Multiscale wavelet modelling of turbulent flows in the atmosphere and oceans

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Numerical weather forecasting helps Canadians manage their lives and businesses day-to-day, and climate modelling helps Canada plan for the future. The effects of extreme weather events, such as storms, floods and droughts, can be mitigated, but only if they are accurately predicted far enough in advance. Operational models use static computational grids, which are not able to adapt to resolve rapidly developing storms or coarsen where less accuracy is needed. This means that computational resources are not used efficiently and that the resulting error is not uniform in space and time. It is also difficult to increase resolution where more accuracy is needed, for example over densely populated areas, or over environmentally sensitive habitats. The goal of this proposed research is to develop an experimental atmosphere and ocean model that will use innovative wavelet techniques to dynamically modify the grid resolution to maintain the desired level of accuracy, or to make optimal use of the available computational resources. The resolution could also be adapted statically to improve predictions in areas of special interest. The first stage of this project is to develop a computer code that adaptively solves the rotating shallow water equations on the sphere. The second stage is to extend the two-dimensional shallow water model to a three-dimensional multilayer hydrostatic model. At this point the computer code will form a so-called "dynamical core" on which more physical effects (e.g. radiation, clouds, the effect of topography, vegetation) can be added to build a true climate model. The final stage of this project will be to extend the multiscale computational model to a multiscale multi-physics model to account for important subgrid scale physical effects, such as cloud formation. This proposal is part of an international effort to develop the next generation of weather and climate models that will use dynamic adaptivity and multiscale modelling to improve computational efficiency and prediction accuracy. Canada has been a world leader in numerical weather prediction and climate modelling, and the knowledge gained in this research project will keep Canada at the forefront as new models are developed to deal with emerging challenges.