MiniCAM
The MiniCAM is a long-term, partial-equilibrium model of the energy, agriculture, and climate system, a reduced form of the GCAM. It contains an emissions model that considers both energy and land use emissions and integrally runs the MAGICC climate model as a part of every run, so that climate implications of scenarios and management strategies are readily available. It considers the full range of greenhouse gases and the major new alternative technologies that are pertinent to questions about the future structure of energy supply. The MiniCAM is used for modeling over long time scales where the characteristics of existing capital stocks are not the dominant factor in determining the dynamics of the energy system.
The MiniCAM modeling system is designed to provide a simple description of a wide range of relevant processes. It operates as the testing ground for new GCAM elements and as a tool for exploring interactions between major components of the climate change issue. The suite of models that make up the MiniCAM system is shown in Table 1. MiniCAM was built to run quickly and to be useful as an exploratory research tool. The model has been used to focus on long-term processes and energy-economy-environment dynamics.
The MiniCAM has been expanded to include greater regional detail-there are now 14 MiniCAM regions: the United States, US, Canada, W. Europe, Australia & New Zealand, Japan, Eastern Europe, The Former Soviet Union, China, Mid-East, Africa, Latin America, Korea, Southeast Asia, and India. In addition, three others are under development: Mexico, Argentina, and Brazil.
The technology suite has been expanded to include a wide array of new technologies. The original set of technologies included oil, gas, coal, commercial biomass, nuclear, solar, and hydropower production with transformations to refined hydrocarbon products and electricity, and transformations of solids to liquids and gases. These technologies have been augmented by a broad suite of technologies including traditional biomass fuels, wind, gas to liquids, hydrogen production from hydrocarbons and electricity, fusion power, space solar power, and a transportation sector that is disaggregated by freight and passenger and within each of these categories by mode and technology. Land-use emissions are derived from an agriculture-land use module that models the competition for land resources and resulting releases of non-CO2 greenhouse gases and aerosols as well as changes in the stock of carbon in terrestrial reservoirs. Considerable work has gone into developing direct links between carbon and other greenhouse-related emissions and agricultural and land-use processes.
| Table 1: MiniCAM Modules | ||||
|---|---|---|---|---|
| Model | Institutional Affiliation | Description | Inputs & Outputs | References |
| ERB | PNNL | The Edmonds-Reilly-Barnes (ERB) model is a market equilibrium model of the energy and economic systems. | Inputs: labor productivity growth; population, fossil and non-fossil fuel resources, energy technologies (69) and productivity growth rates; Outputs: Energy supplies and demands by fuel (9 primary, 5 final) and region (14), greenhouse gas emissions (CO2, CH4,N2O,SO2), and economic activity. Temporal Resolution: 15-year time step. |
Edmonds and Reilly (1985); Edmonds, Reilly, Gardner and Brenkert (1986); Edmonds, Wise, Pitcher, Wigley and MacCracken (1997); |
| AgLU | PNNL | The Agriculture-Land-use Model (AgLU) is a market equilibrium model of the land use. | Inputs: Income, population, regional climate, initial land-use allocation, productivity growth rates, and biomass energy price. Outputs: Agriculture and forestry production; greenhouse emissions; land-use and land-use emissions, agricultural prices and land rental rates. Temporal Resolution: 15-year time step. |
Edmonds, Wise, Sands, Brown, and Kheshgi (1996), Sands and Leimbach (2002). |
| MAGICC | NCAR | MAGICC is an integrated model of the carbon cycle, atmospheric chemistry, radiative forcing, sea level, and global mean climate change. | Inputs: Emissions of greenhouse gases; historic atmospheric composition, climate feedback parameters, ocean inertia; Outputs: Concentration of greenhouse gases; radiative forcing; global mean temperature; sea level. Temporal Resolution: 1-year time step. |
Hulme and Raper (1993); Wigley (1994a,b); Wigley and Raper (1987, 1992, 1993, 2001). |
| SCENGEN | NCAR | SCENGEN models the regional pattern of climate change. | Inputs: Global mean temperature; sulfur-dioxide emissions; Outputs: Geographic patterns of temperature and precipitation change. Temporal Resolution: NA (steady-state) |
Hulme, Jiang, and Wigley (1995) |
| Global Runoff | U. CO | Global hydrologic model. | Inputs: Monthly precipitation and average temperature Soil type, and Holdridge biome type Outputs: Monthly runoff in either mm or cubic kilometers for each 0.5o x 0.5o grid cell, aggregated either to river basin (about 180) or MiniCAM region. Temporal Resolution: NA (steady-state) |
Bandy (1998) |