ENGAGE
Source code for figure generation and analysis of the ENGAGE netzero scenario analysis.
https://github.com/iiasa/ENGAGE-netzero-analysis
Category: Climate Change
Sub Category: Integrated Assessment and Climate Policy
Keywords
data-visualization integrated-assessment opensource pyam scenario-analysis
Last synced: about 23 hours ago
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Repository metadata
Source code for figure generation and analysis of the ENGAGE netzero scenario analysis
- Host: GitHub
- URL: https://github.com/iiasa/ENGAGE-netzero-analysis
- Owner: iiasa
- License: mit
- Created: 2021-10-07T07:35:08.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2021-11-29T15:24:14.000Z (over 3 years ago)
- Last Synced: 2025-04-10T04:00:47.097Z (17 days ago)
- Topics: data-visualization, integrated-assessment, opensource, pyam, scenario-analysis
- Language: Jupyter Notebook
- Homepage: https://data.ece.iiasa.ac.at/engage-netzero-analysis/
- Size: 94.7 KB
- Stars: 13
- Watchers: 5
- Forks: 10
- Open Issues: 0
- Releases: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
README.md
ENGAGE - Analysis of net-zero budget scenarios
Copyright (c) 2021 IIASA Energy, Climate, and Environment Program
This repository is released under the MIT License;
see the LICENSE for details.
Overview
This repository contains Jupyter notebooks to generate figures and analysis
for the following manuscript:
Keywan Riahi, Christoph Bertram, Daniel Huppmann, et al.
Cost and attainability of meeting stringent climate targets without overshoot
Nature Climate Change, 2021
doi: 10.1038/s41558-021-01215-2
The scenario data used in this analysis should be cited as:
ENGAGE Global Scenarios (Version 2.0)
doi: 10.5281/zenodo.5553976
The data can be accessed and downloaded via the ENGAGE Scenario Explorer at https://data.ece.iiasa.ac.at/engage.
Please refer to the license
of the scenario ensemble before redistributing this data or adapted material.
The source code of this notebook is available on GitHub
at https://github.com/iiasa/ENGAGE-netzero-analysis.
A rendered version can be seen at https://data.ece.iiasa.ac.at/engage-netzero-analysis.
About the ENGAGE project
ENGAGE is a global consortium, which explores the feasibility of pathways that can meet
the objectives of the Paris Agreement.
Visit http://www.engage-climate.org for more information!
Dependencies
The notebooks and scripts in this repository use pyam,
an open-source Python package for analysis and visualization
of integrated-assessment scenarios.
Read the docs!
Installation
To install the pyam package, simply run the following in a command line:
pip install pyam-iamc
This command also installs all other dependencies used in the notebooks and scripts.
Funding acknowledgement
Owner metadata
- Name: IIASA
- Login: iiasa
- Email: [email protected]
- Kind: organization
- Description: International Institute for Applied Systems Analysis
- Website: https://www.iiasa.ac.at
- Location: Laxenburg, Austria
- Twitter: IIASAVienna
- Company:
- Icon url: https://avatars.githubusercontent.com/u/15230149?v=4
- Repositories: 128
- Last ynced at: 2024-04-16T01:17:07.573Z
- Profile URL: https://github.com/iiasa
GitHub Events
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- Watch event: 1
Last Year
- Watch event: 1
Committers metadata
Last synced: 6 days ago
Total Commits: 11
Total Committers: 1
Avg Commits per committer: 11.0
Development Distribution Score (DDS): 0.0
Commits in past year: 0
Committers in past year: 0
Avg Commits per committer in past year: 0.0
Development Distribution Score (DDS) in past year: 0.0
| Name | Commits | |
|---|---|---|
| Daniel Huppmann | dh@d****t | 11 |
Committer domains:
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Last synced: 2 days ago
Total issues: 0
Total pull requests: 0
Average time to close issues: N/A
Average time to close pull requests: N/A
Total issue authors: 0
Total pull request authors: 0
Average comments per issue: 0
Average comments per pull request: 0
Merged pull request: 0
Bot issues: 0
Bot pull requests: 0
Past year issues: 0
Past year pull requests: 0
Past year average time to close issues: N/A
Past year average time to close pull requests: N/A
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Past year pull request authors: 0
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Past year merged pull request: 0
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Dependencies
- pyam-iamc >=1.2
Score: 2.5649493574615367