Quantifying uncertainties in greenhouse gas mitigation scenarios

A highly visible stream of methodologically oriented work by the Energy (ENE) Program focused on the quantification of uncertainties surrounding stringent greenhouse gas mitigation scenarios and was published in the journal Nature in early 2013.

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Quantifying uncertainties

The research [1] initiated in 2011 by former YSSP participant and current ENE staff Joeri Rogelj, together with David McCollum and Keywan Riahi, represented a systematic attempt to quantify and rank different types of uncertainties associated with the attainability of various temperature targets.

The research combines a large ensemble of integrated assessment scenarios with probabilistic climate change projections in order to assess the relative importance of four main types of uncertainties: political, geophysical, technological, and societal.

Innovative aspects of the study are the quantification of probabilistic “mitigation cost-risk” surfaces that help to convey the trade-offs between the stringency of the mitigation effort and the resultant risk to exceed certain temperature thresholds.

The main conclusion of the study that uncertainties surrounding the timing of political action dominate over the geophysical or other uncertainties received widespread attention in over 180 independent media articles, including the Scientific American and additional News features in Nature as well as Nature Climate Change (see Figure 1).

Figure 1. The implications of delays in mitigation for the likelihood of limiting global warming to below 2C. The black arrow shows the reduced chances in case of delayed mitigation until 2030 and a mitigation effort of 40$/tCO2. (Source: Rogelj et al, 2013, Nature).

References

[1] Rogelj J, McCollum DL, Reisinger A, Meinshausen M, Riahi K (2013). Probabilistic cost distributions for climate change mitigation. Nature, 493(7430): 79-83.


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Last edited: 22 May 2014

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