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This study investigated a method for creating a climatological dataset with improved reproducibility and reliability for the Southern Ocean. Despite sparse observational sampling, the Southern Ocean has a dominant physical characteristic of a strong topographic constraint formed under weak stratification and strong Coriolis effect. To increase the fidelity of gridded data, the topographic constraint is incorporated into the interpolation method, the weighting function of which includes a contribution from bottom depth differences and horizontal distances. Spatial variability of physical properties was also analyzed to estimate a realistic decorrelation scale for horizontal distance and bottom depth differences using hydrographic datasets. A new gridded dataset, the topographic constraint incorporated (TCI), was then developed for temperature, salinity, and dissolved oxygen, using the newly derived weighting function and decorrelation scales. The root-meansquare (RMS) of the difference between the interpolated values and the neighboring observed values (RMS difference) was compared among available gridded datasets. That the RMS differences are smaller for the TCI than for the previous datasets by 12%-21% and 8%-20% for potential temperature and salinity, respectively, demonstrates the effectiveness of incorporating the topographic constraint and realistic decorrelation scales. Furthermore, a comparison of decorrelation scales and an analysis of interpolation error suggests that the decorrelation scales adopted in previous gridded datasets are 2 times or more larger than realistic scales and that the overestimation would increase the interpolation error. The interpolation method proposed in this study can be applied to other high-latitude oceans, which are weakly stratified but undersampled. [ABSTRACT FROM AUTHOR]

Under the Japanese Antarctic Research Expedition (JARE) program, sea-ice thickness has been routinely monitored off Lützow–Holm Bay (East Antarctica) during the summer (mid-December to early January) since 2000/01, using an electromagnetic induction (EM) instrument onboard the icebreaker Shirase . Analysis of these data over a 10-year period, combined with visual observations using a simplified form of the ASPeCt (Antarctic Sea ice Processes and Climate) protocol, suggests a strong interannual variability in sea-ice thickness in this region. For the repeat pack-ice observation area, where the sea-ice thickness averaged over the nine seasons is ∼1.9 m, mean thicknesses of observed sea-ice in 2010/11 and 2011/12 are exceptionally large, at ∼3.3 and ∼5.8 m, respectively. This result is strongly related to regional patterns of sea ice dynamics. Ice convergence caused by anomalous northerly winds was particularly high in 2011/12, suggesting that the extremely thick ice observed in that season resulted largely from sea-ice deformation processes (including pressure ridging). Longer-term analysis of data from the past 34 years confirms that sea-ice conditions and thickness off Lützow–Holm Bay in summer are determined mainly by the large-scale pattern of atmospheric pressure in December. [ABSTRACT FROM AUTHOR]

At several locations around Antarctica, dense water is formed as a result of intense sea ice formation. When this dense water becomes sufficiently denser than the surrounding water, it descends the continental slope and forms Antarctic Bottom Water (AABW). This study presents the AABW formation off the coast of Cape Darnley [Cape Darnley Bottom Water (CDBW)] in East Antarctica, using a nonhydrostatic model. The model is forced for 8 months by a temporally uniform surface salt flux (because of sea ice formation) estimated from Advanced Microwave Scanning Radiometer for Earth Observing System (EOS; AMSR-E) data and a heat budget calculation. The authors reproduce AABW formation and associated periodic downslope flows of dense water. Descending pathways of dense water are largely determined by the topography; most dense water flows into depressions on the continental shelf, advects onto the continental slope, and is steered downslope to greater depths by the canyons. Intense sea ice formation is the most important factor in the formation of AABW off Cape Darnley, and the existence of depressions is of only minor importance for the flux of CDBW. The mechanism responsible for the periodic downslope flow of dense water is further analyzed using an idealized model setup. The period of dense water outflow is regulated primarily by the topographic beta effect. [ABSTRACT FROM AUTHOR]

The Southern Ocean allows circumpolar structure and the Antarctic coastline plays a role as a waveguide for oceanic Kelvin waves. Under the cyclic conditions, the horizontal wavenumbers and frequencies for circumpolarly propagating waves are quantized, with horizontal wavenumbers 1, 2, and 3, corresponding to periods of about 32, 16, and 11 h, respectively. At these frequencies, westward-propagating signals are detected in sea level variation observed at Antarctic coastal stations. The occurrence frequency of westward-propagating signals far exceeds the statistical significance, and the phase speed of the observed signal agrees well with the theoretical phase speed of external Kelvin waves. Therefore, this study concludes that the observed, westward-propagating sea level variability is a signal of the external Kelvin waves of wavenumbers 1, 2, and 3 around Antarctica. A series of numerical model experiments confirms that Kelvin waves around Antarctica are driven by surface air pressure and that these waves are excited not only by local forcing over the Southern Ocean, but also by remote forcing over the Pacific Ocean. Sea level variations generated over the Pacific Ocean can travel to the western side of the South American coast and cross over Drake Passage to the Antarctic continent, constituting a part of the Kelvin waves around Antarctica. [ABSTRACT FROM AUTHOR]

Antarctic coastal polynyas are important areas of high sea ice production and dense water formation, and thus their detection including an estimate of thin ice thickness is essential. In this paper, the authors propose an algorithm that estimates thin ice thickness and detects fast ice using Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Imager (SSM/I) data in the Antarctic Ocean. Detection and estimation of sea ice thicknesses of <0.2 m are based on the SSM/I 85- and 37-GHz polarization ratios (PR85 and PR37) through a comparison with sea ice thicknesses estimated from the Advanced Very High Resolution Radiometer (AVHRR) data. The exclusion of data affected by atmospheric water vapor is discussed. Because thin ice and fast ice (specifically ice shelves, glacier tongues, icebergs, and landfast ice) have similar PR signatures, a scheme was developed to separate these two surface types before the application of the thin ice algorithm to coastal polynyas. The probability that the algorithm correctly distinguishes thin ice from thick ice and from fast ice is ∼95%, relative to the ice thicknesses estimated from AVHRR. Although the standard deviation of the difference between the thin ice thicknesses estimated from the SSM/I algorithm and AVHRR is ∼0.05 m and thus not small, the estimated ice thicknesses from the microwave algorithm appear to have small biases and the accuracies are independent of region and season. A distribution map of thin ice occurrences derived from the SSM/I algorithm represents the Ross Sea coastal polynya being by far the largest among the Antarctic coastal polynyas; the Weddell Sea coastal polynyas are much smaller. Along the coast of East Antarctica, coastal polynyas frequently form on the western side of peninsulas and glacier tongues, downstream of the Antarctic Coastal Current. [ABSTRACT FROM AUTHOR]

In the Antarctic Ocean, sea ice melts mostly by warming of the ocean mixed layer through heat input (mainly solar radiation) in open water areas. A simplified ice–upper ocean coupled model is proposed in which sea ice melts only by the ocean heat supplied from the air. The model shows that the relationship between ice concentration (i.e., fraction, C) and mixed layer temperature (T) converges asymptotically with time (C–T relationship), which agrees with observed C–T plots during summer in the sector 25°–45°E. This relationship can be used for estimating the bulk heat transfer coefficient between ice and ocean by fitting to observations, and a value of 1.2 × 10-4 m s-1 is obtained. The model shows that the ratio of the heat used for melting to the heat input through open water is inclined to be determined as a function of ice concentration. For typical conditions in the Antarctic ice melt season, the ratio ranges mostly between 0.7 and 0.9. When the model is extended to two dimensions in the meridional direction, with the inclusion of wind forcing, it approximately reproduces the meridional retreat of the Antarctic sea ice. This two-dimensional model can describe the open water–albedo feedback effect, which partly explains the year-to-year variation of the sea-ice retreat in the Antarctic Ocean. [ABSTRACT FROM AUTHOR]