Representing land-ocean heterogeneity via convective adjustment timescale
Bibliographic record
Abstract
Representing land-ocean heterogeneity via convectiveadjustment timescaleBidyut Goswami1 , Andrea Polesello1 , Caroline Muller1 .1Department of Earth Science, Institute of Science and Technology Austria, Klosterneuburg, AustriaJanuary 2024AbstractThe time needed by deep convection to bring the atmosphere back to equilibriumis called convective adjustment timescale or simply adjustment timescale, typicallydenoted by τ . In the Community Atmospheric Model version 6 (CAM6), convectionis parameterized through the Zhang-McFarlan scheme [1], where CAPE undergoesan exponential consumption, of which τ is the time constant. τ is a tunable pa-rameter in CAM6 and it has a default value of 1 hour, worldwide, on both oceanand land. Albeit, there is no justified reason why one adjustment timescale valueshould work over land and ocean both. Continental and oceanic convection is dif-ferent in terms of the vigor of updraft and hence can have different durations.[2, 3]So it is logical to investigate the prescription of two different convective adjustmenttimescales for land (τL ) and ocean (τL ). To understand the impact of representingland-ocean heterogeneity via τ , we investigated CAM climate simulations for twodifferent convective adjustment timescales for land and ocean in contrast to havingone value globally.Following a comparative analysis of 5-year-long climate simulations, we findτO =4hr and τL =1hr to yield the best results. In particular, we obtain a betterdescription of the Madden-Julian Oscillation (MJO). Although these τ values werechosen empirically and require further tuning, the conclusion of our finding remainsthe same, which is, to use two different τ values for land and ocean.References[1] G. Zhang and N. A. McFarlane, “Sensitivity of climate simulations to the parameterization ofcumulus convection in the canadian climate centre general circulation model,” Atmosphere-Ocean, vol. 33, no. 3, pp. 407–446, 1995.[2] C. Lucas, E. J. Zipser, and M. A. Lemone, “Vertical Velocity in Oceanic Convection offTropical Australia,” Journal of the Atmospheric Sciences, vol. 51, pp. 3183–3193, 11 1994.[3] R. Roca, T. Fiolleau, and D. Bouniol, “A Simple Model of the Life Cycle of MesoscaleConvective Systems Cloud Shield in the Tropics,” Journal of Climate, vol. 30, pp. 4283–4298, 6 2017.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".