Towards a Multi-scale Montecarlo Climate Emulator for Coastal Flooding and Long-Term Coastal Change Modeling: The Beautiful Problem
Ana Rueda1, Jose A.A. Antolinez1, Christie Hegermiller2, Katherine Serafin3, Dylan Lawrence Anderson4, Peter Ruggiero4, Patrick Barnard5, Li H Erikson6, Sean Vitousek7, Paula Camus8, Antonio Tomas8, Mauricio Gonzalez8 and Fernando J. Mendez1, (1)University of Cantabria, Ciencias y Tecnicas del Agua y del Medio Ambiente, Santander, Spain, (2)University of California Santa Cruz, Santa Cruz, CA, United States, (3)Oregon State University, College of Earth, Ocean, and Atmospheric Sciences, Corvallis, OR, United States, (4)Oregon State University, Corvallis, OR, United States, (5)USGS California Water Science Center San Diego, San Diego, CA, United States, (6)USGS Pacific Science Ctr, Santa Cruz, CA, United States, (7)Stanford University, Stanford, CA, United States, (8)Environmental Hydraulics Institute, Universidad de Cantabria, Santander, Spain
Abstract:
Long-term coastal evolution and coastal flooding hazards are the result of the non-linear interaction of multiple oceanographic, hydrological, geological and meteorological forcings (e.g., astronomical tide, monthly mean sea level, large-scale storm surge, dynamic wave set-up, shoreline evolution, backshore erosion). Additionally, interannual variability and trends in storminess and sea level rise are climate drivers that must be considered. Moreover, the chronology of the hydraulic boundary conditions plays an important role since a collection of consecutive minor storm events can have more impact than the 100-yr return level event. Therefore, proper modeling of shoreline erosion, beach recovery and coastal flooding should consider the sequence of storms, the multivariate nature of the hydrodynamic forcings, and the different time scales of interest (seasonality, interannual and decadal variability).
To address this ‘beautiful problem’, we propose a hybrid approach that combines: (a) numerical hydrodynamic and morphodynamic models (SWAN for wave transformation, a shoreline change model, X-Beach for modeling infragravity waves and erosion of the backshore during extreme events and RFSM-EDA (Jamieson et al, 2012) for high resolution flooding of the coastal hinterland); (b) long-term data bases (observational and hindcast) of sea state parameters, astronomical tides and non-tidal residuals; and (c) statistical downscaling techniques, non-linear data mining, and extreme value models.
The statistical downscaling approaches for multivariate variables are based on circulation patterns (Espejo et al., 2014), the chronology of the circulation patterns (Guanche et al, 2013) and the event hydrographs of multivariate extremes, resulting in a time-dependent climate emulator of hydraulic boundary conditions for coupled simulations of the coastal change and flooding models.
References
Espejo et al (2014) Spectral ocean wave climate variability based on circulation patterns, J Phys Oc, doi: 10.1175/JPO-D-13-0276.1
Guanche et al (2013) Autoregressive logistic regression applied to atmospheric circulation patterns, Clim Dyn, doi: 10.1007/s00382-013-1690-3
Jamieson et al (2012) A highly efficient 2D flood model with sub-element topography, Proc. Of the Inst Civil Eng., 165(10), 581-595
