Source:Department of Computer Science, University of Calgary, Volume MSc, Calgary (2016)
The icosahedral non-hydrostatic (ICON) model is a climate model based on an icosahedral representation of the Earth and is used for numerical weather prediction. In this thesis, we investigate the unstructured representation of different cells in ICON and undertake the task of designing a technique that converts it to a common structured representation. We introduce icosahedral maps, data structures that are designed to fit the geometry of cells in the ICON model irrespective of their types. These maps represent the connectivity information in ICON in a highly structured two-dimensional hexagonal representation that provides explicit neighborhood information. Our maps facilitate the execution of a multiresolution analysis on the ICON model. We demonstrate this by applying a hexagonal version of the discrete wavelet transform in conjunction with our icosahedral maps to decompose ICON data to different levels of detail and to compress it via a thresholding of the wavelet coefficients.