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The authors examine the sensitivity of the Battisti coupled atmosphere-ocean model - considered as a forecast model for the E1 Niño-Southern Oscillation (ENSO) - to perturbations in the sea surface temperature (SST) field applied at the beginning of a model integration. The spatial structures of the fastest growing SST perturbations are determined by singular vector analysis of an approximation to the propagator for the linearized system. Perturbation growth about the following four reference trajectories is considered: (i) the annual cycle, (ii) a freely evolving model ENSO cycle with an annual cycle in the basic state, (iii) the annual mean basic state, and (iv) a freely evolving model ENSO cycle with an annual mean basic state. Singular vectors with optimal growth over periods of 3, 6, and 9 months are computed. The magnitude of maximum perturbation growth is highly dependent on both the phase of the seasonal cycle and the phase of the ENSO cycle at which the perturbation is applied and on the duration over which perturbations are allowed to evolve. However, the spatial structure of the optimal perturbation is remarkably insensitive to these factors. The structure of the optimal perturbation consists of an east-west dipole spanning the entire tropical Pacific basin superimposed on a north-south dipole in the eastern tropical Pacific. A simple physical interpretation for the optimal pattern is provided. In most cases investigated, there is only one structure that exhibits growth. Maximum perturbation growth takes place for integrations that include the period June-August, and the minimum growth for integrations that include the period January-April. Maxima in potential growth also occur for forecasts of ENSO onset and decay, while minima occur for forecasts initialized during the beginning of a warm event, after the transition from a warm to a cold event, and continuing through the cold event. The physical processes responsible for the large variation in the amplitude of the optimal perturbation growth are identified. The implications of these results for the predictability of short-term climate in the tropical Pacific are discussed.

An atmospheric GCM coupled to a slab ocean model is used to investigate how temperature and precipitation over South America and Africa affect the annual cycle of the Atlantic ITCZ. The main conclusion of this study is that variations in precipitation and temperature forced by the annual cycle of insolation over the continents are as important as variations in insolation over the ocean and in ocean heat transport convergence in forcing the annual march of the Atlantic ITCZ observed in the control simulation. The processes involved are as follows. The intensity of precipitation over land affects the stability of the atmosphere over the tropical Atlantic Ocean, and thus modulates the intensity of deep convection and convergence in the ITCZ. Both the imposed changes in land precipitation and the subsequent changes in the strength of the ITCZ drive surface wind anomalies, thereby changing the meridional gradient of SST in proximity of the basic-state ITCZ. Finally, atmosphere–ocean feedbacks cause the ITCZ to be displaced meridionally. Seasonal changes in surface temperature in the Sahara also have a strong influence on the position of the Atlantic ITCZ. Cold wintertime temperatures produce high surface pressure anomalies over Africa and into the tropical North Atlantic and drive stronger trade winds, which cool the North Atlantic by evaporation. The coupled interactions between the SST, the wind, and the ITCZ intensify the anomalies in the equatorial region, causing the southward displacement of the ITCZ in boreal spring.

Restoring boundary conditions, wherein the temperature and salinity are restored to surface target fields of temperature and salinity, are traditionally used for studies of the ocean circulation in ocean general circulation models. The canonical problem with these boundary conditions is that, when the target fields are chosen as the observed fields, accurate simulation of the surface fields of temperature and salinity would imply that the surface fluxes and therefore the ocean heat transports approach zero, a clearly unrealistic situation. It is clear that the target fields cannot be chosen as the observed fields. A simple but effective method of modifying conventional restoring boundary conditions is introduced, designed to keep the calculated values of surface temperature and salinity as close to observations as possible. The technique involves calculating the optimal target fields in the restoring boundary conditions by an iterative procedure. The method accounts for oceanic processes, such as advection and eddy mixing in the derivation of the new boundary conditions. A reduced version of this method is introduced that produces comparable results but offers greater simplicity in implementation. The simplicity of the method is particularly attractive in idealized studies, which often employ restoring surface boundary conditions. The success of the new method is, however, limited by several factors that cannot be easily compensated by the adjustment of the target profiles. These factors include inaccurate model dynamics, errors in the observations, and the too-simplified form of restoring surface boundary conditions themselves. The application of the method in this study with a coarse-resolution model leads to considerable improvements of the simulation of sea surface temperature (SST) and sea surface salinity (SSS). Both amplitude and phase of the annual cycle in SST greatly improve. The resulting magnitudes of surface heat and freshwater fluxes increase on average, and the meridional heat transport gets stronger. However, the fluxes in some regions remain unrealistic, notably the too-strong freshwater forcing of the western boundary currents in the Northern Hemisphere. Southern Ocean cooling and freshening are also likely to be too strong. The subsurface values of temperature improve greatly, proving that a large part of errors in the subsurface temperature distribution in our model can be corrected by reducing errors at the surface. In contrast, the reduction of errors in surface salinity fails to improve uniformly the simulated subsurface salinity values.

An empirically derived linear dynamical model is constructed using the Comprehensive Ocean-Atmosphere Data Set enhanced sea surface temperature data in the tropical Pacific during the period 1956-95. Annual variation in the Markov model is sought using various tests. A comparison of Nino-3.4 forecast skill using a seasonally varying Markov model to forecast skill in which the seasonal transition matrices are applied during opposite times of the year from which they were derived is made. As a result, it is determined that the seasonal transition matrices are probably not interchangeable, indicating that the Markov model is not annually constant. Stochastic forcing, which has been hypothesized to exhibit seasonality, is therefore not the sole source of the annual variation of El Nino-Southern Oscillation (ENSO) dynamics and the phase locking of ENSO events to peak during November.

Empirical dynamical modeling (EDM) is employed to determine if ENSO forecasting skill using monthly mean SST data can be enhanced by including subsurface temperature anomaly data. The Nino 3.4 index is forecast first using an EDM constructed from the principal component time series corresponding to EOFs of SST anomaly maps of the central and eastern tropical Pacific (328N-328S, 1208E-708W) for the period 1965- 93. Cross validation is applied to minimize the artificial skill of the forecasts, which are made over the same 29-yr period. The forecasting is then repeated with the inclusion of principal components of heat content of the upper 300 m over the northern tropical Pacific (308N-08, 1208E-728W). The forecast skill using SST alone and SST plus subsurface temperature is compared for lead times ranging between 3 and 12 months. The EDM, which includes the subsurface information, forecasts with greater skill at all lead times; particularly important is the second principal component of the heat content, which appears to contribute information on the transition phase between warm and cold ENSO events. The apparent improvement by including subsurface information, although robust, does not appear to be statistically significant. However, the temporal and spatial coverage of the subsurface data is limited, so this study probably underestimates the usefulness of including subsurface temperature data in efforts to predict ENSO. Finally, cross-validated forecasts using a Markov model that includes an annual cycle are shown to be less skillful than forecasts using a seasonally invariant Markov model. The reason for this appears to be that dividing the data yields an insufficient database to derive an accurate Markov model.

The authors present a new model of the tropical surface circulation, forced by changes in sensible heat and evaporative flux anomalies that are associated with prescribed sea surface temperature anomalies. The model is similar to the Lindzen and Nigam (LN) boundary layer model, also driven by the above flux anomalies; but here, since the boundary layer is assumed well mixed and capped by an inversion, the model reduces to a twolayer, reduced-gravity system. Furthermore, the rate of exchange of mass across the boundary layer‐free atmosphere interface is dependent on the moisture budget in the boundary layer. When moist convection is diagnosed to occur, detrainment operates on the timescale associated with the life cycle of deep convection, approximately eight hours. Otherwise, the detrainment is assumed to be associated with the mixing out of the stable tropical boundary layer, which has a timescale of about one day. The model provides a diagnostic estimate of the anomalies in precipitation. However, it is assumed that the latent heat is released above the boundary layer, and it drives a circulation that does not impact the boundary layer. The authors discuss the derivations of the Gill‐Zebiak (GZ) and Lindzen‐Nigam models and highlight some apparent inconsistencies between their derivation and the values of several of the parameters that are required for these models to achieve realistic solutions for the circulations. Then, the new reduced-gravity boundary model equations are rewritten in the form of the GZ and LN models. Using realistic values for the parameters in the new model geometry, it is shown that the constants combine in the rewritten equations to produce the physically doubtful constants in the GZ and LN models, hence, the reason for the apparent success of these models.

Improved observations in the tropical Pacific during the Tropical Ocean-Global Atmosphere (TOGA) program have served to corroborate preexisting notions concerning the seasonally dependent relationships between sea surface temperature, sea level pressure, wind stress, rainfall, upper tropospheric circulation, and ocean thermal structure anomalies in the El Nino-Southern Oscillation (ENSO) phenomenon. However, the paradigm of a quasiperiodic “ENSO cycle,” phase locked with the annual march, does not capture the complexity of the evolution of the anomalies. The inadequacy of this model was particularly apparent during the second half of TOGA when the variability was highly aperiodic. Also, a single modal structure or empirical orthogonal function does not appear to be capable of representing the range of spatial patterns of ocean-atmosphere interaction in the tropical Pacific. These results suggest the need for a more inclusive phenomenological description of ENSO. Data collected during TOGA serve to confirm the influence of tropical Atlantic sea surface temperature anomalies upon rainfall in northeast Brazil.

A 21/2-layer ocean model is developed to investigate the role of the first two baroclinic modes in determining the interannual variations of the sea surface temperature (SST) associated with the El Nino–Southern Oscillation (ENSO) phenomenon. Rather than simply adding an additional mode to the ocean component of the Zebiak–Cane coupled atmosphere–ocean model, it proved necessary to completely rethink all parts of the model. This allowed the external parameters to be specified more realistically. For example, the drag coefficient used in calculating the surface wind stress in the model is now consistent with that empirically derived, and the temperature of the water entrained in the surface layer that affects SST is now more carefully parameterized. When forced by observed wind stress anomalies for 1961–93, the ocean model reproduces the interannual variations of SST satisfactorily. The quantitative discrepancies between the model hindcast and observed SST anomalies are limited to an excessive coo...

The effect of nonlinearities on a previously investigated coupled atmosphere–ocean basin mode is examined. The nonlinearity in the thermodynamic equation for sea surface temperature arises mainly from the dependence of subsurface temperature on the thermocline depth anomaly in the parameterization of entrainment into the mixed layer. This nonlinearity ultimately suppresses the linear growth of the unstable mode and equilibrates it at a finite amplitude. Because this nonlinearity acts differently for warm and cold states, the warm states are enhanced at finite amplitude. It is found that multiple equilibrium states appear as the coupling coefficient increases and as the reflection coefficient of the oceanic Rossby mode at the western boundary decreases. The finite-amplitude warm equilibrium state turns out to be stable, but the finite-amplitude cold state is unstable. The explicit inclusion of the dependence of the coupling strength on the warm and cold sea surface temperature anomalies modulates ...

Four different datasets of monthly mean new-equatorial Pacific sea surface temperature for 1982–83 are compared, and the space-time regions for which there was consensus that cooling or warming took place, are determined. There was consensus that warming took place east of the date line, averaged over the period July-December 1982, and that the warming progressed eastward from the central Pacific. There was also consensus that weak cooling took place in April 1983, and that substantial cooling occurred in June-July 1983, generally over the central and eastern Pacific. However, the analyses tend to agree on the sign of SST change only in periods of cooling or warming in excess of 1°C/month; quantitative agreement at the level of 0.5°C/month or better is almost never found. SST changes in five ocean-circulation model hindcasts of the 1982–83 period (differing only in that each used a different analyzed monthly mean surface wind stress field to drive the ocean), are compared with the observations an...

The El Nino/Southern Oscillation (ENSO) is a phenomenon exhibiting near-global oscillations of sea level pressure and winds, with the largest amplitude in the tropical Southern Hemisphere. Most of the more intense manifestations of wind, sea surface temperature (SST) and precipitation occur in the tropical Pacific, and it is there that most of the modelling and prediction efforts have been concentrated. The ENSO phenomenon appears cyclic, having well-defined sequences of events, but is not periodic, the historical record showing irregularities and long periods of time during which ENSO oscillations did not occur. When ENSO oscillations do occur, the local effects on the coast of Peru are economically catastrophic, and there are indications that mid-latitude weather is affected by equatorial SST anomalies. Consequently, there is great interest in predicting the occurrence of ENSO in the equatorial Pacific.

We review simple instabilities in linear theories of coupled atmosphere-ocean models in both bounded and unbounded ocean basins and describe the mechanisms for instability in these linear theories. We then review nonlinear coupled atmosphere-ocean simulations of the El Nino Southern Oscillation (ENSO) phenomenon and relate the instabilities seen in linear theory to the fully nonlinear ENSO simulations. We present a general discussion of the relation between instability and predictability in the ENSO problem and review some recent work on predictability in coupled models. Finally, we comment on some recent predictions in light of our discussion of predictability.

It is shown that the (cumulus) convective processes in the tropics may be described by a one-dimensional cloud model, while the near-surface ocean may similarly be described by a one-dimensional mixed-layer model. The coupling is achieved through a sea surface flux budget combined with the flux parameterizations implied by Monin-Obukhov similarity theory. The coupled one-dimensional atmosphere-ocean model is applied to the equilibrium situation in which all temperatures reach a steady state. For the ocean, the fluxes must vanish in equilibrium, but the atmosphere maintains a stable lapse rate by balancing cumulonimbus heating against net radiative cooling. All water precipitating from cumulonimbus clouds must have evaporated from the sea. It is shown that this equilibrium system is closed and determinable solely in terms of the solar constant.