5.5 Skill and Spread Assessment of an Ensemble-Based Coastal and Inland Flood Forecast System

Tuesday, 14 January 2020: 11:30 AM
158 (Boston Convention and Exhibition Center)
Hoda el Safty, Stevens institute of technology, Hoboken, NJ; and P. Orton, Z. Chen, S. V. Vinogradov, J. K. Miller, R. Datla, and M. Hajj

Floods are recognized as the most damaging natural disaster with $7.96 billion per year of U.S. flood-related damages averaged over the past 30 years (NWS, 2014). The flood forecasting system at Stevens Institute of Technology has been operational since 2007, and running in an ensemble mode since 2015 (Jordi el al. 2018). The ensemble total water level forecasts are forced from regional meteorological models with more than 100 coupled hydrodynamic-hydrologic simulations reflecting uncertainty in weather forecast forcing (i.e., GFS, GEFS, CMC, ECMWF, NAM). In this study, we evaluate the central and probabilistic forecasts where model results are compared to in situ observations of water levels across the US Mid-Atlantic and Northeast. The analysis for the full ensemble is then compared to that for individual models’ ensembles to determine, if any, the advantages of using a multi-model ensemble.

Jordi, A., Georgas, N., Blumberg, A., Yin, L., Chen, Z., Wang, Y., Schulte, J., Ramaswamy, V., Runnels, D., and Saleh, F., Bull. Amer. Meteorol. Soc., 10.1175/BAMS-D-17-0309.1 2018.

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