Towards a wavelet-based dynamically adaptive climate model
We present results for a hydrostatic implementation based on the DYNAMICO discretization. The grid is adapted horizontally using the strictest condition over all vertical layers and the Lagrangian vertical coordinates are conservatively remapped periodically onto the initial grid. I will describe the results of a number of test cases, as well as assess parallel performance. The goal of this project is to help assess the potential of dynamical adaptivity to improve the computational performance and numerical accuracy of atmosphere and ocean models.
Prof. Nicholas Kevlahan is a Professor in the Department of Mathematics and Statistics at McMaster University, Canada. He has been an invited professor at Université Grenoble-Alpes, INRIA, École Normale Supérieure (Paris), École Polytechnique (Paris), and a visiting researcher at the University of Cambridge. His interdisciplinary research program is focused on advanced mathematical and computational methods for fluid dynamics problems from physics and engineering. His current research includes the theory and computation of fluid turbulence, with a special interest in numerical methods based on the wavelet transform.