Tuesday, 24 January 2017: 9:00 AM
602 (Washington State Convention Center )
While mitigating climate change would require substantial and sustained reductions in greenhouse gas emissions through worldwide consensus and collaborations, adapting to climate change has become a major focus of local policy makers and development practitioners. Planning of adaptation strategies against the changing climate requires a thorough assessment of the potential impacts of climate change at local scales. However, climate change impact assessment is usually subject to a number of challenges, such as the lack of high-resolution climate scenarios and the uncertainty in climate model projections, which may pose barriers to impact researchers and decision makers. To tackle these challenges, we will develop high-resolution regional climate scenarios using multiple regional climate models (e.g., PRECIS, WRF, and RegCM) driven by different global climate models (e.g., HadGEM2-ES, CanESM2, GFDL-ESM2M, and CCSM4) under RCP4.5 and RCP8.5 scenarios. A Bayesian hierarchical model will be proposed to help quantify the uncertainties associated with the regional climate ensemble simulations. Results on model evaluation and probabilistic projections of temperature and precipitation changes over Ontario, Canada will be analyzed and presented. The probabilistic projections can provide useful information for assessing the risks and costs associated with climatic changes at regional and local scales.
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