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Incorporating Hurricane Forecasts into WRF-Hydro for Ensemble Generation
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  • Wen-Ying Wu,
  • Zong-Liang Yang,
  • Brent Austgen,
  • Sabiha Tabassum,
  • Erhan Kutanoglu,
  • John Hasenbein,
  • Carey King,
  • Surya Santoso
Wen-Ying Wu
University of Texas at Austin, University of Texas at Austin

Corresponding Author:[email protected]

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Zong-Liang Yang
Univ Texas Austin, Univ Texas Austin
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Brent Austgen
The University of Texas at Austin, The University of Texas at Austin
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Sabiha Tabassum
University of Texas at Austin, University of Texas at Austin
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Erhan Kutanoglu
The University of Texas at Austin, The University of Texas at Austin
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John Hasenbein
University of Texas at Austin, University of Texas at Austin
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Carey King
University of Texas at Austin, University of Texas at Austin
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Surya Santoso
University of Texas at Austin, University of Texas at Austin
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Abstract

Hurricanes bring heavy rain and induce catastrophic flooding. The damage and fatalities underscore the urgency for understanding and improving the hydrological forecasts. Here we build an integrated hydrological framework in support of decision making, specifically for heavy rainfall caused by tropical storms. We apply different ensemble approaches for short-lived tropical storms (e.g., Tropical Storm Imelda) and long-lasting and major hurricanes (e.g., Hurricane Harvey). To drive the WRF-Hydro/National Water Model (NWM), atmospheric inputs are derived from the dynamical ensemble prediction based on Hurricane Weather Research and Forecasting (HWRF) for Hurricane Harvey. For short-lived tropical storms, which do not have operational hurricane forecast from regional dynamical models, we manually generate an ensemble forecast from a deterministic weather forecast from the Global Forecast System (GFS) and perturb the precipitation intensity and location according to the new runs from the High-Resolution Rapid Refresh (HRRR). On top of the current operational forecast from NWM, both of our approaches generate more than 20 separate forecasts (ensemble members) to address uncertainties in atmospheric dynamics, specifically for tropical storms and hurricanes. We evaluate the storm track, precipitation, and streamflow over the hurricane-prone areas of Texas. By linking ensemble weather forecasts to hydrological forecasts, we seek to provide a more comprehensive understanding of the underlying models and support advanced research on flood resilience for critical infrastructures.