Ocean biogeochemistry in the Canadian Earth System Model version 5.0.3: CanESM5 and CanESM5-CanOE
Bibliographic record
Abstract
Abstract. The ocean biogeochemistry components of the Canadian Earth System Model v. 5 are presented and compared to observations and other models. CanESM5 employs the same biogeochemistry module as CanESM2 whereas CanESM5-CanOE (“Canadian Ocean Ecosystem model”) is a new, more complex biogeochemistry module developed for Sixth Coupled Model Intercomparison Project (CMIP6), with multiple food chains, flexible phytoplankton elemental ratios, and a prognostic iron cycle. This new model is described in detail and the outputs compared to CanESM5 and CanESM2, as well as to observations and other CMIP6 models. Both CanESM5 models show gains in skill relative to CanESM2, which are attributed primarily to improvements in ocean circulation. CanESM5-CanOE shows improved skill relative to CanESM5 in some areas. CanESM5-CanOE includes a prognostic iron cycle, and maintains high nutrient / low chlorophyll conditions in the expected regions (in CanESM2 and CanESM5, iron limitation is specified as a temporally static ‘mask’). Surface nitrate concentrations are biased low in the subarctic Pacific and equatorial Pacific, and high in the Southern Ocean. Export production in CanESM5-CanOE is among the lowest for CMIP6 models; in CanESM5 it is among the highest, but shows the most rapid decline after about 1980. CanESM5-CanOE has relatively low concentrations of zooplankton and detritus relative to phytoplankton, and a high and relatively constant living phytoplankton fraction of total particulate organic matter. In most regions, large and small phytoplankton show decoupled seasonal cycles with greater abundance of large phytoplankton in the productive seasons. Cumulative ocean uptake of anthropogenic carbon dioxide through 2014 is lower in both CanESM5 models than in observation-based estimates or the model ensemble mean, and is lower in CanESM5-CanOE (122 PgC) than in CanESM5 (132 PgC).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".