Authors: Mohamed Abdelkader – University of Iowa, Yinphan Tsang — University of Hawaiʻi at Mānoa
Title: Precipitation Frequency and Storm Analysis in Operational Hydrology
Presentation Type: Lightning Talk
Abstract: This presentation showcases a HydroLearn module developed during the January 2025 CIROH-supported HydroLearn Hackathon. Operational forecasters and hydrologists need to understand the probability and severity of extreme rainfall events to effectively communicate potential risks. Precipitation frequency, which characterizes the likelihood of rainfall events across various intensities and durations, can be leveraged in operational contexts, but its application remains challenging. This module addresses these challenges by guiding learners through the use of precipitation frequency estimates to assess rainfall severity, integrating forecast data from the High Resolution Rapid Refresh (HRRR) model. Through Python notebooks, users develop Depth-Duration-Frequency (DDF) curves from historical rainfall records, determine recurrence intervals for forecasted events, and evaluate storm severity. While the module uses Asheville, North Carolina, and Hurricane Helene as a case study, its methods are broadly applicable across scales.