We analyze high-resolution (1 km) simulations of the western Pacific, Gulf of Mexico, and Arabian Sea to understand submesoscale eddy dynamics. A mask based on the Okubo–Weiss parameter isolates small-scale eddies, and we further classify those with |ζ/f| ≥ 1 as being submesoscale eddies. Cyclonic submesoscale eddies exhibit a vertical depth structure in which temperature anomalies from the large-scale background are negative. Peak density anomalies associated with cyclonic submesoscale eddies are found at a depth approximately twice the mixed layer depth (MLD). Within anticyclonic submesoscale eddies, temperature anomalies are positive and have peak density anomalies at the MLD. The depth–depth covariance structure for the cyclonic and anticyclonic submesoscale eddies have maxima over a shallow region near the surface and weak off diagonal elements. The observed vertical structure suggests that submesoscale eddies have a shallower depth profile and smaller vertical correlation scales when compared to the mesoscale phenomenon. We test a two-dimensional submesoscale eddy dynamical balance. Compared to a geostrophic dynamical balance using only pressure gradient and Coriolis force, including velocity tendency and advection produces lower errors by about 20%. In regions with strong tides and associated internal waves (western Pacific and Arabian Sea), using the mixed layer integrated small-scale steric height within the dynamical equations produces the lowest magnitude errors. In areas with weak tides (Gulf of Mexico), using small-scale sea surface height (SSH) produces the lowest magnitude errors. Recovering a submesoscale eddy with the correct magnitude and rotation requires integration of small-scale specific volume anomalies well below the mixed layer.

The synergistic effects of evaporation (E), precipitation (P), and Ekman transport make the Salinity Processes in the Upper Ocean Regional Study (SPURS-1) region in the subtropical North Atlantic (15–30°N, 30–45°W) the natural location for the world's highest open ocean SSS maximum. Using the MERRA and ERA-Interim atmospheric reanalyses, we reproduce the mean hydrologic state of the atmosphere over the SPURS-1 region since 1979 and roughly deduce the change in salinity across the meridional domain due solely to interactions between E-P and Ekman transport. Our findings suggest a region that is highly evaporative at a mean rate of 4.87 mm/d with a standard deviation of 1.2 mm/d and little seasonality. Precipitation is much more variable with an annual fall maximum around 3 mm/d but only a mean rate of 1.37 mm/d with a standard deviation of 1.46 mm/d. The resulting E-P variable has a mean rate of 3.50 mm/d with a standard deviation of 1.92 mm/d and matches well with the moisture flux divergence term although the former is typically larger by a small margin. Strong prevailing easterly trade winds generate northward Ekman transports that advect water toward the salinity maximum around 25°N. A short calculation shows that atmospheric moisture dynamics could potentially account for about one third of the change in salinity between 15°N and 25°N giving an estimate of the role that surface freshwater flux plays in the maintenance of the salinity maximum.

Wide-swath satellite altimeter observations are contaminated by errors caused by the uncertainties in the geometry and orientation of the on-board interferometer. These errors are strongly correlated across the track, while also having similar error structures in the along-track direction. We describe a method for modifying the geometric component of the error covariance matrix which facilitates accuracy in the removal of the respective error modes from the signal and improves computational efficiency of the data assimilation schemes involving wide-swath altimeter observations. The method has been tested using the Surface Water and Ocean Topography simulator. We show substantial computer cost savings in the pseudo-inversion of the respective error covariance matrix. This efficiency improvement comes with a few per cent error in the approximation of the original covariance model simulating uncertainties in the geometry and orientation of the on-board interferometer.