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Record W4302570689 · doi:10.5957/icetech-2008-150

Extremely Thick Multi-year Ice Still Exists, but Will it Last?

2008· article· en· W4302570689 on OpenAlexaffabout
M. E. Johnston

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsCanadian Cardiovascular Society
Fundersnot available
KeywordsSea iceArctic ice packDrift iceGeologySpring (device)OceanographyArcticFast iceLead (geology)Pressure ridgeAntarctic sea iceFront (military)ClimatologyPhysical geographyGeographyEngineeringPaleontology

Abstract

fetched live from OpenAlex

Reports of Climate Change, decreasing ice concentration, overall thinning of the polar cap and longer periods of open water could give the designers of ships and structures, and their operators, a false sense of security about the amount of dangerous ice, and the likelihood of encountering it. And that could have serious repercussions for everyone involved, including those who live in the Arctic. Contrary to what one might expect, the lengthening summers may actually increase the hazard that multi-year ice poses for ships and structures. Why? Because the absence of first-year ice increases the ease with which multi-year ice moves through the Arctic, and the period during which it is mobile. Take, for example, the spring of 2007, when the ice bridge that usually forms in Nares Strait, blocking the outflow of thick multi-year ice from the Lincoln Sea, failed to form. As a result, old ice streamed out of the Lincoln Sea throughout the winter – pushing the floes in front of it further and further south (Figure 1-a). Two of those floes were instrumented in Nares Strait during the summer of 2006 (Figure 1-b). One of them, Floe 5, had spent 10 months migrating south, arriving off the coast of Newfoundland in the spring of 2007. That floe, along with many others, conspired to make ice conditions off Newfoundland the worst seen in 10 to 15 years (Figure 1-c). The absence of an ice bridge across Nares Strait was one of the factors lead to the unusual amount of old ice off the coast of Newfoundland that spring. Perhaps the decreased extent of first-year ice will allow multi-year ice to move more freely, you say, but surely the longer summer and extended open water season will result in a net decrease in the thickness and strength of these multi-year ice floes? The past three years of measurements on multi-year ice are used to answer that question, starting with the topic: does very thick multi-year ice still exist?. The more than 300 drill hole measurements made on 15 multi-year ice floes in Nares Strait (2006 and 2007 seasons) and the central Canadian Arctic Archipelago (2007 and 2008) show that multi-year ice in excess of 15 m thick commonly occurs in both regions. Comparison of our measurements to past thickness measurements on multi-year ice in the Beaufort Sea (Dickins, 1989; Kovacs, 1983; Wright et al., 1984) shows good agreement in the thickness distributions of multi-year ice Arcticwide. Given Climate Change and its effect on the polar pack, are the drill hole measurements from the 1980s still representative of ice in the Beaufort Sea? The three years of on-ice measurements are also used to describe the changes that multi-year ice undergoes during its summer melt/migration period. The temperature, salinity and strength profiles of a multi-year ice hummock visited in May, June and July reveal that rapid changes occur in the uppermost 4.5 m of ice during the summer melt period (Figure 2). Results from more than 400 borehole jack tests on multi-year ice are used to demonstrate the direct relation between the temperature of multi-year ice and its strength. These kinds of on-ice measurements provide insight into the dramatic changes that have been observed in the Beaufort Sea multi-year pack ice in recent years – ships operating in the Beaufort Sea continue to report back about the decayed state of the ice cover. Ship-based and satellite observations both indicate that large areas of the multi-year pack ice seem to be rapidly disappearing. Some of those observations are discussed in the guide Understanding and Identifying Old Ice in Summer, which is discussed in Johnston and Timco (2008). The results discussed here complement that work.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0040.005
Open science0.0000.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.225
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2008
Admission routes2
Has abstractyes

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