报告题目：Climate model bias correction for impacts and adaptation studies: univariate methods, multivariate methods, and the interface between climate models and impacts modelers

报告人：Alex J. Cannon教授，加拿大环境与气候变化中心

邀请人：陈 杰 教授

时间：2018年11月29号 (星期四) 下午3:30-4:30

地点：国家重点实验室学术报告厅（农水楼一楼）

报告人简介：

    Dr. Alex J. Cannon is a Research Scientist with the Climate Data and Analysis Section of the Climate Research Division, Environment and Climate Change Canada, at the Canadian Centre for Climate Modelling and Analysis in Victoria, Canada. He holds a Ph.D. in Atmospheric Science from the University of British Columbia (UBC) and has served as an associate faculty member in the Department of Earth, Ocean and Atmospheric Sciences at UBC since 2009. He is a member of the World Meteorological Organization's Task Team for Climate Services Toolkit and Downscaling and a past member of the American Meteorological Society Committee on Artificial Intelligence Applications in Environmental Science. He has received the Canadian Meteorological and Oceanographic Society's Andrew Thomson Prize in Applied Meteorology and Tertia M.C. Hughes Memorial Prize, and the World Meteorological Organization’s Research Award for Young Scientists. Dr. Cannon's research is concerned with understanding the state, trends, variability, extremes, and future projections of climate at both global and regional scales. His work often deals with the development and application of statistical and machine learning methods for climate and hydrological data analysis, including climate model bias correction, downscaling, climate extremes and extreme value analysis, probabilistic models for environmental prediction, and assessing impacts of climate variability and change on environmental systems. He has published more than 90 journal articles and book chapters.

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