Multi-resolution visualization techniques for nested weather models

Scaling of simulations challenges the effectiveness of conventional visualization methods. This problem becomes two-fold for mesoscale weather models that operate in near-real-time at cloud-scale resolution. For example, typical approaches to vector field visualization (e.g., wind) are based upon global methods, which may not illustrate detailed structure. In addition, such computations employ multi-resolution meshes to capture small-scale phenomena, which are not properly reflected in both vector and scalar realizations. To address the former critical point analysis and simple bandpass filtering of wind fields is employed for better seed point identification of streamline calculations. For the latter, an encapsulation of nested computational meshes is developed for general realization. It is then combined with the seed point calculation for an improved vector visualization of multi-resolution weather forecasting data.