Water temperature, mixing, and ice phenology in the arctic–alpine Lake Darfáljávri (Lake Tarfala), northern Sweden
Bibliographic record
Abstract
In the rapidly warming circumpolar Arctic, recent research of lakes has focused on their climatology and ecology but is challenged by sparsity of wintertime data. At the c. 48-m-deep and c. 0.5-km2 large proglacial Darfáljávri (Lake Tarfala), located in an arctic–alpine environment in the Scandinavian Mountains, year-round water temperatures were previously reported for 2016 to 2019. Here, this record is continued for 2019–2020 and 2021–2022, complemented by time-lapse imagery records of the state of the lake surface, as well as degree-day modeling of ice phenology (timing of ice-on and ice-off). Darfáljávri is cryostratified during winter, with interannual variations in the thermocline’s thickness and temperature range. The ice season lasts from October to July. Modeled ice-on dates match observed ones reasonably well; however, observed ice-off dates occur much later than modeled ones, likely because of cold impact from Darfáljávri’s glacial environment as inferred from a comparison with a close tundra lake. Though new insights into the complex lake mixing and ice phenology are provided, it remains to attribute the characteristics of Darfáljávri’s winter stratification to additional potential drivers, such as lake ice thickness, atmospheric heat fluxes, and the water balance of the lake.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".