Skip to content
cccskills
FreePublished on GitHub

glm-basics

Basic usage of the General Lake Model (GLM) for lake temperature simulation. Use when you need to run GLM, understand input files, or modify configuration parameters.

The English summary is being prepared. Showing the original description.

See how to install

Files included (1)

  • SKILL.md2.1 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

GLM Basics Guide

Overview

GLM (General Lake Model) is a 1D hydrodynamic model that simulates vertical temperature and mixing dynamics in lakes. It reads configuration from a namelist file and produces NetCDF output.

Running GLM

cd /root
glm

GLM reads glm3.nml in the current directory and produces output in output/output.nc.

Input File Structure

FileDescription
glm3.nmlMain configuration file (Fortran namelist format)
bcs/*.csvBoundary condition files (meteorology, inflows, outflows)

Configuration File Format

glm3.nml uses Fortran namelist format with multiple sections:

&glm_setup
   sim_name = 'LakeName'
   max_layers = 500
/
&light
   Kw = 0.3
/
&mixing
   coef_mix_hyp = 0.5
/
&meteorology
   meteo_fl = 'bcs/meteo.csv'
   wind_factor = 1
   lw_factor = 1
   ch = 0.0013
/
&inflow
   inflow_fl = 'bcs/inflow1.csv','bcs/inflow2.csv'
/
&outflow
   outflow_fl = 'bcs/outflow.csv'
/

Modifying Parameters with Python

import re

def modify_nml(nml_path, params):
    with open(nml_path, 'r') as f:
        content = f.read()
    for param, value in params.items():
        pattern = rf"({param}\s*=\s*)[\d\.\-e]+"
        replacement = rf"\g<1>{value}"
        content = re.sub(pattern, replacement, content)
    with open(nml_path, 'w') as f:
        f.write(content)

# Example usage
modify_nml('glm3.nml', {'Kw': 0.25, 'wind_factor': 0.9})

Common Issues

IssueCauseSolution
GLM fails to startMissing input filesCheck bcs/ directory
No output generatedInvalid nml syntaxCheck namelist format
Simulation crashesUnrealistic parametersUse values within valid ranges

Best Practices

  • Always backup glm3.nml before modifying
  • Run GLM after each parameter change to verify it works
  • Check output/ directory for results after each run

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Perform various data analysis on SEC 13-F and obtain some insights of fund activities such as number of holdings, AUM, and change of holdings between two quarters.

The English summary is being prepared. Showing the original description.

benchflow-ai/skillsbench1.9KUpdated Oct 13, 2026

AC branch pi-model power flow equations (P/Q and |S|) with transformer tap ratio and phase shift, matching `acopf-math-model.md` and MATPOWER branch fields. Use when computing branch flows in either direction, aggregating bus injections for nodal balance, checking MVA (rateA) limits, computing branch loading %, or debugging sign/units issues in AC power flow.

The English summary is being prepared. Showing the original description.

benchflow-ai/skillsbench1.9KUpdated Oct 13, 2026

Redact text from PDF documents for blind review anonymization

The English summary is being prepared. Showing the original description.

benchflow-ai/skillsbench1.9KUpdated Oct 13, 2026

Use when checking simplified ADA-derived plan-view bathroom accessibility constraints such as turning space, door clear width, toilet centerline, grab bars, and lavatory knee/toe clearance.

The English summary is being prepared. Showing the original description.

benchflow-ai/skillsbench1.9KUpdated Oct 13, 2026

Analyze failed GitHub Action jobs for a pull request.

The English summary is being prepared. Showing the original description.

benchflow-ai/skillsbench1.9KUpdated Oct 13, 2026

Use when extracting plan-view architectural geometry from DXF files with semantic CAD layers, especially when outputs must normalize rooms, doors, fixtures, clearances, and grab bars into machine-checkable JSON.

The English summary is being prepared. Showing the original description.

benchflow-ai/skillsbench1.9KUpdated Oct 13, 2026

See all skills by benchflow-ai

Report a problem with this skill