DICE2016R3_PCF ...
# DICE2016R3_PCF This is a revised DICE model including a simple permafrost carbon module. To prepare the Python environment, you can use the following lines: conda create -n test0 python=3.8 conda activate test0 conda install numpy pyomo -c conda-forge conda install ipopt_bin -c cachemeorg Usage: S...
Main Authors: | , |
---|---|
Format: | Article in Journal/Newspaper |
Language: | unknown |
Published: |
Zenodo
2024
|
Subjects: | |
Online Access: | https://dx.doi.org/10.5281/zenodo.10699551 https://zenodo.org/doi/10.5281/zenodo.10699551 |
id |
ftdatacite:10.5281/zenodo.10699551 |
---|---|
record_format |
openpolar |
spelling |
ftdatacite:10.5281/zenodo.10699551 2024-03-31T07:54:56+00:00 DICE2016R3_PCF ... Wang, Kang Zhu, Yang 2024 https://dx.doi.org/10.5281/zenodo.10699551 https://zenodo.org/doi/10.5281/zenodo.10699551 unknown Zenodo https://dx.doi.org/10.5281/zenodo.10699552 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 article Model CreativeWork 2024 ftdatacite https://doi.org/10.5281/zenodo.1069955110.5281/zenodo.10699552 2024-03-04T14:06:53Z # DICE2016R3_PCF This is a revised DICE model including a simple permafrost carbon module. To prepare the Python environment, you can use the following lines: conda create -n test0 python=3.8 conda activate test0 conda install numpy pyomo -c conda-forge conda install ipopt_bin -c cachemeorg Usage: Start the project by running: DICE2016R_Original.ipynb Please cite our manuscript if the code is used: Zhu, Yang and Wang, Kang and Jiao, Wenxian and Xu, Jinlong. 2024. Revisiting permafrost carbon feedback and economic impacts, Environmental Research Letters, ad2b2b, doi: 10.1088/1748-9326/ad2b2b. ... Article in Journal/Newspaper permafrost DataCite Metadata Store (German National Library of Science and Technology) |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
unknown |
description |
# DICE2016R3_PCF This is a revised DICE model including a simple permafrost carbon module. To prepare the Python environment, you can use the following lines: conda create -n test0 python=3.8 conda activate test0 conda install numpy pyomo -c conda-forge conda install ipopt_bin -c cachemeorg Usage: Start the project by running: DICE2016R_Original.ipynb Please cite our manuscript if the code is used: Zhu, Yang and Wang, Kang and Jiao, Wenxian and Xu, Jinlong. 2024. Revisiting permafrost carbon feedback and economic impacts, Environmental Research Letters, ad2b2b, doi: 10.1088/1748-9326/ad2b2b. ... |
format |
Article in Journal/Newspaper |
author |
Wang, Kang Zhu, Yang |
spellingShingle |
Wang, Kang Zhu, Yang DICE2016R3_PCF ... |
author_facet |
Wang, Kang Zhu, Yang |
author_sort |
Wang, Kang |
title |
DICE2016R3_PCF ... |
title_short |
DICE2016R3_PCF ... |
title_full |
DICE2016R3_PCF ... |
title_fullStr |
DICE2016R3_PCF ... |
title_full_unstemmed |
DICE2016R3_PCF ... |
title_sort |
dice2016r3_pcf ... |
publisher |
Zenodo |
publishDate |
2024 |
url |
https://dx.doi.org/10.5281/zenodo.10699551 https://zenodo.org/doi/10.5281/zenodo.10699551 |
genre |
permafrost |
genre_facet |
permafrost |
op_relation |
https://dx.doi.org/10.5281/zenodo.10699552 |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_doi |
https://doi.org/10.5281/zenodo.1069955110.5281/zenodo.10699552 |
_version_ |
1795036243957907456 |