Model concept, solver and details - IMAGE
|Model Documentation - IMAGE|
|Institution||PBL Netherlands Environmental Assessment Agency (PBL), Utrecht University (UU)|
|Concept||The IMAGE framework can best be described as a geographically explicit assessment, integrated assessment simulation model, focusing a detailed representation of relevant processes with respect to human use of energy, land and water in relation to relevant environmental processes.|
|Solution method||Recursive dynamic solution method|
|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.|
Objective and scope of IMAGE
IMAGE is a comprehensive integrated modelling framework of interacting human and natural systems. Its design relies on intermediate complexity modelling, balancing level of detail to capture key processes and behaviour, and allowing for multiple runs to explore aspects of sensitivity and uncertainty of the complex, interlinked systems.
The objectives of IMAGE are as follows:
- To analyse large-scale and long-term interactions between human development and the natural environment to gain better insight into the processes of global environmental change;
- To identify response strategies to global environmental change based on assessment of options for mitigation and adaption;
- To indicate key interlinkages and associated levels of uncertainty in processes of global environmental change.
IMAGE is often used to explore two types of issues:
- How the future unfolds if no deliberate, drastic changes in prevailing economic, technology and policy developments are assumed, commonly referred to as baseline, business-as-usual, or no-new-policy assessment;
- How policies and measures prevent unwanted impacts on the global environment and human development.
IMAGE has been designed to be comprehensive in terms of human activities, sectors and environmental impacts, and where and how these are connected through common drivers, mutual impacts, and synergies and trade-offs. IMAGE 3.0 is the latest version of the IMAGE framework models, and has the following features:
- Comprehensive and balanced integration of energy and land systems was a pioneering feature of IMAGE. Recently, other IAMs have been developed in similar directions and comprehensive IAMs are becoming more mainstream.
- Coverage of all emissions by sources/sinks including natural sources/sinks makes IMAGE appropriate to provide input to bio-geochemistry models and complex Earth System Models (ESMs).
- In addition to climate change, which is the primary focus of most IAMs, the IMAGE framework covers a broad range of closely interlinked dimensions. These include water availability and water quality, air quality, terrestrial and aquatic biodiversity, resource depletion, with competing claims on land and many ecosystem services.
- Rather than averages over larger areas, spatial modelling of all terrestrial processes by means of unique and identifiable grid cells captures the influence of local conditions and yields valuable results and insights for impact models.
- IMAGE is based on biophysical/technical processes, capturing the inherent constraints and limits posed by these processes and ensuring that physical relationships are not violated.
- Integrated into the IMAGE framework,  is a simple climate model calibrated to more complex climate models. Using downscaling tools, this model uses the spatial patterns of temperature and precipitation changes, which vary between climate models.
- Detailed descriptions of technical energy systems, and integration of land-use related emissions and carbon sinks enable IMAGE to explore very low greenhouse gas emissions scenarios, contributing to the increasingly explored field of very low climate forcing scenarios.
- The integrated nature of IMAGE enables linkages between climate change, other
environmental concerns and human development issues to be explored, thus contributing to informed discussion on a more sustainable future including trade-offs and synergies between stresses and possible solutions.
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).
|Computer model||Subject||Developed by|
|Core computer models|
|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||PIK|
|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|
|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.
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.
|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|
- 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