Model scope and methods - GCAM: Difference between revisions
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The Global Change Analysis Model (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. It is used in a wide range of different applications from the exploration of fundamental questions about the complex dynamics between human and Earth systems to the those associated with response strategies to address important environmental questions. GCAM is a community model stewarded by The Joint Global Change Research Institute (JGCRI). Full documentation for GCAM can be found [http://jgcri.github.io/gcam-doc/index.html here]. | |||
GCAM allows users to explore what-if scenarios, quantifying the implications of possible future conditions. These outputs are not predictions of the future; they are a way of analyzing the potential impacts of different assumptions about future conditions. GCAM reads in external “scenario assumptions” about key drivers (e.g., population, economic activity, technology, and policies) and then assesses the implications of these assumptions on key scientific or decision-relevant outcomes (e.g., commodity prices, energy use, land use, water use, emissions, and concentrations) [http://jgcri.github.io/gcam-doc/overview.html <nowiki>[1]</nowiki>]. | |||
Revision as of 20:31, 18 August 2020
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. |
The Global Change Analysis Model (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. It is used in a wide range of different applications from the exploration of fundamental questions about the complex dynamics between human and Earth systems to the those associated with response strategies to address important environmental questions. GCAM is a community model stewarded by The Joint Global Change Research Institute (JGCRI). Full documentation for GCAM can be found here.
GCAM allows users to explore what-if scenarios, quantifying the implications of possible future conditions. These outputs are not predictions of the future; they are a way of analyzing the potential impacts of different assumptions about future conditions. GCAM reads in external “scenario assumptions” about key drivers (e.g., population, economic activity, technology, and policies) and then assesses the implications of these assumptions on key scientific or decision-relevant outcomes (e.g., commodity prices, energy use, land use, water use, emissions, and concentrations) [1].