By combining the high-order accuracy of spectral expansions with the locality and geometric flexibility of finite elements, spectral elements are an attractive option for the next generation of numerical climate models. Crucial to their construction is the configuration of nodes in an element — casual placement leads to polynomial fits exhibiting Runge phenomena manifested by wild spatial oscillations. I provide highorder triangular elements suitable for incorporation into existing spectral element codes. Constructed from a variety of measures of optimality, these nodes possess the best interpolation error norms discovered to date. Motivated by the need to accurately determine these error norms, I present an optimization method suitable for finding extrema in a triangle. It marries a branch and bound algorithm to a quadtree smoothing scheme. The resulting scheme is both robust and efficient, promising general applicability. In order to qualitatively evaluate these nodal distributions, I introduce the concept of a Lagrangian Voronoi tessellation. This partitioning of the triangle illustrates the regions over which each node dominates. I argue that distant and disconnected regions are undesirable as they exhibit a non-physical influence. Finally, I have discovered a link between point distributions in the simplex and on the hypersphere. Through a simple transformation, a distance metric is defined permitting the construction of Voronoi diagrams and the calculation of mesh norms.