Nearshore assessment of wave energy resources in central Chile (2009–2010)

The goal of this work is to estimate nearshore wave energy resources in central Chile with high spatial resolution. Due to the lack of in situ measurements a suite of numerical models are used to assess the wave energy between 2009 and 2010. We compare the effects of different wind forcing reanalysis, particularly CFSR and ERA-Interim, and physics parametrizations on numerical simulations of the nearshore wave energy fluxes near Valparaiso (33°S), central Chile. For this we utilize WAVEWATCH III®, an open source community spectral wave model, configured with a high resolution unstructured grid (200–400 m at the coast). Our results show a difference of 3 kW/m in wave power estimations when using different wind reanalysis, and less a difference of less than 0.5 kW/m when adding the triad wave interactions term. Statistical indicators calculated using buoy and altimeter data for comparison favor the use of ERA-Interim winds and including triad wave interactions. For the Valparaiso region, the area south of Punta Curaumilla was confirmed as a hot spot of wave energy (4–5 MW/yr), with the most energetic and frequent sea state described by Te of 9–11 s and H_s 2.5–3.5 m.

[1]  Justin E. Stopa,et al.  Assessment of wave energy resources in Hawaii , 2011 .

[2]  Gregorio Iglesias,et al.  Wave energy and nearshore hot spots: The case of the SE Bay of Biscay , 2010 .

[3]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

[4]  Kester Gunn,et al.  Quantifying the global wave power resource , 2012 .

[5]  Justin E. Stopa,et al.  Patterns and cycles in the Climate Forecast System Reanalysis wind and wave data , 2013 .

[6]  M. Gómez-Gesteira,et al.  Sensitivity of the SWAN model in a local application to the Artabro Gulf (NW Spain) , 2003 .

[7]  E. Rogers,et al.  Semi-empirical dissipation source functions for ocean waves: Part I, definition, calibration and validation. Fabrice ArdhuinJean-Francois Filipot and Rudy Magne Service Hydrographique et Oceanographique de la Marine, Brest, France , 2010 .

[8]  Uang,et al.  The NCEP Climate Forecast System Reanalysis , 2010 .

[9]  E. Rogers,et al.  Semiempirical Dissipation Source Functions for Ocean Waves. Part I: Definition, Calibration, and Validation , 2009, 0907.4240.

[10]  Bradley J. Buckham,et al.  Wave energy resources near Hot Springs Cove, Canada , 2014 .

[11]  William C. Skamarock,et al.  A time-split nonhydrostatic atmospheric model for weather research and forecasting applications , 2008, J. Comput. Phys..

[12]  Herman Deconinck,et al.  A Conservative Formulation of the Multidimensional Upwind Residual Distribution Schemes for General Nonlinear Conservation Laws , 2002 .

[13]  R. Tomlinson,et al.  Comparison of two wave models for Gold Coast, Australia , 2007 .

[14]  G. Galanis,et al.  The impact of sea surface currents in wave power potential modeling , 2015, Ocean Dynamics.

[15]  Hendrik L. Tolman,et al.  A Third-Generation Model for Wind Waves on Slowly Varying, Unsteady, and Inhomogeneous Depths and Currents , 1991 .

[16]  Laurence D. Mann,et al.  Application of Ocean Observations & Analysis: The CETO Wave Energy Project , 2011 .

[17]  Gregorio Iglesias,et al.  Offshore and inshore wave energy assessment: Asturias (N Spain) , 2010 .

[18]  Doug Scott,et al.  Evaluation of the Potential of Wave Energy in Chile , 2008 .

[19]  P. Mota,et al.  Wave energy potential along the western Portuguese coast , 2014 .

[20]  Bradley J. Buckham,et al.  Characterizing the near shore wave energy resource on the west coast of Vancouver Island, Canada , 2014 .

[21]  J. Stopa,et al.  Intercomparison of wind and wave data from the ECMWF Reanalysis Interim and the NCEP Climate Forecast System Reanalysis , 2014 .

[22]  J. Bidlot,et al.  User manual and system documentation of WAVEWATCH III R version 4.18 , 2014 .

[23]  Fabrice Ardhuin,et al.  A global wave parameter database for geophysical applications. Part 2: Model validation with improved source term parameterization , 2013 .

[24]  P. Queffeulou Long-Term Validation of Wave Height Measurements from Altimeters , 2004 .

[25]  C. Guedes Soares,et al.  Numerical modelling to estimate the spatial distribution of the wave energy in the Portuguese nearshore , 2009 .

[26]  S. Neill,et al.  Realistic wave conditions and their influence on quantifying the tidal stream energy resource , 2014 .

[27]  Fabrice Ardhuin,et al.  Assessment of SARAL/AltiKa Wave Height Measurements Relative to Buoy, Jason-2, and Cryosat-2 Data , 2015 .

[28]  Walter H. F. Smith,et al.  A global, self‐consistent, hierarchical, high‐resolution shoreline database , 1996 .

[29]  F. Ardhuin,et al.  On the developments of spectral wave models: numerics and parameterizations for the coastal ocean , 2014, Ocean Dynamics.

[30]  C. Martínez,et al.  Historical changes in the shoreline and littoral processes on a headland bay beach in central Chile , 2011 .