STRIELAD -- A Scalable Toolkit for Real-time Interactive Exploration of Large Atmospheric Datasets

TL;DR

STRIELAD is a scalable toolkit enabling real-time interactive exploration and visualization of large atmospheric datasets by leveraging high-performance computing and smart rendering techniques.

Contribution

It introduces a novel scalable toolkit that combines parallel feature extraction with level-of-detail rendering for real-time analysis of large weather datasets.

Findings

Enables interactive exploration of large atmospheric datasets.

Achieves real-time visualization through parallel processing and smart rendering.

Supports complex weather data analysis at scale.

Abstract

Technological advances in high performance computing and maturing physical models allow scientists to simulate weather and climate evolutions with an increasing accuracy. While this improved accuracy allows us to explore complex dynamical interactions within such physical systems, inconceivable a few years ago, it also results in grand challenges regarding the data visualization and analytics process. We present STRIELAD, a scalable weather analytics toolkit, which allows for interactive exploration and real-time visualization of such large scale datasets. It combines parallel and distributed feature extraction using high-performance computing resources with smart level-of-detail rendering methods to assure interactivity during the complete analysis process.