IMAGE framework: Difference between revisions
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Various types of IAMs have been developed, evolving from different classes of models with a specific disciplinary focus and point of entry. These are discussed briefly in order to identify the position of IMAGE in relation to other IAM models. The common feature of all IAM models is that they all describe a combination of the Human and Earth systems to gain better understanding global environmental problems. | Various types of IAMs have been developed, evolving from different classes of models with a specific disciplinary focus and point of entry. These are discussed briefly in order to identify the position of IMAGE in relation to other IAM models. The common feature of all IAM models is that they all describe a combination of the Human and Earth systems to gain better understanding global environmental problems. | ||
The [[ADVANCE project]] offers an overview of a number of IAMs and their model properties. See the [[Reference Card]] page which is derived from the ADVANCE model comparison website. | The [[ADVANCE project]] offers an overview of a number of IAMs and their model properties. See the [[Reference Card| Reference card IMAGE 3.0]] page which is derived from the ADVANCE model comparison website. | ||
====Detail versus simplification==== | ====Detail versus simplification==== | ||
As indicated above, a key trade-off in IAMs is detail versus simplification. Sufficient detail is required to include all relevant processes in both the Human and the Earth system according to state-of-the-art knowledge. Simplicity is needed to ensure sufficient transparency in complex model systems, and to explore uncertainties. For instance, a crop growth model with data input on observed, local climate, soil layers and crop variety parameters may perform well at field scale. However, such a model is less suitable for use in an IAM that requires more generic crop growth representation operating as part of a global scale system. | As indicated above, a key trade-off in IAMs is detail versus simplification. Sufficient detail is required to include all relevant processes in both the Human and the Earth system according to state-of-the-art knowledge. Simplicity is needed to ensure sufficient transparency in complex model systems, and to explore uncertainties. For instance, a crop growth model with data input on observed, local climate, soil layers and crop variety parameters may perform well at field scale. However, such a model is less suitable for use in an IAM that requires more generic crop growth representation operating as part of a global scale system. | ||
Revision as of 11:46, 10 August 2015
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