Improvement and Implementation of a Parameterization for Shallow Cumulus in the Global Climate Model ECHAM5-HAM
Bibliographic record
Abstract
Abstract A transient shallow-convection scheme is implemented into the general circulation model ECHAM5 and the coupled aerosol model HAM, developed at the Max Planck Institute for Meteorology in Hamburg. The shallow-convection scheme is extended to take the ice phase into account. In addition, a detailed double-moment microphysics approach has been added. In this approach, the freezing processes and precipitation formation are dependent on aerosols. Furthermore, in the scheme, tracers are transported and scavenged consistently as in the rest of the model. Results of a single-column model simulation for the Barbados Oceanography and Meteorology Experiment (BOMEX) campaign are compared with previously published large-eddy simulation (LES) results. Compared to the standard version, the global ECHAM5-HAM simulations with the newly implemented scheme show a decreased frequency of shallow convection in better agreement with LES. Less shallow convection is compensated by more stratus and stratocumulus. Deep and especially midlevel convection are markedly affected by those changes, which in turn influence high-level clouds. Generally, a better agreement with the observations can be obtained. For a better understanding of the scheme’s impact and to test different setting parameters, sensitivity analyses are performed. The mixing properties, cloud-base vertical velocity, and launching layer of the test parcel, respectively, are varied. In this context, results from simulations without shallow convection are also presented.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".