The simulated response of the climate system to changes in soil moisture parameterization under paleoclimatic boundary conditions at 6000 years before present
Bibliographic record
Abstract
We present the results of a sensitivity study involving modifications to the simple land surface scheme implemented in the second-generation atmospheric general circulation model (GCMII) of the Canadian Climate Centre for Modelling and Analysis (CCCma), under paleoclimatic boundary conditions characteristic of 6000 calendar years before present (6 ka BP). The land surface parameterization is modified in two primary respects. Firstly, we modify the space dependant bucket depth scheme in the original model to one in which this depth is taken to be constant. Secondly, we modify the evapotranspiration parameterization from the space dependant form employed in the control model to a more conventional space independent scheme. In all, 4 experiments have been performed to enable us to resolve both the modern control and the 6 ka BP response to the land surface modifications. A subset of these simulations is also compared with results obtained using other models in the context of the Paleoclimate Model Intercomparison Project (PMIP) to investigate the mid-latitude behaviour of these models to reveal the extent to which model response to a change in radiative forcing may be significantly influenced by changes in the land surface parameterization. These comparisons reveal that the original Canadian GCMII model is an extreme outlier among the members of the set of all models in that its Northern Hemisphere mid-latitude surface continental response to the 6 ka BP insolation anomaly is significantly cold biased in the summer season. We investigate the extent to which this anomalous behaviour may be explained as a consequence of modifications to the land surface parameterizations employed in GCMII. Our results reveal a strong sensitivity in the modern control model to changes in bucket depth, but not to the modification of the evapotranspiration scheme. More interesting, however, is the fact that the model climate sensitivity at 6 ka BP is influenced both by changes in bucket depth and by changes in the evapotranspiration scheme. A detailed investigation of the surface energy balance, cloud cover, surface albedo, and snow cover reveals the role of each of the components that contribute to the 6 ka BP surface temperature response. Comparison of the predictions of the CCCma model with proxy climate indicators of lake levels and surface temperature over Canada, furthermore, demonstrate the extreme sensitivity of climate predictions for this geographical region to changes in the manner in which land surface processes are represented.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".