1. Introduction
The sketch of upper-layer circulation in the tropical Pacific Ocean has been well established through the effort of many oceanographers during the past century, using in situ observational data of various sources (e.g., Wyrtki and Kendall 1967; Wyrtki 1974; Reid 1986; Kessler and Taft 1987; Delcroix et al. 1992; Reverdin et al. 1994; Bonjean and Lagerloef 2002; Johnson et al. 2002). A salient feature of the tropical Pacific surface circulation is the alternating zonal currents across the Pacific Basin, as determined by the large-scale surface wind distribution. These strong zonal currents are important for mass, heat, and tracer distributions of the Indo-Pacific Ocean. Especially their heat transport plays an essential role in setting up the basic thermal structure of the tropical Pacific Ocean, such as the west Pacific warm pool and the east Pacific cold tongue (Enfield 1986; Clement et al. 2005). Anomalies in either the transport or water temperature of these currents can influence sea surface temperature (SST) variability and air–sea interaction in the equatorial Pacific Ocean (e.g., Meyers and Donguy 1984; Gu and Philander 1997; McPhaden and Zhang 2002).
In the western tropical Pacific Ocean (WTPO), there are four major surface zonal currents (Fig. 1). The North Equatorial Current (NEC) is a broad westward flow between 9° and 18°N, with a mean transport of 42–62 Sv (1 Sv ≡ 106 m3 s−1; Toole et al. 1990; Qiu and Joyce 1992; Qiu et al. 2015). It bifurcates off the Philippine coast into the poleward Kuroshio and the equatorward Mindanao Current (e.g., Qiu and Lukas 1996; Hu et al. 2015). At the southern tip of Mindanao, a large portion of the Mindanao Current water turns eastward to feed the North Equatorial Countercurrent (NECC), which is a narrow eastward jet fluctuating between 3° and 8°N (Wyrtki and Kendall 1967; Reverdin et al. 1994; Donguy and Meyers 1996; Yu et al. 2000). On average, it transports more than 30 Sv of warm pool water to the eastern Pacific Basin. The South Equatorial Current (SEC) refers broadly to the westward flows existing between 18°S and 3°N over much of the western and central Pacific Basin, as driven by the equatorial trade winds (Reid 1986). It transports a huge amount of surface warm water to the WTPO, which is fundamental to the formation of the warm pool. Imbedded in the broad SEC, the South Equatorial Countercurrent (SECC) is a narrow eastward flow existing between 11° and 8°S with a mean velocity of several centimeters per second (Reid 1959, 1986).
(a) Annual-mean climatologic zonal current of the upper 30 m U30 (cm s−1) in the WTPO based on the OSCAR product during 1993–2014. The black triangles denote the locations of two subsurface moorings, M01 and M02, while the green dots denote the 12 TAO/TRITON buoys.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
(a) Annual-mean climatologic zonal current of the upper 30 m U30 (cm s−1) in the WTPO based on the OSCAR product during 1993–2014. The black triangles denote the locations of two subsurface moorings, M01 and M02, while the green dots denote the 12 TAO/TRITON buoys.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
(a) Annual-mean climatologic zonal current of the upper 30 m U30 (cm s−1) in the WTPO based on the OSCAR product during 1993–2014. The black triangles denote the locations of two subsurface moorings, M01 and M02, while the green dots denote the 12 TAO/TRITON buoys.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Variations of the WTPO upper circulation on seasonal, interannual, and decadal time scales have been extensively studied in the existing literature (Taft and Kessler 1991; Delcroix et al. 1992; Qiu and Joyce 1992; Reverdin et al. 1994; Sprintall and McPhaden 1994; Donguy and Meyers 1996; Johnston and Merrifield 2000; Chen and Qiu 2004; Shinoda et al. 2011; Qiu and Chen 2012; Hsin and Qiu 2012a,b; Zhao et al. 2013). Low-frequency variations of the zonal currents are mainly induced by wind stress forcing associated with the influential climate modes of the tropical Pacific Ocean. Variabilities of the WTPO circulation are affected by both local wind forcing of the East Asian monsoon system through Ekman pumping (e.g., Masumoto and Yamagata 1991; Qiu and Lukas 1996) and remote wind forcing of the central-to-eastern basin through westward-propagating Rossby waves (e.g., Meyers 1979; Kessler 1990; Qiu and Joyce 1992). In comparison, intraseasonal variability (ISV) of the WTPO zonal currents is much less explored, although prominent ISV in surface circulation has been detected by in situ measurements in many areas of the WTPO (e.g., Qiu et al. 1999; Kashino et al. 2011, 2015; Hu et al. 2013; Zhang et al. 2014).
Two subsurface moorings, M01 and M02, were deployed at 2°N, 140°E and 4.7°N, 140°E (Fig. 1) to monitor the upper-ocean currents in the far WTPO (Wang et al. 2016). Figure 2 shows the zonal current U records of the upward-looking acoustic Doppler current profilers (ADCPs) of M01 and M02 during January–August 2014. At 2°N (Fig. 2a), U is dominated by alternating westward and eastward flows above 150 m and a continuous eastward flow at the depth of the main thermocline (200–300 m). At 4.7°N (Fig. 2b), strong eastward flows characterizing the NECC exist in the upper 200 m, with much weaker westward flow below 200 m. Superimposed on seasonal transition, pronounced ISV of U is discernible at both mooring sites. Using a Lanczos digital filter (Duchon 1979), we obtain the 20–90-day bandpassed U anomaly as a representation of U ISV (Figs. 2c,d). The intraseasonal anomalies are as large as 10–40 cm s−1 in the upper 250 m, comparable to the magnitude of the seasonal-mean flow (~30–80 cm s−1). The pronounced ISV in zonal currents could play a role in the heat and tracer budget of the WTPO. An in-depth understanding of the surface current ISV will contribute to our knowledge of the regional ocean dynamics in the WTPO and tropical air–sea interactions.
Daily zonal current U (cm s−1) measured by the upward-looking ADCPs of the subsurface moorings at (a) 2°N, 140°E (M01) and (b) 4.7°N, 140°E (M02) during January–August 2014. (c),(d) The corresponding 20–90-day bandpass-filtered U anomaly. The dashed lines denote the side effect of the filter.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Daily zonal current U (cm s−1) measured by the upward-looking ADCPs of the subsurface moorings at (a) 2°N, 140°E (M01) and (b) 4.7°N, 140°E (M02) during January–August 2014. (c),(d) The corresponding 20–90-day bandpass-filtered U anomaly. The dashed lines denote the side effect of the filter.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Daily zonal current U (cm s−1) measured by the upward-looking ADCPs of the subsurface moorings at (a) 2°N, 140°E (M01) and (b) 4.7°N, 140°E (M02) during January–August 2014. (c),(d) The corresponding 20–90-day bandpass-filtered U anomaly. The dashed lines denote the side effect of the filter.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
A major origin of the observed prominent surface current ISV is the intraseasonal oscillations (ISOs) of the tropical atmosphere (e.g., Madden and Julian 1971; Goswami and Ajaya Mohan 2001). For instance, the Madden–Julian oscillation (MJO), as the dominant mode of ISOs, propagates eastward swiftly across the equatorial Pacific Basin (Madden and Julian 1971; Zhang 2005). It involves strong fluctuations of surface winds and leaves large-scale imprints on the ocean. Especially the equatorial Kelvin waves induced by MJO winds can propagate from the WTPO to the eastern Pacific and affect the development of El Niño events (Kessler et al. 1995; Hendon et al. 1998; Lengaigne et al. 2002; Shinoda et al. 2008). Besides atmospheric forcing, ocean internal variability also has a large amount of power on the intraseasonal time scale. Even without atmospheric forcing, internal variabilities can be generated by the instabilities of the ocean circulation and stratification. They may manifest as mesoscale eddies, meanders of ocean jets, submesoscale filaments, and the tropical instability waves (TIWs). According to existing observational studies, the WTPO is a region rich in all the forms of variability (e.g., Qiao and Weisberg 1995; Qiu 1999; Chelton et al. 2000; Jochum and Murtugudde 2004; Heron et al. 2006; Yang et al. 2013; Qiu et al. 2014; Chen et al. 2015). In addition, either ISO-forced or ocean internal ISV is modulated by low-frequency oceanic variation and therefore exhibits seasonal and interannual variations in amplitude and characteristics (e.g., Qiu 1999; Shinoda et al. 2008; Qiu et al. 2014; Li and Han 2016). Such an effect is also of interest because enhanced/attenuated ISV may have rectification on the tropical Pacific climate through the nonlinearity of the ocean and air–sea interaction (e.g., Moore and Kleeman 1999; Kessler and Kleeman 2000).
The aim of the present research is to provide a comprehensive investigation for the ISV of the major surface zonal currents in the WTPO. Satellite observational data are analyzed to obtain the primary characteristics of ISV, and then ocean general circulation model (OGCM) experiments are performed to gain insights into the underlying mechanisms. The rest of the paper is organized as follows: Section 2 describes the satellite and in situ observational datasets and the OGCM utilized in this study. Section 3 presents the characteristics of surface current ISV in the WTPO from observational data and verifies the performance of the OGCM. Section 4 explores the underlying mechanisms of surface current ISV, underscoring the relative importance of external forcing by atmospheric ISOs and ocean internal variability. The wind forcing effect of MJOs and the origins of ocean internal variability are further examined. Section 5 provides a summary and discussion for the main findings of the paper.
2. Data and model
a. Data
The NOAA/Pacific Marine Environmental Laboratory (PMEL) provides daily near-surface current measurements at 12 moored buoys of the Tropical Atmosphere Ocean/Triangle Trans-Ocean Buoy Network (TAO/TRITON) in the WTPO (McPhaden 1995). The locations of these buoys are shown in Fig. 1 as green dots. Besides ocean observations, our analysis also involves two atmospheric satellite datasets. The ¼° × ¼° daily cross-calibrated multiplatform (CCMP) 10-m wind version 1.1 data (Atlas et al. 2008) during 2001–11 are used to estimate surface wind variability associated with ISOs, while the 1° × 1° daily NOAA satellite outgoing longwave radiation (OLR) at the top of the atmosphere (Liebmann and Smith 1996) during 2001–11 is employed as the indicator of atmospheric deep convection.
b. HYCOM
The model spins up from a state of rest for 30 years under monthly climatologic atmospheric forcing. Then HYCOM is integrated forward from March 2000 to November 2011, determined by the availability of CERES radiation data at the time when the model experiments were performed. Four parallel experiments are performed for understanding surface current ISV. The Main Run (MR) is forced with the original daily atmospheric data. It contains the complete processes in the Pacific Basin, including variabilities on intraseasonal and low-frequency time scales arising from both atmosphere forcing and ocean internal origin. MR is used as the reference solution for the validation of HYCOM performance against observational data.
The second experiment is NoISO, in which the forcing effects of atmospheric ISOs are removed. Specifically, a 105-day Lanczos low-pass filter is applied to all the forcing fields. As a result, oceanic ISV in the NoISO solution arises mainly from ocean internal variability, and the difference between MR and NoISO can be regarded as a measure of the ISO forcing effect. It should be noted that NoISO is still forced by low-frequency (seasonal and interannual) atmospheric variations. Low-frequency forcing can also affect oceanic ISV through the nonlinearity of ocean processes and through changing the ocean background state upon which oceanic ISV develops (e.g., Qiu 1999; Shinoda et al. 2008; Li and Han 2016). For an estimation of such an effect, the NoLF experiment is performed as the third one, in which low-frequency atmospheric forcing is removed. Specifically, all the forcing fields are 120-day high-pass filtered anomalies (intraseasonal fluctuations) plus the annual-mean climatology of 2000–11. Hence, the difference between MR and NoLF can measure the effect of low-frequency atmospheric forcing on surface current ISV. In the WTPO, wind stress forcing is important in causing upper-ocean circulation variability at various time scales (Kessler 1990; Qiu and Lukas 1996; Hu et al. 2015). The last experiment, TAU, is to examine the effect of intraseasonal wind stress forcing. In TAU, daily wind stress is adopted as in MR, while all the other forcing fields are low-passed with a 105-day Lanczos filter. Under such design, the difference between NoISO and TAU provides a rough measure of intraseasonal wind stress forcing effect. A large difference indicates an important role played by ISO wind stress forcing in generating surface current ISV. On the other hand, the difference between MR and TAU can roughly measure the effect of other forcing fields, such as heat and freshwater fluxes. Output data from the four experiments are stored in 3-day mean resolution, and the 11-yr data of 2001–11 are used for our analysis. Unless otherwise noted, ISV is quantified by 20–90-day bandpass-filtered anomaly data of observations and HYCOM outputs.
3. Observed and simulated surface zonal currents
Comprehensive comparisons between HYCOM MR and satellite/in situ observations have been conducted in Li et al. (2015) and Li and Han (2016) for the upper-ocean temperature, salinity, and circulation of the WTPO. Therefore, we examine only the structure and variability of surface zonal currents here. The climatological distribution of U in the WTPO is featured by the interleaving strong zonal equatorial currents, such as the NEC, NECC, SEC, and SECC (Fig. 3). Measured by OSCAR U30 (mean zonal current of 0–30 m), all the satellite-observed surface zonal currents exhibit evident seasonal changes (left panels of Fig. 3). Both the NEC and SEC are stronger in boreal winter (January; “boreal” omitted hereafter) than in summer (July). The SECC is also strongest in January and nearly disappeared in July (Chen and Qiu 2004). Among others, the NECC also shows evident meridional shift. It is strengthened and shifted southward in summer in the WTPO (Hsin and Qiu 2012a). These primary seasonal variations are all faithfully reproduced by HYCOM (right panels of Fig. 3). To facilitate our further analysis, we define six boxes according to the spatial distribution of the zonal currents. They are the western NEC box (NEC-W; 10°–15°N, 130°–145°E), eastern NEC box (NEC-E; 10°–15°N, 160°–175°E), western NECC box (NECC-W; 3°–8°N, 130°–145°E), eastern NECC box (NECC-E; 3°–8°N, 160°–175°E), SEC box (4°S–1°N, 160°–175°E), and the SECC box (12°–7°S, 160°–175°E). Note that the SEC box covers only the northern branch of the SEC. Its southern branch, located at 18°–12°S, is beyond the scope of the present research. We have also checked the vertical structures of these zonal currents in HYCOM MR (figure not shown). The spatial distribution and typical magnitudes are all in line with existing observational knowledge (e.g., Delcroix et al. 1992; Gouriou and Toole 1993; Johnson et al. 2002).
Climatological U30 (cm s−1) in January, April, July, and October during 2001–11 based on (left) OSCAR product and (right) HYCOM MR output. The six rectangles denote the box areas of the NEC-W (10°–15°N, 130°–145°E), NEC-E (10°–15°N, 160°–175°E), NECC-W (3°–8°N, 130°–145°E), NECC-E (3°–8°N, 160°–175°E), SEC (4°S–1°N, 160°–175°E), and SECC (12°S–7°N, 160°–175°E).
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Climatological U30 (cm s−1) in January, April, July, and October during 2001–11 based on (left) OSCAR product and (right) HYCOM MR output. The six rectangles denote the box areas of the NEC-W (10°–15°N, 130°–145°E), NEC-E (10°–15°N, 160°–175°E), NECC-W (3°–8°N, 130°–145°E), NECC-E (3°–8°N, 160°–175°E), SEC (4°S–1°N, 160°–175°E), and SECC (12°S–7°N, 160°–175°E).
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Climatological U30 (cm s−1) in January, April, July, and October during 2001–11 based on (left) OSCAR product and (right) HYCOM MR output. The six rectangles denote the box areas of the NEC-W (10°–15°N, 130°–145°E), NEC-E (10°–15°N, 160°–175°E), NECC-W (3°–8°N, 130°–145°E), NECC-E (3°–8°N, 160°–175°E), SEC (4°S–1°N, 160°–175°E), and SECC (12°S–7°N, 160°–175°E).
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
The U30 time series from OSCAR and HYCOM MR are further compared with 10-m U measured by 12 TAO/TRITON buoys (Fig. 4). The three datasets, with independent data sources, are generally consistent in variabilities of various time scales. The correlation between OSCAR and buoys is between 0.69 and 0.90 (not shown in Fig. 4), suggesting the fidelity of OSCAR data in representing the observed surface U variations. Hsin and Qiu (2012a) compared OSCAR estimates with TAO/TRITON records over the entire tropical Pacific Basin and also suggested a good consistency in surface U. The correlation between HYCOM MR and buoys, however, exhibits large variation among different buoy sites (the r in Fig. 4). It is interesting that HYCOM can better simulate the observed variability near the equator. The correlations at 2°N, 0°, and 2°S are 0.75–0.88 and dramatically decreased at 5° and 8°N. We also computed their correlation for ISV (the rISV in Fig. 4), which is generally lower than r. Within 2°–2°S, rISV ranges between 0.48 and 0.82 (all significant at 95% confidence level), while at 5° and 8°N, it drops to 0.09–0.29. Such variation in HYCOM/buoy correlation is likely related to the mechanisms controlling U variability. The total U time series contains both low-frequency variations (seasonal and interannual) and ISV. As has been demonstrated by many studies, low-frequency current variations in the WTPO is predominantly produced by wind forcing (e.g., Kessler 1990; Taft and Kessler 1991; Qiu and Joyce 1992; Sprintall and McPhaden 1994; Qiu and Lukas 1996). Such wind-forced variations can be realistically simulated by an OGCM. On the other hand, as will be demonstrated in section 4, a large portion of ISV arises from ocean internal processes, which cannot be reproduced by an OGCM at the correct phase, owing to its nonlinearity. In addition, section 4 will show the ISO wind-forced surface current ISV signals are stronger near the equator, while away from the equator the pointwise ISV arises primarily from ocean internal variability. As a result, the modeled U30 variability tends to achieve higher levels of consistency with observation near the equator and at low frequencies. We further check the variance distribution in frequency space (Fig. 5). For all three datasets, the variance within the 20–90-day band exceeds the 95% significance level and exhibits an increasing trend from 20 to 90 days. Near the equator there tends to be eye-catching power peaks at 40–60 days, particularly at buoys 147e0n, 147e2n, 156e2s, 156e0n, and 156e2n. At 5°N, 5°S, and 8°N, the power is also enhanced at 40–60 days, although the peaks are less striking. The cause for the formation of this power peak will be discussed in section 4.
The 10-m U measured by TAO/TRITON buoys (red), U30 from OSCAR product (green), and U30 from HYCOM MR output (blue) at 12 buoy sites. Locations of the buoy sites are indicated by the buoy names. Mean values have been removed. The correlations between HYCOM and the buoys for the original data (r) and 20–90-day filtered anomaly (rISV) are computed and shown.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
The 10-m U measured by TAO/TRITON buoys (red), U30 from OSCAR product (green), and U30 from HYCOM MR output (blue) at 12 buoy sites. Locations of the buoy sites are indicated by the buoy names. Mean values have been removed. The correlations between HYCOM and the buoys for the original data (r) and 20–90-day filtered anomaly (rISV) are computed and shown.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
The 10-m U measured by TAO/TRITON buoys (red), U30 from OSCAR product (green), and U30 from HYCOM MR output (blue) at 12 buoy sites. Locations of the buoy sites are indicated by the buoy names. Mean values have been removed. The correlations between HYCOM and the buoys for the original data (r) and 20–90-day filtered anomaly (rISV) are computed and shown.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Power spectra of 10-m U measured by TAO/TRITON buoys (red), U30 from OSCAR product (green), and U30 from HYCOM MR output (blue) at 12 buoy sites. The dashed curves denote the 95% significance level.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Power spectra of 10-m U measured by TAO/TRITON buoys (red), U30 from OSCAR product (green), and U30 from HYCOM MR output (blue) at 12 buoy sites. The dashed curves denote the 95% significance level.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Power spectra of 10-m U measured by TAO/TRITON buoys (red), U30 from OSCAR product (green), and U30 from HYCOM MR output (blue) at 12 buoy sites. The dashed curves denote the 95% significance level.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
The root-mean-squared (rms) value of the 20–90-day U30 is a measure of the amplitude of surface zonal current ISV (Fig. 6). For OSCAR U30, ISV is strongest in a narrow band straddling the equator, with its rms value exceeding 20 cm s−1 (Fig. 6a). The amplitude decreases rapidly toward higher latitudes. It drops to ~10 cm s−1 at the latitudes of the NECC and further to 4–8 cm s−1 in the NEC and SECC. The ISV tends to be stronger near the western boundary than in the ocean interior. This may be attributed to the enhanced dynamical instabilities of the western boundary currents, which will be discussed in section 4c. The amplitude rebounds in the area north of 15°N and exceeds 10 cm s−1 near 20°N, reflecting the strong eddy variability in the North Pacific Subtropical Countercurrent region (Qiu 1999; Yang et al. 2013; Qiu et al. 2014). To better quantify the strength of ISV, we compute the ratios of the rms ISV relative to the mean value and the rms seasonal cycle of U30. The former turns out to be controlled by the magnitude of mean U30 (Fig. 6b). This ratio is generally below 50% around the main bodies of the zonal currents and much higher at boundaries where the mean U30 is small (see Fig. 1 for the mean U30 distribution). The ratio of the ISV to the seasonal cycle is >50% in most of the WTPO region and >100% in the NEC, SEC, and SECC areas (Fig. 6c). The WTPO region is subjected to the strong impact of the East Asian monsoon and hence exhibits large seasonal variability in upper-ocean circulation (e.g., Masumoto and Yamagata 1991; Qiu and Lukas 1996; Chen and Qiu 2004). The comparison with the seasonal cycle confirms that ISV of the surface zonal currents is rather prominent and worthy of in-depth investigation.
The rms ISV of (a) U30 (cm s−1), (b) its ratio to the mean magnitude of U30, and (c) its ratio to the seasonal cycle of U30 based on OSCAR product of 1993–2014. The rms ISV maps of (d) AVISO surface geostrophic current UG (cm s−1) during 1993–2014, (e) AVISO SSH (cm) during 1993–2014, and (f) U30 from HYCOM MR solution during 2001–11. ISV is represented by the 20–90-day bandpass-filtered U anomaly.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
The rms ISV of (a) U30 (cm s−1), (b) its ratio to the mean magnitude of U30, and (c) its ratio to the seasonal cycle of U30 based on OSCAR product of 1993–2014. The rms ISV maps of (d) AVISO surface geostrophic current UG (cm s−1) during 1993–2014, (e) AVISO SSH (cm) during 1993–2014, and (f) U30 from HYCOM MR solution during 2001–11. ISV is represented by the 20–90-day bandpass-filtered U anomaly.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
The rms ISV of (a) U30 (cm s−1), (b) its ratio to the mean magnitude of U30, and (c) its ratio to the seasonal cycle of U30 based on OSCAR product of 1993–2014. The rms ISV maps of (d) AVISO surface geostrophic current UG (cm s−1) during 1993–2014, (e) AVISO SSH (cm) during 1993–2014, and (f) U30 from HYCOM MR solution during 2001–11. ISV is represented by the 20–90-day bandpass-filtered U anomaly.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
The ISV of the surface zonal geostrophic current UG based on AVISO SSH data (Fig. 6d) greatly resembles OSCAR U30. It means that the ISV of surface zonal currents is predominantly contributed by the geostrophic component. This result is not surprising, given that the upper-ocean zonal currents in the equatorial Pacific Ocean is approximately in geostrophic balance (e.g., Lukas and Firing 1984; Gouriou and Toole 1993). The ISV of SSH is dramatically different from the surface current, with the amplitude increasing from the equator to the higher latitudes (Fig. 6e). The rms ISV is below 2 cm near the equator. Therefore, the enhanced surface current ISV in the equatorial band is primarily due to the small Coriolis parameter f under which a very small change in SSH leads to large fluctuation in the geostrophic current. The rms ISV of the HYCOM-simulated U30 (Fig. 6f) agrees with OSCAR U30 (Fig. 6a) in both spatial distribution and typical magnitude. HYCOM, however, fails to reproduce the ISV rebound north of 15°N. This is largely attributed to the ⅓° model resolution that is insufficient to resolve the mesoscale and submesoscale eddy variability in the North Pacific Subtropical Countercurrent region (Qiu 1999; Qiu et al. 2014).
Dependence of U30 ISV on the spatial length L between 0 and 3000 km: (a) rms ISV of OSCAR U30 (cm s−1), (b) rms ISV of HYCOM MR U30, and (c) the correlation between OSCAR U30 ISV and HYCOM MR U30 ISV. For a given L, U30 is averaged over an elliptic area with a zonal radius of Rx = L and a meridional radius of Ry = L/2. The ellipses are located around the centers of the NEC-W, NEC-E, NECC-W, NECC-E, SEC, and SECC boxes.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Dependence of U30 ISV on the spatial length L between 0 and 3000 km: (a) rms ISV of OSCAR U30 (cm s−1), (b) rms ISV of HYCOM MR U30, and (c) the correlation between OSCAR U30 ISV and HYCOM MR U30 ISV. For a given L, U30 is averaged over an elliptic area with a zonal radius of Rx = L and a meridional radius of Ry = L/2. The ellipses are located around the centers of the NEC-W, NEC-E, NECC-W, NECC-E, SEC, and SECC boxes.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Dependence of U30 ISV on the spatial length L between 0 and 3000 km: (a) rms ISV of OSCAR U30 (cm s−1), (b) rms ISV of HYCOM MR U30, and (c) the correlation between OSCAR U30 ISV and HYCOM MR U30 ISV. For a given L, U30 is averaged over an elliptic area with a zonal radius of Rx = L and a meridional radius of Ry = L/2. The ellipses are located around the centers of the NEC-W, NEC-E, NECC-W, NECC-E, SEC, and SECC boxes.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
For a better quantification of the consistency between OSCAR and HYCOM in U30 ISV, we compute their correlations at different L (Fig. 7c). Consistent with Fig. 4, HYCOM generally performs better at lower latitudes, showing a higher correlation in the SEC, followed by the NECC and SECC, and worst in the NEC. Correlations are also higher in the basin interior (NECC-E and NEC-E) than in the western boundary areas (NECC-W and NEC-W). These differences are again attributable to the spatial variation in mechanisms (discussed in detail in section 4). Interestingly, accompanying the decrease in amplitude, the correlation coefficient elevates rapidly with L. At short scales (L < 200 km), the correlation is between 0.45 and 0.50 for the SEC and <0.25 for other currents. At 500 km, as a large portion of ocean internal variability has been averaged out, the correlation increased to 0.44–0.72. All the correlations exceed 0.60 for scales larger than 1500 km and reaches as high as 0.80–0.87 in some regions. From the climatic point of view, variations at large scales are much more of interest. The good performance of HYCOM at large scales indicates its usefulness in understanding the surface current ISV.
4. Mechanisms of ISV
a. ISO forcing versus ocean internal variability
The comparisons in section 3 suggest that HYCOM is capable of reasonably reproducing the observed surface current ISV. This lends us confidence for the further investigation of the underlying mechanisms. As shown by existing observational studies (Delcroix et al. 1992; Gouriou and Toole 1993; Johnson et al. 2002) and our HYCOM results, the main bodies of the major zonal currents exist in the upper 150 m. Figure 2 suggests that large ISV anomalies primarily occur within this layer. With these regards, the average current of 0–150 m, that is, U150, is a more suitable representative for the surface-layer transport of a zonal current than U30. In HYCOM, U150 is highly consistent with U30 in ISV, showing similar spatial distribution (Fig. 8a) and correlations of 0.92–0.97 for the six boxes. Hereafter, our analysis will be focused on U150 instead of U30. Effects of atmospheric forcing by ISOs and ocean internal variability can be isolated through HYCOM experiments. Without any form of external intraseasonal forcing, U150 ISV in the NoISO experiment arises primarily from ocean internal variability. The rms ISV of NoISO U150 (Fig. 8b) shows a similar spatial pattern to that of MR. It also has the maximal amplitude in the equatorial band, which is, however, weaker than MR by ~30%. Away from the equator, the ISV amplitudes of MR and NoISO are quite close. The difference between MR and NoISO in rms ISV of U150 is a rough estimation for the atmospheric forcing effect of ISOs (Fig. 8c). Such effect is mainly confined within the equatorial band. By including intraseasonal wind forcing, TAU has evidently stronger ISV in the equatorial band (Fig. 8d) than NoISO (Fig. 8b). The great resemblance between Figs. 8a and 8d further demonstrates that the effect of atmospheric ISOs on the surface current ISV is predominantly through wind stress forcing. The effect of other atmospheric variables, such as heat flux and freshwater flux, is much smaller than wind stress. The results of Figs. 8 suggest that at any grid point of the model, surface current ISV is induced primarily by ocean internal variability and secondarily by ISO wind forcing.
The rms ISV of U150 (cm s−1) from (a) HYCOM MR, (b) the NoISO experiment measuring the ocean internal ISV, and (c) their difference, i.e., rms (MR) − rms (NoISO), measuring the ISO-forced ISV. (d) The rms ISV of U150 from the TAU experiment.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
The rms ISV of U150 (cm s−1) from (a) HYCOM MR, (b) the NoISO experiment measuring the ocean internal ISV, and (c) their difference, i.e., rms (MR) − rms (NoISO), measuring the ISO-forced ISV. (d) The rms ISV of U150 from the TAU experiment.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
The rms ISV of U150 (cm s−1) from (a) HYCOM MR, (b) the NoISO experiment measuring the ocean internal ISV, and (c) their difference, i.e., rms (MR) − rms (NoISO), measuring the ISO-forced ISV. (d) The rms ISV of U150 from the TAU experiment.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Averaged over the six 15° × 5° boxes, the 20–90-day U150 measures the large-scale ISV of the zonal currents (Fig. 9a). In MR (black), the rms ISV exceeds 9 cm s−1 in the SEC (4°S–1°N) and drops to <2 cm s−1 in the NEC (10°–15°N). The ocean internal ISV (blue), as measured by NoISO solution, is much weaker, accounting for ~40% of the amplitude of the total ISV in MR. Its correlation with MR ISV is below 0.3 in all six boxes and even negative in the NEC-W (Fig. 9b). It means that the ocean internal ISV cannot explain much of the large-scale surface current ISV. By including intraseasonal wind stress, ISV in TAU (red) is greatly enhanced, reaching similar magnitudes to MR. Its correlation with MR reaches 0.84–0.92. These results suggest that the large-scale (box average) surface current ISV is mainly induced by atmospheric ISOs through wind stress forcing, while the ocean internal variability plays a secondary role. This mechanism deviates from the one derived from Fig. 8 for the pointwise ISV.
(a) Rms ISV of U150 averaged over the six boxes from MR (black), NoISO (blue), TAU (red), and NoLF (green) experiments. (b) Correlation coefficients between the MR U150 ISV and those of NoISO (blue), TAU (red), and NoLF (green).
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
(a) Rms ISV of U150 averaged over the six boxes from MR (black), NoISO (blue), TAU (red), and NoLF (green) experiments. (b) Correlation coefficients between the MR U150 ISV and those of NoISO (blue), TAU (red), and NoLF (green).
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
(a) Rms ISV of U150 averaged over the six boxes from MR (black), NoISO (blue), TAU (red), and NoLF (green) experiments. (b) Correlation coefficients between the MR U150 ISV and those of NoISO (blue), TAU (red), and NoLF (green).
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Figures 8 and 9 indicate that the relative importance of ISO wind forcing and ocean internal variability is sensitive to the spatial scale. This sensitivity needs to be better assessed to achieve a more in-depth understanding of the ISV mechanism. Following the method used for Fig. 7, we compute the rms U150 ISVs from MR, NoISO, and TAU solutions at a different length scale L (Fig. 10). In all the regions, there is no evident difference between MR and TAU, confirming that ISOs induce surface current ISV primarily through wind stress forcing. The variability at short length scale (e.g., L < 200 km) is much larger than at large L, and the difference between MR and NoISO is quite small at short L. These results indicate that in the open-ocean area of the WTPO, surface-layer current ISV measured by moorings/moored buoys at individual sites, such as those by M01 and M02 (Fig. 2), is predominantly manifestations of ocean internal variability. It will be probably difficult to find its origin in the surface atmospheric forcing. The ocean internal ISV signals are greatly attenuated by increased L. At L > 1000 km, as most of the signals of eddies, filaments, and meanders have been averaged out, the ocean internal ISV has become much weaker than the ISO wind-forced ISV (measured by the difference between MR and NoISO in rms ISV). At scales larger than 500 km, the surface current ISV is basically dominated by ISO wind stress forcing. The large amplitude of ISO-forced ISV is determined by the large-scale nature of the tropical atmospheric ISOs (e.g., Goswami and Ajaya Mohan 2001; Zhang 2005).
Dependence of rms U150 ISV of MR (black), NoISO (blue) and TAU (red) on the spatial length L in the (a) NEC-W, (b) NEC-E, (c) NECC-W, (d) NECC-E, (e) SEC, and (f) SECC regions.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Dependence of rms U150 ISV of MR (black), NoISO (blue) and TAU (red) on the spatial length L in the (a) NEC-W, (b) NEC-E, (c) NECC-W, (d) NECC-E, (e) SEC, and (f) SECC regions.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Dependence of rms U150 ISV of MR (black), NoISO (blue) and TAU (red) on the spatial length L in the (a) NEC-W, (b) NEC-E, (c) NECC-W, (d) NECC-E, (e) SEC, and (f) SECC regions.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Given the evident dependence of the ISV mechanism on the length scale, it is also of interest to examine its dependence on the time scale. This is pursued by comparing the U150 power spectra from different experiments (Fig. 11). Here, ISV is computed for two representative length scales with Eq. (3): L = 200 km, at which ocean internal variability is strong, and L = 1000 km, at which ISO wind forcing effect dominates. At L = 200 km (solid curves), ocean internal ISV (blue) can explain most of the total ISV (black) in the NEC, especially the enhanced power at the 60–90-day band. In NECC, SEC, and SECC, there is a significant difference between MR and NoISO, suggesting the significant effect of ISO wind forcing. Particularly, the wind forcing in MR and TAU contributes greatly to the large power at the 60–90-day band and the power peak at the 50–60-day period that are also features seen in the observations (Fig. 5). The enhanced 50–60-day power may be associated with the MJO, which shows a typical period of 30–60 days (e.g., Zhang 2005). At L = 1000 km (dashed curves), the ocean internal ISV is rather weak, and most of the ISV power are induced by ISO wind forcing.
Power spectra of U150 ISV of MR (black), NoISO (blue) and TAU (red) for L = 200 km (thick solid) and L = 1000 km (thin dashed) in the (a) NEC-W, (b) NEC-E, (c) NECC-W, (d) NECC-E, (e) SEC, and (f) SECC regions.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Power spectra of U150 ISV of MR (black), NoISO (blue) and TAU (red) for L = 200 km (thick solid) and L = 1000 km (thin dashed) in the (a) NEC-W, (b) NEC-E, (c) NECC-W, (d) NECC-E, (e) SEC, and (f) SECC regions.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Power spectra of U150 ISV of MR (black), NoISO (blue) and TAU (red) for L = 200 km (thick solid) and L = 1000 km (thin dashed) in the (a) NEC-W, (b) NEC-E, (c) NECC-W, (d) NECC-E, (e) SEC, and (f) SECC regions.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
b. Signatures of the MJO
In this subsection, we examine the surface current ISV signals produced by the MJO. The real-time multivariate MJO (RMM) index (Wheeler and Hendon 2004) is used to recognize MJO events and conduct composite analysis. It is based on the first two empirical orthogonal functions (EOFs) of the combined fields of near-equatorial 850- and 200-hPa winds and the outgoing longwave radiation. Projecting atmospheric fields onto the two EOFs yields two principal components, defined as the RMM1 and RMM2. Here, we use the phase (varying between 1 and 8) and magnitude (RMM12 + RMM22)1/2 of the RMM index. For each of the eight MJO phases, the ISV anomalies are averaged over the days with RMM magnitude > 1.5 (indicating significant MJO variance). In this manner, the composite MJO event therefore represents the mean evolutions of the atmosphere and ocean conditions during the passage of MJOs (Fig. 12). The MJO is characterized by enhanced/suppressed atmospheric deep convection and low-level wind perturbations. During phases 8–2, the WTPO is controlled by a suppressed convection condition as indicated by the positive OLR anomaly moving eastward along the equator, and during phases 4–6, enhanced convection occurs (negative OLR). The OLR anomaly is accompanied by anomalous winds that give rise to large surface current variations near the equator. Sustained easterly winds during phases 1–4 induce westward U150 of 4–12 cm s−1 in the equatorial band during phases 2–5. Similarly, the prevailing westerly winds during phases 5–8 induce eastward U150 during phases 6–1. Large U150 signals are confined between 10°S and 8°N and have a large zonal wavelength. Away from the equator, U150 anomalies are rather weak and fragmental. Also worth noticing is the eastward-moving tendency of U150 anomalies, likely following the convection and wind perturbations of the MJO.
MJO composite maps of CCMP wind stress (vectors; N m−2), MR U150 (color shading; cm s−1), and satellite-observed OLR (green and purple contours; W m−2) based on the RMM index. The black (green) contours denote the 15 (−15) W m−2 OLR anomaly.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
MJO composite maps of CCMP wind stress (vectors; N m−2), MR U150 (color shading; cm s−1), and satellite-observed OLR (green and purple contours; W m−2) based on the RMM index. The black (green) contours denote the 15 (−15) W m−2 OLR anomaly.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
MJO composite maps of CCMP wind stress (vectors; N m−2), MR U150 (color shading; cm s−1), and satellite-observed OLR (green and purple contours; W m−2) based on the RMM index. The black (green) contours denote the 15 (−15) W m−2 OLR anomaly.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
The propagation behaviors of the composite MJO event can be observed in the time–longitude plots (Fig. 13). Zonal wind stress τx of the MJO, as the primary driver of surface current variability, exhibits swift eastward transition (left panels). Under such wind-forcing conditions, the composite U150 of MR exhibits interesting spatial–temporal characteristics (right panels). The U150 signal package also moves swiftly eastward, as indicated by the black dashed lines, following the eastward-propagating MJO winds. However, in the NEC, NECC, and SECC, there are some U150 signals showing a seemingly westward-moving trend at a much smaller phase speed, as indicated by green dashed lines. This feature could be reflecting the westward-propagating Rossby waves modified by the rapid-changing MJO winds. Near the equator, the MJO-forced surface current signals are expected to be mainly in the form of equatorial Kelvin waves (e.g., Kessler et al. 1995; Shinoda et al. 2008). However, it is difficult to identify wave signals in MJO composite maps.
Time–longitude plots of the (left) MJO composite CCMP zonal wind stress τx (N m−2) and (right) MR U150 (cm s−1) averaged over the latitude ranges of the NEC (10°–15°N), NECC (3°–8°N), SEC (4°S–1°N), and SECC (12°–7°S). In the right panels, the green dashed lines denote the westward propagation of U150 signals, while the black dashed lines denote the eastward propagation of MJOs.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Time–longitude plots of the (left) MJO composite CCMP zonal wind stress τx (N m−2) and (right) MR U150 (cm s−1) averaged over the latitude ranges of the NEC (10°–15°N), NECC (3°–8°N), SEC (4°S–1°N), and SECC (12°–7°S). In the right panels, the green dashed lines denote the westward propagation of U150 signals, while the black dashed lines denote the eastward propagation of MJOs.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Time–longitude plots of the (left) MJO composite CCMP zonal wind stress τx (N m−2) and (right) MR U150 (cm s−1) averaged over the latitude ranges of the NEC (10°–15°N), NECC (3°–8°N), SEC (4°S–1°N), and SECC (12°–7°S). In the right panels, the green dashed lines denote the westward propagation of U150 signals, while the black dashed lines denote the eastward propagation of MJOs.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
To better visualize the U150 signals of MJO-forced waves, we need to broaden our vision to the entire Pacific Basin. Figure 14 shows the time–longitude plots of 20–90-day U150 during 2009 and 2010. The U150 anomaly averaged over 2°S–2°N is able to capture the equatorial Kelvin wave signals. However, in Fig. 14a, eastward- and westward-propagating signals are both seen. Most of the eastward signals originate from the western Pacific and travel quickly to the central and eastern basin. These signals are primarily Kelvin waves induced by MJO winds that are characterized by intraseasonal τx (black and green contours). The strong MJO events during December 2009–March 2010 induced prominent Kelvin waves that traveled across the Pacific Basin. During the late winter–spring of 2009, several strong MJOs occurred in the western basin but got diminished in the central Pacific Basin. The forced Kelvin waves, however, made it to the eastern boundary. No strong MJO event occurred during April–December of 2010, and the eastward-propagating signals were not seen either. It takes about 3–4 months for the Kelvin waves to cross the equatorial Pacific Basin, which is faster than the theoretical phase speed of the first baroclinic mode Kelvin waves (2.7–3.0 m s−1). The larger propagation speed is primarily due to the along-track modification by wind stress (e.g., Roundy and Kiladis 2006; Shinoda et al. 2008). Since the MJOs travel faster (~5 m s−1) than Kelvin waves, they tend to produce new waves ahead of the original waves, accelerating the eastward transition of the wave packet. On the other hand, the westward-propagating signals originate from the eastern basin, with a much slower phase speed (0.5–0.8 m s−1). They comply with the observed features of the TIWs (Qiao and Weisberg 1995). This is confirmed by NoISO (Fig. 14b). These westward-propagating signals arise from ocean internal instability rather than intraseasonal winds. Although the TIWs mainly occur in the central-to-eastern basin, they have considerable effect on the SEC box (160°–175°E). Satellite observations have shown that some TIWs are able to propagate farther west than the date line and possibly all the way to the western boundary (Chelton et al. 2000).
Time–longitude plots of U150 ISV (color shading; cm s−1) from (a) MR and (b) NoISO averaged between 2°S and 2°N during 2009/10. In (a), the 20–90-day τx is superimposed as contours, with black for 0.02 and 0.04 N m−2, and green for −0.02 and −0.04 N m−2. (c),(d) As in (a) and (b), but averaged between 3° and 8°N.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Time–longitude plots of U150 ISV (color shading; cm s−1) from (a) MR and (b) NoISO averaged between 2°S and 2°N during 2009/10. In (a), the 20–90-day τx is superimposed as contours, with black for 0.02 and 0.04 N m−2, and green for −0.02 and −0.04 N m−2. (c),(d) As in (a) and (b), but averaged between 3° and 8°N.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Time–longitude plots of U150 ISV (color shading; cm s−1) from (a) MR and (b) NoISO averaged between 2°S and 2°N during 2009/10. In (a), the 20–90-day τx is superimposed as contours, with black for 0.02 and 0.04 N m−2, and green for −0.02 and −0.04 N m−2. (c),(d) As in (a) and (b), but averaged between 3° and 8°N.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
At the latitudes of the NECC (3°–8°N), only westward-propagating signals are seen (Figs. 14c,d). Comparing with NoISO (Fig. 14d), MR shows stronger variations, especially in the western-to-central Pacific Basin (Fig. 14c). Some of the enhanced signals show a discernible correspondence with the eastward-propagating τx anomalies. This suggests the MJO’s role in inducing the westward-propagating surface current anomalies. In the western basin, the signals travel in a speed of 0.3–0.6 m s−1, roughly consistent with the observed phase speed of the first baroclinic mode Rossby waves at these latitudes (Kessler 1990). At this latitude range, we can still see signatures of the TIWs, as indicated by the resemblance between Figs. 14b and 14d. The large TIW signatures at 3°–8°N are also in line with the well-established notion that the variance maximum of TIWs occurs to the north of the equator (Qiao and Weisberg 1995; Yu et al. 1995; Chelton et al. 2000). In the western basin, there are weaker internal ISV signals (Fig. 14d) that could be either mesoscale eddies or meanders of the NECC (e.g., Heron et al. 2006; Zhao et al. 2013; Chen et al. 2015).
c. Origin of the ocean internal variability
Annual-mean climatology (10−7 m3 s−3) of (a) BC, (b) BC1, (c) BC2, (d) BT, (e) BT1, and (f) BT2 vertically integrated over the upper 150 m of the NoISO output. See the text for the detailed definition and interpretation of these terms.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Annual-mean climatology (10−7 m3 s−3) of (a) BC, (b) BC1, (c) BC2, (d) BT, (e) BT1, and (f) BT2 vertically integrated over the upper 150 m of the NoISO output. See the text for the detailed definition and interpretation of these terms.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
Annual-mean climatology (10−7 m3 s−3) of (a) BC, (b) BC1, (c) BC2, (d) BT, (e) BT1, and (f) BT2 vertically integrated over the upper 150 m of the NoISO output. See the text for the detailed definition and interpretation of these terms.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
5. Summary and discussion
The upper tropical Pacific Ocean circulation is characterized by alternating zonal currents, such as the NEC, NECC, SEC, and SECC. While the seasonal, interannual, and decadal variabilities of these currents have been extensively studied in the existing literature, their variability on the intraseasonal time scale was rarely explored because of the lack of observational data with sufficient resolution and continuity. In this study, we attempt to systematically describe and explain the ISV of the surface zonal currents in the WTPO using satellite observational data and OGCM experiments. Based on the U30 estimate of the OSCAR product, ISV of the surface current is strongest in the equatorial band with the rms magnitude exceeding 20 cm s−1. The amplitude decreases with latitude, to ~10 cm s−1 in the NECC and further to 4–8 cm s−1 in the NEC and SECC. Over much of the WTPO, the ISV accounts for at least 50% of seasonal variability. The ISV of the surface geostrophic current UG from the AVISO sea level product shows similar distribution and magnitude, and thus the surface current ISV is predominantly contributed by the geostrophic component. The power of the ISV exhibits a generally increasing trend from high frequencies to low frequencies. Near the equator enhanced power is seen at the 40–60-day band.
A simulation of HYCOM forced by satellite winds can well represent the structure of upper-ocean circulation in the WTPO and reproduce the observed ISV with realistic spatial–temporal characteristics. A series of HYCOM experiments are performed to gain insights into the underlying mechanisms. The results show that the pointwise ISV is dominated by ocean internal variability with mesoscale structures; while the large-scale ISV is primarily induced by atmospheric ISOs though wind stress forcing. The mechanism of surface current ISV is dependent on the length scale. Ocean internal ISV dominates short length scales (L < 200 km), and its impact decreases rapidly with L as short-scale signals are averaged out. The ISO-forced ISV increases with L and dominates the total ISV at L > 500 km. Power spectrum analysis suggests that wind stress forcing of the ISOs greatly contributes to the large power of lower-frequency (60–90 days) ISV, and the 50–60-day power peak in the equatorial region is probably induced by MJO, which have a typical period of 30–60 days. Further analysis demonstrates that the signatures of the MJO on surface currents are basically confined between 10°S and 8°N. Packages of surface current anomalies exhibit a swift eastward-moving tendency, closely following the eastward-propagating MJO winds. At the equator, the MJO winds produce intraseasonal equatorial Kelvin waves that propagate eastward across the Pacific Basin within 3–4 months. Away from the equator, the MJO wind-forced surface current ISV exists as westward-propagating, intraseasonal Rossby waves.
We further explored the origin of the ocean internal ISV by examining the possible effects of baroclinic and barotropic instabilities, which are the two primary causes for mesoscale ocean internal ISV in the open ocean. We computed the baroclinic and barotropic conversion terms (BC and BT) between the background flow and mesoscale ocean internal variability. Both baroclinic and barotropic instabilities are responsible for the ocean internal ISV in the WTPO. Baroclinic instability is particularly important for the NEC, while barotropic instability dominates in the NECC and SEC. In the Pacific interior, dynamical instabilities are mainly induced by the strong vertical and horizontal shears of the zonal currents, while near the western boundary shears of the meridional flows, such as the Kuroshio and Mindanao Current, are crucial.
In NoISO, seasonal and interannual variations are still retained in the forcing fields, which may also affect ISV through the nonlinearity of the ocean (see section 2b). Such a low-frequency forcing effect can be assessed by comparing MR and NoLF. After removing low-frequency forcing, ISV in NoLF shows little difference from MR (Fig. 9), with close rms magnitudes and high correlations with MR (0.78–0.91). This result suggests that comparing with intraseasonal wind stress and ocean internal variability, the effect of low-frequency forcing on the total surface current ISV is much smaller and thus out of our focus. Surface current ISV also exhibits seasonal and interannual variations in its amplitude. Previous researches have investigated the causes for the seasonal or interannual variabilities of the ISV activity in different regions. Their research usually focused on a specific type of ISV, such as intraseasonal equatorial Kelvin waves (Shinoda et al. 2008), mesoscale eddies (e.g., Qiu 1999; Qiu and Chen 2004; Yang et al. 2013; Chen et al. 2015), and submesoscale eddies/filaments (Qiu et al. 2014). Because of the difference in the generation mechanism, the activity variation and the controlling factors are usually different for each type. As a result, it is difficult to perform an in-depth investigation for the seasonal/interannual variations of the ISV in such a large region as the WTPO. We, however, provide a preliminary discussion for the seasonality. Figure 16 shows the seasonal cycle of the rms U150 ISV, where rms ISV is computed for each calendar month. In all six boxes, the ISV amplitude exhibits evident seasonality. The NECC-E, SEC, and SECC have stronger total ISV in winter and weaker total ISV in summer. This is largely attributable to the seasonality of the MJO (e.g., Zhang 2005), which shows a larger activity in winter (also indicated in Fig. 14). On the other hand, the ISV in NoISO (blue) is also generally stronger in winter than in summer, indicating that ocean internal variability also contributes to the seasonality of ISV. This is not surprising, given the knowledge that the TIWs are enhanced in fall–winter when the equatorial current shear is largest (Fig. 14b; Lee et al. 2012) and the mesoscale eddy variability in the SECC is enhanced in late winter–spring (Qiu and Chen 2004).
The seasonal cycle of rms U150 ISV from MR (black), NoISO (blue), TAU (red), and NoLF (green) in the six regions. The rms U150 ISV is computed for each calendar month. The annual-mean rms ISV is removed.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
The seasonal cycle of rms U150 ISV from MR (black), NoISO (blue), TAU (red), and NoLF (green) in the six regions. The rms U150 ISV is computed for each calendar month. The annual-mean rms ISV is removed.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
The seasonal cycle of rms U150 ISV from MR (black), NoISO (blue), TAU (red), and NoLF (green) in the six regions. The rms U150 ISV is computed for each calendar month. The annual-mean rms ISV is removed.
Citation: Journal of Physical Oceanography 46, 12; 10.1175/JPO-D-16-0033.1
The situations in the NEC-W and NECC-W are quite different (Figs. 16a,c). The total ISV tends to be stronger in summer and weaker in winter, and the ocean internal variability has nothing to do with it. Such seasonality may be related to the summertime surface warming in this region, which destabilizes the atmosphere and leads to enhanced atmospheric convection fluctuations (e.g., Gadgil et al. 1984). These intraseasonal convection events, not only the MJO but also the summer monsoon ISO (e.g., Goswami and Ajaya Mohan 2001), may in turn cause the enhanced ocean ISV in the far WTPO region (NEC-W and NECC-W). In the NEC-E region, the ISV is strong (weak) in spring (fall), and the seasonality is partly contributed by ocean internal variability (Fig. 16b). This seasonality may be induced by the combined effect of different factors. Another interesting issue is to distinguish the effects of ISO activity and ocean background state on the seasonality of ISV. As shown in the above analysis, stronger ISO activity in a season can cause enhanced ocean ISV; the change in the ocean background state, such as stratification and background current shear, can also modulate the amplitude of oceanic ISV. Particularly, the development of ocean internal variabilities strongly depends on the ocean background state. In the NoLF experiment, seasonal ocean variation is removed, and the seasonality of oceanic ISV is determined predominantly by the activity of ISO forcing. One can see in Fig. 16 that the rms ISV from NoLF (green) is roughly consistent with that of MR (black) in the seasonal cycle. It means that the ISO activity plays a more important role than the ocean background state in determining the amplitude of surface current ISV. In section 4, we have demonstrated that large-scale surface current ISV is primarily induced by ISO wind forcing. This type of ISV is more sensitive to the strength of ISO wind forcing rather than the ocean background state. Besides the seasonality, interannual variations of the ISV are also pronounced and even more intriguing due to its connection to ENSO, which is the theme of our ongoing research.
During the past several decades, targeted in situ measurements by moorings and buoys are increasing rapidly throughout the world’s ocean as many countries are beginning to participate in the Global Ocean Observing System. Their measurements provide continuous records of the ocean condition and uncover new features of oceanic variability. In the WTPO, most of observed seasonal and interannual circulation variations were successfully attributed to the wind forcing associated with climate modes (e.g., Sprintall and McPhaden 1994; Kashino et al. 2011). Pronounced ISV is also detected in moored in situ observations, but its connection with intraseasonal wind forcing is usually not evident (e.g., Hu et al. 2013; Zhang et al. 2014; Kashino et al. 2015). Our results suggest that in most areas of the WTPO, the surface-layer current ISV at a single point is predominantly a manifestation of ocean internal variability, providing an explanation for the observed, weak relationship between current ISV and wind forcing. The ocean internal variabilities can develop in various forms, such as eddies, TIWs, meanders, and filaments. However, it is difficult to distinguish the contributions of different types to the total ISV. In some regions, the ISV event exits as in a “mixed” type, such as the eddy/meander on the NECC (e.g., Zhao et al. 2013) and eddy/filament in the subtropical countercurrent region (e.g., Qiu et al. 2014). In most of this paper, we do not distinguish different types and consider them broadly as “ocean internal ISV.” Nevertheless, our eddy-permitting (⅓° × ⅓°) simulation is insufficient to resolve some of these internal ISVs in some areas such as the subtropical countercurrent and the SECC. As shown in Figs. 3–7, there are discernible discrepancies in the HYCOM-simulated surface current from OSCAR and TAO/TRITON data. A more accurate description and understanding of the surface current ISVs require further investigations using datasets or simulations with higher resolution and quality.
Acknowledgments
This research is supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA11010201), the National Basic Research (973) Program of China through Grant 2012CB417401, the NSFC Innovative Group Grant (41421005), and the NSFC-Shandong Joint Fund for Marine Science Research Centers (U1406401). Two anonymous reviewers provided important suggestions for improving our work. HYCOM model experiments are performed on the INDOPAC cluster maintained the Information Technology (OIT) of University of Colorado and the JANUS supercomputer supported by the National Science Foundation (Award Number CNS-0821794) and the University of Colorado.
[OSCAR ocean surface current data are available at http://www.oscar.noaa.gov/; AVISO sea level product is downloaded from http://www.aviso.oceanobs.com/; in-situ observational data of the TAO/TRITON buoys are provided by the NOAA Pacific Marine Environmental Laboratory (PMEL) through the website http://www.pmel.noaa.gov/tao/index.shtml; CCMP sea surface wind data are downloaded from http://podaac.jpl.nasa.gov/; the real-time multivariate MJO (RMM) index is obtained from the Bureau of Meteorology of Australia through http://www.bom.gov.au/climate/mjo/; satellite daily OLR data are provided by the NOAA Earth System Research Laboratory (ESRL) through the website http://www.esrl.noaa.gov/psd/data/; and data processing and graphing work in this study are finished with a licensed MATLAB program.]
REFERENCES
Antonov, J. I., and Coauthors, 2010: Salinity. Vol. 2, World Ocean Atlas 2009, NOAA Atlas NESDIS 69, 184 pp.
Atlas, R., J. Ardizzoneb, and R. N. Hoffmanc, 2008: Application of satellite surface wind data to ocean wind analysis. Remote Sensing Systems Engineering, P. E. Ardanuy and J. J. Puschell, Eds., International Society for Optical Engineering (SPIE Proceedings, Vol. 7087), 70870B, doi:10.1117/12.795371.
Bleck, R., 2002: An oceanic general circulation model framed in hybrid isopycnic-Cartesian coordinates. Ocean Modell., 4, 55–88, doi:10.1016/S1463-5003(01)00012-9.
Bonjean, F., and G. S. E. Lagerloef, 2002: Diagnostic model and analysis of the surface currents in the tropical Pacific Ocean. J. Phys. Oceanogr., 32, 2938–2954, doi:10.1175/1520-0485(2002)032<2938:DMAAOT>2.0.CO;2.
Chelton, D. B., R. A. DeSzoeke, M. G. Schlax, K. El Naggar, and N. Siwertz, 1998: Geographical variability of the first baroclinic Rossby radius of deformation. J. Phys. Oceanogr., 28, 433–460, doi:10.1175/1520-0485(1998)028<0433:GVOTFB>2.0.CO;2.
Chelton, D. B., F. J. Wentz, C. L. Gentemann, R. A. de Szoeke, and M. G. Schlax, 2000: Satellite microwave SST observations of transequatorial tropical instability waves. Geophys. Res. Lett., 27, 1239–1242, doi:10.1029/1999GL011047.
Chen, S., and B. Qiu, 2004: Seasonal variability of the South Equatorial Countercurrent. J. Geophys. Res., 109, C08003, doi:10.1029/2003JC002243.
Chen, X., B. Qiu, S. Chen, Y. Qi, and Y. Du, 2015: Seasonal eddy kinetic energy modulations along the North Equatorial Countercurrent in the western Pacific. J. Geophys. Res. Oceans, 120, 6351–6362, doi:10.1002/2015JC011054.
Clement, A. C., R. Seager, and R. Murtugudde, 2005: Why are there tropical warm pools? J. Climate, 18, 5294–5311, doi:10.1175/JCLI3582.1.
Dee, D., and Coauthors, 2011: The ERA‐Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553–597, doi:10.1002/qj.828.
Delcroix, T., G. Eldin, M. H. Radenac, J. Toole, and E. Firing, 1992: Variation of the western equatorial Pacific Ocean, 1986–1988. J. Geophys. Res., 97, 5423–5445, doi:10.1029/92JC00127.
Donguy, J. R., and G. Meyers, 1996: Mean annual variation of transport of major currents in the tropical Pacific Ocean. Deep-Sea Res. I, 43, 1105–1122, doi:10.1016/0967-0637(96)00047-7.
Ducet, N., P. Le Traon, and G. Reverdin, 2000: Global high-resolution mapping of ocean circulation from TOPEX/Poseidon and ERS-1 and-2. J. Geophys. Res., 105, 19 477–19 498, doi:10.1029/2000JC900063.
Duchon, C. E., 1979: Lanczos filtering in one and two dimensions. J. Appl. Meteor., 18, 1016–1022, doi:10.1175/1520-0450(1979)018<1016:LFIOAT>2.0.CO;2.
Enfield, D. B., 1986: Zonal and seasonal variations of the near-surface heat balance of the equatorial Pacific Ocean. J. Phys. Oceanogr., 16, 1038–1054, doi:10.1175/1520-0485(1986)016<1038:ZASVOT>2.0.CO;2.
Gadgil, S., N. Joshi, and P. Joseph, 1984: Ocean–atmosphere coupling over monsoon regions. Nature, 312, 141–143, doi:10.1038/312141a0.
Goswami, B. N., and R. Ajaya Mohan, 2001: Intraseasonal oscillations and interannual variability of the Indian summer monsoon. J. Climate, 14, 1180–1198, doi:10.1175/1520-0442(2001)014<1180:IOAIVO>2.0.CO;2.
Gouriou, Y., and J. Toole, 1993: Mean circulation of the upper layers of the western equatorial Pacific Ocean. J. Geophys. Res., 98, 22 495–22 520, doi:10.1029/93JC02513.
Gu, D., and S. G. H. Philander, 1997: Interdecadal climate fluctuations that depend on exchange between the tropics and extratropics. Science, 275, 805–807, doi:10.1126/science.275.5301.805.
Hendon, H. H., B. Liebmann, and J. D. Glick, 1998: Oceanic Kelvin waves and the Madden–Julian oscillation. J. Atmos. Sci., 55, 88–101, doi:10.1175/1520-0469(1998)055<0088:OKWATM>2.0.CO;2.
Heron, S. F., E. J. Metzger, and W. J. Skirving, 2006: Seasonal variations of the ocean surface circulation in the vicinity of Palau. J. Oceanogr., 62, 413–426, doi:10.1007/s10872-006-0065-3.
Hsin, Y. C., and B. Qiu, 2012a: Seasonal fluctuations of the surface North Equatorial Countercurrent (NECC) across the Pacific Basin. J. Geophys. Res., 117, C06001, doi:10.1029/2011JC007794.
Hsin, Y. C., and B. Qiu, 2012b: The impact of Eastern-Pacific versus central-Pacific El Niños on the North Equatorial Countercurrent in the Pacific Ocean. J. Geophys. Res., 117, C11017, doi:10.1029/2012JC008362.
Hu, D., and Coauthors, 2013: Direct measurements of the Luzon Undercurrent. J. Phys. Oceanogr., 43, 1417–1425, doi:10.1175/JPO-D-12-0165.1.
Hu, D., and Coauthors, 2015: Pacific western boundary currents and their roles in climate. Nature, 522, 299–308, doi:10.1038/nature14504.
Jochum, M., and R. Murtugudde, 2004: Internal variability of the tropical Pacific Ocean. Geophys. Res. Lett., 31, L14309, doi:10.1029/2004GL020488.
Johnson, G. C., B. M. Sloyan, W. S. Kessler, and K. E. McTaggart, 2002: Direct measurements of upper ocean currents and water properties across the tropical Pacific during the 1990s. Prog. Oceanogr., 52, 31–61, doi:10.1016/S0079-6611(02)00021-6.
Johnson, E. S., F. Bonjean, G. S. E. Lagerloef, J. T. Gunn, and G. T. Mitchum, 2007: Validation and error analysis of OSCAR sea surface currents. J. Atmos. Oceanic Technol., 24, 688–701, doi:10.1175/JTECH1971.1.
Johnston, T. M. S., and M. A. Merrifield, 2000: Interannual geostrophic current anomalies in the near-equatorial western Pacific. J. Phys. Oceanogr., 30, 3–14, doi:10.1175/1520-0485(2000)030<0003:IGCAIT>2.0.CO;2.
Kashino, Y., A. Ishida, and S. Hosoda, 2011: Observed ocean variability in the Mindanao Dome region. J. Phys. Oceanogr., 41, 287–302, doi:10.1175/2010JPO4329.1.
Kashino, Y., I. Ueki, and H. Sasaki, 2015: Ocean variability east of Mindanao: Mooring observations at 7°N, revisited. J. Geophys. Res. Oceans, 120, 2540–2554, doi:10.1002/2015JC010703.
Kessler, W. S., 1990: Observations of long Rossby waves in the northern tropical Pacific. J. Geophys. Res., 95, 5183–5217, doi:10.1029/JC095iC04p05183.
Kessler, W. S., and B. A. Taft, 1987: Dynamic heights and zonal geostrophic transports in the central tropical Pacific during 1979–84. J. Phys. Oceanogr., 17, 97–122, doi:10.1175/1520-0485(1987)017<0097:DHAZGT>2.0.CO;2.
Kessler, W. S., and R. Kleeman, 2000: Rectification of the Madden–Julian oscillation into the ENSO cycle. J. Climate, 13, 3560–3575, doi:10.1175/1520-0442(2000)013<3560:ROTMJO>2.0.CO;2.
Kessler, W. S., M. J. McPhaden, and K. M. Weickmann, 1995: Forcing of intraseasonal Kelvin waves in the equatorial Pacific. J. Geophys. Res., 100, 10 613–10 631, doi:10.1029/95JC00382.
Kummerow, C., W. Barnes, T. Kozu, J. Shiue, and J. Simpson, 1998: The Tropical Rainfall Measuring Mission (TRMM) sensor package. J. Atmos. Oceanic Technol., 15, 809–817, doi:10.1175/1520-0426(1998)015<0809:TTRMMT>2.0.CO;2.
Lee, T., G. Lagerloef, M. M. Gierach, H. Y. Kao, S. Yueh, and K. Dohan, 2012: Aquarius reveals salinity structure of tropical instability waves. Geophys. Res. Lett., 39, L12610, doi:10.1029/2012GL052232.
Lengaigne, M., J.-P. Boulanger, C. Menkes, S. Masson, G. Madec, and P. Delecluse, 2002: Ocean response to the March 1997 westerly wind event. J. Geophys. Res., 107, 8015, doi:10.1029/2001JC000841.
Le Traon, P., F. Nadal, and N. Ducet, 1998: An improved mapping method of multisatellite altimeter data. J. Atmos. Oceanic Technol., 15, 522–534, doi:10.1175/1520-0426(1998)015<0522:AIMMOM>2.0.CO;2.
Li, Y., and W. Han, 2016: Causes for intraseasonal sea surface salinity variability in the western tropical Pacific Ocean and its seasonality. J. Geophys. Res. Oceans, 121, 85–103, doi:10.1002/2015JC011413.
Li, Y., W. Han, T. Shinoda, C. Wang, R. C. Lien, J. N. Moum, and J. W. Wang, 2013: Effects of the diurnal cycle in solar radiation on the tropical Indian Ocean mixed layer variability during wintertime Madden-Julian oscillations. J. Geophys. Res. Oceans, 118, 4945–4964, doi:10.1002/jgrc.20395.
Li, Y., W. Han, and T. Lee, 2015: Intraseasonal sea surface salinity variability in the equatorial Indo-Pacific Ocean induced by Madden-Julian oscillations. J. Geophys. Res. Ocean, 120, 2233–2258, doi:10.1002/2014JC010647.
Liebmann, B., and C. A. Smith, 1996: Description of a complete (interpolated) outgoing longwave radiation dataset. Bull. Amer. Meteor. Soc., 77, 1275–1277.
Locarnini, R. A., A. V. Mishonov, J. I. Antonov, T. P. Boyer, H. E. Garcia, O. K. Baranova, M. M. Zweng, and D. R. Johnson, 2010: Temperature. Vol. 1, World Ocean Atlas 2009, NOAA Atlas NESDIS 68, 184 pp.
Lorenz, E. N., 1955: Available potential energy and the maintenance of the general circulation. Tellus, 7A, 157–167, doi:10.1111/j.2153-3490.1955.tb01148.x.
Lukas, R., and E. Firing, 1984: The geostrophic balance of the Pacific Equatorial Undercurrent. Deep-Sea Res. I, 31, 61–66, doi:10.1016/0198-0149(84)90072-4.
Madden, R. A., and P. R. Julian, 1971: Detection of a 40–50 day oscillation in the zonal wind in the tropical Pacific. J. Atmos. Sci., 28, 702–708, doi:10.1175/1520-0469(1971)028<0702:DOADOI>2.0.CO;2.
Masumoto, Y., and T. Yamagata, 1991: Response of the western tropical Pacific to the Asian winter monsoon: The generation of the Mindanao Dome. J. Phys. Oceanogr., 21, 1386–1398, doi:10.1175/1520-0485(1991)021<1386:ROTWTP>2.0.CO;2.
McPhaden, M. J., 1995: The Tropical Atmosphere–Ocean Array is completed. Bull. Amer. Meteor. Soc., 76, 739–741.
McPhaden, M. J., and D. Zhang, 2002: Slowdown of the meridional overturning circulation in the upper Pacific Ocean. Nature, 415, 603–608, doi:10.1038/415603a.
Meyers, G., 1979: On the annual Rossby wave in the tropical North Pacific Ocean. J. Phys. Oceanogr., 9, 663–674, doi:10.1175/1520-0485(1979)009<0663:OTARWI>2.0.CO;2.
Meyers, G., and J. R. Donguy, 1984: The North Equatorial Countercurrent and heat storage in the western Pacific Ocean during 1982–83. Nature, 312, 258–260, doi:10.1038/312258a0.
Moore, A. M., and R. Kleeman, 1999: Stochastic forcing of ENSO by the intraseasonal oscillation. J. Climate, 12, 1199–1220, doi:10.1175/1520-0442(1999)012<1199:SFOEBT>2.0.CO;2.
Oey, L. Y., 2008: Loop Current and deep eddies. J. Phys. Oceanogr., 38, 1426–1449, doi:10.1175/2007JPO3818.1.
Pedlosky, J., 1987: Geophysical Fluid Dynamics. 2nd ed. Springer-Verlag, 710 pp.
Qiao, L., and R. H. Weisberg, 1995: Tropical instability wave kinematics: Observations from the Tropical Instability Wave Experiment. J. Geophys. Res., 100, 8677–8693, doi:10.1029/95JC00305.
Qiu, B., 1999: Seasonal eddy field modulation of the North Pacific Subtropical Countercurrent: TOPEX/Poseidon observations and theory. J. Phys. Oceanogr., 29, 2471–2486, doi:10.1175/1520-0485(1999)029<2471:SEFMOT>2.0.CO;2.
Qiu, B., and T. M. Joyce, 1992: Interannual variability in the mid- and low-latitude western North Pacific. J. Phys. Oceanogr., 22, 1062–1079, doi:10.1175/1520-0485(1992)022<1062:IVITMA>2.0.CO;2.
Qiu, B., and R. Lukas, 1996: Seasonal and interannual variability of the North Equatorial Current, the Mindanao Current, and the Kuroshio along the Pacific western boundary. J. Geophys. Res., 101, 12 315–12 330, doi:10.1029/95JC03204.
Qiu, B., and S. Chen, 2004: Seasonal modulations in the eddy field of the South Pacific Ocean. J. Phys. Oceanogr., 34, 1515–1527, doi:10.1175/1520-0485(2004)034<1515:SMITEF>2.0.CO;2.
Qiu, B., and S. Chen, 2012: Multidecadal sea level and gyre circulation variability in the northwestern tropical Pacific Ocean. J. Phys. Oceanogr., 42, 193–206, doi:10.1175/JPO-D-11-061.1.
Qiu, B., M. Mao, and Y. Kashino, 1999: Intraseasonal variability in the Indo–Pacific throughflow and the regions surrounding the Indonesian Seas. J. Phys. Oceanogr., 29, 1599–1618, doi:10.1175/1520-0485(1999)029<1599:IVITIP>2.0.CO;2.
Qiu, B., S. Chen, P. Klein, H. Sasaki, and Y. Sasai, 2014: Seasonal mesoscale and submesoscale eddy variability along the North Pacific Subtropical Countercurrent. J. Phys. Oceanogr., 44, 3079–3098, doi:10.1175/JPO-D-14-0071.1.
Qiu, B., D. L. Rudnick, I. Cerovecki, B. D. Cornuelle, S. Chen, M. C. Schönau, J. L. McClean, and G. Copalakrishnan, 2015: The Pacific North Equatorial Current: New insights from the origins of the Kuroshio and Mindanao Currents (OKMC) project. Oceanography, 28, 24–33, doi:10.5670/oceanog.2015.78.
Reid, J. L., 1959: Evidence of a South Equatorial Countercurrent in the Pacific Ocean. Nature, 184, 209–210, doi:10.1038/184209a0.
Reid, J. L., 1986: On the total geostrophic circulation of the South Pacific Ocean: Flow patterns, traces and transports. Prog. Oceanogr., 16, 1–61, doi:10.1016/0079-6611(86)90036-4.
Reverdin, G., C. Frankignoul, E. Kestenare, and M. J. McPhaden, 1994: Seasonal variability in the surface currents of the equatorial Pacific. J. Geophys. Res., 99, 20 323–20 344, doi:10.1029/94JC01477.
Roundy, P. E., and G. N. Kiladis, 2006: Observed relationships between oceanic Kelvin waves and atmospheric forcing. J. Climate, 19, 5253–5272, doi:10.1175/JCLI3893.1.
Shinoda, T., P. E. Roundy, and G. N. Kiladis, 2008: Variability of intraseasonal Kelvin waves in the equatorial Pacific Ocean. J. Phys. Oceanogr., 38, 921–944, doi:10.1175/2007JPO3815.1.
Shinoda, T., H. E. Hurlburt, and E. J. Metzger, 2011: Anomalous tropical ocean circulation associated with La Niña Modoki. J. Geophys. Res., 116, C12001, doi:10.1029/2011JC007304.
Sprintall, J., and M. J. McPhaden, 1994: Surface layer variations observed in multiyear time series measurements from the western equatorial Pacific. J. Geophys. Res., 99, 963–979, doi:10.1029/93JC02809.
Taft, B. A., and W. S. Kessler, 1991: Variations of zonal currents in the central tropical Pacific during 1970 to 1987: Sea level and dynamic height measurements. J. Geophys. Res., 96, 12 599–12 618, doi:10.1029/91JC00781.
Toole, J., R. Millard, Z. Wang, and S. Pu, 1990: Observations of the Pacific North Equatorial Current bifurcation at the Philippine coast. J. Phys. Oceanogr., 20, 307–318, doi:10.1175/1520-0485(1990)020<0307:OOTPNE>2.0.CO;2.
Wang, F., J. Wang, C. Guan, Q. Ma, and D. Zhang, 2016: Mooring observation of equatorial currents over upper 1000 m depth in the western Pacific Ocean in 2014. J. Geophys. Res. Oceans, 121, doi:10.1002/2015JC011510, in press.
Wheeler, M. C., and H. H. Hendon, 2004: An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. Mon. Wea. Rev., 132, 1917–1932, doi:10.1175/1520-0493(2004)132<1917:AARMMI>2.0.CO;2.
Wielicki, B. A., B. R. Barkstrom, E. F. Harrison, R. B. Lee III, G. Louis Smith, and J. E. Cooper, 1996: Clouds and the Earth’s Radiant Energy System (CERES): An Earth Observing System experiment. Bull. Amer. Meteor. Soc., 77, 853–868, doi:10.1175/1520-0477(1996)077<0853:CATERE>2.0.CO;2.
Wyrtki, K., 1974: Sea level and the seasonal fluctuations of the equatorial currents in the western Pacific Ocean. J. Phys. Oceanogr., 4, 91–103, doi:10.1175/1520-0485(1974)004<0091:SLATSF>2.0.CO;2.
Wyrtki, K., and R. Kendall, 1967: Transports of the Pacific Equatorial Countercurrent. J. Geophys. Res., 72, 2073–2076, doi:10.1029/JZ072i008p02073.
Yang, G., F. Wang, Y. Li, and P. Lin, 2013: Mesoscale eddies in the northwestern subtropical Pacific Ocean: Statistical characteristics and three‐dimensional structures. J. Geophys. Res. Oceans, 118, 1906–1925, doi:10.1002/jgrc.20164.
Yu, Z., J. P. McCreary, and J. A. Proehl, 1995: Meridional asymmetry and energetics of tropical instability waves. J. Phys. Oceanogr., 25, 2997–3007, doi:10.1175/1520-0485(1995)025<2997:MAAEOT>2.0.CO;2.
Yu, Z., J. P. McCreary, W. S. Kessler, and K. A. Kelly, 2000: Influence of equatorial dynamics on the Pacific North Equatorial Countercurrent. J. Phys. Oceanogr., 30, 3179–3190, doi:10.1175/1520-0485(2000)030<3179:IOEDOT>2.0.CO;2.
Zhang, C., 2005: Madden-Julian oscillation. Rev. Geophys., 43, RG2003, doi:10.1029/2004RG000158.
Zhang, L., D. Hu, S. Hu, F. Wang, F. Wang, and D. Yuan, 2014: Mindanao Current/Undercurrent measured by a subsurface mooring. J. Geophys. Res. Oceans, 119, 3617–3628, doi:10.1002/2013JC009693.
Zhao, J., Y. Li, and F. Wang, 2013: Dynamical responses of the west Pacific North Equatorial Countercurrent (NECC) system to El Niño events. J. Geophys. Res. Oceans, 118, 2828–2844, doi:10.1002/jgrc.20196.