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Glm calibration

Skill cxcscmu/SkillLearnBench/skills/b1-one-shot-claude-opus-4-6/temperature-simulation/glm-calibration

Calibration strategy for GLM lake temperature simulations, including parameter sensitivity and typical ranges.From its SKILL.md

Install
npx -y skills add cxcscmu/SkillLearnBench --skill glm-calibration

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

SKILL.md

1.2 KB, 319 tokens by cl100k_base, as published. Nobody here has run it

GLM Calibration for Lake Temperature

Key Calibration Parameters (Lake Mendota)

ParameterRangeEffect
Kw[0.1, 0.5]Light extinction; higher = less deep heating, stronger stratification
coef_mix_hyp[0.3, 0.7]Hypolimnetic mixing; higher = more deep mixing, warmer hypolimnion
wind_factor[0.7, 1.3]Wind speed multiplier; higher = more surface mixing
lw_factor[0.7, 1.3]Longwave radiation multiplier; affects surface energy balance
ch[0.0005, 0.002]Sensible heat transfer coefficient

Calibration Strategy

  1. Start with defaults, run, compute RMSE
  2. Adjust Kw first (strongest control on stratification)
  3. Then coef_mix_hyp (controls deep temperatures)
  4. Fine-tune wind_factor and lw_factor for surface/overall bias
  5. ch has moderate effect on surface heat exchange

RMSE Computation

  • Match observations to simulation by exact datetime and rounded depth
  • depth_sim = round(lake_depth - z) to get depth from surface
  • Overall RMSE, deep (>=13m) RMSE, summer deep (Jun-Sep, >=13m) RMSE

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

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