The Dynamics of Climate Change
Climate change is one of the most challenging problems that our society faces today. Understanding our current climate, and predicting how it evolves, depends on our ability to simulate climate systems using high-performance computing. This requires a deep understanding of the physics of climate systems and using numerical experiments to simulate their evolution. The results of these scientific investigations should help to better inform climate-related policy decisions.
The Faculty of Mathematics is home to several members of the University of Waterloo’s Waterloo Climate Institute. These faculty members have expertise in climate related systems and carry out research on physical problems involving the atmosphere, oceans, sea-ice and lakes. Some of these research projects focus on small-scale problems, which are critical for understanding the global climate system as a whole. These Climate Institute members are also training students in fluid dynamics relevant to geophysical systems as well as computational modelling of these problems.
Chris Bauch: Bauch's interested in modeling the dynamics of coupled social-climate systems. This approach studies the two-way interactions between climate dynamics and social dynamics.
Hans De Sterck: De Sterck's research interests include parallel numerical simulation methods for large-scale fluid dynamics problems. He works on compressible fluid and plasma simulations for space physics, including space weather prediction on adaptive cubed-sphere grids. He does not yet have experience with climate applications, but the methods he develops are like those used for global climate models.
Kevin Lamb: Lamb's primary area of research is on internal gravity waves in the ocean. These waves are responsible for a large fraction of mixing in the interior of the ocean and hence play a role in large scale ocean circulation with implications for climate. I also have interests in physical and biogeochemical processes (e.g. hypoxia) in large lakes and how climate change may affect them.
Francis Poulin: Poulin’s research focuses on both physical and biological oceanography. This includes dynamics of the oceans at large-scales, which includes how the energy added at planetary scales is transferred down to smaller scales. Moreover, he also investigates planktonic ecosystems and how they are affected by the physics of the oceans. Part of the research entails developing state-of-the-art computing software that can be used to answer these research questions.
Marek Stastna: Stastna's group studies stratified fluid dynamics from a numerical point of view. We develop simulation and data analysis tools. Areas of climate application we are interested include: the changing winter season of medium and large lakes, the changes in the hydrogeology of the Yucatan peninsula over the Quaternary period, and coherent structures in large ocean simulations that impact offshore-onshore exchange.
Michael Waite: Waite uses numerical simulations with various degrees of complexity to study turbulence and convection in the atmosphere. These phenomena are responsible for mixing, transport, and dissipation, but are often not resolved by climate and numerical weather prediction models. His research group works on fundamental research of small-scale dynamics that will lead to improved parameterizations of these processes.
Christine Dow: Dow’s research is focused on ice and glacier changes in a warming climate. She uses numerical modeling to examine the impact of water flow underneath glaciers on their flow speed and contribution to global sea level rise.
Chris Fletcher: Fletcher’s research program uses computer models of the Earth system to investigate climate variability and change at scales ranging from global to a single watershed. He is interested in understanding how snow and ice in cold countries like Canada will change in response to global heating. His research team uses state-of-the-art modelling and supercomputing resources to help reduce the uncertainty in these projections, to deliver data that is more useful to support decision-making activities.
Andrea Scott: Scott's research focuses on retrieval of sea ice quantities from remote sensing data to improve our knowledge of the state of sea ice in the Arctic. This includes investigation of information content of observational data and data fusion/data assimilation methods. Novel data-driven approaches (eg. convolutional neural networks) to extract sea ice information from satellite data are particularly promising. Recent interests include investigating methods that combine data-driven approaches with physical models for improved sea ice state estimation, and links between these methods and data assimilation.