Projected Freshening of the Arctic Ocean in the 21st Century
Bibliographic record
Abstract
Abstract Using state‐of‐the‐art models from the Coupled Model Intercomparison Project phase 5 (CMIP5), this study found the upper Arctic Ocean likely to freshen considerably in the future. Arctic Ocean average sea surface salinity is projected to decrease by 1.5 ± 1.1 psu, and the liquid freshwater column is projected to increase by 5.4 ± 3.8 m by the end of the 21st century under the Representative Concentration Pathway 8.5 (RCP8.5) scenario. Most freshening would occur in the Arctic Ocean basins, that is, the Canada, Makarov, and Amundsen basins. Anomalies in freshwater flux from sea ice melt, Bering Strait inflow, net precipitation (P‐E), river runoff, and freshwater through the Barents Sea Opening (BSO) would contribute to Arctic Ocean freshening. CMIP5 historical and RCP8.5 experiments showed that the respective projected contributions from BSO freshwater flux, river runoff, P‐E, and Bering Strait inflow are about 6.4, 5.0, 2.7, and 2.2 times the contribution from sea ice melt averaged throughout the 21st century. Contributions from sea ice melt and Bering Strait inflow would increase and then decrease gradually, while those from BSO freshwater flux, river runoff, and P‐E would increase continuously. The CMIP5 models are able to simulate the Arctic Ocean freshwater system more accurately than CMIP3 models. However, the simulated rate of increase of freshwater content (296 ± 232 km 3 /yr) is weaker than estimated (600 ± 300 km 3 /yr) based on observations (1992–2012). Moreover, the simulated BSO and Davis Strait freshwater fluxes still exhibit substantial intermodel spread and they differ considerably from observed values.
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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 | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".