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Kuroshio intrusion in the Luzon Strait in an eddy-resolving ocean model and air-sea coupled model
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Qian Yang1, 2, Hailong Liu1, 2, *, Pengfei Lin1, 2, Yiwen Li1, 2
Acta Oceanologica Sinica | 2020, 39(11) : 52 - 68
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Acta Oceanologica Sinica | 2020, 39(11): 52-68
• Physical Oceanography, Marine Meteorology and Marine Physics •
Kuroshio intrusion in the Luzon Strait in an eddy-resolving ocean model and air-sea coupled model
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Qian Yang1, 2, Hailong Liu1, 2, *, Pengfei Lin1, 2, Yiwen Li1, 2
Affiliations
  • 1 State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
  • 2 College of Earth Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
Published: 2020-11-25 doi: 10.1007/s13131-020-1670-5
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The Kuroshio intrusion in a quasi-global eddy-resolving model (LICOMH) and a fully air-sea coupled model (LICOMHC) was evaluated against observations. We found that the Kuroshio intrusion was exaggerated in the former, while biases were significantly attenuated in the latter. Luzon Strait transport (LST) in winter was reduced from –8.8×106 m3/s in LICOMH to –6.0×106 m3/s in LICOMHC. Further analysis showed that different LST values could be explained by different large-scale and local surface wind stresses and the eddies east to the Luzon Strait as well. The relatively stronger cyclonic eddies in LICOMH northeast of the Luzon Island led to weak Kuroshio transport and strong intrusion through the Luzon Strait. The summed transport of all three factors was approximately 2.0×106 m3/s, which was comparable with the difference in LST between the two experiments. The EKE budget showed that strong EKE transport and the baroclinic transformation term led to strong cyclonic eddies east of the Kuroshio in LICOMH, while surface winds contributed little to the differences in the eddies.

Kuroshio intrusion  /  South China Sea  /  eddy-resolving model  /  air-sea coupled model
Qian Yang, Hailong Liu, Pengfei Lin, Yiwen Li. Kuroshio intrusion in the Luzon Strait in an eddy-resolving ocean model and air-sea coupled model[J]. Acta Oceanologica Sinica, 2020 , 39 (11) : 52 -68 . DOI: 10.1007/s13131-020-1670-5
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1 Introduction
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The Luzon Strait (LS), located between the Luzon Island and the Taiwan Island, is a primary gap of the South China Sea (SCS) that forms a connection with the western North Pacific. The Kuroshio, the northward western boundary current of the subtropical gyre of the North Pacific, commonly intrudes westward into the SCS through the LS via various pathways. Sometimes, the intrusion may induce a loop current in the LS, and Kuroshio water flows out of the SCS through the northern part of the LS. The Kuroshio intrusion not only affects stratification (Metzger and Hurlburt, 1996; Qu et al., 2000; Xu and Su, 2000), circulation (Metzger and Hurlburt, 1996; Qu et al., 2000; Xu and Su, 2000; Tian et al., 2006), and mesoscale eddies (Sun et al., 2016) in the northern SCS but also affects the mass, heat and salt budgets of the whole SCS basin (Metzger and Hurlburt, 1996; Qu et al., 2000; Xu and Su, 2000).
Recently, some major features of the Kuroshio intrusion have been gradually identified due to an increasing number of in situ measurements, high resolution satellite data and numerical products, including intrusion types (Hu et al., 2000; Caruso et al., 2006; Nan et al., 2011a; Nan et al., 2015; Huang et al., 2016), water exchange in the LS (Lan et al., 2004; Tian et al., 2006; Shu et al., 2014), and interactions between the Kuroshio and mesoscale processes (Yuan et al., 2006; Sheu et al., 2010; Zhao and Luo, 2010; Nan et al., 2011b; Lu and Liu, 2013; Lien et al., 2014; Chang et al., 2015; Nan et al., 2015; Kuo et al., 2017). The Kuroshio intrusion into the SCS also has multiscale variability, ranging from seasonal (Qu et al., 2000, 2004; Xu and Su, 2000; Lan et al., 2004; Yang et al., 2013; Huang et al., 2017) to interannual (Kim et al., 2004; Qu et al., 2004; Wang et al., 2006a; Wu, 2013) to decadal (Nan et al., 2013) timescales. All relevant works prior to 2014 were well documented in the review paper by Nan et al. (2015).
The Kuroshio intrusion is usually estimated by Luzon Strait transport (LST) in the upper 400 m or 1 000 m (Qu et al., 2004; Nan et al., 2013) water layer from 18.5°N to 22.0°N along 120.75°E due to the relatively large number of observations. However, LST cannot describe which path the Kuroshio intrusion takes in the northern SCS. Hu et al. (2000) and Caruso et al. (2006) concluded that there were four and five types of paths, respectively. Nan et al. (2011a) and Nan et al. (2015) recently proposed an area-average geostrophic vorticity method (based on satellite data in the southwestern region of Taiwan) to classify the Kuroshio intrusion. Three different types were identified: the leaping path, the looping path and the leaking path. Huang et al. (2016, 2017) further refined the method into two subindices, called the double index (DI). These methods have been effective for identifying Kuroshio intrusion paths in both observational and modeling studies (Nan et al., 2013; Huang et al., 2017).
In addition to observational studies, many theoretical and numerical models have also been used to study the Kuroshio intrusion (Metzger and Hurlburt, 1996, 2001; Sheremet, 2001; Xue et al., 2004; Yuan and Wang, 2011; Wu and Hsin, 2012; Jan et al., 2017; Kuo et al., 2017). However, great diversity exists in these modeling results due to the complexity of the processes involved as well as biases in the physics used in the models and/or in the forcing datasets. The annual mean LST in the models summarized by Nan et al. (2015) ranged from –0.6×106 m3/s (Metzger, 2003) to –10.2×106 m3/s (Song, 2006). Metzger and Hurlbert (2001) and Huang et al. (2017) also pointed out that the modeled LST and intrusion path were very sensitive to the resolved topography in the LS. Finer grids and more resolved islands led to smaller LST in the models and less looping or leaking intrusion paths.
With the tremendous increases in computing resources in recent years, more studies have begun to use global- or basin-scale eddy-resolving models either with (Nan et al., 2011b) or without data assimilations (Huang et al., 2017) instead of regional or coarse resolution models due to the large impacts of mesoscale eddy activities on the Kuroshio intrusion (Yuan et al., 2006; Sheu et al., 2010; Zhao and Luo, 2010; Nan et al., 2011b; Lien et al., 2014; Chang et al., 2015; Nan et al., 2015; Kuo et al., 2017). It is likely that circulation becomes more complicated when the models can resolve mesoscale eddies. Therefore, it is necessary to systematically evaluate the Kuroshio intrusion in eddy-resolving models.
Moreover, eddy-resolving models generally tend to simulate stronger eddy activities globally (Masumoto et al., 2004; Yu et al., 2012) and around the LS (Lin et al., 2015; Sun et al., 2016), which is always attributed to insufficient subgrid scale diffusion. The recent works of Renault et al. (2016), Ma et al. (2016) and Feng et al. (2017) all suggested that eddy kinetic energy is significantly reduced in air-sea coupled models due to current feedback or eddy potential energy (EPE) reduction (or both). However, we note that the processes considered in these studies greatly differ. It is also necessary to investigate the simulation of the Kuroshio intrusion in a coupled model.
In the present study, the Kuroshio intrusion in a quasi-global eddy-resolving model and an air-sea coupled model was systemically compared and evaluated against observations. The LST biases in the coupled model were significantly reduced. Differences in the Kuroshio intrusion between the two models could be explained primarily by differences in large-scale surface winds over the Pacific, local surface wind around the LS, and eddy fields. The rest of the paper is organized as follows. Section 2 introduces the datasets. Section 3 presents the Kuroshio intrusion in the two models. Section 4 and Section 5 focus on possible mechanisms to explain the differences between the two models, including remote and local surface wind stress, the pressure gradient between the Pacific and SCS, and mesoscale eddies. In Section 6, we further investigate the mechanisms leading to different eddy fields in terms of budgets. Finally, the discussion and conclusions are provided in Section 7.
2 The numerical models, experiments and observational datasets
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2.1 Models and experiments
The eddy-resolving oceanic general circulation model (OGCM) that was used in the present study was the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics/Institute of Atmospheric Physics (LASG/IAP) Climate System Ocean Model version 2.0 (LICOM2.0) (Liu et al., 2012). To avoid the singularity of the North Pole in the longitude-latitude grid, the model domain extended from 79°S to 66°N. The horizontal grid spacing was uniformly 0.1° with 55 vertical levels. The upper 300 m consisted of 36 uneven levels that increased with depth.
A 60-year hindcast was conducted after a 12-year spinup using climatological forcing from the Ocean Model Intercomparison Project (OMIP; Röske, 2001). For this 60-year period, the model was forced by using the daily Coordinated Ocean-Ice Reference Experiments (COREs) algorithm and data from 1948 to 2007 (Large and Yeager, 2004). Owing to the lack of a sea ice module in LICOM2.0, the sea ice concentration was derived from the observational dataset from the Hadley Center (HadISST, https://climatedataguide.ucar.edu/climate-data/sea-ice-concentration-data-hadisst).
The air-sea coupled model used here mainly consisted of the abovementioned eddy-resolving version of LICOM2.0 and the atmospheric model CAM4 (Community Atmosphere Model version 4), with a 25 km horizontal resolution and 36 vertical levels. The land and sea ice models used in the coupled model were CLM4 (Community Land Model version 4) and CICE4 (Community Ice Code version 4), respectively. The four components were coupled with NCAR Flux Coupler version 7 (Craig et al., 2012). The coupling frequency between the atmosphere and the ocean was 6 h. Because the ocean model excludes the Arctic Ocean, the salinity and potential temperature at the northern boundary are nudged toward the observation of the World Ocean Atlas 2005 (WOA, https://www.nodc.noaa.gov/). The low resolution of this coupled model was described and evaluated in Lin et al. (2016). Here, we called the ocean-only and coupled experiments LICOMH and LICOMHC, respectively. The fully coupled experiment was conducted for 7 a from a quasi-steady state of LICOMH and a CAM spinup. The results from the last 5 years of both experiments were chosen for our analysis.
2.2 Observational datasets
Merged satellite altimeter products from the archiving, validation and interpretation of satellite oceanographic (AVISO, http://www.aviso.oceanobs.com) dataset were used in this study for the period of 2003–2007 to match the period of the ocean model simulation. The spatial resolution of the data was 0.25°×0.25°. We averaged the AVISO daily product every 5 d to obtain the pentad averaged data. The absolute dynamic topography (ADT) was calculated by adding the sea level anomaly (SLA) to the mean dynamic topography. The surface currents were obtained with the geostrophic relation. Water depths less than 200 m were excluded from the diagnosis due to errors caused by tidal signals (Yuan et al., 2006; Nan et al., 2011a).
3 The simulations of the Kuroshio intrusion in LICOMH and LICOMHC
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Figures 1a–c compare the mean SSH field and related surface geostrophic currents near the LS among the AVISO observation, LICOMH and LICOMHC. The red lines in Fig. 1 are the Kuroshio axis, defined as the contours of zero geostrophic vorticity. In the observation, the Kuroshio axis extended westward to approximately 120.5°E. The annual mean Kuroshio intrusion in the LICOMH reached approximately 119°E, approximately 1.5° west of the observation. The westward velocity vectors around the LS in the LICOMH were also overestimated, consistent with the exaggerated intrusion. However, the Kuroshio intrusion was greatly reduced in the coupled experiment, LICOMHC, in which the Kuroshio axis extended only to approximately 120.5°E.
The Kuroshio intrusion has evident seasonal variability, being strong in winter and weak in summer (Nan et al., 2015) (Table 1). We further compared the winter intrusion, defined as the average from December to February, in Figs 1d–f. Clearly, the surface current and LST (Table 1) are stronger in winter than the annual mean, while the Kuroshio intrusion was more exaggerated in LICOMH than in LICOMC. The Kuroshio axis in LICOMH extended to approximately 117.5°E, compared to 119°E in LICOMHC. The surface currents were also significantly stronger in the two modeled experiments in winter than the annual mean.
The upper 400 m-integrated currents (both vectors and magnitudes) from these two experiments are also presented (Fig. 2). The annual and winter mean velocity vectors (Figs 2a–b and 2d–e, respectively) resembled the surface geostrophic current shown in Figs 1b–c and 1e–f, confirming the more exaggerated Kuroshio intrusion in LICOMH than in LICOMHC for the upper 400 m. Circulations east of the LS also differed between these two experiments. Generally, the eastward Subtropical Counter Current (STCC) could not be clearly found in LICOMH in the annual and winter mean fields (Figs 2a and d), while this current was clearly located at approximately 20.5°N in LICOMHC, which was not the usual location that was noted in the observation. Furthermore, the STCC was only found in LICOMH in the winter mean field east to 130°E, at a location that was approximately 1° north of that in LICOMHC (not shown). The NEC seems to be a bit more northward in LICOMH, so that the Kuroshio intrusion should be weaker in LICOMHC.
The annual and winter circulation differences between LICOMH and LICOMHC (LICOMH minus LICOMHC) are also shown in Figs 2c and f. The annual and winter spatial mean patterns were similar because winter circulation is dominant in this region. The clockwise circulation difference in southwestern Taiwan and weaker upstream Kuroshio both confirmed the stronger intrusion in LICOMH than in LICOMHC. Moreover, the counterclockwise circulation difference at about 18°–21°N east of the LS was related to the missing STCC and weak North Equatorial Current (NEC) at approximately 18°N in LICOMH.
To quantify the intrusion in these two models, we further showed the seasonal cycle of LST in the upper 400 m for these two experiments (Fig. 3). Positive (negative) values represented eastward (westward) transport. The results did not change when the depth was further integrated to the upper 1 000 m (not shown). Table 1 compares the modeled LST with the observed ranges that were tabulated in Nan et al. (2015). The 5-year mean modeled LST values were –5.4×106 m3/s and –4.4×106 m3/s in LICOMH and LICOMHC, respectively, both of which were within the observed range, –0.5×106 m3/s to –12.4×106 m3/s (Table 1). The most notable total difference occurred in winter, which was approximately 2.8×106 m3/s. The LST in LICOMHC (–6.0×106 m3/s) was smaller than that in LICOMH (–8.8×106 m3/s) for the upper 400 m (Table 1).
We further investigated the various paths of the Kuroshio intrusion using the DI (the detailed method is presented in Appendix A). The frequencies associated with the three types of Kuroshio paths for LICOMH and LICOMHC and their corresponding LST values are listed in Table 2. We find out that the leaking path dominated in winter. The probability of occurrence of leaking path and looping path in LICOMH is 63.3% and 28.9%, but 54.4% and 33.3% for LICOMHC. This finding indicates that the Kuroshio in winter likely penetrated the SCS (Nan et al., 2015). We further calculated the annual (winter) mean transport when the Kuroshio takes its looping path and leaking path in LICOMH and LICOMHC, respectively. According to Nan et al. (2015), this phenomenon explains why the most notable LST difference between LICOMH and LICOMHC occurs in winter. It is also evident that the looping frequency is increased in LICOMHC, which may be caused by the changes of the local surface wind or circulations within the SCS.
Previous studies have suggested that when the Kuroshio intrusion is relatively weaker, the eddy activity southwest of Taiwan becomes weaker (Nan et al., 2013; Sun et al., 2016) and vice versa. This scenario is also consistent with the weaker intrusion in LICOMHC than in LICOMH, as shown in the surface eddy kinetic energy (EKE) fields (Fig. 4), although both simulations showed much stronger EKE throughout the study region regardless of season compared with the observation (Figs 4a and d). Here, the EKE was calculated as $ ({u}^{'2}+{v}^{'2}) /{2}$, where $ {u}' $ and $ {v}' $ are the geostrophic velocity anomalies deduced from the SLA.
In summary, we found that the Kuroshio intrusion was exaggerated in the ocean-only model (LICOMH), while the biases were reduced in the fully coupled model (LICOMHC). Since the ocean component in the coupled model was identical to the stand-alone ocean-only model, the changes in the Kuroshio intrusion may have been related to differences in large-scale surface winds (both local and remote) or the pressure gradient between the Pacific Ocean and the SCS between these two experiments. Because the changes of sea surface temperature and currents will affect the atmospheric state in the fully coupled model, including the atmosphere temperature and surface wind. That is, the air-sea interactions tend to dump the large changes of the ocean. In addition, mesoscale eddies in the vicinity of the LS, which are related to intrinsic ocean processes, may also have affected the intrusion, mainly through modifying upstream Kuroshio transport (Lien et al., 2014; Nan et al., 2015). The different EKE fields shown in Fig. 4 suggest the different impacts of mesoscale eddies in the two experiments, especially during winter. We will further investigate these potential contributions next.
4 Impact of large-scale and local winds on the Kuroshio intrusion
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According to Qu et al. (2000), the impact of large-scale wind stress on the Kuroshio intrusion can be explained by the “island rule” that was proposed by Godfrey (1989). Thus, LST can be expressed as follows:
$ \mathrm{L}\mathrm{S}\mathrm{T}={\oint _{{\rm{ABCD}}}} ^{} {\tau }^{\left(\mathrm{l}\right)}\mathrm{d}l/\left[{\rho }_{0}({f}_{\mathrm{D}}-{f}_{\mathrm{A}})\right], $
where, $ {\tau }^{\left(\mathrm{l}\right)} $ is the wind stress along ABCD (Fig. 5a). The Coriolis parameters of A and D are fA and fD, respectively, A is located at the southern tip of Mindanao at approximately 4.75°N, and D is located at the northernmost Luzon at approximately 18.75°N. B and C represent two points at the same latitudes as A and D on the American coast; ρ0 is the reference sea-water density (1 030 kg/m3).
Figure 5 shows the annual mean surface wind stress (vectors) and wind stress curl (WSC) (shaded) for both LICOMH and LICOMHC. The patterns of wind stress were similar to each other in both experiments but the magnitudes were slightly larger in LICOMH. The averaged LST calculated using Eq. (1) was –7.1×106 m3/s in LICOMH, slightly stronger than –6.0×106 m3/s in LICOMHC (Table 1), and this difference can reasonably explain a large part of the modeled LST difference between these two experiments. Although the island rule cannot be used for studying seasonal changes (Yang et al., 2013), it is also important in explaining the winter differences between the two experiments. Therefore, large-scale wind was used in this study to explain the difference in annual mean LST between LICOMH and LICOMHC.
Furthermore, we calculated the volume transport of the simulated upstream Kuroshio along the western coastat around 19.0°N. Other latitudes have also been tested, and the results are basically the same. We found that the transport for the coupled mode (19.01×106 m3/s at 19.0°N) is larger than that for the ocean model (18.78×106 m3/s at 19.0°N) and this will lead to stronger Kuroshio intrusion in LICOMH. The results are basically similar to Fig. 2. Moreover, the WSC can almost describe the NEC bifurcation latitude, so that is also qualitatively same as the results from the island rule.
Different local winds could also have contributed to the LST difference between LICOMH and LICOMHC (Qu et al., 2000; Nan et al., 2013). Figures 6a and b show the annual mean and winter surface wind stress differences (LICOMH-LICOMHC), respectively. Most of the surface wind differences still existed during winter. Strong southward (or southeastward) differences in the LS may drive westward Ekman transport. Therefore, westward Ekman transport in LICOMH may tend to strengthen the LST. We computed the Ekman transport differences along 120.75°E for these two experiments. The annual mean (winter) transport differences reached 0.2×106 m3/s (0.44×106 m3/s), which accounted for approximately 15%–20% of the total transport difference.
In addition to Ekman transport and the island rule, local WSC can also affect the pressure head between the Pacific Ocean and SCS or change the local gradients of the pressure on both sides of the Kuroshio, which can also affect the intrusion through changing the velocity of the upstream Kuroshio. Figures 6c and d show the annual and winter mean surface WSC difference between these two experiments (LICOMH-LICOMHC), with the hatched area representing values above the 95% significance level. The positive differences throughout the LS suggest that sea surface height anomalies tend to be lower in LICOMH due to Ekman pumping, which compensates for the gradient of sea surface height between the open ocean and the SCS, thus potentially reducing LST. So that, the local wind stress was not responsible for the large intrusion bias in LICOMH.
These results suggest that the excessive intrusion in LICOMH can be largely explained by the remote effect of surface winds through the island rule, with 1.1×106 m3/s for the annual mean. Ekman transport associated with surface winds also contributed approximately 0.2×106 m3/s (or 0.44×106 m3/s during winter) to the biases, approximately 20% of the LST difference.
5 Effect of eddies on the Kuroshio intrusion
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Although the NEC bifurcation is an important candidate affecting the Kuroshio intrusion, the mesoscale eddies can also contribute to part of the changes of KI. Previous studies suggested that cyclonic eddies (CEs) and anticyclonic eddies (AEs) east of Luzon Island may weaken and strengthen the velocity of Kuroshio east of the LS, respectively (Chang et al., 2015). Weaker (stronger) Kuroshio transport will consequently result in a looping (leaping) path (Sheu et al., 2010) and lead to a stronger (weaker) intrusion. Figure 4 shows that the eddy activity east of Luzon was more intense in LICOMH, thus potentially influencing the Kuroshio intrusion.
We use the eddy detection and tracking method of Lin et al. (2007) to categorize eddies in the present study (detailed in Appendix B). Here, we focused on eddies with lifetimes longer than 5 weeks and amplitudes greater than 3 cm. Figure 7 shows the annual and winter mean EKE due to CEs and AEs for LICOMH and LICOMHC in a 1° box. The EKE in the region just west of 121°E and at approximately 124°E was significantly larger in LICOMH than in LICOMHC, particularly during winter. In the upstream region of (18.5°–20.5°N, 123.5°–125.5°E), called northeast of Luzon (NEL), the winter average EKE values due to CEs were 598 cm2/s2 and 220 cm2/s2 in LICOMH and LICOMHC, respectively (Table 3). Intensive CEs in the NEL region reduced upstream Kuroshio transport and increased the intrusion in LICOMH. However, the EKE due to AEs in the NEL region still differed between these two experiments, but the magnitude was less than that of CEs, especially in winter, as shown in Table 3.
The larger EKE in LICOMH may likely be due to the much stronger intensity and frequency of eddies. Figures 8 and 9 show the annual and winter mean occurrence number and intensity of CEs and AEs for the two experiments. The occurrence number of CEs had some differences in general, and the intensity in LICOMH in the NEL region was much higher than that in LICOMHC. The AE results were also consistent, but the difference was small between the two models. During the 5-year integration, we found 305 (1 210) CEs in the NEL region in LICOMH and 220 (1 430) in LICOMHC in winter (5 a) (Table 3). According to the trajectories of these eddies, most were propagated from the STCC region east of the LS (not shown). The location of the large difference due to CEs was colocated with cyclonic circulation anomalies of the mean flow (Figs 2c and f), indicating the westward propagation of CEs in LICOMH is much stronger.
The difference was much more evident in intensity: approximately 23 cm (23 cm) and 15 cm (19 cm) in the NEL region in winter (composite mean during 5 a) for LICOMH and LICOMHC, respectively (Figs 8c and d, Table 3). Moreover, the 15 cm contours in the NEL region were more westward in LICOMH (approximately 123.5°E for 5 a and 121.5°E in winter) than in LICOMHC (approximately 125°E for 5 a and 123°E in winter) (Figs 8c and d). This result suggests that stronger CEs in LICOMH contributed to the stronger modeled Kuroshio intrusion.
To further analyze the impacts of eddies on the Kuroshio intrusion, we performed a composite SLA and corresponding surface geostrophic current analysis according to the polarity of eddies occurring in the NEL region (Table 3). Figures 10 and 11 show the composite SLA and associated surface geostrophic currents when AEs and CEs occurred in the NEL region, during winter and the 5 years, respectively, and the seasonal circulation was subtracted. We confirmed that eddies affected the Kuroshio intrusion in the models, and the intrusions were significantly stronger when CEs occurred than when AEs occurred, especially in winter. From Fig. 10, the anomaly circulation of Kuroshio was the same as the weak looping path when AEs occurred in the NEL region, while strong transport occurred all the way to the entrance of the SCS (similar to the leaking path) when CEs occurred in LICOMH. However, in LICOMHC, a weak looping pattern was found when CEs occurred, and the intrusion seemed to be weaker than the mean state in Figs 1f and 2f. The pattern looked similar to the leaping path during AE occurrence, and transport anomalies entered the SCS at the northern part of the LS at approximately 22°N. Strong CE circulation in the SCS during AEs occurred in the NEL region in both LICOMH and LICOMHC, hindering the Kuroshio from intruding through the LS. Thus, CEs east of the LS strengthened the Kuroshio intrusion, while AEs weakened it (Zhao and Luo, 2010; Lien et al., 2014; Chang et al., 2015; Nan et al., 2015). The results for the composite mean (Fig. 11) were basically the same, but the enhancement (reduction) of intrusion brought by CEs (AEs) was obviously weaker. It is reasonable to compare the effects related to mesoscale eddies through LST. In this way, we calculated the change in LST when mesoscale eddies occurred in the NEL region (Table 3). The difference in LST caused by eddies in LICOMH was 0.2×106 m3/s stronger than that in LICOMHC in the composite mean state during 5 a, and the difference was 1.2×106 m3/s stronger during winter.
In addition, we investigated the evolution of LST when CEs occurred in the NEL region during winter. The LICOMH and LICOMHC scenarios are shown in Figs 12 and 13, respectively. When comparing with the winter mean state, the spatial scale for the westward transport caused by CEs in LICOMH was apparently stronger than that in LICOMHC. The LST anomalies due to CEs were –1.1×106 m3/s for LICOMH and –0.5×106 m3/s for LICOMHC for the study cases. Thus far, we may certainly conclude that different CEs east of the LS between the two models contributed significantly to the difference in LST between the two models.
The above analysis showed that due to the difference in mesoscale eddies simulated in LICOMH and LICOMHC, the enhancement of the Kuroshio intrusion caused by mesoscale eddies in LICOMH was stronger, which could partly explain the difference in intrusion between the two modes.
6 EKE budget
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As mentioned previously, the strengthening effect of CEs on the Kuroshio intrusion was stronger in LICOMH than in LICOMHC. This result implies that less EKE was dissipated, more kinetic energy was transferred from the mean flow or more kinetic energy was transported from other regions. To understand the difference in eddies, the EKE budget for each CE in the NEL region was calculated following Chen et al. (2014), which can be used to explain the transport and transformation of EKE change. The details of the method are shown in Appendix C. Here, we primarily investigated the rate of EKE due to the redistribution caused by horizontal advection (AKE), the energy transformation between eddy potential energy (EAPE) and EKE (DKE), which is also called baroclinic production if the DKE is positive (von Storch et al., 2012), and eddy momentum fluxes (MKE) through barotropic instability.
The annual and winter mean vertically integrated AKE, DKE and MKE in the upper 400 m for LICOMH and LICOMHC are shown in Fig. 14. The area-averaged values of the three terms throughout the NEL region are listed in Table 4.
We found that large values of these terms occurred either along the boundary or along the Kuroshio. In the LS, the balances were between the rate of EKE advection and the transformation of barotropic instability, but the rates of EKE due to baroclinic instability were relatively small (Fig. 14). That is, the EKE generated by horizontal velocity shear was transported by currents outside this region. The comparison between the two models showed that there was more EKE transport outside the LS in LICOMH than in LICOMHC.
However, in the NEL region, which is outside of the western boundary, the patches of negative and positive values were scattered throughout the region. We computed the area averages of the three terms in the NEL region during winter (Table 4). The EKE balances in the two experiments differed. In LICOMH, EKE was mainly transported into the region through advection and was generated through baroclinic instability, while the barotropic term was relatively weak. However, in LICOMHC, EKE was generated through the transformation from EAPE and transported outside and dissipated through barotropic processes. We also found that the absolute magnitudes of the main terms, AKE and DKE, were larger in LICOMH than in LICOMHC, indicating strong eddies in LICOMH. The composite mean results in the 5 a were similar, except that EKE dissipation was caused by the barotropic term in LICOMH.
In addition, it has been demonstrated that winds can also dissipate eddy energy (Ferrari and Wunsch, 2009) and can significantly influence mesoscale ocean eddies, especially in energetic western boundary current regions (Xu et al., 2016). Gaube et al. (2015) proposed a formula of the eddy attenuation time scale (Te):
$ {T}_{\mathrm{e}}\thicksim\frac{2{\rho }_{0}D}{3{\rho }_{\mathrm{a}}{C}_{\mathrm{D}}{U}_{\mathrm{a}}}\thicksim\frac{1}{\sqrt{\left|\vec{\tau }\right|}}, $
where Te mainly depends on the vertical scale of the mesoscale eddy D, and the wind speed Ua; ρ0 (1 020 kg/m3), ρa (1.2 kg/m3), and CD (1.3×10–3) are surface seawater density, surface air density and the drag coefficient, respectively. Because the differences in D in the two models were very small, we compared the eddy attenuation time scales in LICOMH and LICOMHC by comparing the wind speed. By ignoring the sea surface velocity, Te is inversely proportional to the reciprocal of the square root of wind stress. That is, the smaller the surface wind stress, the longer the eddy attenuation time scale and the weaker the dumping effect.
Figure 15 shows the reciprocal of the square root of wind stress for LICOMH and LICOMHC and their differences. The attenuation times for eddies in the annual mean in LICOMH and LICOMHC were approximately the same, but with a relatively large magnitude in LICOMH during winter. We calculated the area average of ${1}\big/{\sqrt{\left|\vec{\tau }\right|}}$ differences throughout the NEL region. These differences could be neglected compared with the effects of wind stress in LICOMH and LICOMHC (accounting for approximately 5%). Therefore, local wind was not responsible for the differences in eddies between the two models.
In general, the strong horizontal transport of EKE and strong baroclinic effects in LICOMH led to strong eddies in LICOMH, while surface winds contributed little to the differences in the eddies. The advection term was opposite in the coupled model, and thus, the effect of the air-sea interaction on the EKE balance needs further analysis.
7 Discussion and conclusions
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In the present study, the Kuroshio intrusion in a quasi-global eddy-resolving model and an air-sea coupled model was compared and evaluated against observations. The causes of the differences in the Kuroshio intrusion between the two models were explained by differences in large-scale and local surface winds over the tropical Pacific and around the LS, respectively, as well as eddy simulations between the two models. Finally, the balance of EKE was determined to understand differences in the simulated eddies. Interestingly, the Kuroshio intrusion was exaggerated in the ocean-only model, while the biases were significantly attenuated in the fully coupled model. Although the annual mean LST was not significantly reduced in LICOMHC, LST in winter was reduced from –8.8×106 m3/s in LICOMH to –6.0×106 m3/s in LICOMHC, approximately 2.8×106 m3/s less. The transport due to the looping path in LICOMHC was also reduced by approximately 20%, from –8.3×106 m3/s in LICOMH to –6.3×106 m3/s in LICOMHC. The reduction in the Kuroshio intrusion was also demonstrated by other variables, such as the EKE west to the LS.
The analysis of surface winds showed that the large intrusion could be largely explained by the remote effect of surface winds through the island rule. In addition, local wind stress partially contributed to the difference in LST through Ekman transport and directly changed the upstream speed of the Kuroshio. In addition, weaker CEs in the NEL region in LICOMHC led to a relatively strong Kuroshio and subsequently weakened intrusion, also indicating that a change in the eddy simulation changed the Kuroshio intrusion. Although the remote effect of wind could not be quantified seasonally by using the island rule, the sum of all three factors was approximately 2×106 m3/s, which was comparable with the difference in LST between the two runs in winter.
Further assessment of the EKE budget showed that strong EKE transport, and a strong baroclinic production led to strong CEs in winter east of the Kuroshio in LICOMH. Additionally, the EKE balances east of the Kuroshio were basically different between the two models. The advection and barotropic terms were EKE sinks in the coupled model, while the barotropic effect was slightly weak in LICOMH compared with the other terms. That is, the EKE east of the Kuroshio in LICOMH was transferred from the mean flow and the energy from EAPE. These results were similar to those of Ma et al. (2016), who found that air-sea coupling led to a weak mean flow state via the change in the EKE budget. However, some detailed mechanisms and processes are needed for further investigation.
We also found that there were large differences in the EKE and eddy intensity due to CEs between the two models in the southeastern region of Taiwan (Figs 7 and 8). LST in the presence of CEs east of Taiwan (22.5°–23.5°N, 122.5°–123.5°E) was also computed in the two models (figures not shown). We found that the CEs east of Taiwan in LICOMH led to a more westward intrusion (almost 1°), but LST was slightly weaker than that in LICOMHC. Therefore, the CEs east of Taiwan may have contributed little to part of the Kuroshio intrusion, but these eddies were not a primary factor. This result was different from the study of Chang et al. (2015), who demonstrated that larger numbers of CEs east of Taiwan strengthened the Kuroshio in the LS because of upstream convergence and downstream divergence. However, this finding is also worth further investigation using observational data.
The results also indicate there are biases in the surface wind of CORE dataset in the tropic Pacific Ocean. Recently, Sun et al. (2019) has pointed out that the corrections of surface wind made by CORE lead to a weak NECC in almost all the CORE experiments. The biases in surface wind would result in biases in the volume transports in the tropic Pacific region, and then might affect the transport of Kuroshio and the Kuroshio intrusion in the Luzon Strait. The processes related with the surface wind biases and the exaggerate Kuroshio intrusion need further investigating.
Acknowledgement
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We appreciate the constructive comments of Yu-heng Tseng, and acknowledge the technical support from the National Key Scientific and Technological Infrastructure Project “Earth System Science Numerical Simulator Facility” (EarthLab).
Funding
Less
  • The National Key R&D Program for Developing Basic Sciences under contract Nos 2018YFA0605703, 2016YFC1401401 and 2016YFC1401601; the Strategic Priority Research Program of Chinese Academy of Sciences under contract No. XDB42010404; the National Natural Science Foundation of China under contract Nos 41976026, 41776030, 41931183, 41931182 and 41576026.
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Appendix
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Year 2020 volume 39 Issue 11
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doi: 10.1007/s13131-020-1670-5
  • Receive Date：2020-06-13
  • Online Date：2026-03-31
  • Published：2020-11-25
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  • Received：2020-06-13
  • Accepted：2020-07-23
Funding
The National Key R&D Program for Developing Basic Sciences under contract Nos 2018YFA0605703, 2016YFC1401401 and 2016YFC1401601; the Strategic Priority Research Program of Chinese Academy of Sciences under contract No. XDB42010404; the National Natural Science Foundation of China under contract Nos 41976026, 41776030, 41931183, 41931182 and 41576026.
Affiliations
    1 State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
    2 College of Earth Sciences, University of Chinese Academy of Sciences, Beijing 100049, China

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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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