Wind stress curl patterns over the north Pacific, between 3 ø and 55øN, are calculated from the Comprehensive Ocean-Atmosphere Data Set (COADS). The mean wind stress curl pattern consists of a basin-wide band of negative curl south of about 30øN and a basin-wide band of positive curl to the north. Most of the variance lies in the northern half of the domain, associated with variability in the Aleutian low during winter. The dominant modes of variability are associated with the changes in position and intensity of the Aleutian low and the north Pacific (subtropical) high, each of which extends across the basin, the former in winter and the latter in summer. The seasonal signal accounts for about 40% of the variability in the region of the Aleutian low, about 30% of the variability in the northeast of the basin, and about 60% of the variability in the southwest of the basin between 20 ø and 30øN. The seasonal signal and first three nonseasonal empirical orthogonal functions (eofs) account for about 60% of the total variability in the mid-latitude interior Pacific. The first eof represents variations in intensity of the Aleutian low, the second eof represents changes in intensity of the subtropical high and in the latitudinal position of the Aleutian low, and the third eof represents changes in the longitudinal position and orientation of the low. These three eofs together account for about 30% of the nonseasonal variability. On an interannual time scale, a negative (positive) wind stress curl anomaly in winter in the northeast often coincides with a positive (negative) SST anomaly in that region, although the relationship is far from perfect because of the importance of other mechanisms which influence SST variability. There is no distinct relationship between E1 Nino-southern oscillation events and wind stress curl anomalies, although weak E1 Ninos seem to coincide with a positive wind stress curl anomaly across the central north Pacific. most of the variance in each of their eofs is contained in the annual and semiannual periods.Here the wind stress curl variability over the north Pacific is investigated using COADS. Previous analyses of atmospheric variability over the north Pacific have used sea level pressure data. The seasonal and interannual variability inferred from COADS is in good agreement with these other analyses which are briefly summarized in section 2. A discussion of the wind stress data set and curl calculation is given in section 3; the seasonal signal and eofs calculated from the nonseasonal curl anomaly are discussed in section 4.The climatology of surface pressure over the north Pacific is dominated by the Aleutian low during winter and the sub-5O69

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The influence of mesoscale and seasonal ocean variability on three-dimensional acoustic ray paths from Heard Island through the Southern and Pacific Oceans to the California coast is investigated. For the simulation of these global acoustic ray paths, a three-dimensional Hamiltonian ray-tracing code was used. The input sound-speed fields to the acoustic ray model were interpolated from gridded temperature and salinity output data from the Semtner–Chervin eddy-resolving, global, general circulation model. The ray-tracing results have provided input to experimental planners for receiver placement off the California coast in the Heard Island Feasibility Test and shed light on the variability of the acoustic paths, insonified locations, arrival azimuthal angles, and travel times.

The optimization method proposed in this paper is for determining open boundary conditions from interior observations. Unknown open boundary conditions are represented by an open boundary parameter vector (B), while known interior observational values are used to form an observation vector (O). For a hypothetical B* (generally taken as the zero vector for the first time step and as the optimally determined B at the previous time step afterward), the numerical ocean model is integrated to obtain solutions (S*) at interior observation points. The root-mean-square difference between S* and O might not be minimal. The authors change B* with different increments ␦B. Optimization is used to get the best B by minimizing the error between O and S.The proposed optimization method can be easily incorporated into any ocean models, whether linear or nonlinear, reversible or irreversible, etc. Applying this method to a primitive equation model with turbulent mixing processes such as the Princeton Ocean Model (POM), an important procedure is to smooth the open boundary parameter vector. If smoothing is not used, POM can only be integrated within a finite period (45 days in this case). If smoothing is used, the model is computationally stable. Furthermore, this optimization method performed well when random noise was added to the ''observational'' points. This indicates that realtime data can be used to inverse the unknown open boundary values.

In support of the Heard Island experimental effort, the influence of mesoscale and seasonal ocean variability on three-dimensional acoustic ray paths from Heard Island through the Indian and Pacific Oceans to the California coast is investigated. For the simulation of these global acoustic ray paths, a three-dimensional Hamiltonian ray tracing code is used. The input sound-speed fields to the acoustic ray model are interpolated from gridded temperature and salinity output data from the Semtner–Chervin eddy-resolving, global, general circulation model. A previous ray analysis was conducted using ocean fields containing only the mesoscale variability. This analysis provided input to experimental planners for receiver placement off the California coast [C. S. Chiu and A. J. Semtner, J. Acoust. Soc. Am. Suppl. 1 88, S92–S93 (1990)]. Here, a new analysis is presented that includes the acoustic effects of ocean seasonal cycles. In particular, the variability of the paths, arrival azimuthal angles, and travel times are discussed.