Wednesday, 9 January 2013: 4:15 PM
Room 10A (Austin Convention Center)
On November 4th, 2011, the city of Genoa, Italy, located between the Tyrrhenian Sea and the Apennine mountains, was witness to a catastrophic flash flood. About 500 millimeters of rain, a third of the average annual rainfall, fell in approximately six hours. The waters that flooded the town center equated to an approximately 300 year flood event. Six people perished, commercial property was inundated, cars were swept away and many trees were uprooted. We analyze the performance of cloud-permitting (1 km) numerical weather prediction model simulations of the convective system responsible for this extreme event using the Advanced Research Weather and Forecasting Model (ARW-WRF, version 3.3) with its associated hydrological modeling extension (WRF-Hydro') focusing on the utility of model quantitative precipitation forecasts (QPFs) for flash flood prediction. WRF model skill is assessed with respect to specification of cloud microphysics, convection and land surface physics parameterizations. The QPF results strongly suggest an event dominated by comparatively shallow warm rain processes where local maxima were the product of both synoptic scale dynamics and orographic enhancement over the Apennine mountain range. Land and sea surface temperature forcing was assessed but found to be secondary in importance. Streamflow prediction skill from the fully coupled WRF-Hydro modeling system was compared against observations and against offline or uncoupled' hydrological model runs, driven by several quantitative precipitation estimate (QPEs) products. The results illustrate the significant sensitivity of the predicted (simulated) streamflow event to QPF (QPE) skill and emphasize the importance of taking into account many factors and sources of error in the hydrometeorological prediction chain. The end product of this study is a comprehensive evaluation and justification for optimal configurations of the WRF-Hydro modeling system for high-impact Mediterranean flood events for use in future forecasting operations.
![](images/flag.png)
![](images/blue_ribbon.png)