Modelling of climate indicators - IMAGE

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Model Documentation - IMAGE

Corresponding documentation
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Model information
Model link
Institution Utrecht University (UU), Netherlands,, 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.

Change in atmospheric gas concentrations also changes the amount of radiation absorbed or transmitted by the atmosphere, and thus changes the earth's energy balance and temperature. The energy balance change is expressed as radiative forcing per gas, measured in W/m2. In MAGICC, concentrations of long-lived greenhouse gases are translated into radiative forcing values using radiative efficiency estimates from the IPCC 1, and radiative forcing of tropospheric ozone is calculated based on ozone sensitivity factors from MAGICC 6.0 23.

However, other processes also lead to changes in the atmospheric energy balance, which are also modelled and assigned a radiative forcing value. Aerosols, such as SO2, NOX, and organic carbon, have a direct cooling effect by reflecting more radiation back into space (direct aerosol effect). They also interact with clouds and precipitation in many ways (indirect aerosol effect); this cloud feedback is the largest source of uncertainty in estimating climate sensitivity 4. Although also an aerosol, black carbon has a strong direct warming effect 5.

Direct and indirect aerosol effects are approximated in MAGICC by scaling the radiative forcing in a reference year (mostly 2005) with the relative increase in future emissions with respect to emissions in the reference year. As MAGICC assumes radiative forcing by albedo and mineral dust to stay constant over the scenario period 2, this is also assumed in IMAGE.


  1. ^  | | |  Myhre G, D. Shindell, F.-M. Breon, W. Collins, J. Fuglestvedt, J. Huang, D. Koch, J.-F. Lamarque, D. Lee, B. Mendoza, T. Nakajima, A. Robock, G. Stephens, T. Takemura and H. Zhang (2013). Anthropogenic and Natural Radiative Forcing. In  (Ed.), Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge (UK) / New York.
  2. a b  | | |  Malte Meinshausen, SCB Raper, TML Wigley (2011). Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 - Part 1: Model description and calibration. Atmospheric Chemistry and Physics, 11 (4), 1417-1456.
  3. ^  | | |  Wigley TML Meinshausen M, Raper SCB (2011). Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 - Part 2: Applications. Atmospheric Chemistry and Physics. Atmospheric Chemistry and Physics, 11 (4), 1457-1471.
  4. ^  | | |  K L Denman, G Brasseur, A Chidthaisong, P Ciais, P M Cox, R E Dickinson, D Hauglustaine, C Heinze, E Holland, D Jacob, U Lohmann, S Ramachandran, P L da Silva Dias, S C Wofsy, X Zhang (2007). Couplings {Between} {Changes} in the {Climate} {System} and {Biogeochemistry}.. In  (Eds.), Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, United Kingdom and New York, NY, USA.: Cambridge University Press.
  5. ^  | | |  WMO/UNEP (2011). Integrated assessment of black carbon and tropospheric ozone. Nairobi, Kenya: World Metrological Organisation, United Nations Environmental Programme.