Impact of the hydrological cycle on past climate changes: three illustrations at different time scales
Bibliographic record
Abstract
We investigate in the paper the impact of the hydrologic cycle on climate at different periods. The aim is to illustrate how the changes in moisture transport, precipitation pattern, and weathering may alter, at regional or global scales, the CO 2 and climate equilibriums. We choose three climate periods to pinpoint intricate relationships between water cycle and climate. The illustrations are the following. ( i ) The onset of ice-sheet build-up, 115 kyr BP . We show that the increased thermal meridian gradient of SST allows large moisture advection over the North American continent and provides appropriate conditions for perennial snow on the Canadian Archipelago. ( ii ) The onset of Indian Monsoon at the end of the Tertiary . We demonstrate that superimposed to the Tibetan Plateau, the shrinkage of the Tethys, since Oligocene, plays a major role to explain changes in the geographical pattern of the southeastern Asian Monsoon. ( iii ) The onset of Global Glaciation (750 Ma). We show that the break-up of Rodinia occurring at low latitudes is an important feature to explain how the important precipitation increase leads to weathering and carbon burial, which contribute to decrease atmospheric CO 2 enough to produce a snows ball Earth. All these periods have been simulated with a hierarchy of models appropriate to quantify the water cycle impact on climate.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".