Future Changes in Arctic River Runoff and its Impact on the Ocean
Bibliographic record
Abstract
Freshwater plays an important role in the Arctic Ocean, where stratification and circulation are dominated by salinity. River runoff is an important piece of the Arctic freshwater budget, and it is changing rapidly with climate change. River runoff into the Arctic Ocean has been increasing in both amount and temperature, a trend which is expected to continue into the future. We look at forcing a state of the art ocean model with future runoff projections for the Arctic Ocean, to understand how this increase in runoff temperature and flow impacts the changing Arctic. Runoff projections are produced using the A-HYPE hydrological model, over the Arctic drainage basin, giving both runoff and river temperature data. These are used to force a regional configuration of the Nucleus for European Modelling of the Ocean (NEMO) framework 4.2, with a nested 1/12 degree Arctic Ocean. As opposed to traditional methods of linearly scaling runoff for future projections, combining hydrological model output with ocean models gives a more complete spatially and temporally varying picture of runoff. Changes in river runoff has implications for sea ice futures, circulation patterns, freshwater storage and release of freshwater to lower latitudes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".