Climate - IMAGE

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Model Documentation - IMAGE

Corresponding documentation
Previous versions
Model information
Model link
Institution PBL Netherlands Environmental Assessment Agency (PBL), Netherlands,
Solution concept Partial equilibrium (price elastic demand)
Solution method Simulation
Anticipation Simulation modelling framework, without foresight. However, a simplified version of the energy/climate part of the model (called FAIR) can be run prior to running the framework to obtain data for climate policy simulations.

Climate model MAGICC

IMAGE uses the simple climate model MAGICC 6.0 IMG_Meinshausen_2011aIMG_Meinshausen_2011b, which was developed by developed by the MAGICC 6 group (link) to simulate the effects of changing greenhouse gas emissions on atmospheric composition, radiative forcing and global mean temperature. MAGICC calculates atmospheric CO2 concentration based on CO2 emission data for energy, industry and land-use change; terrestrial carbon balance; and carbon uptake by the oceans (calculated in MAGICC on the basis of the Bern Ocean Carbon model).

Concentrations of other long-lived greenhouse gases (CH4, N2O, and halocarbons), and tropospheric ozone (O3) precursors (CO, NMVOC) are calculated by MAGICC in a simple atmospheric chemistry module. Halocarbons and N2O concentrations mostly show a simple mass-concentration conversion and half-life behaviour. CH4 and ozone dynamics are more complex, with CH4 lifetime depending on the OH concentration level, and O3 and OH concentration levels depending on CH4 concentrations, and NOX, CO and NMVOC emissions IMG_Meinshausen_2011b.

MAGICC was used extensively in the Third, Fourth, and Fifth assessment reports of IPCC (Intergovernmental Panel on Climate Change) in assessing a range of greenhouse gas concentration scenarios. Since publication of these reports, MAGICC has been updated in line with results from Atmosphere-Ocean General Circulation Models (AOGCMs).

There is still considerable uncertainty in climate change simulations, as illustrated by differences in results from various AOGCMs, in terms of mean global temperature, and even more so in geographical patterns of surface temperature and precipitation. By adjusting the values of a few of the model parameters, MAGICC 6.0 can reproduce timedependent responses of AOGCMs IMG_Meinshausen_2011aIMG_Meinshausen_2011b. This allows IMAGE to reflect the uncertainty in AOGCM results, and to provide plausible projections of future climate-change feedbacks and impacts.

The analysis of climate impacts and feedbacks requires location-specific temperature and precipitation changes. Thus, a pattern scaling technique is applied in IMAGE by combining MAGICC results with maps on climate change from the same AOGCMs assessed in AR4 IMG_IPCC_2007 and used for calibrating MAGICC. The consistent combination of AOGCM-specific parameter settings for MAGICC and matching geographical patterns of climate change make the dynamic results from IMAGE physically more consistent, and extend the range of uncertainties that can be covered to include future climate change.