IEEE VIS 2024 Content: Interactive Visualization of Ensemble Data Assimilation Forecasts for Freshwater Floods

Interactive Visualization of Ensemble Data Assimilation Forecasts for Freshwater Floods

Ameya B Patil - University of Washington, Seattle, United States

Marlee Smith - National Center for Atmospheric Research, Boulder, United States

Helen Kershaw - National Center for Atmospheric Research, Boulder, United States

Moha El Gharamti - National Center for Atmospheric Research, Boulder, United States

Room: Esplanade Suites I + II + III

2024-10-14T12:30:00ZGMT-0600Change your timezone on the schedule page
2024-10-14T12:30:00Z
Abstract

Freshwater floods during hurricanes are known to cause significant damage to life and property. We could be better prepared to prevent these losses if flood forecasts can be made accurately and understood effectively. In addition to the technical complexities when modeling freshwater systems, forecasting freshwater floods also involves numerous uncertainties which also need to be considered to make reliable data driven decisions. In this demo, we describe the design and implementation of HydroVis–a decision support system designed to help both weather scientists to triage the flood forecasting models, and the policymakers to help them understand the forecasts effectively and make informed decisions accordingly.