This chapter describes the background and modeling approaches used in simple climate models (SCMs) (Harvey et al. 1997). In general, SCMs are the simplified models used by the Intergovernmental Panel on Climate Change (IPCC) to provide projections of the atmospheric concentrations of greenhouse gases, global mean temperature and sea-level change response using as input emissions scenarios describing the future developments in the emissions of greenhouse gases. SCMs are computationally more efficient than more complex, computationally expensive three-dimensional models such as atmosphere-ocean general circulation models (AOGCMs). SCMs are therefore particularly suitable for multiple scenario studies, uncertainty assessments and analysis of feedbacks. The SCM approach is illustrated by applying one such model, meta-IMAGE (den Elzen 1998), to uncertainty analysis.
The SCM meta-IMAGE is a simplified version of the more complex climate assessment model IMAGE 2. IMAGE 2 aims at a more thorough description of the complex, long-term dynamics of the biosphere-climate system at a geographically explicit level (0.5° X 0.5° latitude-longitude grid) (Alcamo et al. 1996, 1998). Meta-IMAGE is a more flexible, transparent and interactive simulation tool that adequately reproduces the IMAGE-2.1 projections of global atmospheric concentrations of greenhouse gases, temperature increase and sea-level rise for the various IMAGE 2.1 emissions scenarios (see Figure 45.1). Meta-IMAGE consists of an integration of a global carbon cycle model (den Elzen et al. 1997), an atmospheric chemistry model and a climate model (upwelling-diffusion energy balance box model of Wigley and Schlesinger 1985 and Wigley and Raper 1992). The climate model also includes global temperature impulse response functions (IRFs; see, for example, Hasselmann et al. 1993) based on simulation experiments with various AOGCMs (den Elzen and Schaeffer 2001). This core model has lately been supplemented by a climate 'attribution' module, which calculates the regional contributions to various categories of emissions, concentrations of greenhouse gases and temperature and sea-level rise, especially developed for the evaluation of the Brazilian Proposal (UNFCCC 1997). Meta-IMAGE itself forms an integral part of the overall FAIR model (Framework to Assess International Regimes for burden sharing), which was developed to explore options for international burden sharing (den Elzen et al. 1999).
In the following section we describe a step-by-step approach along the cause and effect chain of climate change: from emissions to concentrations, from concentrations to radiative forcing and, finally, from radiative forcing to global mean surface air temperature
• Global carbon cycle model:
- terrestrial carbon cycle of Goudriaan & Ketner (IMAGE 2), with 8 land-use types (not geographically explicit)
- ocean carbon cycle: convolution integral of Maier-Reimer & Hasselman
- Other C-cycle models (Bern, Magicc) (optional)
• Atmospheric chemistry model:
- IMAGE 2: chemistry model
• Global climate model:
- Upwelling-diffusion energy balance model
- Global temperature increase response functions (for about 10 AOGCMs: CSIRO, ECHAM, Hadley)
- IMAGE 2: Oerlemans
Figure 45.1 The climate assessment model meta-IMAGE2.1 as used for the model analysis increase. Various modeling approaches being used in SCMs, and in particular metaIMAGE, are discussed. In the subsequent uncertainty analysis, we present an example of such a model analysis with meta-IMAGE of the impact of various carbon balancing mechanisms on the future projections of the atmospheric CO2 concentration and the global mean temperature increase.
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