GLOBAL SCALE DATA MODEL COMPARISON

Transforming raw observations into globally regular sampling grids or surface tessellations is a fundamental data processing and storage problem underlying much of our global data analysis. The basic geometry of traditionally employed quadrilateral-based point or area grids, while well suited to array storage and matrix manipulation, may inherently hinder numerical and geostatistical modeling efforts. Several scientists have noted the superior performance of triangular point grids and associated hexagonal surface tessellations, although no thorough evaluation of global data model alternatives has been conducted. In this paper we present results from a global grid comparison study that focused on recursive tiling of polyhedral faces projected onto the globe. A set of evaluation criteria for global gridding methods were developed. Of these, metrics for spheroidal surface area, compactness, and centerpoint spacing were found to be of particular importance. We present examples of these metrics applied to compare different recursive map projection-based and quadrilateral spherical subdivision tilings. One map projection approach, the Icosahedral Snyder Equal Area (ISEA) recursive tiling, shows particular promise due to its production of equal area hexagonal tiles on the spheroid at all levels of recursive partitioning