2.1 Integrated prediction of heavy rainfall and flood events with WRF-Hydro

Gochis, David, Wei Yu, National Center for Atmospheric Research, Antonio Parodi, Elisabetta Fiori, Fondazione Centro Internazionale in Monitoraggio Ambientale, Italy

Prediction of heavy rainfall and flash flooding remains as a critical hydrometeorological challenge and require improved understanding of the linkages between atmospheric and land surface processes. Obviously flood prediction skill is intrinsically liked to quantitative precipitation forecast skill, which emphasizes the need to produce mesoscale predictions of high fidelity. However, in many cases land surface parameters can also exert significant control on the runoff response to heavy rainfall and on the formation or localization of heavy rainfall as well. Factors impeding the advancement of flood forecasting skill at the 0-12 hour timeframe are explored in the context of predicting mountain front flood events from the Continental U.S. and the northern Mediterranean coastline. Using the coupled WRF/WRF-Hydro system we present a paired study analysis of flood events from these regions. Our analysis focuses on quantifying the respective roles of model initialization, model physics selections and the selection of land surface parameters which influence heavy rainfall and runoff responses. The results of this study to date strongly suggest that an integrated land surface-atmosphere data assimilation approach is required to maximize predictive skill from models.