Observation and simulation of a floe drift near the North Pole

Shu, Qi; Ma, Hongguang; Qiao, Fangli

doi:10.1007/s10236-012-0554-4

Cited by 8 publications

(6 citation statements)

References 12 publications

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“…Um represents the mean state, and this can be estimated from the constant ratio We first calculated Um by averaging the ratio (U/Ua) over 6 hour for the months of November and December 2012, obtaining Um = 0.018 m s -1 ± 0.007 (N=244). This value is comparable to or slightly larger than the values reported in some of previous studies (Shu et al, 2012;Fissel and Tang, 1991;Thorndike and Colony, 1982), although other studies have shown smaller values (Lukovich et al, 2011). U was then calculated by U = U -Um.…”

Section: Atmospheric Forcingsupporting

confidence: 82%

Small-scale deformation of an Arctic sea ice floe detected by GPS and satellite imagery

Hwang

Elósegui

Wilkinson

2015

Deep Sea Research Part II: Topical Studies in Oceanography

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Small-scale (~100 to 200 m) deformations of an Arctic sea ice floe were detected from multiple GPS-equipped buoys that were deployed on the same ice floe. Over a nine-month period three deformation events were recorded. At each case the event was of limited duration, each lasting less than a day. The events were highly compressive in nature with the area occupied by the buoy array decreasing by over half of the original area. The strain rate during the deformation, of the order of 10-5 s-1 , is about three orders of magnitude larger than previous estimates for brittle fracturing for cracks of about 100 m in length. On the 2-day time scale, the strain rate became too small and none of the deformation events could be detected. This suggests that satellite data with longer time scales may significantly underestimate the amount of intermittent, small-scale brittle failure of total deformation. Taken as a whole, our results show the influence that large-scale wind stress can have on small-scale deformation. However, it is important to note that the impact of largescale wind stress is also dependent on the properties of sea ice as well as on the spatial and temporal evolution of the underlying forces that influence the fracturing process.

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Section: Atmospheric Forcingsupporting

confidence: 82%

Small-scale deformation of an Arctic sea ice floe detected by GPS and satellite imagery

Hwang

Elósegui

Wilkinson

2015

Deep Sea Research Part II: Topical Studies in Oceanography

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“…high-resolution sea ice dynamic models to reproduce linear kinematic features of ice deformation (e.g., Hutter and Losch, 2020). Dependence of the ratio of ice speed to wind speed on resampling frequency implies that temporal resolution should be considered carefully when using wind forcing data to parameterize or simulate sea ice drift (e.g., Shu et al, 2012).…”

Section: Discussionmentioning

confidence: 99%

Seasonal changes in sea ice kinematics and deformation in the Pacific Sector of the Arctic Ocean in 2018/19

Lei¹,

Hoppmann²,

Cheng³

et al. 2020

Preprint

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Abstract. Arctic sea ice kinematics and deformation play significant roles in heat and momentum exchange between atmosphere and ocean. However, mechanisms regulating their changes at seasonal scales remain poorly understood. Using position data of 32 buoys in the Pacific sector of the Arctic Ocean (PAO), we characterized spatiotemporal variations in ice kinematics and deformation for autumn–winter 2018/19. In autumn, sea ice drift response to wind forcing and inertia were stronger in the southern and western than in the northern and eastern parts of the PAO. These spatial heterogeneities decreased gradually from autumn to winter, in line with the seasonal evolution of ice concentration and thickness. Areal localization index decreased by about 50 % from autumn to winter, suggesting the enhanced localization of intense ice deformation as the increased ice mechanical strength. In winter 2018/19, a highly positive Arctic Dipole and a weakened high pressure system over the Beaufort Sea led to a distinct change in ice drift direction and an temporary increase in ice deformation. During the freezing season, ice deformation rate in the northern part of the PAO was about 2.5 times that in the western part due to the higher spatial heterogeneity of oceanic and atmospheric forcing in the north. North–south and east–west gradients in sea ice kinematics and deformation of the PAO observed in autumn 2018 are likely to become more pronounced in the future as sea ice losses at higher rates in the western and southern than in the northern and western parts.

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“…Figures 3a-3d show that C dw varies with Re at different D/h w and α w (Note that open circles represent FDS results, see details in Section 4.2). According to the ridge parameters and ice velocity characteristics in Table 1 (Kreyscher et al, 2000;Leppäranta, 2011;Shu et al, 2012;Thorndike & Colony, 1982), Re ranges from 8.7 × 10 4 to 1.1 × 10 8 in the Arctic Ocean. Field experiments have been performed to study the turbulent boundary layer under sea ice (McPhee, 2002(McPhee, , 2008.…”

Section: Labe Measurementsmentioning

confidence: 99%

“…Note. The Reynolds number Re is calculated from keel wet length (Equation 6), where ice velocity U takes on a characteristic value between 0.01 and 1 m/s (Kreyscher et al, 2000;Leppäranta, 2011;Shu et al, 2012;Thorndike & Colony, 1982). Abbreviation: FY, first-year.…”

Section: Fds Setupmentioning

confidence: 99%

On the Form Drag Coefficient Under Ridged Ice: Laboratory Experiments and Numerical Simulations From Ideal Scaling to Deep Water

Lü

Leppäranta

et al. 2021

JGR Oceans

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The bottom topography of ridged sea ice differs greatly from that of other sea‐ice types. The form drag of ridge keels has an important influence on sea‐ice drift and deformation. In this study, both laboratory experiment (LabE) and fluid dynamics numerical simulation (FDS) have been carried out for a physical ridge model in a tank to better understand the quantitative characteristics of the form drag. The LabEs covered both laminar and turbulent conditions. The local form drag coefficient of a keel, Cdw, varied with the keel depth hw and the slope angle αw in the turbulent regime. After validated by the LabE measurements, the FDSs were employed to extend the parameterization from the finite water depth to deep water. The results gave Cdw = 0.68∙ln (αw/7.8°), R2 = 0.998, 10° ≤ αw ≤ 90°, with Cdw ranging from 0.17 to 1.66, when the keel depth was much less than the water depth. For a large ridging intensity (keel depth/spacing ≥0.01), the variation of the local form drag coefficient and its contribution to total drag coefficient were sensitive to the keel slope angle. Assuming the log‐normal distribution for this angle, the average value of the local form drag coefficient was 0.75, recommended for sea‐ice dynamic models.

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Observation and simulation of a floe drift near the North Pole

Cited by 8 publications

References 12 publications

Small-scale deformation of an Arctic sea ice floe detected by GPS and satellite imagery

Small-scale deformation of an Arctic sea ice floe detected by GPS and satellite imagery

Seasonal changes in sea ice kinematics and deformation in the Pacific Sector of the Arctic Ocean in 2018/19

On the Form Drag Coefficient Under Ridged Ice: Laboratory Experiments and Numerical Simulations From Ideal Scaling to Deep Water

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