Jahn et al. 153 Arctic freshwater export variability: A model study
Bibliographic record
Abstract
We present an analysis of the variability of the Arctic freshwater (FW) export to the North Atlantic, using a simulation from the Community Climate System Model (CCSM), version 3, which includes passive tracers that track the movement of FW from the different FW sources in the Arctic. We find that in Fram Strait the FW export is mainly composed of Eurasian river runoff and FW of Pacific origin, whereas the FW export through the Canadian Arctic Archipelago (CAA) is mainly composed of Pacific FW and North American runoff. The FW export variability is found to be related to changes in the large-scale atmospheric forcing over the Arctic, and not to changes in the FW input. We show that the details of the export variability are different for the export through Fram Strait and the CAA, with a much larger influence of salinity changes in the Fram Strait outflow than in the CAA, where the FW export variability is dominated by velocity anomalies. This difference explains the higher correlation of the Arctic Oscillation (AO) index with the liquid FW export through the CAA than through Fram Strait. The export of FW from different sources also shows differences in the correlation with the AO index, with much larger correlations between the export of Pacific FW, Eurasian river runoff, and North American river runoff and the AO than for the total liquid FW export.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".