Model scope and methods - GCAM: Difference between revisions

From IAMC-Documentation
Jump to navigation Jump to search
mNo edit summary
mNo edit summary
 
(2 intermediate revisions by the same user not shown)
Line 3: Line 3:
|DocumentationCategory=Model scope and methods
|DocumentationCategory=Model scope and methods
}}
}}
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].  
The Global Change Analysis Model (GCAM) is a global model that represents the behavior of, and interactions between five systems: energy, water, agriculture and land use, economy, and 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 those associated with response strategies to address important environmental questions. GCAM is a community model stewarded by The Joint Global Change Research Institute ([http://www.globalchange.umd.edu/ 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>].
GCAM is an integrated, multi-sector model that explores both human and Earth system dynamics. The role of models like GCAM is to bring multiple human and physical Earth systems together in one place to shed light on system interactions and provide scientific insights that would not otherwise be available from the pursuit of traditional disciplinary scientific research alone. GCAM is constructed to explore these interactions in a single computational platform with a sufficiently low computational requirement to allow for broad explorations of scenarios and uncertainties. Components of GCAM are designed to capture the behavior of human and physical systems, but they do not necessarily include the most detailed process-scale representations of its constituent components. On the other hand, model components in principle provide a faithful representation of the best current scientific understanding of underlying behavior. See [http://jgcri.github.io/gcam-doc/overview.html GCAM Model Overview] for an overview of the model and its capabilities.

Latest revision as of 19:14, 1 September 2020

Alert-warning.png Note: The documentation of GCAM is 'under review' and is not yet 'published'!

Model Documentation - GCAM

Corresponding documentation
Previous versions
No previous version available
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: energy, water, agriculture and land use, economy, and 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 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 is an integrated, multi-sector model that explores both human and Earth system dynamics. The role of models like GCAM is to bring multiple human and physical Earth systems together in one place to shed light on system interactions and provide scientific insights that would not otherwise be available from the pursuit of traditional disciplinary scientific research alone. GCAM is constructed to explore these interactions in a single computational platform with a sufficiently low computational requirement to allow for broad explorations of scenarios and uncertainties. Components of GCAM are designed to capture the behavior of human and physical systems, but they do not necessarily include the most detailed process-scale representations of its constituent components. On the other hand, model components in principle provide a faithful representation of the best current scientific understanding of underlying behavior. See GCAM Model Overview for an overview of the model and its capabilities.