IMAGE framework summary/Data uncertainties limitations: Difference between revisions

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|Description=<h2>Data, uncertainty and limitations</h2>
<h2>Data, uncertainty and limitations</h2>


===Data===
===Data===
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Table 2: Overview of key uncertainties .
Table 2: Overview of key uncertainties .
Model component Uncertainty
Model component Uncertainty
Drivers Overall population size, economic growth  
*Drivers: Overall population size, economic growth  
Food production and consumption Yield improvements, meat consumption, total consumption rates
*Food production and consumption: Yield improvements, meat consumption, total consumption rates
Energy system Preferences, energy policies, technology development, resources
*Energy system: Preferences, energy policies, technology development, resources
Emissions Emission factors – in particular those in energy system
*Emissions: Emission factors – in particular those in energy system
Land cover / carbon cycle Growth rates of different ecosystems
*Land cover / carbon cycle: Growth rates of different ecosystems
N-cycle
*N-cycle:
Water cycle
*Water cycle:
Climate system Climate sensitivity, patterns of climate change
*Climate system: Climate sensitivity, patterns of climate change
Biodiversity Impact – biodiversity relationships
*Biodiversity: Impact – biodiversity relationships


Limitations
===Limitations===
The IMAGE model is relatively strong in its representation of the physical world, i.e. both in terms of the earth system as well as the resource  and technology selection in the human system. A high level of integration has been achieved for these systems, with key parameters being exchanged across the different parts of the model (e.g. bio-energy, temeperature feedbacks on crop production and the energy system, consistent treatment of climate policy and a consistent model for land cover and the carbon cycle). However, there are also important limitations to the model:
The IMAGE model is relatively strong in its representation of the physical world, i.e. both in terms of the earth system as well as the resource  and technology selection in the human system. A high level of integration has been achieved for these systems, with key parameters being exchanged across the different parts of the model (e.g. bio-energy, temeperature feedbacks on crop production and the energy system, consistent treatment of climate policy and a consistent model for land cover and the carbon cycle). However, there are also important limitations to the model:
The economy is represented separately in different model components, and in most submodels financial feedbacks are poorly represented. This implies that the model is better adapted for long-term trends than for short-term questions and also that the model is not suitable to study more detailed  economic impacts, such as for instance sector impacts)
*      The economy is represented separately in different model components, and in most submodels financial feedbacks are poorly represented. This implies that the model is better adapted for long-term trends than for short-term questions and also that the model is not suitable to study more detailed  economic impacts, such as for instance sector impacts)
The model runs start  in 1970, which implies that 2010 is model output. Although the model is calibrated against historical data up to 2005, the representation of historical data is obviously not perfect, nor is the extension based on major trends until 2010 . This has implications for short-term applications. By design, the model is rather aggregated to allow for global coverage and a long time horizon, while keeping run times in check. Detailed, differentiated processes at local scale, and also national policies are typically represented as part of global region trends, ignoring country specific measures.
* The model runs start  in 1970, which implies that 2010 is model output. Although the model is calibrated against historical data up to 2005, the representation of historical data is obviously not perfect, nor is the extension based on major trends until 2010 . This has implications for short-term applications. By design, the model is rather aggregated to allow for global coverage and a long time horizon, while keeping run times in check. Detailed, differentiated processes at local scale, and also national policies are typically represented as part of global region trends, ignoring country specific measures.
The physical orientation of the model implies that it is well adapted  to study technical measures to achieve certain policy goals, but less well  to study specific policies. Some can be represented such as  a carbon tax, but others including R&D policies not. Also the model has no representation of governance systems, and these tend to be handled as exogenous (variant) scenario parameters serving as proxies.
* The physical orientation of the model implies that it is well adapted  to study technical measures to achieve certain policy goals, but less well  to study specific policies. Some can be represented such as  a carbon tax, but others including R&D policies not. Also the model has no representation of governance systems, and these tend to be handled as exogenous (variant) scenario parameters serving as proxies.
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Revision as of 12:22, 11 December 2013