Interannual and Seasonal Variability of the Surface Energy Balance and Temperature of Central Great Slave Lake
Bibliographic record
Abstract
This paper addresses interannual and seasonal variability in the thermal regime and surface energy fluxes in central Great Slave Lake during three contiguous open-water periods, two of which overlap the Canadian Global Energy and Water Cycle Experiment (GEWEX) Enhanced Study (CAGES) water year. The specific objectives are to compare the air temperature regime in the midlake to coastal zones, detail patterns of air and water temperatures and atmospheric stability in the central lake, assess the role of the radiation balance in driving the sensible and latent heat fluxes on a daily and seasonal basis, quantify magnitudes and rates of the sensible and latent heat fluxes and evaporation, and present a comprehensive picture of the seasonal and interannual thermal and energy regimes, their variability, and their most important controls. Atmospheric and lake thermal regimes are closely linked. Temperature differences between midlake and the northern shore follow a seasonal linear change from 6°C colder midlake in June, to 6°C warmer in November–December. These differences are a response to the surface energy budget of the lake. The surface radiation balance, and sensible and latent heat fluxes are not related on a day-to-day basis. Rather, from final lake ice melt in mid-June through to mid- to late August, the surface waters strongly absorb solar radiation. A stable atmosphere dominates this period, the latent heat flux is small and directed upward, and the sensible heat flux is small and directed downward into the lake. During this period, the net solar radiation is largely used in heating the lake. From mid- to late August to freeze up in December to early January, the absorbed solar radiation is small, the atmosphere over the lake becomes increasingly unstable, and the sensible and latent heat fluxes are directed into the atmosphere and grow in magnitude into the winter season. Comparing the period of stable atmospheric conditions with the period of unstable conditions, net radiation is 6 times larger during the period of stable atmosphere and the combined latent and sensible heat fluxes are 9 times larger during the unstable period. From 85% to 90% of total evaporation occurs after mid-August, and evaporation rates increase continuously as the season progresses. This rate of increase varies from year to year. The time of final ice melt exerts the largest single control on the seasonal thermal and energy regimes of this large northern lake.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".