gcam-core

GCAM -- The Global Change Analysis Model

https://github.com/jgcri/gcam-core

Science Score: 57.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 2 DOI reference(s) in README
  • Academic publication links
  • Committers with academic emails
    56 of 84 committers (66.7%) from academic institutions
  • Institutional organization owner
    Organization jgcri has institutional domain (www.pnnl.gov)
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (10.3%) to scientific vocabulary

Keywords

climate coupled-human-natural-systems economics energy gcam human-earth-system integrated-assessment land water

Keywords from Contributors

china gcam-china integrated-assessment-model climate-change climate-model hector emissions food-security
Last synced: 6 months ago · JSON representation

Repository

GCAM -- The Global Change Analysis Model

Basic Info
Statistics
  • Stars: 353
  • Watchers: 33
  • Forks: 188
  • Open Issues: 244
  • Releases: 0
Topics
climate coupled-human-natural-systems economics energy gcam human-earth-system integrated-assessment land water
Created about 10 years ago · Last pushed 7 months ago
Metadata Files
Readme Contributing License

README.md

Global Change Analysis Model (GCAM)

The Joint Global Change Research Institute (JGCRI) of the Pacific Northwest National Laboratory (PNNL) is the home and primary development institution for GCAM, a multisector tool for exploring consequences of and responses to global change. Climate change is a global issue that impacts all regions of the world and all sectors of the global economy. Multisector tools such as GCAM capture these interconnected impacts in an economic framework in order to explore interactions between regions and sectors.

GCAM has been developed at PNNL for over 20 years and is now a freely available community model and documented online (See below). The team at JGCRI is comprised of economists, engineers, energy experts, forest ecologists, agricultural scientists, and climate system scientists who develop the model and apply it to a range of science and policy questions and work closely with Earth system and ecosystem modelers to integrate the human decision components of GCAM into their analyses.

Model Overview

GCAM is a dynamic-recursive model with technology-rich representations of the economy, energy sector, land use and water linked to a climate model that can be used to explore climate change mitigation policies including carbon taxes, carbon trading, regulations and accelerated deployment of energy technology. Regional population and labor productivity growth assumptions drive the energy and land-use systems employing numerous technology options to produce, transform, and provide energy services as well as to produce agriculture and forest products, and to determine land use and land cover. Using a run period extending from 1990 2100 at 5 year intervals, GCAM has been used to explore the potential role of emerging energy supply technologies and the greenhouse gas consequences of specific policy measures or energy technology adoption including; CO2 capture and storage, bioenergy, hydrogen systems, nuclear energy, renewable energy technology, and energy use technology in buildings, industry and the transportation sectors. GCAM is an Representative Concentration Pathway (RCP)-class model. This means it can be used to simulate scenarios, policies, and emission targets from various sources including the Intergovernmental Panel on Climate Change (IPCC). Output includes projections of future energy supply and demand and the resulting greenhouse gas emissions, radiative forcing and climate effects of 16 greenhouse gases, aerosols and short-lived species at 0.50.5 degree resolution, contingent on assumptions about future population, economy, technology, and climate mitigation policy.

Community guidelines for peer-reviewed journal articles using GCAM

This section outlines some suggested language which the GCAM user community can employ to describe GCAM in papers in peer-reviewed journal articles using GCAM or versions of GCAM. GCAM is under continuous development. The suggested language for the opening paragraphs of a methodology or introduction section of a paper describing GCAM is as follows:

"The Global Change Analysis Model (GCAM) is a multisector model developed and maintained at the Pacific Northwest National Laboratorys Joint Global Change Research Institute (JGCRI, 2023) <include additional citations to previous GCAM studies as relevant>. GCAM is an open-source community model. In this study, we use GCAM v NN. The documentation of the model is available at the GCAM documentation page (http://jgcri.github.io/gcam-doc) and the description below is a summary. GCAM includes representations of: economy, energy, agriculture, and water supply in 32 geopolitical regions across the globe; their GHG and air pollutant emissions and global GHG concentrations, radiative forcing, and temperature change; and the associated land allocation, water use, and agriculture production across 384 land sub-regions and 235 water basins. <If using GCAM-USA, include without quotes: "This study uses a U.S.-focused version of GCAM called GCAM-USA that includes representation of energy, economy, and water systems for the fifty states and the District of Columbia in addition to 31 regions outside of the United States.>. The version of GCAM used in this study is available along with full source code and instructions for use in a public repository <include citation including link to the GCAM repository with doi used in paper>.

Subsequent paragraphs of the description might expound on particular capabilities, systems, or sectors of focus in the paper. Details in the GCAM documentation page can be used as a reference to develop these paragraphs.

Community users of GCAM might also undertake their own model developments and/or assumptions for papers. It is recommended that these departures from the publicly available version of the model be clearly described. In addition, if these developments are substantial, we suggest making this clear by including an additional phrase (e.g. region name or name of institution) in the name of the model and explicitly calling it out in place of or immediately following the italicized portion in the above paragraphs. For example: "This study uses a modified version of GCAM/GCAM-USA called GCAM-<institution name>/GCAM-USA-<institution name>. GCAM-<institution name>/GCAM-USA-<institution name> incorporates additional details and modified assumptions from GCAM v NN as described subsequently".

Documentation

Selected Publications

Calvin, K., Patel, P., Clarke, L., Asrar, G., Bond-Lamberty, B., Cui, R. Y., Di Vittorio, A., Dorheim, K., Edmonds, J., Hartin, C., Hejazi, M., Horowitz, R., Iyer, G., Kyle, P., Kim, S., Link, R., McJeon, H., Smith, S. J., Snyder, A., Waldhoff, S., and Wise, M.: GCAM v5.1: representing the linkages between energy, water, land, climate, and economic systems, Geosci. Model Dev., 12, 677698, https://doi.org/10.5194/gmd-12-677-2019, 2019.

Edmonds, J., and J. Reilly (1985)Global Energy: Assessing the Future (Oxford University Press, New York) pp.317.

Edmonds, J., M. Wise, H. Pitcher, R. Richels, T. Wigley, and C. MacCracken. (1997) An Integrated Assessment of Climate Change and the Accelerated Introduction of Advanced Energy Technologies, Mitigation and Adaptation Strategies for Global Change, 1, pp. 311-39

Kim, S.H., J. Edmonds, J. Lurz, S. J. Smith, and M. Wise (2006) The ObjECTS Framework for Integrated Assessment: Hybrid Modeling of Transportation Energy Journal (Special Issue #2) pp 51-80.

Full list of GCAM publications

Owner

  • Name: Joint Global Change Research Institute
  • Login: JGCRI
  • Kind: organization
  • Location: College Park, MD, USA

Advancing fundamental understanding of human and Earth systems

GitHub Events

Total
  • Create event: 5
  • Issues event: 94
  • Release event: 5
  • Watch event: 72
  • Issue comment event: 163
  • Push event: 11
  • Pull request event: 4
  • Pull request review event: 3
  • Pull request review comment event: 2
  • Fork event: 28
Last Year
  • Create event: 5
  • Issues event: 94
  • Release event: 5
  • Watch event: 72
  • Issue comment event: 163
  • Push event: 11
  • Pull request event: 4
  • Pull request review event: 3
  • Pull request review comment event: 2
  • Fork event: 28

Committers

Last synced: 6 months ago

All Time
  • Total Commits: 8,008
  • Total Committers: 84
  • Avg Commits per committer: 95.333
  • Development Distribution Score (DDS): 0.828
Past Year
  • Commits: 53
  • Committers: 6
  • Avg Commits per committer: 8.833
  • Development Distribution Score (DDS): 0.302
Top Committers
Name Email Commits
Pralit Patel p****l@p****v 1,381
Ben Bond-Lamberty b****y@p****v 1,365
Josh Lurz j****4@g****m 968
Kyle, G Page p****e@p****v 514
Steven J Smith s****h@p****v 451
kvcalvin k****n@p****v 408
abigailsnyder a****r@p****v 345
kdorheim k****m@p****v 267
russellhz r****z@p****v 224
Matthew Binsted m****d@p****v 202
rynacui y****i@p****v 191
Robert Link r****k@p****v 135
Sonny Kim s****m@p****v 132
Kanishka Narayan k****1@g****m 125
Neal Graham n****m@p****v 96
Leyang Feng l****g@p****v 89
Turner, Sean W s****r@p****v 84
enlochner e****r@p****v 80
stan656 a****i@p****v 71
Vincent Nibali v****i@w****u 62
cwroney c****y@p****v 52
mollycharles m****s@p****v 51
CLynchy c****h@p****v 42
zarrar z****5@g****m 38
Jill Horing j****g@p****v 35
Rachel Hoesly r****y@p****v 34
Kyle d****7@w****v 32
Zhao, Xin x****o@p****v 31
yeyman n****n@p****v 31
yalingliupnnl y****u@p****v 29
and 54 more...

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 464
  • Total pull requests: 22
  • Average time to close issues: 3 months
  • Average time to close pull requests: 3 months
  • Total issue authors: 211
  • Total pull request authors: 11
  • Average comments per issue: 1.94
  • Average comments per pull request: 0.82
  • Merged pull requests: 4
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 86
  • Pull requests: 4
  • Average time to close issues: 11 days
  • Average time to close pull requests: N/A
  • Issue authors: 48
  • Pull request authors: 2
  • Average comments per issue: 0.98
  • Average comments per pull request: 0.0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • robbieorvis (19)
  • Youyi77 (15)
  • Wentemi (13)
  • stm19950929 (11)
  • jiangyongye (10)
  • fkanyako (10)
  • jayfuhrman (8)
  • rjplevin (8)
  • Kofimoley (7)
  • atmos-project (7)
  • msispah (7)
  • chloe-fauvel (6)
  • Lance-bot (6)
  • debibooo (6)
  • mxq517 (6)
Pull Request Authors
  • aldivi (8)
  • mmowers (2)
  • PoonamNK (2)
  • rjplevin (2)
  • bje- (2)
  • ankurmalyan (1)
  • djvdven (1)
  • zcranmer (1)
  • publicmatt (1)
  • jonsampedro (1)
  • kvcalvin (1)
Top Labels
Issue Labels
question (4) bug (4) Documentation (2) dplyr/tidyr (2) help wanted (2) ModelInterface (1) duplicate (1) enhancement (1) gcam-question (1)
Pull Request Labels

Dependencies

input/gcamdata/DESCRIPTION cran
  • R >= 3.1.2 depends
  • assertthat >= 0.2 imports
  • data.table >= 1.10.4 imports
  • dplyr >= 0.8.2 imports
  • magrittr >= 1.5 imports
  • methods * imports
  • readr >= 1.3.1 imports
  • rlang * imports
  • tibble >= 1.1 imports
  • tidyr >= 0.7.1 imports
  • R.utils >= 2.6.0 suggests
  • drake >= 6.2.1 suggests
  • gcamdata.compdata * suggests
  • igraph >= 1.0.1 suggests
  • knitr * suggests
  • mockr >= 0.1 suggests
  • rmarkdown * suggests
  • testthat >= 1.0.2 suggests
  • usethis >= 1.4.0 suggests