Advances in upward looking sonar technology for studying the processes of change in Arctic Ocean ice climate
Bibliographic record
Abstract
A major impetus for scientific studies of climate change in the Arctic Ocean has been the reduction in the areal extent and thickness of its sea ice cover. An extended measurement record of the horizontal dimensions of this ice cover is available for the full Arctic Ocean Basin based upon a record compiled from more than 30 years of relatively continuous satellite based measurements. Unfortunately, data accumulations for the ice cover’s vertical dimension, ie, sea ice thickness, tend to be limited to data sets with durations no longer than 15 years, reflecting underlying greater measurement difficulties. Moreover, the longest duration ice thickness data collection efforts have been confined only to two specific portions of the Basin, namely, Fram Strait and the Canadian sector of the Beaufort Sea. Elsewhere, the available data sets are either of notably shorter duration or non-existent.Upward-looking sonar (ULS) has been and continues to be the primary source of data with volumes and accuracy sufficient for meaningfully monitoring ice thickness. Originally deployed from polar-traversing submarines during the Cold War, the limited amounts and accessibility of the collected data stimulated development of purpose-built sea-floor moored ULS instrumentation which, beginning in the late 1980s, began to supply the bulk of newly acquired ice draft and ice under-surface topography data. Technological advances have subsequently led to new generations of ULS instruments including ice-profiling sonar (IPS), incorporating much expanded on-board data storage capacities (69 Mbytes to 8 Gbytes) and powerful real-time firmware which now allow unprecedented temporal (ping rates of up to 1Hz) and horizontal resolution of ice topography. These instruments operate autonomously during one year or longer deployments, returning draft data on time and spatial scales of 1s and 1m or better, respectively, which are essential to understandings of mechanical and thermodynamical aspects of sea ice processes. Such processes govern ocean-atmosphere exchanges in polar waters, thereby determining ice extent and thickness parameters. The larger data storage capacities of the newest instruments also allow collection of additional information associated with acoustic returns from different levels in the upper water column and the lower ice cover. Such data have potential for improving understandings of ice processes occurring during the initial freeze-up and early consolidation phases of sea ice growth on the basis of acoustic backscatter from frazil, grease, shuga and nilas ice forms. With International Polar Year programmes now well underway, ice profiling instruments, sharing a common technology, are and/or will be deployed in unprecedented numbers from both fixed subsurface moorings and drifting buoys. This deployment commitment holds great promise for delivery of data with both temporal and spatial detail and areal coverage sufficient to strongly upgrade present capabilities for monitoring and modelling ice cover change.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".