Sea ice and iceberg observations in the western Barents sea in 1987

Løset, Sveinung; Carstens, Torkild

doi:10.1016/0165-232x(95)00029-b

Cited by 20 publications

(7 citation statements)

References 9 publications

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“…The sea ice in the Barents Sea is predominantly seasonal ice, but multi‐year ice is regularly advected from the Arctic Basin. The marginal ice zone (MIZ) in the Western Barents Sea extends south to 75°–78° N in early spring and retreats to about 80°–82° N in late summer, with a trend to higher latitudes during the last 10 years [ Løset and Carstens , 1996; Tronstad et al , 2007]. The sea ice extent in the Barents Sea shows high interannual variability, overlaying a negative trend in summer ice extent 1966–1988 [ Vinje and Kvambekk , 1991].…”

Section: Introductionmentioning

confidence: 99%

Decrease of sea ice thickness at Hopen, Barents Sea, during 1966–2007

Gerland

Renner

Godtliebsen

et al. 2008

Geophysical Research Letters

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[1] Seasonal fast ice thickness at the island of Hopen (Barents Sea) was monitored over 40 years. Sea ice thickness variability as a climate indicator provides more quantitative information on the state of the ice cover than solely sea ice extent. Usually, starting to form just before December Hopen fast ice reaches maximum thickness in May (on average 0.99 m), before the ice starts to decay. Swell, currents, and winds interrupt the fast ice development at Hopen during several of the winters observed, leading to ice removal and new ice formation. Since 2000, no ice thicker than 1.0 m was observed. We find a trend in the ice thickness anomalies of À0.11 m per decade, coinciding with decreasing seasonal maximum ice thickness, and an increase in local surface air and water temperatures. This is consistent with the decreasing sea ice extent in the Barents Sea and the entire Arctic.

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Section: Introductionmentioning

confidence: 99%

Decrease of sea ice thickness at Hopen, Barents Sea, during 1966–2007

Gerland

Renner

Godtliebsen

et al. 2008

Geophysical Research Letters

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“…The study adopted several field observations to analyze the iceberg draft. The key values of 12 field studies reported by El-Tahan et al (1985) (38 cases), Woodworth-Lynas et al (1985) (1 case), Løset and Carstens (1996) (52 cases), Barker et al (2004) To demonstrate the significant difference between the means of the individual datasets, the T-test and the P-value for the datasets were calculated, presuming that the P-value of 0.05 or less is statistically significant (Azimi and Shiri, 2020), where an alternative hypothesis influences the likelihood of the relationship between the observed values. This P-value for the constructed dataset was estimated as 0.008, representing that the correlations were statistically significant.…”

Section: Construction Of Datasetmentioning

confidence: 96%

Determination of Parameters Affecting the Estimation of Iceberg Draft

2023

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Recent offshore oil and gas loading facilities developed in the Arctic area have led to a considerable awareness of the iceberg draft approximation, where deep keel icebergs may gouge the ocean floor, and these submarine infrastructures would be damaged in the shallower waters. Developing reliable solutions to estimate the iceberg draft requires a profound understanding of the problem’s dominant parameters. As such, the dimensionless groups of the parameters affecting the iceberg draft estimation were determined for the first time in the present study. Using the dimensionless groups recognized and the linear regression (LR) analysis, nine LR models (i.e., LR 1 to LR 9) were developed and then validated using a comprehensive dataset, which has been constructed in this study. A sensitivity analysis distinguished the premium LR models and important dimensionless groups. The best LR model, as a function of all dimensionless parameters, was able to estimate the iceberg draft with the highest level of precision and correlation along with the lowest degree of complexity. The ratio of iceberg length to iceberg height as the “iceberg length ratio” and the ratio of iceberg width to iceberg height as the “iceberg width ratio” was detected as the important dimensionless groups in the estimation of the iceberg draft. An uncertainty analysis demonstrated that the best LR model was biased towards underestimating the iceberg drafts. The premium LR model outperformed the previous empirical models. Ultimately, a set of LR-based relationships were derived for estimating the iceberg drafts for practical engineering applications, e.g., the early stages of the iceberg management projects.

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“…Since 2006, the fjord systems transitioned from an Arctic state to a more Atlantic state along the west coast of Spitsbergen (Cottier et al 2007;Muckenhuber et al 2016). In the Svalbard region, the maximum sea-ice extent typically occurs in March or April, while the minimum sea-ice extent occurs in September or October (Loset & Carstens 1996;Muckenhuber et al 2016).…”

Section: Study Sitementioning

confidence: 99%

Stability of space use in Svalbard coastal female polar bears: intra-individual variability and influence of kinship

et al. 2021

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Philopatry influences animal distribution and can lead to a kinship-based spatial structure, where proximity and relatedness are tightly linked. In the Barents Sea region, polar bears (Ursus maritimus) of the coastal ecotype remain year-round within the Svalbard archipelago. This coastal strategy is thought to be stable across years; however, little is known about the intra-individual variability in site fidelity or the influence of kinship on space use. Using high-resolution GPS telemetry, we looked at multi-year philopatry among 17 coastal female polar bears over eight years (2011–19) and investigated whether it is linked to the females’ degree of kinship. Individuals showed a stable space use in both consecutive and non-consecutive years. Yearly individual home ranges (HRs) overlapped, on average, by 44% (range: 9–96%), and their centroids were, on average, 15 km (range: 2–63 km) apart. The space use of related females revealed a year-round strong female kin structure. Annual HRs of related females overlapped, on average, by 24% (range: 0–66%), and their centroids were, on average, 18 km (range: 2–52 km) apart. In contrast, non-related females had much larger distances between centroids (average: 160 km, range: 59–283 km). Additionally, females showed a great site fidelity in all seasons: individual seasonal HR centroids were, on average, less than 30 km (range: 1.8–172 km) apart. Bears in this region seem to exhibit a stronger site fidelity than those reported from other parts of the species range. These findings also highlight the importance of maternal learning in space use.

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Sea ice and iceberg observations in the western Barents sea in 1987

Cited by 20 publications

References 9 publications

Decrease of sea ice thickness at Hopen, Barents Sea, during 1966–2007

Decrease of sea ice thickness at Hopen, Barents Sea, during 1966–2007

Determination of Parameters Affecting the Estimation of Iceberg Draft

Stability of space use in Svalbard coastal female polar bears: intra-individual variability and influence of kinship

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