ELM

Orchestrate end-to-end ELM runs with KI tools for preprocessing, execution, and analysis.

1|Updated Mar 31, 2026
One-click install
npx skills add https://github.com/lzwei196/KISS---Knowledge-Infrastructure-for-Scientific-Simulation --skill elm
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ELM
Source: https://github.com/lzwei196/KISS---Knowledge-Infrastructure-for-Scientific-Simulation/tree/main/models/ELM
Command: npx skills add https://github.com/lzwei196/KISS---Knowledge-Infrastructure-for-Scientific-Simulation --skill elm

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, pandas, netCDF4, xarray.

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.

Frequently Asked Questions about ELM

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate the ELM earth system model workflow from forcing conversion to output parsing?▼

Yes, the ELM knowledge infrastructure framework includes Python tools for surface data preparation, forcing conversion, namelist configuration, and spin-up planning, covering the full preprocessing pipeline before HPC execution.

Can I use xarray and netCDF4 to parse ELM model outputs?▼

The ELM workflow enforces consistent structure, unit-aware data handling, and safety checks across preprocessing, execution, and post-processing, ensuring reproducibility for researchers preparing regional spin-ups and HPC runs.

What is the best way to configure namelists and spin up carbon pools for ELM runs?▼

The workflow includes Python tools like convert_surface_data.py and run_elm.py to handle domain setup, data preparation, and CIME-based model execution, ensuring consistent configuration across HPC environments.

Does the ELM knowledge infrastructure support regional spin-up and HPC execution?▼

It leverages included Python tools such as convert_forcing_to_elm.py, convert_surface_data.py, run_elm.py, and parse_elm_output.py to ensure reproducible workflows from domain setup to post-run analysis.

How do I prepare surface data and convert forcing for ELM earth system model runs?▼

The workflow enforces consistent structure across preprocessing, execution, and post-processing, enabling researchers to auto-extract key diagnostics for validation after HPC runs.