Model Documentation - GCAM
Note: The documentation of GCAM is 'under review' and is not yet 'published'!| Corresponding documentation | |
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| Model information | |
| Model link | |
| Institution | Pacific Northwest National Laboratory, Joint Global Change Research Institute (PNNL, JGCRI), USA, https://www.pnnl.gov/projects/jgcri. |
| Solution concept | General equilibrium (closed economy)GCAM solves all energy, water, and land markets simultaneously |
| Solution method | Recursive dynamic solution method |
| Anticipation | GCAM is a dynamic recursive model, meaning that decision-makers do not know the future when making a decision today. After it solves each period, the model then uses the resulting state of the world, including the consequences of decisions made in that period - such as resource depletion, capital stock retirements and installations, and changes to the landscape - and then moves to the next time step and performs the same exercise. For long-lived investments, decision-makers may account for future profit streams, but those estimates would be based on current prices. For some parts of the model, economic agents use prior experience to form expectations based on multi-period experiences. |
GCAM is a global model that represents the behavior of, and interactions between five systems: the energy system, water, agriculture and land use, the economy, and the climate. GCAM has been under development for over 30 years. Work began in 1980 with the work first documented in 1982 in working papers (Edmonds and Reilly, 1982a,b,c)[1] [2] [3] and the first peer-reviewed publications in 1983 (Edmonds and Reilly, 1983a,b,c)[4][5][6]. At this point, the model was known as the Edmonds-Reilly (and subsequently the Edmonds-Reilly-Barnes) model. The model was renamed MiniCAM in the mid-1990s, the model code was re-written in object-oriented C++ (Kim et al. 2006)[7] and renamed to GCAM in the mid-2000s. The first coupling to a carbon cycle model was published in Edmonds et al. (1984)[8]. The first use of GCAM (MiniCAM at the time) in conjunction with a Monte Carlo uncertainty analysis was published in Reilly et al. (1987)[9].
Throughout its lifetime, GCAM has evolved in response to the need to address an expanding set of science and assessment questions. The original question that the model was developed to address was the magnitude of mid-21st-century global emissions of fossil fuel CO2. Over time GCAM has expanded its scope to include a wider set of energy producing, transforming, and using technologies, emissions of non-CO2 greenhouse gases, agriculture and land use, water supplies and demands, and physical Earth systems. GCAM has been used to produce scenarios for national and international assessments ranging from the very first IPCC scenarios (Response Strategies Working Group, 1990)[9] through the present Shared Socioeconomic Pathways (Calvin et al., 2017)[10]. GCAM is increasingly being used in multi-model, multi-scale analysis, in which it is either soft- or hard-coupled to other models with different focuses and often greater resolution in key sectors. For example, a range of downscaling tools have been developed for use with GCAM to be able to land and water outputs at a grid resolution. Similarly, it has been coupled to a state of the art Earth system model (Collins, et al., 2015)[11]. Hundreds of papers have been published in peer-reviewed journals using GCAM over its lifetime and the GCAM system continues to be an important international tool for scientific inquiry. GCAM is also a community model being used by researchers across the globe, creating a shared global research enterprise. GCAM can be run on Windows, Linux, Mac, and high-performance computing systems.
The official documentation for GCAM can be found here.
- ↑ Edmonds, J. and J. Reilly. 1982a. “Global energy and CO2 to the year 2050,” IEA/ORAU Working Paper Contribution No. 82-6.
- ↑ Edmonds, J. and J. Reilly. 1982b. “Global energy production and use to the year 2050,” IEA/ORAU Working Paper Contribution No. 82-7.
- ↑ Edmonds, J. and J. Reilly. 1982c. An introduction to the use of the IEA/ORAU, Long-term, global energy model,” IEA/ORAU Working Paper Contribution No. 82-9.
- ↑ Edmonds, J. and J. Reilly. 1983a. “Global Energy and CO2 to the Year 2050,” The Energy Journal, 4(3):21-47.
- ↑ Edmonds, J. and J. Reilly. 1983b. “A Long-Term, Global, Energy-Economic Model of Carbon Dioxide Release From Fossil Fuel Use,” Energy Economics, 5(2):74-88.
- ↑ Edmonds, J. and J. Reilly. 1983c. “Global Energy Production and Use to the Year 2050,” Energy, 8(6):419-32.
- ↑ Kim, S.H., J. Edmonds, J. Lurz, S. J. Smith, and M. Wise (2006) The ObjECTS Framework for Integrated Assessment: Hybrid Modeling of Transportation. The Energy Journal 27(Special Issue 2): pp 63-91.
- ↑ Edmonds, J., J. Reilly, J.R. Trabalka and D.E. Reichle. 1984. An Analysis of Possible Future Atmospheric Retention of Fossil Fuel CO2. TR013, DOE/OR/21400-1. National Technical Information Service, U.S. Department of Commerce, Springfield Virginia 22161.
- ↑ 9.0 9.1 Reilly, J.M., Edmonds, J.A., Gardner, R.H., and Brenkert, A.L. 1987. “Uncertainty Analysis of the IEA/ORAU CO2 Emissions Model,” The Energy Journal, 8(3):1-29. Response Strategies Working Group, Intergovernmental Panel on Climate Change. 1990. Emissions Scenarios.
- ↑ Calvin, K., B. Bond-Lamberty, L. Clarke, J. Edmonds, J. Eom, C. Hartin, S. Kim, P. Kyle, R. Link, R. Moss, H. McJeon, P. Patel, S. Smith, S. Waldhoff and M. Wise (2017). “The SSP4: A world of deepening inequality.” Global Environmental Change 42: 284-296.
- ↑ Collins, William D., Anthony P. Craig, John E. Truesdale, A. V. Di Vittorio, Andrew D. Jones, Benjamin Bond-Lamberty, Katherine V. Calvin, James A. Edmonds, Allison M. Thomson, Benjamine Bond-Lamberty, Pralit Patel, Sonny H. Kim, Peter E. Thornton, Jiafu Mao, Xiaoying Shi, Louise P. Chini, and George C. Hurtt. “The integrated Earth system model version 1: formulation and functionality.” Geoscientific Model Development 8, no. 7 (2015): 2203-2219.