e-learning
Functionally Assembled Terrestrial Ecosystem Simulator (FATES) with Galaxy Climate JupyterLab
Abstract
The practical aims at familiarizing you with running CLM-FATES within Galaxy Climate JupyterLab.
About This Material
This is a Hands-on Tutorial from the GTN which is usable either for individual self-study, or as a teaching material in a classroom.
Questions this will address
- Why and when using Galaxy Climate JupyterLab for CLM-FATES?
- How to start Galaxy Climate JupyterLab in Galaxy?
- How to upload input data for running CLM-FATES?
- How to create CLM-FATES case in Galaxy Climate JupyterLab?
- How to customize your run?
- How to analyze your model outputs?
- How to save your model results into a Galaxy history?
- How to share your results?
Learning Objectives
- Motivation for using the Galaxy Climate JupyterLab for CLM-FATES.
- Setting up CLM-FATES case with Galaxy Climate JupyterLab.
- Running CLM-FATES in Galaxy for single-point locations where in-situ measurements are available.
- Analyzing CLM-FATES results.
- Sharing CLM-FATES simulations.
- Composing, executing and publishing the corresponding Jupyter notebooks.
Licence: Creative Commons Attribution 4.0 International
Keywords: Climate, interactive-tools
Target audience: Students
Resource type: e-learning
Version: 15
Status: Active
Prerequisites:
- Functionally Assembled Terrestrial Ecosystem Simulator (FATES)
- Introduction to Galaxy Analyses
- JupyterLab in Galaxy
- Programming with Python
- The Unix Shell
Learning objectives:
- Motivation for using the Galaxy Climate JupyterLab for CLM-FATES.
- Setting up CLM-FATES case with Galaxy Climate JupyterLab.
- Running CLM-FATES in Galaxy for single-point locations where in-situ measurements are available.
- Analyzing CLM-FATES results.
- Sharing CLM-FATES simulations.
- Composing, executing and publishing the corresponding Jupyter notebooks.
Date modified: 2023-12-05
Date published: 2020-10-25
External resources:
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