GCAM

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

Category: Climate Change
Sub Category: Integrated Assessment and Climate Policy

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-model climate-change hector climate-science climate-variability downscaling emissions

Last synced: about 8 hours ago
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GCAM -- The Global Change Analysis Model

README.md

Global Change Analysis Model (GCAM)

The Joint Global Change Research Institute (JGCRI) is the home and
primary development institution for GCAM, an integrated assessment
tool for exploring consequences 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. Thus, any responses
to the threat of climate change, such as policies or international
agreements to limit greenhouse gas emissions, can have wide ranging
consequences throughout the energy system as well as on land use and
land cover. Integrated assessment models endeavor to represent all
world regions and all sectors of the economy in an economic framework
in order to explore interactions between sectors and understand the
potential ramifications of climate mitigation actions.

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 0.5×0.5 degree resolution, contingent on
assumptions about future population, economy, technology, and climate
mitigation policy.

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, 677–698, 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


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GitHub Events

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Last Year

Committers metadata

Last synced: 7 days ago

Total Commits: 8,007
Total Committers: 84
Avg Commits per committer: 95.321
Development Distribution Score (DDS): 0.828

Commits in past year: 66
Committers in past year: 8
Avg Commits per committer in past year: 8.25
Development Distribution Score (DDS) in past year: 0.424

Name Email Commits
Pralit Patel p****l@p****v 1380
Ben Bond-Lamberty b****y@p****v 1365
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...

Committer domains:


Issue and Pull Request metadata

Last synced: 1 day ago

Total issues: 453
Total pull requests: 17
Average time to close issues: 3 months
Average time to close pull requests: about 1 month
Total issue authors: 203
Total pull request authors: 11
Average comments per issue: 2.38
Average comments per pull request: 0.88
Merged pull request: 3
Bot issues: 0
Bot pull requests: 0

Past year issues: 100
Past year pull requests: 3
Past year average time to close issues: 22 days
Past year average time to close pull requests: 7 months
Past year issue authors: 56
Past year pull request authors: 2
Past year average comments per issue: 1.91
Past year average comments per pull request: 0.67
Past year merged pull request: 0
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/jgcri/gcam-core

Top Issue Authors

  • robbieorvis (19)
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  • jayfuhrman (8)
  • rjplevin (8)
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  • atmos-project (7)
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Top Pull Request Authors

  • aldivi (4)
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  • ankurmalyan (1)
  • kvcalvin (1)
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Top Issue Labels

  • question (4)
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  • gcam-question (1)

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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

Score: 10.729766045699256