School of Meteorology (Defense)

Probabilistic Flash Flood Forecasting Using a Storm-scale NWP Ensemble

Jill Hardy
OU School of Meteorology

21 July 2014, 9:00 AM

National Weather Center, Room 5600
120 David L. Boren Blvd.
University of Oklahoma
Norman, OK

Flash flooding is one of the most costly and deadly natural hazards in the US and across the globe. The loss of life and property from flash floods could be mitigated with better guidance from hydrological models, but these models have limitations. For example, they are commonly initialized using rainfall estimates derived from weather radars. This introduces a problem for forecasting flash floods because the time interval between observations of heavy rainfall and a flash flood can be on the order of minutes, particularly for small basins in urban settings. Increasing the lead time for these events is critical for protecting life and property. Therefore, this study advances the use of quantitative precipitation forecasts (QPFs) from the stormscale CAPS ensemble system into a distributed hydrological model setting to yield basin-specific, probabilistic flash flood forecasts (PFFFs).

Rainfall error characteristics of the individual QPF members are first diagnosed and quantified in terms of structure, amplitude, and location (SAL; Wernli et al., 2008). To compute the PFFFs, we considered the June 14, 2010 Oklahoma City flash flood event. A novel methodology is explained and tested, which incorporates hydrological and meteorological components to reach the final product. The hydrological component involves inputting the probability-match mean (Ebert, 2001) of the QPF ensemble into a distributed hydrological model to get simulated streamflow that can be converted to estimated return period. These return periods are compared to the catchment size of their cells to create a probability of exceedance grid. The meteorological component uses the ensemble to create a weighted neighborhood probabilistic QPF field. This new approach is shown to: 1) identify the specific basin scales within the broader regions that are forecast to be impacted by flash flooding based on cell movement, rainfall intensity, duration, and the basin’s susceptibility factors such as initial soil moisture conditions; 2) yield probabilistic information about the forecast hydrologic response; and 3) improve lead time by using stormscale NWP ensemble forecasts.

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