Abstract

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.

Abstract

The salinity distribution in the South China Sea (SCS) has a pronounced subsurface maximum from 150–220 m throughout the year. This feature can only be maintained by the existence of a mean flow through the SCS, consisting of a net inflow of salty North Pacific tropical water through the Luzon Strait and outflow through the Mindoro, Karimata, and Taiwan Straits. Using an inverse modeling approach, the authors show that the magnitude and space–time variations of the SCS thermohaline structure, particularly for the salinity maximum, allow a quantitative estimate of the SCS throughflow and its distribution among the three outflow straits. Results from the inversion are compared with available observations and output from a 50-yr simulation of a highly resolved ocean general circulation model.

The annual-mean Luzon Strait transport is found to be 2.4 ± 0.6 Sv (Sv ≡ 10⁶ m³ s⁻¹). This inflow is balanced by the outflows from the Karimata (0.3 ± 0.5 Sv), Mindoro (1.5 ± 0.4), and Taiwan (0.6 ± 0.5 Sv) Straits. Results of the inversion suggest that the Karimata transport tends to be overestimated in numerical models. The Mindoro Strait provides the only passage from the SCS deeper than 100 m, and half of the SCS throughflow (1.2 ± 0.3 Sv) exits the basin below 100 m in the Mindoro Strait, a result that is consistent with a climatological run of a 0.1° global ocean general circulation model.

Abstract

Sea ice models that allow for deformation are primarily based on rheological formulations originally developed in the 1970s. In both the original viscoplastic (VP) and elastic-VP schemes, the internal pressure term is modeled as a function of variable sea ice thickness and concentration with spatially and temporally constant empirical parameters for ice strength. This work considers a spatially variable extension of the rheology parameters as well as wind stress in a one-dimensional VP sea ice data assimilation system. In regions of total ice cover, experiments that assimilate synthetic ice-state observations using variable rheological parameters show larger improvements than equivalent experiments using homogeneous parameters. For partially ice-covered regions where internal ice stresses are relatively unimportant, experiments assimilating synthetic sea ice velocity observations demonstrate reasonable reconstruction of spatially variable wind stresses. These results suggest practical benefits for sea ice–state reconstruction and forecasts by using sea ice velocity, thickness, and concentration observations to optimize spatially varying rheological parameters and to improve wind stress forcing.

Abstract

Monitoring surface currents by coastal high-frequency radars (HFRs) is a cost-effective observational technique with good prospects for further development. An important issue in improving the efficiency of HFR systems is the optimization of radar positions on the coastline. Besides being constrained by environmental and logistic factors, such optimization has to account for prior knowledge of local circulation and the target quantities (such as transports through certain key sections) with respect to which the radar positions are to be optimized.

In the proposed methodology, prior information of the regional circulation is specified by the solution of the 4D variational assimilation problem, where the available climatological data in the Bering Strait (BS) region are synthesized with dynamical constraints of a numerical model. The optimal HFR placement problem is solved by maximizing the reduction of a posteriori error in the mass, heat, and salt (MHS) transports through the target sections in the region. It is shown that the MHS transports into the Arctic and their redistribution within the Chukchi Sea are best monitored by placing HFRs at Cape Prince of Wales and on Little Diomede Island. Another equally efficient configuration involves placement of the second radar at Sinuk (western Alaska) in place of Diomede. Computations show that 1) optimization of the HFR deployment yields a significant (1.3–3 times) reduction of the transport errors compared to nonoptimal positioning of the radars and 2) error reduction provided by two HFRs is an order of magnitude better than the one obtained from three moorings permanently maintained in the region for the last 5 yr. This result shows a significant advantage of BS monitoring by HFRs compared to the more traditional technique of in situ moored observations. The obtained results are validated by an extensive set of observing system simulation experiments.

Abstract

The Luzon Strait transport (LST) from the Pacific into the South China Sea (SCS) is examined using results from a high-resolution ocean general circulation model. The LST from the model has a mean value of 2.4 Sv (Sv ≡ 10⁶ m³ s⁻¹) and reaches its seasonal maximum (6.1 Sv westward) in winter and seasonal minimum (0.9 Sv eastward) in summer. Both the annual mean and seasonal variation of LST compare favorably with earlier observations. On an interannual time scale, LST tends to be higher during El Niño years and lower during La Niña years, with its maximum (minimum) leading the mature phase of El Niño (La Niña) by 1 month. The interannual variation of LST appears to be oppositely phased with the Kuroshio transport east of Luzon, indicating a possible nonlinear hysteresis of the Kuroshio as a driving mechanism of LST. For the annual average, water leaving the SCS in the south is of higher temperature than that with LST, thus producing a cooling advection in the upper 405 m equivalent to a surface heat flux of −19 W m⁻². Most of this cooling advection is balanced by the atmospheric heating (17 W m⁻²). From late spring to early fall, surface heat flux is the primary heating process; only a small part of the heat content change can be explained by heat advection. But, in winter, heat advection seems to be the only important process responsible for the cooling in the upper layer of the SCS. The interannual variation of the upper-layer heat content has a strong signature of ENSO, cooling in the development of El Niño and warming in the development of La Niña. An oceanic connection is revealed, in which LST seems to be a key process conveying the impact of the Pacific ENSO into the SCS.