Effect of mosaic representation of vegetation in land surface schemes on simulated energy and carbon balances
Bibliographic record
Abstract
Abstract. Energy and carbon balance implications of representing vegetation using a composite or mosaic approach in a land surface scheme are investigated. In the composite approach the attributes of different plant functional types (PFTs) present in a grid cell are aggregated in some fashion for energy and water balance calculations. The resulting physical environmental conditions (including net radiation, soil moisture and soil temperature) are common to all PFTs and affect their ecosystem processes. In the mosaic approach energy and water balance calculations are performed separately for each PFT tile using its own vegetation attributes, so each PFT "sees" different physical environmental conditions and its carbon balance evolves somewhat differently from that in the composite approach. Simulations are performed at selected boreal, temperate and tropical locations to illustrate the differences caused by using the composite versus mosaic approaches of representing vegetation. These idealized simulations use 50% fractional coverage for each of the two dominant PFTs in a grid cell. Differences in simulated grid averaged primary energy fluxes at selected sites are generally less than 5% between the two approaches. Simulated grid-averaged carbon fluxes and pool sizes at these sites can, however, differ by as much as 46%. Simulation results suggest that differences in carbon balance between the two approaches arise primarily through differences in net radiation which directly affects net primary productivity, and thus leaf area index and vegetation biomass.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".