The Importance of Spring and Autumn Atmospheric Conditions for the Evaporation Regime of Lake Superior
Bibliographic record
Abstract
Abstract Feedbacks between ice extent and evaporation have long been suspected to be important for Lake Superior evaporation because it is during autumn and winter when latent heat fluxes are highest. Recent direct measurements of evaporation made at the Stannard Rock Lighthouse have provided new information on the physical controls on Lake Superior evaporation, in particular that evaporation can react within hours to days to a change in synoptic conditions. However, the large heat capacity of the lake creates a strong seasonal cycle of energy storage and release. There is a complex interaction among heat storage, evaporation, and ice cover that is highly dependent on atmospheric conditions in the spring and autumn “shoulder seasons.” Small changes in conditions in November and March caused by synoptic-scale events can have profound impacts on annual evaporation, the extent of ice cover, and the length of the ice-covered period. Early winter air temperatures in November and December dictate the nature of ice formation and much of the winter evaporative flux. Decreased ice cover, by itself, does not necessarily lead to enhanced annual evaporation losses. Rather, a combination of low ice cover and warm spring air temperatures, leading to an early breakup, can significantly lengthen the next evaporation season and cause greater cumulative water loss the subsequent year. The influence of individual synoptic events on annual evaporation is notable enough that the research community should ensure that their role is properly captured in numerical models to provide sound predictions of future Laurentian Great Lakes evaporation regimes.
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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 | 0.000 | 0.000 |
| 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".