Contract no. 4/30.08.2013, Source of funding: The Executive Unit for Financing in Higher Education, Research, Development and Innovation (UEFISCDI)

Funding amount: 621.000 lei



Project description

             DAMWAVE project aims to implement data assimilation methods to improve the wave predictions  in the nearshore of the Black Sea.

       The first component of the system proposed in the framework of the DAMWAVE project is related to the wave prediction and is based on the spectral phase averaged wave model SWAN (Simulating WAves Nearshore). This was already implemented by PL in the Black Sea. It has to be highlighted the fact that, for similar conditions, the present SWAN implementation provides in general better results than the WAM based modelling system, as shown by the comparison of the results provided by the two models with buoy data. When comparing with ocean models as WAM, the SWAN implementation in the Black Sea presents also the advantage that one single model covers the full scale of the modelling process from the deep water wave generation and towards the coast.

In the second phase, DA modules (DATA ASSIMILATION) based on the techniques mentioned below will be implemented, tested and coupled for various computational levels to the wave modelling system in the framework of the DAMWAVE project.

Assimilation techniques for the wave predictions are commonly classified in two categories: sequential methods and variational methods. The sequential methods combine all observations falling within a particular time window and update the model solution without reference to the model dynamics. The most widely adopted DA schemes are based either on instantaneous sequential procedures like Optimal Interpolation (OI), or successive corrections method (SCM), these being attractive especially due to their lower computational demands. Methods based on the Kalman Filter (KF) are multi-level in time, and they are able also to provide error statistics on the model variables. The problem of implementing these techniques arises from the dimension of the error covariance matrix and for this reason some simplifications are necessary.



“Dunărea de Jos”  University Galați

Faculty of Engineering

Galați, 111, Domneasca Street
Postal Code: 800201

Tel: 0336 130 208 Fax: 0336 130 283




Data Assimilation Methods for improving the WAVE predictions in the Romanian nearshore of the Black Sea


“Dunărea de Jos” University Galați


Faculty of Engineering

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