No abstract

No abstract

To address questions concerning the intensity and spatial structure of the 3-dimensional circulation within the Pacific Ocean and the associated advective and diffusive property flux divergences, data from approximately 3000 high-quality hydrographic stations collected on 40 zonal and meridional cruises have been merged into a physically consistent model. The majority of the stations were occupied as part of the World Ocean Circulation Experiment (WOCE), which took place in the 1990s. These data are supplemented by a few pre-WOCE surveys of similar quality, and time-averaged direct-velocity and historical hydrographic measurements about the equator. An inverse box model formalism is employed to estimate the absolute along-isopycnal velocity field, the magnitude and spatial distribution of the associated diapycnal flow and the corresponding diapycnal advective and diffusive property flux divergences. The resulting large-scale WOCE Pacific circulation can be described as two shallow overturning cells at mid-to low latitudes, one in each hemisphere, and a single deep cell which brings abyssal waters from the Southern Ocean into the Pacific where they upwell across isopycnals and are returned south as deep waters. Upwelling is seen to occur throughout most of the basin with generally larger dianeutral transport and greater mixing occurring at depth. The derived pattern of ocean heat transport divergence is compared to published results based on air-sea flux estimates. The synthesis suggests a strongly east/west oriented pattern of air-sea heat flux with heat loss to the atmosphere throughout most of the western basins, and a gain of heat throughout the tropics extending poleward through the eastern basins.

No abstract

Accurate short-term prediction of surface currents can improve efficiency of search-and-rescue operations, oil-spill response, and marine operations. We developed a linear statistical model for predicting surface currents (up to 48 hours in the future) based on a short time-history of past HF-radar observations (past 48 hours) and an optional forecast of surface winds. Our model used empirical orthogonal functions (EOFs) to capture spatial correlations in the HF-radar data and used a linear autoregression model to predict the temporal dynamics of the EOF coefficients. We tested the developed statistical model using historical observations of surface currents in Monterey Bay, California. The predicted particle trajectories separated from particles advected with HF-radar data at a rate of 4.4 km/day, which represents an improvement over the existing statistical model (drifter separation of 5.5 km/day). We found that the minimal length of the HF-radar data required to train an accurate statistical model was between one and two years, depending on the accuracy desired.