Simulation of multiannual thermal profiles in deep Lake Geneva: A comparison of one‐dimensional lake models
Why this work is in the frame
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Bibliographic record
Abstract
In this study, we report on the ability of four one‐dimensional lake models to simulate the water temperature profiles of Lake Geneva, the largest water body in Western Europe, over a 10‐yr period from 1996 to 2005, using lake models driven by a common atmospheric forcing. These lake models have already demonstrated their capability of reproducing the temperature distribution in smaller lakes and include one eddy‐diffusive lake model, the Hostetler model; a Lagrangian model, the one‐dimensional Dynamic Reservoir Simulation Model "DYRESM" a к ‐ ε turbulence model, "SIMSTRAT"; and one based on the concept of self‐similarity (assumed shape) of the temperature‐depth curve, the Freshwater Lake model "FLake." Only DYRESM and SIMSTRAT reproduce the variability of the water temperature profiles and seasonal thermocline satisfactorily. In layers in which thermocline variability is greatest, the temperature root mean square error is ≪2°C and 3°C (at the time of highest stratification) for these models, respectively. It is possible to apply certain one‐dimensional lake models that simulate the behavior of temperature to investigate the potential future warming of the water column in Lake Geneva. Importantly, the metalimnion boundary is successfully modeled, which represents an encouraging step toward demonstrating the feasibility of coupling biogeochemical modules, such as, for example, a phytoplanktonic model, to assess the possible biological responses within lakes to climate change.
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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 | 0.000 |
| 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 it