Physical drivers of interannual chlorophyll variability in the eastern subtropical North Atlantic
Bibliographic record
Abstract
Interannual chlorophyll variability and its driving mechanisms are evaluated in the eastern subtropical North Atlantic, where elevated surface chlorophyll concentrations regularly extend more than 1500 km into the central subtropical North Atlantic and modulate the areal extent of the North Atlantic's lowest chlorophyll waters. We first characterize the considerable interannual variability in the size of the high chlorophyll region using SeaWiFS satellite data. We then evaluate the relationship between satellite chlorophyll and sea surface height (SSH), which are anticorrelated in the study region, most likely as a result of the inverse relationship between SSH and nutricline depth. To put these results in a longer temporal context, we study a hindcast simulation of a global ocean model with biogeochemistry (GFDL's MOM4.1 with TOPAZ biogeochemistry), after evaluating the model's skill at simulating chlorophyll and SSH relative to observations. In the simulation, the variability seen during the satellite era appears to be imbedded in a much larger multidecadal modulation. The drivers of such variability are assessed by evaluating all the terms in the nutrient budget of the euphotic zone. Because diffusive processes are not a dominant control on nutrient supply, stratification is not a good indicator of nutrient supply. Rather, vertical advection of nutrients, strongly tied to Ekman pumping, is the leading driver of variability in the size of the high chlorophyll region and the productivity within the study area.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".