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Run2 glm config

Skill cxcscmu/SkillLearnBench/skills/b2-self-feedback-gemini-3-flash-preview/temperature-simulation/run2_glm-config

Advanced GLM configuration and calibration strategies for vertical temperature profiles.From its SKILL.md

Install
npx -y skills add cxcscmu/SkillLearnBench --skill run2_glm-config

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

1.5 KB, 369 tokens by cl100k_base, as published. Nobody here has run it

Advanced GLM Configuration

The General Lake Model (GLM) performance depends on several key parameters that govern energy balance and mixing.

Calibration Parameters and Effects

  • Kw (Light Extinction): Controls how deep light penetrates. Higher Kw keeps deep layers cooler and surface layers warmer. Range: [0.1, 0.5].
  • wind_factor: Scales input wind speed. Affects surface mixing and latent/sensible heat fluxes. Range: [0.7, 1.3].
  • lw_factor: Scales incoming longwave radiation. Affects the overall heat budget. Range: [0.7, 1.3].
  • ch (Sensible Heat Transfer): Bulk coefficient for sensible heat flux. Affects surface temperature. Range: [0.0005, 0.002].
  • coef_mix_hyp: Controls mixing below the thermocline. Lower values reduce heating of the hypolimnion. Range: [0.3, 0.7].

Configuration Workflow

  1. Baseline Run: Start with default parameters.
  2. Energy Balance: Adjust lw_factor and ch to align the overall temperature magnitude.
  3. Stratification: Adjust Kw and wind_factor to match the thermocline depth and surface temperatures.
  4. Deep Mixing: Adjust coef_mix_hyp to match deep water temperatures during summer.

Example sed command for precise replacement:

sed -i 's/\bKw\s*=\s*[0-9.e+-]*/Kw = 0.4/' glm3.nml

Or use Python regex for more complex cases.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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