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https://github.com/danielhuppmann/engage-pyam-tutorial
Tutorial notebook of the pyam package
https://github.com/danielhuppmann/engage-pyam-tutorial
climate-change climate-policy energy-systems integrated-assessment pyam python scenario-analysis
Last synced: about 2 months ago
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Tutorial notebook of the pyam package
- Host: GitHub
- URL: https://github.com/danielhuppmann/engage-pyam-tutorial
- Owner: danielhuppmann
- License: mit
- Created: 2022-01-31T22:59:18.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2023-07-04T13:50:55.000Z (over 1 year ago)
- Last Synced: 2024-06-11T17:02:21.098Z (8 months ago)
- Topics: climate-change, climate-policy, energy-systems, integrated-assessment, pyam, python, scenario-analysis
- Language: Jupyter Notebook
- Homepage: https://teaching.ece.iiasa.ac.at/tutorials/pyam.html
- Size: 2.59 MB
- Stars: 9
- Watchers: 2
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# ENGAGE Capacity Building Workshop: the pyam package
[](https://github.com/IAMconsortium/pyam)
[](https://github.com/psf/black)
Copyright 2022-2023 Daniel Huppmann; this repository is released under the [MIT License](LICENSE).
## Overview
This repository holds a [Jupyter notebook](tutorial-notebook.ipynb) for a live-demo
of the **pyam** package given as part of the *hands-on tutorial sessions*
of the **NAVIGATE-ENGAGE Summer School 2023 on Integrated-Assessment Modeling**.
This workshop was organized as part of the Horizon 2020 project ENGAGE
([link](https://www.engage-climate.org/navigate-engage-summer-school-2023/)).
The Jupyter notebook is based on the advanced assignment
of the [Modelling Lab](https://github.com/danielhuppmann/climate-risks-academy-2021),
which was part of the *Climate Risks Academy 2021* organized by
the European University Institute (EUI) Florence School of Banking and Finance
in cooperation with Oliver Wyman.
The **slides for the related presentation** are available
at https://doi.org/10.5281/zenodo.8112529 (ZENODO).
## Tutorial data source
The scenario data used in this tutorial notebook is taken from
the **NGFS Scenario Ensemble**, Phase 3, see Richters et al, 2022 ([link](https://www.ngfs.net/sites/default/files/medias/documents/ngfs_climate_scenarios_for_central_banks_and_supervisors_.pdf.pdf)).
The data was downloaded from the following scenario database:
> **Emissions scenario database of the European Scientific Advisory Board on Climate Change, hosted by IIASA**
> Release 2.0
> European Scientific Advisory Board on Climate Change, 2023
> doi: https://doi.org/10.5281/zenodo.7660150
> url: https://data.ece.iiasa.ac.at/eu-climate-advisory-board
## The pyam package
This tutorial uses the Python package **pyam**, an open-source community toolbox for
analysis & visualization of scenario data.
The package was developed to facilitate working with timeseries scenario data
conforming to the format developed by the
[Integrated Assessment Modeling Consortium (IAMC)](https://www.iamconsortium.org).
The package is used in ongoing assessments by the IPCC and in many model comparison
projects at the global and national level, including several Horizon 2020 projects.
[Read the docs](https://pyam-iamc.readthedocs.io) for more information!
## Getting started
To run the notebooks on your machine, please install Python version 3.7 or higher.
To install the required packages and dependencies, download or git-clone this repository
and run the following command in the root folder:
```
pip install -r requirements.txt
```
Then, you can start a Jupyter notebook using
```
jupyter notebook
```
## Funding acknowledgement
This project has received funding from the European Union’s Horizon 2020 research
and innovation programme under grant agreement No. 821471 (ENGAGE).