Data assimilation of ocean wind waves using Neural Networks. A case study for the German Bight

Abstract A novel approach of data assimilation based on Neural Networks (NN’s) is presented and applied to wave modeling in the German Bight. The method takes advantage from the ability of NN’s to emulate models and to invert them. Combining forward and inverse model NN with the Levenberg–Marquardt algorithm provides boundary values or wind fields in agreement with measured wave integrated parameters. Synthesized HF-radar wave data are used to test the technique for two academic cases.

[1]  Assimilation of SAR Imagery in a Nearshore Spectral Wave Model , 2006 .

[2]  M. U. Altaf,et al.  Inverse Shallow-Water Flow Modeling Using Model Reduction , 2009 .

[3]  Judith Wolf,et al.  Data assimilation of partitioned HF radar wave data into Wavewatch III , 2013 .

[4]  Istvan Szunyogh,et al.  Assimilating non-local observations with a local ensemble Kalman filter , 2007 .

[5]  Piero Lionello,et al.  Assimilation of altimeter data in a global third-generation wave model , 1992 .

[6]  J. Veeramony,et al.  Optimizing spectral wave estimates with adjoint-based sensitivity maps , 2014, Ocean Dynamics.

[7]  G. Evensen.  Sequential data assimilation with a nonlinear quasi‐geostrophic model using Monte Carlo methods to forecast error statistics , 1994 .

[8]  H. Ngodock,et al.  A Variational Assimilation System for Nearshore Wave Modeling , 2013 .

[9]  Peter Jan,et al.  Particle Filtering in Geophysical Systems , 2009 .

[10]  Istvan Szunyogh,et al.  A local ensemble transform Kalman filter data assimilation system for the NCEP global model , 2008 .

[11]  M. Baldauf,et al.  Operational Convective-Scale Numerical Weather Prediction with the COSMO Model: Description and Sensitivities , 2011 .

[12]  E. Stanev,et al.  Consistency and complementarity of different coastal ocean observations: A neural network‐based analysis for the German Bight , 2011 .

[13]  F. L. Dimet,et al.  Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects , 1986 .

[14]  J. A. Battjes,et al.  ENERGY LOSS AND SET-UP DUE TO BREAKING OF RANDOM WAVES , 1978 .

[15]  Yiquan Qi,et al.  Incorporation of artificial neural networks and data assimilation techniques into a third-generation wind-wave model for wave forecasting , 2006 .

[16]  Peter A. E. M. Janssen,et al.  Improvement of the Short-Fetch Behavior in the Wave Ocean Model (WAM) , 1999 .

[17]  S. Hasselmann,et al.  Assimilation of wave spectra from pitch-and-roll buoys , 1997 .

[18]  Peter A. E. M. Janssen,et al.  Progress in ocean wave forecasting , 2008, J. Comput. Phys..

[19]  Helmut Schiller,et al.  Some neural network applications in environmental sciences. Part I: forward and inverse problems in geophysical remote measurements , 2003, Neural Networks.

[20]  J. Nazuno.  Haykin, Simon. Neural networks: A comprehensive foundation, Prentice Hall, Inc. Segunda Edición, 1999 , 2000 .

[21]  Istvan Szunyogh,et al.  Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter , 2005, physics/0511236.

[22]  Vladimir M. Krasnopolsky,et al.  Domain check for input to NN emulating an inverse model , 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

[23]  Joanna Staneva,et al.  Blending Surface Currents from HF Radar Observations and Numerical Modeling: Tidal Hindcasts and Forecasts , 2015 .

[24]  Geir Evensen,et al.  The Ensemble Kalman Filter: theoretical formulation and practical implementation , 2003 .

[25]  Helmut Schiller.  Model Inversion by Parameter Fit Using NN Emulating the Forward Model – Evaluation of Indirect Measurements , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

[26]  Helmut Schiller.  Model Inversion by Parameter Fit Using NN Emulating the Forward Model - Evaluation of Indirect Measurements , 2006, IJCNN.

[27]  Dimitri P. Solomatine,et al.  Non-linear wave data assimilation with an ANN-type wind-wave model and Ensemble Kalman Filter (EnKF) , 2010 .