Atmospheric composition and climate: Difference between revisions

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|KeyReference=Van Vuuren and Stehfest, 2013; Meinshausen et al., 2011a; Meinshausen et al., 2011b; Müller et al., a (unpublished); Van Vuuren et al., 2011;
|KeyReference=Van Vuuren and Stehfest, 2013; Meinshausen et al., 2011a; Meinshausen et al., 2011b; Müller et al., a (unpublished); Van Vuuren et al., 2011;
|Reference=IPCC, 2007a;
|Reference=IPCC, 2007a;
|InputVar=Terrestrial C balance; BC, OC, NOx emissions; SO2 emission; CO, NMVOC emissions; Non CO2 GHG emissions (CH4, N2O, Halocarbon); CO2 emission from energy and industry; Terrestrial CO2 emission - grid; NEP (net ecosystem production) - grid; Nr of wet days - grid; Cloudiness - grid;  
|InputVar=Terrestrial C balance; BC, OC, NOx emissions; SO2 emission; CO, NMVOC emissions; Non CO2 GHG emissions (CH4, N2O, Halocarbon); CO2 emission from energy and industry; Terrestrial CO2 emission - grid; NEP (net ecosystem production) - grid; Nr of wet days - grid; Cloudiness - grid;
|OutputVar=CO2 concentration; Non CO2 GHG concentrations; CO2 concentration; Radiative forcing; Global mean temperature; Temperature - grid; Precipitation - grid; Ocean carbon uptake;
|Parameter=MAGICC parameter settings; Radiative forcing factors; CGM pattern (temperature, precipitation) - grid; Sulphate pattern - grid;
|Description=Climate change is considered to be one of impacts  of human interference on the environment. Emissions from fossil fuels, industry, land use and land-use change have increased greenhouse gas ([[HasAcronym::GHG]]) concentrations and led to almost 1 oC rise in global mean temperature on pre-industrial levels ([[IPCC, 2007a]]). The impacts are already visible and are expected to increase in the coming century. Without further action, mean global temperature could increase by 4 to 6 °C  by the end of this century ([[IPCC, 2007a]]). Climate change impacts manifest themselves in all world regions, and practically affect all aspects of human activity.
 
Modelling of climate change (changes in temperature and precipitation) is central in global integrated assessments for baseline developments in climate change and for climate policy options.  IMAGE uses the simple climate model [[MAGICC model|MAGICC]]  (!!! INVALID CITATION !!!) to simulate the effects of changing greenhouse gas emissions on atmospheric composition, radiative forcing and global mean temperature. MAGICC was used extensively in the Third Fourth, and Fifth IPCC Assessment Reports  ( 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 ([[HasAcronym::AOGCM]]).
 
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, MAGICCC can reproduce time-dependent responses of AOGCMs ([[Meinshausen et al., 2011a]]; [[Meinshausen et al., 2011b]]). This allows IMAGE to reflect the uncertainty in the AOGCM results, and to provide plausible projections of future climate-change feedbacks and impacts.
 
The analysis of climate impacts and feedbacks requires only 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 [[HasAcronym::AR|AR4]] ([[IPCC, 2007a]]) 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. 


|OutputVar=CO2 concentration; Non CO2 GHG concentrations; CO2 concentration; Radiative forcing; Global mean temperature; Temperature - grid; Precipitation - grid; Ocean carbon uptake; 
|Parameter=MAGICC parameter settings; Radiative forcing factors; CGM pattern (temperature, precipitation) - grid; Sulphate pattern - grid;
|Description=Climate change is generally considered among the most serious of human interferences in the environment. Emissions from fossil fuels, industry, land use and land-use change have increased greenhouse gas ([[HasAcronym::GHG]]) concentrations and caused the global mean temperature to be almost 1 oC above pre-industrial levels ([[IPCC, 2007a]]) . The impacts of climate change are already visible today and are expected to become much stronger during this century and beyond, if no action is taken and if global mean temperature could increase by 4 to 6 °C ([[IPCC, 2007a]]). Climate change impacts manifest themselves in all world regions, and practically affect all aspects of human activity.
Therefore, the modelling of climate change (i.e. changes in temperature and precipitation), is central in global integrated assessments to study baseline developments of climate change as well as policy options. In IMAGE, we use the simple climate model [[MAGICC model|MAGICC]] ([[Meinshausen et al., 2011a]]; [[Meinshausen et al., 2011b]]) to simulate the effect of changing greenhouse gas emissions on atmospheric composition, radiative forcing and global mean temperature change. MAGICC was used extensively in the Third and Fourth Assessment Reports of IPCC (Intergovernmental Panel on Climate Change) for assessing a range of greenhouse-gas concentration scenarios. Since the publication of these reports, MAGICC has been updated to be in line with the most recent results from Atmosphere-Ocean General Circulation Models ([[HasAcronym::AOGCM]]).
The uncertainty in climate change simulations remains substantial, as illustrated by differences between the results from various Atmosphere-Ocean General Circulation Models (AOGCMs), in terms of global mean temperature, but even much more so in geographical patterns of surface temperature and precipitation. MAGICC has been designed to reproduce time-dependent responses of AOGCMs by adjusting the values of a limited number of  model parameters ([[Meinshausen et al., 2011a]]; [[Meinshausen et al., 2011b]]). This allows IMAGE to also reflect the uncertainty in the AOGCM results, and to provide plausible projections of future climate-change feedbacks and impacts.
For both impacts and feedbacks, not global mean temperature change, but location-specific temperature and precipitation changes are relevant. Therefore, a pattern scaling technique is applied in IMAGE by combining MAGICC results with maps on climate change from the same AOGCMs as were assessed in [[HasAcronym::AR|AR4]] ([[IPCC, 2007a]]) 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.
|ComponentCode=ACC
|ComponentCode=ACC
|AggregatedComponent=Earth System
|AggregatedComponent=Earth System
|FrameworkElementType=state component
|FrameworkElementType=state component
}}
}}

Revision as of 16:26, 10 February 2014

Link to framework components overview

Parts of Atmospheric composition and climate

  1. Introduction page
  2. Model description
  3. Policy issues
  4. Data, uncertainty and limitations
  5. Overview of references
Component is implemented in:
Components:
Related IMAGE components
Projects/Applications
Models/Databases
Key publications
References
Atmospheric composition and climate model (based on MAGICC 6.0) in IMAGE 3.0
Flowchart Atmospheric composition and climate. See also the Input/Output Table on the introduction page.

Key policy issues

  • What would be the impact of global climate change in this century without additional mitigation policies and measures?
  • To what extent would the various scenarios to significantly reduce net greenhouse gas emissions lead to a reduction in climate change?
  • To what extent does the uncertainty of geographical patterns in temperature and precipitation change influence future climate impacts and response strategies?

Introduction

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