A Seasonally Forced Ocean–Atmosphere Model for Paleoclimate Studies
Bibliographic record
Abstract
Seasonal forcing is applied to an idealized model of the ocean-atmosphere system by prescribing monthly values of solar insolation at the top of the atmosphere and wind stress at the ocean surface.In addition, meridional near-surface wind velocities are applied for the advection term in the parameterization of the atmospheric moisture transport.The simulated seasonal cycle is compared with observations and reanalysis climatologies.It is found that the model can reasonably well simulate the present-day seasonal cycle.Largest model errors are found in the performance of the hydrological cycle.The sensitivity of the thermohaline circulation is examined with respect to seasonal versus annual-mean forcing.It is shown that meridional overturning is increased (20%) if seasonal forcing is applied instead of annual-mean forcing.Both seasonality in wind stress and insolation forcing contribute to the increased overturning.Two stable equilibria, one with deep water formation in the North Atlantic and one without, exist irrespective of seasonal or annual-mean forcing.However, lower sensitivity of the thermohaline circulation to meltwater input into the North Atlantic results if seasonal forcing is applied.It is shown that a large part of this difference is due to an increased effective vertical heat diffusion in the seasonally forced model.Vertical mixing is enhanced by the wind-induced seasonality in meridional overturning.A quantitative estimate of the difference in effective vertical eddy diffusivities between the seasonally and the annually forced model versions is given.
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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".