Sediment resuspension and its occurring conditions in the Soya warm current region observed from ADCP backscatter strength

Subinertial and seasonal variations in the Soya Warm Current (SWC) are investigated using data obtained by high frequency (HF) ocean radars, coastal tide gauges, and a bottom-mounted acoustic Doppler current profiler (ADCP). The HF radars clearly captured the seasonal variations in the surface current fields of the SWC. Almost the same seasonal cycle was repeated in the period from August 2003 to March 2007, although interannual variations were also discernible. In addition to the annual and interannual variations, the SWC exhibited subinertial variations with a period of 5–20 days. The surface transport by the SWC was significantly correlated with the sea level difference between the Sea of Japan and Sea of Okhotsk for both the seasonal and subinertial variations, indicating that the SWC is driven by the sea level difference between the two seas. The generation mechanism of the subinertial variation is discussed using wind data from the European Centre for Medium-range Weather Forecasts (ECMWF) analyses. The subinertial variations in the SWC were significantly correlated with the meridional wind stress component over the region. The subinertial variations in the sea level difference and surface current delay from the meridional wind stress variations by one or two days. Sea level difference through the strait caused by wind-generated coastally trapped waves (CTWs) along the east coast of Sakhalin and west coast of Hokkaido is considered to be a possible mechanism causing the subinertial variations in the SWC.

Subinertial variations in the Soya Warm Current (SWC) are investigated using data obtained by high frequency (HF) ocean radars, coastal tide gauges, and a bottom-mounted acoustic Doppler current profiler (ADCP). The SWC exhibited subinertial variations with a period of 5-20 days. The surface transport by the SWC was significantly correlated with the sea level difference between the Sea of Japan and Sea of Okhotsk for both the seasonal and subinertial variations, indicating that the SWC is driven by the sea level difference between the two seas. The subinertial variations in the SWC were significantly correlated with the meridional wind stress component over the region. Sea level difference through the strait caused by wind-generated coastally trapped waves along the east coast of Sakhalin and west coast of Hokkaido are considered to be a possible mechanism causing the subinertial variations in the SWC.

Propagation of subinertial variations in the Soya Warm Current (SWC), which flows through the Soya Strait located between Hokkaido, Japan and Sakhalin Island, Russia, is investigated using data from HF ocean radars together with in situ observations, such as bottom-mounted acoustic Doppler current profilers (ADCPs) and coastal tide gauges. The subinertial variations with periods from 5 to 20 days were captured by the HF radars. The subinertial variations were significantly correlated with the meridional wind stress component over the region, suggesting that the sea level difference through the strait caused by wind-generated coastally-trapped waves on the east coast of Sakhalin and west coast of Hokkaido are considered to be a possible mechanism casing the subinertial variations in the SWC. Propagation of the subinertial variations was also clearly captured by the HF radars. The estimated phase velocity suggests that the subinertial variations propagate downstream along the coast as the 3rd-mode barotropic continental shelf waves.

Direct measurements using a free-falling micro-profiler were conducted on the northeast coast of Hokkaido in the summer of 2007 to clarify the mixing process in the Soya Warm Current (SWC) region in terms of microstructure. The distribution of the Turner angle (Tu) showed that these regions have a high potential for double diffusive convection, but direct measurements of the turbulent dissipation rate (e) and dissipation of temperature variance (\( \chi_{T} \)) did not necessarily correspond to each other in the SWC region, especially in the offshore front of SWC and farther offshore. The mixing efficiency indicated that, even though the Turner angle (Tu) indicated a high potential for double diffusive convection, turbulent mixing was the main contributor to the mixing process in this region, and double-diffusive convection only contributed partially and sparsely, especially in the boundary off SWC water. The bottom mixed layer (BML) is known to thicken off the SWC. The vertical diffusivity coefficient was enhanced near the bottom (10−4–10−3 m2 s−1) off the SWC, and these results support that turbulence near the bottom off the SWC contributed to the thickening of the BML.

The cold-water belt (CWB) is frequently formed off the Soya Warm Current (SWC) during summer and autumn. The detailed distribution of the flow and temperature fields observed by the R/V Sinyo-maru in the summer of 2001 captured the structures of the SWC and the CWB. The temperature and density distributions showed that the vertical distribution of the CWB is associated with the upwelling formed off the SWC. Numerical experiments using a two-layer model with realistic bottom topography have been performed to understand the formation mechanism of CWB and the upwelling structure off the current. In the experiment, the sea level difference between the Japan Sea and the Okhotsk Sea, and baroclinic flow assuming the Tsushima Warm Current were given along the open boundary. The numerical model well reproduces the current system of the SWC and upwelling region off it. The upwelling region is formed at the Soya Strait first, and then it spreads on the offshore side along the SWC as a developing current system. Analysis of the model data indicated that the geostrophic balance mainly dominates in the current system, while convergence of the bottom Ekman transport due to the SWC forms the upwelling region as the secondary circulation. In addition, the advection effect due to the SWC is found to strengthen the upwelling.

Three High Frequency (HF) ocean radar stations were installed around the Soya/La Perouse Strait in the Sea of Okhotsk in order to monitor the Soya Warm Current (SWC). The frequency of the HF radar is 13.9 MHz, and the range and azimuth resolutions are 3 km and 5 deg., respectively. The radar covers a range of approximately 70 km from the coast. The surface current velocity observed by the HF radars was compared with data from drifting buoys and shipboard Acoustic Doppler Current Profilers (ADCPs). The current velocity derived from the HF radars shows good agreement with that observed using the drifting buoys. The root-mean-square (rms) differences were found to be less than 20 cm s−1 for the zonal and meridional components in the buoy comparison. The observed current velocity was also found to exhibit reasonable agreement with the shipboard ADCP data. It was shown that the HF radars clearly capture seasonal and short-term variations of the SWC. The velocity of the Soya Warm Current reaches its maximum, approximately 1 m s−1, in summer and weakens in winter. The velocity core is located 20 to 30 km from the coast, and its width is approximately 40 km. The surface transport by the SWC shows a significant correlation with the sea level difference along the strait, as derived from coastal tide gauge records at Wakkanai and Abashiri.

Three high-frequency (HF) ocean radars were deployed around the Soya (La Perouse) Strait in 2003 to monitor the Soya Warm Current (SWC). Surface current observed by the HF radars contains a wind drift component, which must be removed in order to estimate the interior SWC. The wind drift parameters, speed factor and turning angle were derived from the surface current measured by the HF radars, the vertical current profile measured by a bottom-mounted acoustic Doppler current profiler (ADCP), and wind data from the numerical weather analysis system operated by the Japan Meteorological Agency (JMA) from October 1, 2006 to July 24, 2008. The ensemble-mean turning angle and speed factor from the entire dataset (excluding August 2007) were estimated to be 28° and 0.66 %, respectively. No significant seasonal variations were discernible in the wind drift parameters. After removal of the wind drift current estimated from the wind with the ensemble-mean drift parameters, the correlation coefficient between the along-shore current speed and sea level difference between the Sea of Japan and Sea of Okhotsk improved from 0.791 to 0.825. It was revealed that the magnitude of wind drift current reaches 45 % of that of the interior current in winter and approximately 20 % in summer, indicating the importance of wind drift current estimation in this region.

We examined the data obtained by acoustic Doppler current profiler, conductivity‐temperature‐depth profiler, and expendable bathythermograph observations, which were collected in the summers of 2000, 2001, and 2002, to clarify the characteristics of the cold‐water belt (CWB), i.e., lower‐temperature water than the surrounding water extending from the southwest coast of Sakhalin along the offshore side of Soya Warm Current (SWC) and to confirm one of the formation mechanisms of the CWB as suggested by our previous study, i.e., the upwelling due to the convergence of bottom Ekman transport off the SWC region. The CWB was observed at about 30 km off the coast, having a thickness of 14 m and a minimum temperature of 12°C at the sea surface. The CWB does not have the specific water mass, but is constituted of three representative water types off the northeast coast of Hokkaido in summer, i.e., SWC water, Fresh Surface Okhotsk Sea Water, and Okhotsk Sea Intermediate Water. In a comparison of the horizontal distributions of current and temperature, the CWB region is found to be advected to the southeast at an average of 40 ± 29% of the maximum current velocity of the SWC. The pumping speed due to the convergence of the bottom Ekman transport is estimated as (1.5–3.0) × 10−4 m s−1. We examined the mixing ratio of the CWB, and the results implied that the water mass of the CWB is advected southeastward and mixes with a water mass upwelling in a different region off SWC.

This study provides formulae for monthly estimates of the Soya Warm Current (SYC) transport from the sea-level difference (SLD) across the Soya Strait and along the current, and creates a 50-yr data set of the SYC transport. The formulae are based on the dynamical balance both across the strait and along the current by considering the barotropic and baroclinic components. It is suggested that the barotropic and baroclinic components in transport variability are comparable in summer, whereas the barotropic component is dominant in winter. We compared the 50-year time series of the SYC transport with those of the Tsushima (TSC) and Tsugaru Warm Currents estimated from the SLDs from the viewpoint of the Japan Sea Throughflow (JSTF) system. The variabilities of the SYC and TSC transports are mostly shared for any season, showing relatively high coherence at periods of 2–5 years as well as 1 year. The winter variability of the JSTF transport originates partly from that of the SYC transport caused by the winter monsoon variability in the Sea of Okhotsk. The SYC transport is significantly correlated with the transport through the eastern channel of the TSC, but not that through the western channel. We found difficulty in extracting variability and relationships at periods longer than 5 years among the three transports estimated from the SLDs, probably due to incomplete correction of the ground movements for the sea-level data.

To design a method for predicting outbreaks of paralytic shellfish poisoning (PSP) in scallop fishing grounds, the relationship between the distribution of the toxic dinoflagellate Alexandrium tamarense and the dynamics of the Soya Warm Current (SWC) was examined in the Okhotsk Sea off Hokkaido. Surveys were conducted from May to June to clarify the transportation mechanism of A. tamarense from the oceanic area to the coastal area. The sea-level difference (SLD) between Wakkanai and Abashiri was monitored as an index of the strength of the SWC southeastward flow in an alongshore belt to examine the possible occurrence of A. tamarense in the coastal area during temporal weakening of the SWC. A bottom-mounted acoustic Doppler current profiler (ADCP) was used for direct observations of the SWC. The results indicated that PSP occurred when low-salinity water contaminated with A. tamarense extended to the coast during temporal weakening of the SWC due to a decrease of the SLD. Our results strongly indicate that predictions can be realized by monitoring the decrease of SLD as an index of temporal weakening of the SWC after surveys of the distribution of A. tamarense in the oceanic area before the period of PSP occurrence.

The vertical structure of the Soya Warm Current (SWC) was observed by a bottom-mounted acoustic Doppler current profiler (ADCP) in the region of the SWC axis near the Soya Strait during a 1-year period from May 2004. The ADCP data revealed a marked seasonal variability in the vertical structure, with positive (negative) vertical shear in summer and fall (winter and spring). The volume transport of the SWC is estimated on the basis of both the vertical structure observed by the ADCP and horizontal structure observed by the ocean radars near the strait. The transport estimates have a minimum in winter and a maximum in fall, with the yearly-averaged values in the range of 0.94–1.04 Sv (1 Sv = 106 m3 s−1). These lie within a reasonable range in comparison to those through other straits in the Japan Sea.

Time-series data of the vertical structure of the Soya Warm Current (SWC) were obtained by a bottom-mounted acoustic Doppler current profiler (ADCP) in the middle of the Soya Strait from September 2006 to July 2008. The site of the ADCP measurement was within the coverage of the ocean-radar measurement around the strait. The volume transport of the SWC through the strait is estimated on the basis of both the vertical structure observed by the ADCP and the horizontal structure observed by the radars for the first time. The annual transport estimates are 0.62–0.67 Sv (1 Sv = 106 m3s−1). They are somewhat smaller than the difference between the previous estimates of the inflow and outflow through other straits in the Sea of Japan, and smaller than those obtained in the region downstream of the strait during 2004–05 (0.94–1.04 Sv). The difference in the two periods may be attributed to interannual variability of the SWC and/or the different measurement locations.

An algorithm is described and tested to provide accurate and robust deep-sea seafloor classification based on the backscatter data derived from a multibeam bathymetry system. This article focuses on significant heterogeneity in the deep-sea backscatter strength (BS) data. The angular response curve information is decomposed into different units, and BS data are grouped on the basis of the incidence angle to address the heterogeneity in the across-ship direction. Subsequently, a sliding window is applied on BS data in each group, and a robust estimation method is used to address the potential heterogeneity in the window during feature extraction. Thereafter, the extracted features are learned by fuzzy c-means (FCM) to obtain a clustering solution. In the learning process, the features of each group are learned by an independent FCM. The modified FCM algorithm is used to cluster each group of data to handle unbalanced backscatter data sets. With this procedure, heterogeneity in BS data can be accounted for, which is universal in deep-sea survey application. Finally, the results of the different groups are merged to obtain a global label set for the survey region. The method was tested on the multibeam data collected from an offshore region around the Kyushu–Palau Ridge. Monte Carlo simulation was performed to evaluate the performance of the robust method. Computational results demonstrate that the improved algorithm can address the heterogeneity in BS data efficiently and provide an accurate classification solution in the deep-sea survey environment.

Resistance to macrolides in Streptococcus pneumoniae is usually mediated by methylation of 23S ribosomal RNA, encoded by the erm(B) methylation gene, or by efflux mediated by the mef(A) gene. Changes in the L4 and L22 ribosomal proteins have also been associated with macrolide resistance and reduced telithromycin activity. This study generated in vitro mutants from three parent strains of S. pneumoniae: 02J1175 [mef(A) +], 02J1095 [erm(B) +] and NCTC 13593 (macrolide susceptible). The erm(B) and the erm(B) upstream region, the mef(A) genes and the mef(A) upstream and downstream regions, the 23S rRNA genes encoding domains II and V and the L4 and L22 genes of the telithromycin-resistant strains were all amplified by PCR and all, except the mef(A) upstream and downstream regions, were sequenced. No changes were present in any of the genes of the mef(A) + mutants. No changes were found in the erm(B) genes, the 23S rRNA genes or the L4 protein genes of the erm(B) + mutants. However, a Lys-94 to Gln-94 amino acid mutation did occur in a mutant derived from erm(B) + with a telithromycin MIC of >32 mg/L. A 210 base pair deletion in the erm(B) upstream region was also present in this strain. We believe this is the first incidence of a Lys-94 to Gln-94 change in L22 associated with telithromycin resistance and also the first time that such a large deletion in the erm(B) upstream region has been identified in S. pneumoniae.

The casein gene cluster spans 250 to 350 kb across mammalian species and is flanked by non-coding DNA with largely unknown functions. These regions likely harbor elements regulating the expression of the 4 casein genes. In Bovidae, this cluster is well studied in domestic cattle and to a lesser extent in zebu and water buffalo. This study used a cattle-specific SNP microarray to analyze 12 Bovidae taxa and estimate casein gene cluster variability across 5 bovid subfamilies. Genotyping identified 126 SNPs covering the entire casein gene cluster and 2 Mb of upstream and downstream regions. Dairy cattle, watusi, and zebu showed the highest polymorphism: 63.7-68.2% in the 5'-upstream region, 35.6-40.0% in the casein cluster, and 40.4-89.4% in the 3'-downstream region. Among wild bovids, only a 'semi-aquatic' lechwe revealed high polymorphism similar to cattle. Other species exhibited lower variability, ranging from 9.1-27.3% in the 5'-upstream, 8.9-20.0% in the casein, and 4.2-10.6% in the 3'-downstream regions. For the first time, genome variability data were obtained for impala, waterbuck, and lechwe. It appears that higher variability in cattle's casein gene cluster may relate to its intense expression. This study confirms the effectiveness of cattle-derived microarrays for genotyping Bovidae.