1. Introduction
Meinen and McPhaden (2000) showed observationally that variations in the tropical 20°C isotherm depth, a proxy for the thermocline depth, consisted of two main modes—a tilting mode essentially in phase with eastern equatorial Pacific Ocean sea surface temperature (SST) and a discharge and recharge of warm water volume (WWV) above the 20°C isotherm whose time derivative is negatively correlated with eastern equatorial Pacific SST. These properties can be seen in Figs. 1 and 2 for the equatorial strip from 5°S to 5°N and the El Niño index Niño-3.4 (the SST anomaly averaged over the east-central equatorial Pacific region 5°S–5°N, 170°–120°W). The first EOF describes 51% of the variance and the second 35% so that these modes describe 86% of the variance, essentially all of the interannual variability of the equatorial thermocline.
The EOF structure function in Fig. 1a tilts upward in the central Pacific from about 160°E to 120°W, in approximately the same region as the westerly wind anomalies in Fig. 3 (about 155°E–140°W). Physically, the wind stress pushes surface water eastward and holds it there, the eastward wind force balancing the zonal pressure gradient. This balance was first established observationally for the interannual Pacific thermocline depth by Kessler (1990) and for the sea level by Li and Clarke (1994).





In the equatorial literature the balance (1.4) has often been referred to as “Sverdrup balance.” This is an unfortunate choice of words because, from (1.5), it implies that V = 0. But V is often referred to as “Sverdrup transport,” so we have a situation in which the Sverdrup transport is zero when the Sverdrup balance is satisfied! This is very confusing in some of the key papers in ENSO discharge/recharge theory—many authors state that Sverdrup balance of the form (1.4) or similar holds but then incorrectly state that Sverdrup transport V ≠ 0.
Returning to the observations, we note that the thermocline tilt/eastward wind stress balance in anomaly form does not completely explain the anomalous 20°C isotherm depth behavior. Specifically, the 20°C isotherm depth amplitude east of about 100°W falls rapidly (Fig. 1a) and the zonal wind stress anomaly structure function is only weakly negative. The discrepancy is probably due to the 20°C isotherm depth not being a good proxy for the thermocline depth because the satellite-derived sea level anomalies in phase with the zonal wind anomalies and Niño-3.4 do not fall rapidly east of 100°W (see Fig. 4). The sea level anomalies behave more in line with theory; their amplitude gently decreases east of about 120°W, consistent with the weak equatorial wind anomalies there (see Fig. 3).
While the first EOF mode is generally consistent with theory, there is some disagreement in the literature concerning the physics of the second EOF mode. In contrast with the first EOF, whose structure function is of opposite sign in the eastern and western Pacific, the second mode EOF has a structure function essentially of one sign right across the Pacific (cf. Figs. 1a and 2a). Rather than a thermocline tilt, it represents an anomalous storage of warm water. This WWV varies in time like the time integral of Niño-3.4 (see Fig. 2b).
The seminal papers of Jin (1997a, b) have discussed the discharge/recharge of WWV theoretically. However, those papers do not emphasize the importance of the wind stress curl for ENSO recharge/discharge. In fact, based on Jin’s parameters (see Jin 1997b), the zonal interannual wind stress has a large north–south scale, so large that the zonal interannual wind stress is essentially constant over the equatorial box bounded by 5°S and 5°N and the curl is very small. Quantitatively, for such a large north–south scale and realistic equatorial wind stress anomalies, curl anomalies at 5°S and 5°N generate changes in the WWV that are too small by a factor of more than 3.
In this paper we argue that the wind stress curl anomaly is crucial to the ENSO discharge/recharge. However, this does not mean that the meridional recharge/discharge is given by the traditional midlatitude formula for upper ocean Sverdrup transport—one must also take into account vortex stretching at ENSO time scales. We will also suggest that, in coupled discharge/recharge physics, the main ocean–atmosphere coupling occurs in the west-central equatorial Pacific rather than in the eastern equatorial Pacific as proposed in previous discharge/recharge oscillator models.
We begin the analysis of discharge/recharge physics by first presenting theory for the storage and discharge of WWV in an equatorial strip in section 2 and then testing it in section 3. The theory and observations suggest that the anomalous wind stress curl is crucial to the recharge and discharge of the WWV anomaly and that the meridional discharge and recharge is not in Sverdrup balance in any sense. Section 4 discusses a simplified discharge/recharge coupled model based on past results and the results in sections 2 and 3. Section 5 contains some concluding remarks.
2. Theory for anomalous storage and discharge of the WWV



Meinen and McPhaden (2001) and Meinen (2005) checked the balance (2.3) by calculating UW, VS, and VN as a sum of geostrophic and Ekman transports, the geostrophic transport being determined from hydrographic observations. Such an analysis does not enable us to determine how the WWV anomaly is forced by the wind anomalies since the geostrophic anomalous currents are given rather than being related to the wind anomalies.















Note that h on the left-hand side of (2.15) is time-dependent and that (2.15) is a linear equation. From now on we will consider interannual and longer low frequency variability governed by (2.15) with h, curl τ, and TW replaced by their low-frequency versions: h′, curl τ′, and T ′W.





3. Comparison of the theory with observations
We will check the theory of section 2 by testing the validity of the low-frequency version of (2.15). In addition to h, kindly provided by the Bureau of Meteorology Research Center, Australia (Smith 1995a, b), we will need observationally based anomalous wind stress curl and T ′W. Given that wind data are often noisy and incomplete, the curl of the wind stress, involving a derivative of the wind stress, is even more noisy. We therefore decided to base our main results on the scatterometer-derived winds (available online at http://www.ifremer.fr/cersat/en/index.htm), the most complete and accurate curl data available.
The net interannual western boundary layer transport supplies T ′W, the remaining term to be calculated in (2.15). Previous theoretical (e.g., Zebiak 1989; An and Kang 2001) and observational (Meinen and McPhaden 2001) work has suggested that this western boundary layer transport and, therefore, T ′W contribute significantly. However T ′W could not be estimated as directly as the other terms in (2.15) because the geostrophic ocean current estimates at 156°E, generously provided by Christopher Meinen (Meinen and McPhaden 2001; Meinen 2005), were only available at 3.5°S, 0°, 3.5°, and 6.5°N. We were concerned that these measurements might not be close enough together to resolve the meridional structure of the interannual geostrophic flow. We therefore calculated the interannual transport T ′W in two ways. Both ways used along-track TOPEX/Poseidon altimeter measurements, available every 6–7 km, to obtain high-resolution interannual geostrophic surface flow. In one case we obtained the subsurface geostrophic flow structure by linearly interpolating and extrapolating the vertical structure of the geostrophic flow at 3.5°S, 0°, 3.5°, and 6.5°N based on observations. For the other estimate we noted that the observed vertical structure of the geostrophic flow at the four latitudes is similar to that of a first vertical mode, and we approximated the geostrophic subsurface flow structure by the first vertical mode structure calculated every one degree of latitude. Two estimates of T ′W were obtained as a sum of each interannual geostrophic transport and the Ekman transport. Details are given in appendix B. Our two transport estimates for T ′W differed negligibly.
Figure 5a shows monthly time series of the left- and right-hand sides of (2.15). Each monthly anomaly time series has been detrended and filtered with a Trenberth (1984) filter; this filter passes essentially no amplitude at frequencies higher than 2π/8 months and passes greater than 80% of the amplitude at frequencies lower than 2π/2 yr. The two time series are correlated [r = 0.63, rcrit (95%) = 0.60] but the amplitude of the right-hand side of (2.15) is too small. If T ′W were zero, then the amplitudes of both sides would be nearly the same (Fig. 5b) and there would be a balance. But it is unlikely that observed T ′W is negligible since we calculated it in two different ways (see section 2 and appendix B) and obtained nearly exactly the same nonnegligible result. Furthermore, T ′W is well correlated with Niño-3.4 [r = 0.81, rcrit(95%) = 0.69], suggesting that we are calculating a meaningful signal. Thus it is likely that T ′w is nonzero and our imbalance is real. The imbalance implies that our assumption that the 20°C isotherm depth is a material surface and can therefore only be changed by volume transport is wrong. It ignores the possibility that the WWV can be changed by anomalous heating and cooling. For example, if the WWV is anomalously cooled so that some of it is less than 20°C, then the WWV is decreased as the 20°C isotherm rises (i.e., there is a loss of WWV through the bottom of the WWV box). This is consistent with previous work by Meinen and McPhaden (2001) for a larger box (8°S–8°N, 156°E–95°W); they also found substantial transport across the 20°C isotherm. In addition, Wang and McPhaden (2000) and Holland and Mitchum (2003) both document interannual heating and cooling at the sea surface.
As noted by Meinen and McPhaden (2001), T ′W is mostly due to western boundary flows. Although this transport is substantial, Fig. 5b shows that, if we put T ′W = 0 in the anomaly version of (2.15), thus ignoring both T ′W and anomalous flow through the bottom of the box, then (2.15) [and also (2.20)] approximately holds; that is, observed interannual WWV fluctuations can be regarded as being driven by wind stress curl anomalies.
Equation (2.20) then helps us understand the relationship of the time variation of the warm water volume anomaly with respect to El Niño. The wind responds rapidly to the SST anomalies, so we might expect the wind stress curl anomaly to vary in time like the SST anomaly index Niño-3.4. Figure 6 shows that this is indeed the case, as the wind stress curl anomaly term in (2.20) and Niño-3.4 are maximally correlated [r = 0.87, rcrit (95%) = 0.68] at zero lag. It follows from (2.20) that the WWV anomaly ∫A h dA should be proportional to −∫t0 NINO3.4(t*) dt*. This is approximately the case; the correlation between these two time series is r = 0.77 with rcrit (95%) = 0.69.
Why, physically, should the above correlation be negative? When there is an El Niño, the major wind anomalies in the west-central equatorial Pacific are westerly and decay away from the equator (Fig. 3). This results in a positive curl at 5°N and a negative curl at 5°S (Fig. 7). The positive curl at 5°N increases the ocean’s angular momentum in two ways [see (2.14)]: it increases its vorticity by discharging parcels northward where f is larger and increases its moment of inertia by decreasing h and thereby fattening fluid parcels. Both of these ocean adjustments lead to decreased h. By similar arguments, the negative curl along 5°S also decreases h. Thus, when there is an El Niño (Niño-3.4 is positive), the wind stress curl anomalies cause a discharge (ht < 0) of WWV in accordance with (2.20).
4. A simple discharge/recharge oscillator theory
The discharge/recharge oscillator of Jin (1997a, b) emphasizes the major role of the WWV anomaly and how that leads to a self-sustained coupled ocean–atmosphere oscillation. Discharge/recharge of equatorial WWV anomaly is also central to the model to be discussed here but it differs from Jin’s in two main ways: our model emphasizes the physics associated with the wind stress curl anomalies and also that the critical ENSO air–sea interaction takes place in the west-central equatorial Pacific (≈156°E–140°W) rather than in the eastern equatorial Pacific. The west-central equatorial Pacific is where the zonal ENSO wind anomalies driving the ocean are strongest (see Figs. 3, 7) and also where the interannual ENSO heating of the atmosphere is strongest (see Fig. 8). The strongest air–sea interaction occurs here rather than in the eastern equatorial Pacific [where the sea surface temperature anomalies (SSTAs) are larger] because the eastern equatorial Pacific is usually too cold to support deep atmospheric convection—SST usually has to be at least 27.5°–28°C before tropical large-scale deep atmospheric convection can occur (Krueger and Gray 1969; Gadgil et al. 1984; Graham and Barnett 1987).
To illustrate the main physical ideas as clearly as possible, our coupled model will consist of only two central equatorial Pacific variables: T ′, the SSTA, and D′, the 20°C isotherm depth anomaly, both averaged over the region 5°S–5°N, 156°E–140°W.
a. T′ drives D′


b. D′ drives T′




Consider the first term on the right-hand side of (4.4). Jin and An (1999) argue that u′ is proportional to D′ because u′ is related to the meridional gradient of the thermocline depth via geostrophic balance. Since ∂
With regard to the second term on the right-hand side of (4.4), first note that correlation calculations with detrended and Trenberth filtered D′ and ∂T ′/∂t monthly time series show that they are significantly positively correlated [r = 0.79, rcrit(95%) = 0.42]. This result, (4.4), and −u′∂
Consider, for example, the idealized case when the mixed layer depth is constant and water is stratified beneath the mixed layer. When D′ = 0, normal wind-generated turbulence at the base of the mixed layer results in cooler water parcels moving into the mixed layer and warmer parcels leaving it; that is, there is a heat flux out of the mixed layer but no net exchange of mass. This mean heat flux is balanced by mean heat fluxes into the mixed layer from the surface and/or horizontal advection so that T ′ = 0. Suppose now that D′ < 0; that is, the 20°C isotherm has now been displaced upward. Since the mixed layer depth is constant, conservation of mass requires that in the nonmixing region beneath the mixed layer and above the 20°C isotherm, water must have diverged horizontally. Thus there is cooler water at the base of the mixed layer, so, even though the wind stress may be unaltered, wind-generated turbulence at the base of the mixed layer causes an anomalous heat flux down through the bottom of the mixed layer; that is, Q′W < 0. Similar arguments suggest that, if D′ > 0, then Q′W > 0. It follows that Q′W should be positively correlated with D′.

The relationship (4.5) is similar to that used by Jin (1997a, b) in his original discussion of a simple discharge/recharge oscillator model. Equation (4.5) differs in that T ′ represents the west-central equatorial Pacific temperature anomaly between 156° and 140°W whereas in Jin’s model T ′ refers to the SSTA in the eastern half of the basin. Note, however, that when T ′ refers to the SSTA in the eastern half of the basin the relationship (4.5) is no longer valid. This is because, at ENSO periodicity, (4.5) predicts that T ′ lags the local 20°C isotherm depth by several months, but analysis of observations by Zelle et al. (2004) shows that the lag in the eastern equatorial Pacific is a few months or less (see Fig. 11).
c. Solution



The physics of the oscillation is summarized in Fig. 12. We begin our discussion at the height of an El Niño (upper left panel). Then T ′ is maximally positive and the wind anomalies are maximally eastward. As shown in Figs. 1 and 2, the wind anomalies cause a twofold ocean response. One part of the response consists of an anomalous tilt of the thermocline in phase with the westerly wind anomalies as the wind stress forcing is balanced by the zonal pressure gradient. While this tilt affects the thermocline depth in the eastern and western equatorial Pacific, the net displacement in the west-central Pacific region, 156°E–140°W, is mainly due to the anomalous wind stress curl, which causes poleward transport of warm water [mathematically, when T ′ is a maximum the loss of equatorial warm water is greatest in (4.1)]. One quarter of a period later (Fig. 12, upper right panel), the warm water has been discharged from the equator and the thermocline is anomalously shallow (D′ < 0). A raised thermocline implies colder water nearer the surface and a negative heat flux through the base of the mixed layer. It also results in an anomalous westward flow that advects cold water from the eastern equatorial Pacific. These processes both cause T ′ to decrease [see (4.4) and (4.5)]. Eventually, one-quarter of a period later (Fig. 12, bottom left panel) T ′ has reached its negative extremum and the model exhibits La Niña conditions with an anomalous thermocline tilt upward in the eastern equatorial Pacific and heat content anomaly zero. Through their curl, the easterly wind anomalies cause a transport of water onto the equator so that one-quarter period later (Fig. 12, bottom right panel) the warm water volume on the equator is at its maximum and D′ > 0. This, then, results in a positive heat flux at the base of the mixed layer and eastward equatorial current anomalies, causing ∂T ′/∂t to be greater than zero [see (4.4) and (4.5)] and El Niño conditions to return one-quarter of a period later (Fig. 12, upper left panel).
The above idealized model errs in several respects. For example, observations (Meinen and McPhaden 2000) suggest that the same amplitude positive and negative WWV anomalies produce different amplitude SSTAs whereas the idealized model makes no such distinction. Kessler (2002) also found that the recharge/discharge oscillator only operates for three-quarters of the cycle; there is a break in the cycle from La Niña to recharge. In addition, our idealized oscillator is not phase locked to the seasonal cycle; in the observations Niño-3.4 tends to have largest variance in December and minimum variance in April. Nevertheless, the idealized model does illustrate the idea that wind stress curl anomalies play a key role in ENSO dynamics; without wind stress curl, heat storage is negligible and the recharge/discharge oscillator mechanism fails completely.
5. Concluding remarks
Our analysis leads us to the following main conclusions: First, near-equatorial wind stress curl anomalies play a fundamental role in ENSO dynamics since they make a major contribution to the WWV anomalies. While the wind stress curl anomalies drive the poleward transport of warm water, the midlatitude Sverdrup balance, in which poleward transport is in quasi-steady balance with the windstress curl, does not hold. This is because on ENSO time scales the vortex stretching term proportional to ht contributes significantly in the vorticity equation and is an order-one contributor to the WWV anomalies. We also point out that it is confusing to call the balance (1.4) “Sverdrup balance” because it implies that the “Sverdrup transport” V is negligible.
Second, we emphasize that unlike previously proposed recharge/discharge physics, the observations suggest that the main region of ENSO air–sea coupling is in the west-central equatorial Pacific. An idealized simple model for this region (5°S–5°N, 156°E–140°W) illustrates the essential elements of the discharge/recharge physics there.
We are grateful for funding from the National Aeronautics and Space Administration (Fellowship NNG04GQ75H, for Giuseppe Colantuono) and the National Science Foundation (Grant ATM-0326799). Drs. Christopher Meinen (ocean current estimates at 156°E) and Neville Smith (20°C isotherm depth) generously provided data. Satellite estimates of sea level and wind stress were obtained from NASA and European Remote Sensing Web sites. The Climate Diagnostics Center, Boulder, Colorado (see online at http://www.cdc.noaa.gov/), provided the Reynolds Optimal Interpolation SST data.
REFERENCES
An, S. I., , and I-S. Kang, 2001: Tropical Pacific basin-wide adjustment and oceanic waves. Geophys. Res. Lett., 28 , 3975–3978.
Clarke, A. J., 1994: Why are surface equatorial winds anomalously westerly under anomalous large-scale convection? J. Climate, 7 , 1623–1627.
Ebisuzaki, W., 1997: A method to estimate the statistical significance of a correlation when the data are serially correlated. J. Climate, 10 , 2147–2153.
Gadgil, S., , P. V. Joseph, , and N. V. Joshi, 1984: Ocean–atmosphere coupling over monsoon regions. Nature, 312 , 141–143.
Graham, N. E., , and T. P. Barnett, 1987: Sea surface temperature, surface wind divergence and convection over tropical oceans. Science, 238 , 657–659.
Holland, C. L., , and G. T. Mitchum, 2003: Interannual volume variability in the tropical Pacific. J. Geophys. Res., 108 .3369, doi:10.1029/2003JC001835.
Jin, F-F., 1997a: An equatorial ocean recharge paradigm for ENSO. Part I: Conceptual model. J. Atmos. Sci., 54 , 811–829.
Jin, F-F., 1997b: An equatorial ocean recharge paradigm for ENSO. Part II: A stripped-down coupled model. J. Atmos. Sci., 54 , 830–847.
Jin, F-F., , and S-I. An, 1999: Thermocline and zonal advective feedbacks within the equatorial ocean recharge oscillator model for ENSO. Geophys. Res. Lett., 26 , 2989–2992.
Kessler, W. S., 1990: Observations of long Rossby waves in the northern tropical Pacific. J. Geophys. Res., 95 , 5183–5217.
Kessler, W. S., 2002: Is ENSO a cycle or a series of events? Geophys. Res. Lett., 29 .2125, doi:10.1029/2002GL015924.
Krueger, A. F., , and T. I. Gray, 1969: Long-term variations in equatorial circulation and rainfall. Mon. Wea. Rev., 97 , 700–711.
Li, B., , and A. J. Clarke, 1994: An examination of some ENSO mechanisms using interannual sea level at the eastern and western equatorial boundaries and the zonally averaged equatorial wind. J. Phys. Oceanogr., 24 , 681–690.
McArdle, B. H., 1988: The structural relationship: Regression in biology. Can. J. Zool., 66 , 2329–2339.
McPhaden, M. J., 1981: Continuously stratified models of the steady-state equatorial ocean. J. Phys. Oceanogr., 11 , 337–354.
Meinen, C. S., 2005: Meridional extent and interannual variability of the Pacific Ocean tropical–subtropical warm water exchange. J. Phys. Oceanogr., 35 , 323–335.
Meinen, C. S., , and M. J. McPhaden, 2000: Observations of warm water volume changes in the equatorial Pacific and their relationship to El Niño and La Niña. J. Climate, 13 , 3551–3559.
Meinen, C. S., , and M. J. McPhaden, 2001: Interannual variability in warm water transports in the equatorial Pacific during 1993–99. J. Phys. Oceanogr., 31 , 1324–1345.
Picaut, J., , S. P. Hayes, , and M. J. McPhaden, 1989: Use of the geostrophic approximation to estimate time-varying zonal currents at the equator. J. Geophys. Res., 94 , 3228–3236.
Smith, N. R., 1995a: An improved system for tropical ocean subsurface temperature analysis. J. Atmos. Oceanic Technol., 12 , 850–870.
Smith, N. R., 1995b: The BMRC ocean thermal analysis system. Aust. Meteor. Mag., 44 , 93–110.
Trenberth, K. E., 1984: Signal versus noise in the Southern Oscillation. Mon. Wea. Rev., 112 , 326–332.
Wang, W., , and M. J. McPhaden, 2000: The surface-layer heat balance in the equatorial Pacific Ocean. Part II: Interannual variability. J. Phys. Oceanogr., 30 , 2989–3008.
Zebiak, S. E., 1989: Oceanic heat content variability and El Niño cycles. J. Phys. Oceanogr., 19 , 475–486.
Zelle, H., , G. Appeldoorn, , G. Burgers, , and G. J. van Oldenborgh, 2004: The relationship between sea surface temperature and thermocline depth in the eastern equatorial Pacific. J. Phys. Oceanogr., 34 , 643–655.
APPENDIX A
Justification for the Neglect of Relative Vorticity at Low Latitude

First note that, under the large-scale approximation that the Rossby number is small, (ζ + f ) may be replaced by f in (A.1). At latitude 5°, | f| ≃ 1.2 × 10−5 s−1 and |ζ| ≲ 10−6 s−1, so this condition is satisfied.


In summary, since the Rossby number and (c/fΔy)2 are small, the vorticity equation in (A.2) can be reduced to the large-scale vorticity equation in (2.6) of the main text. As shown in the main text, (2.6) can also be deduced from the approximate momentum equation in (2.5).
APPENDIX B
Estimating T ′W, the Eastward Interannual Transport above the 20°C Isotherm between 5°S and 5°N at 156°E

As noted in section 3, monthly geostrophic ocean current estimates at 156°E were generously made available at 3.5°S, 0°, 3.5°, and 6.5°N by Christopher Meinen (Meinen 2005). These estimates were derived using the meridian 156°E of the equatorial Pacific TAO/TRITON Array (see online at http://www.pmel.noaa.gov/tao/index.shtml). We calculated monthly interannual geostrophic currents from the monthly time series by removing the 12-point annual time series and Trenberth filtering in a similar way to the Ekman transport.





If d(y) and ϕ(y, t) were adequately resolved by the measurement array at the four latitudes, 6.5°N, 3.5°N, 0°, and 3.5°S, then we could approximate the first term on the right-hand side of (B.6) by a finite sum. But calculations show that the ϕi(t) are insignificantly correlated with each other (Table B1) and d(yi) is considerably larger south of the equator (see Fig. B2) where we only have one measurement.
We overcame the ϕ resolution problem by calculating the eastward interannual surface flow ϕ from high-resolution along-track satellite altimeter data for the 2 nearest tracks to 156°E. In each case we assumed that the zonal scale was much larger than the meridional so that dynamically both tracks were perpendicular to the equator and high-resolution zonal interannual geostrophic surface currents could be estimated. Our final estimate was an average of the estimates for each track.
With regard to the d(y) resolution problem, we noticed that the structures Gi(z) in Fig. 13 are similar to those of the first vertical mode, suggesting that high-resolution G(y, z) in (B.3) and hence d(y) in (B.5) might be obtained by calculating the first vertical mode as a function of latitudinally varying buoyancy frequency and water depth. Figure B2 shows an estimate of d(y) obtained from (B.5) and such an estimate for G together with d(yi) based on the EOF Gi(z) from (B.2). We calculated T ′W using d(y) in (B.6) from a first vertical mode calculation and d(y) based on the interpolation and extrapolation of the four EOF d(yi) values from the estimated currents. The two T ′W time series differed negligibly.

The (a) first EOF (51% of the variance) of the 20°C isotherm depth anomaly (m) for the equatorial (5°S–5°N) Pacific and (b) corresponding first principal component (solid line). The principal component time series has been normalized to have variance = 0.5 so that (a) represents the amplitude of the isotherm depth anomaly. The dashed curve in (b) is the Niño-3.4 time series normalized so that it has the same variance as the first principal component. The correlation coefficient between the two time series is r = 0.93. The isotherm data were supplied by N. Smith (Smith 1995a, b).
Citation: Journal of Physical Oceanography 37, 4; 10.1175/JPO3035.1

(a), (b) As in Fig. 1 but for the second EOF, explaining 35% of the variance. In this case the dashed curve is not Niño-3.4 but rather ∫t0 NINO3.4(t*) dt*. The integral time series has zero mean and variance 0.5.
Citation: Journal of Physical Oceanography 37, 4; 10.1175/JPO3035.1

Regression of the ERS zonal wind stress anomaly onto the El Niño index Niño-3.4 for the time interval from January 1992 to December 2000. Negative contours are dashed, positive contours are solid, and the zero line is a solid line thinner than those for the positive contours. The contours are in intervals of 5 mPa °C−1.
Citation: Journal of Physical Oceanography 37, 4; 10.1175/JPO3035.1

As in Fig. 1 but with TOPEX/Poseidon/Jason satellite-estimated sea level anomalies (cm) replacing the 20°C isotherm depth anomalies. In the sea level case the first EOF explains 69% of the variance and the correlation of the first principal component with Niño-3.4 is r = 0.95.
Citation: Journal of Physical Oceanography 37, 4; 10.1175/JPO3035.1

(a) Monthly time series of the rhs (dashed curve) and the lhs (solid curve) of (2.15). The time series have been detrended and filtered (see main text). The correlation between the time series is r = 0.63 with rcrit (95%) = 0.60. (b) As in (a) but now the rhs (dashed curve) of (2.15) has T ′W = 0. In this case r = 0.85 with rcrit (95%) = 0.66.
Citation: Journal of Physical Oceanography 37, 4; 10.1175/JPO3035.1

Detrended and Trenberth (1984) filtered monthly time series of the zonally integrated wind stress curl anomaly term [the rhs of (2.15) with T ′W omitted: dashed curve] and Niño-3.4 (solid curve). The time series are maximally correlated [r = 0.87, rcrit (95%) = 0.68] at zero lag. Each time series has been normalized by its standard deviation.
Citation: Journal of Physical Oceanography 37, 4; 10.1175/JPO3035.1

Regression of the ERS wind stress curl anomaly onto the El Niño index Niño-3.4 for the time interval January 1992–December 2000. Negative contours are dashed, positive contours are solid, and the zero line is a solid line thinner than those for the positive contours. The contours are in intervals of (10−8 Pa m−1) °C−1.
Citation: Journal of Physical Oceanography 37, 4; 10.1175/JPO3035.1

Regression of outgoing longwave radiation (OLR) anomalies (W m−2) onto the El Niño index Niño-3.4 for the period January 1974–June 2004. The El Niño index has been normalized to have variance equal to 0.5 so that the regression plot represents a typical ENSO amplitude. Negative OLR anomalies are a proxy for anomalous deep convective precipitation.
Citation: Journal of Physical Oceanography 37, 4; 10.1175/JPO3035.1

(a) The lhs (dashed) and rhs (solid) of (4.1). Both time series have been filtered with the low-pass Trenberth (1984) filter. The correlation r = 0.73 with rcrit (95%) = 0.40. (b) As in (a) but for (4.5). The correlation r = 0.79 with rcrit (95%) = 0.42. (c) Trenberth-filtered T ′ (in °C: solid curve) and Trenberth-filtered D′ divided by its standard deviation (dashed curve). Lagged correlation between these time series shows that D′ is maximally correlated with T ′ when it leads it by 11 months (r = 0.74) and −T ′ is maximally correlated with D′ when it leads it by 10 months (r = 0.56). This is consistent with (a) and (b) and an oscillation of ENSO periodicity.
Citation: Journal of Physical Oceanography 37, 4; 10.1175/JPO3035.1

Monthly time series of the lhs (dashed) and rhs (solid) of (4.2) with T ′W − T ′E omitted. The time series have been filtered with the Trenberth (1984) interannual filter. The correlation between the time series is r = 0.79 with rcrit (95%) = 0.65.
Citation: Journal of Physical Oceanography 37, 4; 10.1175/JPO3035.1

Lag correlation between observed Z20 anomalies (i.e., D′) and SST anomalies on the equator. A positive lag means Z20 is leading SST. The correlation was computed using monthly temperature data from the TAO/TRITON array for the period of 1990–99 (Zelle et al. 2004).
Citation: Journal of Physical Oceanography 37, 4; 10.1175/JPO3035.1

An idealized schematic of the discharge/recharge oscillator. All quantities shown are anomalies. The dashed and heavy solid lines denote the zero thermocline depth anomaly and the actual thermocline depth anomaly, respectively. The anomalous heating and cooling of the atmosphere occurs in the west-central equatorial Pacific through anomalous deep atmospheric convection denoted by the cloud symbols—the plus, minus, and zero notation denoting positive, negative, and zero anomalies. The atmospheric convection anomalies are driven by west-central equatorial Pacific SST anomalies of the same sign (not shown). The eastern equatorial Pacific temperature anomalies, a feature of the standard recharge/discharge paradigm (Jin 1997a, b), are not shown since they do not play a role in the dynamics. The thin arrows at the surface refer to the zonal equatorial wind anomalies with stress τa. These anomalies, driven by the deep anomalous atmospheric convection, decrease meridionally with latitude and the resultant wind stress curl anomalies drive meridional ocean transport (solid thick arrows). This stress curl anomaly is a key aspect of the dynamics and has not been properly recognized in the standard recharge/discharge paradigm. The text discusses the oscillation in the sequence 1–4.
Citation: Journal of Physical Oceanography 37, 4; 10.1175/JPO3035.1

Fig. B1. The first EOF structure functions Gi(z) for 3.5°S (solid curve), 0° (dashed curve), 3.5°N (dotted curve), and 6.5°N (dash–dot curve). The structure functions end at the average 20°C isotherm depth. The first mode EOF at 3.5°S explained 93% of the variance there. The corresponding percentages for the first mode EOFs at 0°, 3.5°, and 6.5°N are 86%, 96%, and 98%, respectively.
Citation: Journal of Physical Oceanography 37, 4; 10.1175/JPO3035.1

Fig. B2. The meridional structure function d(y), based on a first vertical mode estimation, and d(yi) at each of the four measurement locations.
Citation: Journal of Physical Oceanography 37, 4; 10.1175/JPO3035.1
Table B1. Correlations (upper triangle) between the first principal components ϕi(t) for i = 1 (3.5°S), i = 2 (0°), i = 3 (3.5°N), and i = 4 (6.5°N).
