run_glm_simulation
Executes the GLM simulation and retrieves lake-specific depth data to ensure accurate mapping between model output and field observations.
- License 许可
- MIT
- 最近更新
- 2026-10-02
- Stars
- ★ 92
- Forks
- 7
01 前言 Front Matter
- name
- run_glm_simulation
- description
- Executes the GLM simulation and retrieves lake-specific depth data to ensure accurate mapping between model output and field observations.
03 SKILL.md 正文
Before processing, extract the lake_depth from the &init_profiles section of the namelist to correctly derive the depth of water layers (depth = lake_depth - z). Ensure the output at /root/output/output.nc is generated successfully.
import subprocess
import f90nml
import xarray as xr
def run_simulation():
# Extract lake depth from nml for correct depth calculation
nml = f90nml.read('/root/glm3.nml')
lake_depth = nml['init_profiles']['lake_depth']
# Run the model
subprocess.run(['glm', 'x86_64', '--nml', '/root/glm3.nml'], check=True)
return lake_depth
04 同仓库更多 Skills
object_counter
Count occurrences of an object in the image using computer vision algorithm.
travel-planning-workflow
Invoke this skill when performing travel planning. It defines a structured workflow for generating itineraries. Following this workflow is essential to ensure the final plan satisfies user requirements.
bundled-dataset-search-tool
invoke this skill when you need to perform database search for travel planning. This skill provides some useful pre-packaged tools to look up accommodations, attractions, cities, driving distance, flights, and restaurants from the bundled dataset.
glm-output
Output-processing guidance for GLM tasks. Especially useful after glm-basics and glm-calibration when you need verifier-matching metrics from output.nc and a final /root/metrics.json.
glm-calibration
Calibration guidance for GLM tasks. Often most effective after glm-basics has clarified the setup; glm-output is the companion skill for exact final metric computation.
glm-basics
A good starting point for GLM calibration tasks. Use to inspect glm3.nml, confirm how GLM runs, and identify the relevant files before moving on to calibration and output evaluation.