Constraining the strength of the terrestrial CO <sub>2</sub> fertilization effectin the Canadian Earth system model version 4.2 (CanESM4.2)
Why this work is in the frame
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Bibliographic record
Abstract
Abstract. Earth system models (ESMs) explicitly simulate the interactions between the physical climate system components and biogeochemical cycles. Physical and biogeochemical aspects of ESMs are routinely compared against their observation-based counterparts to assess model performance and to evaluate how this performance is affected by ongoing model development. Here, we assess the performance of version 4.2 of the Canadian Earth system model against four land carbon-cycle-focused, observation-based determinants of the global carbon cycle and the historical global carbon budget over the 1850–2005 period. Our objective is to constrain the strength of the terrestrial CO2 fertilization effect, which is known to be the most uncertain of all carbon-cycle feedbacks. The observation-based determinants include (1) globally averaged atmospheric CO2 concentration, (2) cumulative atmosphere–land CO2 flux, (3) atmosphere–land CO2 flux for the decades of 1960s, 1970s, 1980s, 1990s, and 2000s, and (4) the amplitude of the globally averaged annual CO2 cycle and its increase over the 1980 to 2005 period. The optimal simulation that satisfies constraints imposed by the first three determinants yields a net primary productivity (NPP) increase from ∼ 58 Pg C year−1 in 1850 to about ∼ 74 Pg C year−1 in 2005; an increase of ∼ 27 % over the 1850–2005 period. The simulated loss in the global soil carbon amount due to anthropogenic land use change (LUC) over the historical period is also broadly consistent with empirical estimates. Yet, it remains possible that these determinants of the global carbon cycle are insufficient to adequately constrain the historical carbon budget, and consequently the strength of terrestrial CO2 fertilization effect as it is represented in the model, given the large uncertainty associated with LUC emissions over the historical period.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it