ELM

What problem does it solve?

This Skill orchestrates the end-to-end ELM Knowledge Infrastructure workflow, enabling consistent setup, execution, and analysis of ELM runs within a KI framework.

Core Features & Use Cases

• End-to-end pipeline orchestration: coordinates domain/grid setup, data preparation, forcing conversion, namelist configuration, spin-up planning, and post-run analysis.
• KI tooling integration: leverages the included Python tools (convert_forcing_to_elm.py, convert_surface_data.py, run_elm.py, parse_elm_output.py) and diagnostic workflows to ensure reproducibility.
• Use Case: a researcher prepares a regional ELM spin-up with surface data and forcing, runs the model through CIME, and auto-extracts key diagnostics for validation.

Quick Start

Configure and run an end-to-end ELM KI workflow for a given site by auto-creating a case, preparing data, converting forcing, spinning up, executing, and parsing outputs.