Numerical investigation with a coupled single-column surface-atmosphere model and an application to central Mediterranean
Bibliographic record
Abstract
An atmospheric single-column model (SCM) developed in the framework of the Canadian Regional Climate Model, CRCM, driven by NCEP-NCAR reanalyses is applied to study the non-linear interactions between the surface and the planetary boundary layer (Goyette et al., 2020). The approach to solve the model equations and the technique described may be implemented in any RCM system environment as a model option. The working hypothesis underlying this SCM formulation is that a substantial portion of the variability simulated in the column can be reproduced by processes operating in the vertical dimension and a lesser portion comes from processes operating in the horizontal dimension. This SCM offers interesting prospects as the horizontal and vertical resolution of the RCM is ever increasing. Due to its low computational cost, multiple simulations may be carried out in a short period of time. In this paper, a range of possible results obtained by changing the lower boundary from open water surface to land, and by varying model parameters are mainly shown for central Mediterranean but also for other applications. Results show that the model responded in a highly nonlinear but coherent manner in the lowest levels with changes in air temperature, moisture and windspeed profiles. The latter are consistent with those of the surface vertical sensible, latent heat and momentum fluxes. For example in the central Mediterranean, during a simulated year, air temperature is increased during all the seasons. Specific humidity is increased during the autumn and winter seasons but decreased by during the spring and summer seasons thus showing the contrasting influence of the land surface. The potential for further developments, as well as some guidance as to how to handle mixed land/open water coupling in RCMs, is also provided.GOYETTE, Stéphane, FONSECA, Cédric, TRUSCELLO, Léonard. Assessment of nonlinear effects of a deep subgrid lake with an atmospheric single‐column model. In: International Journal of Climatology, 2020. doi: 10.1002/joc.689
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".