Pc. Mcintosh et Rb. Schahinger, COASTAL-TRAPPED WAVE MODE FITTING - REANALYSIS OF THE AUSTRALIAN COASTAL EXPERIMENT, Journal of physical oceanography, 24(5), 1994, pp. 949-965
The original time domain analysis of data from the Australian Coastal
Experiment involved fitting coastal-trapped wave modes to an array of
velocity time series using a truncated singular value decomposition. W
hile the truncation was necessary for noise reduction, it is shown tha
t important information concerning the separation of mode 1 and mode 2
was discarded. A weighted least-squares mode-fitting technique is int
roduced that uses the data to estimate both the signal-to-noise ratio
and the relative weighting of the fitted modes. In addition, the veloc
ity data are augmented by sea-level data. Findings from the present an
alysis differ in several important respects from the original results.
It is found that mode 1 has approximately twice the energy flux of mo
de 2 and that mode 3 is statistically insignificant at the southern en
d of the East Australian waveguide. In addition, mode 1 is not highly
correlated with mode 2. These differences are primarily due to changes
in mode 1; mode 2 remains essentially unchanged from the original ana
lysis. These revised modes, when used as boundary conditions to a wind
-forced coastal-trapped wave model that predicts velocity and sea leve
l along the coast, lead to a small but significant increase in predict
ion skill over the original modes. The reanalysis raises questions reg
arding the energy source for the coastal-trapped wave modes. The diffe
rence between the original and present analyses is reduced by the incl
usion of sea-level data. The ability of the instrument array to resolv
e coastal-trapped wave modes is discussed, and the problems associated
with nonorthogonality of the theoretical modal structures as sampled
by the array are highlighted. It is noted that the small number of deg
rees of freedom in the data leads to 95% confidence limits on modal en
ergy fluxes that are as large as 69% of the estimated values.