Multiscale Methods for Geophysical Fluid Dynamics
Lead Researcher and Department
Dr. Jahrul Alam, Department of Mathematics and Statistics, Memorial University
Collaborators and Students
Graduate students: Rokibul Islam (MSc), Zahangir Hossain (MSc)
Funding Resources
NSERC
Summary
Understanding turbulent flows at a fundamental level is essential to understand fluid flows in the atmosphere and oceans, and is critical for such varied purposes as weather forecasting, projecting climate change, and mitigating air pollution. Our current conceptual and technical tools are inadequate for explaining turbulence, and have yet to approach towards a comprehensive theory. Moreover, due to limitations of memory and CPU time, inadequate representation of interactions across multiple spatio-temporal scales in the atmosphere and oceans is one stumbling reason for poor performance of computer models. For example, satellite observations in the atmosphere and oceans exhibit localized, filamentary structures with relevant scales that are much smaller than scales of global dynamics. Clearly, if we knew how to define and extract such localized structures, this would lead to a promising multi-scale numerical modeling approach, thereby leading to new parameterization techniques or improving existing parameterizations. Recent scientific developments in multi-scale approaches, such as wavelet methods, may provide a novel multi-scale modeling frame work for geophysical fluid dynamics, but little is know how wavelet methodology can be used for atmospheric or oceanic modeling. For example, can one use wavelets to model multiscale features in the atmosphere or oceans? How the computational challenges of geophysical fluid dynamics can be addressed to some extent using a multi-scale approach? This research aims for the development of a new multiscale modeling framework that is based on a multiscale wavelet methodology.
More specifically, this research will study the following: i) Multi-scale wavelet methodology for geophysical turbulence; ii) A fully-Lagrangian modeling system to investigate the nonlinear evolution of unresolved scales; iii) Reliability and scalability of numerical model's output after many time steps. There are possibilities of accepting potential candidates for doctoral or post-doctoral studies.
Dates
2009-2013
Keywords
Turbulence, Geophysical flows, Wavelet models, Atmospheric Modeling
Locations
St. John's
Avalon Peninsula
Industry Sectors
Mathematics Research and Development Services (Professional, Scientific and Technical Services — Scientific Research and Development Services — Research and Development in the Physical, Engineering and Life Sciences)
Thematic Categories
Mathematics and Statistics (Science Research)
Departments
Mathematics & Statistics, Faculty of Science (STJ)