IEEE VIS 2024 Content: A Ridge-based Approach for Extraction and Visualization of 3D Atmospheric Fronts

Honorable Mention

A Ridge-based Approach for Extraction and Visualization of 3D Atmospheric Fronts

Anne Gossing - Zuse Institute Berlin, Berlin, Germany

Andreas Beckert - Universität Hamburg, Hamburg, Germany

Christoph Fischer - Universität Hamburg, Hamburg, Germany

Nicolas Klenert - Zuse Institute Berlin, Berlin, Germany

Vijay Natarajan - Indian Institute of Science, Bangalore, India

George Pacey - Freie Universität Berlin, Berlin, Germany

Thorwin Vogt - Universität Hamburg, Hamburg, Germany

Marc Rautenhaus - Universität Hamburg, Hamburg, Germany

Daniel Baum - Zuse Institute Berlin, Berlin, Germany

Room: Bayshore VI

2024-10-16T16:09:00ZGMT-0600Change your timezone on the schedule page
2024-10-16T16:09:00Z
Exemplar figure, described by caption below
Atmospheric fronts play a significant role in mid-latitude weather dynamics and are responsible for 50% - and locally up to 90% - of extreme precipitation. To support visual analysis of frontal processes, in this paper we present a ridge-based approach for the extraction and visualization of three-dimensional atmospheric fronts. Current contour-based visualization techniques require data smoothing that can lead to local inaccuracies, whereas our ridge detection algorithm extracts fronts as continuous surfaces without smoothing. This preserves the original data resolution, thereby facilitating the investigation of small-scale processes in frontal environments.
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Keywords

Atmospheric front, ridge surface, visual analysis.

Abstract

An atmospheric front is an imaginary surface that separates two distinct air masses and is commonly defined as the warm-air side of a frontal zone with high gradients of atmospheric temperature and humidity (Fig. 1, left). These fronts are a widely used conceptual model in meteorology, which are often encountered in the literature as two-dimensional (2D) front lines on surface analysis charts. This paper presents a method for computing three-dimensional (3D) atmospheric fronts as surfaces that is capable of extracting continuous and well-confined features suitable for 3D visual analysis, spatio- temporal tracking, and statistical analyses (Fig. 1, middle, right). Recently developed contour-based methods for 3D front extraction rely on computing the third derivative of a moist potential temperature field. Additionally, they require the field to be smoothed to obtain continuous large-scale structures. This paper demonstrates the feasibility of an alternative method to front extraction using ridge surface computation. The proposed method requires only the second derivative of the input field and produces accurate structures even from unsmoothed data. An application of the ridge-based method to a data set corresponding to Cyclone Friederike demonstrates its benefits and utility towards visual analysis of the full 3D structure of fronts.