wrf-install
NewClaude Code skill: complete WRF+WPS compilation and installation from source
Summary
This skill automates the complete compilation and installation of the Weather Research and Forecasting (WRF) model and its preprocessing system (WPS) from source code.
- It handles dependency resolution, including NetCDF and MPI libraries, saving developers hours of manual configuration and troubleshooting.
Install & Usage
mkdir -p .claude/skillsmkdir -p .claude/skills && curl -o .claude/skills/wrf-install.md https://raw.githubusercontent.com/cainiaoxiaotao/wrf-install.git/main/SKILL.md/wrf-installUse Cases
Usage Examples
/wrf-install --wrf-version 4.5 --wps-version 4.5 --with-mpi
Install WRF and WPS with NetCDF support for a single-node forecast run.
/wrf-install --help
Security Audits
Frequently Asked Questions
What is wrf-install?
This skill automates the complete compilation and installation of the Weather Research and Forecasting (WRF) model and its preprocessing system (WPS) from source code. It handles dependency resolution, including NetCDF and MPI libraries, saving developers hours of manual configuration and troubleshooting.
How to install wrf-install?
To install wrf-install: create the skills directory (mkdir -p .claude/skills), then run: mkdir -p .claude/skills && curl -o .claude/skills/wrf-install.md https://raw.githubusercontent.com/cainiaoxiaotao/wrf-install.git/main/SKILL.md. Finally, /wrf-install in Claude Code.
What is wrf-install best for?
wrf-install is a skill categorized under Development. It is designed for: claude-code, claude-skill, wrf, wps, weather, forecast, netcdf, mpi.
What can I use wrf-install for?
wrf-install is useful for: Set up a fresh WRF+WPS environment on a new Linux server for weather forecasting research.; Recompile WRF with different compiler options or optimization flags for performance tuning.; Install WRF with MPI parallelization support for running distributed simulations on a cluster.; Automate the installation of NetCDF and other required libraries as part of a CI/CD pipeline for weather models.; Quickly reproduce a known working WRF build configuration across multiple machines.; Upgrade an existing WRF installation to a newer version without manual dependency hunting..