Simulations of Hydrographic Properties in the Northwestern North Atlantic Ocean in Coupled Climate Models
Bibliographic record
Abstract
Abstract The performance of coupled climate models (CCMs) in simulating the hydrographic structure and variability of the northwestern North Atlantic Ocean, in particular the Labrador and Irminger Seas, has been assessed. This area plays an important role in the meridional overturning circulation. Hydrographic properties of the preindustrial run of eight CCMs used in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) are compared with observations from the World Ocean Circulation Experiment Repeat section 7 (WOCE AR7). The mean and standard deviation of 20 yr of simulated data are compared in three layers, representing the surface waters, intermediate waters, and deep waters. Two models simulate an extremely cold, fresh surface layer with model biases down to −1.7 psu and −4.0°C, much larger than the observed ranges of variability. The intermediate and deep layers are generally too warm and saline, with biases up to 0.7 psu and 2.8°C. An analysis of the maximum mixed layer depth shows that the low surface salinity is related to a convective regime restricted to the upper 500 dbar. Thus, intermediate water formed by convection is partly replaced by warmer water from the south. Model biases seem to be caused by the coupling to the atmospheric component of the CCM. Model drift during long spinup periods allows the initially small biases in water mass characteristics to become significant. Biases that develop in the control run are carried over to the twentieth-century runs, which are initialized from the control runs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".