Abstract
AbstractAnalyzing 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.
Highlights
According to the UN Office for Disaster Risk Reduction (UNDRR), the indirect economic losses caused by climate-related disasters inc 2021 The Author(s) Computer Graphics Forum c 2021 The Eurographics Association and John Wiley & Sons Ltd
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 in historical data and their use for nowcasting
We present a visual analytics framework for the visualization of thunderstorms based on weather radar data, storm tracking by a storm cell identification and tracking software (i.e., Titan [DW93]), and probabilistic forecast generated by an analog-based nowcasting system (e.g., Atencia Zawadzki [AZ15])
Summary
According to the UN Office for Disaster Risk Reduction (UNDRR), the indirect economic losses caused by climate-related disasters inc 2021 The Author(s) Computer Graphics Forum c 2021 The Eurographics Association and John Wiley & Sons Ltd. There are two groups of operational techniques that can be used and combined to provide human forecasters with an adequate guidance for issuing short-time warnings [SXW∗13]: numerical weather prediction and data-driven prediction ( known as nowcasting) The latter is based on the extrapolation of weather radar data in time using different approaches like optical flow [PNPH∗19], tracking of individual convective cells or convective cell clusters [DW93], analog forecasting [AZ15] or deep learning [FSN∗19, ASH20]. Only a few works [UCAb, UCAa, Nin] address the visualization of very-shortterm weather forecasting that takes place between a few minutes and six hours These tools visualize weather radar data and trajectories, there is still a need of integrating storm tracking results and basic radar data and their properties at different levels of abstraction and with enough simplicity to make quick decisions in the context of nowcasting. This approach helped us to adjust our visual design to the specifics of the domain tasks, such as rapid detection, prompt analysis, and quick decision making
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