台灣周邊海域海流之數值研究

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(1)國立臺灣師範大學地球科學研究所博士論文. 台灣周邊海域海流之數值研究 Numerical study on the currents around Taiwan. 研究生：辛宜佳 (Yi-Chia Hsin) 指導教授：吳朝榮博士 (Dr. Chau-Ron Wu). 中華民國九十七年七月.

(2) 國立臺灣師範大學學位論文授權書本授權書所授權之論文為授權人在國立臺灣師範大學地球科學研究所九十六學年度第二學期取得博士學位之論文。論文題目：台灣周邊海域海流之數值研究 (Numerical study on the currents around Taiwan) 指導教授：吳朝榮博士授權事項： ■同意非專屬無償授權本校及國家圖書館將上列論文資 □不同意料以微縮、數位化或其他方式進行重製，並可上載網路收錄於本校博. 一、授權人. 碩士論文系統、國家圖書館全國博碩士論文資訊網及臺灣師範校院聯合博碩士論文系統，提供讀者基於個人非營利性質之線上檢索、瀏覽、下載、傳輸、列印或複印等利用。二、論文全文電子檔上載網路公開時間：【第一項勾選同意者，以下須擇一勾選】 □ 即時公開 ■ 自＿九十八年＿元月＿一日始公開。授權人姓名：學. （請親筆正楷簽名）. 號：892440040. 中. 華. 民. 國. 九十七年七月三十一日 - II -.

(3) 國立臺灣師範大學地球科學系(研究所)博士論文通過簽名表系所別：地球科學系（研究所）姓名：辛宜佳. 學號：892440040. 博士論文題目：台灣周邊海域海流之數值研究 Numerical study on the currents around Taiwan 經審查合格，特予證明論文口試委員. 系主任（所長）簽章：_____________________ 中華民國九十七年七月三十日. - III -.

(4) Abstract A multiple grid-size nesting ocean model system is developed in this work to perform studies on the variations of the flow in the Taiwan Strait and the Kuroshio east of Taiwan. The transport in the Taiwan Strait is studied using the East Asian Marginal Seas (EAMS) model. Three model experiments using different wind data sets (ERA40, NCEP Reanalysis version 2, and QuikSCAT/NCEP blend wind) were performed. Model experiments suggested that the best simulation is achieved when the model is driven by the QuikSCAT/NCEP blend wind forcing. Involving the strong wintertime southward flow events in the Taiwan Strait, the annual averaged modeled transports through the Taiwan Strait is 1.09 Sv (1 Sv=106 m3/s). The result suggests that shipboard Acoustic Doppler Current Profiler (sb-ADCP) observations are biased toward estimates in summer and fair weather since bad weather during the winter northeast monsoon often prevents seagoing observations. Linear regression lines are also proposed to give simple relations between transport and wind stress for roughly evaluating the transport through a known wind stress value. The spatial and temporal variations of the Kuroshio east of Taiwan are investigated using model outputs, surface drifter trajectories, satellite-based altimetric data, and wind data. From the simulation of the EAMS model over a span of 24 years from 1982 to 2005, the variability of the Kuroshio east of Taiwan is studied in detail. Between 22 and 25°N, the mean state and variability of the Kuroshio, such as the two paths observed in the trajectories of surface drifters southeast of Taiwan and the branching of the Kuroshio - VI -.

(5) northeast of Taiwan, are well reproduced by the model. Southeast of Taiwan, the Kuroshio is mostly in the top 300 m in the inshore path but extends to 600 m in the offshore path. Northeast of Taiwan, the Kuroshio follows the shelf edge in the East China Sea, but sometimes branches along a path south of the Ryukyu Islands. The latter path often meanders southward, and a significant portion of the Kuroshio transport may be diverted to this path. The Kuroshio extends from the coast to 123°E ~ 123.5°E between 22°N ~ 25°N with currents reaching a depth of 1000 m at some latitudes. The Kuroshio transports averaged over five sections east of Taiwan are 28.4 ± 5.0 Sv and 32.7 ± 4.4 Sv with and without the contribution from the countercurrent, respectively. Using satellite data and the Seas Around Taiwan (SAT) model simulation, the intra-seasonal variation of the Kuroshio southeast of Taiwan is further studied. Superimposed with the main stream of the Kuroshio, two intra-seasonal signals longer than 2 weeks are revealed in the study region, 20 ~ 30 days and 40 ~ 90 days. The variation of 20 ~ 30 days is only significant between Taiwan and the Lan-Yu Island. A mechanism is proposed to describe how the wind stress curl in the northeastern South China Sea modulates the circulation southeast of Taiwan on this timescale. The fluctuation with a longer period of 40 ~ 90 days is resulted from the westward propagating eddies.. (Key words: volume transport, Taiwan Strait, numerical modeling, Kuroshio, intra-seasonal variation). - VII -.

(6) Table of contents page. 謝誌……………………………………………………….. IV Abstract ………………………………………………….. VI Table of contents ………………………………................ VIII List of tables ……………………………………………... XI List of figures …………………………………….............. XII Chapter 1 Introduction …………………………………. 1 1.1 Geographic background around Taiwan ………………..... 1. 1.2 Motivation …………………………………………...…........ 4. 1.3 References …………………………………………………... 8. Chapter 2 Volume transport through the Taiwan Strait: a numerical study …......................................... 13 2.0 Abstract ……….…..………………….……………………... 13 2.1 Introduction ……….…..………………….………………… 14 2.2 The numerical model ………………………………………. 17 2.3 Results and discussions …………………………………….. 20 2.3.1 Model experiments and validation ………………………. 20 2.3.2 Transport through the Penghu Channel ………………….. 22 2.3.3 Transport through the Taiwan Strait ……………………... 26 - VIII -.

(7) 2.4 Conclusions ………………………………………………..... 31 2.5 References ………………………………………………....... 33. Chapter 3 Spatial and Temporal Variations of the Kuroshio East of Taiwan, 1982-2005: A numerical study.............................................. 37 3.0 Abstract …………………………………………………....... 37 3.1 Introduction ……………………………………………........ 38 3.2 Model description ………………………………………….. 43 3.3 Result from model simulation ……………………………... 45 3.3.1 Mean surface currents …………………………………… 46 3.3.2 Seasonal variation of currents with depths ……………..... 49 3.3.3 Transport …………………………………………………. 55 3.4 Discussions ………………………………………………….. 61 3.5 Conclusions …………………………………………………. 64 3.6 References …………………………………………………... 66. Chapter 4 Intra-seasonal Variation of the Kuroshio southeast of Taiwan and its possible forcing mechanism ...................................................... 72 4.0 Abstract …………………………………………………....... 72 4.1 Introduction ………………………………………………… 72 4.2 Satellite data and numerical model ……………………...... 75 - IX -.

(8) 4.3 Results ……………………………………………………..... 76 4.3.1 Velocity property and intra-seasonal variation …………... 76 4.3.2 Dynamics of the Kuroshio fluctuations ………………...... 80 4.4 Conclusions …………………………………………………. 85 4.5 References …………………………………………………... 86. Chapter 5 Conclusions ………………………………...... 89 Appendix I: Publication list …….…………………......... 92. -X-.

(9) List of tables page Table 3.1. Mean Kuroshio transport east of Taiwan in earlier observations ……………………………………….….. 39. - XI -.

(10) List of figures page Figure 1.1. Bathymetry around Taiwan.…………………….......... 1. Figure 1.2. Seasonal average wind field (COADS) around Taiwan. The vector denotes the wind speed in m/s. JFM, AMJ, JAS, and OND represent spring, summer, fall, and winter, respectively…………………………. 3. Figure 2.1. (a) The integrated domain of the EAMS model with realistic bathymetry. (b) The study area with locations of mooring stations (triangles) and the Penghu Channel (PHC). The horizontal line across the Penghu Island is chosen to calculate the strait-wide volume transport from model. The color shading represents the bottom topography…………... 14. Figure 2.2. (a) Time series of observed transport through the Taiwan Strait calculated from four bottom-mounted ADCPs (from Teague et al. [2003] and Ko et al. [2003]). (b) The model-derived volume transports across the Taiwan Strait. The red, blue, and purple lines represent the transports estimated from three numerical experiments QS, EC and NC, respectively. The observed transport is also plotted (black line) for comparison.…………………….................................. 21. Figure 2.3. Model-derived transport compared to observations through the Penghu Channel. Pink segments and red circle are calculated from sb-ADCP measurements by Jan and Chao [2003] and Wang et al. [2004], respectively. Blue stars are calculated from sb-ADCP observations by Dr. Ruo-Shan Tseng (unpublished data)………………………………………………….. 23. Figure 2.4. Relationship between the model-derived transport through the Penghu Channel and the along-strait wind stress………………………………………….... 23. - XII -.

(11) Figure 2.5. Model-derived transport and observed transports in the Taiwan Strait. Blue stars and red circles represent strait-wide volume transports calculated from sb-ADCP measurements by Dr. Ruo-Shan Tseng (unpublished data) and by Chung et al. [2001], respectively. Purple line represents monthly mean model-derived transport.…………………….............. 27. Figure 2.6. Relationship between model-derived transport through the Taiwan Strait and the along-strait wind stress.…………............................................................ 27. Figure 2.7. Model-derived pressure gradient force between north and south entrances of the Taiwan Strait during the period from 1999 to 2003. The pressure gradient is cal culat ed fro m mod el s e a s u r f a c e h e i g h t difference……………………………………............. 29. Figure 2.8. Comparison between model-derived transport (red line) and transport estimated using a resistance coefficient (blue line) during the period from 1999 to 2003………………………………………………….. 30. Figure 2.9. Comparison of upper-layer temperatures (0 ~ 50 m) to the east (black line) and west (red line) of the Penghu Island during the period from 1999 to 2003. The temperatures are averaged over the regions of black and red rectangles shown in the upper panel............................................................................. 30. Figure 3.1. The nested system of numerical simulation. (a) The NPO model domain with the EAMS domain in a box. (b) The EAMS model domain and bathymetry. (c) Enlarged view of bathymetry in the seas around Taiwan……………...................................................... 40. - XIII -.

(12) Figure 3.2. The annual mean surface current averaged from 0 to 50 m (a) in the full EAMS domain and (b) in the vicinity of Taiwan. The color bar is for both panels and represents the current speed. The number of grids is doubled and the length of the velocity vector is reduced by half from 15 to 35ºN and from 120 to 140ºE in (a). Six lines labeled as 1 to 6 indicate the sections for transport calculation at 22.5ºN, 24ºN, 25.25ºN, 124ºE, PCM-1, and PN-LINE, respectively.. 46. Figure 3.3. Vertical distributions of horizontal velocities between 0 and 1000 m in sections at 22.5°N, 24°N, 25.25°N, and 124°E. The velocity is averaged over data from 24-years’ model simulation. The left panels are zonal velocity component (U), and the right ones are the meridional velocity component (V). The contour interval is 10 cm/s. The negative contours in gray shading denote westward flow in U or southward flow in V.…………………………………………….. 48. Figure 3.4. Maximum horizontal currents between 0 and 200 m from model simulation. The unit vector is 50 cm/s, and color-shading indicates current speed. Panels (a) ~ (d) are for spring, summer, fall, and winter, respectively………………………………………...... 50. Figure 3.5. Same as Figure 3.4 but for flow averaged over 300 ~ 600 m. The unit vector is 40 cm/s.………………....... 51. Figure 3.6. Figure 3.6 Same as Figure 3.4 but for flow averaged over 700 ~ 1000 m. The unit vector is 30 cm/s…........ 52. Figure 3.7. (a) Variation of model-derived transport at PCM-1 from December 1994 to May 1995, (b ~ f) snapshots of the sea surface height during this period, and (g ~ k) the kinetic energy in the upper 500 m of the water column.………………………………………………. 53. - XIV -.

(13) Figure 3.8. Dependence of the Kuroshio transport on latitude. The thick solid line denotes transport integrated from the coast of Taiwan eastward to the 10 cm/s isotach at the surface. The other lines are transports integrated to five longitude lines: 122.5, 123, 123.5, 124, and 124.5°E.………………………………........................ 56. Figure 3.9. (a) Variation of volume transport as a function of the lower boundary of vertical integration at the six sections shown in Figure 3.2. Transport is also calculated using flow (b) in the downstream direction only and (c) in the upstream direction only.…………. 57. Figure 3.10 Volume fluxes at 22°N. Fluxes contributed by the northward and southward flow are shown by short-dashed and long-dashed lines, respectively (left axis). The sum of the two is plotted as a thin solid line. The thick solid line is the cumulative percentage of contribution by the northward flow from west (right axis). The gray shading indicates the location of the Lan-Yu Island…………………………………. 59 Figure 3.11 Power spectral density function for downstream transport in Figure 3.9b. The 80%, 90%, and 95% confidence intervals are shown.………………........... 60 Figure 3.12 Schematic diagram showing transports in Sv at sections in the Kuroshio east of Taiwan……………... 62 Figure 3.13 Trajectories of surface drifters passing through the region east of Taiwan from Centurioni et al., [2004]. The surface drifters were launched at a depth of 15 m during 1988 ~ 2004. The red lines and the blue lines represent the inshore path and the offshore path, respectively…………………….................................. 62. - XV -.

(14) Figure 4.1. Bathymetry and mean surface flow around Taiwan. The vector denotes the annual mean flow at 30 m compiled by the National Center for Ocean Research, Taiwan. W and E denote the locations of moorings used in Wu et al. [2005]. The dashed frame marked with “L” represents the low-velocity region……........ 76. Figure 4.2. Geostrophic velocities along 22°N. The meridional geostrophic velocity and zonal velocity are plotted for east and west of Taiwan. LY and TW denote the Lan-Yu Island and Taiwan, respectively. The positive sign represents the eastward and northward flows, respectively, for zonal and meridional geostrophic velocities…………………………………….............. 77. Figure 4.3. Panels (a) and (b) represent the variance (energy) preserving spectra of GSV west of the Lan-Yu Island (120.75 ~ 121.5°E) and east of the Lan-Yu Island (121.5 ~ 123°E), respectively. The spectrum of GSU west of Taiwan (120 ~ 120.5°E) is revealed in panel (c). The data used for panels (a) ~ (c) is from 1993 to 2006. Panel (d) shows the spectrum of WSC (2000 ~ 2005) off southwest Taiwan (119.5 ~ 120.5°E, 20.75 ~ 21.75°N)………………………………………........ 79. Figure 4.4. Wind Stress Curl (WSC) around southern Taiwan. The WSC averaged over 22.5 ~ 23°N is used for east of Taiwan, and that averaged over 21 ~ 21.5°N is used for west of Taiwan. LY and TW represent the Lan-Yu Island and Taiwan, respectively……………. 81. Figure 4.5. Zonal geostrophic velocity along 120.75°E in the northern Luzon Strait between 21.5 and 22°N. The positive sign represents the eastward flow…………... 81. Figure 4.6. Averaged wind field in (a) October-March, (b) May-August, and (c) July-August 2004. Arrows represent wind stress vector and color shading with zero contour line shows wind stress curl……………. 82. - XVI -.

(15) Figure 4.7. Modeled surface flow (0 ~ 200 m) with shading of speed in (a) December 1 ~ 31, 2000 and (b) April 1 ~ 20, 2001…………………………………………........ 84. Figure 4.8. The 40-90 day band-passed sea level anomaly along 22°N……………………………………………......... 84. - XVII -.

(16) CHAPTER 1 Introduction. 1.1 Geographic background around Taiwan The bathymetric distribution is rather complicated in the seas around Taiwan (Figure 1.1). The East China Sea and South China Sea are in the north. Figure 1.1 Bathymetry around Taiwan.. -1-.

(17) and south of Taiwan, respectively. A broad continental shelf extends from the northwest of Taiwan in the East China Sea to the southwest of Taiwan in the northern South China Sea. West of Taiwan, the Taiwan Strait connects these two marginal seas and plays an important role in material transport and nutrient budget between them [Huh and Su, 1999; Liu et al., 2000]. The wide Pacific Ocean with a deep depth over 5000 m is on the eastside of Taiwan. There are two main entrances around Taiwan exchanging water between the Pacific Ocean and the two marginal seas: the East China Sea and the South China Sea. Between Taiwan and the Luzon Island, the Luzon Strait connects the South China Sea and the Pacific Ocean, and it plays a significant role in exchanging deep water between them [Wu et al., 1999; Metzger and Hurlburt, 2001]. Off northeast Taiwan, the Kuroshio transports water into the East China Sea through the East Taiwan Channel [Nitani, 1972]. Around Taiwan, the East Asian Monsoon is the most significant atmospheric forcing. Shown as Figure 1.2, the northeasterly and southwesterly winds take turns in winter and summer. The inverse Monsoon wind and its associated wind stress curl inject obvious seasonal perturbation into the seas around Taiwan as a result of air-sea interaction. Thus, in the literature, the seasonal variability of circulation and sea surface temperature in the surrounding seas of Taiwan, including the South China Sea (e.g. Shaw and Chao [1994]; Hu et al. [2000]), the Taiwan Strait (e.g. Jan et al. [2002]; Jan and Chao [2003]; Jan et al., [2006]), and the East China Sea (e.g. Tseng et al. [2000]; Ichikawa and Beardsley [2002]), have been extensively described. Other factors also affect the currents around Taiwan, such as geography and topography, river discharge, westward propagating eddies, and variability of -2-.

(18) the Kuroshio. For example, the Kuroshio may either form a loop current or flow at a straight path when it encounters the land crevice in the Luzon Strait [Hu et al., 2000]. West of Taiwan, the Strait current flows from the South China Sea to the East China Sea through the Taiwan Strait. The current is sometimes called as the Taiwan Warm Current which has been thought as a source of the Tsushima Warm Current in the Tsushima Strait [Teague et al., 2003]. In the earlier studies, the current was regarded as a northeastward flow all year round [Wytyki, 1961]. Figure 1.2 Seasonal average wind field (COADS) around Taiwan. The vector denotes the wind speed in m/s. JFM, AMJ, JAS, and OND represent spring, summer, fall, and winter, respectively. -3-.

(19) in spite of the northeasterly wind prevailing in winter. Recently, a set of bottom-mounted Acoustic Doppler Current Profilers, deployed across the Taiwan Strait in October ~ November 1999, demonstrated that the existence of strong event-like southward currents in winter [Ko et al., 2003; Teague et al., 2003; Lin et al., 2005]. The most important current around Taiwan is the Kuroshio. The Kuroshio originates from the North Equatorial Current east of the Luzon Island, and passes the east coast of Taiwan into the East China Sea through the East Taiwan Channel [Nitani, 1972]. Some water, branched from the Kuroshio south of the East Taiwan Channel, continues flowing along the east of the Ryukyu Islands to the northeast. Before reaching the eastern Taiwan, the Kuroshio presents a complex behavior in the Luzon Strait. The Kuroshio intrusion relevant issue is one of the most important studies in the region. Some studies suggested that the Kuroshio intrudes the South China Sea all year round [Liang, 2002; Liang et al., 2003], but some preferred the seasonal intrusion that the Kuroshio intruded into the South China Sea only in winter but not in summer [Hu et al., 2000]. Westward propagating mesoscale eddies, originating from the interior Pacific Ocean, also insert some variability into the Kuroshio east of Taiwan, especially on the timescale of ~ 100 days [Yang et al., 1999; Johns et al., 2001; Zhang et al., 2001].. 1.2 Motivation Oceanic data have been acquired by several ways for the oceanic. -4-.

(20) research. The observational data are directly obtained from in-situ surveys, which are trustable but take a lot of money and manpower. Furthermore, the in-situ survey is always restricted by the bad weather conditions, especially in winter when the northeasterly wind bursts. Another is the remote sensing method observing the ocean surface condition from sensors loaded on satellites or aircrafts. Such a method obtains surface data over the global ocean in the relative shorter period than that of in-situ surveys, but it lacks for the subsurface information. The other is by means of the numerical model simulation. A massive data can be produced from numerical models for particular research purposes. However, careful validations have to be done to make sure the usability of modeled data. Because of the continuity in spatial and temporal of the modeled data, numerical models can be adopted as a powerful tool to describe the phenomena in the ocean and atmosphere, and study the associated dynamics after being carefully validated. Many factors act on the performance of a regional ocean model. Surface stress is one of the most important factors in modeling the surface circulation in the upper ocean. Except for an accurate surface forcing, how to provide fine and proper boundary conditions is in particular an important issue for the regional oceanic modeling community [Ezer, 2000; Marchesiello et al., 2001]. Therefore, the one-way nesting technique, which provides more suitable initial and boundary conditions from a larger scale model to a finer scale model, is adopted to set up a nesting model system in the thesis. Such a technique is extensively used in the atmospheric modeling community. In ocean modeling, this is also a proper way to eliminate the uncertainty on the providing of the boundary conditions for regional ocean models, and it has been used in the -5-.

(21) recent studies of the circulation in the East China Sea (e.g. Guo et al. [2003]; Guo et al. [2007]). In the thesis, the East Asian Marginal Seas (EAMS) model (1/8°×1/8°) coupled to a larger scale model (West Pacific Ocean (WPO) model or North Pacific Ocean (NPO) model) is the major model. The results of the EAMS are adopted to analyze the transports through the Taiwan Strait and the Kuroshio east of Taiwan. The Seas Around Taiwan (SAT) model (1/20°×1/20°) coupled to the EAMS model is adopted in the intra-seasonal study off southern Taiwan. There are three parts in this thesis. The first part is concerning the variability of volume transports through the Taiwan Strait and the Penghu Channel. Using in-situ current and hydrographic data, the transports in the Taiwan Strait have been studied in the literature (e.g. Jan and Chao [2002]; Wang et al. [2003]; Jan et al. [2006]). The mean transports through the Taiwan Strait and the Penghu Channel were estimated from short-term field works. The strong wintertime southward transport events, which were at first demonstrated from a set of bottom-mounted Acoustic Doppler Current Profilers in winter of 1999, are always absent from the data obtained from in-situ surveys. Therefore, in chapter 2, by taking advantage of the merit of well-validated numerical model, the mean transports through the Taiwan Strait and the Penghu Channel are estimated from the simulation data involving strong inverse current events in winter. Furthermore, linear regression lines between the simulated transports and wind stress are proposed to provide linear equations to roughly calculate a transport value from a given wind stress value which is easier to be gained. The second and third parts, presented in chapters 3 and 4, focus on variability of the Kuroshio around Taiwan. Revealed from hydrographic and -6-.

(22) current data obtained from short-term in-situ surveys, the Kuroshio east of Taiwan varies from cruise to cruise [Chu, 1974; Liu et al., 1998]. Variations of large-scale wind and mesoscale eddies could make great impacts on the Kuroshio variability. Although the progress of observational technique after 1990s supplies a better view on the mean state of the Kuroshio east of Taiwan [Liang et al., 2003], the coverage of ship-board Acoustic Doppler Current Profiler’s (sb-ADCP) data is limited in the upper ocean. Moreover, the spatial and temporal variations of the Kuroshio result in large uncertainty on estimation of mean transport of the Kuroshio. Therefore, several basic characteristics concerning the Kuroshio east of Taiwan should be addressed. How deep is the Kuroshio? How wide is the Kuroshio? Or what is the eastern boundary of the Kuroshio? How much water does the Kuroshio transport to the north through the seas east of Taiwan? What are possible causes changing the state of the Kuroshio in temporal and spatial and how do they influence the Kuroshio? In chapter 3, adopting a long-term (1982 ~ 2005) modeled velocity data with a careful validation with the results from sb-ADCPs, a detailed descriptive study concerning the spatial and temporal variations of the Kuroshio east of Taiwan is performed to address the above questions. On the other hand, the intra-seasonal variability associated with the Kuroshio around Taiwan has been suggested in some studies. Off northeast Taiwan, the 30 ~ 70 days’ intra-seasonal variability of velocity on the East Taiwan Channel was thought to be associated with the instability of the Kuroshio [Zhang et al., 2001]. The disappearance of cold dome near the shelf break in the southern East China Sea is related to the migration of the Kuroshio [Tang et al., 2000; Wu et al., 2008]. Therefore, the purposes of chapter 4 are to -7-.

(23) identify the variation of the Kuroshio off southeast Taiwan on intra-seasonal timescale between 2 weeks and 90 days, and further to introduce two possible mechanisms to address how these intra-seasonal variations are induced. Finally, the conclusions of the thesis will be given in chapter 5.. 1.3 References Ezer, T., and G. L. Mellor (2000), Sensitivity studies with the North Atlantic sigma coordinate Princeton Ocean Model, Dynamics of Atmospheres and Oceans, 32, 185 - 208. Guo, X., H. Hukuda, Y. Miyazawa, and T. Yamagata (2003), A Triply Nested Ocean Model for Simulating the Kuroshio - Roles of Horizontal Resolution on JEBAR, Journal of Physical Oceanography, 33, 146 - 169. Guo, X., Y. Miyazawa, and T. Yamagata (2007), The Kuroshio onshore intrusion along the shelf bread of the East China Sea: The origin of the Tsushima Warm Current, Journal of Physical Oceanography, 36, 2205 2231. Hu, J., H. Kawamura, H. Hong, and Y. Qi (2000), A review on the currents in the South China Sea: Seasonal circulation, South China Sea Warm Current and Kuroshio intrusion, Journal of Oceanography, 56, 607 - 624. Huh, C. - A., and C. - C. Su (1999), Sedimentation dynamics in the East China Sea elucidated from 210Pb, 137Cs and 239,240Pu, Marine Geology, 160, 183 196. -8-.

(24) Ichikawa, H., and R. C. Beardsley (2002), The current system in the Yellow and East China Seas, Journal of Oceanography, 58, 77 - 92. Jan, S., D. D. Sheu, and H. - M. Kuo (2006), Water mass and throughflow transport variability in the Taiwan Strait, Journal of Geophysical Research, 111, C12012, doi: 10.1029/2006JC003656. Jan, S., J. Wang, C. - S. Chern, and S. - Y. Chao (2002), Seasonal variation of the circulation in the Taiwan Strait, Journal of Marine Systems, 35, 249 268. Jan, S., and S. - Y. Chao (2003), Seasonal variation of volume transport in the major inflow region of the Taiwan Strait: the Penghu Channel, Deep-Sea Research II, 50, 1117 - 1126. Johns, W. E., T. N. Lee, D. Zhang, R. Zantopp, C. - T. Liu, and Y. Yang (2001), The Kuroshio east of Taiwan: Moored transport observations from WOCE PCM-1 array, Journal of Physical Oceanography, 31, 1031 1053. Ko, D. S., R. H. Preller, G. A. Jacobs, T. Y. Tang, and S. F. Lin (2003), Transport reversals at Taiwan Strait during October and November 1999, Journal of Geophysical Research, 108, C11, 3370, doi: 10.1029/ 2003JC001836. Liang, W. - D. (2002), Study of Upper Ocean Thermal and Current Variation in the South China Sea, PhD Thesis, Institute of Oceanography, National Taiwan University, Taiwan.. -9-.

(25) Liang, W. - D., T. Y. Tang, Y. J. Yang, M. T. Ko, and W. - S. Chuang (2003), Upper-ocean currents around Taiwan, Deep-Sea Research II, 50, 1085 1105. Lin, S. F., T. Y. Tang, S. Jan, and C. - J. Chen (2005), Taiwan strait current in winter, Continental Shelf Research, 25, 1023 - 1042. Liu, K. - K., T. Y. Tang, G. - C. Gong, L. - Y. Chen, and F. - K. Shiah (2000), Cross-shelf and along-shelf nutrient fluxes derived from flow fields and chemical hydrography observed in the southern East China Sea off northern Taiwan, Continental Shelf Research, 20, 493 - 523. Marchesiello, P., J. C. McWilliams, and A. Shchepetkin (2001), Open boundary conditions for long-term integration of regional oceanic models, Ocean Modelling, 3, 1 - 20. Metzger, E. J., and H. E. Hurlburt (2001), The nondeterministic nature of Kuroshio penetration and eddy shedding in the South China Sea, Journal of Physical Oceanography, 31, 1712 - 1732. Nitani, H. (1972), Beginning of the Kuroshio, in Kuroshio - Its physical aspects, p. 129 - 163, edited by H. Stommel and K. Yoshida, Univ. of Tokyo Press, Tokyo. Shaw, P. - T., and S. - Y. Chao (1994), Surface Circulation in the South China Sea, Deep-Sea Research I, 41, 1663 - 1683. Teague, W. J., G. A. Jacobs, D. S. Ko, T. Y. Tang, K. - I. Chang, and M. - S. Suk (2003), Connectivity of the Taiwan, Cheju, and Korea straits, Continental - 10 -.

(26) Shelf Research, 23, 63 - 77. Tseng, C., C. Lin, S. Chen, and C. Shyu (2000), Temporal and spatial variations of sea surface temperature in the East China Sea, Continental Shelf Research, 20, 373 - 387. Wang, Y. - H, S. Jan, and D. - P. Wang (2003), Transports and tidal current estimates in the Taiwan Strait from shipboard ADCP observations (1999 2001), Estuarine coastal and shelf science, 57, 193 - 199. Wu, C. - R., H. - F. Lu, and S. - Y. Chao (2008), A numerical study on the formation of upwelling off northeast Taiwan, Journal of Geophysical Research, In press . Wu, C. - R., P. - T. Shaw, and S. -Y. Chao (1999), Assimilating altimetric data into a South China Sea model, Journal of Geophysical Research, 104 (C12), 29987 - 30005. Wyrtki, K. (1961), Physical oceanography of the southeast Asian waters, Scientific Results of Marine Investigation of the South China Sea and the Gulf of Thailand, NAGA Report Vol. 2, Scripps Institution of Oceanography, La Jolla, California, 195 pp. Yang, Y., C. - T. Liu, J. - H. Hu, and M. Koga (1999), Taiwan Current (Kuroshio) and impinging Eddies, Journal of Oceanography, 55, 609 617. Zhang, D., T. N. Lee, W. E. Johns, C. - T. Liu, and R. Zantopp (2001), The Kuroshio east of Taiwan: Modes of variability and relationship to interior - 11 -.

(27) ocean mesoscale eddies, Journal of Physical Oceanography, 31, 1054 1074.. - 12 -.

(28) CHAPTER 2 Volume transport through the Taiwan Strait: a numerical study An edited version of this paper was published by TAO. Copyright (2005) TAO. Wu, C. - R., and Y. - C. Hsin (2005), Volume Transport Through the Taiwan Strait: A Numerical Study, Terrestrial, Atmospheric, and Oceanic Sciences, 16 (2), 377 - 391.. 2.0 Abstract A fine grid resolution model with realistic bathymetry was constructed to study the spatial and temporal structures of flow through the Taiwan Strait where observations are limited. The model covers an expanded domain that includes the entire East China Sea and South China Sea, as well as the region occupied by the Kuroshio. The fine-resolution model derives its open boundary conditions from a larger scale Western Pacific Ocean model. Two numerical weather products from European Center for Medium-Range Weather Forecasts and National Centers for Environmental Prediction, and one satellite observation-based wind set (QuikSCAT/NCEP) are used to force the ocean model. Model experiments suggested that the best simulation is achieved when the model is driven by the QuikSCAT/NCEP wind forcing. Several important features are reproduced in the model simulation. The volume transport is northward and largest in summer while minimal volume transport is southward and occurs in fall and winter. The general trend of volume transport is related to the seasonal reversal of monsoon winds. The present model also suggests that. - 13 -.

(29) flow in the entire Taiwan Strait is to the southwest during periods of strong northeasterly wind. The annual average transport based on the present model is 1.09 Sv (1 Sv=106 m3/s), which is smaller than most published values based on shipboard Acoustic Doppler Current Profiler (sb-ADCP) observations. The result suggests that sb-ADCP observations are biased toward estimates in summer and fair weather since bad weather during the winter northeast monsoon often prevents seagoing observations.. 2.1 Introduction The Taiwan Strait connects the South China Sea with the East China Sea. The orientation of the strait is approximately southwest to northeast. Except for. Figure 2.1 (a) The integrated domain of the EAMS model with realistic bathymetry. (b) The study area with locations of mooring stations (triangles) and the Penghu Channel (PHC). The horizontal line across the Penghu Island is chosen to calculate the strait-wide volume transport from model. The color shading represents the bottom topography. - 14 -.

(30) the deep Penghu Channel in the southeastern corner, the Strait is generally shallower than 60 m (Figure 2.1b). Several studies suggested that the Taiwan Strait, although shallow, is essential to material transport in and out of the East China Sea. For example, Huh and Su [1999] reported that the Taiwan Strait transport contributed about one third of the total sediment input into the East China Sea. Liu et al. [2000] found that the transport through the Taiwan Strait plays a major role in the circulation and the nutrient balance over the East China Sea. Isobe [1999] pointed out that the Tsushima Current originates from the Taiwan Strait year round except during fall. Despite the importance of mass flux through the Taiwan Strait, data from direct current measurements are limited. Composite velocities obtained from shipboard Acoustic Doppler Current Profilers (sb-ADCP) between 1990 and 2001 indicate northward flow in the Taiwan Strait year round [Liang et al., 2003]. Southward flow during prevailing northeasterly wind occurred occasionally in the data of a moored current meter deployed in the Penghu Channel between March and October [Chuang, 1985; Chuang, 1986]. On the other hand, from the distribution of water properties, Chen [2003] argued that water in the Taiwan Strait in winter should be predominantly from the East China Sea. Northward flow occurs in winter only during sudden relaxation of the steady northeasterly wind. Recent bottom-mounted ADCPs deployed in the Taiwan Strait from October to November 1999 further demonstrated that strong southwestward flow could occur during strong northeasterly wind bursts at a biweekly period [Teague et al., 2003; Ko et al., 2003]. Based on the analysis of 2.5-year (1999 ~ 2001) sb-ADCP data, Wang et al. [2003] provided quantitative estimates for the mean current and total - 15 -.

(31) transport through the Taiwan Strait. The average velocity is about 0.40 m/s, and the mean transport through the Taiwan Strait is northward at 1.8 Sv (1 Sv=106 m3/s). They also pointed out that the maximum seasonal transport occurs in summer at 2.7 Sv, northward. The minimum transport is in winter, at 0.9 Sv northward. Wyrtki’s [1961] bimonthly transport estimates are 0.5 ~ 1.0 Sv northward in summer, 0.5 Sv southward in fall and winter, and 0.0 Sv in spring. Although the annual mean transport of 1.8 Sv by Wang et al. [2003] is different from the earlier estimate of 0.0 Sv by Wyrtki [1961], the ranges of seasonal variation (about 1.7 Sv) in these two estimates are similar. Recent sb-ADCP observations showed that the northward flow through the Penghu Channel, the only deep passage in the Taiwan Strait, is the major pathway for flow in the Taiwan Strait [Jan and Chao, 2003]. The volume transports through the Penghu Channel calculated by Jan and Chao [2003] are -0.11 ~ 0.02, 0.56 ~ 1.10, 1.26 ~ 1.72 and 0.76 Sv in winter, spring, summer and fall, respectively. The strong seasonal variability with generally northward transport is evident both in the Taiwan Strait and the Penghu Channel [Jan and Chao, 2003]. Nevertheless, these transport estimates are based on data of limited spatial and temporal coverage. It seems necessary to use new-generation models with realistic forcing and higher resolution to provide better estimates for the transports through the Taiwan Strait. In this work, we study the volume transport through the Taiwan Strait using the Princeton Ocean Model (POM, see section 2.2 for details) with realistic topography and forcing at a horizontal resolution of 1/8° embedded in an expanded domain model. The expanded domain eliminates the ambiguities in the upstream boundary conditions. The primary objective of this study is to - 16 -.

(32) describe volume transports through the Taiwan Strait and the Penghu Channel. We will also attempt to relate the model results to observations.. 2.2 The numerical model The East Asian Marginal Seas (EAMS) model used here is a sigma-coordinate version of the Blumberg and Mellor [1987] hydrodynamic model. The three-dimensional, free surface model solves the primitive equations for momentum, salt and heat. It includes a 2.5-level turbulence closure sub-model developed by Mellor and Yamada [Mellor and Yamada, 1974; Mellor and Yamada, 1982] and the Smagorinsky formulation for horizontal mixing [Oey et al., 1985]. Additional information on the model can be found in Blumberg and Mellor [1987]. The domain of the EAMS model with realistic bathymetry is presented in Figure 2.1a. The horizontal grid size is 1/8° and there are 26 sigma levels in the vertical. On the open boundaries, the EAMS model derives its boundary condition from a larger-scale West Pacific Ocean (WPO) model. The WPO model is based on the Miami Isopycnic Coordinate Ocean Model (MICOM) and has a horizontal resolution of 1/4° and 15 isopycnic layers [Liang, 2002]. The WPO model domain extends from 95°E to 160°E in longitude, and from 20.8°S to 45.1°N in latitude. The WPO model driven by monthly climatological fluxes from European Center for the Medium-Range Weather Forecasts (ECMWF) is first spun up for 10 years from rest and then continuously forced using 1996 ~ 2003 ECMWF daily wind data. A detailed description of the WPO model has been given by Liang [2002].. - 17 -.

(33) The Blumberg and Mellor model uses the mode splitting technique, in which the separation of the vertically integrated governing equations (barotropic, external mode) and the equations governing vertical structure (baroclinic, internal mode) are used. Boundary conditions are formulated for the barotropic and baroclinic modes separately and then adjusted to take into account the different truncation errors for those modes [Blumberg and Mellor, 1987]. The one-way coupling between the EAMS and WPO models is described below. The barotropic, vertically averaged velocities on the open boundaries of the EAMS model were estimated by the Flather [1976] formulation:. u n = u n0 +. g (η − η 0 ) H. (1). where u n is the vertically averaged outward normal component of the velocity on the open boundary of the EAMS model at time t, u n0 is the vertically averaged normal component of the velocity on the open boundary at time t estimated from the WPO model.. The model sea surface height η is. calculated from the continuity equation and is located half of a grid inside of the open boundary in the EAMS model domain. The WPO model sea surface height η 0 is located on the open boundary of the EAMS model. The water depth on the open boundary is H, and g is the gravitational acceleration. An adjustment procedure was used to balance the net transport from the WPO - 18 -.

(34) model with the associated variation of sea surface height. Outputs from the WPO model have daily records of sea surface height and transports, which were interpolated to the EAMS model grid using bivariate interpolation and to the EAMS model time step linearly in order to form η 0 and u n0 in Equation (1). As a result, there is a lack of continuity between the total transport through the open boundaries estimated from u n0 and the total change in the sea surface height of the modeling area estimated from η 0 . A value, inversely proportional to the water depth on the open boundaries, was added to u n0 along the open boundaries to balance the transport. Baroclinic velocities on the open boundaries of the EAMS model have been determined using an inflow condition for the normal component of the velocity [Mellor, 2003], i.e., daily baroclinic velocities from the WPO model were spatially interpolated and assigned to the open lateral boundary grids of the EAMS model. For temperature and salinity on the open boundaries, upstream advection boundary conditions were used [Mellor, 2003]. Advected values calculated from the WPO profiles of temperature and salinity were interpolated to the EAMS model grid. The EAMS model was initialized by the temperature and salinity fields of the WPO model outputs in January 1999 and was under climatology forcing for one year. After the spin-up period, the EAMS model was forced with different wind data sets to investigate the sensitivity of transport to various atmospheric wind products. The three different wind data sets are from ECMWF, the National Centers for Environmental Prediction (NCEP) [Kalnay et al., 1996], and QuikSCAT/NCEP (NASA Quick Scatterometer/NCEP). - 19 -.

(35) ECMWF products include 10 meter winds and surface stresses (6-hourly at 2.5˚ resolution). The NCEP forcing (also 6-hourly at 2.5˚ resolution) is a surface stress product. The blended QuikSCAT/NCEP wind stress data set is one of the most up-to-date high-resolution data sets of ocean surface winds at the present time. We adopted 6-hourly maps of 10 m zonal and meridional wind components at a resolution of 0.5° × 0.5°. The maps are derived from a space and time blend of QuikSCAT-DIRTH satellite scatterometer observations and NCEP analyses [Milliff et al., 1999]. The EAMS model was forced by the three 6-hourly surface wind stress data sets and coupled (as described above) at the open boundaries to the WPO model. The model was then run for 1999 ~ 2003 period. The only difference in all model experiments presented here is wind forcing.. 2.3 Results and discussions 2.3.1 Model experiments and validation To display the ocean model response to atmospheric wind forcing, three experiments EC (ECMWF), NC (NCEP) and QS (QuikSCAT/NCEP) are conducted. Each of these experiments is initialized from the tenth-year outputs from the WPO model with identical boundary conditions, and is integrated for 5 years with three different wind forcing data sets. As mentioned in the introduction, the observed velocities in the Taiwan Strait are limited. Figure 2.2a shows the only strait-wide transport data available to date (after Teague et al. [2003] and Ko et al. [2003]). From - 20 -.

(36) October to November 1999, transport through the Taiwan Strait was measured with four bottom-mounted ADCPs (the locations as shown in Figure 2.1b). The time series in Figure 2.2a shows transport reversals at a biweekly period, possibly caused by the biweekly atmospheric winter fronts. For comparison and validation, the model-derived volume transports together with the observed transport across the Taiwan Strait are presented in Figure 2.2b. Differences are. Figure 2.2 (a) Time series of observed transport through the Taiwan Strait calculated from four bottom-mounted ADCPs (from Teague et al. [2003] and Ko et al. [2003]). (b) The model-derived volume transports across the Taiwan Strait. The red, blue, and purple lines represent the transports estimated from three numerical experiments QS, EC and NC, respectively. The observed transport is also plotted (black line) for comparison. - 21 -.

(37) significant among the three model runs. In experiment EC, all model transports are positive (northward) during the entire period. This is not consistent with the observation. On the other hand, experiments NC and QS showed five reversal events similar to the observation. Furthermore, the peak-to-peak comparison indicates that the result from experiment QS has better agreement with observations than that from experiment NC. For example, both transports from observation and experiment QS reach around -5 Sv (southward) on October 17, 1999, but the corresponding volume transport in experiment NC is only around -3 Sv. The comparison indicates that QuikSCAT/NCEP wind forcing produces much more realistic results and supports the existence of strong southward current bursts observed by bottom-mounted ADCPs. The occurrence of southward current bursts explains why estimates from multiple-years averages missed the southward flow. To our knowledge, this is the first time that a southward transport is produced in a numerical model without any data assimilation. Ko et al. [2003] also showed the existence of a southwestward flow in a model with data assimilation. Their model assimilated satellite altimeter data, Muti-Channel Sea Surface Temperature (MCSST), and the static climatology from Modular Ocean Data Assimilation System (MODAS) to produce the three-dimensional fields of temperature and salinity.. 2.3.2 Transport through the Penghu Channel Figure 2.3 shows model-derived transport in experiment QS through the Penghu Channel. Several recent measurements are also shown for comparison. Pink segments, including ± 0.20 Sv error bars, indicate sb-ADCP - 22 -.

(38) Figure 2.3 Model-derived transport compared to observations through the Penghu Channel. Pink segments and red circle are calculated from sb-ADCP measurements by Jan and Chao [2003] and Wang et al. [2004], respectively. Blue stars are calculated from sb-ADCP observations by Dr. Ruo-Shan Tseng (unpublished data).. Figure 2.4 Relationship between the model-derived transport through the Penghu Channel and the along-strait wind stress.. measurements from Jan and Chao [2003]. Model-produced transports are generally consistent with these segments. Seasonal variations are clearly evident in both the data of Jan and Chao [2003] and the present model. Largest northward transport appears in summer, and the transport is much weaker or even southward in fall and winter. The seasonal variation is consistent with the - 23 -.

(39) seasonal reversal of the East Asian monsoon. The optimal solution (red circle), calculated from a sb-ADCP survey on 17 ~ 20 May 1999 [Wang et al., 2004], is slightly higher than the model predicted value. Wang et al. [2004] pointed out that there was a strong southerly wind burst prior to the field study and the wind burst might have increased the northward flow. Blue stars represent transports calculated from sb-ADCP observations by Dr. Ruo-Shan Tseng (unpublished data). Again, the model transports are comparable to these values. The annual averaged transport based on the present model is 0.55 Sv, which is significantly less than the value 0.86 Sv calculated from sb-ADCP measurements [Jan and Chao, 2003]. Bad weather often prevents seagoing operations in the Taiwan Strait and the Penghu Channel, especially during winter when the strong northeast monsoon dominates. Thus, sb-ADCP observations are lacking during periods when the southward flow is most likely to appear. Excluding those data points, the annual averaged transport from sb-ADCP measurements is overestimated. The transport in the Penghu Channel is modulated by the East Asian monsoon, northeasterly in winter and southwesterly in summer. The strong seasonal variation is evident in the model-produced transport (Figure 2.3). For many years, researchers have tried to provide a simple linear relationship between the transport and the along-strait wind stress. The purpose is to provide a quick estimate of the volume transport in the area using wind stress information, which is easier to acquire. Following this path, Figure 2.4 compares the calculated transport with the QuikSCAT/NCEP wind stress averaged over the Channel from 119.5°E to 120°E and from 23°N to 24°N. The best fit for the transport and the local wind stress is achieved using two - 24 -.

(40) regression lines. One line represents the situation during strong winds (< -1.5 dyne/cm2) and the other represents condition with weak winds (> -1.5 dyne/cm2). The equation for the blue line (correlation coefficient γ = 0.92) is. Transport (Sv) = 0.18 × wind stress (dyne/cm2) + 0.44,. WS < -1.5. (2). WS > -1.5. (3). The equation for the red line (γ = 0.94) is. Transport (Sv) = 0.52 × wind stress (dyne/cm2) + 0.95,. In general, the blue line represents the strong wind conditions that occur mostly during winter. On the other hand, the red line represents the conditions for the rest of the year when the wind stress is weak or northward. The two regression lines show the different responses of volume transport through the Penghu Channel to wind forcing. The slope of the blue line is less than that of the red line, indicating that as the wind stress increases, transport increases much slower under strong northeasterly wind in winter than in other seasons. It is suggested that a northward pressure gradient not forced by local wind is present.. - 25 -.

(41) 2.3.3 Transport through the Taiwan Strait Figure 2.5 shows the model-derived transport together with some limited observed transports through the Taiwan Strait. Blue stars and red circles represent strait-wide volume transports calculated from sb-ADCP observations by Dr. Ruo-Shan Tseng (unpublished data) and by Chung et al. [2001]. Similar to the volume transport through the Penghu Channel, the model-derived transports through the Taiwan Strait are comparable to the observed values. The average strait-wide transport of 1.09 Sv is about double the average transport through the Penghu Channel although the cross-sectional area of the Penghu Channel is only one-fifth of that of the Taiwan Strait. Therefore, currents are much stronger in the Penghu Channel than in the rest of the strait. The model result is consistent with the well-known statement that the Penghu Channel is the major pathway for the northward flow entering the Taiwan Strait (e.g. Wang and Chern [1988] and Jan and Chao [2003]). Strong seasonal variation in the Penghu Channel is evident in Figure 2.5 as well. The volume transport is northward and largest in summer. It is minimum and even southward in fall and winter. The trend of the volume transport is related to the seasonal reversal of the monsoons. The occasional strong northeasterly wind bursts in fall or winter drive currents southward and produce large and negative transport up to -5 Sv (Figure 2.5). These events of winter fronts are seldom observed because of severe weather, but are important to balance the nutrient budget. In addition to the seasonal variation, inter-annual variation also exists. The purple line in Figure 2.5 shows the smoothed transport. The mean transport - 26 -.

(42) Figure 2.5 Model-derived transport and observed transports in the Taiwan Strait. Blue stars and red circles represent strait-wide volume transports calculated from sb-ADCP measurements by Dr. Ruo-Shan Tseng (unpublished data) and by Chung et al. [2001], respectively. Purple line represents monthly mean model-derived transport.. Figure 2.6 Relationship between model-derived transport through the Taiwan Strait and the along-strait wind stress.. in summer 2003 is largest in the 5-year period. On the other hand, southward transport is smallest in fall and winter of 2002. Furthermore, variations of volume transport in summer are much smaller than those in winter, indicating that flow conditions in the Taiwan Strait are more complex during wintertime. - 27 -.

(43) Several factors could account for the phenomenon, e.g., local effects of the northeast monsoon and sea level differences between the East China Sea and South China Sea. The annual average transport of 1.09 Sv is much smaller than most observed values, which contain uncertainties due to coarse spatial resolution and lack of winter measurements. Figure 2.6 shows the relationship between volume transport through the Taiwan Strait and along-strait wind stress obtained by averaging the QuikSCAT/NCEP wind stress in the domain from 118°E to 120°E and from 23°N to 25°N. Unlike the two regression lines shown in Figure 2.4, only one simple regression line suffices in the figure, and its correlation coefficient (γ) is equal to 0.82. The equation is:. Transport (Sv) = 1.06 × wind stress (dyne/cm2) + 1.99. (4). The volume transport is 1.99 Sv northward when wind stress is zero. The result suggests that the strait-wide volume transport is contributed by not only wind stress but also a northward pressure gradient force. Figure 2.7 shows the model-derived pressure gradient force between north and south entrances of the Taiwan Strait during the period from 1999 to 2003. The pressure gradient is calculated from model sea surface height difference. The sea surface height at the north entrance is averaged over the domain from 119°E to 121.5°E and from 25°N to 25.25°N and that at the south. - 28 -.

(44) entrance is averaged over the domain from 117.25°E to 120.25°E and from 23.5°N to 23.75°N. The pressure gradient is always negative because sea surface is always lower at the north entrance of the Taiwan Strait than at the south end. This pressure gradient forces a mean current northward year round and is not driven by local winds. However, the large-scale monsoon is still responsible for building up the sea level in the south. The monsoon wind field is affected by coastline, resulting in the large difference between the sea surface height in the East China Sea and South China Sea. The Kuroshio intrusion through the Luzon Strait is also a possible source of higher sea level south of the Taiwan Strait. There is significant seasonal variation in Figure 2.7. For example, the pressure gradient force is generally larger in winter than in summer. This seasonal variation of the pressure gradient force might affect the volume transport as well. However, it seems that its effect is not significant in this study.. Figure 2.7 Model-derived pressure gradient force between north and south entrances of the Taiwan Strait during the period from 1999 to 2003. The pressure gradient is calculated from model sea surface height difference. - 29 -.

(45) We have excluded the volume transport caused by the pressure gradient force and have done regression analysis with the along-strait wind stress. The regression line is similar to that in Figure 2.6 with correlation coefficient (γ) increasing slightly from 0.82 (Figure 2.6) to 0.84. Chuang [1985] proposed a simple equation to describe the balance of along-channel momentum for friction dominated steady flow in a straight. Figure 2.8 Comparison between model-derived transport (red line) and transport estimated using a resistance coefficient (blue line) during the period from 1999 to 2003.. Figure 2.9 Comparison of upper-layer temperatures (0 ~ 50 m) to the east (black line) and west (red line) of the Penghu Island during the period from 1999 to 2003. The temperatures are averaged over the regions of black and red rectangles shown in the upper panel. - 30 -.

(46) channel. Using the regression equation (4) as well as Chuang’s [1985] equation, a resistance coefficient was estimated. An approximate transport was thereafter calculated from the wind stress, resistance coefficient, and model sea surface height based on Chuang’s simple equation. The agreement between the model-derived transport (red line) and the approximate transport (blue line) in Figure 2.8 supports the friction dominant scenario. From Figures 2.4 and 2.6, model-derived transports through the Taiwan Strait and the Penghu Channel, respectively, are -6 and -1 Sv at WS = -8 dyne/cm2, and are -2 and -0.5 Sv at WS = -4 dyne/cm2. The results suggest that under strong northeast monsoon, most southward transport in the Taiwan Strait is to the west of the Penghu Island, where the current along the coast of China transports cold coastal water southward. The modeled temperature distribution confirmed this statement. Figure 2.9 shows a comparison of upper-layer temperatures to the east and west of Penghu Island during the period from 1999 to 2003. The upper-layer temperatures were averaged vertically from surface to 50 m deep. All five-year data show that temperature is 1 ~ 2 °C lower west of the Penghu Island than east of it in winter. The results are consistent with earlier observations that cold, fresh China coastal water in the western portion of the Taiwan Strait was forced southward in winter under the strong and steady northeast monsoon.. 2.4 Conclusions Most studies to date support that mean currents in the Penghu Channel. - 31 -.

(47) are northward throughout the year, as first proposed by Chuang [1985]. Southward flow in winter was shown by Teague et al. [2003] and Ko et al. [2003]. The present model further shows that southward flow is possible during the period from 1999 to 2003. The speed is high during a strong northeast monsoon. Consequently, volume transport in the Taiwan Strait could be southward in winter. Model experiments also suggest that the best simulation is achieved by the QuikSCAT/NCEP wind forcing. The seasonal variation of the modeled transport in the Strait is related to the seasonal reversal of the East Asian monsoon. The annual averaged model-derived transports through the Taiwan Strait and the Penghu Channel are northward at 1.09 Sv and 0.55 Sv, respectively. Transports calculated from sb-ADCP observations could be biased because of lack of winter measurements. Further, the model results suggest that the net transport across the strait is southward under strong northeast monsoon, with a major contribution from the western portion of the Taiwan Strait. The modeled temperature distribution confirms that transport in the western portion brings cold China coastal water southward under strong northeasterly wind in winter. An innovation in this study is to use two regression lines rather than one to describe the relationship between the volume transport and wind stress in the Penghu Channel. The two regimes of wind stress clearly demonstrate the different dynamic responses of transport to wind stress and demonstrate the existence of a north-south pressure gradient force. Knowledge of volume transports through the Taiwan Strait and the Penghu Channel obtained from this study could provide understanding in mass fluxes and nutrient balance in the region. Ongoing work is to develop a Taiwan Strait model with finer - 32 -.

(48) horizontal resolution of 5 km. The fine-resolution model will provide further information on the flow pattern and its characteristics in the region in the near future.. 2.5 References Blumberg, A. F., and G. L. Mellor (1987), A description of a three-dimensional coastal ocean circulation model. In: Heaps, N.S. (Ed.), Coastal and Estuarine Sciences 4: Three Dimensional Coastal Models. AGU, Washington, DC, 1 - 16p. Chen, C. T. A. (2003), Rare northward flow in the Taiwan Strait in winter: A note, Continental Shelf Research, 23, 387 - 391. Chuang, W. - S. (1985), Dynamics of subtidal flow in the Taiwan Strait, Journal of Oceanography, 41, 83 - 90. Chuang, W. - S. (1986), A note on the driving mechanisms of current in the Taiwan Strait, Journal of The Oceanographical Society of Japan, 42, 355 - 361. Chung, S. - W., S. Jan, and K. - K. Liu (2001), Nutrient fluxes through the Taiwan. Strait. in. spring. and. summer. 1999, Journal. of. The. Oceanographical Society of Japan, 57, 47 - 53. Flather, R. A. (1976), A tidal model of the north-west European continental shelf, Memories de la Society Royal des Sciences de Liege, 6 (10), 141 -. - 33 -.

(49) 164. Huh, C. - A. and C. - C. Su (1999), Sedimentation dynamics in the East China Sea elucidated from 210Pb, 137Cs and 239,240Pu, Marine Geology, 160, 183 196. Isobe, A. (1999), On the origin of the Tsushima Warm Current and its seasonality, Continental Shelf Research, 19, 117 - 133. Jan, S., and S. - Y. Chao (2003): Seasonal variation of volume transport in the major inflow region of the Taiwan Strait: the Penghu Channel, Deep-Sea Research II, 50, 1117 - 1126. Kalnay, E., M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, Y. Zhu, A. Leetmma, B. Reynolds, M. Chelliah, W. Ebisuzaki, W. Higgins, J. Janowiak, K. C. Mo, C. Ropelewski, J. Wang, R. Jenne, and D. Joseph (1996), The NCEP/NCAR 40-year reanalysis project, Bulletin of the American Meteorological Society, 77, 437 - 471. Ko, D. S., R. H. Preller, G. A. Jacobs, T. Y. Tang, and S. F. Lin (2003), Transport reversals at Taiwan Strait during October and November 1999, Journal of Geophysical Research, 108, C11, 3370, doi: 10.1029/ 2003JC001836. Liang, W. - D. (2002), Study of upper ocean thermal and current variation in the South China Sea, Ph. D. Thesis, Institute of Oceanography, National Taiwan University, 127 pp.. - 34 -.

(50) Liang, W. - D., T. Y. Tang, Y. J. Yang, M. T. Ko, and W. - S. Chuang (2003), Upper-ocean currents around Taiwan, Deep-Sea Research II, 50, 1085 1105. Liu, K. - K., T. Y. Tang, G. - C. Gong, L. - Y. Chen, and F. - K. Shiah (2000), Cross-shelf and along-shelf nutrient fluxes derived from flow fields and chemical hydrography observed in the southern East China Sea off northern Taiwan, Continental Shelf Research, 20, 493 - 523. Mellor, G. L. (2004), Users guide for a three-dimensional, primitive equation, numerical ocean model, Program in Atmospheric and Oceanic Sciences, Princeton University, 53 pp. Mellor, G. L., and T. Yamada (1974), A hierarchy of turbulence closure models for planetary boundary layers, Journal of Atmospheric Science, 31, 1791 1806. Mellor, G. L., and T. Yamada (1982), Development of a turbulence closure model for geophysical fluid problems, Review of Geophysics and Space Physics, 20, 851 - 875. Milliff, R. F., W.G. Large, J. Morzel, G. Danabasoglu, and T. M. Chin (1999), Ocean general circulation model sensitivity to forcing from scatterometer winds, Journal of Geophysical Research, 104, 11337 - 11358. Oey, L. - Y., G. L. Mellor, and R. I. Hires (1985), A three-dimensional simulation of the Hudson- Raritan estuary. Part I: Description of the model and model simulations, Journal of Physical Oceanography, 15,. - 35 -.

(51) 1676 - 1692. Teague, W. J., G. A. Jacobs, D. S. Ko, T.Y. Tang, K. - I. Chang, and M. - S. Suk (2003), Connectivity of the Taiwan, Cheju, and Korea Straits, Continental Shelf Research, 23, 63 - 77. Wang, J., and C. S. Chern (1988), On the Kuroshio branch in the Taiwan Strait during wintertime, Progress in Oceanography, 21, 469 - 491. Wang, Y. - H, S. Jan, and D. - P. Wang (2003), Transports and tidal current estimates in the Taiwan Strait from shipboard ADCP observations (1999 2001), Estuarine coastal and shelf science, 57, 193 - 199. Wang, Y. - H., L. - Y. Chiao, K. M. M. Lwiza, and D. - P. Wang (2004), Analysis of flow at the gate of Taiwan Strait, Journal of Geophysical Research, 109, C02025, doi: 10.1029/2003JC001937. Wyrtki, K. (1961), Physical oceanography of the southeast Asian waters, Scientific Results of Marine Investigation of the South China Sea and the Gulf of Thailand, NAGA Report Vol. 2, Scripps Institution of Oceanography, La Jolla, California, 195 pp.. - 36 -.

(52) CHAPTER 3 Spatial and Temporal Variations of the Kuroshio East of Taiwan, 1982-2005: A numerical study An edited version of this paper was published by AGU. Copyright (2008) American Geophysical Union. Hsin, Y. - C., C. - R. Wu, and P. - T. Shaw (2008), Spatial and temporal variations of the Kuroshio east of Taiwan, 1982–2005: A numerical study, Journal of Geophysical Research, 113, C04002, doi: 10.1029/2007JC004485. 3.0 Abstract A 1/8º East Asian Marginal Seas Model nested to a larger-domain North Pacific Ocean Model is implemented over a span of 24 years from 1982 to 2005 to investigate the spatial and temporal variations of the Kuroshio east of Taiwan. Between 22 and 25°N, the mean state and variability of the Kuroshio, such as the two paths observed in the trajectories of surface drifters southeast of Taiwan and the branching of the Kuroshio northeast of Taiwan, are well reproduced by the model. Southeast of Taiwan, the Kuroshio is mostly in the top 300 m in the inshore path but extends to 600 m in the offshore path. Northeast of Taiwan, the Kuroshio follows the shelf edge in the East China Sea but may branch along a path south of the Ryukyu Islands. The latter path often meanders southward, and a significant portion of the Kuroshio transport may be diverted to this path. The Kuroshio extends from the coast to 123°E ~ 123.5°E between 22°N and 25°N with currents reaching a depth of 1000 m at some latitudes. The Kuroshio transports averaged over five sections east of - 37 -.

(53) Taiwan are 28.4 ± 5.0 Sv and 32.7 ± 4.4 Sv with and without the contribution from the countercurrent, respectively.. 3.1 Introduction The Kuroshio is the most important current in the seas east of Taiwan. It originates from the North Equatorial Current that bifurcates between 12° and 15°N in the western equatorial Pacific Ocean [Qu and Lukas, 2003]. The southward branch is the Mindanao Current, and the northward branch becomes the Kuroshio [Nitani, 1972; Qiu and Lukas, 1996; Qu et al., 1998; Centurioni et al., 2004; Yaremchuk and Ou, 2004]. The Kuroshio flows northward along the coasts of the Luzon Island and Taiwan, continues to the shelf edge of the East China Sea, and finally becomes the Kuroshio Extension after departing from Japan [Nitani, 1972]. The Kuroshio transports warm water from the tropical ocean to mid-latitudes and is an important source of heat for the atmosphere in the global heat balance [Qu, 2003]. The Kuroshio east of Taiwan has been studied extensively using in-situ data from both hydrographic and current meter measurements. Based on hydrographic surveys from eight cruises, Chu [1974] found large spatial and temporal flow variability in the Kuroshio east of Taiwan. For example, the distance of the high velocity core from the coast of Taiwan at 23.75°N ranges from 30 to 120 km with maximum current speeds between 60 and 120 cm/s. Table 3.1 summarizes the estimates of the Kuroshio transport east of Taiwan in earlier studies. The transport varies between 15 and 44 Sv (1 Sv = 106 m3/s). - 38 -.

(54) Table 3.1 Mean Kuroshio transport east of Taiwan in earlier observations Publication. Nitani [1972] Nitani [1972] Chu [1976]. Period Sep. 1965 May 1967 (4 cruises) 1965 - 1967 (5 cruises) 1942 - 1966 (5 cruises) 1974 - 1975 (6 cruises). Liu [1983]. Jul. 26-29, 1983 (1 cruise). 24°N. Geostrophic. 44.2. Liu et al. [1998]. Oct. 1990 May 1995 (12 cruises). ETC** (~ 24.5°N). Adjusted geostrophic & Sb-ADCP. 19.7 (0 - 350 m) 22.6 (0 - bottom). Johns et al. [2001]. Sep. 19, 1994 May 27, 1996. ETC (~ 24.5°N). Mooring array (3 methods). 21.5 ± 2.5. Hwang and Kao [2002]. Dec. 1992 Apr. 2000. Northeast (~ 24.5°N) and Southeast (~ 22°N) of Taiwan. TOPEX/Poseidon Altimeter. 19 ± 6 (Northeast) 26 ± 5 (Southeast). Gilson and Roemmich [2002]. 1993 - 2001 (34 cruises). Southeast of Taiwan (0 - 800 m). Geostrophic (RD = 800 m). 22.0 ± 1.5. Chu [1970]. Position. Method. Mean Q (Sv). 21.75 23.75°N. Geostrophic (RD* = 800 dbar). 17.8 - 20.4. ~ 23°N 25°N ~ 24°N. Geostrophic (RD = 1200 dbar) Geostrophic (RD = 1200 dbar) Geostrophic (RD = 800 dbar). Nov. 1992 Yang and Geostrophic Jun. 1996 21.75°N Liu (RD = 1000 dbar) [2003] (8 cruises) 22 - 25°N Liang et al. 1991 - 2000 Sb-ADCP [2003] (0 - 300 m) * RD=reference depth; ** ETC=East Taiwan Channel.. 40 33 29.3. 22.9 ± 14.2 15.4 - 24.3. with a smaller range of 15 ~ 26 Sv in studies after 1990. The large range of transport values may be contributed by the variation of the flow in the Kuroshio but may also be a result of the methods and data used in computation. For example, Nitani [1972] estimated the Kuroshio transport relative to several - 39 -.

(55) reference pressure surfaces; the transport relative to the 800 db pressure surface is about 80 % of the value relative to the 1200 db pressure surface. Recent composite pictures of the velocity field obtained from shipboard Acoustic Doppler Current Profilers (Sb-ADCP) between 1990 and 2001 [Liang et al., 2003] indicated that the Kuroshio is 150 ~ 200 km wide and splits into two paths when reaching the Lan-Yu Island (Figure 3.1c). The two paths join again at 23°N. Afterward, the Kuroshio flows into the East China Sea through the East Taiwan Channel (ETC) between Taiwan and the Ishigakijima (Figure 3.1c). A mooring array was deployed during the World Ocean Circulation Experiment (WOCE) along an extensively studied section called PCM-1 in the ETC between September 1994 and May 1996. The flow direction during this period varies greatly, indicating large meandering of the current [Zhang et al.,. Figure 3.1 The nested system of numerical simulation. (a) The NPO model domain with the EAMS domain in a box. (b) The EAMS model domain and bathymetry. (c) Enlarged view of bathymetry in the seas around Taiwan. - 40 -.