Download or read book High-Resolution Regional Climate Downscaling and Probabilistic Projection for Impact Assessment - A Canadian Case Study written by Xiuquan Wang and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human-induced climate change has been regarded as one of the most pressing issues around the world because it often leads to severe, widespread, and irreversible consequences. Assessing the potential impacts of climate change is essential and critical for developing appropriate mitigation and adaptation strategies against the changing climate. In this research, a series of approaches and methodologies have been proposed for dealing with the challenges in climate change impact assessment due to the lack of highresolution climate projections and the difficulty in quantifying the uncertainties associated with future climate projections. The proposed approaches and methodologies have been applied to the Province of Ontario, Canada to demonstrate their effectiveness in generating probabilistic and high-resolution regional climate scenarios. Specifically, a new statistical downscaling tool, named SCADS, has been developed to help perform rapid development of downscaled scenarios under current and future climate forcing conditions. The SCADS uses a cluster tree to effectively deal with continuous and discrete variables, as well as nonlinear relations between large-scale atmospheric variables and local surface ones. A hybrid downscaling approach by coupling the PRECIS model and the SCADS model has been proposed to construct high resolution climate projections for studying climate change impacts at local scales. The coupled approach was applied for projecting the future climate over Ontario at a fine resolution of 10 km. A Bayesian hierarchical model has been developed to quantify the uncertainties of regional climate projections in a statistical framework based upon a limited number of explicit assumptions for prior distributions. By feeding the observations for current climate and the PRECIS ensemble simulations into the Bayesian model, probabilistic projections of future climatic changes over Ontario have been developed. The likely changes in temperature and precipitation as well as extreme precipitation events across the Province of Ontario were evaluated to help understand its local climate's response to global warming. A public climate change data portal, named Ontario CCDP, have been established to ensure impact researchers and decision makers have free access to the high-resolution climate projections, thus supporting further impact studies and development of climate mitigation and adaptation strategies.