Characterizing uncertainty in modeling primary terrestrial ecosystem processes
Bibliographic record
Abstract
The simulation results from models participating in the Coupled Climate Carbon Cycle Model Intercomparison Project (C 4 MIP) highlight the role of positive carbon‐climate feedback in accelerating growth of atmospheric CO 2 . The large range among models in the strength of this feedback indicates the uncertainty in our understanding of the response of the land and the oceans to continued climate warming and increasing CO 2 . Most of this uncertainty is associated with the response of terrestrial ecosystems to changes in climate and atmospheric CO 2 . The reasons for differences between models' responses to transient climate and CO 2 forcing are not easily identified because of their complex parameterizations and spatially distributed processes. In this paper, we show that a simple box model can reasonably reproduce the globally averaged primary land‐atmosphere CO 2 fluxes and carbon pools of two complex terrestrial ecosystem models (TEMs) over a range of emission scenarios. The parameters of the box model are calculated by fitting the box model to each TEM's response to transient climate and CO 2 forcing. This approach is also applied to terrestrial carbon cycle components of carbon‐climate models participating in the C 4 MIP study. The resulting set of parameter values based on a common box model structure yields a wide range of parameter values, which suggests an absence of clear consensus in modeling primary terrestrial ecosystem processes and provides some insight into the reasons for divergent responses of terrestrial carbon cycle components.
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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".