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Hornero: Thunderstorms Characterization using Visual Analytics
Author(s) -
Diehl Alexandra,
Pelorosso Rodrigo,
Ruiz Juan,
Pajarola Renato,
Gröller M. Eduard,
Bruckner Stefan
Publication year - 2021
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.14308
Subject(s) - nowcasting , visual analytics , thunderstorm , computer science , workflow , visualization , convective storm detection , interactive visual analysis , analytics , context (archaeology) , storm , weather forecasting , data visualization , data science , data mining , meteorology , database , radar , geology , telecommunications , paleontology , physics
Analyzing the evolution of thunderstorms is critical in determining the potential for the development of severe weather events. Existing visualization systems for short‐term weather forecasting (nowcasting) allow for basic analysis and prediction of storm developments. However, they lack advanced visual features for efficient decision‐making. We developed a visual analytics tool for the detection of hazardous thunderstorms and their characterization, using a visual design centered on a reformulated expert task workflow that includes visual features to overview storms and quickly identify high‐impact weather events, a novel storm graph visualization to inspect and analyze the storm structure, as well as a set of interactive views for efficient identification of similar storm cells (known as analogs) in historical data and their use for nowcasting. Our tool was designed with and evaluated by meteorologists and expert forecasters working in short‐term operational weather forecasting of severe weather events. Results show that our solution suits the forecasters' workflow. Our visual design is expressive, easy to use, and effective for prompt analysis and quick decision‐making in the context of short‐range operational weather forecasting.