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360 | IAASTD Global Report
Table A.5.3 Overview of major uncertainties in IMAGE 2.4
Model component |
Uncertainty |
Model structure |
• TIMER Energy model: Integration in larger economy and dynamic formulation in energy model (learning by doing) |
Parameters |
• Energy: Resource assumption and learning parameters |
Driving force |
• Income growth (GDP) |
Initial condition |
• Emissions in base year (2000) |
Model operation |
• Downscaling method in climate change model (Eickhout et al., 2004) |
The carbon cycle model has also recently been used for a sensitivity analysis to assess uncertainties in carbon cycle modeling in general (Leemans et al., 2002). Finally, a main uncertainty in IMAGE's climate model has to do with (1) "climate sensitivity," i.e., the response of global temperature computed by the model to changes in atmospheric greenhouse gas concentrations, and (2) regional patterns of changed temperature and precipitation. IMAGE 2.2 has actually been set up in such a way that these variables can be easily manipulated on the basis of more scientifically-detailed models. To summarize, most of IMAGE would need to go into the category of established but incomplete knowledge (Table A.5.4). |
|
A.5.3 The Global Trade and Environment Model (GTEM) A.5.3.1Introduction |
Table A.5.4 Level of confidence in different types of scenario calculations from IMAGE
Level of Agreement/ Assessment |
High Low |
Established but incomplete • Climate impacts on agriculture and biomes |
Well established • Energy modeling and scenarios |
|
Low |
High |
|
Amount of evidence (theory, observations, model outputs) |
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