A Simple Coupled Atmosphere–Ocean–Sea Ice–Land Surface Model for Climate and Paleoclimate Studies*
Bibliographic record
Abstract
The authors develop a coupled atmosphere–ocean–sea ice–land surface model for long-term climate change studies that incorporates the seasonal cycle. Three ocean basins, the Antarctic Circumpolar Current region, and the major continents are resolved. The model variables are sectorially averaged across the different ocean basins and continents. The atmosphere is represented by an energy–moisture balance model in which the meridional energy and moisture transports are parameterized by a combination of advection and diffusion processes. The zonal heat transport between land and ocean obeys a diffusion law, while the zonal moisture transport is parameterized so that the ocean always supplies moisture to the land. The ocean model is due to Wright and Stocker, and the sea ice model is a zero-layer thermodynamic one in which the ice thickness and concentration are predicted by the methods of Semtner and Hibler, respectively. In the land surface model, the temperature is predicted by an energy budget equation, similar to Ledley’s, while the soil moisture and river runoff are predicted by Manabe’s bucket model. The above model components are coupled together using flux adjustments in order to first simulate the present-day climate. The major features of this simulation are consistent with observations and the general results of GCMs. However, it is found that a diffusive law for heat and moisture transports gives better results in the Northern Hemisphere than in the Southern Hemisphere. Sensitivity experiments show that in a global warming (cooling) experiment, the thermohaline circulation (THC) in the North Atlantic Ocean is weakened (intensified) due to the increased (reduced) moisture transport to the northern high latitudes and the warmer (cooler) SST at northern high latitudes. Last, the coupled model is employed to investigate the initiation of glaciation by slowly reducing the solar radiation and increasing the planetary emissivity, only in the northern high latitudes. When land ice is growing, the THC in the North Atlantic Ocean is intensified, resulting in a warm subpolar North Atlantic Ocean, which is in agreement with the observations of Ruddiman and McIntyre. The intensified THC maintains a large land–ocean thermal contrast at high latitudes and hence enhances land ice accumulation, which is consistent with the rapid ice sheet growth during the first 10 kyr of the last glacial period that was observed by Johnson and Andrews. The authors conclude that a cold climate is not responsible for a weak or collapsed THC in the North Atlantic Ocean; rather it is suggested that increased freshwater or massive iceberg discharge from land is responsible for such a state.
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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) | 0.001 | 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 | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".