An evaluation of deep soil configurations in the CLM3 for improved representation of permafrost
Bibliographic record
Abstract
A thin layer of soil used in many coupled global climate models does not resolve the heat reservoir represented by underlying ground material. Under representation of this feature leads to unrealistic simulation of temperature dynamics in the active layer and permafrost. Using the Community Land Model (CLM3) and its modifications we estimate a required thickness of soil layers to calculate temperature dynamics within certain errors. Our results show that to compute the annual cycle of temperature dynamics for cold permafrost, the soil thickness should be at least 30 meters. Decadal‐to‐century time scales require significantly deeper soil layers, e.g. hundreds of meters. We also tested a new geometrical configuration of the soil layer geometry which is called slab permafrost. This configuration is represented by a thick soil layer underneath the traditional resolved soil layer. The model configuration with 30 m deep resolved soil layer and a 30 to 100 m thick slab shows results that favorably compare with our benchmark model which has a fully resolved 300 m‐deep soil layer.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".