Coast to Coast Seminar Series - Abstracts
Coast-to-Coast Seminar Series: "Applying machine learning methods to climate variability"
William Hsieh
Department of Earth and Ocean Sciences, University of British Columbia
Date: Sep 21, 2010
Time: 11:30 - 12:30
Room: ASB10900
WebSite: Click Here
Abstract
Machine learning methods, having originated from computational intelligence (i.e. artificial intelligence) are now ubiquitous in the environmental sciences. Applications of machine learning methods, such as neural networks and support vector machines, to the analysis of climate variability and to short term climate prediction will be presented. Examples include the El Nino phenomenon in the tropical Pacific, and interannual variability in the Canadian winter climate and extreme weather.
About The Speaker: William Hsieh obtained from the University of British Columbia his B.S. degree in combined honours mathematics and physics (1976), an M.S. in physics (1978), and a Ph.D. degree in oceanography and physics (1981). He did postdoctoral work at Cambridge University and at the University of New South Wales, before returning to the University of British Columbia, where he eventually became Professor in the Department of Earth and Ocean Sciences and in the Department of Physics and Astronomy, as well as the Chair of the Atmospheric Science Programme. He is currently professor emeritus, with an active research group. Best known for his pioneering work in developing and applying machine learning methods in the environmental sciences, he has over 90 peer-reviewed publications covering areas of climate variability and prediction, machine learning, oceanography, atmospheric science and hydrology. His graduate-level book "Machine Learning Methods in the Environmental Sciences -- Neural Networks and Kernels" (2009) was published by Cambridge University Press.Coast-to-Coast Seminar Series: "Insight into Lower Atmospheric Composition from Remote Sensing and Modeling"
Randall Martin
Department of Physics and Atmospheric Science, Dalhousie University
Date: Oct 05, 2010
Time: 11:30 - 12:30
Room: ASB10900
WebSite: Click Here
Abstract
Satellite remote sensing of atmospheric composition (such as aerosols, ozone, and their precursors) has progressed markedly over the past decade. Global numerical modeling plays a critical role in interpreting these observations. This talk will highlight recent advances in both remote sensing and global modeling of the troposphere, and their application for insight into processes affecting climate and global air quality.
About the Speaker: Randall Martin is a Killam Professor in the Department of Physics and Atmospheric Science at Dalhousie University, and a Research Associate at the Harvard-Smithsonian Center for Astrophysics. He received a B.S. from Cornell University in Engineering in 1996, a M.Sc. in Environmental Science from Oxford University in 1998, and a Ph.D. from Harvard University in 2002 with a focus on Atmospheric Chemistry. He is a recipient of the Langstroth Memorial Teaching Award, an NSERC Discovery Accelerator Supplement, and a Killam Prize. He has published 70 peer-reviewed journal articles on the processes that affect atmospheric composition, and their implications for climate and air quality
Coast-to-Coast Seminar Series
Francis Zwiers
Director, Climate Research Division, Environment Canada
Date: Oct 19, 2010
Time: 11:30 - 12:30
Room: ASB10900
WebSite: Click Here
Abstract
Coast-to-Coast Seminar Series
Marlon Lewis
Department of Oceanography, Dalhousie University
Date: Nov 02, 2010
Time: 11:30 - 12:30
Room: ASB10900
WebSite: Click Here
Abstract
Coast-to-Coast Seminar Series: "How will marine ecosystems adapt to a future ocean that will be warmer, more stratified, more acidic and less oxygenated?"
Ken Denman
DFO Institute of Ocean Sciences, and EC Canadian Centre for Climate Modelling and Analysis, University of Victoria
Date: Nov 16, 2010
Time: 11:30 - 12:30
Room: ASB10900
WebSite: Click Here
Abstract
Primarily from burning fossil fuels, humans are adding increasing amounts of the greenhouse gas carbon dioxide to the atmosphere. More than a third of this new carbon dioxide ends up in the ocean, and more than 90% of the additional heat from the greenhouse effect is entering the oceans. As a result the oceans are becoming warmer and more stratified, which reduces the mixing of nutrients from below up into the surface ocean and of oxygen from the surface layer down into the subsurface ocean. In addition the extra carbon dioxide is causing the oceans to become more acidic. Can we predict how whole marine ecosystems will adapt, when we do not yet know how much capacity individual species have to adapt to these expected changes to their environment. I will outline a modelling framework to explore the capacity of species to adapt to a changing environment based on existing 'phenotypic' diversity and potential 'plasticity'.
About The Speaker: Ken Denman is a Senior Scientist with Fisheries and Oceans Canada (DFO), since 2000 working at the Canadian Centre for Climate Modelling and Analysis of Environment Canada, located at the University of Victoria where he is an Adjunct Professor. His research involves the interactions between marine ecosystems, biogeochemical cycles and climate change. His current research interests centre on forecasting the responses of marine ecosystems to the acidification of the oceans and to other aspects of climate change including possible geoengineering measures. He was Coordinating Lead Author of Chapter 7 of the 2007 Intergovernmental Panel on Climate Change (IPCC) WG1 AR4 titled "Couplings between changes in the climate system and biogeochemistry"; and Coordinating Lead Author of Chapter 10 in the Second Assessment Report (1995) of IPCC WG1, titled "Marine biotic responses to environmental change and feedbacks to climate". The IPCC shared the 2007 Nobel Peace Prize with Al Gore for its work on climate change. Ken Denman is a Fellow of the Royal Society of Canada, and has received the President's Prize of the Canadian Meteorological and Oceanographic Society, the T.R. Parsons Medal for excellence in ocean science, and the Wooster Award of the North Pacific Marine Sciences Organization (PICES) for research excellence in the North Pacific. He has served on the Steering Committees of the Joint Global Ocean Fluxes Study (JGOFS), the Global Ocean Observing System (GOOS), and the Surface Ocean Lower Atmosphere Study (SOLAS). He recently completed 6 years as a member of the Joint Scientific Committee of the World Climate Research Programme. He received a PhD in ocean physics from the University of British Columbia.Coast-to-Coast Seminar Series: "Climate Impacts of Freshwater Forcing of the Ocean General Circulation"
Richard Peltier
Centre For Global Change Science, University of Toronto
Date: Nov 30, 2010
Time: 11:30 - 12:30
Room: ASB10900
WebSite: Click Here
Abstract
During the past million years of Earth history, climate variability has been dominated by a 100 kyr cycle of continental scale glaciation and deglaciation. Each of these quasi-periodic events owed its existence to the minute variations in the distribution of solar radiation caused by gravitational n-body effects in the solar system. In each cycle of this process continental glaciation was accompanied by a fall of mean sea level of approximately 120 m. The glaciation phase of each cycle persisted for approximately 90,000 years whereas the deglaciation phase was much more rapid, lasting approximately 10,000 years. During deglaciation, the return of freshwater to the ocean basins was responsible for highly significant disruptions of climate, foremost among which was the so-called ``Younger-Dryas" climate reversal during which northern hemisphere surface temperatures were forced to return to near full-glacial cold conditions even as the system was in the process of returning to a state of modern warmth. This phenomenon provides a target for testing the transient response of the global climate models that are employed to make predictions of the influence of global warming due to increasing concentrations of the atmospheric greenhouse gases. This test will be described in detail.
