glm-calibration
CommunityCalibrate GLM params to minimize RMSE.
AuthorKaiserWhoLearns
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Calibrate GLM parameters for water temperature simulations to minimize RMSE between modeled and observed temperatures, enabling more accurate hydrological predictions.
Core Features & Use Cases
- Parameter tuning for Kw, coef_mix_hyp, wind_factor, lw_factor, and ch to improve model fidelity.
- Supports both automated optimization using Python (SciPy minimize) and manual calibration per best practices.
- Use cases include lake temperature forecasting, scenario analysis, and model validation against observational data.
Quick Start
Run the calibration workflow with the default parameters to begin optimizing RMSE against observed data.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: glm-calibration Download link: https://github.com/KaiserWhoLearns/skillsbench/archive/main.zip#glm-calibration Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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