DEVELOPMENT OF AN INVERSE ESTIMATION METHOD OF SEA SURFACE DRAG COEFFICIENT UNDER STRONG WIND CONDITIONS

Masaki Yokota, Noriaki Hashimoto, Koji Kawaguchi, Hiroyasu Kawai

Abstract


For the purpose of clarifying the mechanism of energy transfer from high wind to waves, the ADWAM, a wave prediction model incorporating the data assimilation method, was modified to deduce the sea surface drag coefficients as its control variables. Validity of the model was verified through the identical twin experiment in deep sea conditions. Also, the behavior of the deduced parameter was examined through several experiments. As a result, it was confirmed that the drag coefficient deduced by the model is accurate enough when the number of the given observation data is sufficient compared with the number of the unknown parameter. It was also confirmed that the accuracy of the deduced coefficient can be improved by adding an a priori condition even if the number of the observation data is insufficient.

Keywords


sea surface drag coefficient; data assimilation; adjoint WAM

References


Andreas E. L.:An algorithm to predict the turbulent air-sea fluxes in high-wind, spray conditions, 12th Conf. on interaction of sea and atmosphere, CD-ROM, 3.4.

Giering, R. 1995. The Adjoint Model Compiler, MPI report.

Hersbach, H.(1998):Application of the adjoint of the WAM model to inverse wave modeling, J. Geophys. Res. Vol.103,(C5), pp.10469-10487. http://dx.doi.org/10.1029/97JC03554

Powell, M.D., Vickery, P.J and T.A. Reinhold (2003): Reduced drag coefficient for high wind speeds in tropical cyclones, Nature, 422, pp.279-283 PMid:12646913 http://dx.doi.org/10.1038/nature01481

Hashimoto, N and K. Matsuura,Evaluation of cost function in wave data assimilation with WAM Proc. 6th Int. Conf. Hydrodynamics VI, Theory and applications,pp.199-204.,2004.01.

Hashimoto, N., K. Matsuura, T. Nagai, H. Kawai. 2007. Application of Adjoint WAM to NOWPHAS Wave Observation Network for Establishment of Reasonable Observation Network, Proc. 30th Int.

Conf. Coastal Eng. 'Coastal Engineering 2006',Vol.1, 565-577.

Hashimoto, N., K. Matsuura, H. Kawai, Attempt for Accuracy Improvement of Wave Hindcasting /

Forecasting in Coastal Sea and Inner Sea by Data Assimilation, Proc. 31th Int. Conf. Coastal Eng. 'Coastal Engineering 2008',2009.05

Hersbach H. and Janssen P.A.E.M. 1999. Improvement of the Short Fetch Behavior in the WAM model, J. Atmos. Ocean. Techn., 16, pp.884-892. http://dx.doi.org/10.1175/1520-0426(1999)016<0884:IOTSFB>2.0.CO;2

Holthuijsen, L. H. et at. 2000. SWAN Cycle III version 40.11, USER MANUAL, Delft University of Technology, 124p.

Hsiao, S. V. and Shemdin, O.H. 1983. Measurements of wind velocity and pressure with a wave follower during MARSEN, J. Geophys. Res., 88(C14), 9841-9849. http://dx.doi.org/10.1029/JC088iC14p09841

Janssen P. E. A. M. 1991. Quasi-linear theory of wind-wave generation applied to wave forecasting, J. Physical Oceanography, 21, 1631-1642. http://dx.doi.org/10.1175/1520-0485(1991)021<1631:QLTOWW>2.0.CO;2

Kobayashi T., Adachi T. and Yasuda T. 2003. Estimation of Wave Fields with Open Boundaries by Ap-plying an Adjoint Model, Asian Pacific Coasts 2003, 8p.

Komen, G. J. et al. 1994. Dynamics and Modelling of Ocean Waves. Cambridge University Press, 532p. 1994.

Mitsuyasu, H. and T. Honda, 1982. Wind-induced growth of water waves, J. Fluid Mech., 123, 425-442. http://dx.doi.org/10.1017/S0022112082003139

NOAA/NWS/NCEP/OMB technical note 166, 110p.

Tolmann, H. L.1999. User manual and system documentation of WAVEWATCH-III Version 1.18, The WAMDI Group (13 Authors). 1988. The WAM model-A third generation ocean wave prediction model, J. Phys. Oceanogr., 18, pp.1378-1391.

Zhang, W., W. Perrie. and W. Li, 2006. Impacts of Waves and Sea Spray on Midlatitude Storm Structure and Intensity, Monthly Weather Review, 2006 American Meteorological Society,Vol. 134, 2418-2442.


Full Text: PDF

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.