Operational Ocean Ice Prediction System Validation for the Canadian Arctic and Northwest Atlantic
Bibliographic record
Abstract
Abstract Ocean-Ice prediction systems maximize the information value of scarce in-situ ocean and ice observations. They provide assessed and forecast ocean and ice conditions that combine satellite observations and in-situ observations along with ocean and ice physics. Such information supports many applications and marine operations including navigation in open and ice covered waters, search and rescue drift prediction and oil spill drift prediction (with and without ice cover). Additional benefits include more accurate weather predictions through coupling of prediction systems and better oceanographic information support for marine resources and marine life applications. With decreasing ice coverage and increased navigation activity in the Arctic, the availability of operational ocean and ice predictions are important for ensuring safety of marine operations as well as timely responses to marine emergencies. We review the validation methodology of ocean ice prediction systems for the Canadian North under the Canadian Operational Network of Environmental PredicTion System (CONCEPTS) activities. CONCEPTS is an MOU governing an ocean, ice and atmospheric prediction collaboration of three government departments: National Defense, Environment and Climate Change Canada and Fisheries and Oceans Canada. Validation metrics include comparisons of ice and ocean forecast parameters against satellite (AMSRE Radiometry, Cryosat Altimetry) and in-situ observations from ships, moorings and autonomous floats. Forecast performance for the years 2015 and 2016 are presented herein. The overall goal is to estimate forecast reliability through development of vetted procedures for providing performance statistics against observations, both in real time and delayed mode for the Canadian CONCEPTS Ocean Ice Prediction systems. The approach is part of the GODAE Ocean View international collaboration network in Operational Oceanography for comparing ocean ice predictions against observations. Ultimately we aim to provide a framework by which participating ocean operators can provide in-situ observations from their assets (ships, rigs, ice camps, etc.) and receive performance stats (year in review, month in review) of ocean and ice prediction systems against the observations they provide.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".