Statistical Modeling of the World: Computer and Physical Models in Earth, Ocean, and Atmospheric Sciences

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Collaborative Research Team Project: 2014-2017

Recent gains in computational power have increased the ability to simulate complex physical phenomena. With these gains comes the potential to investigate scientific questions that historically would have been addressed only through expensive physical experimentation, if at all. Examples of exploration of complex systems via computational models are common in science, with recent applications ranging from astrophysics to climate change to the study of micro-scale organisms. In fact, the recent Intergovernmental Panel on Climate Change (IPCC) report contains several conclusions that are based on inference about the real world using computational models.

This project aims to bring together statistical and earth scientists to develop new methodology for using complex computer models and field observations for important environmental applications.  Specific scientific goals focus on leveraging each source of information to make predictions of the physical system, with estimates of uncertainty, and to estimate unknown physical constants (i.e., a type of inverse problem).  We aim to create a program that promotes collaboration among scientists, makes important contributions to statistical and earth, ocean, and atmospheric sciences and enhances graduate student training.

The team leader is Derek Bingham of Simon Fraser University, and collaborators are Hugh Chipman, Richard Karsten and Pritam Ranjan of Acadia University, Gwenn Flowers of Simon Fraser University, Douw G. Steyn and William Welch of University of British Columbia and researchers at Brigham Young University, Los Alamos National Laboratory and the National Center for Atmospheric Research.

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