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Predictability of Compound Impacts From Hurricane Helene and Predecessor Rain Event in CFSv2 Operational Forecasts

  • Wei Ching Hsu
  • , Gabriel J. Kooperman
  • , Kevin A. Reed
  • , J. Marshall Shepherd
  • University of Georgia

Research output: Contribution to journalLetterpeer-review

Abstract

In late September 2024, Hurricane Helene contributed to catastrophic flooding in the Southeastern United States. The impacts of the hurricane were compounded by a predecessor rain event (PRE) 1-day earlier, inducing unusually high precipitation and soil moisture (SM). In this case study, we examined the predictability of precipitation and SM conditions associated with these events in NOAA's operation Coupled Forecast System model (CFSv2). Specifically, we investigated the predictability of Helene and the PRE as a function forecast lead time (LT). To assess the model's ability to represent both Helene and PRE, as well as the predictability of their resulting precipitation and SM, we applied tracking of both systems with different LTs from 3 to 6 days. Our results show that the predictability drops around 4- to 5-day LTs, in association with biases in the timing and location of Helene and PRE, as well as underestimated precipitation associated with the PRE.

Original languageEnglish
Article numbere2025GL119139
JournalGeophysical Research Letters
Volume52
Issue number24
DOIs
StatePublished - Dec 28 2025

Keywords

  • CFSv2
  • forecasts
  • Hurricane Helene
  • precipitation
  • predecessor rain events
  • soil moisture

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