JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 111, C04013, doi:10.1029/2005JC003080, 2006

Seasonal to interannual variations of the western of the subarctic North Pacific by a combination of the altimeter and gauge levels Osamu Isoguchi1 and Hiroshi Kawamura1 Received 31 May 2005; revised 30 November 2005; accepted 20 January 2006; published 28 April 2006.

[1] Seasonal to interannual variations of the East Kamchatka Current (EKC) and the Oyashio are examined by focusing on their barotropic response to wind forcing by a combined use of altimeter-derived and sea levels. An empirical orthogonal function (EOF) analysis is performed on the 9-year altimeter maps with thermosteric signals removed. A second EOF (EOF2) shows a spin-up and spin-down of the subarctic gyres, and its temporal variation is almost accounted for by the time- dependent Sverdrup balance. Tide gauge sea levels at Petropavlovsk-Kamchatsky (PK) agree with EOF2 and the Sverdrup transports in terms of not only the seasonal variation but also its year-to-year variability in winter when the subarctic gyre is spun up most. We also detect two types of EKC/Oyashio variations from the altimeter data: drifting velocities of sea level disturbances and geostrophic velocity anomalies. These two EKC/ Oyashio temporal variations are also accounted for by the Sverdrup balance and agree with the PK sea levels and EOF2. The results imply that the PK sea levels can be a good representative of the subarctic gyre and EKC/Oyashio variations. On the basis of this relation, interannual variations during winter are discussed. The 44-year wintertime sea levels at PK correlate with the wintertime Sverdrup transport and springtime sea surface off the northeastern coast of Japan with decadal-scale variability. This demonstrates that EKC/Oyashio is primarily explained by a barotropic response to large- scale atmospheric forcing and fluctuates on a decadal timescale almost in phase with atmospheric changes and influences the oceanic condition east of Japan. Citation: Isoguchi, O., and H. Kawamura (2006), Seasonal to interannual variations of the western boundary current of the subarctic North Pacific by a combination of the altimeter and tide gauge sea levels, J. Geophys. Res., 111, C04013, doi:10.1029/2005JC003080.

1. Introduction which is characterized by a minimum in the North Pacific subtropical gyre [e.g., Talley, 1993; Talley et al., [2] The East Kamchatka Current (EKC), which is a part of 1995; Yasuda et al., 1996, 2001]. The North Pacific Inter- western boundary currents of the subarctic North Pacific, mediate Water is the deepest and densest water mass flows southwestward along the Kamchatka Peninsula and ventilating the North Pacific, and have a great impact on the Kuril Islands. A part of EKC enters the Okhotsk Sea, long-term climate changes. Understanding and predicting establishes circulation and then exits into the North Pacific. the variation of the subarctic gyre and EKC/Oyashio are thus This water forms the Oyashio by mixing with the water that important for not only societal aspects but also oceano- has directly flown southwestward along the Kuril Islands. graphic and climatic interests. The Oyashio carries cold, fresh, oxygen and nutrient-rich [3] The Oyashio sometimes intrudes anomalously south- water toward the Pacific coast of Japan. Its behavior has a ward along the Sanriku coast with cold water from winter to great impact on fishing grounds [e.g., Yasuda and Watanabe, late spring and directly influences coastal weather and 1994; Yasuda and Kitagawa, 1996], as well as agriculture oceanic conditions. Figure 1 shows a sea surface tempera- through weather conditions in northeastern Japan. Addition- ture (SST) field on 10 April 2003, from the New Generation ally, it has been reported that isopycnal mixing between the SST data (http://www.ocean.caos.tohoku.ac.jp/merge/ cold and fresh Oyashio water and warm and salty Kuroshio sstbinary/actvalbm.cgi?eng=1). These data have been qual- water is a possible mechanism of the formation of North ity controlled, and generated on a high spatial resolution Pacific Intermediate Water [e.g., Sverdrup et al., 1942], (0.05 0.05), on daily basis by objectively merging satellite SST observations from infrared radiometers (Ad- 1Center for Atmospheric and Oceanic Studies, Graduate School of vanced Very High Resolution Radiometers (AVHRR) and Science, Tohoku University, Miyagi, Japan. Moderate Resolution Imaging Spectroradiometer (MODIS)) and microwave radiometer (Advanced Microwave Scanning Copyright 2006 by the American Geophysical Union. 0148-0227/06/2005JC003080$09.00 Radiometer–Earth Observing System (AMSR-E)) [Guan

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Figure 1. (SST) image from the New Generation Sea Surface Temperature (NGSST) product on 10 April 2003. Schematic illustration of the surface currents (East Kamchatka Current (EKC) and Oyashio), geographical features cited in this study, and bathymetric lines are superimposed every 2000 m. Grids used for computation of sea level anomaly (SLA) maps along the western boundary are also shown with gray dots. and Kawamura, 2004]. A southward intrusion of cold water observations [Uehara et al., 1997; Kono and Kawasaki, appears along the Sanriku coast. In early spring when the 1997] and satellite altimeter measurements [Isoguchi et al., Oyashio advances more southward, the mixed layer deepens 1997; Qiu, 2002b; Ito et al., 2004]. EKC/Oyashio strength- up to 100 m; hence SST fields can be used as a good ens in winter and weakens in summer and fall, which is representative of temperature at that depth, which has been approximately explained by the time-dependent Sverdrup conventionally used to define the Oyashio water. Many dynamics [Isoguchi et al., 1997; Qiu, 2002b]. Altimeter- studies focusing on the year-to-year variation of the derived large-scale and low-frequency (>30 days) sea level Oyashio southward intrusion have been conducted using variations with the steric height component removed have an index based on temperature fields at a depth of 100 m also been described by the time-dependent Sverdrup bal- [Sekine, 1988, 1999; Hanawa, 1995]. Sekine [1988] showed ance in the subarctic North Pacific [Fu and Davidson, 1995; that the anomalous southward intrusion of the Oyashio is Isoguchi et al., 1997; Stammer, 1997; Vivier et al., 1999]. linked to development of the prominent Aleutian low. [5] Tide gauge sea level records collected for over several Moreover, Sekine [1999] successfully simulated the anom- decades all over the world are very useful data set for long- alous southward intrusions by using a two-layer model, and term studies. Sea level varies intensively in regions of pointed out these could be explained by a barotropic strong currents. Indeed, many studies have been conducted response to wind fields related to the development of the by using the tide gauge records along the Kuroshio path to Aleutian low. Hanawa [1995] pointed out that there exists estimate and describe its variations and volume transport an agreement between annual mean southernmost latitudes [e.g., Kawabe, 1980, 2001]. In the subarctic region, on the of the Oyashio intrusions and the wintertime Sverdrup other hand, only a few studies have been done probably transports, and proposed a simple prediction model for because of following reasons. (1) There exist only a few tide these intrusions. gauges but no stations exist on both sides of a current axis, [4] With the accumulation of observations with a finer and (2) the EKC/Oyashio-induced signals seem to have a resolution in time and space, we began to investigate lower variability. Kashiwai [1991] established a relation seasonal to interannual variations of EKC/Oyashio. Distinct between tide gauge sea levels along EKC/Oyashio and other seasonality of the Oyashio variation has been revealed by indices related to the variation of the subarctic gyre, that is, direct current measurements and repeated hydrographic the southernmost latitude of the Oyashio intrusions and

2of17 C04013 ISOGUCHI AND KAWAMURA: WIND-DRIVEN EKC/OYASHIO VARIATIONS C04013 coastal SSTs. He showed a significant negative correlation and Altimeter Combination System (SSALTO/DUACS) between the sea level at the Petropavlovsk-Kamchatsky Delayed Time Sea Level Anomalies (DT-MSLA)’’, which (PK; see Figure 1) and the monthly zonal index for the is a project that produces maps of sea level anomaly (SLA) Far East, which is defined as a difference of 500 hPa height obtained from the TOPography Experiment for 90–170E between 40 and 60N and which describes (TOPEX)/Poseidon and European Remote Sensing satellite the strength of winter monsoon and the meridional shifts of (ERS) observations; there are available every 7 days for the westerlies; however he showed no further linkage with the period from October 1992 to February 2002 (10 years). EKC/Oyashio variation. Isoguchi and Kawamura [2002] No ERS data were used between January 1994 and March showed that monthly sea levels at PK were in agreement, 1995, corresponding to the 168 day repeat cycle geodetic on a seasonal timescale, with the time series of a first mission of ERS-1 (phases E and F). The grid interval is a empirical orthogonal function (EOF) calculated from 6-year Mercator 1/3, ranging from 37 km at the equator to 18.5 km altimeter-derived sea level anomaly (SLA) maps north of at 60N/S. Details of data processing are described by Ducet 20N in the Pacific, which was correlated with the time et al. [2000]. series of the Sverdrup transport with a correlation of 0.57. [9] A dominant sea level variation in the extratropical Hurlburt et al. [1996] carried out numerical simulations open ocean, except for some coastal areas where wind- with a free surface hydrodynamic model, with realistic induced signals are important, is a steric height component geometry at 1/8 resolution, with six layers, and with caused by seasonal density variations, due to mainly in the realistic bottom topography and showed that simulated upper ocean expansion or contraction of the sea levels are in agreement with monthly sea levels at PK [Gill and Niiler, 1973]. This has been confirmed by hydro- with a correlation of 0.66. They also pointed out that in graphic observations [Gill and Niiler, 1973] and recently by the region east of PK, interface ventilation (isopycnal altimeter sea level data [e.g., Stammer, 1997; Vivier et al., outcropping) occurred strongly. 1999]. In this study, upper ocean steric signals are estimated [6] In the present study, we first evaluate the Isoguchi and and removed from sea level data, on the basis of the fact that Kawamura [2002] results by examining the relationship they hardly have any effect on higher-frequency currents. between the variation of a local tide gauge sea level at PK, Upper ocean steric height signals result from the changes in the altimeter-estimated EKC/Oyashio variations, and large- temperature and salinity. Because the latter halosteric height scale sea level variations for an extended time period longer signals are substantially smaller than the former thermo- than 9 years. Here we treat estimation of steric height steric signals over most of the North Pacific [Gill and Niiler, signals more distinctively, compared with our previous 1973; Vivier et al., 1999; Qiu, 2002b], only the thermosteric works. We adopt new index of the EKC/Oyashio variations signals are considered hereinafter. Following Stammer from the SLA data along EKC/Oyashio, in order to enhance [1997], Vivier et al. [1999], and Qiu [2002b], the thermo- 0 the credibility of our previous results. In addition, on the steric signals (h heat) are estimated using net surface heat basis of the relation between the local tide gauge sea level flux data as and the altimeter-derived large-scale sea level variations, Z t which is derived for the 9-year altimeter observation period, 0 0 1 0 a discussion on the subarctic gyre and EKC/Oyashio varia- hheatðÞt hheatðÞþt0 aT ðÞQnet À hiQnet dt ; ð1Þ rocp t tions is extended to include an interannual timescale by the 0 use of the tide gauge sea level records longer than 40 years. where ro and cp are reference density and the specific heat This study thus demonstrates the effectiveness of combining À1 of which are taken as constants; aT (=r @r/@T) tide gauge data with altimeter data for a long-term study. is the thermal expansion coefficient which spans 1 10À4 The remainder of this paper is as follows. Data used and the to 3 10À4 CÀ1 for ocean, which is derived from monthly method for estimation of steric height signals are described temperature and salinity fields [Levitus and Boyer, 1994; in section 2. In section 3, analyses using both tide gauge and Levitus et al., 1994]; Q is the net surface heat flux, which altimeter-derived sea levels and a long-term investigation net is also collected from the NCEP/NCAR reanalysis. hQneti is are presented. Section 4 is devoted to discussion and a time averaged value. Mixed layer depth (MLD) was section 5 gives summary and conclusions. determined as the depth where the potential density increased by 0.125 sigma-theta from the surface value, 2. Data and Methods and aT was calculated from the mean temperature and salinity averaged over the MLD. Thus monthly thermosteric [7] Tide gauge sea level records were provided from the heights were calculated on a 1 1 grid over the North Permanent Service for Mean Sea Level, hosted by the Pacific. The integration constant in function (1) was Proudman Oceanographic Laboratory [Woodworth, 1991]. determined such that the temporal mean becomes zero Monthly sea levels at PK (52590N, 158390E; see Figure 1) (i.e., the temporal anomalies were calculated). for the period from July 1957 to December 2001 (44 and a [10] The estimated thermosteric heights show an annual half year) are used. Inverted barometric pressure correction cycle with a maximum in fall. Their amplitudes were is applied by using monthly sea level pressure data provided calculated by harmonic analysis (Figure 2). These have a by the National Centers for Environmental Prediction/the maximum of about 10 cm around the Kuroshio Extension National Center for Atmospheric Research (NCEP/NCAR) and gradually decrease to 2 cm in the subarctic region and reanalysis (http://www.cdc.noaa.gov/). the eastern Pacific, in agreement with Vivier et al. [1999] [8] Altimeter data used in the present study have been and Qiu [2002b], indicating that the estimated values generated by ‘‘Segment Sol multimissions d’ALTime´trie, represent seasonal variations reasonably well. The errors d’Orbitographie et de localisation pre´cise/Data Unification

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Figure 2. Amplitude of the annual cycle of the thermosteric signals estimated from the net surface heat flux.

in Qnet and aT can induce an error factor in the estimated is located on the EKC region. Since the southward flow of thermosteric height. It has been reported by Trenberth et al. EKC is weak in summer and intensified in winter, the [2001] that seasonal net surface flux anomalies from NCEP/ advection does not transport a significant amount of heat NCAR and the Comprehensive Ocean Atmosphere Data Set toward PK. Therefore we consider that the heat advection is (COADS) agree well over the northern extratropical , not a major factor in the annual phase discrepancy at PK, with root-mean-square (RMS) differences of 10–13 WmÀ2. where the tide gauge sea level has a maximum in winter. This suggests that the time-varying component of Qnet, Hereinafter we will use the PK sea level time series after which is essential to the thermosteric height estimation, is removing the thermosteric signals. relatively accurate in our analyzed region. Nevertheless, [12] Global SST data were obtained from the Subarctic since some errors may be temporally integrated because of Gyre Experiment project (SAGE) [Japan Meteorological the nature of calculation, the errors with long-term fluctua- Agency, 2001], which contain monthly mean analyzed SSTs tions are apt to be generated and the distinct evaluation of for the period from January 1946 to December 2000 on a the errors for each component is difficult. Assuming 2 2 2 grid over the global ocean between 80S and 80N. standard deviations (s) of the thermosteric height anomalies The monthly mean SST is based on in situ SST data from the annual cycle as the maximum error in estimates of compiled by Japan Meteorological Agency, the Compre- the annual cycle, these are compared with the amplitudes of hensive Ocean–Atmosphere Data Set [Woodruff et al., the annual cycle (Figure 2). The maximum error approx- 1987], and AVHRR-based SST [Japan Meteorological imately corresponds to the 95% confidence interval for a Agency, 1990]. normally distributed variable. The 2s exceeds the amplitude [13] The North Pacific Index (NPI) data, which was of the annual cycle over some subtropical regions, whereas provided by the Climate Analysis Section, NCAR, Boulder, over almost the whole subarctic region (north of 40N), USA [Trenberth and Hurrell, 1994], is used as a long-term which is the main target here, the annual amplitude exceeds atmospheric index in the extratropical North Pacific. The 2s (the mean amplitude of 2.8 cm versus the mean 2s of NPI is the area-weighted sea level pressure over the region 2.0 cm). Hence we consider that the errors are not likely to 30N–65N, 160E–140W[Trenberth and Hurrell, 1994] be significant over the subarctic region. and is representative of the variability of the Aleutian low. [11] Monthly thermosteric signals near PK are also esti- mated on a decadal timescale (1957–2001). In this case, aT 3. Results is calculated from the decadal time series of the upper ocean 3.1. Altimeter-Derived Sverdrup Sea Level Pattern temperature data of White [1995] and the annual cycle of the and Its Relation With Local Tide Gauge Sea Levels salinity fields of Levitus et al. [1994]. The annual cycles of the tide gauge sea levels at PK and the estimated thermo- [14] We first examine a relation between the altimeter- steric signals at the nearest grid (53N, 160E) from PK are derived large-scale sea level pattern, the tide gauge sea depicted in Figure 3a while the residuals between them is levels at PK, and the Sverdrup transport variation for 9 and shown in Figure 3b. The amplitude of the thermosteric a half years spanning from October 1992 to February 2002. signals around PK is about 2 cm, which is significantly Isoguchi and Kawamura [2002] reported that the time series smaller than that of the tide gauge sea levels (6–7 cm). of the first EOF of the 6-year altimeter SLAs, which agreed This implies that the thermosteric signals are not a principal with the Sverdrup transport in subarctic, could explain the sea level component at PK. The original sea level cycle spin-up and spin-down of the subarctic gyre. Furthermore, (Figure 3a) has a maximum (minimum) in winter (summer), they found a good agreement between the EOF and monthly on the other hand, the sea level cycle after removing the tide gauge sea level at PK with a correlation of 0.63. We thermosteric signal (Figure 3b) indicates a minimum in fall, here revisit their analysis, extending a time period to over which emphasizes on an abrupt change from the minimum 9 years, focusing more on steric height effect. (fall) to the maximum (winter). In the thermosteric signal [15] The 7-day SLA maps were averaged to obtain estimation based on equation (1), contributions from advec- monthly maps to match the tide gauge data. Then we tion are neglected. Though an appropriate estimate of the averaged within a 1 1 box and the estimated thermo- heat advection is difficult, it can be one of possible error steric signals were subtracted from them. An EOF analysis sources in estimating the thermosteric signals at PK, which was performed for the residual SLA maps (hereinafter,

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Figure 3. (a) Annual cycles of monthly mean tide gauge sea levels at PK (black line) and monthly thermosteric signals near PK (gray line) and (b) their residuals (tide-thermosteric) for the period from 1957 to 2002 (black line) and the Sverdrup transport averaged over 40N–50N at 150E for the period from 1957 to 2002 (gray line). Vertical lines indicate standard deviations. The annual cycle is repeated twice side by side. referred to as SLA). A correlation matrix was used instead Figure 1d] who estimated how well altimeter-derived sea of a covariance for the EOF calculation so as not to be levels are represented by the topographic time-varying governed by large amplified sea level variations found in Sverdrup balance. the western Pacific. As a result of a significance test by the [17] The Sverdrup transport was calculated from the Monte Carlo technique [Overland and Preisendorfer, 1982], ocean surface wind data provided from the NCEP/NCAR only first 13 EOFs are found to be statistically significant at reanalysis. The monthly mean 10-m winds were first con- the 95% confidence level, in the sense that they are verted to wind stresses using wind speed-dependent drag distinguishable from noise. coefficients of Kondo [1975]. From curls the [16] The first EOF, which accounts for 14.9% of total Sverdrup transports were derived for 40–50N by inte- variance, exhibits an interannual variation, while the second grating the wind stress curl from the eastern boundary of the one (Figure 4, hereinafter referred to as EOF2), which Pacific to the Kuril-Kamchatka Trench, by assuming a flat accounts for 10.6%, suggests an annual (seasonal) variation bottomed ocean. In the subarctic region north of 40N, the pattern. These spatial patterns are found to be of physical bottom topography is flat, except for the Emperor Sea significance at the 95% confidence level by another signif- Mounts at 170E; since we deal with the western boundary icance test [Santhanam et al., 2002], in the sense that they transports only, which is integrated for a long distance over deviate from the Gaussian distribution. These derived the Pacific, topography-induced effects on the integrated dominant EOFs are somewhat different from our previous transports are thought to be unimportant. studies [Isoguchi et al., 1997; Isoguchi and Kawamura, [18] The time series of the Sverdrup transport anomalies, 2002], where the first EOF represented an annual pattern. averaged over 40–50N at 150E, are superimposed on Discussion on the differences and the description of the Figure 4b (gray line). The monthly time series correspond first EOF are given in Appendix A. In this work, we focus well with a correlation of 0.69, significant at 95% confi- only on EOF2 pattern. EOF2 exhibits a large variability in dence with 37 degrees of freedom. It is noted that, in this the subarctic region north of 40N; sea levels in the open study, the degrees of freedom are roughly estimated by ocean of the subarctic region fall in winter (shaded areas in dividing total time length by time intervals for which their Figure 4a). The spatial pattern in the northwestern Pacific is autocorrelations fall below 0.2. In the case of comparisons indeed reminiscent of the Western Subarctic Gyre. More- with the Sverdrup transports at 160E and 170E correla- over, the spatial pattern is similar to Vivier et al. [1999, tions are 0.67 and 0.65, respectively, which indicates that

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Figure 4. (a) Spatial pattern and (b) time coefficients of the second EOF of the SLA maps with thermosteric signals removed (EOF2). Contour interval in Figure 4a is 0.2. A cross on the spatial map indicates the grid at which the spatial coefficients have the maximum of 0.61. Monthly mean Sverdrup transport anomalies averaged over 40N–50N are also superimposed in Figure 4b (gray line), and their scale is shown on the right-hand side. the western extent of integration in the calculation of the waves, and barotropic Sverdrup balance), as done by Vivier Sverdrup transport hardly affects its temporal variation. This et al. [1999], will be important for the further discussion of is probably due to the fact that atmospheric fields related to the subtropical and subarctic gyres. changes in the strength and meridional positions of wester- [20] The monthly tide gauge sea level at PK is shown lies, which have a great effect on the Sverdrup transports in with a black line in Figure 5. It correlates well with the time the subarctic gyre, tend to have zonal structure. series of EOF2 and the Sverdrup transport with correlations [19] The two time series show not only the aforemen- of 0.62 and 0.67. They are significant to 95% confidence tioned seasonal feature with the maximum (minimum) in even if degrees of freedom are estimated as 9 on the basis of winter (fall) but also its year-to-year variation; relative the fact that characteristic timescales are annual variability. stronger (weaker) peaks appear in 1995/1996, 1997/1998, The time series of EOF2 is overlaid with a gray line. They and 1999/2000 (1993/1994, 1996/1997, and 1998/1999) show relatively similar seasonal tendency and year-to-year winters. This implies that EOF2 shows the spin-up and variability except for 1993 and 1997. Correlations decrease spin-down of the subarctic North Pacific, which is to 0.48 and 0.64 in the case of comparisons with the tide accounted for by the time-dependent Sverdrup balance. gauge sea levels including the thermosteric heights. This On the other hand, a spatially organized sea level pattern suggests the validity of removing thermosteric signals. for the whole subtropical gyre is not detected by the EOF Nevertheless the effect of the removing signals is not so calculation. Vivier et al. [1999] estimated the sea level large at PK since a ratio of the thermosteric signal to the components accounted for by various factors. They pointed total variance is small (see Figure 3a). out that the ratios of the sea level components due to the [21] It was shown that the time series of EOF2, the barotropic Sverdrup balance were low in the subtropical Sverdrup transports, and the PK sea levels have statistically North Pacific, where baroclinic westward propagation over- significant correlations especially in terms of seasonal whelmed the barotropic sea levels. The situation was variability. In the case of the year-to-year variability relative different from the subarctic region, in which the Sverdrup to their annual cycles, the correlations of EOF2 with the PK sea level components dominated the SLA variation after sea levels and the Sverdrup transports are 0.14 and 0.25, removing the steric height components. The SLA used for respectively. They indicate positive correlations but are not the EOF calculation in this study includes the propagating significant at the 95% confidence interval. However, as sea level components. A small ratio of the Sverdrup sea mentioned above, their year-to-year changes might corre- levels and contamination by other components may be the spond with each other in wintertime when both the atmo- reason that the explicit Sverdrup sea level patterns in the spheric forcing (the Sverdrup transports) and PK sea levels subtropical gyre could not be detected by the EOF calcu- have peaks in their annual cycles (Figure 3). Their winter- lation. Thus the adequate estimation and decomposition of time mean (December–February) anomalies relative to the sea level components (i.e., the baroclinic propagating these annual cycles were calculated over 10 years. The

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Figure 5. Monthly time series of the tide gauge sea level at PK (black line) and the time coefficients of EOF2 (gray line). correlation between the wintertime EOF2 and Sverdrup (minimum) southwestward flow in winter (summer to transports is 0.68, which is significant at 95% confidence, autumn), which is approximately dominated by the time- whereas those of the wintertime PK sea levels with the dependent Sverdrup relation [Isoguchi et al., 1997; Isoguchi wintertime Sverdrup transports and EOF2 are 0.61 and 0.38, and Kawamura, 2003]. respectively. These correlations involving the PK sea levels [24] Isoguchi and Kawamura [2003] pointed out, using do not exceed the 95% confidence interval for 10 years data, -measured current data at a 2000 m depth, that probably because of the above-mentioned large discrepan- anticyclonic eddies over the Kuril-Kamchatka Trench were cies in 1993 and 1997 (see Figure 5). Nevertheless they still roughly advected by the time-dependent wind-driven EKC/ show positive correlations, suggesting that the PK sea levels Oyashio currents on a seasonal timescale. Thus propagating can be a good indicator of the subarctic circulation, even in velocities of SLA perturbations over the Kuril-Kamchatka terms of the wintertime year-to-year variability. Trench might be one of indices of the EKC/Oyashio [22] The correspondences between time series of the sea variation. So we computed the along-trench propagating levels at PK, EOF2, and the Sverdrup transports suggest velocities of the SLA patterns and compared with the that PK is representative of spatially organized sea level Sverdrup transports and the PK sea levels. variations associated with the time-dependent Sverdrup [25] The SLA maps were interpolated onto a 25 km relation in the subarctic North Pacific. This can be inferred 25 km grid along the Japan Trench and the Kuril-Kamchatka from the spatial pattern of EOF2 (Figure 4a); the spatial Trench at every 7 days (see Figure 1). The defined trench coefficient reaches a maximum of 0.61 at the east coast of covers 200 km in width by 2250 km in length. Trench the Kamchatka Peninsula (52.5N, 159.5E) near PK direction is defined as a constant value in 3 respective (shown by a cross), which is almost the same correlation ranges: 6.3 (clockwise from the north) for the range south as that between EOF2 and the PK tide gauge sea levels. In of 40.66N (Range 1), 60 for the range between 40.66N the case when a correlation matrix is applied to the EOF and 45N (Range 2), and 51.8 for the range north of 45N calculation, the spatial coefficients are equivalent to corre- (Range 3). A spatial mean SLA was removed from each lations between time series of each EOF and original data at 7-day SLA map to emphasize small-scale perturbations, and respective grids, which indicates that about 36% of the sea the time series at each grid was then normalized with its level variation near PK (squared spatial coefficient) are standard deviation to have a uniform spatial weight. Next accounted for by EOF2. This suggests that PK may be the normalized SLAs were averaged over 200 km wide one of the point where the spun-up signals in winter are across the trench and the SLA profiles along the trench are exhibited most efficiently in the North Pacific. plotted with respect to time (Figure 6). The reference point (0) of x axis in Figure 6 is an intersection of Range 1 and 3.2. Altimeter-Derived Western Boundary Current Range 2 and positive (negative) range in x is equivalent to Variation and Its Relation With Tide Gauge Sea Levels Range 2 and Range 3 (Range 1). [23] In the previous section, we showed that the tide [26] A detailed behavior of the individual eddies over the gauge sea levels at PK are in agreement with the altimeter- Kuril-Kamchatka Trench, which is probably explained by derived seasonal sea level variation in the subarctic North the combination of some self-propelled mechanisms, such Pacific, which could be explained by the time-dependent as advection by mean flow, and some local effects such Sverdrup balance. It is inferred that the large-scale sea level as -eddy interaction, is very complicated as seen in pattern expressed by EOF2 (Figure 4a) represents the EKC/ Figure 6. Nevertheless, characteristic seasonality, that is, Oyashio variation as well, because a relatively strong sea positive anomalies tend to move southwestward (negative level gradient across the Kuril-Kamchatka Trench (see direction) in winter and move northeastward (positive Figure 1) can be seen in the spatial pattern of EOF2. We direction) from summer to fall, can be seen in many cases. now investigate the relation between the PK sea levels and An abrupt change from northeastward (positive) to south- the EKC/Oyashio variation derived from the altimeter sea westward (negative) in propagating direction in early winter levels. Using only 2–3 years’ data, it has been reported that is remarkable, especially for the strong anomalies in Ranges the Oyashio variation by direct current meters deployed at a 1–2 (shown by arrows in Figure 6). The southwestward middle layer exhibits seasonal variations with a maximum propagation during winter becomes indistinct after 1999. As

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Figure 6. Cross-trench mean SLAs along the Japan Trench and the Kuril-Kamchatka Trench as a function of time and along-trench distance. The SLAs were normalized with a standard deviation. A reference point of the x axis is an intersection of the Japan Trench and the Kuril-Kamchatka Trench. Red arrows show the prominent turnaround timings of positive SLAs in early winter. described later, it corresponds to the weakening of winter- distance (e.g., 1995–1996 and 1998–1999). For instance, time atmospheric forcing (i.e., the Sverdrup transport). It is the 2 positive anomalies that had propagated northeastward also notable that when more than two clear positive anoma- around 39N and 45N in the second half of 1995 turn lies are seen, they tend to move in phase regardless of their around and keep moving southwestward, involving one

8of17 C04013 ISOGUCHI AND KAWAMURA: WIND-DRIVEN EKC/OYASHIO VARIATIONS C04013 more anomaly around 48–46N, in the first half of 1996. Trench (Range 2 and 3) show almost the same variation, After that, they turn around in mid-1996 and propagate while the other one over the Japan Trench (Range 1) is northeastward again in the second half of 1996. This implies noisier with high-frequency and energetic variations on the that the movement of the SLA perturbations along the same basic seasonal variation as the former two. This is trench is primarily controlled, on a seasonal timescale, by probably caused by energetic eddies crossing the eastern gyre-scale phenomena such as the EKC/Oyashio currents side of the Japan Trench. Some of them are the Kuroshio rather than a local mechanism such as eddy-topography and/ warm core rings detached from the Kuroshio Extension near or eddy-eddy interactions, as pointed out by Isoguchi and the Japan Trench or the eastern region. Those east of the Kawamura [2003]. They calculated the moving velocities Japan Trench propagate westward into Range 1 and, as a of 7 anticyclonic eddies from their trajectories and demon- consequence, several eddies frequently exist and interact at strated that their temporal variations corresponded, on a each other around the Japan Trench. The mean geostrophic seasonal timescale, with that of the Sverdrup transport and current anomaly (GCA) at the Kuril-Kamchatka Trench is the Oyashio current measured by moored current meter. aligned with DVA in Figure 7b. The GCA is also low-pass [27] Drifting velocities of the along-trench SLA pattern filtered. The amplitudes of the two types of the current were estimated from the SLA-time plots (Figure 6) as variations are different, which is discussed later. Neverthe- follows. First, cross correlations between the successive less, a good agreement between their temporal variations along-trench SLA profiles every 7 days were calculated with a correlation of 0.60, which is significant to 95% and a distance at which the cross correlation has a maximum confidence, may support the idea that eddies over the Kuril- (a grid offset: dLmax) was determined. Drifting velocities Kamchatka Trench are advected, on a seasonal timescale, by were derived every 7 days by dividing the grid offset by the EKC/Oyashio flow. Meanwhile the long-term means of the time interval, dt (i.e., dLmax/dt). Although resolution the eddy drifting velocities in Ranges 1–2 are northeast- in estimating velocity is originally defined as 4.1 cm/s ward, which is opposite to the EKC/Oyashio mean flow. (25 km/7days), it is refined to 0.21 cm/s in this study, Yasuda et al. [2000] explained the mechanism of the long- by determining the grid offset in a subgrid scale with term northeastward movement of the eddies by a pseudo-b the fast Fourier transform (FFT) oversampling method effect, which results from the potential vorticity gradient (Appendix B). against the planetary b effect when there is vertical velocity [28] We calculated 4 types of the drifting velocities for the shear. The velocity shear is caused by a northeastward deep respective 3 ranges (Ranges 1–3; see Figure 1) and the flow that has been observed on the offshore side of the whole region. Their mean values (standard deviations) are Kuril-Kamchatka Trench [Owens and Warren, 2001]. À0.19 cm/s (0.89 cm/s), À0.42 cm/s (1.19 cm/s), 0.33 cm/s [30] The monthly PK tide gauges are overlaid with GCA (1.19 cm/s), and À0.16 cm/s (1.15 cm/s) for Ranges 1–3 (Figure 7c). As inferred from the previous result, they show and the whole region, respectively. Positive indicates south- similar variability on both seasonal and year-to-year time- westward. Because the standard deviations largely surpass scales: the correlations for the time series with and without the mean values and all the velocities basically show similar their annual cycles are 0.64 and 0.38, respectively, which temporal changes, only the time series for the whole region are significant to 95% confidence. This result indicates that will be discussed hereinafter. We also attempted to calculate the sea level at PK well represents the EKC/Oyashio the drifting velocities from the 14-day interval pairs, but the variation and can be a good monitoring point for it. estimated velocities were almost the same as those derived Generally, sea level measurements across a current axis from the 7-day interval pairs. The calculated drifting veloc- are required to monitor larger-scale geostrophic currents. In ity anomaly (DVA) is depicted in Figure 7a. A wintertime this case, as inferred from the spatial pattern of EOF2 (see maximum following an abrupt shift from late autumn can be Figure 4a), the sea levels across the EKC/Oyashio axis seen as a seasonal variation similar to the other time series oscillate like a seesaw near PK. So the PK tide gauge sea in the previous section. Indeed, the 7-day Sverdrup transport levels, which are in agreement with EOF2, correlate linearly (gray line), which was calculated from the NCEP/NCAR with a sea level gradient across the current axis. This seems daily 10-m wind products, corresponds with a correlation of to be the reason why the tide gauge data at only one station 0.65, significant at 95% confidence level with 60 degrees of can give a good expression of a current variation. freedom. Note that since the time-dependent Sverdrup balance is dominant at periods longer than a month 3.3. Annual Cycles [Willebrand et al., 1980], both DVA and the Sverdrup [31] The annual cycle of the Sverdrup transports averaged transport have previously been low-pass filtered with a over 40–50N at 150E is shown in Figure 3b. This annual 35-day (7-day 5) running mean (both the original time cycle has a maximum (a northward transport in the interior) series before the smoothing are noisy but show similar in winter and a minimum in fall, which is the same seasonal temporal variations with a correlation of 0.50, which is also feature as that of the PK sea levels. This means that the PK significant to 95% confidence). As described above, the sea levels are representative of wind-driven sea level signals dropoff of the wintertime maximum after 1999 is perceived in the subarctic region even from a climatological point of from both time series. view. Moreover, a little hump can be seen around June from [29] For additional information, along-trench geostrophic the annual cycle of the Sverdrup transports (Figure 3b), current anomalies were calculated from mean SLA differ- which has been also pointed out from the sea level pressure ences across the trench (dh) at the 3 respective ranges (i.e., data by Trenberth and Hurrell [1994], although it is not Àgdh/fdS, where g is the acceleration due to gravity, f is the necessarily significant. It’s interesting to note that a hump in Coliolis parameter, and dS is the trench width, 200 km). The June is also confirmed from both the annual cycles of the two types of the current estimates over the Kuril-Kamchatka 44-year PK sea levels (Figure 3b) and the 9-year DVA (not

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Figure 7. (a) Seven-day time series of along-trench drifting velocity anomalies (DVA) of the SLA pattern derived from the time versus along-trench SLAs (black line) and Sverdrup transport anomalies averaged for the 40N–45N region (gray line). (b) Along-trench anomalies (GCA) over the Kuril-Kamchatka Trench (black line) and DVA (gray line). (c) Time series of the monthly mean tide gauge sea level at PK (black line) and GCA (gray line). Thermosteric height signals were removed from the tide gauge data. DVA, the Sverdrup transport, and GCA were low-pass filtered with a 35-day running mean. shown), suggesting that the EKC/Oyashio fluctuates almost since the PK sea levels showed a good agreement with the concurrently with atmospheric spin-up and spin-down even other measurements in wintertime when the subarctic gyre on an intraseasonal timescale. This may be one character- is spun-up most, we now discuss the interannual variations, istic phenomenon indicating the barotropic nature of the focusing mainly on wintertime. The wintertime mean PK sea EKC/Oyashio. level and Sverdrup transport were calculated for 44 years (1957–2001) and their anomalies from the 44-year mean 3.4. Interannual to Decadal Variations are shown in Figures 8a, and 8b, respectively. In this [32] We now discuss the interannual to decadal variations case, winter spans from December to March, when both by using the PK sea levels over 40 years, on the basis of the the annual cycles have positive values (see Figure 3b). previously derived result that the PK sea levels can be one The 5-year running means are also depicted by black lines. of the indices of the subarctic gyre and EKC/Oyashio They show similar temporal variations with high-frequency variations. We first calculated the PK sea level and Sverdrup (2–3 years) variability as well as long-term changes, transport anomalies relative to their annual cycles (Figure 3) although the wintertime PK sea level is a little lower in from July 1957 to December 2001 (503 months). Their the late 1960s and higher in the late 1990s. The correlations interannual time series agree with a correlation of 0.35, for the original time series and those filtered with the 5-year which still exceeds the 95% confidence limit. In particular, running mean are 0.68 and 0.85, which are significant at

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Figure 8. Time series of the wintertime (from December to March) mean (a) tide gauge sea level at PK, (b) Sverdrup transport, and (c) North Pacific index for the period from 1958 to 2001 (44 years). Black lines depict the 5-year running mean. Y axis in Figure 8c is reversed.

95% confidence with 22 and 9 degrees of freedom, respec- Hanawa, 1995; Isoguchi et al., 1997]. The wintertime tively. On the other hand, significant correlations higher (December to March) NPI [Trenberth and Hurrell, 1994] than 0.4 were found for the spring and fall time series, but anomaly is indicated in Figure 8c as an index of the not for summer (a correlation of 0.09). The Sverdrup Aleutian low variability. The y axis is reversed for easy transport as well as the PK sea level has the highest (lowest) comparison with the Figures 8a and 8b. The wintertime NPI interannual variance in winter (summer) (see Figure 3b). shows a similar variation as the above two time series. Thus the high variability in winter, due to the Sverdrup Correlations (for the 5-year running means) with the win- response, might lead to the good correspondence by ob- tertime PK sea level and Sverdrup transport are À0.71 scuring the effect of sea level variations except for the (À0.79) and À0.90 (À0.94), which are significant to 95% Sverdrup balance. The result indicates that the PK sea level confidence. We interpret this result as follows. When the can be representative of spinning up by wintertime wind Aleutian low is relatively strong (low NPI), cyclonic wind fields even on an interannual timescale. fields over the subarctic North Pacific produce the anoma- [33] The behavior of the Aleutian low, its strength and lous northward Sverdrup transport in the interior (high meridional position, has an impact on the wintertime Sverdrup transports), resulting in intensification of south- Sverdrup transport in the subarctic North Pacific [Trenberth westward EKC/Oyashio and concurrent rising of the PK sea and Hurrell, 1994], and the effect of the Aleutian low (or level (high PK sea levels). wintertime westerlies) on the subarctic gyre (the Oyashio [34] The NPI (i.e., the Aleutian low) has been reported to intrusion) has been pointed out elsewhere [Sekine, 1988; fluctuate on a decadal timescale, followed by wintertime

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Figure 9. (a) Regression map of springtime mean SST (March to June) on the normalized wintertime tide gauge sea level at PK for the period from 1958 to 2000. Contour interval is 0.1C. Negative contours are dashed. The areas exceeding a 95% confidence limit are shaded. (b) Time series of the springtime mean SST off the Sanriku coast (38N–42N, 140E–144E). The 5-year running mean is also depicted with a black line. Y axis is reversed.

SST variations in the midlatitudes of the North Pacific; the the basis of changes between 1945–1975 and 1976–1998, regime shifts in the mid-1970s and in the late-1980s were and suggested that saltier shifts were confirmed to the confirmed for the period after the 1950s [Trenberth and Western Subarctic Gyre, reflecting a shallower halocline, Hurrell, 1994]. The decadal variations including the above consistent with the spinning up of the subarctic gyre. two regime shifts can be seen from the wintertime PK sea [35] In order to investigate the effect of EKC/Oyashio on level as well as the wintertime Sverdrup transport and NPI; SST fields, a regression map of the SSTs on the wintertime the two lower periods from the 1960s to the mid-1970s and PK sea level is calculated over the North Pacific north of from the late-1980s to the mid-1990s, and the two higher 20N. Here we adopted the wintertime tide gauge data periods from the mid-1970s to the late-1980s and after the because in winter the Oyashio is the strongest and can mid-1990s. The fact that the PK sea levels can be a good actively affect SST fields, especially off the Sanriku coast approximation of the variation of the subarctic gyre and via the Oyashio intrusions. Since the observed southernmost EKC/Oyashio suggests that they change on a decadal scale latitude of the Oyashio intrusions follows the accomplish- at almost the same time as atmospheric forcing. That is, at ment of the barotropic response by 2–3 months [Sekine, higher periods, the intensification of the Aleutian low (low 1999], 43-year springtime mean SST fields (March–June) NPI) results in the intensification of the subarctic gyre (high with a time lag of 3 months from the wintertime PK sea Sverdrup transports and PK sea levels) and vice versa. level were used for a regression. The regression map is Some previous studies have indeed pointed out the regime shown in Figure 9, where shadings indicate the area shifts of the subarctic North Pacific using various data exceeding the 95% confidence limit. The highly negative [Hanawa, 1995; Minobe, 1997; Joyce and Dunworth-Baker, SST region over the midlatitudes of the central Pacific is 2003]. Hanawa [1995] examined the annual mean south- considered as traces of the wintertime SST fields associated ernmost latitude of the Oyashio intrusions from 1964 to with the Pacific Decadal Oscillation [e.g., Mantua et al., 1984, and pointed out that its southward shift from the mid- 1997], because the wintertime PK sea level correlated well 1970s was accompanied by coastal SST lowering that was with the NPI having a decadal variation. On the other hand, speculated to be connected with the regime shift in the mid- highly negative areas < À0.5C can be seen east of the 1970s. Minobe [1997] showed that spring-to-summer Sanriku coast where the Oyashio intrudes from winter to coastal SSTs off the Sanriku coast, which can be a good spring. This area, whose regression coefficients exceed the index of the southward Oyashio intrusion, had interdecadal 95% confidence limit, is apart from the former central variability (50–70 year climatic oscillation) associated with negative area. The SST cooling in the central area is the Aleutian low. Joyce and Dunworth-Baker [2003] inves- attributed to atmospheric forcing (the effects of net surface tigated hydrographic changes in the northwest Pacific, on heat flux, , and entrainment, etc.). We rule

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Figure 10. Time series of residuals of normalized GCA from normalized DVA (thin black line) and the normalized Sverdrup transports (thin gray line). Thick lines represent low-pass-filtered data with a 6-month running mean. out the heat advection by eastward surface currents around decadal-scale atmospheric variations affects oceanic struc- 40N, since their typical velocity < 0.3 m/s, adopted from ture in the North Pacific. On the other hand, as discussed in the mean drifter velocity map by Niiler et al. [2003], is not the next section, the contribution of a baroclinic response enough for its effect to reach to the central and eastern to the low-frequency EKC/Oyashio variation is still impor- Pacific for three months. The cooling east of the Sanriku tant. The PK sea levels might give good information on the coast is, on the other hand, probably dominated by the baroclinic contribution by calculating the residuals from the advection of the Oyashio mean current. The time series of barotropic component, although more distinct treatment for the spring mean SST anomalies off the Sanriku coast the estimation of low-frequency steric height signals will be (38N–42N, 140E–144E) is depicted in Figure 9b, required. These subjects are beyond the scope of the present where the y axis is reversed for a comparison with study but should be addressed in the future. Figure 8. Since the Oyashio southward intrusion is some- times blocked by the Kuroshio warm core rings [Sekine, 4. Discussion 1988] and the Kuroshio Extension itself also can affect the SST fields off the Sanriku coast, the SST time series is not [37] In the previous section, agreement between the DVA always consistent with the wintertime PK sea level in terms and GCA was demonstrated (Figure 7b), and the amplitude of high-frequency variability. Nevertheless, their decadal- of GCA was found to be larger by a factor of 2.5 than that of scale variations are approximately consistent, implying that DVA. This difference might be attributed to a vertical EKC/Oyashio driven by wintertime atmospheric forcing has current shear; GCA definitely gives surface current varia- an impact on oceanic condition east of Japan on a decadal tions, while DVA probably represents current variations at a timescale. Our result further reconfirms the previous works middle layer due to the deep vertical structure of eddies. [Sekine, 1988; Hanawa, 1995] by newly adopted parame- Isoguchi and Kawamura [2003] traced respective eddy ters directly connected with the EKC/Oyashio variation. propagation over the Kuril-Kamchatka Trench by using [36] As mentioned above, description of the Pacific altimeter-derived SLA maps and compared the propagating Decadal Oscillation or regime shifts and their impact on velocities with in situ current velocities measured by moor- temperature fields off the Sanriku coasts has been provided ings deployed on the inshore slope of the Kuril-Kamchatka by many researchers [e.g., Hanawa, 1995; Minobe, 1997]. Trench off Hokkaido. They demonstrated that the eddy However, there have been few long-term dynamic param- velocities agreed with the current velocities at a middle eters related to velocity (transport) variations of EKC/ layer (2006 m depth) with a correlation of 0.5, which is Oyashio, unlike the Kuroshio, because of a lack of hydro- significant to 95% confidence, and with a root-mean-square graphic observations. In this study, we defined the new (RMS) ratio of 0.8. Isoguchi et al. [1997] also pointed out index (the PK sea level) related to the EKC/Oyashio (or the by using other mooring current data off Hokkaido that Western Subarctic Gyre) variations by combining the current variations at a middle layer (1250 m depth) rather altimeter-derived SLAs with the PK sea levels, and recon- than those at an upper layer (350m depth) correlate well firmed that the SST variation off Sanriku is due to heat with the Sverdrup transport variations. Thus this suggests advection by using that index. The PK sea level that agreed that DVA is representative of middle-layer current variations with the Sverdrup transports demonstrated that barotropic accounted for by the Sverdrup balance. In fact, the Sverdrup components contribute largely to the wintertime EKC/Oya- transports shown in Figure 7a agreed well with DVA rather shio variations, even on decadal timescales. This also means than GCA. Assuming this, the residuals of optimal fitting of that EKC/Oyashio is intensified responding to atmospheric the barotropic components (DVA or the Sverdrup transport) forcing with a time lag of no more than a few months, to the surface current variations (GCA) may show some which is different from the case of the Kuroshio, which is indicators related to a baroclinic component. The residuals reported to have lags of 4–6 years [e.g., Deser et al., 1999; of the normalized GCA from DVA and the Sverdrup Qiu, 2002a]. It is of interest to know how the difference in transportareshownwiththinblackandgraylinesin the response of the two western boundary current systems to Figure 10. Also shown with the thick lines are low-pass-

13 of 17 C04013 ISOGUCHI AND KAWAMURA: WIND-DRIVEN EKC/OYASHIO VARIATIONS C04013 filtered 6-month running means. Interestingly, a long-term currents seems to be critical for the accurate estimation of variation with negative in 1993–1996 and positive (strong the EKC/Oyashio transport. Further discussions on the southwestward currents) in 1997–2000 primarily agrees volume transport of EKC/Oyashio are beyond the scope with the previous estimations of the EKC/Oyashio varia- of this study and should be addressed in the future tions accounted for by baroclinic response [Qiu, 2002b; by combining numerical model experiments and in situ Ito et al., 2004]. Qiu [2002b] compared current variations observations. derived from altimeter sea level differences with those estimated from wind data on the basis of the Sverdrup 5. Summary and Conclusions balance at the EKC/Oyashio region. He pointed out that both velocities agreed well in terms of an annual cycle and [39] Annual to interannual variations of the subarctic year-to-year changes at wintertime peaks, while there still gyre in the North Pacific and EKC/Oyashio were investi- remained lower-frequency differences where the altimeter gated by the data analyses combining the altimeter-derived EKC/Oyashio velocities are smaller than the Svedrup and tide gauge sea levels. First, we examined the relation velocities in 1992–1995, whereas they are stronger in between the large-scale sea level variation associated with 1996–1998. He also demonstrated that the low-frequency a barotropic response and the local tide gauge sea level at difference was determined by baroclinic Rossby waves. Ito PK using 9 years data. The second EOF of the altimeter et al. [2004] estimated Oyashio transport variations on the SLA maps, after removing the estimated thermosteric basis of a combination of altimeter-derived SLAs and signal (EOF2), showed that the seasonal variation corre- hydrographic observations repeatedly conducted along sponds to the temporal variation of the Sverdrup transport the altimeter ground track off Hokkaido. The residuals at 40–50N. The time series of EOF2 was in agreement of the Oyashio southwestward transports from the with that of the monthly tide gauge sea level at PK on a Sverdrup transports were negative in 1994–1996 and year-to-year timescale as well as on a seasonal timescale. positive in 1997–2000. Our result might be one evidence Therefore the PK sea level was considered to be represen- that corroborates their results, although the comparison tative of the gyre-scale sea level variation associated with here includes many assumptions and is not based on the time-dependent Sverdrup balance in the subarctic North quantitative evidence. It also implies, as pointed out by Pacific. Qiu [2002b], that the EKC/Oyashio variations are primar- [40] The correspondence between the EKC/Oyashio var- ily explained by the Sverdrup balance but a baroclinic iation and the PK sea level was also examined. As indices of response still contributes to them, especially on an inter- the EKC/Oyashio variation, DVA and GCA were calculated annual timescale. by using the 7-day SLA maps over the Japan/Kuril- [38] Here we briefly discuss the EKC/Oyashio volume Kamchatka Trenches. DVA was applied on the basis of the transports quantitatively on the basis of the previous studies. fact that the short-term propagation of anticyclonic eddies By repeated hydrographic and mooring observations con- over the Japan/Kuril-Kamchatka Trenches is roughly con- ducted southeast off Hokkaido, the Oyashio mass transport trolled by the EKC/Oyashio flow variation, which is was estimated to be maximum in winter and minimum in accounted for primarily by the time-dependent Sverdrup fall, ranging from 3 to 19 Sv (106m3/s) (T. Kono et al., balance [Isoguchi and Kawamura, 2003]. DVA agreed with Seasonal variation of the Oyashio southeast off Hokkaido, GCA and the Sverdrup transport variations. These three times Japan, submitted to Geophysical Research Letters, 2005, series also showed similar seasonal to year-to-year variability hereinafter referred to as Kono et al., submitted manuscript, to the PK sea level, which implied that the PK sea level can 2005). They also pointed out estimated transports had a also be an index of the EKC/Oyashio variation. similar quantity to the Sverdrup transport calculated be- [41] It is noteworthy that the SLA disturbances over the tween the Hokkaido coast and the Emperor Sea Mounts at Japan Trench (Range 1) also undergo a rapid turnaround in 170E. In this study, the monthly Sverdrup transport used early winter (see Figure 6), which is likely to be dominated for the comparisons was calculated from the eastern end of primarily by the Sverdrup relation. The Oyashio variation the Pacific and ranged from À27.7 to 47.5 Sv. However, in off the Sanriku coast (over the Japan Trench) has been the case of integration from 170E, it ranges from À5.3 to discussed by using an indirect index such as the 5C 15.6 Sv which still has almost the same temporal variability isotherm at 100 m depth [e.g., Sekine, 1988]. Nevertheless, as that over the whole Pacific. This transport is indeed there is not enough knowledge about the current structure closer to the Kono et al. submitted manuscript (2005) and its temporal variability. The result in Figure 6 suggests Oyashio transport, which may support their suggestion that that the time-dependent Sverdrup relation seems to extend the Oyashio could be balanced with the Sverdrup transport to the branch of the Oyashio off the Sanriku coast. In of the Western Subarctic Gyre. On the other hand, Uehara addition, the fact that the Oyashio variability is correlated et al. [2004] estimated that the absolute Oyashio transport in well with the upstream PK sea levels suggests that the PK January 2001 is at least 31 Sv by combining hydrographic sea level will be useful data for the operational monitoring observations with direct current measurements deployed of the Oyashio and the oceanic condition east of Japan. two dimensionally along a hydrographic section. Their Near-real-time and high-frequency data and its global net- estimation is comparable with the monthly Sverdrup trans- work, which is being developed by the Global Sea Level port integrated over the Pacific even though it is just one Observing System (GLOSS) [e.g., Mitchum et al., 2001], case. In this case, with the correction by the direct current would be desirable for operational monitoring. measurements, the absolute transport of 0–1000 db is [42] Moreover, we discussed the interannual variation estimated to be greater than the relative geostrophic trans- of EKC/Oyashio by using the 44-year tide gauge records port by a factor of 1.8. Thus the evaluation of barotropic on the basis of the 10-year relation between the PK sea

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Figure A1. (a) Spatial pattern and (b) time coefficients of the first EOF of SLA maps with thermosteric signals removed. Contour interval in Figure A1a is 0.2. level and the altimeter-derived subarctic gyre and EKC/ altimeter-derived sea level data for 9 years. This supports Oyashio signals. The wintertime mean PK sea level the idea that the combination of tide gauge data with corresponded with the wintertime Sverdrup transport and altimeter data compensates for the sparse spatial resolution NPI and exhibited not only year-to-year variability but of the tide gauge data and therefore aids the discussion on also decadal variation including the regime shifts in the long-term variability. mid-1970s and the late-1980s. The springtime SST fields east of the Sanriku coast where the Oyashio sometimes Appendix A: Leading EOFs intrudes had a similar interannual variation to the winter- time PK sea level, as well as the wintertime Sverdrup [44] Differences in the EOF calculation between Isoguchi transport and NPI. It was found from those results that and Kawamura [2002] (hereinafter referred to as IK02) and EKC/Oyashio fluctuated on a decadal timescale, respond- this study are (1) the time period of the calculation and ing to the decadal-scale atmospheric variability, and had (2) the method of estimating the steric height components. an impact on the SST fields east of the Sanriku coast. These factors probably bring about the fact that the inter- This suggests that the previous studies by Sekine [1988] annual patterns appear in the leading EOF and the contri- and Hanawa [1995] have been reconfirmed for an ex- bution rate of the annual variation mode decreases. tended time period by adopting the new parameters such Figure A1 shows the spatial pattern and time coefficient as the PK tide gauge data and the altimeter-derived EKC/ of the first EOF (hereinafter EOF1). EOF1-like patterns Oyashio signals. (Figure A1a) have not been detected by IK02. The time [43] The results derived in this study are not basically coefficient of EOF1 (Figure A1b) exhibits the interannual based on quantitative evidence but rather on just temporal variation whose phase is drastically inverted in 1998/1999, correspondence between the several time series (correla- while the variability before 1998 is weak. This is probably tions). Nevertheless, the following significant findings pro- the reason that the EOF1-like pattern could not be detected vide evidence and corroborate the main results: (1) the in the IK02 EOFs, which were calculated for the period several types of measurements such as the PK sea levels, from 1992 to 1998. In fact, Qiu [2002b], who has performed the EOFs of the sea level fields, GCA, and DVA, which EOF calculations for the period from October 1992 to July were derived by different methods, showed good correspon- 2000, has detected the first EOF similar to our EOF1. The dence between them, and (2) the relationship between the contribution rate of 14.6% is almost the same as that of PK sea levels and the subarctic gyre was explained by the EOF1 (14.9%). Thus extending the time period of SLA spatial pattern of EOF2, whose highest spatial coefficients leads to detection of rapid and energetic changes occurring were found near PK. In the current study, we could discuss during the extended period as in the leading modes, and it is gyre variability on interannual to decadal timescales by accompanied by relative decreasing of the contribution rate using long-term tide gauge sea levels on the basis of the of the annual mode. This might be one of the factors in the results derived by combining them with the spatially dense difference.

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[45] The contribution rate of annual mode, that is, the (N2 = 16). Let H(fi), i =0,1,ÁÁÁ, N2 À 1 be a function in second EOF (EOF2; see Figure 4) is 10.6%, significantly frequency domain, and substitute the original data into both different from about 20% in the previous studies. Even if edges of H(fi)as the sea level variations explained by EOF1 (14.9%) is completely eliminated, EOF2 accounts for about 12% only. HðÞ¼0 GðÞ0 ; HðÞ¼1 GðÞ1 ; HðÞ¼2 GðÞ2 ; HðÞ¼3 GðÞ3 ; This difference is probably caused by the incorrect estimate HðÞ¼12 GðÞ4 ; HðÞ¼13 HðÞ5 ; HðÞ¼14 GðÞ6 ; HðÞ¼15 GðÞ7 ; of the steric signals in the previous study, where the steric component is estimated as an area-averaged SLA. As and then substitute zero into H(4), H(5), ÁÁÁ, H(11) (zero pointed out by Qiu [2002b], since amplitudes of the steric padding). Finally, calculating the inverted FFT of H(f ), we signal have in a spatial distribution especially in the i obtain the cross correlation (h(f )) with 16 elements meridional direction (see Figure 2), artificial meridional i (N = 16). In this case, grid resolution is improved to 0.5, oscillations remain after subtracting the area-average SLAs. 2 and the scale factor becomes two (N /N = 16/8). In the Some parts of the artificial oscillations seemed to be 2 1 present study, we applied the scale factor of 20 so that the absorbed into the wind-induced Sverdrup sea level signals resolution for estimating velocity was artificially improved since it has a similar annual cycle, which has probably by twenty times (from 4.1 cm/s to 0.21 cm/s). distorted the spatial pattern of the first EOF in the previous study. The effect is particularly significant in the subtrop- [48] Acknowledgments. The altimeter products were produced by ical region. EOF2 has large amplitudes in the subarctic SSALTO/DUACS as part of the Environment and Climate European Union region, while it has little variance in the subtropical region. (EU) Enhanced Ocean Data Assimilation and Climate Prediction (ENACT) The improvement in the estimation of the thermosteric project (EVK2-CT2001-00117) and distributed by Archiving, Validation and Interpretation of Satellites Oceanographic data (AVISO), with support signal in the subtropical region mainly contributes to the from Centre National d’Etudes Spatiales (CNES). The NCEP/NCAR decreasing of the contribution rates from 20% to 10%. reanalysis was provided by the National Oceanic and Atmospheric Admin- Thus EOF2, as discussed in the main text, exhibits sea istration (NOAA), Cooperative Institute for Research in Environmental level patterns related to the Sverdrup balance mainly in the Sciences (CIRES) Climate Diagnostics Center, Boulder, Colorado. The authors thank the editor and the anonymous reviewers for constructive subarctic North Pacific. In fact, EOF2 accounts for > 16% comments and English editing, which were helpful in improving this paper. (squared correlation coefficients) of the variance of SLA This study is supported by Special Coordination Fund for Promoting (raw SLAs minus thermosteric height) over most of the Science and Technology ‘‘New Generation SST’’ of Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan and Category 7 of subarctic region (shaded area in the Figure 4) and up to the MEXT PR2002 Project for Sustainable Coexistence of Human, Nature 36% in the northwestern North Pacific. With the interan- and the Earth. nual variations taken account of, the variance explained by EOF2 might be valid compared with the previous dynam- References ical estimates by Vivier et al. [1999]. They have estimated Deser, C., M. A. Alexander, and M. S. 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Miyagi 980-8578, Japan. ([email protected])

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