Seasonal and interannual variations in the propagation of photosynthetically available radiation through the Arctic atmosphere
Bibliographic record
Abstract
The Arctic atmosphere–surface system transmits visible light from the Sun to the ocean, determining the annual cycle of light available to microalgae. This light is referred to as photosynthetically available radiation (PAR). A known consequence of Arctic warming is the change at the atmosphere–ocean interface (longer ice-free season, younger ice), implying an increase in the percentage of PAR being transferred to the water. However, much less is known about the recent changes in how much PAR is being transferred by the overlaying atmosphere. We studied the transfer of PAR through the atmosphere between May 21 and July 23 at a pan-Arctic scale for the period ranging from 2000 to 2016. By combining a large data set of atmospheric and surface conditions into a radiative transfer model, we computed the percentage of PAR transferred to the surface. We found that typical Arctic atmospheres convey between 60% and 70% of the incident PAR received from the Sun, meaning the Arctic atmosphere typically transmits more light than most sea ice surfaces, with the exception of mature melt ponds. We also found that the transfer of PAR through the atmosphere decreased at a rate of 2.3% per decade over the studied period, due to the increase in cloudiness and the weaker radiative interaction between the atmosphere and the surface. Further investigation is required to address how, in the warmer Arctic climate, this negative trend would compensate for the increased surface transmittance and its consequences on marine productivity.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".