Multi-resolution visualization techniques for nested weather models

Abstract

Scaling of simulations challenge 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 for 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.

Visual Analysis of the Air Pollution Problem in Hong Kong

“…Treinish [20,21] has conducted various research works on weather data visualization but his approaches lean more toward scientific visualization rather than information visualization. Healey et al [9] used nonphotorealistic brush strokes for visualizing multidimensional information spaces like weather data.…”

A Visualization System for Weather Forecast Analogs

“…He discusses problems such as multiresolution visualization [15] and data fusion [16] for weather data. Case studies are carried out to analyze severe rainfall events [17].…”

Visualization of Multi‐Variate Scientific Data

“…Treinish investigated how specialized visualizations can be used to effectively visualize weather data using views of varying complexity [Tre99] and presented a multi‐resolution technique for complex weather data [Tre00] (see Figure 9).…”