This study examined the effects of freshwater discharge by artificial dikes from the Kanwol and Bunam lakes on the dynamics in the Chunsu Bay, Yellow Sea, Korea, during the summer season based on three-dimensional numerical modeling experiments. Model performances were evaluated in terms of skill scores for tidal elevation, velocity, temperature, and salinity and these scores mostly exceeded 90 %. The variability in residual currents before and after the freshwater discharge was examined. The large amount of lake water discharge through artificial dikes may result in a dramatically changed density field in the Chunsu Bay, leading to an estuarine circulation system. The density-driven current formed as a result of the freshwater inflow through the artificial dikes (Kanwol/Bunam) caused a partial change in the tidal circulation and a change in the scale and location of paired residual eddies. The stratification formed by strengthened static stability following the freshwater discharge led to a dramatic increase in the Richardson number and lasted for a few weeks. The strong stratification suppressed the vertical flux and inhibited surface aerated water mixing with bottom water. This phenomenon would have direct and indirect impacts on the marine environment such as hypoxia/anoxia formation at the bottom.
Vertical land motion at tide gauges influences sea level rise acceleration; this must be addressed for interpreting reliable sea level projections. In recent years, tide gauge records for the Eastern coast of Korea have revealed rapid increases in sea level rise compared with the global mean. Pohang Tide Gauge Station has shown a +3.1 cm/year sea level rise since 2013. This study aims to estimate the vertical land motion that influences relative sea level rise observations at Pohang by applying a multi-track Persistent Scatter Interferometric Synthetic Aperture Radar (PS-InSAR) time-series analysis to Sentinel-1 SAR data acquired during 2015–2017. The results, which were obtained at a high spatial resolution (10 m), indicate vertical ground motion of −2.55 cm/year at the Pohang Tide Gauge Station; this was validated by data from a collocated global positioning system (GPS) station. The subtraction of InSAR-derived subsidence rates from sea level rise at the Pohang Tide Gauge Station is 6 mm/year; thus, vertical land motion significantly dominates the sea level acceleration. Natural hazards related to the sea level rise are primarily assessed by relative sea level changes obtained from tide gauges; therefore, tide gauge records should be reviewed for rapid vertical land motion along the vulnerable coastal areas.
Monthly mean sea-levels have annual maxima in August in the northeast Asian marginal seas (NEAMS). Based on satellite altimetry data, the rising rate of the August NEAMS sea-level (ANS, 4.2 mm∙yr−1) is greater than those of the NEAMS (3.6 mm∙yr−1) and global (3.4 mm∙yr−1) annual mean sea-levels. Thus, the interannual variations of ANS are classified as relatively high (period H) and low (period L) years and have been analysed because of the high risk of sea-level fluctuation to the coastal regions in August. In period H, there are large atmospheric pressure gradients between the high pressure zone in the Kuroshio Extension (KE) and the low pressure zone in the west of Taiwan (WT). In period L, the atmospheric pressure gradients are small between the above-mentioned zones. Large atmospheric pressure gradients induce strong west-northwestward wind stresses and more Ekman transport from the northwest Pacific Ocean into the NEAMS. The correlation coefficient between August NEAMS sea-level index (ANSI), which is the difference of atmospheric pressure anomalies between the KE and the WT, and the August NEAMS sea-level anomaly (ANSA) is 0.73. Although there is a significant correlation (coefficient: 0.64) between ANSA and the East Asian summer monsoon index (EASMI), ANSI might be more useful in estimating the variability of ANSA.
<p>Korean coasts are exposed to high risks such as storm surge, storm-induced high waves and wave overtopping. Also, localized heavy rainfall events have occurred frequently due to climate change, too. Especially, since coastal urban areas depend heavily on pump and pipe systems, extreme rainfalls that exceed the design capacity of drainage facility result in increasing inland flood damage. Nevertheless, the population in Korea is concentrated in the coastal areas and the value and density of coastal utilization are increasing. In this study, the risk of hybrid disasters in the coastal areas was assessed for safe utilization and value enhancement of coastal areas. The framework of the coastal risk assessment has been adopted from the concept of climate change vulnerability of the IPCC(2001). Coastal Risk Index(CRI) in this study was defined as a function of Exposure and Sensitivity exclude Adaptive Capacity using GIS-based DBs. Indicators of Exposure consisted of a storm surge, storm-induced high waves, wave overtopping and rainfalls. Indicators of Sensitivity consisted of human(population density), property(buildings and roads), and geography(inundation area). All these indicators were gathered from government agencies, numerical model experiments(ADCIRC, unSWAN, FLOW3D and XP-SWMM model), and field surveys(Drone & Lidar survey). And then spatial analysis was performed by using a GIS program after passing the quality control and analyzed data were standardized and classified 4 grades; Attention(blue color), Caution(yellow color), Warning(orange color) and Danger(red color). This frame of risk assessment was first applied to Marine City, Haeundae in Busan, Korea which was heavily damaged by the typhoon CHABA in 2018. According to the assessment results, it was confirmed that the results were in good agreement with the observation data and damage range. At present, the study area of risk assessment is expanding to other areas. The results of coastal risk assessment are used as reference indicators to identify and prevent the cause of coastal disasters, establish countermeasures, determine the development or management of coastal areas based on GIS, thus will contribute to effective and safe coastal management.</p>
This dataset was generated to support the following research paper.The detailed method for measuring data here is provided in the methods section of the following paper.Those who use data here, please consult Professor Kitack Lee (ktl@postech.ac.kr) and cite the following paper. Persistent Organic Alkalinity in the Oceanby Chang-Ho Lee1, Kitack Lee1,2*, Kwang-Young Jeong3, Young-Ho Ko4*1Division of Environmental Science and Engineering, Pohang University of Science and Technology, Pohang, 37673, Korea2Institute for Convergence Research and Education in Advanced Technology, Yonsei University, Seoul, 03722, Korea3Ocean Research Division, Korea Hydrographic and Oceanographic Agency, Busan, 49111, Korea4OJEong Resilience Institute, Korea University, Seoul, 02481, Korea *CorrespondenceKitack Lee (ktl@postech.ac.kr)Young-Ho Ko (younghko@korea.ac.kr)
It is vital to improve estimations of long-term trends in global and regional sea level rise to help mitigate and adapt to climate change. Satellite altimetry data have been widely used for this purpose; however, data collected in regions with strong tidalmotions often suffer from significant aliasing effects unless they are sufficiently corrected using accurate ocean tide models.Long-term trends estimated from altimetry data are often also considerably affected by regional circulation changes, and by artificial effects arising from inconsistencies between different satellite missions. Here, we focused on two regions with high (>5 mm⋅yr –1 ) rates of long-term linear trend in sea level rise (LTSLR) around the Korean Peninsula (KP). We addressed the impacts of tidal correction and mission inconsistency in satellite altimetry data, and discussed the potential impacts of circulation changes on LTSLR. Because the LTSLR estimation is affected by the aliasing effects of altimetry data when the tidal motions are not corrected sufficiently, yet the correction depends on the performance of ocean tide models, we employed eight ocean tide models to correct altimetry data for comparison and validated the results against observations from 13 tide gauge (TG) stations around the KP. We also estimated LTSLR from 1993 to 2019 using annual mean sea level anomalies (SLAs) from two satellite (two-sat) and all 21 satellite (all-sat) missions, with corrections for ocean tides. The TPXO9 model showed the most reasonable spatial LTSLR rate pattern (∼3 mm⋅yr –1 ), with the smallest difference from TG observations. It performed best near the west coast where the tidal range was the largest and when using two-sat data, because of inconsistencies in all-sat altimetry data. In contrast, off the east coast, where the impact of tidal correction is negligible, the high (∼7 mm⋅yr –1 ) LTSLR rates were robust regardless of ocean tide models and altimetry missions, potentially driven by long-term changes in regional circulation. Our results highlight the importance of tidal correction and mission inconsistency for improving LTSLR estimations around the KP. They also have significant implications for determining regional sea level rise under changing circulation patterns, within and beyond the region.
<p>Recently, the rate of sea level rise in accelerating with time, and many studies have reported that sea level will increase rapidly in the near future. Also, various global ocean climate models are used to predict sea level rise due to global warming. However, most global ocean climate models have low resolutions, so it is hard to explain detailed the ocean phenomena such as sea level and currents around Korean Peninsula. This study aims to past 30-year reproduce and future 100-year predict for rising trend of sea level using Regional Climate Ocean Model (RCOM) with ROMS according to IPCC climate change scenario (RCP 4.5).</p><p>The RCOM with high resolution of 1/20&#176; horizontally and 40 layers vertically has been established for reproduction and long term forecast of sea-level rise in the Northwest Pacific, including marginal seas around Korea. Dynamic downscaling processes using result of the global climate models were applied to the open boundary conditions of our RCOM. To prepare the optimal boundary data for RCOM, the CMIP5 climate model was evaluated to select 4 climate models: IPSL-CM5A-LR, and -MR, NorESM1-M, MPI-ESM-LR.</p><p>Based on the RCOM results of 4 experiments, the rate of sea level rise for IPCC climate change scenario (RCP4.5) around Korean peninsula were 2.52, 2.21, 3.11, 3.36 mm/yr for the last 30 years (1976~2005), and 5.17, 4.99, 5.62, 5.42 mm/yr for the next 100 years (2006~2100), respectively. Ensemble mean value of next 100 years for 4 model results was 5.30 mm/yr. The sea level rise of 4 models for RCP 4.5 were 48, 48, 58, 48 cm for next 100 years, respectively, and ensemble mean value of 4 models was 50 cm during 2006~2100.</p><p>Future studies will focus on predicting the next 100 years of sea level change based on IPCC climate change scenario (RCP2.6, 8.5).</p><p>&#160;</p>
Kim, B.-J.; Lee, D.E.; Ro, Y.-J., and Jeong, K.-Y., 2021. Weather-driven coastal dynamics in a tide-dominated area: Cases from Spring 2016 along the west coast of Korea. Journal of Coastal Research, 37(3), 494–505. Coconut Creek (Florida), ISSN 0749-0208.Analyses of current dynamics recorded using multilayer current meters in Spring 2016 (15 April–17 May, 32 d) at two stations near Kkotji Beach in Anmyeon-do, Yellow Sea, Korea, are presented. Harmonic analysis is applied to identify tidal characteristics in the study area. A slightly rotational current pattern is detected at ST01, while oscillations predominantly in north–south orientation are detected at ST02. Nontidal residual currents and the concurrent surface atmosphere data are analyzed together. Residual currents converge (diverge) between ST01 and ST02 following the increase (decrease) in thickness between two stations. Using advanced statistical methods, the spatial patterns of such dynamic events are shown with their association with surface atmosphere. Complex correlation analysis reveals that residual currents are significantly correlated with abrupt surface wind fluctuations associated with extratropical cyclones. The characteristics of residual currents and surface wind vectors are further analyzed, using complex empirical orthogonal functions (CEOF). The first residual current mode (R1) accounts for 46.8% of the total variation, while the second mode (R2) accounts for 24.9%. R1 represents a wind-induced component in the longshore direction, while R2 represents a bottom-driven component in the opposite direction. Both the modes correlate significantly with the first wind mode (W1, longshore wind), which leads the associated residual current modes by a few hours. Spectral analysis indicates that the two significant periods of surface wind and residual current modes are well matched to each other, exhibiting cycles of 1.6 and 4 days.
The interannual variability of winter sea levels averaged over the northeast Asian marginal seas, consisting of the Yellow Sea, East China Sea, and the East Sea (ES), was investigated. The spatial-mean sea level in winter observed using satellite altimetry shows significant interannual variations with a long-term rising trend of 3.88 mm y−1 during 1993–2017, with relatively high (Period H) and low (Period L) sea level anomalies. These anomalies correlate with the patterns of the East Asian winter monsoon at interannual timescales. The atmospheric pressure difference between the Sea of Okhotsk (SO) and ES around the Soya Strait is large during Period H. Ekman transport increases due to enhanced southeastward wind stress and results in a horizontal mass convergence that yields positive sea level anomalies during Period H. In contrast, the wind-induced transport is enhanced in the southern ES rather than in the southern SO resulting in horizontal mass divergence and negative anomalies in the spatial-mean winter sea level during Period L. Our results highlight the important roles of local wind forcing and Ekman dynamics in inducing interannual winter sea level variability in the region indicating the high predictive ability of atmospheric pressure anomalies around the Soya Strait.
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