Atmospheric composition and climate/Description: Difference between revisions
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A change in atmospheric gas concentrations also changes the amount of radiation absorbed or transmitted by the atmosphere, and thereby causes a change in the earth’s energy balance and temperature. This change in the energy balance is expressed as ‘radiative forcing’ per gas, measured in W/m2. In MAGICC, concentrations of long-lived greenhouse gases and O3 are translated into radiative forcing values using the estimates from the IPCC's AR4 ([[Forster et al., 2007]]). | A change in atmospheric gas concentrations also changes the amount of radiation absorbed or transmitted by the atmosphere, and thereby causes a change in the earth’s energy balance and temperature. This change in the energy balance is expressed as ‘radiative forcing’ per gas, measured in W/m2. In MAGICC, concentrations of long-lived greenhouse gases and O3 are translated into radiative forcing values using the estimates from the IPCC's AR4 ([[Forster et al., 2007]]). | ||
However, there are other processes that also lead to changes in the energy balance of the atmosphere, which are therefore also modelled, and assigned a radiative forcing value. Aerosol precursors, such as SO2, NOx, and organic carbon have a direct, cooling effect by reflecting more radiation back into space (direct aerosol effect). Black carbon, although also an aerosol precursor, has a strong direct warming effect ([[WMO/UNEP, 2013]]), by acting as condensation nuclei for water vapour in the atmosphere, since – in very general terms – more clouds keep more energy within the earth’s atmosphere. | However, there are other processes that also lead to changes in the energy balance of the atmosphere, which are therefore also modelled, and assigned a radiative forcing value. Aerosol precursors, such as SO2, NOx, and organic carbon have a direct, cooling effect by reflecting more radiation back into space (direct aerosol effect). Black carbon, although also an aerosol precursor, has a strong direct warming effect ([[WMO/UNEP, 2013]]), by acting as condensation nuclei for water vapour in the atmosphere, since – in very general terms – more clouds keep more energy within the earth’s atmosphere. | ||
Both direct and the indirect aerosol effects are approximated in MAGICC by scaling the 2005 radiative forcing with the relative increase in future emissions above the 2005 emission level. As MAGICC assumes radiative forcing by albedo and mineral dust to stay constant over the scenario period ([[Meinshausen et al., 2011a]]), this is also assumed in IMAGE. | Both direct and the indirect aerosol effects are approximated in MAGICC by scaling the 2005 radiative forcing with the relative increase in future emissions above the 2005 emission level. As MAGICC assumes radiative forcing by albedo and mineral dust to stay constant over the scenario period ([[Meinshausen et al., 2011a]]), this is also assumed in IMAGE. | ||
The core of MAGICC 6.0, the upwelling–diffusion climate model, calculates global mean temperature change as a result of these radiative forcings ([[Meinshausen et al., 2011a]]; [[Meinshausen et al., 2011b]]). It is a ‘four-box’ model, representing the earth by a northern and southern land component, and a northern and southern ocean component. | The core of MAGICC 6.0, the upwelling–diffusion climate model, calculates global mean temperature change as a result of these radiative forcings ([[Meinshausen et al., 2011a]]; [[Meinshausen et al., 2011b]]). It is a ‘four-box’ model, representing the earth by a northern and southern land component, and a northern and southern ocean component. | ||
The energy fluxes simulated by MAGICC include heat transport from the atmosphere, through the mixing top layer of the ocean, to lower water layers (60 layers), and heat transfer between land and ocean. Due to the slow heat transport to the ocean, it takes a long time until the earth's temperature is in a new equilibrium following a change in radiative forcing. The parameters of the MAGICC model that control heat transport and final global mean temperature change are calibrated to reproduce the results of 19 Global Circulation Models of AR4 ([[Meinshausen et al., 2011b]]). Next to these 19 alternative [[AOGCM]]-specific sets of parameters, also a ‘medium’ parameterisation is available, which results in a behaviour that represents the mean of these 19 model emulations. | The energy fluxes simulated by MAGICC include heat transport from the atmosphere, through the mixing top layer of the ocean, to lower water layers (60 layers), and heat transfer between land and ocean. Due to the slow heat transport to the ocean, it takes a long time until the earth's temperature is in a new equilibrium following a change in radiative forcing. The parameters of the MAGICC model that control heat transport and final global mean temperature change are calibrated to reproduce the results of 19 Global Circulation Models of AR4 ([[Meinshausen et al., 2011b]]). Next to these 19 alternative [[AOGCM]]-specific sets of parameters, also a ‘medium’ parameterisation is available, which results in a behaviour that represents the mean of these 19 model emulations. | ||
The global mean temperature change from MAGICC, and maps of temperature and precipitation change are used in a pattern scaling, to derive spatially explicit temperature and precipitation changes in every time step, which may subsequently be used by various other IMAGE modules (on [[C cycle and natural vegetation dynamics]], [[Crop and grassland model]], [[Hydrological cycle]], [[Nutrients]]). Based on grid-specific temperature and precipitation changes and corresponding changes in global mean temperature (2071–2100 compared to 1961–1990) from AR4’s AOGCM model results (Ref database), the global mean temperature change in each time step is used to calculate grid-specific temperature and precipitation changes via linear interpolation. For future calculations, the results of AR5 should be used to update the MAGICC parameterisation for all available AOGCMs, and to update the gridded patterns of climate change. | The global mean temperature change from MAGICC, and maps of temperature and precipitation change are used in a pattern scaling, to derive spatially explicit temperature and precipitation changes in every time step, which may subsequently be used by various other IMAGE modules (on [[C cycle and natural vegetation dynamics]], [[Crop and grassland model]], [[Hydrological cycle]], [[Nutrients]]). Based on grid-specific temperature and precipitation changes and corresponding changes in global mean temperature (2071–2100 compared to 1961–1990) from AR4’s AOGCM model results (Ref database), the global mean temperature change in each time step is used to calculate grid-specific temperature and precipitation changes via linear interpolation. For future calculations, the results of AR5 should be used to update the MAGICC parameterisation for all available AOGCMs, and to update the gridded patterns of climate change. | ||
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Revision as of 14:00, 10 December 2013
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