Publications

Hornero: Thunderstorms Characterization using Visual Analytics

A. Diehl, R. Pelorosso, J. Ruiz, R. Pajarola, M. E. Gröller, and S. Bruckner

Abstract

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 forecastersÂ’ 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.

A. Diehl, R. Pelorosso, J. Ruiz, R. Pajarola, M. E. Gröller, and S. Bruckner, "Hornero: Thunderstorms Characterization using Visual Analytics," Computer Graphics Forum, vol. 40, iss. 3, 2021.
[BibTeX]

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 forecastersÂ’ 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.
@article{Diehl-2021-HTC,
author = {Alexandra Diehl and Rodrigo Pelorosso and Juan Ruiz and Renato Pajarola and Meister Eduard Gr\"{o}ller and Stefan Bruckner},
title = {Hornero: Thunderstorms Characterization using Visual Analytics},
journal = {Computer Graphics Forum},
volume = {40},
number = {3},
pages = {},
keywords = {visual analytics, weather forecasting, nowcasting},
doi = {},
abstract = {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 forecastersÂ’ 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.},
year = {2021},
pdf = "pdfs/Diehl-2021-HTC.pdf",
thumbnails = "images/Diehl-2021-HTC.png",
images = "images/Diehl-2021-HTC.jpg",
vid = "vids/Diehl-2021-HTC.mp4",
project = "MetaVis"
}
projectidMetaVisprojectid

Media

Downloads

Full paper [PDF]