• Ocean and Polar Research
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• v.23 no.4
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• pp.433-440
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• 2001

Marine organisms in Antarctica live in an environment which exhibits variability in physical processes over a wide range of temporal scales, from seconds to millennia. This time scale tends to be correlated with the spatial scale over which a given process operates, though this relationship is influenced by biology. The way organisms respond to variability in the physical environment depends on the time-scale of that variability in relation to life-span. Short-term variations are perceived largely as noise and probably have little direct impact on ecology. Of much greater importance to organisms in Antarctica are seasonal and decadal variations. Although seasonality has long been recognised as a key feature of polar environments, the realization that decadal scale variability is important is relatively recent. Long-term change has always been a feature of polar environments and may be a key factor in the evolution of the communities we see today.

• Ocean and Polar Research
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• v.32 no.3
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• pp.187-201
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• 2010

The purpose of this study was to investigate the temporal and spatial variability of taxonomic groups and major species of the mesozooplankton community in Lake Shihwa, Korea. Monthly collections were carried out at five stations in Lake Shihwa for a period of one year. The mesozooplankton community showed distinct seasonal variability with water temperature and salinity. Major mesozooplankton species in each seasonal community were derived from non-metric MDS and SIMPER as follows: winter community (Acartia hongi and Eurytemora pacifica), spring community (Acartia hudsonica and Polychaeta larvae), summer community (Acartia sinjiensis, Pavocalanus crassirostris, Evadne tergestina and Cirripedia nauplii) and fall community (Paracalanus indicus and Podon leuckarti). The succession of the seasonal species, A. hudsonica and A. sinjiensis, was the most remarkable event during the seasonal changes of the mesozooplankton community. The species response curve of these species fitted with the logistic regression in relation to water temperature and salinity. The curve also correctly represented the characteristics of the occurrence of A. hudsonica and A. sinjiensis in Lake Shihwa.

• Ocean and Polar Research
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• v.29 no.4
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• pp.349-366
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• 2007

Seasonal variations of various physicochemical components (temperature, salinity, pH, DO, COD, DOC, nutrients-silicate, DIN, DIP) and potential limiting factor for phytoplankton primary production were studied in the surface water of semi-enclosed Masan Bay. Seasonal variations of nutrient concentrations, with lower values in summer and winter, and higher in fall, are probably controlled by freshwater loadings to the bay, benthic flux and magnitude of occurrence of phytoplankton communities. Their spatial distributional patterns are primarily dependent on physical mixing process between freshwater and coastal seawater, which result in a decreasing spatial gradient from inner to outer part of the bay. In the fall season of strong wave action, the major part of nutrient inputs (silicate, ammonium, dissolved inorganic phosphorus) comes from regeneration (benthic flux) at sediment-water interface. During the summer period, high Si:DIN and Si:DIP and low DIN:DIP relative to Redfield ratios suggest a N- and secondarily P-deficiency. During other seasons, however, silicate is the potential limiting factor for primary production, although the Si-deficiency is less pronounced in the outer region of the bay. Indeed, phytoplankton communities in Masan Bay are largely affected by the seasonal variability of limiting nutrients. On the other hand, the severe depletion of DIN (relatively higher silicate level) during summer with high freshwater discharge probably can be explained by N-uptake of temporary nanoflagellate blooms, which responds rapidly to pulsed nutrient loading events. In Masan Bay, this rapid nutrient consumption is considerably important as it can modify the phytoplankton community structures.

• Journal of the Korean earth science society
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• v.44 no.1
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• pp.1-12
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• 2023

Oceanic wind waves have been recognized as one of the important indicators of global warming and climate change. It is necessary to study the spatial and temporal variability of significant wave height (SWH) and wave direction in the Yellow Sea and a part of the East China Sea, which is directly affected by the East Asian monsoon and climate change. In this study, the spatial and temporal variability including seasonal and interannual variability of SWH and wave direction in the Yellow Sea and East China Sea were analyzed using European Center for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5) data. Prior to analyzing the variability of SWH and wave direction using the model reanalysis, the accuracy was verified through comparison with SWH and wave direction measurements from Ieodo Ocean Science Station (I-ORS). The mean SWH ranged from 0.3 to 1.6 m, and was higher in the south than in the north and higher in the center of the Yellow Sea than in the coast. The standard deviation of the SWH also showed a pattern similar to the mean. In the Yellow Sea, SWH and wave direction showed clear seasonal variability. SWH was generally highest in winter and lowest in late spring or early summer. Due to the influence of the monsoon, the wave direction propagated mainly to the south in winter and to the north in summer. The seasonal variability of SWH showed predominant interannual variability with strong variability of annual amplitudes due to the influence of typhoons in summer.

• Journal of Environmental Science International
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• v.29 no.11
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• pp.1141-1151
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• 2020

The impact of sound speed variability in the sea is the very important on acoustic propagation for the underwater acoustic systems. Understanding of the temporal and spatial variability of ocean sound speed in the sea around the Ieodo were obtained using oceanographic data (temperature, salinity). from the Korea Oceanographic Data Center, collected by season for 17 years. The vertical distributions of sound speed are mainly related to seasonal variations and various current such as Chinese coastal water, Yellow Sea Cold Water (YSCW), Kuroshio source water. The standard deviations show that great variations of sound speed exist in the upper layer and observation station between 16 and 18. In order to quantitatively explain the reason for sound speed variations, Empirical Orthogonal Function (EOF) analysis was performed on sound speed data at the Line 316 covering 68 cruises between 2002 and 2018. Three main modes of EOFs respectively revealed 55, 29, and 5% the total variance of sound speed. The first mode of the EOFs was associated with influence of surface heating. The second EOFs pattern shows that contributions of YSCW and surface heating. The first and second modes had seasonal and inter-annul variations.

• Fisheries and Aquatic Sciences
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• v.5 no.3
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• pp.219-228
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• 2002

Based on the five-year (October 1992 through September 1997) Topex/Poseidon altimeter measurements, we describe the statistical characteristics of the eddy variability in the East Sea in terms of sea surface height anomaly, slope variability, and eddy kinetic energy (EKE). The sea surface height anomalies in the East Sea are produced with standard corrections from Topex/Poseidon measurements. In order to eliminate the high frequency noise in the sea surface height anomaly data, the alongtrack height anomaly data was filtered by about 40 km low-pass Lanczos filter based on Strub et al. (1997) and Kelly et a1. (1998). We find that there exists a distinct spatial contrast of high eddy variability in the south and low eddy energy in the north, bordering the Polar Front. In the northwestern area $(north\;of\;39^{\circ}N\;and\;west\;of\;133^{\circ}E)$ from the Polar Front where the eddies frequently appear, the EKE is also considerabel. The high kinetic energy in the southern East Sea reveals a close connection with the paths of the Tsushima Warm Current, suggesting that the high variability in the south is mainly generated by the baroclinic instability process of the Tsushima Warm Current. This finding is supported by other studies (Fu and Zlontnicki, 1989; Stammer, 1997) wh.ch have shown the strong eddy energy coupled in the major current system. The monthly variation of the EKE in both areas of high and low eddy variability shows a strong seasonality of a high eddy kinetic energy from October to February and a relatively low one from March to September. The sequential pattern of wind stress curl shows resemblance with those of monthly and seasonal EKE and the two sequences have a correlation of 0.82 and 0.67, respectively, providing an evidence that wind stress curl can be the possible forcing for the monthly and seasonal variation of the EKE in the East Sea. The seasonality of the EKE also seems to correlate with the seasonality of the Tsushima Warm Current. There also exists the large spatial and interannual variabilities in the EKE.

• Proceedings of the KSRS Conference
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• v.2
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• pp.922-925
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• 2006

The objective of this study is first to resolve the spatial and seasonal variability of BL in the bay using 'the most comprehensive' data set available for the bay and then to understand the formation mechanisms and variability in the light of the known dynamical and thermodynamical processes. The most recent study [Masson et al., 2002] on the BL variability in the bay was based on the World Ocean Atlas (WOA98) of Levitus [1998]. The temperature and salinity profiles in the bay have increased considerably after the release of WOA98. The WOA98, itself has been updated to WOA01 in 2001. Further, the deployment of ARGO profiling floats in the bay since 2002 has generated many additional profiles. In addition to the ARGO data and the updated WOA01, the hydrographic data collected from the bay under several Indian national programs and archived in the Indian Oceanographic Data Centre (IODC) was also considered in the present study. The WOA98 and WOA01 consist of only limited data from the IODC archive, especially from the Exclusive Economic Zone of India. Therefore, the combination of these data from the three different sources (WOA01, ARGO and IODC) provides ‘the most comprehensive data set’ for the bay to resolve the BLT structure and its variability in a much better scale than in the past.

• Current Research on Agriculture and Life Sciences
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• v.32 no.4
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• pp.203-209
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• 2014

This study investigated characteristics of rainfall and water quality in Saemangeum area with attention to temporal and spatial distributions. A high variability in rainfall was noted during July and August. The temporal analysis of water quality data indicated that DO and TN as well as BOD, COD and SS were within national standards except for increased concentrations during spring and summer, unlike TP values that indicated poor water quality. Standard deviation showed a high variability in SS among the seasons most especially during summer. The high dispersion indicated variability in the chemical composition of pollutants where the temporal and spatial variations caused by polluting sources and/or seasonal changes were most evident for BOD and COD during winter and spring. The box plots and bar charts showed steadily low concentrations of BOD, COD, TN and TP except within Iksan and notable significant variations in SS concentrations among the monitoring stations. Thus, high pollution levels requiring intervention were identified in Mangyeong river basin with particular concern for areas represented by Iksan station. It was noted that Iksan received a considerable amount of rainfall which meant high runoff which could explain the significant pollution levels revealed in the water quality spatial distribution. Major pollution contributing pollutants within Saemangeum area were identified as SS, BOD, COD and TN. Therefore the present results could be used as a guideline for the temporal and spatial distributions analysis of both rainfall and water quality in Saemangeum watershed.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.2
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• pp.201-211
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• 2015

Acoustic propagation in shallow water with changing environments is a major concern of navy. Temporal and spatial variability of acoustic propagation in the northern East China Sea (ECS) is studied, using the 11 years hydrographic data and the Bellhop acoustic model. Acoustic propagation in the northern ECS is highly variable due to extensive interaction of various ocean currents and boundaries. Seasonal variations of transmission loss (TL) with various source depths are highly affected by sharp gradient of sound speed and bottoms interaction. Especially, various bottom sediment types lead to severely degrading a waterborne propagation with bottom loss. In particular, the highly increased TL near the ocean front depends on the source position, and the direction of sound propagation.

• Ocean and Polar Research
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• v.38 no.1
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• pp.1-19
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• 2016

Recently, there has been a growing interest in physical-biological ocean-modeling systems by communities in the fields of science and business. In this paper, we present preliminary results from a coupled physical-biological model for the Northwestern Pacific marginal seas. The ocean circulation component is an implementation of the Regional Ocean Modeling System (ROMS), and the lower trophic level ecosystem component is a Nutrient-Phytoplankton-Zooplankton-Detritus (NPZD) model. The ROMS-NPZD coupled system, with a 25 km resolution, is forced by climatological atmospheric data and predicts the physical variables and concentrations of nitrate, phytoplankton, zooplankton, and detritus. Model results are compared with remote-sensed sea surface temperature and chlorophyll, and with climatological sea surface salinity and nitrate. Our model adequately reproduces the observed spatial distribution and seasonal variability of nitrate and chlorophyll concentrations as well as physical variables, showing a high correlation in the East Sea (ES) and Kuroshio/Oyashio Extension (KOE) region but relatively low correlation in the Yellow Sea (YS) and East China Sea (ECS). Although some deficiencies were found in the biological components, such as the over/underestimation of the intensity of phytoplankton blooms in the ES and KOE/the YS and ECS, our system demonstrates the capability of the model to capture and record dominant seasonal variability in physical-biological processes and this holds out the promise of coming to a better understanding of such processes and making better predictions .