Temporal Visualization of Hurricane Wind Fields Using Mapper Graphs

Authors

Justin Hoffmeier (Florida Polytechnic University)

Keywords

Topological data analysis, time-series visualization, tropical cyclone wind field asymmetry

Abstract

Topological Data Analysis (TDA) provides an effective framework for visualizing the underlying shape of high-dimensional data, revealing structural insights often obscured by traditional methods. In particular, the Mapper algorithm generates graph-based representations that capture global connectivity and local similarity within high-dimensional point clouds. While time-series data is frequently clustered without explicit temporal timestamps to prevent biasing similarity metrics, the resulting topological structures of TC wind field data can inherently preserve the temporal sequence. This phenomenon is particularly evident in the Mapper graphs of tropical cyclone (TC) wind fields. We present a novel visualization tool designed to recover and project this latent temporal information onto the topological map. Applying this tool to a longitudinal study of tropical cyclones from 2012–2025 reveals that specific wind field states are present among TCs with high intensities.