Sensitivity of the Interannual Kuroshio Transport Variation South of Japan to Wind Dataset in OGCM Calculation

Transcription

1 Journal of Oceanography, Vol. 60, pp. 341 to 350, 2004 Sensitivity of the Interannual Kuroshio Transport Variation South of Japan to Wind Dataset in OGCM Calculation HIROSHI YOSHINARI 1 *, MOTOYOSHI IKEDA 2, KIYOSHI TANAKA 1 and YUKIO MASUMOTO 3 1 Core Research for Evolutional Science and Technology, Japan Science and Technology Corporation, Kawaguchi , Japan 2 Graduate School of Environmental Earth Science, Hokkaido University, Sapporo , Japan 3 Department of Earth and Planetary Science, Graduate School of Science, University of Tokyo, Tokyo , Japan (Received 30 April 2003; in revised form 16 December 2003; accepted 17 December 2003) Numerical experiments were carried out using OGCM (Ocean General Circulation Model), MOM2.2 (Modular Ocean Model Ver. 2.2), over realistic topography data, ETOPO5 (Earth Topography - 5 Minute), to investigate the interannual variability of the Kuroshio transport in south of Japan; 1) the PN line located off the East China Sea, and 2) the ASUKA (Affiliated Surveys of the Kuroshio off Cape Ashizuri) line located off Cape Ashizuri. We adopted two wind datasets as driving forces of the OGCM: 1) the NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis monthly mean wind stress data, and 2) the ECMWF (European Centre for Medium-range Weather Forecasts) daily wind data. In the ECMWF experiments we replaced the NCEP/NCAR data only in because of the availability of the data. The OGCMs and observation basically agree on the temporal variation patterns of the transports until 1986 on the PN line with correlation coefficients of about 0.6. During the 1990s, when data were collected on the ASUKA line, the NCEP/NCAR experiments give lower correlation coefficients (less than 0.3), on both PN and ASUKA lines, while the ECMWF experiments have a higher value on the ASUKA line (0.5). One of the reasons for the disagreement between the observations and OGCMs during the 1990s might arise from the NCEP/NCAR data. An additional analysis of a wind-driven circulation was performed to examine the sensitivity of integrated Sverdrup transport along the western boundary to the propagation speed of a baroclinic Rossby wave, which is varied by stratification. A variation of the stratification, which might be induced by variability of air-sea heat and freshwater fluxes, cannot be a main cause of the disagreement. Keywords: Interannual Kuroshio transport variation, MOM2.2, ETOPO5, NCEP/NCAR wind stress data, ECMWF wind data, comparing with observation data, PN and ASUKA lines. 1. Introduction The western boundary current in the North Pacific Subtropical Gyre, called the Kuroshio, transports enormous amounts of mass, heat and geochemical materials * Corresponding author. hy@hawaii.edu Present address: International Pacific Research Center, School of Ocean and Earth Science and Technology, University of Hawaii, Honolulu, HI 96822, U.S.A. Present address: Center for Environmental Research, Ocean Research Institute, University of Tokyo, Tokyo , Japan. Copyright The Oceanographic Society of Japan. from the low to mid-latitude regions, playing an important role in the Earth s climate system (e.g., Vonder Haar and Oort, 1973; Macdonald and Wunsch, 1996). The Kuroshio transport is also closely related to bimodality of the Kuroshio path south of Japan (e.g., Nitani, 1972; White and McCreary, 1976; Kawabe, 1980; Masuda, 1982; Yoon and Yasuda, 1987; Akitomo et al., 1991; Kawabe, 1995). Therefore, it is very important not only to understand the Kuroshio transport variability, but also its relation to the Kuroshio path. Previous analyses of the observation of data have clarified that the Kuroshio transport varies on a variety of time scales (e.g., Saiki, 1982; Qiu and Joyce, 1992; 341

2 Ichikawa and Beardsley, 1993; Kawabe, 1995; Hinata, 1996; Deser et al., 1999; Imawaki et al., 2001). Since the Kuroshio flows in the western boundary part of the winddriven circulation (subtropical gyre), many studies have investigated the relationship between the Kuroshio transport and wind stress field over the North Pacific. Recently, Isobe and Imawaki (2002) used a two-layer numerical model, which had the bottom topographic features of the Izu-Ogasawara Ridge and was driven by the wind stress, to explain the observed annual variation of the Kuroshio transport south of Japan. It was suggested that a large fraction of the wind-driven barotropic Rossby waves could not cross the ridge, which was why the annual variation of the observed Kuroshio transport was different from that expected from Sverdrup transport. Numerical experiments with the multi-level Ocean General Circulation Model (hereafter OGCM) named Modular Ocean Model Version 2.2 (hereafter MOM2.2), by Tanaka and Ikeda (2004, hereafter, TI04) demonstrated that interannual variability of the Kuroshio transport could be determined by an interannual wind stress forcing far east from Japan. Once the interannual wind stress forcing is imposed east of major bottom topographic features, such as the Izu-Ogasawara Ridge and the Shatsky Rise in the North Pacific, most wind-driven first-mode baroclinic Rossby waves are transmitted across the ridges to the south of Japan, having net mass transport. Most barotropic Rossby waves cannot cross the ridges due to the topographic effects, as shown by Isobe and Imawaki (2002). The second baroclinic mode excited directly by the wind stress forcing does not arrive in the south of Japan because of turbulent dissipation. Although the second-mode baroclinic Rossby waves converted from the first-mode on the ridges can arrive at the south of Japan, their contributions are minor, which suggests that the interannual variability of the Kuroshio transport south of Japan is determined mainly through the first-mode baroclinic Rossby wave. Akitomo et al. (1996) and Kawabe (2000, 2001) have actually revealed this possibility in the real ocean. Considering a major role of the first-mode baroclinic Rossby wave on the interannual variability of the Kuroshio transport, Kawabe (1995) found a high correlations between the tide levels of several islands in the East China Sea and the observed transport across the PN line (this line is used in the present study: see the next section for details). He derived multiple regression equations which predicted the Kuroshio transport, indicating a comparatively high correlation coefficient (greater than 0.6). This regression analysis, however, was valid only for the transport across the PN line, while another regression has to be constructed for the Kuroshio transport south of Honshu. Tanaka et al. (2004, hereafter, TIM04) simulated the interannual variability of the Kuroshio transport in MOM2.2 by adopting the real bottom topography and the NCEP/NCAR reanalysis wind stress data (HINDCAST experiment). They examined the predictability of the transport variation by using observed wind data followed by wind stress fixed at the value at the starting year of the prediction for three years (FORECAST experiment). They showed that it was possible to predict the interannual variability of the Kuroshio transport at a statistically significant level. The success of the FORECAST experiment by TIM04 requires the condition that the interannual variability of the Kuroshio transport generated by the HINDCAST experiment actually reproduces the observed transport valiability. If the experiment cannot reproduce the observed transport, we should search for the reason Fig. 1. Model domain and bottom topography used in this study. Contour interval is 1000 m. 342 H. Yoshinari et al.

3 by examining the reasons for the disagreement one by one. In this study we compare the variability of the transport calculated by the HINDCAST experiment with observed values to investigate how the effect of wind explains the Kuroshio transport variation. The next section, describes the outline of MOM2.2, which TIM04 also used, and the observational Kuroshio transport data used in this study. In Sections 3 and 4 we show the results of the observation-hindcast comparison in the cases using NCEP/NCAR reanalysis wind stress data and the ECMWF reanalysis wind data, respectively. Finally, we summarize all consequences and discuss the reasons for disagreement in the comparison. 2. Model and Data The OGCM used in this study is identical to that in TIM04 based on the GFDL Modular Ocean Model Version 2.2β (MOM2.2) (Pacanowski, 1996). The model domain extends from 120 E to 80 W and 5 S to 60 N, and the maximum depth is 5200 m (see Fig. 1). The longitudinal grid spacing is 0.25 around Japan (west of E), increasing smoothly to 1.5 towards the eastern boundary at 125 W. The meridional one is also 0.25 around Japan (between 14 N and 39 N), increasing smoothly to 0.75 southward to 5 S and northward to 0.8 by 60 N. The model has 24 levels in the vertical, with a spacing of 25 m at the surface, smoothly increasing to 450 m by 5200 m depth (see Table 1). The bottom topography is taken from the ETOPO5 (Earth Topography - 5 Minute) data (National Geophysical Data Center). The governing equations are primitive equations in a spherical coordinate system under the Boussinesq, hydrostatic and rigid-lid approximations. The Smagorinsky scheme is adopted to calculate the horizontal viscosity and diffusivity coefficients with the adjustable constant chosen to be 0.45 in the present model (Smagorinsky, 1963; Rosati and Miyakoda, 1988; Pacanowski, 1996). For vertical mixing, the Laplacian dissipation is used with constant coefficients of m 2 s 1 for momentum and of m 2 s 1 for tracers. These values are regarded as appropriate, based on past studies. The wind stress, a single forcing for driving interannual variability of the oceanic circulation, is taken from the NCEP/NCAR reanalysis monthly mean data (Kalnay et al., 1996) during the period from 1960 to The surface fluxes of heat and salt are given by the Newtonian damping of the potential temperature and salinity to the monthly mean climatological data of Levitus (1982) with a restoring time scale of 30 days. This time scale is chosen so that SST and SSS may fit tightly with the monthly mean climatology, but vary smoothly. In contrast to the surface restoration, we have to avoid an influence on an interannual variability, but also change the propagation speeds of Rossby waves from the basic climatological values during the time integration. Therefore, we gently restore the potential temperature and salinity fields in the ocean interior to the Levitus (1982) values. The restoring timescale is 15 years for layers shallower than 2000 m, decreasing smoothly to 3 years by 3000 m depth, below which it is fixed to 3 years. Thus, the basic stratification structure is maintained around the pycnocline, which strongly contributes to the behavior of the baroclinic Rossby waves. On the other hand, the 3- year restoring time scale in the deeper layer is not considered to affect the Rossby waves, because no density variability exists. Sponge layers, where the potential temperature and salinity are restored with a timescale of 5 days, are also applied to grids along the northern and southern artificial boundaries, and in marginal seas, such as the Okhotsk, Bering and Japan seas. The experiments are carried out as follows: first, the model is integrated for ten years with annual mean climatological forcing, and for the following ten years with monthly mean climatological forcing in order to spin up the model. After the spin-up for twenty years, we run a HINDCAST experiment covering the period from 1960 to 2001, using the NCEP/NCAR and/or ECMWF wind stress data. During this period we examine the Kuroshio transport. Table 1. Depth and thickness of model levels used in this study. Level Depth (m) Thickness (m) Sensitivity of the Interannual Kuroshio Transport Variation South of Japan to Wind Dataset in OGCM Calculation 343

4 (cm) Fig. 2. Locations of PN and ASUKA lines. We use two kinds of observed Kuroshio transport data for comparison with those from the HINDCAST experiment. The first is the transport which crosses the PN line located in the East China Sea (see Fig. 2), belonging to Nagasaki Marine Observatory. The transport data are the geostrophics referred to 700 dbar or near the bottom, and exist in all four seasons in every year from 1972 to For a precise description of this data set we refer the reader to Saiki (1982) and Hinata (1996), for example. The other kind is the transport which crosses the ASUKA line, located off Cape Ashizuri (see Fig. 2), belonging to ASUKA Group. This transport is the estimated value from the TOPEX/POSEIDON sea surface altimeter and hydrographic data for the upper 1000 m calculated by Imawaki et al. (2001), called absolute geostrophic transport, and exists for approximately a 10-day interval from October, 1992 to December, More detailed descriptions are given elsewhere (Uchida and Imawaki, 2004). Note that, due to the restriction of horizontal and vertical grids, the positions of both lines in the model do not completely agree with the actual ones. However, it is considered that these disagreements do not have a strong effect on the transport calculation. In this study, we focus on the reproduction of an interannual component of the Kuroshio transport variability, considering neither a seasonal component nor higher frequency ones due to meso-scale eddies and so on. Thus, the following comparison between the HINDCAST experiment and the observational transports is made after a one-year running mean has been applied to the observed values and the model output. 3. General Ocean Circulation Field In the companion work, TI04 examined the Kuroshio transport variability as a consequence of westward propagation of a wind-driven circulation in the more idealized situation: i.e., in addition to the idealized bottom topography and wind variation pattern, no mean circulation was included. They focused on a linear response of a winddriven Rossby wave without nonlinear effects of the subtropical and subpolar gyres. However, our objective is to Fig. 3. Temporal-mean sea surface height averaged between January, 1960 and December, 2001 in the model. NCEP/ NCAR reanalysis monthly wind stress data was used to drive the model. Contour interval is 10 cm. Shaded area denotes the less than average height. examine the capability of the model and the appropriateness of the model setting while reproducing the Kuroshio transport. Therefore, we are concerned with the mean wind-driven gyres in the present model. Figure 3 shows the temporal-mean sea surface height averaged between January, 1960 and December, The subpolar and subtropical gyres are reproduced in the northern and southern sides of the 40 N line, respectively. The western boundary current, the Kuroshio, is reproduced near the western boundary from Taiwan to the east coast of Japan. The mean transports are about 20 to 25 Sv (1 Sv = 10 6 m 3 /s) on the PN line, and 40 to 46 Sv on the ASUKA line, which is in good agreement with the observations (Imawaki et al., 2001). The Kuroshio maintains the larger stationary meander south of Japan. This meander has appeared only a third of the time in the past, while the model always shows it. The existence of the stationary meander might affect the Kuroshio transport on the ASUKA line, while it is hard to imagine its influence on the PN line upstream of the stationary meander. The Kuroshio does not separate from the southeastern tip of Japan islands, but instead flows northward along the northeastern coast of Japan and reaches the south of Hokkaido. This phenomenon is obviously different from the real Kuroshio path. However, the main purpose of this study is to reproduce the interannual variability of the Kuroshio transport south of Japan, and hence, the problem of the Kuroshio separation is not our concern here. All consequences described above guarantee that the present OGCM is reasonable for analyzing the Kuroshio transports, with some doubt concerning the ASUKA line transport, depending on the stationary meander. 344 H. Yoshinari et al.

5 4. Temporal Variations of the Transport Derived from NCEP/NCAR Data Since the NCEP/NCAR wind stress data are available over a longer time series, we first tried to reproduce the Kuroshio transports from them. Figure 4(a) shows the time series of the two types of Kuroshio transport across the PN line; one is calculated by the HINDCAST experiment relative to 700 m, while the other is the geostrophic transports relative to 700 dbar or near-bottom calculated from the hydrographic data (e.g., Saiki, 1982; Hinata, 1996). Comparing the temporal variation patterns between the two transports, we see a relatively good agreement of peak positions between them until 1984, especially in The correlation coefficient between them in this comparatively correspondent term (June, 1972 December, 1985), is about 0.6, which is statistically significant at the 95% confidence interval. Here, the correlation was referred to anomalies from each mean transport, and numbers of degrees of freedom (DOF) were calculated from (a) the total data length divided by a time lag at which variability had no auto-correlation. It should be noted that the zero correlation time was close to a quarter of (b) a dominant variation period. In this case, we adopted a) as 14 years and b) as 4 years, giving a DOF of 14. By contrast, after 1986, the temporal variation patterns become incoherent, particularly in the 1990s. The correlation coefficient is less than 0.3 in However, when we compare these temporal patterns at about 10-year scale: in , there are many similar portions. We now look at the other section closer to Japan, the ASUKA line. Figure 4(b) shows the time series of the modeled and observed Kuroshio transports across the ASUKA line. The observed transport is referred to as the upper 1000 m transport calculated by absolute geostrophic velocity (Imawaki et al., 2001), which includes the information of the TOPEX/POSEIDON altimeter data and in-situ observations. Although the observed data are available only from 1993, the temporal variation pattern is quite different from the observed one, with a correlation coefficient of about 0.2. From the model-data comparison described above, we found that about 10-year scale variability of the Kuroshio transport was reproduced by the HINDCAST experiment prior to the 1990s, as shown on the PN line, but we could not reproduce the transport variability during the 1990s. Although there are only a few ASUKA line data after 1993, we must search for reasons for the disagreement and then improve the transport variability in the HINDCAST experiments. Several reasons are considered, as follows: 1) Since the most influential driving force of the HINDCAST experiments is the wind stress dataset, the first candidate is the reliability of the NCEP/NCAR (a) (b) :PN Line :ASUKA Line Fig. 4. Time series of the Kuroshio transport across (a) PN line and (b) ASUKA line. Solid line denotes the transport calculated by the HINDCAST experiment (OGCM) using the NCEP/NCAR monthly mean wind stress data: the transport relative to 700 m in (a), the absolute transport upper 1000 m in (b). Dotted line in (a) denotes the geostrophic transports relative to 700 dbar or near bottom calculated from the hydrographic data; dotted line in (b) denotes the observed upper 1000 m transport derived from absolute geostrophic velocity (Imawaki et al., 2001). Unit is Sv (1 Sv = 10 6 m 3 /s). One-year running mean is applied to each transport. reanalysis monthly mean wind stress data. In other words, it is doubtful whether NCEP/NCAR data represent a real wind stress field. 2) A major mechanism for temporal variability of the Kuroshio transport is the first-mode baroclinic Rossby wave, which is driven by wind stresses and propagates westward depending upon a density stratification in the upper several hundreds of meters (e.g., Deser et al., 1999; Kawabe, 2000; TI04). We can therefore imagine that there might be some problems in the density stratification, which was maintained close to the historical stratification in the present experiments. It is well known that an interdecadal variability exists in heat and freshwater fluxes through the sea surface, which modifies the stratification (e.g., Minobe, 2000; Mantua and Hare, 2002). 3) When the first-mode baroclinic Rossby wave propagates westward in the middle of the North Pacific, its phase shifts over the Shatsky Rise and the Izu- Sensitivity of the Interannual Kuroshio Transport Variation South of Japan to Wind Dataset in OGCM Calculation 345

6 Ogasawara Ridge before it reaches the ASUKA line (TI04). Although it has been demonstrated that the fundamental effects reduce the barotropic wave and transmit the baroclinic waves, the conversion among them and the phase shift in the first-mode baroclinic wave is sensitive to the bottom topography. It is thus questionable whether the HINDCAST experiment correctly reproduces the effect of the bottom topography. 4) Many meso-scale eddies exist around the Kuroshio. Once meso-scale processes activate the Kuroshio meanders, the volume transport can be varied through eddy-mean flow interactions (Ikeda and Apel, 1981). The other example is the Kuroshio path with the stationary meander south of Japan, as shown in Fig. 3. Since the present model always reproduces the stationary meandering path of the Kuroshio, and gives no high resolution for the meso-scale variability in these HINDCAST experiments, the nonlinear effects might modify the Kuroshio transport (e.g., Qiu and Miao, 2000). To examine reason 1), we conducted an additional HINDCAST experiment using different wind data than the NCEP/NCAR values and inspected whether the disagreement of the interannual HINDCAST transport variability is reduced. Hereafter, we call this new experiment the HINDCAST re-experiment. The outline of the HINDCAST re-experiment is described in the next section. Furthermore, to examine reason 2), the Sverdrup transport is integrated over the mid-latitude North Pacific on the characteristics corresponding to different phase speeds of the first-mode baroclinic Rossby waves, as shown in the Summary and Discussion section. 5. Temporal Variations of the Transport Derived from ECMWF Data In this section we describe the HINDCAST re-experiment conducted to investigate the variability of the Kuroshio transport when the NCEP/NCAR wind data are replaced by different wind data, for which we adopted the ECMWF reanalysis daily wind speed data. The daily wind data were first converted to wind stresses and then averaged for each month. The temporal and spatial distributions of this ECMWF wind dataset are available from January, 1979 to December, 1993, at 2.5 grid interval in both longitudinal and latitudinal directions. The period of the ECMWF data is shorter than that of the NCEP/ NCAR used in this study. Under the restriction of this data availability, we carried out the HINDCAST re-experiment using the NCEP/NCAR reanalysis monthly mean wind stress data during January, 1960 December, 1978, the ECMWF monthly mean wind data during January, 1979 December, 1993, and then the NCEP/NCAR reanalysis monthly mean wind stress data again during January, 1994 December, These calculation procedures for the HINDCAST re-experiment are shown as Fig. 5. Diagram of the calculation procedures for the HINDCAST re-experiment (using ECMWF wind data from January, 1979 to December, 1993). a chart in Fig. 5. Since the ECMWF reanalysis database contains no wind stress data, we converted 10m-height wind velocity into wind stress, employing the relation given by Smith (1981), and derived the conversion equation from the neutral case as follows: CD = U where C D denotes a 10m-height drag coefficient, and U 10 denotes 10m-height wind speed (m/s). After calculating C D from each value of the ECMWF 10m-height wind speed using this equation, we derived the wind stress from the quadratic bulk formula. We then applied the stress data to the HINDCAST re-experiment. Figures 6 show the mean (from January, 1979 to December, 1993) wind stress curl (curl τ) fields of the NCEP/NCAR and the ECMWF, respectively. There are no remarkable differences in the distributions and the magnitudes of curl τ between the two data sets. If we look more closely, however, some differences are found: i.e., the larger areas where curl τ is less than N m 3 are found around 180 E, 30 N and 130 W, 35 N in the NCEP/NCAR rather than in the ECMWF. Moreover, the ECMWF has a larger area around 120 E, 23 N where curl τ is less N m 3 than the NCEP/ NCAR. These small differences may be related to possible causes that produce differences in the variabilities of the Kuroshio transports calculated in the HINDCAST experiments, as Ishikawa et al. (2003) pointed out; a fiveyear scale variation of the Kuroshio transport across the PN line might be determined by the variation of curl τ around Taiwan. Figure 7(a) shows the temporal variability of the Kuroshio transport across the PN line calculated in the HINDCAST re-experiment. In comparison with the variation pattern of the transport generated in the HINDCAST experiment by the NCEP/NCAR data, both patterns are very similar to each other after one-year filtering to retain the interannual variability. A minor difference in the transport values may be caused by the adoption of the H. Yoshinari et al.

7 Fig. 6. Mean wind stress curl (curl τ) field in January, 1979 December, 1993 of (a) NCEP/NCAR and (b) ECMWF. Contour interval is N m 3. Shaded area denotes negative value. 10m-height drag coefficient for the HINDCAST re-experiment. The similarity between the two wind datasets suggests that a major reason for the disagreement of the Kuroshio transports between the HINDCAST experiment and the observations is not due to unreliability of the NCEP/NCAR reanalysis data, at least in the case of the PN line. There might be another reason, for example, the present model cannot expresses the effects of local bottom topography and (or) the nonlinear nature of the strong Kuroshio current. Figure 7(b) shows the temporal variability of the Kuroshio transport across the ASUKA line calculated in the HINDCAST re-experiment. The temporal variation pattern of the transport is similar to that of the HINDCAST experiment until By contrast, after 1991, the variation patterns become different from each other. A clear difference is seen from As shown in Fig. 4(b), the observed Kuroshio transport decreased from 1993 to the middle of 1995 and recovered rapidly (increased) by This variation pattern is a minor improvement in the HINDCAST re-experiment. It is noted that, even in the HINDCAST re-experiment, we adopted the NCEP/NCAR wind stress data from 1994, as described previously. Nevertheless, the transport variation pattern of the Fig. 7. Time series of the Kuroshio transport across (a) PN line (relative to 700 m) and (b) ASUKA line (the absolute transport upper 1000 m). Solid line denotes the transport calculated by the HINDCAST experiment (NCEP/NCAR), doted line denotes the HINDCAST re-experiment (ECMWF and NCEP/NCAR). One-year running mean is applied to each transport. HINDCAST re-experiment is different from that of the HINDCAST experiment, giving a slightly better agreement with the observed value from In the present analysis, we cannot find a clear cause for this minor improvement. The correlation coefficients with the observed transport are about 0.2 with the HINDCAST experiment and about 0.5 with the HINDCAST re-experiment, showing some improvement using the ECMWF data. As described in the previous section and this section, the temporal variabilities of the Kuroshio transports from both wind datasets are consistent with the observed one until Even though the HINDCAST has been improved to a certain degree using the ECMWF data, there may be a major reason for the disagreement of interannual variabilities of the Kuroshio transports during the 1990s other than the wind data. 6. Summary and Discussion We have carried out OGCM calculations using two kinds of wind datasets, NCEP/NCAR and ECMWF, as Sensitivity of the Interannual Kuroshio Transport Variation South of Japan to Wind Dataset in OGCM Calculation 347

8 (Sv) Transport Year Fig. 8. Time series of the integrated Sverdrup transport in the mid-latitude (26 N 32 N) using curl τ anomaly at each month from the monthly climatological calculated from 1) the NCEP/NCAR reanalysis monthly wind stress data in January, 1979 December, 1999 (solid lines), and 2) ECMWF ones in January, 1979 December, 1993 used in the HINDCAST re-experiment (dotted lines). Integration was carried out along the characteristics of each propagation speed of the first-mode baroclinic Rossby wave (black: 7 cm/s, red: 6 cm/s, green: 5 cm/s) from 170 W to 125 E. driving forces to investigate the reproduction of the interannual variability of the Kuroshio transport. The variation patterns in the OGCM were nearly similar to the observed ones until By contrast, after 1986, the variation patterns did not agree well with the observed patterns. A minor improvement was found in the ECMWF case, which was closer to the observed values than in the NCEP/NCAR case, which suggests that there might be another reason why the variability is not reproduced for some period of wind-driven OGCM calculations. Next, we invesigated another reason than selecting the wind datasets which were adopted to drive OGCM. As described in a previous section as reason 2), our hypothesis is that a major interannual variability of the Kuroshio transport is related to the first-mode baroclinic Rossby waves generated by the wind stresses (e.g., Deser et al., 1999; Kawabe, 2000; TI04). It is probable that the density stratification (especially around the pycnocline) is modified by the bidecadal climate change (e.g., Minobe, 2000; Mantua and Hare, 2002), and the phase speed change of the baroclinic Rossby waves may modify the variation patterns of the Kuroshio transport. With this purpose in mind, we calculated the curl τ anomaly each month from the monthly wind data of 1) the NCEP/NCAR reanalysis from January, 1979 to December, 1999, and 2) the alternative one with the ECMWF data from January, 1979 to December, 1993 which were used in the HINDCAST re-experiment by replacing the NCEP/NCAR data. We then averaged them in the meridional direction from 26 N to 32 N. We next integrated curl τ anomalies along the characteristics of propagation speed of the firstmode baroclinic Rossby wave from 170 W to 125 E. This integration produces the Sverdrup transport propagating with the first-mode baroclinic Rossby wave, and hence, the transport of the western boundary current, the Kuroshio. Figure 8 shows the time series of the integrated Sverdrup transports following the derivation methods described above. The first-order estimate indicates that the phase speed of the first-mode baroclinic Rossby wave is about 6 cm/s in the middle of subtropical gyre (Kawabe, 2000). Climate change could produce change in density of about 0.1 kg/m 3 in the top 200 m, inducing a change in phase speed by about 1 cm/s. We show the three cases of phase speeds of 5, 6 and 7 cm/s in Fig. 8. Both the NCEP/ NCAR and ECMWF variation patterns, which have about a five-year periodic motion, are similar to each other with about a one-year phase difference between the cases of 5 and 7 cm/s. This result suggests that, even if the variations of heat and freshwater fluxes at the sea surface occur, such as the regime shift, and change the strength of the density stratification, a drastic change in the Kuroshio transport variability may not occur. However, by looking closely at the variability patterns, we notice some differences, such as a nearly monotonic decrease from 1993 to 1996 in the 7 cm/s case, while it fluctuates in the 5 cm/s case. This result suggests that the stratification might be responsible to a certain extend for the variation of the Kuroshio transport, whereas it is difficult to attribute a major model-data disagreement to the stratification as well as the variation of the wind stress field. Let us consider the reproduction of the bottom topography or stratification effects that has been mentioned in the previous section as reason 3). The bottom topography dataset used in the HINDCAST experiments is ETOPO5, which is one of the most reliable topography datasets. On the other hand, the vertical resolution of the OGCM used in this study is 24 levels (layers), and 10 layers are assigned above Izu-Ogasawara Ridge (see Table 1). This arrangement seems to enable the HINDCAST experiments to transmit and convert the baroclinic Rossby waves up to the second-mode (refer to TI04). It seems, however, to be unsatisfactory to expect the effects of the bottom topography and the stratification to be reproduced more correctly under the specification that has the 24- level vertical resolution. An OGCM with finer resolution should be adopted to reproduce the variation of the Kuroshio transport more correctly. We still have an open question why the HINDCAST experiments were not successful for some period in the 1990s. In the future, further work should be devoted to a more precise study of the effect of the bottom topography on Rossby waves and the nonlinear effects of the Kuroshio flowing along the western boundary of the Pacific Ocean in numerical (OGCM) simulation. Our final remark is that the path variation of the Kuroshio must be 348 H. Yoshinari et al.

9 reproduced properly ( reason 4) ) before the HINDCAST experiments become reliable in reproducing the Kuroshio transport variability at several year scales. For this, we need to improve the horizontal resolution of the OGCM from present 0.25 grid spacing to higher one that enables it to fully reproduce meso-scale eddies. Acknowledgements We would like to thank Y. Wakata, T. Awaji, S. Imawaki, M. Kamachi, A. Isobe, H. Sumata and Y. Masuda for giving useful suggestions, K. Murakami and T. Hinata for supplying us the observation data of PN line, H. Uchida for supplying us the observation data of ASUKA line, and T. Ikeda for correction of our English expressions. Most of the figures were produced by GFD- DENNOU Library. This study was supported by the Core Research for Evolutional Science and Technology (CREST) of Japan Science and Technology Corporation (JST). References Akitomo, K., T. Awaji and N. Imasato (1991): Kuroshio pass variation south of Japan: 1. Barotropic inflow-outflow model. J. Geophys. Res., 96, Akitomo, K., M. Ooi, T. Awaji and K. Kutsuwada (1996): Interannual variability of the Kuroshio transport in response to the wind stress field over the North Pacific: Its relation to the path variation south of Japan. J. Geophys. Res., 101, Deser, C., M. A. Alexander and M. S. Timlin (1999): Evidence for a wind-driven intensification of the Kuroshio current extension from the 1970s to the 1980s. J. Climate, 12, Hinata, T. (1996): Seasonal variation and long-term trends of the oceanographic conditions along a fixed hydrographic line crossing the Kuroshio in the East China Sea. Oceanogr. Mag., 45, Ichikawa, H. and R. C. Beardsley (1993): Temporal and spatial variability of volume transport of the Kuroshio in the East China Sea. Deep Sea Res. I, 40, Ikeda, M. and J. R. Apel (1981): Mesoscale eddies detached from spatially growing meanders in an eastward-flowing oceanic jet using a two-layer quasi-geostrophic model. J. Phys. Oceanogr., 11, Imawaki, S., H. Uchida, H. Ichikawa, M. Fukazawa, S. Umatani and the ASUKA Group (2001): Satellite altimeter monitoring the Kuroshio transport south of Japan. Geophys. Res. Lett., 28, Ishikawa, K., Y. Takatsuki, S. Shiraishi, S. Tsubaki, A. Nakadate, T. Miyao, M. Kitano, H. Inoue, N. Kubo and J. Nishizawa (2003): Ocean variability observed along JMA s hydrographic sections and its cause. Weath. Service Bull., 70, S1 S34 (in Japanese). Isobe, A. and S. Imawaki (2002): Annual variation of the Kuroshio transport in a two-layer numerical model with a ridge. J. Phys. Oceanogr., 32, Kalnay, E. and Coauthers (1996): The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, Kawabe, M. (1980): Sea level variations around the Nansei Islands and the large meander in the Kuroshio south of central Japan. J. Oceanogr. Soc. Japan, 36, Kawabe, M. (1995): Variations of current path, velocity, and volume transport of the Kuroshio in relation with the large meander. J. Phys. Oceanogr., 25, Kawabe, M. (2000): Calculation of interannual variations of sea level in the subtropical North Pacific. J. Oceanogr., 56, Kawabe, M. (2001): Interannual variations of sea level at the Nansei Islands and volume transport of the Kuroshio due to wind changes. J. Oceanogr., 57, Levitus, S. (1982): Climatological atlas of the world ocean. NOAA Prof. Pap., 13, U.S. Government Printing Office, Washington, D.C., 173 pp. Macdonald, A. M. and C. Wunsch (1996): An estimate of global ocean circulation and heat fluxes. Nature, 382, Mantua, N. J. and S. R. Hare (2002): The pacific decadal oscillation. J. Oceanogr., 58, Masuda, A. (1982): An interpretation of the bimodal character of the stable Kuroshio path. Deep Sea Res. A, 29, Minobe, S. (2000): Spatio-temporal structure of the pentadecadal variability over the North Pacific. Prog. Oceanogr., 47, Nitani, H. (1972): Begining of the Kuroshio. p In Kuroshio Its Physical Aspects, ed. by H. Stommel and K. Yoshida, Univ. of Tokyo Press. Pacanowski, R. C. (1996): MOM 2.2β, documentation, user s guide and reference manual. GFDL Ocean Technical Report 3.2, Geophysical Fluid Dynamics Laboratory, Princeton, 329 pp. Qiu, B. and T. M. Joyce (1992): Interannual variability in the mid- and low-latitude Western North Pacific. J. Phys. Oceanogr., 22, Qiu, B. and W. Miao (2000): Kuroshio path variations south of Japan: bimodality as a self-sustained internal oscillation. J. Phys. Oceanogr., 30, Rosati, A. and K. Miyakoda (1988): A general circulation model for upper ocean simulation. J. Phys. Oceanogr., 18, Saiki, M. (1982): Relation between the geostrophic flux of the Kuroshio in the Eastern China Sea and its large-meanders in south of Japan. Oceanogr. Mag., 32, Smagorinsky, J. (1963): General circulation experiments with the primitive eqations: I. The basic experiment. Mon. Wea. Rev., 91, Smith, S. D. (1981): Coefficients for sea-surface wind stress and heat exchange. Report series of Bedford Institute of Oceanography, Dartmouth, Nova Scotia, Canada, December. Tanaka, K. and M. Ikeda (2004): Propagation of Rossby waves over ridges excited by interannual wind forcing in a western North Pacific model. J. Oceanogr., 60, this issue, Tanaka, K., M. Ikeda and Y. Masumoto (2004): Predictability of interannual variability in the Kuroshio transport south of Japan based on wind stress data over the North Pacific. Sensitivity of the Interannual Kuroshio Transport Variation South of Japan to Wind Dataset in OGCM Calculation 349

10 J. Oceanogr., 60, this issue, Uchida, H. and S. Imawaki (2004): Ten-year record of the Kuroshio transport south of Japan estimated from satellite altimeter data (in preparation). Vonder Haar, T. H. and A. H. Oort (1973): New estimate of annual poleward energy transport by northern hemisphere oceans. J. Phys. Oceanogr., 3, White, W. B. and J. P. McCreary (1976): On the formation of the Kuroshio meander and its relationship to the large-scale ocean circulation. Deep Sea Res. and Oceanogr. Abst., 23, Yoon, J.-H. and I. Yasuda (1987): Dynamics of the Kuroshio large meander: Two layer model. J. Phys. Oceanogr., 17, H. Yoshinari et al.