Model concept, solver and details - IMAGE

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Model Documentation - IMAGE

Corresponding documentation
Previous versions
Model information
Model link
Institution PBL Netherlands Environmental Assessment Agency (PBL), Netherlands, https://www.pbl.nl/en.
Solution concept Partial equilibrium (price elastic demand)
Solution method Simulation
Anticipation Simulation modelling framework, without foresight. However, a simplified version of the energy/climate part of the model (called FAIR) can be run prior to running the framework to obtain data for climate policy simulations.

IMAGE framework

The IMAGE framework can best be described as an integrated assessment simulation model, that describes the relevant economic and environmental processes with a considerable amount of physical detail. IMAGE has been set-up as an integrated assessment framework in a modular structure, with some components linked directly to the model code of IMAGE, and others connected through soft links (the models run independently with data exchange via data files). This architecture provides more flexibility to develop components separately and to perform sensitivity analyses, recognising that feedback may not always be strong enough to warrant full integration. For example, the various components of the Earth system are fully linked on a daily or annual basis. However, components of the Human system, such as the TIMER energy model and the agro-economic model MAGNET, are linked via a soft link, and can also be run independently.

The IMAGE core model comprises most parts of the Human system and the Earth system, including the energy system, land-use, and the plant growth, carbon and water cycle model LPJmL. The IMAGE framework includes soft-linked models, such as the agro-economic model MAGNET, and PBL policy and impact models, such as FAIR (climate policy), GLOBIO (biodiversity), GLOFRIS (flood risks) and GISMO (human development).

Table 1: Core computer models
Computer model Subject Developed by
Fair model Climate policy and policy response PBL
IMAGE land use model Land use and global change PBL
LPJmL model Carbon, vegetation, agriculture and water LEI
MAGICC model Atmospheric composition and climate MAGICC team
TIMER model Energy supply and demand PBL
Associated computer models
CLUMondo model Land-use allocation
GISMO model Impacts on human development PBL
GLOBIO model Impacts on biodiversity PBL
GLOFRIS model Flood risk assessment PBL, Deltares, UU, IVM
Related computer models
GUAM model Health PBL
Impact model Agricultural economy IFPRI
MAGNET model Agriculture economy LEI

Computer models are classified in: core, associated and related models.

  • Core IMAGE models are used for the integrated assessments projects and developed by the IMAGE team or in close collaboration with partners.
  • Associated models use the results of the core models to compute various impacts. These models are developed in consultation with the IMAGE team
  • Related models are not part of the IMAGE framework, but may be used in the framework, depending on the type of project. They are not developed by the IMAGE team.

Uncertainty

Systematic uncertainty analyses have been performed on the individual IMAGE models. In addition, IMAGE has been assessed in model comparison projects (e.g., Energy Modelling Forum, AMPERE, LIMITS and AgMIP via MAGNET) 1. These studies also contribute to understanding key uncertainties, as the experiments in these projects tend to be set up in the form of sensitivity runs, in which comparison with other models provides useful insights. An overview of key uncertainties in the IMAGE framework is presented in the table below.

Table 2: Overview of key uncertainties in IMAGE 3.0 (from IMAGE 3.0 documentation)
Model component Uncertainty
Drivers Overall population size, economic growth
Agricultural systems Yield improvements, meat consumption, total consumption rates
Energy systems Preferences, energy policies, technology development, resources
Emissions Emission factors, in particular those in energy system
Land cover / carbon cycle Intensification versus expansion, effect of climate change on soil respiration, CO2, fertilization effect
N-cycle Nutrient use efficiencies
Water cycle Groundwater use, patterns of climate change
Climate system Climate sensitivity, patterns of climate change
Biodiversity Biodiversity effect values, effect of infrastructure and fragmentation

References

  1. ^  |  Martin von Lampe, Dirk Willenbockel, Helal Ahammad, Elodie Blanc, Yongxia Cai, Katherine Calvin, Shinichiro Fujimori, Tomoko Hasegawa, Petr Havlik, Edwina Heyhoe, Page Kyle, Hermann Lotze-Campen, Daniel Mason d'Croz, Gerald C. Nelson, Ronald D. Sands, Christoph Schmitz, Andrzej Tabeau, Hugo Valin, Dominique van der Mensbrugghe, Hans van Meijl (2013). Why do global long-term scenarios for agriculture differ? An overview of the AgMIP Global Economic Model Intercomparison. Agricultural Economics, 45 (), 3-20. http://dx.doi.org/10.1111/agec.12086