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Water depth (m) of the Taiwan Strait and the surrounding seas (CYR: Chang-Yun Rise; TWB: Taiwan Banks).
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The sea surface temperature (SST) in the Taiwan Strait (TS) during autumn and winter (October–March) is strongly influenced by the northeast monsoon, which drives the cold China Coastal Current to flow southward into the TS, where it encounters the warm Kuroshio Branch Current coming from the south to form a quasi-steady front. Using Advanced Very...
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Context 1
... the northeast monsoon season (October-March), the wind-driven China Coastal Current (CCC) flows southward along the Chinese coast; therefore, the northeast monsoon may weaken the northward current in the TS ( Jan et al. 2002). Topography considerably affects circulation in the TS; a distinct topographical structure (the Chang-Yun Rise; Figure 1) in the middle of the strait narrows northward and/or southward CONTACT Ming-An Lee malee@ntou.edu.tw INTERNATIONAL JOURNAL OF REMOTE SENSING 2018, VOL. ...
Context 2
... the northeast monsoon season (October-March), the wind-driven China Coastal Current (CCC) flows southward along the Chinese coast; therefore, the northeast monsoon may weaken the northward current in the TS ( Jan et al. 2002). Topography considerably affects circulation in the TS; a distinct topographical structure (the Chang-Yun Rise; Figure 1) in the middle of the strait narrows northward and/or southward CONTACT Ming-An Lee malee@ntou.edu.tw INTERNATIONAL JOURNAL OF REMOTE SENSING 2018, VOL. ...
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Citations
... The spatial pattern of CCF in the Taiwan Strait remains unclear and inconclusive. For example, the often-repeated claim that the CCF extends along the 50-m isobath is inconsistent with the existence of a broad (~50 km wide) shallow area northwest of the Taiwan Bank, with depths of <40 m and often <30 m (as evidenced by bathymetry maps in Belkin andLee, 2014, Figure1 andKuo et al., 2018, Figure 1). This shallow area (submarine isthmus connecting the Bank with the continent) would constrain the CCC and associated CCF. ...
High-resolution (2 km) high-frequency (hourly) SST data from 2015-2021 provided by the Advanced Himawari Imager (AHI) onboard the Japanese Himawari-8 geostationary satellite were used to study spatial and temporal variability of the China Coastal Front (CCF) in the South China Sea. The hourly SST data were processed with the Belkin and O’Reilly (2009) algorithm to generate long-term mean monthly maps of SST gradient magnitude (GM) and frontal frequency (FM). The horizontal structure of CCF was investigated from cross-frontal distributions of SST along 11 fixed lines that allowed to determine inshore and offshore boundaries of the CCF and calculate the CCF strength defined as the total cross-frontal step dSST = Offshore SST – Inshore SST. Combined with the results of Part1 of this study (Belkin, Lou, Yin, 2023), where the CCF was documented in the East China Sea, the new results reported in this paper allowed the CCF to be reliably traced from the East China Sea via Taiwan Strait into the northern South China Sea and farther west up to the east coast of Hainan Island.
... The sea surface wind field has obvious seasonal characteristics, and the surface water movement of the strait is affected by the monsoon. After statistical analysis of more than 6000 aerial survey data, Kuo et al. (2018) concluded that the winter wind in the Taiwan Strait is strong, the wind direction is stable, and the NE wind is dominant. The summer wind is weak, and the wind direction is a changeable but mainly southerly wind. ...
Zhang, X.; Meng, J.; Sun, L., and Zhang, H., 2023. Characteristics and influencing factors of internal solitary waves in the Penghu Channel based on satellite remote sensing. Journal of Coastal Research, 39(4), 685–699. Charlotte (North Carolina), ISSN 0749-0208.
The Taiwan Strait has always been considered a hot spot for the occurrence of internal waves in the ocean. Recent research shows that the Penghu Channel also has a strong and previously unknown source of internal solitary waves (ISWs). In this paper, 23 satellite remote sensing images covering the Penghu Channel from Sentinel-1 synthetic aperture radar (SAR), Envisat advanced synthetic aperture radar, HY-1D, and GF-1 satellites are examined to reveal the sea surface characteristics of the area's ISWs through image interpretation and dynamics analysis and to study the local generation of ISWs and their evolutionary characteristics in this sea area. The results show that SE and SW cross-propagating ISWs exist in the Penghu Channel. They are generated near the Penghu Islands and the continental shelf of Taiwan at the same latitude and propagate in a countercurrent direction along the Penghu Channel. The ISWs from these two directions meet and continue to propagate southward in a V shape, with various wave–wave interactions occurring in the middle of the channel, such as Mach and resonance interactions, depending on the strength and angle characteristics of the ISWs. SAR images also show that waveform broadening occurs during the propagation of ISWs to the shallow shelf and the ISWs' polarity transition phenomenon. Although the specific generation mechanism is not clear, it is speculated that the interaction of the tidal current with the complex topography of the Penghu Channel is the main source of energy for these ISWs. In addition, the combination of drifting buoy data and analysis of hydrographic conditions in the Penghu Channel indicates that ISW phenomena on the sea surface are observed more frequently during summer flood tides with low wind speeds, low sea conditions, strong stratification, and strong currents.
... This trend the main fishing ground of coastal and offshore fisheries off western Taiwan is located in the waters of Chang-Yun Rise. The study also indicated that the hydrological condition of the coastal waters off south-western Taiwan is more stable and warmer relative to other sites [39]. The hydrological condition and biological features influence species composition, and they comprise current speed, current direction, oxygen, chlorophyll-a concentration, and zooplankton [33]. ...
... The hydrological condition and biological features influence species composition, and they comprise current speed, current direction, oxygen, chlorophyll-a concentration, and zooplankton [33]. Northwestern Taiwan is often affected by monsoons, and this factor increases the difficulty of fishing for local fisherman [39]. Monsoons can benefit fish by providing an abundance of nutrients in summer through upwelling; specifically, the China Coastal Current (CCC) that occurs in the Taiwan Strait (TS) produces the highest nutrient concentration around the coast in winter. ...
Black sea bream, Acanthopagrus schlegelii, is among the most commercially valuable species in the coastal fishery industry and marine ecosystems. Catch data comprising capture locations for the gillnet fisheries, remotely sensed environmental data (i.e., sea surface temperature, chlorophyll-a concentration, and current velocity), and topography (bathymetry) from 2015 to 2018 were used to construct a spatial habitat distribution of black sea bream. This species is concentrated in coastal waters (<3 nm) from December to April (spawning season). The maximum entropy (MaxEnt) method and corresponding habitat suitability index among seasons were used to clarify the species’ spatial distribution and identify the seasonal variations in habitat selection. The patterns corresponded closely to the changes in oceanographic conditions, and the species exhibited synchronous trends with the marine environment’s seasonal dynamics. Chlorophyll-a concentration and bathymetry substantially influenced (80.1–92.9%) black sea bream’s habitat selection. By applying the MaxEnt model, the optimal habitats were identified with four variables including depth and satellite-derived temperature, current velocity and chlorophyll-a concentration, which provides a foundation for the scientific assessment and management of black sea bream in coastal waters of the Eastern Taiwan Strait.
... In February, the SST in the northwestern TS was generally lower than 16 C, which was employed as an index for the winter thermal front boundary between the CCC and the KBC in the TS [3]. The SST gradient increased gradually from November onward as the CCC intruded southward along the Chinese coast [37]. ...
... Interestingly, a fast warming trend with 0.63 C/ decade since 2012 was accompanying this "warming hiatus" after 1998. Kuo et al. [37] suggested that the East Asian winter monsoon (EAWM) may appear as one of the most important phenomena. They postulated that the SST warming and cooling phenomena were attributable to the weakening and strengthening of the EAWM before and after 2000, respectively. ...
... From 1980 to 1998, the EAWM index demonstrated an increasing trend, peaking in 1998, indicating the weakening of the northeasterly monsoon. Subsequently, the EAWM index decreased over the following 13 years, exhibiting the strengthening trend of the northeasterly monsoon in the past decade [37]. After 2012, the EAWM index slightly increased again. ...
... Among the ocean colour sensors available, MODIS is currently the most used for investigating ocean biology. The data were tested and validated using in situ measurements to ensure their accuracy (El Hourany et al., 2017;Ghanea et al., 2016;Kuo et al., 2018;Moore et al., 2009;Young and Donelan, 2018). ...
The climatological means and annual variation of chlorophyll-a (Chl-a) concentration, sea surface temperature (SST) and sea surface wind (SSW) from 2002 to 2016 in the Savu Sea (SS) within Indonesia were analysed. Chl-a variability and SST information was used as a reference in determining potential fishing grounds. The research aimed to investigate the variability of Chl-a and SST along with the influencing factor of the Australian-Indonesian Monsoon (AIM) winds. The study was conducted in SS waters, in East Nusa Tenggara (NTT), Indonesia, using 15 years of monthly Aqua MODIS Level 3 data. The retrieved data were corrected geometrically and radiometrically and then analysed to produce mean climatology data. The results indicated that the spatial and temporal AIM winds had a significant influence on the Chl-a concentration and the SST in SS waters. There was a two-month delay in the peak concentration of Chl-a/SST; moreover, the AIM wind speed, which peaks in June, was not followed by either the SST minima or the Chl-a maxima, which occur in August. The level of Chl-a in the SS waters showed seasonal patterns, with the highest concentration occurring during the east season (June–August), the peak concentration being 0.52 mg m⁻³, alongside a wind speed of 5.42 m s⁻¹ and an SST of 22.89 oC in August. Meanwhile, the lowest concentration of Chl-a 0.17 mg m⁻³ occurred in February during the west season (December–February), with a wind speed of 2.10 m s⁻¹ and an SST of 29.57 oC. Three specific areas showed characteristics that differed from the general pattern of the monsoon winds’ effects on Chl-a and SST in the SS. This study provides the latest description of Chl-a, SST and wind speed distribution at seasonal and spatial scales and their variability across the Savu Sea. The results of this study are essential for fishing catching activities and fisheries management in the region.
... The effects of fishing pressure on the moonfish resource are becoming more serious and should be carefully monitored. Also, the catches of the moonfish have a negative relationship with sea-surface temperature and sea-surface height (Chen, 2016), and after October the strengthen of the Northeast monsoon (Jan et al., 2002) leads to the decrease of seasurface temperature (Kuo et al., 2018), resulting to the increase of the average monthly CPUE and catches of the moonfish. ...
The moonfish (Mene maculata) is a common fish caught by coastal fisheries in the waters of southwestern Taiwan. Considering the sustainable utilization of fishery resources, this study aims to analyze the characteristics of the temporal and spatial changes of moonfish catch location and to estimate the length-weight relationship on the moonfish. According to 2014-2016 fishery data, the primary fishing methods in this area are Taiwanese seine and trawl. Generally, moonfish are caught by Taiwanese purse seine. Moonfish hotspots, located on the southwestern coast of Taiwan, produce a high catch per unit effort (CPUE). Over time, relatively distinct spatial variations have occurred in moonfish hotspots; most notably, numerous moonfish were caught in the waters offshore of Penghu in 2016. The most productive fishing season is from January to March, and the main fishing grounds are in coastal waters off southwestern Taiwan. The fishing grounds are relatively far from the shore from April to September and somewhat scattered. Analyzing 388 moonfish samples collected from the southwestern waters of Taiwan indicates positive allometric growth (b > 3) for moonfish, indicating fish grew faster in weight than in length and a good correlation between body length and body weight. Further studies are recommended to explore the relationship between environmental factors and the spatiotemporal distribution of moonfish and the affecting factors of the L-W relationship.
... Previous studies have shown that wind field is a very important driving force for the hydrodynamic environment of the TWS in winter (Kuo et al. 2018;Pan et al. 2013;Zhang et al. 2005). The ZMCW is driven southward by northeastern winds along the coast of Zhejiang and Fujian (Hong et al. 2011). ...
... Although there is no direct correlation between wind and ZMCW InI (p > 0.2), a decrease in temperature will favor an increase in the strength of the ZMCW (Zhang and Hong, 2014). Kuo et al. (2018) have also found that the warming and cooling of TWS SST are mainly attributable to the weakening and strengthening of the East Asia winter monsoon, respectively. Furthermore, the winter monsoon drives shoreward Ekman transport, raising the sea level along the western side of the TWS (Shaw and Chao, 1994). ...
The cold, low-salinity, and nutrient-rich Zhe-Min Coastal Water (ZMCW), an important part of the China Coastal Current, plays a key role in the hydrodynamics, biogeochemical processes and marine ecosystem in the Taiwan Strait (TWS). In this study, the long-term characteristics of the ZMCW were investigated using available data sets, including merged satellite-derived sea surface temperature (SST) data, wind, ocean current, and heat flux data. The results demonstrated that the impact area and intensity of the ZMCW decreased from 1986 to 1998, and then increased significantly from 1999 to 2016. The enhancements of the ZMCW resulted in SST reductions after 1998. The enhancements of the ZMCW in winter after 1998 can be attributed to the intensification of northeast winds, weakening of the Strait Warm Water, and increasing of net surface heat flux (from ocean to atmosphere). In addition, the impact area and intensity of the ZMCW tend to strengthen during La Niña and weaken during El Niño events.
... A similar lag correlation (0-6 months) between rainfall anomalies and ONI values during the La Niña events was observed in the western Pacific (Wang et al., 2000). Kuo et al. (2017) indicated SST in the TS was warming with a trend of about 0.15 • C year −1 during the period between 1980 and 2000. The possible interaction between the warming trend and cold events is unclear at this moment. ...
The objectives of this study were to assess the predictability of exceptionally cold water in the Taiwan Strait (TS) and to develop a warning system on the basis of the scientific mechanism, which is a component of the information technology system currently under development in Taiwan to protect aquaculture against extreme hazards. Optimum interpolation sea surface temperature (SST) data were used to find exceptionally cold water days from January 1995 to May 2017. We found that the SST and wind speed over the TS are low and strong in La Niña winters, respectively. According to tests conducted using relative operating characteristic curves, predictions based on the Oceanic Niño Index and integrated wind speed can be employed at lead times of 60–120 and 0–25 days, respectively. This study utilized these two proxies to develop a possible warning mechanism and concluded four colors of warning light: (1) blue, meaning normal (0 % occurrence probability); (2) cyan, meaning warning (∼50 % occurrence probability); (3) yellow, meaning moderate risk (∼60 % occurrence probability); and (4) red, meaning high risk (∼75 % occurrence probability). Hindcasting winters over the period 1995–2017 successfully predicted the cold water hazards in the winters of 2000, 2008, and 2011 prior to the coldest day by ∼20 days.
... From 1981 to 2013, the spatial average of winter SST warming in the Taiwan Strait was 3C (Kuo and Lee, 2013;Belkin and Lee, 2014). Long-term warming was strongly enhanced in winter, with a maximum warming of 0.07C/ year in February (Kuo et al., 2018). Nevertheless, the unusual cold CCC intrusion into the southern Taiwan Strait might result in the increased abundance of some migratory species, such as Japanese anchovy, during La Niña years . ...
