Sea wave modeling with X-band COSMO-SkyMed © SAR-derived wind field forcing and applications in coastal vulnerability assessment

Abstract. In this paper, X-band COSMO-SkyMed© synthetic aperture radar (SAR) wind field data are first used to force coastal wind wave modeling for both sea wave numerical simulation and coastal vulnerability assessment purposes. The SAR-based wind field retrieval is accomplished by resolving the SAR-based wind speed and wind direction retrieval problems independently. The sea surface wind speed is retrieved through the azimuth cut-off procedure, and the sea surface wind direction is determined by the multi-resolution analysis of the discrete wavelet transform. The wind wave modeling is based on the third-generation Simulating WAves Nearshore (SWAN) model, which is used for sea wave state estimation in coastal and inland regions. The coastal vulnerability assessment is provided by means of a key parameter, known as impact index, which evaluates the coastal risk due to the inundation of the inshore land. Experiments consist of SWAN numerical simulations run with respect to some relevant wave storms recorded in the southern Tyrrhenian Sea on 2010, with applications in coastal vulnerability assessment along the Sele coastal plain. Experimental results show the benefits of blended wind field products, provided by European Centre for Medium Weather Forecast (ECMWF) model winds and SAR-based wind field estimations, for both wind wave modeling and coastal vulnerability assessment purposes.

[1]  P. Bruun.  Sea-Level Rise as a Cause of Shore Erosion , 1962 .

[2]  P. Aucelli,et al.  Historical and recent changes of the Sele River coastal plain (Southern Italy): natural variations and human pressures , 2012, Rendiconti Lincei.

[3]  C. Guedes Soares,et al.  Uncertainty of Ocean Wave Hindcasts Due to Wind Modeling , 1995 .

[4]  Donald R. Thompson,et al.  Ocean wind field mapping from synthetic aperture radar and its application to research and applied problems , 2005 .

[5]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  P. Janssen.  The Interaction of Ocean Waves and Wind , 2004 .

[7]  1 WIND FIELDS RETRIEVED FROM SAR IN COMPARISON TO NUMERICAL MODELS , .

[8]  N. Booij,et al.  A third-generation wave model for coastal regions-1 , 1999 .

[9]  Guido Benassai,et al.  Introduction to Coastal Dynamics and Shoreline Protection , 2006 .

[10]  Marcos Portabella Arnús.  Wind Field Retrieval from Satellite Radar Systems , 2002 .

[11]  J. Harlan.  Short time scale effects on high frequency radar-derived current velocity measurements , 2003 .

[12]  K. L. Beach,et al.  X band microwave backscattering from ocean waves , 1995 .

[13]  Johannes Schulz-Stellenfleth,et al.  Measurement of 2-D sea surface elevation fields using complex synthetic aperture radar data , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[14]  Hilary F. Stockdon,et al.  Empirical parameterization of setup, swash, and runup , 2006 .

[15]  Implementation and Validation of Wave Watch III Model Offshore the Coastlines of Southern Italy , 2006 .

[16]  P. Vachon,et al.  Analysis of ERS-1/2 synthetic aperture radar wave mode imagettes , 1998 .

[17]  Maurizio Migliaccio,et al.  Wind speed estimation in the Tyrrhenian Sea by means of X-band COSMO-SkyMed SAR data , 2012, 2012 Tyrrhenian Workshop on Advances in Radar and Remote Sensing (TyWRRS).

[18]  Maurizio Migliaccio,et al.  An Innovative Technique for Postprocessing Descalloping , 2013, IEEE Geoscience and Remote Sensing Letters.

[19]  G. Perillo,et al.  Vulnerability to Sea-Level Rise on the Coast of the Buenos Aires Province , 2007 .

[20]  Robert G. Dean,et al.  Convolution Method for Time-Dependent Beach-Profile Response , 1993 .

[21]  G..  A Theory for Multiresolution Signal Decomposition : The Wavelet Representation , 2004 .

[22]  Ola M. Johannessen,et al.  Coastal wind field retrievals from ERS synthetic aperture radar images , 1998 .

[23]  Paris W. Vachon,et al.  Wind direction estimation from SAR images of the ocean using wavelet analysis , 2002 .

[24]  M. Migliaccio,et al.  X-band Azimuth cut-off for wind speed retrieval by means of COSMO-SkyMed SAR data , 2012, 2012 IEEE/OES Baltic International Symposium (BALTIC).

[25]  N. Booij,et al.  A Spectral Wave Model for the Coastal Zone , 1994 .

[26]  N. Booij,et al.  A third‐generation wave model for coastal regions: 2. Verification , 1999 .

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

[28]  T. Barnett,et al.  Measurements of wind-wave growth and swell decay during the Joint North Sea Wave Project (JONSWAP) , 1973 .

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

[30]  G. Evensen,et al.  Satellite earth observation in operational oceanography , 2000 .

[31]  Xiaofeng Li,et al.  Comparison of Ocean Surface Winds From ENVISAT ASAR, MetOp ASCAT Scatterometer, Buoy Measurements, and NOGAPS Model , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[32]  Jochen Horstmann,et al.  High resolution wind fields retrieved from SAR in comparison to numerical models , 2002, IEEE International Geoscience and Remote Sensing Symposium.

[33]  The Propagation of Wind Errors Through Ocean Wave Hindcasts , 1996 .

[34]  L. Chambers.  Linear and Nonlinear Waves , 2000, The Mathematical Gazette.

[35]  T. Carter,et al.  IPCC technical guidelines for assessing climate change impacts and adaptations : part of the IPCC special report to the first session of the conference of the parties to the UN framework convention on climate change , 1994 .