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Economically optimal risk reduction strategies in the face of uncertain climate thresholds

Economically optimal risk reduction strategies in the face of uncertain climate thresholds Anthropogenic greenhouse gas emissions may trigger climate threshold responses, such as a collapse of the North Atlantic meridional overturning circulation (MOC). Climate threshold responses have been interpreted as an example of “dangerous anthropogenic interference with the climate system” in the sense of the United Nations Framework Convention on Climate Change (UNFCCC). One UNFCCC objective is to “prevent” such dangerous anthropogenic interference. The current uncertainty about important parameters of the coupled natural – human system implies, however, that this UNFCCC objective can only be achieved in a probabilistic sense. In other words, climate management can only reduce – but not entirely eliminate – the risk of crossing climate thresholds. Here we use an integrated assessment model of climate change to derive economically optimal risk-reduction strategies. We implement a stochastic version of the DICE model and account for uncertainty about four parameters that have been previously identified as dominant drivers of the uncertain system response. The resulting model is, of course, just a crude approximation as it neglects, for example, some structural uncertainty and focuses on a single threshold, out of many potential climate responses. Subject to this caveat, our analysis suggests five main conclusions. First, reducing the numerical artifacts due to sub-sampling the parameter probability density functions to reasonable levels requires sample sizes exceeding 10 3 . Conclusions of previous studies that are based on much smaller sample sizes may hence need to be revisited. Second, following a business-as-usual (BAU) scenario results in odds for an MOC collapse in the next 150 years exceeding 1 in 3 in this model. Third, an economically “optimal” strategy (that maximizes the expected utility of the decision-maker) reduces carbon dioxide(CO 2 ) emissions by approximately 25% at the end of this century, compared with BAU emissions. Perhaps surprisingly, this strategy leaves the odds of an MOC collapse virtually unchanged compared to a BAU strategy. Fourth, reducing the odds for an MOC collapse to 1 in 10 would require an almost complete decarbonization of the economy within a few decades. Finally, further risk reductions (e.g., to 1 in 100) are possible in the framework of the simple model, but would require faster and more expensive reductions in CO 2 emissions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Climatic Change Springer Journals
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