Kress, JamesAfzal, ShehzadDasari, Hari PrasadGhani, SohaibZamreeq, ArjanGhulam, AymanHoteit, IbrahimDutta, SoumyaFeige, KathrinRink, KarstenZeckzer, Dirk2023-06-102023-06-102023978-3-03868-223-3https://doi.org/10.2312/envirvis.20231103https://diglib.eg.org:443/handle/10.2312/envirvis20231103Extreme rainfall events can devastate infrastructure and public life and potentially induce substantial financial and life losses. Although weather alert systems generate early rainfall warnings, predicting the impact areas, duration, magnitude, occurrence, and characterization as an extreme event is challenging. Scientists analyze previous extreme rainfall events to examine the factors such as meteorological conditions, large-scale features, relationships and interactions between large-scale features and mesoscale features, and the success of simulation models in capturing these conditions at different resolutions and their parameterizations. In addition, they may also be interested in understanding the sources of anomalous amounts of moisture that may fuel such events. Many factors play a role in the development of these events, which vary depending on the locations. In this work, we implement a visualization environment that supports domain scientists in analyzing simulation model outputs configured to predict and analyze extreme precipitation events. This environment enables visualization of important local features and facilitates understanding the mechanisms contributing to such events. We present a case study of the Jeddah extreme precipitation event on November 24, 2022, which caused great flooding and infrastructure damage. We also present a detailed discussion about the study's results, feedback from the domain experts, and future extensions.Attribution 4.0 International LicenseCategories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Meteorological VisualizationI.3.3 [Computer Graphics]Meteorological Visualization10.2312/envirvis.2023110325-328 pages