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Explore the relevance of climate model simulations in informing policy decisions using the example of applying the MAGICC model to greenhouse gas mitigation. This article discusses the needs and understanding of policy makers, uncertainty analysis essentials, and remaining challenges.
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Understanding the relevance of climate model simulations to informing policy: An example of the application of MAGICC to greenhouse gas mitigation policy F. Niehörster, N. Ranger, L. A. Smith
Outline • Talking to Policy Makers: What do they ask for? What do they understand? • Essentials of uncertainty analysis • Remaining challenges
The Example: A Policy Brief What do they ask for? In preparation for the COP15 in Copenhagen it was asked how much global emissions of greenhouse gases will have to fall from present levels to create a reasonable chance (i.e. a 50 per cent probability) of avoiding a rise in global average temperature of more than 2°C above its pre-industrial levels. Policy Brief 2 December 2009 Available on: www.lse.ac.uk/grantham
What do they understand? Example from the executive summary: • “Given the uncertainties in both the science and the economics, it is essential that any policy framework for climate change mitigation incorporates, from the outset, mechanisms to update the long-term goal, in a transparent fashion, in response to new developments in the science or economics, while holding policy-makers accountable for their actions.” • ...
Presenting Uncertainty Review of uncertainty of IPCC and Meinshausen et al (2006) for reaching certain temperature limits given stabilized GHG concentrations. For negotiations the implied emission pathways were needed!
Emission Pathways Offering a variety of options for decision making !
The MAGICC Model Highlighting the basics of the approach
Main results Estimated median temperature response to emission pathways
Uncertainty analysis Lower(!) bounds of uncertainty for single emission pathways by exploring parametric uncertainty related to scientific uncertainty (e.g. climate sensitivity)
Uncertainty analysis Sensitivity of the findings to different assumptions is necessary. Here: different scenarios for aerosols lead to different answers
Remaining challenges • Is looking for the 50% Isopleths really what your risk averseness implies? • Understanding the science of uncertainty • Enhance understanding of model uncertainties
Conclusions • Talking to Policy Makers is not as bad as you think! • But if you do so, don’t forget the essentials of uncertainty analysis • Remaining challenges (always make sure you have some!)
Content of the Policy Brief • Mitigating climate change through reductions in greenhouse gas emissions: background • Mitigating climate change through reductions in greenhouse gas emissions: climate science constraints on annual global emissions targets for 2020 and 2050 • Mitigating climate change through reductions in greenhouse gas emissions: economic assessment of emissions targets • Annex 1 The approach and its implications for the conclusions • Annex 2 Key information for 20 emissions paths