Hornero: Thunderstorms Characterization using Visual Analytics

Information

• Publication Type: Journal Paper (without talk)
• Workgroup(s)/Project(s):
  • Visualization Group
• Date: June 2021
• DOI: 10.1111/cgf.14308
• Journal: Computer Graphics Forum
• Number: 3
• Open Access: yes
• Volume: 40
• Pages: 1 – 12

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 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.

Additional Files and Images

Weblinks

• Entry in reposiTUm (TU Wien Publication Database)
• Entry in the publication database of TU-Wien
• DOI: 10.1111/cgf.14308

BibTeX

@article{Diehl_2021,
  title =      "Hornero: Thunderstorms Characterization using Visual
               Analytics",
  author =     "Alexandra Diehl and Rodrigo Pelorosso and J Ruiz and Renato
               Pajarola and Eduard Gr\"{o}ller and Stefan Bruckner",
  year =       "2021",
  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 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.",
  month =      jun,
  doi =        "10.1111/cgf.14308",
  journal =    "Computer Graphics Forum",
  number =     "3",
  volume =     "40",
  pages =      "1--12",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2021/Diehl_2021/",
}