Please note that this session was withdrawn and is no longer available in the respective programme. This withdrawal might have been the result of a merge with another session.
Probabilistic frameworks for estimating uncertainties in impacts of future climate change
Conventional approaches for assessing the potential impacts of future anthropogenic climate change commonly make use of climate scenarios. These scenarios are usually based on direct outputs from general circulation models (GCMs) or on information downscaled from GCMs and their selection tends to be arbitrary. Few impact studies examine how well such scenarios represent uncertainties in future projections of climate change. This results in a set of impact estimates, each scenario-dependent, with no information about their relative likelihood. Recently, climate modellers have begun to represent future climates probabilistically, using ensemble simulations from single or multiple GCMs and/or their downscaled derivatives. Probabilities are usually conditional on a given scenario of future emissions. Probabilistic climate projections, combined with quantitative information on other uncertainties associated with estimates of future impacts, offer an opportunity to express future impacts in terms of risk. Submissions are invited that explore different aspects of quantifying the risks of future (decadal- to century-scale) impacts of climate change using probabilistic methods.