and dynamics (winds, tides, currents and ocean swell). These thermodynamic and dynamic conditions are different between the western Arctic (e.g., Chukchi and Beaufort Seas) and the eastern Arctic (e.g., Fram Strait). For example, the MIZ in the western Arctic is strongly influenced by a warm ocean due to enhanced sea-ice albedo feedback, while the MIZ in the eastern Arctic is strongly influenced by ocean swell. We hypothesise that this regional difference can affect the FSD differently between the two regions. To address the hypothesis, we analysed the FSD data derived the images from MEDEA and synthetic aperture radar (SAR) TerraSAR-X in Chukchi Sea, East Siberian Sea and Fram Strait. Our results show that the FSD in Chukchi Sea the most dynamic as it contains a larger percentage of smaller floes and undergoes a greater interannual variability in the FSD compared to East Siberian Sea and Fram Strait. In particular, the FSD in Chukchi Sea shows a notable change before and after 2012. This change is likely attributed to the severe storm occurred in early August 2012 and the presence of thinner ice in this region.</p>

scholarly journals Arctic sea-ice melt in 2008 and the role of solar heating

2011 ◽  
Vol 52 (57) ◽  
pp. 355-359 ◽  
Author(s):  
Donald K. Perovich ◽  
Jacqueline A. Richter-Menge ◽  
Kathleen F. Jones ◽  
Bonnie Light ◽  
Bruce C. Elder ◽  
...  
Keyword(s):  
Sea Ice ◽  
Heat Input ◽  
Large Scale ◽  
Beaufort Sea ◽  
Arctic Sea Ice ◽  
Solar Heat ◽  
Ice Melt ◽  
Ice Surface ◽  
Arctic Sea ◽  
Ice Concentration

AbstractThere has been a marked decline in the summer extent of Arctic sea ice over the past few decades. Data from autonomous ice mass-balance buoys can enhance our understanding of this decline. These buoys monitor changes in snow deposition and ablation, ice growth, and ice surface and bottom melt. Results from the summer of 2008 showed considerable large-scale spatial variability in the amount of surface and bottom melt. Small amounts of melting were observed north of Greenland, while melting in the southern Beaufort Sea was quite large. Comparison of net solar heat input to the ice and heat required for surface ablation showed only modest correlation. However, there was a strong correlation between solar heat input to the ocean and bottom melting. As the ice concentration in the Beaufort Sea region decreased, there was an increase in solar heat to the ocean and an increase in bottom melting.

Temporal and vertical variations of lipid biomarkers during a bottom ice diatom bloom in the Canadian Beaufort Sea: further evidence for the use of the IP25 biomarker as a proxy for spring Arctic sea ice

Polar Biology ◽  
2010 ◽  
Vol 34 (12) ◽  
pp. 1857-1868 ◽  
Author(s):  
Thomas A. Brown ◽  
Simon T. Belt ◽  
Benoît Philippe ◽  
Christopher J. Mundy ◽  
Guillaume Massé ◽  
...  
Keyword(s):  
Sea Ice ◽  
Beaufort Sea ◽  
Arctic Sea Ice ◽  
Lipid Biomarkers ◽  
Diatom Bloom ◽  
Arctic Sea ◽  
Vertical Variations

scholarly journals PRELIMINARY RESULTS OF SEA ICE FREEBOARD MEASUREMENTS OF BEAUFORT SEA FROM CRYOSAT-2 ALTIMETRY

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1811-1815
Author(s):  
S. Zhang ◽  
Y. Zuo ◽  
F. Xiao ◽  
L. Yuan ◽  
T. Geng ◽  
...  
Keyword(s):  
Sea Ice ◽  
Sea Water ◽  
High Reliability ◽  
Beaufort Sea ◽  
Arctic Sea Ice ◽  
Reliability Estimation ◽  
The Arctic ◽  
Average Height ◽  
Maximum Value ◽  
Arctic Sea

<p><strong>Abstract.</strong> Satellite altimetry has been used to observe the Arctic sea ice in long term and large scale, and the records show a continued decline for Arctic sea ice thickness over decades. In this study, the sea ice freeboard in Beaufort Sea of Arctic have been estimated using CryoSat-2 data, and validated with Upward Looking Sonar (ULS) data of Beaufort Gyre Exploration Project (BGEP). The results show an obvious seasonal variation of the Beaufort Sea with a high reliability estimation of the sea ice freeboard. The average height of the sea ice freeboard increase from January to March and achieve the maximum value 0.38&amp;thinsp;m in March. The sea ice melts after March and the average height of the sea ice freeboard reduces to the minimum 0.12&amp;thinsp;m in August. In the next few months the sea water begins to freeze and the average height of the sea ice freeboard will increase to the maximum value.</p>

Assessment of relationships between Arctic sea ice and stratification of water column modelled by NEMO version 4.0

2020 ◽  
Author(s):  
Byoung Woong An ◽  
Pil-Hun Chang
Keyword(s):  
Sea Ice ◽  
Water Column ◽  
Chukchi Sea ◽  
Numerical Models ◽  
Forecast Accuracy ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
The Impact

&lt;p&gt;The Arctic Ocean is globally important for the weather and climate and has a unique environment. Therefore accurate prediction of the Arctic sea ice remains crucial in most numerical models. It is because small changes within the atmosphere or the ocean can cause major changes in the areal extent and thickness of the sea ice. Such changes, in turn, will have pronounced effects on the ocean and atmosphere through modification of the albedo, the ocean-atmosphere heat and momentum exchanges, and the ocean-ice heat and salt fluxes. The focus of this study is on the impact of such coupling on sea ice and upper ocean properties and the halostad related sea ice variations and inflows from Oceans. To assess the impact of the vertical mixing, we perform a set of sensitivity experiments with a global oceanic configuration at 1/4&amp;#176; resolution based on the version 4.0 of NEMO (Nucleus for European Modelling of the Ocean). In particular we examine the spatio-temporal distributions of Pacific and Eastern Arctic origin waters in the Chukchi Sea using 2016-2018 hydrographic data. Overall, the model agrees well with observations in terms of sea ice extent in spite of inaccurate vertical stratification of the water column. We conclude that beyond seasonal time scale forecast accuracy could be improved by more accurate representation of the structure of water masses.&lt;/p&gt;

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