near-annual sst variability in the equatorial pacific in a

Near-Annual SST Variability in the Equatorial Pacific in a Coupled General Circulation Model
RENGUANG WU
BEN P. KIRTMAN
School for Computational Sciences, George Mason University, Fairfax, Virginia, and Center for Ocean–Land–Atmosphere Studies, Calverton, Maryland
(Manuscript received 20 December 2004, in final form 4 May 2005)
ABSTRACT
Equatorial Pacific sea surface temperature (SST) anomalies in the Center for Ocean–Land–Atmosphere Studies (COLA) interactive ensemble coupled general circulation model show near-annual variability as well as biennial El Niño–Southern Oscillation (ENSO) variability. There are two types of near-annual modes: a westward propagating mode and a stationary mode. For the westward propagating near-annual mode, warm SST anomalies are generated in the eastern equatorial Pacific in boreal spring and propagate westward in boreal summer. Consistent westward propagation is seen in precipitation, surface wind, and ocean current. For the stationary near-annual mode, warm SST anomalies develop near the date line in boreal winter and decay locally in boreal spring. Westward propagation of warm SST anomalies also appears in the developing year of the biennial ENSO mode. However, warm SST anomalies for the westward propagating near-annual mode occur about two months earlier than those for the biennial ENSO mode and are quickly replaced by cold SST anomalies, whereas warm SST anomalies for the biennial ENSO mode only experience moderate weakening.
Anomalous zonal advection contributes to the generation and westward propagation of warm SST anomalies for both the westward propagating near-annual mode and the biennial ENSO mode. However, the role of mean upwelling is markedly different. The mean upwelling term contributes to the generation of warm SST anomalies for the biennial ENSO mode, but is mainly a damping term for the westward propagating near-annual mode. The development of warm SST anomalies for the stationary near-annual mode is partially due to anomalous zonal advection and upwelling, similar to the amplification of warm SST anomalies in the equatorial central Pacific for the biennial ENSO mode. The mean upwelling term is negative in the eastern equatorial Pacific for the stationary near-annual mode, which is opposite to the ENSO mode.
The development of cold SST anomalies in the aftermath of warm SST anomalies for the westward propagating near-annual mode is coupled to large easterly wind anomalies, which occur between the warm and cold SST anomalies. The easterly anomalies contribute to the cold SST anomalies through anomalous zonal, meridional, and vertical advection and surface evaporation. The cold SST anomalies, in turn, enhance the easterly anomalies through a Rossby-wave-type response. The above processes are most effective during boreal spring when the mean near-surface-layer ocean temperature gradient is the largest. It is suggested that the westward propagating near-annual mode is related to air–sea interaction processes that are limited to the near-surface layers.
1. Introduction
Tropical Pacific sea surface temperature (SST) anomalies display a variety of time scales. In addition to the dominant El Niño–Southern Oscillation (ENSO), there is variability on quasi-biennial (Ropelewski et al.
Corresponding author address: Dr. Renguang Wu, Center for Ocean–Land–Atmosphere Studies, 4041 Powder Mill Rd., Suite 302, Calverton, MD 20705. E-mail: [email protected]
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1992), decadal (Tourre et al. 1999), and near-annual (Jin et al. 2003) time scales. In particular, the near- annual time scale variability contributes to some minor El Niño and La Niña events (Jin et al. 2003; Kang et al. 2004). Documenting the evolution and physics of the near-annual variability has implications for understanding the tropical Pacific SST anomalies.
Previous empirical and modeling investigations have suggested near-annual variability of SST in the equatorial Pacific. Based on analyses using the National Cen- ters for Environmental Prediction (NCEP) ocean as- similation dataset (Ji et al. 1995), Jin et al. (2003) pointed out that there is significant variability on 12– 18-month time scales for SST in the region of 2°S–2°N, 170°–120°W. Some fairly regular and nearly annual variability appears in the equatorial Pacific after the major 1997/98 El Niño event and fluctuations with similar time scales also occurred between all the major El Niño events (Jin et al. 2003; Kang et al. 2004). SST and wind stress exhibit westward propagation in the equatorial Pacific at this time scale. The equatorial zonal current at 140°W and 10 m derived from current meter moorings displays a strong annual peak during 1985–89 (Perigaud and Dewitte 1996). Near-annual and subannual variability has been identified in the Zebiak–Cane coupled model (Zebiak and Cane 1987). Jin et al. (2003) showed evidence for the near-annual variability of SST, zonal wind, zonal current, and thermocline depth in the equatorial Pacific with a strong westward propagating tendency in a long-term simulation of the Zebiak–Cane coupled model. Westward propagation of equatorial Pacific SST and surface zonal wind stress anomalies is also found at subannual time scales with a period of about 9 months (the so-called mobile mode: Zebiak 1985; Mantua and Battisti 1995). In a simulation using the Zebiak–Cane coupled model, Perigaud and Dewitte (1996) found that the SST changes in the equatorial central Pacific are dominated by a 9-month oscillation, which corresponds to the oscillation of the simu- lated anomalous zonal currents that show obvious westward propagation. In examining the temporal evolution along the equatorial Pacific in the Center for Ocean– Land–Atmosphere Studies (COLA) interactive ensemble coupled general circulation model (CGCM) (Kirtman and Shukla 2002), we identified obvious westward propagating SST, rainfall, and surface wind stress anomalies on near-annual time scale. Understanding the near-annual variability in the CGCM in comparison with that in observations and even the Zebiak–Cane model may ultimately lead to improved climate prediction.
Previous studies indicate that the physical processes important to the near-annual variability or the mobile
mode are fundamentally different from those control- ling ENSO. For ENSO, the thermocline feedback is primary for both the growth and transition phase, and the zonal advective feedback plays a secondary role (Jin and An 1999; An and Jin 2001). For the near- annual or mobile mode, anomalous zonal advection plays a dominant role for SST anomalies (Mantua and Battisti 1995; Jin et al. 2003; Kang et al. 2004). The anomalous zonal advection serves not only as a growth term but also as a phase transition mechanism (Jin et al. 2003; Kang et al. 2004). The anomalous upwelling is important for the genesis of SST anomalies in the eastern Pacific (Mantua and Battisti 1995; Kang et al. 2004). The mean upwelling acts as strong damping for SST anomalies in the mobile mode (Mantua and Battisti 1995).
The near-annual variability is especially active during the cold phase of the ENSO cycle when intensified zonal surface currents and larger zonal SST gradients allow for more intense zonal SST advection, although it can exist independently of the ENSO cycle (Mantua and Battisti 1995; Jin et al. 2003). The fast (i.e., near annual) and slow (i.e., interannual) modes also coexist in more complex models (Neelin 1990; Philander et al. 1992). The interaction between the mobile mode and ENSO is a cause for the irregularity of ENSO in the Zebiak–Cane coupled model (Mantua and Battisti 1995). Thus, understanding the occurrence of this mode may have implications for ENSO prediction.
In analyzing the output of the COLA interactive ensemble CGCM, we found that the model displays both ENSO and near-annual variability in the equatorial Pa- cific. There are two types of near-annual variability. In the first type, the warm phase appears in boreal spring in the eastern Pacific and propagates westward to the central and western Pacific in boreal summer and fall. In the second type, warm SST anomalies develop near the date line in boreal winter and decay locally. These two types appear to be similar to the westward propagation and intensifying period of the model’s canonical ENSO. Identifying the mechanisms for the westward propagation and the local decay of SST anomalies in the near-annual variability, which is the main focus of this study, would be helpful for understanding the development and propagation of ENSO anomalies in the model. The spatial structure and temporal evolution of the near-annual westward propagating SST and wind stress anomalies along the equatorial Pacific in the model has similarities with observations as documented in previous studies (e.g., Jin et al. 2003). Thus, understanding the physical processes associated with this study may help diagnose and predict ENSO events in observations.
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The organization of the rest of the paper is as follows. In section 2, we describe the coupled model. The evidence for the three modes (one biennial ENSO and two near-annual modes) in the coupled model is presented in section 3. Section 4 describes the spatial structure and temporal evolution of the three modes. A budget analysis of the ocean mixed layer temperature is performed in section 5 in order to understand the processes for the generation and evolution of SST anomalies in the near-annual modes and differences from the biennial ENSO mode. Section 6 discusses the long-term tendency of the frequency of near-annual modes, impacts of ENSO phase on the near-annual modes, impacts of the near-annual variability on the irregularity of ENSO, and the trigger for the near-annual modes. Section 7 summarizes the main results.
2. The coupled model
This study use outputs from a long-term integration of the COLA interactive ensemble CGCM (Kirtman and Shukla 2002). The atmospheric component is the COLA global spectral atmospheric general circulation model (AGCM) with a horizontal resolution of T42 (about 2.8° 2.8°) and 18 unevenly spaced vertical levels (Kinter et al. 1997). The ocean component is ver- sion 3 of the Geophysical Fluid Dynamics Laboratory (GFDL) modular ocean general circulation model (OGCM MOM3: Pacanowski and Griffies 1998), which has 25 vertical levels. The longitudinal resolution of the ocean model is 1.5°. The latitudinal resolution changes from 0.5° within 10°S–10°N to 1.5° in the extratropics. The thickness is 15 m for the top 9 layers and increases to 900 m for the lowest layer.
The CGCM employs an anomaly coupling strategy (Kirtman et al. 1997, 2002) as follows. The atmosphere and ocean models exchange anomalies of heat, momentum, and freshwater fluxes, which are computed with respect to their own model climatology. The climatology upon which the anomalies are superim- posed is specified by observations. The ocean model climatology is determined from an uncoupled extended integration with observed momentum flux and surface relaxation of temperature and salinity to observations after a 50-yr spinup in the same way using the observed climatology. The atmosphere model climatology is determined from a multidecadal simulation with specified observed SST. The models are coupled once a day, exchanging daily mean fluxes and SST.
The CGCM further employs an interactive ensemble coupling strategy (Kirtman and Shukla 2002) with six realizations of the COLA AGCM coupled to one real-
ization of the GFDL MOM3 OGCM. The six atmospheric realizations only differ in terms of their initial conditions. Each atmospheric realization experiences the same SST produced by the ocean model. The ocean model is subjected to the ensemble average of fluxes of heat, momentum, and freshwater from the six atmospheric realizations. The interactive ensemble coupling technique reduces the impacts of atmospheric internal dynamics on the fluxes at the air–sea interface and thus facilitates the detection of coupled atmosphere–ocean signals (Wu and Kirtman 2003; Yeh and Kirtman 2004). The coupled model has been integrated over a period of more than 900 years with no flux adjustments applied other than the anomaly coupling. In the first 400 years of the model integration, the SST and heat content (the average temperature for the upper 300 m) in the equatorial central Pacific has a cooling trend of about 0.1°C and 0.2°C (100 yr)1, respectively. After that, there is no apparent trend.
The model performance has been evaluated with respect to SST observations (Reynolds and Smith 1994) for the mean, annual cycle, and ENSO behavior in previous studies (Kirtman et al. 2002; Kirtman and Shukla 2002; Wu and Kirtman 2003). The mean equatorial Pa- cific SST is lower than observations by 0.5°–1.0°C and the cold tongue is too strong and extends too far to the west (Kirtman et al. 2002; Wu and Kirtman 2003). The SST annual cycle in the equatorial Pacific agrees gen- erally well with observations (Kirtman et al. 2002) since this is largely prescribed in the anomaly coupling strategy. The model ENSO is biased to the biennial time scale (Kirtman and Shukla 2002; Wu and Kirtman 2004). The ENSO SST anomalies are somewhat weaker and extend too far to the west compared to observations (Kirtman et al. 2002; Wu and Kirtman 2003). The global teleconnection associated with ENSO is cap- tured quite realistically by the model (Kirtman and Shukla 2002).
3. The three anomalous SST modes
Equatorial Pacific SST anomalies display both interannual and near-annual variability during the long-term integration of the coupled model. To provide evidence for the near-annual SST variability, we display in Fig. 1 the time series of SST anomalies averaged over the region of 2°S–2°N, 170°E–170°W for three periods. This region is chosen because the near-annual variability is the most pronounced in this region. The three episodes are selected as examples for the three different SST events. Similar temporal evolutions as those in Fig. 1 are present in other periods. The evolution in the three selected periods is relatively regular and thus is
convenient as a sample for the composite analysis. The results based on these periods are representative of general results of the model simulation.
Near-annual variability is prominent for the period of model years 2053–56 during which warm SST anomalies recur every year (Fig. 1a). The warm SST anomalies peak in boreal summer and are followed by cold SST anomalies, which reach their largest amplitude around the end of the year. Near-annual variability is also obvious for the period of 2615–20 during which warm SST anomalies appear in the beginning of each year, though the amplitude of the SST anomalies changes from year to year (Fig. 1c). These warm SST anomalies are usually followed by a cooling in the same year. Apparent biennial variability is seen for the period of 2115–28 during which the model shows alternating warm and cold events every other year (Fig. 1b). Note that the data for January 2122 were lost during the postprocess- ing of the model output. The warm SST anomalies peak in the beginning of the year as in Fig. 1c. There is a secondary peak in the preceding summer and fall. These secondary peaks are similar to those in Fig. 1a.
The three types of variability are further demon-
strated using Fig. 2, which shows Hovmöller diagrams along the equator (2°S–2°N average). During the period of 2053–56, near-annual variability dominates (Fig. 2a). Westward propagation of warm SST anomalies is apparent in the equatorial central Pacific during the middle of the year, followed by cold SST anomalies that also propagate westward in the same year. Prominent near-annual variability is also seen during the period of 2615–20 (Fig. 2c). Warm SST anomalies appear near the date line every year, and weak or moderate cold SST anomalies are seen between warm SST anomalies. During the period of 2115–28, biennial variability dominates (Fig. 2b). Large warm and cold SST anomalies appear in the equatorial central Pacific every other year. The warm SST anomalies propagate eastward to coastal South America within a few months. This dif- fers from the period of 2615–20 during which the warm SST anomalies decay locally in the equatorial central Pacific. Before the peak of warm SST anomalies, we see westward propagating warm SST anomalies similar to those seen in the period of 2053–56. These warm SST anomalies correspond to the secondary peak seen in Fig. 1b. In contrast, the warm anomalies are followed
FIG. 1. SST anomalies (°C) averaged over the region of 2°S–2°N, 170°E–170°W for the Jan to Jan period of (a) 2051–61, (b) 2111–31, and (c) 2611–21. Shading highlights the periods during which the same type of variability recurs and for which the composite is made. The vertical dashed lines denote the time of Jul in (a) and Jan in (b), (c).
by cold anomalies in Fig. 2a, but only show moderate weakening in Fig. 2b.
The evolution of SST anomalies discussed above indicates that the coupled model simulates both biennial and near-annual time scale variability. The SST anomalies on the biennial time scale consist of a westward propagating phase, an amplification phase in the equatorial central Pacific, and an eastward propagation phase. The two types of near-annual variability are similar to the westward propagating phase and the local amplification stage of the biennial variability, respectively. Distinct from the biennial variability, however, warm SST anomalies associated with the westward
propagating near-annual variability are followed immediately by large cold SST anomalies that propagate westward as well, and those in the stationary near- annual variability decay quickly and do not propagate to the eastern equatorial Pacific.
Near-annual variability as those in Figs. 1 and 2 but with opposite warm–cold anomalies is also identified in the model simulation. For distinguishing, the SST anomalies as Figs. 1 and 2 are called warm events and those opposite to Figs. 1 and 2 are called cold events. The spatiotemporal evolution for the cold events is ba- sically opposite to the corresponding warm events and thus the present study only documents the warm
FIG. 2. As in Fig. 1 but for SST anomalies along the equator (2°S–2°N average). The contour interval is 0.2°C with dashed contours for negative values.
events. These near-annual warm and cold events recur during the model integration. The power spectrum for SST anomalies averaged over the region of 2°S–2°N, 170°E–170°W (not shown here) displays a significant peak around a 12-month period. The near-annual varia- tion for SST anomalies in the above region, as extracted by a bandpass filter with the half-amplitude response at 8 and 16 months, accounts for about 10% of the total variance. In view of its recurrence with specific spatiotemporal structure, in the following we term the near-annual variability in Figs. 1a and 2a as the westward propagating near-annual mode, the near-annual variability in Figs. 1c and 2c as the stationary near- annual mode, and the biennial variability in Figs. 1b and 2b as the biennial ENSO mode.
Near-annual equatorial Pacific SST variability also appears in the anomaly coupled model with only a single realization of the AGCM and, thus, is not specific to the interactive ensemble coupling strategy. The interactive ensemble coupling approach is designed to reduce the noise level and increase the percent variance explained by the signal. This approach improves the simulation of the large-scale SST anomaly pattern associated with ENSO in the tropical Indian Ocean and the extratropical Pacific Ocean and the Indian summer monsoon–ENSO relationship (Kirtman and Shukla 2002). Preliminary analyses indicate that the near- annual variability in the anomaly coupled model has a spatiotemporal structure similar to that in the interactive ensemble coupled model. This study only present results from the interactive ensemble coupled model that has a much longer integration, which facilitates the discussion of the long-term change of the near-annual variability.
The results presented Figs. 1 and 2 raise several questions:
• What processes lead to the westward propagation of warm SST anomalies during the periods of 2053–56 and 2115–28?
• What generates the cold SST anomalies in the aftermath of warm SST anomalies during the period of 2053–56?
• What limits the eastward propagation of warm SST anomalies during the period of 2615–20?
To answer these questions, we compare the spatial structure and temporal evolution and perform an ocean budget analysis for all three modes in the following two sections.
4. The spatial structure and temporal evolution
As seen in Figs. 1 and 2, the SST anomaly evolution is quite similar within each of the three periods. As
such, a composite with respect to the calendar month for each of the three periods is calculated in order to diagnose the spatial and temporal evolution of the three modes. For the westward propagating near- annual mode, the anomalies in the 4-yr period (2053– 56) are averaged to obtain the composite. For the stationary near-annual mode, the anomalies in the 6-yr period (July 2614–June 2620) are averaged. For the biennial ENSO mode, the anomalies in the period of 2115–28 except for the lost model output for January 2122 are averaged every other year. In the following, we first describe the structure and evolution for the biennial ENSO mode. Then, we document the structure and evolution for the annual modes and compare these to the biennial ENSO mode.
a. The biennial ENSO mode
The temporal evolution of SST, precipitation, surface wind stress, heat content, and surface ocean current anomalies along the equator (2°S–2°N average) for the biennial ENSO mode is shown in Fig. 3. The model El Niño peaks around January in the equatorial central Pacific (Fig. 3a). The evolution of warm SST anomalies consists of three stages: a westward propagation of moderate SST anomalies during summer and fall, amplification in the equatorial central Pacific around De- cember, and an eastward propagation in boreal winter and the following spring. The evolution of rainfall anomalies (Fig. 3b) is consistent with that of SST anomalies. Westerly and easterly wind anomalies develop to the west and east of the warm SST anomalies, respectively. These wind anomalies propagate with the SST and rainfall anomalies. Positive heat content anomalies precede warm SST anomalies during the amplification and eastward propagation periods, but they lag warm SST anomalies during the westward propagation period (Fig. 3c). Eastward propagating positive heat content anomalies are also seen in the western and central equatorial Pacific prior to the development of westward propagating warm SST anomalies. Obvious propagation is also seen in the ocean surface current anomalies (Fig. 3c), consistent with that of heat content anomalies. Eastward surface current anomalies lie over the warm SST anomalies.
The spatiotemporal evolution for the biennial ENSO mode is further demonstrated in Fig. 4, which shows the two-dimensional structure of SST, precipitation, surface wind stress, heat content, and surface ocean current anomalies every other month. In March, cold SST anomalies are centered on the equator. The spatial structure and temporal evolution indicates that the heat content anomalies feature a reflected downwelling
Kelvin wave from the western boundary in association with eastward surface current anomalies. In May, weak warm SST anomalies appear in the eastern equatorial Pacific when the downwelling Kelvin wave arrives. At this time, eastward surface current anomalies cover the entire equatorial Pacific with the largest in the eastern equatorial Pacific. It appears that both the thermocline change and the anomalous zonal advection contribute to the development of warm SST anomalies in the eastern equatorial Pacific as will be shown later. At the same time, low-level wind convergence starts to develop above warm SST anomalies.
From May to July, the warm SST anomalies intensify and move westward along the equator, accompanied by westward migration of the low-level convergence and eastward ocean surface current anomalies. The heat content changes are relatively small during this period. From July to November, warm SST anomalies mainly propagate westward with little change in amplitude. The surface wind and ocean current anomalies propagate westward in the equatorial Pacific and westerly wind and eastward ocean current anomalies amplify at
the same time. Relatively large heat content anomalies near the equator also appear to move westward.
Eastward propagation and strong amplification in SST, wind, heat content, and ocean current anomalies appear from November to January. This propagation is preceded by a strong intensification of westerly wind and eastward ocean current anomalies in the western equatorial Pacific, and a strong deepening of thermocline in the equatorial central Pacific. In the western equatorial Pacific, the heat content anomalies also change sign.
After January, warm SST anomalies decay and ex- pand eastward, as do the surface wind anomalies. In the western equatorial Pacific, ocean current anomalies reverse corresponding to the change in the structure of heat content anomalies. At this time, large warm SST anomalies appear along coastal South America, which corresponds to the arrival of large positive heat content anomalies and accompanying eastward ocean current anomalies. In the following May, SST and wind anomalies further weaken, and ocean current anomalies reverse in the eastern equatorial Pacific.
FIG. 3. (a) Composite SST (°C), (b) precipitation (mm day1) and surface wind stress (dyn cm2), and (c) heat content (°C) and surface ocean current (cm s1) along the equator (2°S–2°N average) for the period of Jan 2115–Dec 2128. The contour interval is 0.2°C for SST, 0.6 mm day1 for precipitation, and 0.2°C for heat content. The scales for the wind stress and ocean current are displayed at the top right of the respective panels. The heat content refers to ocean temperature averaged over the upper 300 m. The y axis is the time from 1 Jan of the first year to 24 Dec of the following year.
b. The westward propagating near-annual mode
The temporal evolution along the equator for the westward propagating near-annual mode is similarly shown in Fig. 5. The westward propagation of warm SST, above-normal precipitation, surface wind, and
ocean current anomalies is pronounced during spring and summer. The warm SST anomalies are generated in spring around 120°W (Fig. 5a). The amplitude of the SST anomalies increases as the anomalies propagate from the eastern to central Pacific, while the anomalies decay after crossing the date line. Above-normal pre-
FIG. 4. (left) Composite SST (°C) and surface wind stress (dyn cm2), and (right) heat content (°C) and surface ocean current (cm s1) for the period of Jan 2111–Dec 2128. (top to bottom) Mar, May, Jul, Sep, and Nov in the first year and Jan, Mar, and May in the following year. The contour interval is 0.2°C for SST and 0.4°C for heat content. The scales for the wind stress and ocean current are displayed at the top of the respective panels. The heat content refers to ocean temperature averaged over the upper 300 m.
cipitation and anomalous low-level convergent winds are coupled with the warm SST anomalies (Fig. 5b). The easterly anomalies appear to be much stronger than the westerly anomalies. The positive rainfall anomalies are located to the east of warm SST anomalies. The development of positive heat content anomalies in the equatorial eastern Pacific (Fig. 5c) seems to occur later than the warm SST anomalies and appears to be loosely connected with the SST evolution. The surface ocean current displays westward anomalies to
the east of warm SST anomalies and eastward anomalies over and to the west of warm SST anomalies.
Westward propagating cold SST anomalies immediately follow the warm SST anomalies (Fig. 5a). The largest cold SST anomalies are located to the south of the equator, as seen in Fig. 6, which is similar to Fig. 4 but for the westward propagating near-annual mode. The warm and cold SST anomalies form an SST couplet. A similar couplet is seen in precipitation anomalies (not shown). The strong southeasterly anomalies
FIG. 4. (Continued)
are coupled to the SST couplet, indicating that the wind anomalies are strongly related to the SST gradient. On the other hand, the southeasterly anomalies produce anomalous cold advection and anomalous upwelling (as will be shown later), which in turn favors the development of cold SST anomalies. Thus, air–sea coupling processes may be important for the westward propagating near-annual mode. We will return to this point later in the paper.
Eastward current anomalies develop in the eastern equatorial Pacific in May, consistent with positive heat content anomalies. The horizontal structure of the heat content anomalies, however, changes quickly. In July, the heat content anomalies on the equator are relatively small compared to those in the off-equatorial re- gions east of 160°W. Correspondingly, ocean current anomalies reverse in the eastern equatorial Pacific. These current anomalies propagate westward following westward propagating off-equatorial positive heat content anomalies. The latter are related to westward- propagating equatorial easterly anomalies and associated off-equatorial anticyclonic wind stress curl anomalies.
The westward propagation is seen both for the biennial ENSO mode and the westward propagating near- annual mode. However, there are important differences. First, the warm SST anomalies occur about two months earlier for the westward propagating near- annual mode than for the biennial ENSO mode (Fig. 5a versus 3a). Second, the easterly anomalies to the east of warm SST anomalies are much stronger for the near- annual mode (Fig. 5b versus 3b). Third, in association with these easterly anomalies, cold SST anomalies develop immediately following warm SST anomalies for the near-annual mode (Fig. 5a). These cold SST anomalies terminate the preceding warm SST anomalies quickly. For the biennial ENSO mode, warm
SST anomalies only experience moderate weakening (Fig. 3a). Another difference is that the above-normal rainfall anomalies lie to the east of warm SST anomalies for the near-annual mode, whereas positive rainfall and SST anomalies are collocated for the ENSO mode.
The westward propagation of SST and wind stress anomalies along the equatorial Pacific seen in the present study resembles that documented in previous studies (Mantua and Battisti 1995; Jin et al. 2003; Kang et al. 2004). Another consistent feature is that the warm SST anomalies are followed by cold SST anomalies. In comparison, the westward propagation of heat content and zonal current anomalies is obvious in our model and the Zebiak–Cane model, but not in the ocean as- similation data (Jin et al. 2003).
c. The stationary near-annual mode
The composite for the stationary near-annual mode (Fig. 7) shows warm SST anomalies near the date line and cold SST anomalies around 130°W in boreal winter (Fig. 7a). These anomalies develop and decay locally. Cold SST anomalies are also seen in the western equatorial Pacific. Overlying the warm SST anomalies are above-normal precipitation and anomalous low-level wind convergence (Fig. 7b). Negative precipitation anomalies are seen around 150°W located between warm and cold SST anomalies. The positive precipitation anomalies propagate eastward from the Mari- time Continent during boreal fall and winter. Positive heat content anomalies correspond to the warm SST anomalies (Fig. 7c). These heat content anomalies display eastward propagation in boreal winter and the following spring. However, they weaken quickly and become very weak in the eastern equatorial Pacific. East- ward propagating negative heat content anomalies are
FIG. 5. As in Fig. 3 except for the period of Jan 2053–Dec 2056.
obvious in the preceding season. Eastward surface ocean current anomalies also display eastward propagation in the western and central equatorial Pacific (Fig. 7c).
The structure of the anomalies in the mature phase of the stationary near-annual mode is similar to the biennial ENSO mode. However, there are also obvious differences from the biennial ENSO mode. First, warm SST anomalies are located farther to the west for the stationary near-annual mode compared to the biennial
ENSO mode (Fig. 7a versus 3a). Second, warm SST anomalies for the near-annual mode are not preceded by a westward propagation phase, and heat content anomalies are negative across the entire equatorial Pa- cific basin in advance of the development of the warm SST anomalies (Fig. 7c). Third, the SST anomalies for the near-annual mode are weaker and more localized and cannot propagate to the eastern equatorial Pacific. This is related to the weak heat content anomalies present in the eastern equatorial Pacific.
5. Budget analysis
To understand the physical processes associated with the SST anomaly evolution for the three modes, we performed a budget analysis for the ocean mixed layer. In the figures, we show the SST tendency, which is equivalent to the mixed layer temperature tendency. In the following, we discuss the contribution of different terms to the SST tendency.
a. The biennial ENSO mode
Previous studies have demonstrated that for the ENSO the thermocline feedback plays a primary role in both the growth and phase transition, whereas the zonal advective feedback is secondary (e.g., Jin and An 1999; An and Jin 2001). Figure 8 shows composite SST tendency (calculated using centered differencing), surface heat flux (negative indicating cooling of the ocean surface), and mixed layer mean advection terms for the biennial ENSO mode. The heat budget is done based on monthly mean model output and then a composite is made. The mixed layer depth is determined by a local temperature difference of 0.5°C, following previous studies (e.g., Monterey and Levitus 1997). The nonlin- ear advection terms are usually small and are not shown. For simplicity, in the following discussions, the anomalous horizontal (vertical) advection of mean temperature gradient is referred to as anomalous advection (upwelling), and the advection of anomalous temperature gradient by mean horizontal current (vertical mo- tion) is referred to as mean advection (upwelling).
For the biennial ENSO mode, the most important budget terms are anomalous zonal advection and mean upwelling. The anomalous zonal advection term (Fig. 8b) dominates in the central and western Pacific. In the eastern Pacific, the mean upwelling term (Fig. 8g) is the
largest. This is broadly consistent with Huang and Schneider (1995) whose budget analysis showed that the El Niño development in an OGCM is mainly due to the anomalous zonal advection in the west, the mean meridional advection in the central, and the displace- ment of thermocline in the east Pacific. The mean meridional advection term (Fig. 8f) contributes in the eastern Pacific, especially for the coastal warming during the spring in the decaying year. Anomalous vertical advection (Fig. 8d) has a nontrivial contribution to the amplification of warm SST anomalies in the equatorial central Pacific and for the coastal warming. The surface heat flux term (Fig. 8a) tends to be out of phase with SST anomalies, and thus mainly serves as a damping term.
The development of westward propagating warm SST anomalies has significant contributions from both mean upwelling and anomalous zonal advection. The westward propagation and the amplification in the equatorial central Pacific occur largely due to anomalous zonal advection. The eastward propagation has significant contributions from mean upwelling and anomalous zonal advection. The role of anomalous zonal advection for the amplification and eastward propagation of warm SST anomalies is consistent with Picaut et al. (1997), who suggested that the anomalous zonal advection could be responsible for the origin of ENSO.
b. The westward propagating near-annual mode
For the westward propagating near-annual mode, most of the terms contribute to the SST tendency in different stages. The generation of warm SST anomalies in the eastern equatorial Pacific is due to anomalous zonal advection (Fig. 9b) and anomalous upwelling (Fig. 9d). These two terms also contribute to the westward propagation of the warm SST anomalies. An ad-
FIG. 7. As in Fig. 3 except for the period of Jul 2614–Jun 2620 with the time starting from Jul (5) of the first year to Jun (6) of the following year.
ditional contribution comes from the surface heat flux (Fig. 9a). The generation of cold SST anomalies in the eastern Pacific is due to anomalous upwelling (Fig. 9d), surface heat flux (Fig. 9a), anomalous meridional advection (Fig. 9c), and anomalous zonal advection (Fig. 9b). The westward propagation of cold SST anomalies is due to anomalous zonal advection, anomalous meridional advection, anomalous upwelling, mean zonal advection (Fig. 9e), and surface heat flux. The mean upwelling term (Fig. 9g) acts to damp the SST anomalies.
The results of the heat budget for the westward propagating near-annual mode are consistent with previous studies (Hirst 1986; Mantua and Battisti 1995; Jin et al. 2003; Kang et al. 2004). Agreement is found in the important role of anomalous zonal advection for the growth and westward propagation of SST anomalies, the role of the anomalous upwelling for the genesis of SST anomalies in the eastern Pacific, and the role of mean upwelling as a damping term. Note that the anomalous meridional advection was neglected in previous studies (Mantua and Battisti 1995; Kang et al. 2004).
The main processes contributing to the SST tendency for the westward propagating near-annual mode have similarities and differences compared with those attrib- uted to the biennial ENSO mode. The anomalous zonal advection contributes to the generation and westward propagation of warm SST anomalies for both the ENSO mode and the near-annual mode. However, the role of mean upwelling is very different. For the ENSO mode the mean upwelling term has a positive contribution to the generation of warm SST anomalies (Fig. 8g), whereas for the near-annual mode the mean upwelling is mainly a damping term (Fig. 9g).
Westward propagating warm SST anomalies for the biennial ENSO mode are only subjected to a moderate weakening (Fig. 3a), whereas for the westward propagating near-annual mode they are replaced quickly by cold anomalies (Fig. 5a). We note that the anomalous upwelling term is negative and large for the near- annual mode (Fig. 9d), but not for the ENSO mode (Fig. 8d). The anomalous zonal and meridional advection terms are also larger for the near-annual mode than for the ENSO mode (Figs. 8b,c versus 9b,c). These differences are linked to easterly wind anomalies in the eastern equatorial Pacific, which are much stronger for the near-annual mode than for the ENSO mode (Fig. 3b versus 5b). The strong easterly wind anomalies induce large anomalous upwelling to the east of warm SST anomalies (Fig. 9d). The large easterly anomalies along the equator are associated with anticyclonic wind stress curl off the equator (Fig. 6, May–September), which deepens the thermocline off the equator. This
induces anomalous westward ocean current along the equator (Fig. 6, July–September). As a result, large anomalous zonal and meridional advection develops for the near-annual mode (Figs. 9b,c). These terms overcome the mean upwelling (Fig. 9g) and lead to cold SST anomalies. The surface heat flux term (Fig. 9a) also contributes, related to an enhanced surface evaporation induced by large easterly anomalies between the warm and cold SST anomalies. The eastward location of above-normal rainfall anomalies relative to warm SST anomalies for the near-annual mode (Figs. 5a,b) also contribute to negative surface heat flux anomalies through cloud–radiation feedback.
The anomalous advection and upwelling terms are most effective in boreal spring when the mean near- surface–layer ocean temperature gradient is large. This is demonstrated in Figs. 10a,b, which show the annual cycle of the mean SST. In boreal spring, the eastern equatorial Pacific SST is the warmest. The zonal SST gradient is the largest in the eastern equatorial Pacific (to the east of the warm SST anomalies, Fig. 10a). The region of negative meridional SST gradient is closest to the equator in the eastern tropical Pacific (Fig. 10b). In association with the warmest SST, the mean zonal wind stress is weakest at this time (Fig. 10c). Correspond- ingly, the vertical mixing is also the weakest. This increases the vertical temperature gradient in the upper ocean (Fig. 10d). All of these factors favor the contribution of anomalous zonal, meridional, and vertical advection of the background ocean temperature gradient to the SST tendency.
Based on our analysis of the westward propagating near-annual mode and the biennial ENSO mode, we suggest that the critical difference is most apparent during May through July. For example, during July, the two modes have comparable warm SST anomalies near the equator but the near-annual mode has considerably stronger cold SST anomalies to the southeast of the warm SST anomalies. Consistent with these stronger cold SST anomalies are stronger easterly wind anomalies occurring between the warm and cold SST anomalies, presumably through a Rossby-wave-type response to the SST anomalies (Matsuno 1966; Gill 1980). Fur- thermore, the enhanced low-level convergence is consistent with the enhanced rainfall during this period. The stronger easterlies associated with the westward propagating near-annual mode enhance the local SST cooling through enhanced evaporation (Fig. 9a), stronger upwelling of cold water (Fig. 9d), and cold advection from the southeast (Figs. 9b,c). These local feedbacks weaken or even reverse the SST anomalies, ultimately inhibiting the development of a warm ENSO event. It appears that surface air–sea interaction pro-
cesses dominate the difference between the biennial ENSO mode and the westward propagating near- annual mode during the May–July time frame.
Why are surface easterly anomalies and cold SST anomalies to the southeast of the warm SST anomalies stronger for the westward propagating near-annual mode than for the biennial ENSO mode? We are un- able to answer this question at this point; however, we speculate that random or stochastic atmospheric processes may play a key role in the excitation of the westward propagating near-annual mode versus the biennial ENSO mode. Indeed, our search for some mode select- ing “precursors” in, for example, the heat content has failed. The differences are largely in surface processes, and we have not found consistent triggering mechanisms. This, perhaps, suggests the role of stochastic processes as a trigger, whereas local air–sea feedbacks lead to the amplification of the anomalies.
c. The stationary near-annual mode
For the stationary near-annual mode, the development of warm SST anomalies near the date line is due to anomalous zonal advection and upwelling terms (Figs. 11b,d). The mean upwelling term (Fig. 11g) is negative in the eastern Pacific, which limits the eastward propagation of warm SST anomalies. The surface heat flux (Fig. 11a) is mainly a damping term.
Compared to the biennial ENSO mode, the SST tendency in the equatorial central Pacific is smaller and lying to the west for the stationary near-annual mode (Fig. 11a versus 8a). This is related to the weaker zonal current and upwelling anomalies. Weaker anomalous zonal advection and upwelling are also linked to smaller zonal and vertical gradients of mean ocean temperature in the western compared to the central equatorial Pacific. Another difference from the biennial
FIG. 8. Composite SST tendency (shading, °C month1): (a) surface heat flux (heatf, °C month1), (b) anomalous zonal advection (UadxTm), (c) anomalous meridional advection (VadyTm), and (d) anomalous vertical advection (WadzTm) of mean temperature gradient, (e) mean zonal advection (UmdxTa), (f) mean meridional advection (VmdyTa), and (g) mean vertical advection (WmdzTa) of anomalous temperature gradient along the equator (2°S–2°N average) for the period of Jan 2115–Dec 2128. The advection terms (°C month1) are averages for the mixed layer, defined by a local temperature difference of 0.5°C. The contour interval for heat flux and advection terms is 0.2°C month1. The y axis is the time from 1 Jan of the first year to 24 Dec of the following year.
Fig 8 live 4/C
ENSO mode is that the mean upwelling term is negative in the eastern equatorial Pacific (Fig. 11g). This is related to negative heat content anomalies (Fig. 7c), which is unfavorable for the eastward propagation of warm SST anomalies.
6. Discussion
The frequency of occurrence for warm and cold events of near-annual modes shows apparent long-term change based on an examination of the temporal evolution of SST anomalies averaged over the region of 2°S–2°N, 170°E–170°W. The warm events of the westward propagating near-annual mode and the cold events of the stationary near-annual mode are more frequent in the earlier part of the 900-yr simulation, whereas the opposite occurs during the later period. We suspect that these tendencies are related to the mean-state change in the model. One important long- term change occurring during the model simulation is
the decrease of heat content across the tropical Pacific. We note that one unfavorable term for the generation of SST anomalies in the westward propagating near- annual mode is the mean upwelling. For the warm (cold) events associated with the westward propagating near-annual mode, the effect of this term increases (decreases) when the heat content decreases. This would lead to a less (more) frequent occurrence of westward propagating warm (cold) events in the later period of the model. For the stationary near-annual mode, the mean upwelling term has the role of limiting the eastward propagation of warm SST anomalies. Lower heat content would enhance this role, thus in- creasing the occurrence of stationary warm events in the later period. For the stationary cold events, lower heat content would increase the likelihood of cold SST anomaly amplification and eastward propagation, which could turn into La Niña events. As such, the occurrence for the stationary cold events shows a decreasing trend.
FIG. 8. (Continued)
Fig 8 live 4/C
An apparent long-term trend is also seen in the frequency of occurrence for El Niño and La Niña events. El Niño events are more frequent in the early period, whereas La Niña events are frequent in the later period. We speculate that this trend is related to the decreasing trend of heat content in the tropical Pacific.
The anomalous zonal advection contributes to the generation and westward propagation of warm (cold) SST anomalies preceding El Niño (La Niña). The magnitude of the anomalous zonal advection depends on the zonal gradient of mean temperature. As such, the mean state change may affect the strength of westward propagating SST anomalies. If these westward propagating SST anomalies are considered to occur on the El Niño and La Niña background, then the magnitude of these SST anomalies may differ between El Niño and La Niña. Examination of filtered time series of equatorial central Pacific SST anomalies around the annual frequency indicates that these SST anomalies are stron-
ger when they occur before La Niña than before El Niño. This is consistent with previous studies (Mantua and Battisti 1995; Jin et al. 2003; Kang et al. 2004). These studies suggest that the La Niña state enhances the zonal SST gradient and, thus, the effect of anomalous zonal advection, which ultimately favors the development of stronger SST anomalies.
The presence of near-annual modes enriches the SST variability in the equatorial Pacific. The stationary near-annual mode is relevant to an aborted ENSO event and can become a “mini-ENSO” if the SST anomalies attain sufficient magnitude. Further, the westward propagating SST anomalies preceding El Niño and La Niña contribute to the irregularity of ENSO. We speculate that this may make prediction of ENSO more difficult. The westward propagating SST anomalies and associated wind anomalies also play an important role for the amplification of SST anomalies in the equatorial central Pacific. Note that there is a substantial intensification of rainfall and westerly
Fig 9 live 4/C
anomalies in the western equatorial Pacific when warm SST anomalies arrive (Figs. 3, 4). This intensification is related to a higher mean SST in the western Pacific. These westerlies deepen the thermocline and enhance eastward warm advection and anomalous downwelling (Fig. 9). These contribute to the amplification of warm SST anomalies.
For the stationary near-annual mode, no preceding westward propagating SST anomalies are seen (Fig. 7a). Warm SST anomalies develop quickly near the date line, similar to the amplification of warm SST anomalies for the biennial ENSO mode. What is the trigger for the stationary mode? We speculate that the large precipitation anomalies seen in November over the Maritime Continent (Fig. 7b) move eastward to 150°E in December. In association, westerly anomalies develop and deepen the thermocline (Figs. 7b,c), which drives eastward warm advection and anomalous downwelling (Figs. 11b,d). This ultimately leads to the development of warm SST anomalies that, in turn, feed back on the atmosphere, resulting in further growth of wind and SST anomalies.
7. Summary
The COLA interactive ensemble coupled model displays multiple time scale variability in the equatorial Pacific. In addition to the biennial ENSO mode, there are two near-annual modes: a westward propagating mode and a stationary mode. In the westward propagating near-annual mode, the SST anomalies are generated in the eastern equatorial Pacific in boreal spring and propagate westward during boreal summer and fall. Consistent westward propagation is found in the wind, precipitation, and ocean surface current anomalies. In the stationary near-annual mode, SST anomalies develop in boreal winter near the date line and decay locally during the following spring. These near-annual modes may contribute to the irregularity of ENSO. Un- derstanding the mechanism for the near-annual variability may advance our understanding of the irregularity of ENSO and lead to improved ENSO prediction. The spatiotemporal evolution of the westward propagating near-annual mode has important similarities with observations. The stationary near-annual mode resembles some observed aborted ENSO events that fea-
FIG. 10. Climatological annual cycle of SST (°C) along (a) the equator (2°S–2°N average) and (b) along 130°–110°W, (c) zonal wind stress (dyn cm2) along the equator (2°S–2°N average), and (d) change of ocean temperature (°C) with depth (m, y axis) averaged over the region of 2°S–2°N, 130°–110°W.
ture weak–moderate SST anomalies near the date line developing and decaying locally. Understanding the physical processes associated with this study may help diagnose and predict aborted ENSO events in observations.
The warm SST anomalies in the westward propagating near-annual mode resemble those occurring in the westward propagation phase of the biennial ENSO mode. The anomalous zonal advection acts as a major mechanism for the generation and westward propagation of warm SST anomalies. By comparison to the biennial ENSO mode, the warm SST anomalies for the westward propagating near-annual mode occur two months earlier and are followed immediately by cold SST anomaliesthat propagate westward as well. In association, the easterly anomalies lying to the east of warm SST anomalies are much stronger. The mean upwelling is a damping term for the westward propagating near-annual mode, but contributes to the generation of warm SST anomalies for the biennial ENSO mode.
For the westward propagating near-annual mode, the warm SST anomalies are accompanied by large easterly anomalies and cold SST anomalies. The spatial phase relationship and coherent westward propagation of SST and wind anomalies leads us to hypothesize that the development of cold SST anomalies in the aftermath of warm SST anomalies is associated with surface air–sea interaction processes occurring in a favorable background state. The larger easterly anomalies to the east of warm SST anomalies contribute to the development of cold SST anomalies through anomalous zonal advection, anomalous meridional advection, anomalous vertical advection, and enhanced surface evaporation. The cold SST anomalies, in turn, enhance the easterly anomalies. The larger horizontal and vertical gradients of mean near-surface-layer ocean temperature in boreal spring are favorable for easterly anomalies to induce large SST anomalies when these wind anomalies are triggered. The presence of cold SST anomalies in the southeastern tropical Pacific is also a favorable condi-
FIG. 11. As in Fig. 8 except for the period of Jul 2614–Jun 2620 with the time starting from Jul (5) of the first year to Jun (6) of the following year.
Fig 11 live 4/C
tion. However, it is unclear what triggers the above processes for the westward propagating near-annual mode.
The development of warm SST anomalies for the stationary near-annual mode is related to air–sea interaction processes resembling the amplification of warm SST anomalies for the biennial ENSO mode. Anoma- lous zonal advection and anomalous upwelling contribute to these SST changes for both modes. In comparison, the anomalies for the stationary near-annual mode are weaker and do not propagate into the eastern Pa- cific. This is related to smaller zonal and vertical gradients of mean ocean temperature in the western Pacific compared to the central Pacific. The trigger for the stationary near-annual mode may be related to anomalous heating over the far western tropical Pacific. For the biennial ENSO mode, the westward propagating SST anomalies can act as a mechanism for the amplification of SST anomalies in the equatorial central Pacific.
The applicability of the model results depends on the model performance in the mean simulation, especially differences in the mean temperature gradient and surface wind stress between the model and observations. In the eastern equatorial Pacific the difference is small for the zonal gradient of mean SST, whereas the meridional gradient of mean SST is larger and the vertical gradient of mean subsurface temperature is smaller in the model compared to observations. This indicates that the contribution of anomalous meridional advection may be larger and that of anomalous upwelling may be smaller in the model as compared to observations. The mean zonal wind stress in the tropical Pacific is weaker in the model compared to observations, indicating weaker mean upwelling. Thus, the model may underestimate the role of mean upwelling. Because the mean upwelling in the model is a favorable term for the biennial ENSO mode but an unfavorable term for the near-annual mode, this implies that the near-annual variations relative to the ENSO may account for a larger percent of the variance compared to observations.
Acknowledgments. The authors thank D. Straus for his careful reading of an earlier draft of this manuscript. The comments of two anonymous reviewers led to the improvement of this manuscript. This research was sup- ported by National Science Foundation Grants ATM- 9814295 and ATM-0122859, National Ocean and At- mospheric Administration Grant NA16-GP2248, and National Aeronautics and Space Administration Grant NAG5-11656.
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