Global water balance and atmospheric water vapour transport at last glacial maximum: climate simulations with the Canadian Climate Centre for Modelling and Analysis atmospheric general circulation model
Bibliographic record
Abstract
A series of new simulations of the climate state at last glacial maximum has been performed using the Canadian second-generation atmospheric general circulation model and are described herein. The primary goal has been to assess the dynamic changes in the global water balance and water vapour transport that were characteristic of the climate state during this epoch of Earth's history. We pay special attention to comparisons of the atmospheric model simulations of last glacial maximum climate with those produced with a much simpler coupled energy balance-ice-sheet model, which has been designed to simulate the late Pleistocene cycle of glacial-interglacial ice volume variations. Our analyses, using the atmospheric model, demonstrate that the vigour of the hydrological cycle was markedly decreased under last glacial maximum conditions, as would be expected on the simplest thermodynamic grounds. The primary components of the hydrological cycle in the atmospheric model, namely precipitation and evaporation, constitute essential mechanisms that control ice-sheet mass balance. We also investigate changes in the Northern Hemisphere stationary wave patterns, as well as changes in the total and eddy moisture transport by the global circulation at last glacial maximum to illustrate the role played by the dynamics of the atmosphere in the maintenance of the Northern Hemisphere ice sheets. In particular, we find that the enhancement of the stationary wave pattern along with the convergence in atmospheric water vapour transport produces increased cooling and snow accumulation at last glacial maximum over the southeastern lobes of the Laurentide Ice Sheet. This suggests an explanation for the previously unexplained extension of these lobes deep into the New England states.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".