Modelling convectively induced secondary circulations in the <i>terra incognita</i> with <scp>TerrSysMP</scp>
Bibliographic record
Abstract
Advances in high‐performance computing have led to kilometre and even sub‐kilometre scale regional simulations with numerical weather prediction models. This range of grid resolution – also termed ‘ terra incognita ’ – approaches the length‐scale of the most energetic eddies of the convective atmospheric boundary layer ( ABL ), which accordingly can only be inadequately resolved. This dilemma becomes particularly obvious when simulating convectively induced secondary circulations ( CISCs ) in the terra incognita , because the modelled CISC ‐like circulations – also termed M‐CISCs – are poorly resolved and exhibit a grid‐resolution dependence. Previous studies have pointed out this problem using different modelling platforms and also suggested options for attenuating poorly resolved M‐CISCs with methods specific to the applied ABL schemes. This study examines M‐CISCs at horizontal grid resolutions of O (1 km), using the Terrestrial Systems Modelling Platform ( TerrSysMP ) for idealized and real case studies. The analysis of simulations using different surface heterogeneity and grid resolutions of O (1 km) shows that the presence of a superadiabatic layer near the surface and the increase of the horizontal grid resolution allow the critical Rayleigh number to be exceeded, generating poorly resolved M‐CISCs , whose amplitudes are strongly dependent on the horizontal grid resolution. We show that the asymptotic turbulent mixing length‐scale in the used ABL scheme can be tuned in a way that M‐CISCs are attenuated while the non‐resolved turbulence dealt with by the ABL scheme effectively propagates the surface fluxes into the ABL and sustains reasonable ABL profiles.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".