Climate Variability of Coastal Flooding Risk in San Francisco Bay: the Wonderful Problem
Abstract:
To address this ‘wonderful problem’, we propose a hybrid approach that combines: (a) hydrodynamic models (WWIII for waves, statistically or dynamically downscaled winds, Delft3D for high resolution tide-surge-wave modeling); (b) long-term data bases (observational and hindcast); and (c) non-linear data mining and statistical downscaling methods. At monthly scales, variability is driven by astronomic tides (perigean and nodal cycles) and the El Niño Southern Oscillation (ENSO). At a daily scale, sea level pressure fields are the predictors of wind, waves and surge levels. The statistical downscaling models are based on circulation patterns for multivariate variables (Espejo et al., 2014) and on extremes (Izaguirre et al, 2012), resulting in a time-dependent climate emulators which define the hydraulic boundary conditions for Delft3D.
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