Ching-Yuan Lu

Mr. Ching-Yuan Lu

orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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9 March 2020 in Remote Sensing
Verified
Journal Article
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Po-Chun HsuPo-Chun Hsu
Po-Chun Hsu
CHChia-Ying Ho
Chia-Ying Ho
HLHung-Jen Lee
Hung-Jen Lee
CLChing-Yuan Lu
Ching-Yuan Lu
CHChung-Ru Ho
Chung-Ru Ho
Dynamics of ocean current-induced island wake has been an important issue in global oceanography. Green Island, a small island located off southeast of Taiwan on the Kuroshio path was selected as the study area to more understand the spatial structure and temporal variation of well-organized vortices formed by the interaction between the Kuroshio and the island. Sea surface temperature (SST) and chlorophyll-a (Chl-a) concentration data derived from the Himawari-8 satellite and the second generation global imager (SGLI) of global change observation mission (GCOM-C) were used in this study. The spatial SST and Chl-a variations in designed observation lines and the cooling zone transitions on the left and right sides of the vortices were investigated using 250 m spatial resolution GCOM-C data. The Massachusetts Institute of Technology general circulation model (MITgcm) simulation confirmed that the positive and negative vortices were sequentially detached from each other in a few hours. In addition, totals of 101 vortexes from July 2015 to December 2019 were calculated from the 1-h temporal resolution Himawari-8 imagery. The average vortex propagation speed was 0.95 m/s. Totals of 38 cases of two continuous vortices suggested that the average vortex shedding period is 14.8 h with 1.15 m/s of the average incoming surface current speed of Green Island, and the results agreed to the ideal Strouhal-Reynolds number fitting curve relation. Combined with the satellite observation and numerical model simulation, this study demonstrates the structure of the wake area could change quickly, and the water may mix in different vorticity states for each observation station.

7 October 2021 in Journal of Geophysical Research: Oceans
Verified
Journal Article
Open access
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Po-Chun HsuPo-Chun Hsu
Po-Chun Hsu
LCLuca Centurioni
Luca Centurioni
HSHuan‐Jie Shao
Huan‐Jie Shao
QZQuanan Zheng
Quanan Zheng
CLChing-Yuan Lu
Ching-Yuan Lu
RTRuo-Shan Tseng
Ruo-Shan Tseng
Ocean currents in the southern East China Sea (ECS) are complex and have long lacked systematic observational data. Observations from coastal radars in northern Taiwan, along with several drifters and satellite data, reveal a detailed ECS surface flow structure and thermal front. Drifter trajectories followed the seasonal flow field and were oscillatory and trapped due to strong tidal currents. Three drifters crossed the oceanic front off the northern coast of Taiwan following the tidal motion with a rapid change in the sea surface temperature by 2.5°C, which was recorded within a small distance of 500 m. A significant seasonal water mass exchange cycle occurred in the southern ECS. Starting in October, the Kuroshio Current intrudes onto the ECS shelf, causing the formation of a southwestward Northern Taiwan Coastal Current that mixes with the China Coastal Current to form a southward flow in the northern Taiwan Strait. Beginning in March, the ocean current off northwestern Taiwan shifts northward and then gradually flows eastward into the Kuroshio region. With satellite‐derived and model‐simulated surface currents contradicting each other over long periods of time, hourly coastal radar data have not only successfully explained the spatiotemporal variations in the sea surface temperature, salinity, and chlorophyll concentration observed by satellites but have also resolved the long‐standing disputes over the surface currents in the southern ECS.

2 September 2020 in Remote Sensing
Verified
Journal Article
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Po-Chun HsuPo-Chun Hsu
Po-Chun Hsu
CLChing-Yuan Lu
Ching-Yuan Lu
Tai-Wen HsuTai-Wen Hsu
Tai-Wen Hsu
CHChung-Ru Ho
Chung-Ru Ho
The waters in the north of Taiwan are located at the southern end of the East China Sea (ECS), adjacent to the Taiwan Strait (TS), and the Kuroshio region. To understand the physical dynamic process of ocean currents and the temporal and spatial distribution of the ocean chlorophyll concentration in the north of Taiwan, hourly coastal ocean dynamics applications radar (CODAR) flow field data and geostationary ocean color imager (GOCI) data are analyzed here. According to data from December 2014 to May 2020, the water in the TS flows along the northern coast of Taiwan into the Kuroshio region with a velocity of 0.13 m/s in spring and summer through the ECS. In winter, the Kuroshio invades the ECS shelf, where the water flows into the TS through the ECS with a velocity of 0.08 m/s. The seasonal variation of ocean chlorophyll concentration along the northwestern coast of Taiwan is obvious, where the average chlorophyll concentration from November to January exceeds 2.0 mg/m3, and the lowest concentration in spring is 1.4 mg/m3. It is apparent that the tidal currents in the north of Taiwan flow eastward and westward during ebb and flood periods, respectively. Affected by the background currents, the flow velocity exhibits significant seasonal changes, namely, 0.43 m/s in summer and 0.27 m/s in winter during the ebb period and is 0.26 m/s in summer and 0.45 m/s in winter during the flood period. The chlorophyll concentration near the shore is also significantly affected by the tidal currents. Based on CODAR data, virtual drifter experiments, and GOCI data, this research provides novel and important knowledge of ocean current movement process in the north of Taiwan and indicates diurnal to seasonal variations in the ocean chlorophyll concentration, facilitating future research on the interaction between the TS, ECS, and Kuroshio.

1 August 2021 in Remote Sensing
Verified
Journal Article
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YTYu-Hao Tseng
Yu-Hao Tseng
CLChing-Yuan Lu
Ching-Yuan Lu
QZQuanan Zheng
Quanan Zheng
CHChung-Ru Ho
Chung-Ru Ho
Sea surface currents observed by high-frequency (HF) radars have been widely used in ocean circulation research. In this study, hourly sea surface currents observed by the Taiwan Coastal Ocean Dynamics Applications Radar (CODAR) system from 2015 to 2019 were analyzed by the empirical orthogonal function (EOF) analysis to reveal the characteristics of the sea surface currents around Taiwan Island. The study area is divided into two regions, the Kuroshio region east of Taiwan Island and the Taiwan Strait west of Taiwan Island. In the Kuroshio region, the first EOF mode shows that the Kuroshio is characterized by higher current speeds with greater variability in summer. The second and third EOF modes present a dipole eddy pair and single eddy impingement on the Kuroshio during different periods. The seasonal variation of the dipole eddy pair indicates that the cyclonic/anticyclonic eddy on the north/south side appears more frequently in summer. Single eddy impingement occurs at multiple periods, including daily, intraseasonal, interseasonal, and annual periods. For the Taiwan Strait, the first EOF mode displays the tide signals. The tides enter the Taiwan Strait from the north and south, forming strong sea surface currents around the northern tip of Taiwan Island and the Penghu Archipelago. The second EOF mode exhibits the seasonal changes of the sea surface currents driven by the monsoon winds. The sea surface currents in the northern Taiwan Strait are relatively strong, possibly due to the narrow and shallow terrain there. The high spatiotemporal resolution of sea surface currents derived from CODAR observations provide more detailed characteristics of sea surface circulation around Taiwan Island.

28 October 2021 in Remote Sensing
Verified
Journal Article
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Po-Chun HsuPo-Chun Hsu
Po-Chun Hsu
HLHung-Jen Lee
Hung-Jen Lee
CLChing-Yuan Lu
Ching-Yuan Lu
Yilan Bay is in the northeast corner of Taiwan at the junction of the East China Sea (ECS) and the Pacific Ocean. This study clarified the composition of water masses adjacent to Yilan Bay. The upper seawater in the bay is characterized by Kuroshio surface water, Taiwan warm current water, and shelf mixed water masses. The flow field in this area is mainly determined by the inter-actions among the northeastern Taiwan countercurrent, Kuroshio Current (KC), and tidal currents. The fall season is the main rainfall period in Yilan Bay, which causes a large amount of river runoff and a further increase in chlorophyll concentration, and the salinity of the upper water layer is observed much lower than other seasons. Water with a high chlorophyll concentration can flow into the ECS with ebb currents and the KC with ebb and flood currents. Combining hourly geosynchronous ocean color imager data and numerical simulation flow field helps us understand short-term changes of chlorophyll concentration. The trajectories of the drifters and virtual particle simulations help us understand the sources and movement of ocean currents in Yilan Bay. The seasonal swing of the KC path outside the bay is an important factor affecting the flow field and hydrological characteristics.

12 June 2022 in Remote Sensing
Verified
Journal Article
Open access
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YYYi Chung Yang
Yi Chung Yang
CLChing-Yuan Lu
Ching-Yuan Lu
SHShih-jen Huang
Shih-jen Huang
TYThwong-Zong Yang
Thwong-Zong Yang
YCYu-Cheng Chang
Yu-Cheng Chang
CHChung-Ru Ho
Chung-Ru Ho
Satellite remote sensing sea surface temperature (SST) data are lost due to cloud cover. Missing data often cause inconvenience in subsequent applications and thus need to be reconstructed. In this study, the Data Interpolating Empirical Orthogonal Function (DINEOF) method was used to reconstruct the hourly SST data missing from the Himawari-8 satellite in the waters near Taiwan. The SST characteristics in the waters around Taiwan are quite complex, with high SST at Kuroshio in the east of Taiwan and great variation in the SST west of Taiwan due to the influence of tides. Therefore, the analysis with DINEOF was conducted using 25-h data to match the tidal cycle. The influence of SST characteristics on the accuracy of SST reconstruction is also discussed. The results show that in the western sea area where the variation of SST is large, the average root-mean-square error of SST between the original SST and the reconstructed SST is the lowest and the average coefficient of determination is the highest. The accuracy of the reconstructed SST is positively correlated with the SST variation. Furthermore, the statistical results also show that the DINEOF method can effectively reconstruct the SST regardless of the missing data rate.