Vertical and horizontal variations in phytoplankton chlorophyll <scp><i>a</i></scp> in response to a looping super typhoon
Bibliographic record
Abstract
Abstract Previous studies suggested that the increase in surface chlorophyll a (Chl a ) is due to nutrient upwelling or to the upward mixing of the subsurface Chl a maximum layer under the influence of tropical cyclones, while often ignoring the influence of the subsurface Chl a minimum layer and horizontal advection on Chl a . In this study, we show the important roles of the upward mixing of the subsurface Chl a minimum layer, horizontal advection, as well as the upwelling of the subsurface Chl a maximum layer, taking a looping super typhoon “Saola” in the northwest Pacific in August 2023 as an example. The temporal and spatial changes of Chl a and its physical properties were investigated by combining satellite, Argo, reanalysis, and model data. The results indicate that the combined effects of the upwelling of the subsurface Chl a maximum layer caused by wind stress curls and concurrent near‐surface wind mixing were responsible for the surface Chl a increase in the looping area during the typhoon, while the 13% increase in the depth‐integrated Chl a after the typhoon is mainly due to the nutrients brought by upwelling and subsequent biochemical processes. In the edge area affected by the typhoon, the surface Chl a decrease during the typhoon was mainly due to the upward mixing of the subsurface Chl a minimum layer (the effect of upwelling in this area is relatively weak). Furthermore, the horizontal advection led to a continuous surface Chl a decrease in the edge area after the typhoon. These findings could enhance understanding of Chl a dynamics post‐tropical cyclones, aiding marine ecosystem prediction.
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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 | 0.001 |
| 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".