E. Firing et al., Time-dependent island rule and its application to the time-varying North Hawaiian Ridge Current, J PHYS OCEA, 29(10), 1999, pp. 2671-2688
Since November 1988, repeated shipboard ADCP transects have been made acros
s the North Hawaiian Ridge Current (NHRC) north of Oahu. Prominent aspects
of the NHRC transport time series include 1) a shift in late 1991 from a re
latively strong and steady state to a weaker and more variable state and 2)
the absence of an annual cycle, despite the annual cycle in the wind stres
s.
A simple conceptual framework for understanding NHRC variability is provide
d by our extension of Godfrey's island rule to upper-layer flow in the baro
clinic time-dependent case. The interior ocean flow east of the islands is
viewed as the sum of Ekman transport, geostrophic adjustment to Ekman pumpi
ng, and long Rossby waves. The net interior flow normal to the offshore edg
e of the NHRC is carried around the island barrier, with the split between
northward and southward flow governed by a simple vorticity constraint invo
lving only the inflow and outflow from the interior and the wind circulatio
n around the island. The latter is of minor importance to the Hawaiian Isla
nds. The time-dependent island rule calculation does not reproduce the obse
rved time series, but it approximates the observed magnitude and character
of variability. The result is sensitive to the choice of wind product.
To improve the simulation and to investigate the importance of processes mi
ssing from the island rule, a numerical 2 1/2-layer reduced-gravity model o
f the Pacific Ocean is driven by the FSU winds. Although the modeled NHRC d
oes not match the ADCP observations in every detail, the mean transport and
some aspects of the variability are similar: the model shows the 1991 tran
sition and lacks an annual cycle. Experiments with and without temporal win
d variability near the equator show that the NHRC is governed primarily by
winds east of the Hawaiian Islands; equatorial winds have little effect. No
nlinearity is shown to be important.