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Gayana (Concepción)

versión impresa ISSN 0717-652Xversión On-line ISSN 0717-6538

Gayana (Concepc.) v.68 n.2 supl.TIProc Concepción  2004 


Gayana 68(2) supl. t.I. Proc. : 151-156, 2004 ISSN 0717-652X



Boris Dewitte1, Sang-Wook Yeh2, Carole Cibot3 & Laurent Terray3

1. Laboratoire d'Etude en Géophysique et Océanographie Spatiale IRD 14, Av. Edouard Belin 31401 Toulouse Cedex, France Tel: (33) 5 61 33 29 66, fax (33) 61 25 32 05
2. Center for Ocean-Land-Atmosphere Studies 4041 Powder Mill Road, Suite 302 Calverton, MD 20705 Tel (301) 595-7000, fax (301) 595-9793
3. CERFACS URA 1875, 31057 Toulouse Cedex 1, France


A 200-yr long coupled general circulation model (CGCM) simulation is used to investigate the characteristics and impact of the low frequency variability of the equatorial background stratification on the ENSO modulation. A vertical mode decomposition of the model mean vertical structure is performed and the interdecadal variability of the baroclinic mode parameters is analyzed. The low frequency variations of the baroclinic mode parameters associated to the decadal mode in the model are then used to force an intermediate coupled anomaly model "tuned" with the CGCM derived climatologies and wave parameters. Results of sensitivity experiments indicate that a rectification of the interannual variability (ENSO timescales) by the interdecadal variability associated to changes in the oceanic mean states does take place. However, the magnitude and characteristics of this rectification highly depends on the strength of the interaction between the ENSO mode and the seasonal cycle. Implications for ENSO decadal predictability is then discussed.



Although ENSO (El Niño Southern Oscillation) tends to be phase looked to the annual cycle and peaks in amplitude in the northern winter (Rasmusson and Carpenter, 1982; Thenberth, 1997), the evolution of El Niño events has changed substantially. One of the most recent striking evidence of these changes is the abrupt climate shift in the Pacific circulation centered in the Tropics that occured in the 70s (Miller et al., 1994; Trenberth and Hoar, 1996; Zhang et al., 1997). Most theories proposed to explain Pacific interdecadal variability predict oscillatory behavior that is regarded as being superimposed on random noise. Whereas, in the mid latitudes, simple climate models that treats SST as a response to random white noise forcing by the atmosphere are capable of sustaining an interdecadal variability with a realistic amplitude (Hasselmann, 1976), the recent studies place the source mechanisms for the interdecadal climate variability in the Pacific sector within the tropics. In particular, interdecadal variations occur in the same type of model that is often invoked to explain ENSO. This is the so-called delayed oscillator model that suggests that baroclinic Rossby waves propagate westward to the western boundary (with a delay of years) and reflect as equatorial Kelvin waves that switch the phase of ENSO. Generating interdecadal variations requires Rossby waves to propagate at higher latitudes than those associated to ENSO (Lysne et al., 1997; White et al., 2003) or with higher vertical baroclinic mode structures (Dewitte, 2000 ­ Hereafter D0; Liu et al., 2002). Interdecadal ENSO modulation are also possible in a linear shallow water ocean model when thermocline adjustments at midlatitudes are included (D0; Jin, 2001). Non-linear theories can also produce decadal timescales in simple models (Tziperman et al., 1995; Chang et al., 1996; Timmerman and Jin, 2002). Fundamentally all the perturbations of the tropical system can potentially lead to a change in the nature of the ocean-atmosphere coupled instabilities and therefore produce ENSO modulation (An and Jin, 2000; D0; Wang and An, 2002). The characteristics of these perturbations remains however unclear in particular with respect to the changes that they can produce on the oceanic background mean state. The difficulty to identify these characteristics is intrinsic to the coupled nature of the system: Are these changes induced by ENSO itself through changes in the characteristics of the unstable couple modes (non-linearities) or is there is a "direct" oceanic forcings from the extratropics?

As a first step towards the validation of the equatorially based models for explaining observed interdecadal variations, it appears necessary to estimate the characteristics (amplitude, spatial pattern, energy spectrum..) of the perturbations that can lead to the changes of the equatorial coupled instabilities. In this study, we focus on the low frequency perturbations (decadal to interdecadal timescales) of the ocean assuming some teleconnexions between the tropics (equator) and the extra-tropics (higher latitudes) as a source for equatorial low frequency variability. A 200-year long simulation of the state-of-the art coupled model is used. Considering the complete physics of the model and the span of the simulation, it allows accessing to realistic variations in parameters at decadal timescales, which remains difficult to obtain from the temporally and spatially limited observations. In addition, the use of a full-physics global coupled model simulation ensures that most of the coupled processes are taken into account. The simulation used for this study, was already investigated in a previous recent work (Cibot et al., 2004) with a focus on the identification of the sources of the decadal variability and its relationship with the ENSO modulation. In particular a region of relatively large decadal variability is found in the South (~8°S) Western Pacific that is apparently associated to wind stress curl forcing rather than westward-equatorward propagating variability from the South central Pacific (figure 1). Although weaker, decadal changes in thermocline depth are also present along the equator. How this decadal mode impacts the equatorial wave dynamics and lead to ENSO modulation is the focus of this paper. As a support for the interpretation, we will make use of an intermediate anomaly coupled model similar to D0 to test ideas and investigate the impact of changes in the background mean state and model parameters as derived from the CGCM simulation.

The paper is organized as follow. Section 2 is devoted to the coupled models' description. Section 3 focuses on the analysis of the decadal variability of the CGCM derived wave parameters. In section 4, the results of sensitivity experiments with the intermediate coupled model to imposed decadal forcing as derived from the CGCM outputs are presented. Section 5 is a discussion.

Figure 1: Spatial pattern of the dominant (47%) EOF mode of Tsub25 (i.e. the temperature projected on the sq=25 surface). (after Cibot et al. (2004))


ARPEGE-OPA (hereafter ARPA)

The ocean component ORCA2 is the global configuration of the OPA8 Ocean General Circulation Model (OGCM), an hydrostatic primitive equation model with a free surface formulation (Roullet and Madec, 2000). The model includes a sea-ice component, the Hibler-type dynamic-thermodynamic LLN sea-ice model, developed at the UCL in Louvain-La-Neuve by Fichefet and Morales Maqueda (1997).

The atmospheric component is the third version of the ARPEGE-Climat Atmospheric General Circulation Model (AGCM) (ARPEGE is the acronym for Action de Recherche Petite Echelle Grande Echelle: Research Project on Small and Large Scales) developed at Météo-France (Déqué et al, 1994). The standard configuration of the climate version employs a T63 triangular horizontal truncation.

The ARPEGE and ORCALIM (ORCA/Louvain Ice Model) models are coupled through the OASIS 2.5 coupler developed at CERFACS (Terray et al., 1995), which ensures the time synchronization between the GCMs and does the spatial interpolation from one grid to another.

More detail on the model configuration and variability can be found in Cibot et al. (2004).


It is a tropical Pacific ocean-atmosphere model of intermediate complexity. It is an extension of the Zebiak and Cane (1987)'s model (hereafter ZC model) in that it is based on similar physics, i.e. shallow-water for both components. The ocean component comprehends 3 baroclinic modes with characteristics of phase speed cn , projection coefficient Pn and 'thermocline coefficient' scln (used to derive the thermocline fluctuations in a multi-mode context and which depends directly on N2 and the vertical derivative of the baroclinic mode vertical structures ­ see D0 for details) derived from the Levitus data set. A mixed layer model is embedded in the ocean model that consists in a thermodynamical budget in a 50m-thick surface layer. The surface heat flux is parameterized as being negatively proportional to local SST anomalies. Subsurface entrainment temperature into the surface mixed layer is parameterized as a function of thermocline depth anomalies and mean thermocline depth (cf. Dewitte and Perigaud, 1996). The reader is invited to refer to D0, Gushchina et al. (2000) and Dewitte et al. (2002) for more details about the model and results on sensitivity tests to parameters and ENSO predictions with this model.


Following Cibot et al. (2004), a 7-yr period threshold was chosen for the low-pass filter that will be applied on the model outputs to investigate the decadal variability in ARPA. Many aspects of this variability were investigated in Cibot et al. (2004). Here, we concentrate on the equatorial vertical structure variability without trying to relate it to the off-equatorial patterns which have been described in Cibot et al. (2004).

Baroclinic mode fluctuations:

The vertical mode were calculated in a similar way than in Dewitte et al. (1999). The reader is invited to refer to this work for more technical details about the method. In order to capture the low frequency changes in the mean stratification, the vertical mode decomposition is performed at each time step from the ARPA salinity and temperature averaged over the last 200 yrs to which was superimposed the 7-yr low-pass filtered signal.

Such variations at decadal timescales of the mean equatorial vertical structure have a signature on the baroclinic mode characteristics that can be quantified through the variations of the parameters (Pn, scln). Figure 2 presents the 7-yr low-pass filtered 20°C isotherm depth anomalies along with the deviations from their mean values of the parameter Pn and scln (noted hereafter δPn and δscln) for the first three baroclinic modes. dscln was calculated at the actual depth of the thermocline, which can result in 'jumps' due to the non-linear relationship between both quantities.

From figure 2, it can be first noted that δP1(t) is anti-correlated to δP2(t) (c=-0.60) and δP3(t) (c=-0.68) whereas δPn exhibits an high correlation for mode 1 and anti-correlation for modes 1 and 2 towards variations of the 20°C isotherm depth (δD20). This traduces that a shallower (deeper) thermocline leads to a decreased (increased) contribution of the first baroclinic mode and an increased (decreased) contribution of the higher-order baroclinic modes. A different phase relationship exist between δscln and δD20: A deeper (shallower) thermocline leads to larger (smaller) value of scln for the first three baroclinic modes. This illustrate the subtle impact of the changes in stratification within the thermocline on the vertical mode structures, which could not be guessed from the relatively small variations of the mean thermocline along the equator (cf. figure 1). The maximum variations (in absolute value) of δPn (δscln) reach 10% (14%), 20% (16%) and 36% (25%) of the mean for mode 1, 2 and 3 respectively, which is about 3 times more than for cn (not shown). A closer inspection of figure 2 suggests that there is a lagged relationship between δD20 and δPn and δscln as a function of the baroclinic mode order. Thus, δD20 leads δP1 by 11 months (c=0.70) whereas minimum correlation between δD20 and δP2 and δP3 is obtained at lag 0 (c=-0.98) and ­2 (c=-0.94) month (δP3 ahead) respectively. For δscln, the phase relationship with δD20 is maximum for lag +1 (c=0.87), 0 (c=0.88) and ­2 (c=0.84) month for modes 1, 2 and 3 respectively. This again illustrates the complex nature of the processes that may transmit the decadal equatorial vertical structure variability to the ocean wave dynamics. In the forthcoming section, we will test how this impacts an intermediate coupled model variability.

Figure 2: (top) 7-yr low-pass filtered of the 20°C isotherm depth, (middle) variations in the "thermocline coefficient", dscln associated by low-frequency variations in the 20°C isotherm depth and stratification, (bottom) low frequency component of the wind projection coefficient, δPn. Units are m for the 20°C isotherm depth anomalies, 0.1 unit of scln for δscln, and 0.1 unit of Pn for δPn. The (red) first, (blue) second and (green) third baroclinic modes are displayed for δPn and δscln.


How operate the rectification?:

Our hypothesis is that there is a rectification of the interannual variability (ENSO timescales) by the interdecadal variability associated to changes in the oceanic mean states. To test this hypothesis, we will use two configurations of LODCA: the first one "tuned" as in D0, i.e. with a realistic background stratification and climatologies derived from observations. The second one "tuned" as above from the ARPA derived climatologies and parameters. The approach consists in forcing the anomaly model with the interdecadal fluctuations of (Pn, scln) as derived from the CGCM simulation. These experiments will allow to investigate 1- if a rectification does take place and 2- the relationship between the ENSO modulation produced by the model and the imposed forcing.

Let's first consider that a change at decadal timescales takes place through variations on the oceanic parameter. The variations in Pn and scln (dPn, dscln) described above will lead to variations in the ocean dynamics (du,dv,dws,dh) and therefore on

SST changes. These latter variations, i.e. ,

feedback onto the atmosphere, leading to changes in wind stress anomalies (dTX, dTY), which in turn can feedback onto the ocean wave dynamics. This is what we call the "weak coupling" case because the incremental changes do not feedback on the mean state. On the other hand, if we now assume that over a certain period of time, say T, the changes in wind stress forcing modify the mean thermocline

depth by , the latter can convert into changes of the (Pn, scln) parameters in a similar way than what was derived from ARPA (figure 2). In that configuration, the former loop ("weak coupling") is maintained, leading to a "strong coupling" case. Figure 3 summarizes by a schematic how the rectification can operate.

In the following we will test both configurations ("weak" and "strong") for two different settings of the intermediate coupled model.

Figure 3: Schematic of the rectification feedbacks.


"Weak" coupling case:

LODCA is run with and without (δPn, δscln) forcing for two different settings of its background climatology. The results indicate that the variation in (Pn, scln) impact the ENSO modulation only if LODCA is "tuned" with observed climatologies. Thus the ENSO modulation (quantified through the RMS of the N3VAR index (see Cibot et al. (2004) for definition) is increased by ~10% (74%) when LODCA is "tuned" with the ARPA (observed) climatologies. Note also that there is no significant correlation between N3VAR and variations in the 20°C isotherm depth (dD0) and (dPn, dscln) for both experiments for lags ranging from ­5 to 5 years.

"Strong" coupling case:

On the other hand, the rectification is significantly amplified for both background climatological setting when the changes in mean thermocline depth simulated by the model itself are allowed to feedback on Pn (see figure 4). The ENSO modulation is increased by 40% even when LODCA is "tuned" as in ARPA.

Figure 4 : NINO3SST (thin black lines) and N3VAR (thick red line) indices for LODCA "tuned" with the ARPA climatologies in the case of no dPn forcing is imposed (top) and in the case with dPn forcing derived from the simulated thermocline ("strong" coupling case) (bottom). The low frequency thermocline depth fluctuations are indicated in the bottom part of the bottom panel (thick black line).


The equatorial variability of a 200-yrs full-physic CGCM simulation was investigated with a focus on the processes responsible for the ENSO modulation. The vertical structure variability is first investigated, which shows that high-order baroclinic mode contributions are favored as compared to observations (Moon et al., 2004) or similar OGCM simulation forced with realistic winds (Dewitte et al. 1999).

The decadal variability is then investigated concentrating on 7-yrs low-pass filtered model outputs. In particular, an estimation of the low frequency characteristics of shallow-water model parameters, that account for the subtle changes in the stratification within the thermocline, is provided. The analysis shows that the variations in the wind projection coefficient Pn and the 'thermocline coefficient', scln, introduced by D0, can reach up to 36% of their mean value for the first baroclinic modes. These variations have the potential to lead to a rectification of the ENSO variability by the interdecadal variability as suggested by intermediate coupled experiment. The magnitude of this rectification depends however on the characteristics of the mean state of the ocean. It is also more efficient when the low frequency changes of thermocline depth feedback on the wave dynamics. This suggest a complex interaction between the different timescales (seasonal, ENSO and decadal modes) to produce ENSO modulation. In particular, the large sensitivity illustrated here to the oceanic climatologies indicates that the proposed mechanism of rectification may be at work at some period but not at other.

At last, in view of the threat of global warming, we can wonder how increased greenhouse gas concentrations will affect such mechanism of ENSO modulation. As a warmer tropics should lead to a deeper thermocline and consequently a larger relative contribution of the higher-order baroclinic modes, it is likely that such mechanism is favored in a global warming scenario. This needs to be tested from other CGCM experiments.


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