Influence of Indian Ocean Dipole and Pacific recharge on following year’s El Niño: interdecadal robustness

The Indian Ocean Dipole (IOD) can affect the El Niño–Southern Oscillation (ENSO) state of the following year, in addition to the well-known preconditioning by equatorial Pacific Warm Water Volume (WWV), as suggested by a study based on observations over the recent satellite era (1981–2009). The present paper explores the interdecadal robustness of this result over the 1872–2008 period. To this end, we develop a robust IOD index, which well exploits sparse historical observations in the tropical Indian Ocean, and an efficient proxy of WWV interannual variations based on the temporal integral of Pacific zonal wind stress (of a historical atmospheric reanalysis). A linear regression hindcast model based on these two indices in boreal fall explains 50 % of ENSO peak variance 14 months later, with significant contributions from both the IOD and WWV over most of the historical period and a similar skill for El Niño and La Niña events. Our results further reveal that, when combined with WWV, the IOD index provides a larger ENSO hindcast skill improvement than the Indian Ocean basin-wide mode, the Indian Monsoon or ENSO itself. Based on these results, we propose a revised scheme of Indo-Pacific interactions. In this scheme, the IOD–ENSO interactions favour a biennial timescale and interact with the slower recharge-discharge cycle intrinsic to the Pacific Ocean.     

Does sea surface temperature outside the tropical Pacific contribute to enhanced ENSO predictability?

In this paper we seek to identify inter-annual sea surface temperature anomalies (SSTA) patterns outside the tropical Pacific that may influence El Niño/Southern Oscillation (ENSO) through atmospheric teleconnections. We assume that a linear ENSO hindcast based on tropical Pacific warm water volume and Niño3.4 SSTA indices captures tropical Pacific intrinsic predictability inherent to recharge oscillator dynamics. This simple hindcast model displays statistically significant skill at the 95 % confidence level at leads of up to seven seasons ahead of the ENSO peak. Our results reveal that ENSO-independent equatorial wind stress anomalies only significantly improve the skill of that linear hindcast at the 95 % level in boreal spring and summer before the ENSO peak and in boreal fall, five seasons ahead of the ENSO peak. At those seasons, the robust large-scale SST patterns that provide a statistically significant enhancement of ENSO predictability are related to the Atlantic meridional mode and south Pacific subtropical dipole mode in spring, the Indian Ocean Dipole and the south Atlantic subtropical dipole mode in fall. While the first two regions display significant simultaneous correlations with western equatorial Pacific wind stress in three reanalyses (ERA-I, NCEP and NCEP2), the Indian Ocean Dipole and south Atlantic subtropical dipole mode correlation with Pacific winds is less robust amongst re-analyses. We discuss our results in view of other studies that suggest a remote influence of various regions on ENSO. Although modest, the sensitivity of our results to the dataset and to details of the analysis method illustrates that finding regions that influence ENSO from the statistical analysis of observations is a difficult task.     

Global seasonal climate predictability in a two tiered forecast system. Part II: boreal winter and spring seasons

We examine the Florida Climate Institute–Florida State University Seasonal Hindcast (FISH50) skill at a relatively high (50 km grid) resolution two tiered Atmospheric General Circulation Model (AGCM) for boreal winter and spring seasons at zero and one season lead respectively. The AGCM in FISH50 is forced with bias corrected forecast sea surface temperature averaged from two dynamical coupled ocean–atmosphere models. The comparison of the hindcast skills of precipitation and surface temperature from FISH50 with the coupled ocean–atmosphere models reveals that the probabilistic skill is nearly comparable in the two types of forecast systems (with some improvements in FISH50 outside of the global tropics). Furthermore the drop in skill in going from zero lead (boreal winter) to one season lead (boreal spring) is also similar in FISH50 and the coupled ocean–atmosphere models. Both the forecast systems also show that surface temperature hindcasts have more skill than the precipitation hindcasts and that land based precipitation hindcasts have slightly lower skill than the corresponding hindcasts over the ocean.     

Ocean–atmosphere coupling and the boreal winter MJO

The influence of ocean–atmosphere coupling on the simulation and prediction of the boreal winter Madden–Julian Oscillation (MJO) is examined using the Seoul National University coupled general circulation model (CGCM) and atmospheric—only model (AGCM). The AGCM is forced with daily SSTs interpolated from pentad mean CGCM SSTs. Forecast skill is examined using serial extended simulations spanning 26 different winter seasons with 30-day forecasts commencing every 5 days providing a total of 598 30-day simulations. By comparing both sets of experiments, which share the same atmospheric components, the influence of coupled ocean–atmosphere processes on the simulation and prediction of MJO can be studied. The mean MJO intensity possesses more realistic amplitude in the CGCM than in AGCM. In general, the ocean–atmosphere coupling acts to improve the simulation of the spatio-temporal evolution of the eastward propagating MJO and the phase relationship between convection (OLR) and SST over the equatorial Indian Ocean and the western Pacific. Both the CGCM and observations exhibit a near-quadrature relationship between OLR and SST, with the former lagging by about two pentads. However, the AGCM shows a less realistic phase relationship. As the initial conditions are the same in both models, the additional forcing by SST anomalies in the CGCM extends the prediction skill beyond that of the AGCM. To test the applicability of the CGCM to real-time prediction, we compute the Real-time Multivariate MJO (RMM) index and compared it with the index computed from observations. RMM1 (RMM2) falls away rapidly to 0.5 after 17–18 (15–16) days in the AGCM and 18–19 (16–17) days in the CGCM. The prediction skill is phase dependent in both the CGCM and AGCM.     

Mechanisms controlling warm water volume interannual variations in the equatorial Pacific: diabatic versus adiabatic processes

Variations of the volume of warm water above the thermocline in the equatorial Pacific are a good predictor of ENSO (El Ni?o/Southern Oscillation) and are thought to be critical for its preconditioning and development. In this study, the Warm Water Volume (WWV) interannual variability is analysed using forced general circulation model experiments and an original method for diagnosing processes responsible for WWV variations. The meridional recharge/discharge to higher latitudes drives 60% of the ENSO-related equatorial WWV variations, while diabatic processes in the eastern equatorial Pacific account for the remaining 40%. Interior meridional transport is partially compensated by western boundary transports, especially in the southern hemisphere. Diabatic equatorial WWV formation (depletions) during La Ni?a (El Ni?o) are explained by enhanced (reduced) diathermal transport through enhanced (reduced) vertical mixing and penetrating solar forcing at the 20°C isotherm depth. The respective contribution of diabatic and adiabatic processes during build-ups/depletions strongly varies from event-to-event. The WWV build-up during neutral ENSO phases (e.g. 1980–1982) is almost entirely controlled by meridional recharge, providing a text-book example for the recharge/discharge oscillator’s theory. On the other hand, diabatic processes are particularly active during the strongest La Ni?a events (1984, 1988, 1999), contributing to more than 70% of the WWV build-up, with heating by penetrative solar fluxes explaining as much as 30% of the total build-up due to a very shallow thermocline in the eastern Pacific. This study does not invalidate the recharge/discharge oscillator theory but rather emphasizes the importance of equatorial diabatic processes and western boundary transports in controlling WWV changes.     

Characteristics of tropical Pacific SST predictability in coupled GCM forecasts using the NCEP CFS

The limits of predictability of El Niño and the Southern Oscillation (ENSO) in coupled models are investigated based on retrospective forecasts of sea surface temperature (SST) made with the National Centers for Environmental Prediction (NCEP) coupled forecast system (CFS). The influence of initial uncertainties and model errors associated with coupled ENSO dynamics on forecast error growth are discussed. The total forecast error has maximum values in the equatorial Pacific and its growth is a strong function of season irrespective of lead time. The largest growth of systematic error of SST occurs mainly over the equatorial central and eastern Pacific and near the southeastern coast of the Americas associated with ENSO events. After subtracting the systematic error, the root-mean-square error of the retrospective forecast SST anomaly also shows a clear seasonal dependency associated with what is called spring barrier. The predictability with respect to ENSO phase shows that the phase locking of ENSO to the mean annual cycle has an influence on the seasonal dependence of skill, since the growth phase of ENSO events is more predictable than the decay phase. The overall characteristics of predictability in the coupled system are assessed by comparing the forecast error growth and the error growth between two model forecasts whose initial conditions are 1 month apart. For the ensemble mean, there is fast growth of error associated with initial uncertainties, becoming saturated within 2 months. The subsequent error growth follows the slow coupled mode related the model’s incorrect ENSO dynamics. As a result, the Lorenz curve of the ensemble mean NINO3 index does not grow, because the systematic error is identical to the same target month. In contrast, the errors of individual members grow as fast as forecast error due to the large instability of the coupled system. Because the model errors are so systematic, their influence on the forecast skill is investigated by analyzing the erroneous features in a long simulation. For the ENSO forecasts in CFS, a constant phase shift with respect to lead month is clear, using monthly forecast composite data. This feature is related to the typical ENSO behavior produced by the model that, unlike the observations, has a long life cycle with a JJA peak. Therefore, the systematic errors in the long run are reflected in the forecast skill as a major factor limiting predictability after the impact of initial uncertainties fades out.     

Impact of bio-physical feedbacks on the tropical climate in coupled and uncoupled GCMs

The bio-physical feedback process between the marine ecosystem and the tropical climate system is investigated using both an ocean circulation model and a fully-coupled ocean–atmosphere circulation model, which interact with a biogeochemical model. We found that the presence of chlorophyll can have significant impact on the characteristics of the El Niño-Southern Oscillation (ENSO), including its amplitude and asymmetry, as well as on the mean state. That is, chlorophyll generally increases mean sea surface temperature (SST) due to the direct biological heating. However, SST in the eastern equatorial Pacific decreases due to the stronger indirect dynamical response to the biological effects outweighing the direct thermal response. It is demonstrated that this biologically-induced SST cooling is intensified and conveyed to other tropical-ocean basins when atmosphere–ocean coupling is taken into account. It is also found that the presence of chlorophyll affects the magnitude of ENSO by two different mechanisms; one is an amplifying effect by the mean chlorophyll, which is associated with shoaling of the mean thermocline depth, and the other is a damping effect derived from the interactively-varying chlorophyll coupled with the physical model. The atmosphere–ocean coupling reduces the biologically-induced ENSO amplifying effect through the weakening of atmospheric feedback. Lastly, there is also a biological impact on ENSO which enhances the positive skewness. This skewness change is presumably caused by the phase dependency of thermocline feedback which affects the ENSO magnitude.     

ENSO modes of the equatorial Pacific Ocean in observations and CMIP5 models

El Niño/Southern Oscillation (ENSO) is the predominant interannual variability of the global climate system. How might ENSO change in a warmer world? The dominant two Combined Empirical Orthogonal Functions (CEOF) of the equatorial ocean temperature and zonal and vertical motion identify two modes that shown a transition in the eastern Pacific from a warming eastward/downward motion to a cooling westward/upward flow. These results also suggest consistent changes to the west and at depths down to 300 m. These dominate CEOFs provide a compact tool for assessing Coupled Model Intercomparison Project Phase 5 ocean model output for both the recent historical period and for the latter part of the twenty first century. Most of the analyzed models replicate well the spatial patterns of the dominant observational CEOF modes, but nearly always underestimate the magnitudes. Comparing model output for the twentieth and twenty first centuries there is very little change between the spatial patterns of the ENSO modes of the two periods. This lack of response to climate change is shown to be partly related to competing influences of climatic changes in the mean ocean circulation.     

The seasonal predictability of the Asian summer monsoon in a two-tiered forecast system

An extensive set of boreal summer seasonal hindcasts from a two tier system is compared with corresponding seasonal hindcasts from two other coupled ocean–atmosphere models for their seasonal prediction skill (for precipitation and surface temperature) of the Asian summer monsoon. The unique aspect of the two-tier system is that it is at relatively high resolution and the SST forcing is uniquely bias corrected from the multi-model averaged forecasted SST from the two coupled ocean–atmosphere models. Our analysis reveals: (a) The two-tier forecast system has seasonal prediction skill for precipitation that is comparable (over the Southeast Asian monsoon) or even higher (over the South Asian monsoon) than the coupled ocean–atmosphere. For seasonal anomalies of the surface temperature the results are more comparable across models, with all of them showing higher skill than that for precipitation. (b) Despite the improvement from the uncoupled AGCM all models in this study display a deterministic skill for seasonal precipitation anomalies over the Asian summer monsoon region to be weak. But there is useful probabilistic skill for tercile anomalies of precipitation and surface temperature that could be harvested from both the coupled and the uncoupled climate models. (c) Seasonal predictability of the South Asian summer monsoon (rainfall and temperature) does seem to stem from the remote ENSO forcing especially over the Indian monsoon region and the relatively weaker seasonal predictability in the Southeast Asian summer monsoon could be related to the comparatively weaker teleconnection with ENSO. The uncoupled AGCM with the bias corrected SST is able to leverage this teleconnection for improved seasonal prediction skill of the South Asian monsoon relative to the coupled models which display large systematic errors of the tropical SST’s.     

The impact of tropical western Pacific convection on the North Pacific atmospheric circulation during the boreal winter

In this study, we investigate the impact of atmospheric convection over the western tropical Pacific (100–145°E, 0–20°N) on the boreal winter North Pacific atmosphere flow by analyzing National Center for Environmental Prediction Reanalysis 1, Extended Reconstructed Sea Surface Temperature and Global Precipitation Climatology Project data. The western tropical Pacific convection is not only the main energy source driving the local Hadley and Walker circulations, but it also significantly influences North Pacific circulation, by modifying a mid-latitude Jet stream through the connection with the local Hadley circulation. On the one hand, this strong convection leads to a northward expansion of local Hadley cells simultaneous with a northward movement of the western North Pacific jet because of the close correlation between the Jet and Hadley circulation boundaries. On the other hand, this strong convection also intensifies tropical Pacific Walker circulation, which reduces the eastern Pacific sea surface temperature, resembling a La Nina state through the enhanced equatorial upwelling. The cooling of the eastern tropical Pacific has an inter-tropical convergence zone located further north; thus, the local Hadley circulation moves northward. As a result, the jet axis over the eastern North Pacific, which also corresponds to the boundary of the local Hadley circulation, moves to higher latitude. Consequently, this northward movement of the Jet axis over the North Pacific is reflected as a northwest–southeast dipole sea level pressure (SLP) pattern. The composite analysis of SLP over the North Pacific against the omega (Ω) (Pa/s) at 500 hPa over the western tropical Pacific actually reveals that this northwest-southeast dipole structure is attributed to the intensified tropical western Pacific convection, which pushes the Pacific Jet to the north. Finally we also analyzed south Pacific for the austral winter as did previously to North Pacific, and found that the results were consistent.     

Remotely forced variability in the tropical Atlantic Ocean

An ensemble of eight hindcasts has been conducted using an ocean-atmosphere general circulation model fully coupled only within the Atlantic basin, with prescribed observational sea surface temperature (SST) for 1950–1998 in the global ocean outside the Atlantic basin. The purpose of these experiments is to understand the influence of the external SST anomalies on the interannual variability in the tropical Atlantic Ocean. Statistical methods, including empirical orthogonal function analysis with maximized signal-to-noise ratio, have been used to extract the remotely forced Atlantic signals from the ensemble of simulations. It is found that the leading external source on the interannual time scales is the El Niño/Southern Oscillation (ENSO) in the Pacific Ocean. The ENSO signal in the tropical Atlantic shows a distinct progression from season to season. During the boreal winter of a maturing El Niño event, the model shows a major warm center in the southern subtropical Atlantic together with warm anomalies in the northern subtropical Atlantic. The southern subtropical SST anomalies is caused by a weakening of the southeast trade winds, which are partly associated with the influence of an atmospheric wave train generated in the western Pacific Ocean and propagating into the Atlantic basin in the Southern Hemisphere during boreal fall. In the boreal spring, the northern tropical Atlantic Ocean is warmed up by a weakening of the northeast trade winds, which is also associated with a wave train generated in the central tropical Pacific during the winter season of an El Niño event. Apart from the atmospheric planetary waves, these SST anomalies are also related to the sea level pressure (SLP) increase in the eastern tropical Atlantic due to the global adjustment to the maturing El Niño in the tropical Pacific. The tropical SLP anomalies are further enhanced in boreal spring, which induce anomalous easterlies on and to the south of the equator and lead to a dynamical oceanic response that causes cold SST anomalies in the eastern and equatorial Atlantic from boreal spring to summer. Most of these SST anomalies persist into the boreal fall season.

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Dynamical seasonal prediction of Southern African summer precipitation

Prediction skill for southern African (16°–33°E, 22°–35°S) summer precipitation in the Scale Interaction Experiment-Frontier coupled model is assessed for the period of 1982–2008. Using three different observation datasets, deterministic forecasts are evaluated by anomaly correlation coefficients, whereas scores of relative operating characteristic and relative operating level are used to evaluate probabilistic forecasts. We have found that these scores for December–February precipitation forecasts initialized on October 1st are significant at 95 % confidence level. On a local scale, the level of prediction skill in the northwestern and central parts of southern Africa is higher than that in northeastern South Africa. El Niño/Southern Oscillation (ENSO) provides the major source of predictability, but the relationship with ENSO is too strong in the model. The Benguela Niño, the basin mode in the tropical Indian Ocean, the subtropical dipole modes in the South Atlantic and the southern Indian Oceans and ENSO Modoki may provide additional sources of predictability. Within the wet season from October to the following April, the precipitation anomalies in December-February are the most predictable. This study presents promising results for seasonal prediction of precipitation anomaly in the extratropics, where seasonal prediction has been considered a difficult task.     

Extra-tropical atmospheric response to ENSO in the CMIP5 models

The seasonal mean extra-tropical atmospheric response to El Niño/Southern Oscillation (ENSO) is assessed in the historical and pre-industrial control CMIP5 simulations. This analysis considers two types of El Niño events, characterized by positive sea surface temperature (SST) anomalies in either the central equatorial Pacific (CP) or eastern equatorial Pacific (EP), as well as EP and CP La Niña events, characterized by negative SST anomalies in the same two regions. Seasonal mean geopotential height anomalies in key regions typify the magnitude and structure of the disruption of the Walker circulation cell in the tropical Pacific, upper tropospheric ENSO teleconnections and the polar stratospheric response. In the CMIP5 ensembles, the magnitude of the Walker cell disruption is correlated with the strength of the mid-latitude responses in the upper troposphere i.e., the North Pacific and South Pacific lows strengthen during El Niño events. The simulated responses to El Niño and La Niña have opposite sign. The seasonal mean extra-tropical, upper tropospheric responses to EP and CP events are indistinguishable. The ENSO responses in the MERRA reanalysis lie within the model scatter of the historical simulations. Similar responses are simulated in the pre-industrial and historical CMIP5 simulations. Overall, there is a weak correlation between the strength of the tropical response to ENSO and the strength of the polar stratospheric response. ENSO-related polar stratospheric variability is best simulated in the “high-top” subset of models with a well-resolved stratosphere.     

On the Atlantic–Pacific Niños connection: a multidecadal modulated mode

Atlantic and Pacific El Niño are the leading tropical oceanic variability phenomena at interannual timescales. Recent studies have demonstrated how the Atlantic Niño is able to influence on the dynamical processes triggering the development of the Pacific La Niña and vice versa. However, the stationarity of this interbasin connection is still controversial. Here we show for the first time that the Atlantic–Pacific Niños connection takes place at particular decades, coinciding with negative phases of the Atlantic Multidecadal Oscillation (AMO). During these decades, the Atlantic–Pacific connection appears as the leading coupled covariability mode between Tropical Atlantic and Pacific interannual variability. The mode is defined by a predictor field, the summer Atlantic Sea Surface Temperature (SST), and a set of predictand fields which represent a chain of atmospheric and oceanic mechanisms to generate the Pacific El Niño phenomenon: alteration of the Walker circulation, surface winds in western Pacific, oceanic Kelvin wave propagating eastward and impacting on the eastern thermocline and changes in the Pacific SST by internal Bjerknes feedback. We suggest that the multidecadal component of the Atlantic acts as a switch for El Niño prediction during certain decades, putting forward the AMO as the modulator, acting through changes in the equatorial Atlantic convection and the equatorial Pacific SST variability. These results could have a major relevance for the decadal prediction systems.     

Tropical Pacific impacts of convective momentum transport in the SNU coupled GCM

Impacts of convective momentum transport (CMT) on tropical Pacific climate are examined, using an atmospheric (AGCM) and coupled GCM (CGCM) from Seoul National University. The CMT scheme affects the surface mainly via a convection-compensating atmospheric subsidence which conveys momentum downward through most of the troposphere. AGCM simulations—with SSTs prescribed from climatological and El Nino Southern Oscillation (ENSO) conditions—show substantial changes in circulation when CMT is added, such as an eastward shift of the climatological trade winds and west Pacific convection. The CMT also alters the ENSO wind anomalies by shifting them eastward and widening them meridionally, despite only subtle changes in the precipitation anomaly patterns. During ENSO, CMT affects the low-level winds mainly via the anomalous convection acting on the climatological westerly wind shear over the central Pacific—so that an eastward shift of convection transfers more westerly momentum toward the surface than would occur without CMT. By altering the low-level circulation, the CMT further alters the precipitation, which in turn feeds back on the CMT. In the CGCM, CMT affects the simulated climatology by shifting the mean convection and trade winds eastward and warming the equatorial SST; the ENSO period and amplitude also increase. In contrast to the AGCM simulations, CMT substantially alters the El Nino precipitation anomaly patterns in the CGCM. Also discussed are possible impacts of the CMT-induced changes in climatology on the simulated ENSO.     

Interdecadal changes in the relationship between Southern China winter-spring precipitation and ENSO

Winter-spring precipitation in southern China tends to be higher (lower) than normal in El Niño (La Niña) years during 1953–1973. The relationship between the southern China winter-spring precipitation and El Niño-Southern Oscillation (ENSO) is weakened during 1974–1994. During 1953–1973, above-normal southern China rainfall corresponds to warmer sea surface temperature (SST) in the equatorial central Pacific. There are two anomalous vertical circulations with ascent over the equatorial central Pacific and ascent over southern China and a common branch of descent over the western North Pacific that is accompanied by an anomalous lower-level anticyclone. During 1974–1994, above-normal southern China rainfall corresponds to warmer SST in eastern South Indian Ocean and cooler SST in western South Indian Ocean. Two anomalous vertical circulations act to link southern China rainfall and eastern South Indian Ocean SST anomalies, with ascent over eastern South Indian Ocean and southern China and a common branch of descent over the western North Pacific. Present analysis shows that South Indian Ocean SST anomalies can contribute to southern China winter-spring precipitation variability independently. The observed change in the relationship between southern China winter-spring rainfall and ENSO is likely related to the increased SST variability in eastern South Indian Ocean and the modulation of the Pacific decadal oscillation.     

Comparing the patterns of 20–70 days intraseasonal oscillations over Central Africa during the last three decades

In this paper, we used the Outgoing Longwave Radiation (OLR) data to compare the intraseasonal atmospheric variability patterns over Central Africa, during the last three decades. The spectral analysis indicates that for the three decades, the intraseasonal variability is dominated by 20–80 days periods band with the center near 40–50 days. The results of Empirical Orthogonal Functions (EOFs) analysis have shown that the amount of variance explained by the three retained EOFs are 41.6 % for 1981–1990, 44.2 % for 1991–2000 and 42.6 % for 2001–2010. For the three decades, the three leading EOFs retained exhibit high spatial loadings over Northern Congo, Southern Ethiopia, and Southwestern Tanzania. The power spectra of the leading principal components have their peaks near 40 days for the three decades, indicating MJO signal. The PCs time series revealed that the amplitude of intraseasonal oscillations (ISO) globally decreases from decade to another. The plot of ISO and El Niño-Southern Oscillation (ENSO) indices revealed that the lowest values of ISO strength generally correspond to the relatively large values of ENSO indices and inversely. The mean ISO strength and ISO fluctuations were highest during 1981–1990, and this period also corresponds to the highest fluctuations of ENSO signal.     

Effectiveness of the Bjerknes stability index in representing ocean dynamics

The El Niño-Southern Oscillation (ENSO) is a naturally occurring coupled phenomenon originating in the tropical Pacific Ocean that relies on ocean–atmosphere feedbacks. The Bjerknes stability index (BJ index), derived from the mixed-layer heat budget, aims to quantify the ENSO feedback process in order to explore the linear stability properties of ENSO. More recently, the BJ index has been used for model intercomparisons, particularly for the CMIP3 and CMIP5 models. This study investigates the effectiveness of the BJ index in representing the key ENSO ocean feedbacks—namely the thermocline, zonal advective, and Ekman feedbacks—by evaluating the amplitudes and phases of the BJ index terms against the corresponding heat budget terms from which they were derived. The output from Australian Community Climate and Earth System Simulator Ocean Model (a global ocean/sea ice flux-forced model) is used to calculate the heat budget in the equatorial Pacific. Through the model evaluation process, the robustness of the BJ index terms are tested. We find that the BJ index overestimates the relative importance of the thermocline feedback to the zonal advective feedback when compared with the corresponding terms from the heat budget equation. The assumption of linearity between variables in the BJ index formulation is the primary reason for these differences. Our results imply that a model intercomparison relying on the BJ index to explain ENSO behavior is not necessarily an accurate quantification of dynamical differences between models that are inherently nonlinear. For these reasons, the BJ index may not fully explain underpinning changes in ENSO under global warming scenarios.     

Current status of ENSO prediction skill in coupled ocean–atmosphere models

The overall skill of ENSO prediction in retrospective forecasts made with ten different coupled GCMs is investigated. The coupled GCM datasets of the APCC/CliPAS and DEMETER projects are used for four seasons in the common 22 years from 1980 to 2001. As a baseline, a dynamic-statistical SST forecast and persistence are compared. Our study focuses on the tropical Pacific SST, especially by analyzing the NINO34 index. In coupled models, the accuracy of the simulated variability is related to the accuracy of the simulated mean state. Almost all models have problems in simulating the mean and mean annual cycle of SST, in spite of the positive influence of realistic initial conditions. As a result, the simulation of the interannual SST variability is also far from perfect in most coupled models. With increasing lead time, this discrepancy gets worse. As one measure of forecast skill, the tier-1 multi-model ensemble (MME) forecasts of NINO3.4 SST have an anomaly correlation coefficient of 0.86 at the month 6. This is higher than that of any individual model as well as both forecasts based on persistence and those made with the dynamic-statistical model. The forecast skill of individual models and the MME depends strongly on season, ENSO phase, and ENSO intensity. A stronger El Niño is better predicted. The growth phases of both the warm and cold events are better predicted than the corresponding decaying phases. ENSO-neutral periods are far worse predicted than warm or cold events. The skill of forecasts that start in February or May drops faster than that of forecasts that start in August or November. This behavior, often termed the spring predictability barrier, is in part because predictions starting from February or May contain more events in the decaying phase of ENSO.