IMAGE framework summary/Data uncertainties limitations: Difference between revisions

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{{FrameworkSummaryPartTemplate
{{FrameworkSummaryPartTemplate
|Status=On hold
|PageLabel=Data, uncertainty and limitations
|PageLabel=Data, uncertainty and limitations
|Sequence=4
|Sequence=9
|Description=<h2>Data, uncertainty and limitations</h2>
|Reference=IEA, 2012; USGS, 2000; Mulders et al., 2006; Hoogwijk, 2004; FAO, 2013a; JRC/PBL, 2012; IPCC-DDC, 2007; Lucas et al., 2007;
}}
<div class="page_standard">
<h2>Data, uncertainty and limitations</h2>
===Data===
Many IMAGE components rely on a number of key data sources. The main data sources are listed below and described in the pages for the respective IMAGE components.


===Data===
====Main data sources for the IMAGE model====
Obviously, the many  components of IMAGE rely on a range of different data sources.  Here, a selection of the most important data sources per category are:
Categories and main data sources
*Energy: [[International Energy Agency]] [[Hoogwijk et al.]], [[Rogner]]
* Energy (see  (see Component [[Drivers]]):
*Land use and agricultural production/consumption: [[FAOSTAT database|FAO]]
** International Energy Agency ([[IEA, 2012]]);
*Emissions: [[EDGAR model|EDGAR]]
** fossil fuel resources ([[USGS, 2000]]; [[Mulders et al., 2006]]);
*Climate data: [[DDC]]? [[ISIMIP]]?
** renewable energy resources ([[Hoogwijk, 2004]]);
** various sources on technology assumption.
* Land use and agricultural production/consumption:
** Data on national crop and livestock production, agricultural yields, and land resources from [[FAO, 2013a|FAO]]
* Emissions:
** [[EDGAR database|EDGAR]] database ([[JRC/PBL, 2012]])
*Climate data (Historic climate data):  
** [[CRU database|CRU]] global climate dataset;
** [[AR4 (IPCC) database|AR4]] data repository ([[IPCC-DDC, 2007]])
* Costs data climate policy (other than energy)
** [[Lucas et al., 2007]]


===Uncertainty analysis===
===Uncertainties===
Systematic uncertainty analyses have been performed at the level of individual submodels of IMAGE. In addition, the model has participated in many model comparison projects ([[EMF]], [[AMPERE model|AMPERE]]). These also contribute to understanding and mapping uncertainty, as these project tend to be set up in the form of sensitivity experiments while comparison with other models provides a useful reference. Based on the results of the individual experiments the following key uncertainties can be identified.  
Systematic uncertainty analyses have been performed on the individual IMAGE models. In addition, IMAGE has been assessed in model comparison projects (e.g., [[AgMIP and ISI-MIP project|AGMIP]] via [[MAGNET model|MAGNET]] ([[Von Lampe et al., 2014]]). 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 below.  


Overview of key uncertainties .
====Overview of key uncertainties in the IMAGE framework====
Model component Uncertainty
Model components and uncertainty
*Drivers: Overall population size, economic growth  
*Drivers:
*Food production and consumption: Yield improvements, meat consumption, total consumption rates
** Overall population size, economic growth;
*Energy system: Preferences, energy policies, technology development, resources
*Agricultural systems:
*Emissions: Emission factors – in particular those in energy system
**Yield improvements, meat consumption, total consumption rates;
*Land cover / carbon cycle: Growth rates of different ecosystems
*Energy systems:
*N-cycle:
** Preferences, energy policies, technology development, resources;
*Water cycle:
*Emissions:
*Climate system: Climate sensitivity, patterns of climate change
**Emission factors, in particular those in energy system;
*Biodiversity: Impact – biodiversity relationships
*Land cover / carbon cycle:
** Intensification versus expansion, effect of climate change on soil respiration, CO<sub>2</sub> 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,


===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 the representation of the physical world in the Earth system, and the resource and technology selection in the Human system. A high level of integration has been achieved of these systems, with key parameters exchanged in different parts of the model (e.g. bioenergy, temperature feedbacks on crop production and the energy system, consistent treatment of climate policy and a consistent model for land cover and the carbon and water cycle).  
*     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.
However, there are also several limitations to the model:
* 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 economy is represented separately in different model components, notably in the agriculture and energy models with monetary feedback not well represented in the energy model. This implies that the model is better adapted for long-term trends than for short-term issues, and is not suitable to assess detailed economic impacts, such as sector level impacts.
}}
* A model run starts in 1970, which implies that 2010 is model output. The model is calibrated against historical data up to 2005 and to 2010, depending on the module, which has implications for applications that use IMAGE output for the 2010-2020 period (for instance, evaluation of 2020 policies by [[FAIR model|FAIR]]).  
* By design, the model is aggregated to allow for global coverage and a long time horizon, while keeping run times in check. Detailed, differentiated processes at local scale and national policies are represented as part of global region trends, without taking into account country-specific measures and processes.
* The physical orientation implies that the model is well adapted to study technical measures to achieve policy goals, but less so to study specific policies. Some policies, such as a carbon tax, can be represented but others, such as {{abbrTemplate|R&D}} policies, cannot. The model has no representation of governance systems, which tend to be handled as exogenous (variant) scenario parameters serving as proxies.
</div>

Latest revision as of 09:25, 11 March 2020

Parts of IMAGE framework summary

  1. Introduction page
  2. Introduction model description
  3. Drivers
  4. The Human system
  5. Interaction Human - Earth system
  6. Earth system
  7. Impacts
  8. Policy issues
  9. Data, uncertainty and limitations
  10. Overview of references
Projects/Applications
Relevant overviews
Key publications
References


Data, uncertainty and limitations

Data

Many IMAGE components rely on a number of key data sources. The main data sources are listed below and described in the pages for the respective IMAGE components.

Main data sources for the IMAGE model

Categories and main data sources

Uncertainties

Systematic uncertainty analyses have been performed on the individual IMAGE models. In addition, IMAGE has been assessed in model comparison projects (e.g., AGMIP via MAGNET (Von Lampe et al., 2014). 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 below.

Overview of key uncertainties in the IMAGE framework

Model components and 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,

Limitations

The IMAGE model is relatively strong in the representation of the physical world in the Earth system, and the resource and technology selection in the Human system. A high level of integration has been achieved of these systems, with key parameters exchanged in different parts of the model (e.g. bioenergy, temperature feedbacks on crop production and the energy system, consistent treatment of climate policy and a consistent model for land cover and the carbon and water cycle).

However, there are also several limitations to the model:

  • The economy is represented separately in different model components, notably in the agriculture and energy models with monetary feedback not well represented in the energy model. This implies that the model is better adapted for long-term trends than for short-term issues, and is not suitable to assess detailed economic impacts, such as sector level impacts.
  • A model run starts in 1970, which implies that 2010 is model output. The model is calibrated against historical data up to 2005 and to 2010, depending on the module, which has implications for applications that use IMAGE output for the 2010-2020 period (for instance, evaluation of 2020 policies by FAIR).
  • By design, the model is aggregated to allow for global coverage and a long time horizon, while keeping run times in check. Detailed, differentiated processes at local scale and national policies are represented as part of global region trends, without taking into account country-specific measures and processes.
  • The physical orientation implies that the model is well adapted to study technical measures to achieve policy goals, but less so to study specific policies. Some policies, such as a carbon tax, can be represented but others, such as R&D policies, cannot. The model has no representation of governance systems, which tend to be handled as exogenous (variant) scenario parameters serving as proxies.
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