Large-scale three-dimensional visualization of Doppler reflectivity data

Peter Kristof, Purdue University

Abstract

The super resolution NEXRAD Level II Doppler radar data provides critical information on reflectivity, wind velocity and spectrum width for the entire United States. The goal of this work is to develop a framework that enables multiple users to interactively access, analyze and visualize the Doppler reflectivity data in 3D to study near real-time weather events. To provide interactive high-quality volumetric weather visualization, we combined two approaches dealing with large-scale storage of global weather data and out-of-core volume rendering using CUDA ray casting. The results of our work show that the reflectivity data from multiple radars can be preprocessed into data format that is efficient for large-scale volumetric visualization of reflectivity data in near-real time and requires minimal run-time processing.

Degree

M.S.

Advisors

Benes, Purdue University.

Subject Area

Meteorology|Computer science

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