GUIDE WAVE ANALYSIS AND FORECASTING - WMO

66
Significant wave height (m)
90% confidence limits
3G WAM
instead of U 5 (see Section 3.2). This has been superseded
by a new quasi-linear formulation by Janssen (1991) (see
also Komen et al., 1994) which includes the effect of the
growing waves on the mean flow. The dissipation source
function, S ds, corresponds to the form proposed by
Komen et al. (1984), in which the dissipation has been
tuned to reproduce the observed fetch-limited wave
growth and to eventually generate the fully developed
Pierson-Moskowitz spectrum. The non-linear wave
interactions, S nl, are calculated using the discrete interaction
approximation of Hasselmann et al. (1985). The
model can be used both as a deep water and a shallow
water model. Details are described by the WAMDI
Group (1988) and a comprehensive description of the
model, its physical basis, its formulation and its various
applications are given in Komen et al. (1994).
Other models may differ in the propagation
schemes used, in the method for calculating the nonlinear
source term, S nl, and in the manner in which they
deal with shallow water effects and the influence of
ocean currents on wave evolution.
GUIDE TO WAVE ANALYSIS AND FORECASTING
Day of the month with hour of the day
Figure 5.4 — A comparison of calculated and observed wave heights during Hurricane Camille (1969). At the
height of the storm the wave sensor failed (WAMDI Group, 1988)
The WAM model has shown good results in
extreme wind and wave conditions. Figure 5.4 shows a
comparison between observed significant wave heights
and significant wave heights from the WAM model
during Hurricane Camille, which occurred in the Gulf of
Mexico in 1969. The grid spacing was a 1 /4° in latitude
and longitude. The comparison shows a good performance
of the model in a complicated turning wind
situation.
The WAM model is run operationally at the
European Centre for Medium-range Weather Forecasts
(ECMWF) on a global grid with 1.5° resolution. It is
also run operationally at a number of other weather
services including the National Weather Service (USA)
and the Australian Bureau of Meteorology. Further, it
may be run at higher resolution as a nested regional
model, and once again a number of national Meteorological
Services have adopted it in this mode (see also
Table 6.2 in Chapter 6). It has also been used in wave
data assimilation studies using data from satellites (e.g.
Lionello et al., 1992).