Simulated El Nino-Southern Oscillation Research Articles

Estimating Uncertainty in Simulated ENSO Statistics

AbstractLarge ensembles of model simulations are frequently used to reduce the impact of internal variability when evaluating climate models and assessing climate change induced trends. However, the optimal number of ensemble members required to distinguish model biases and climate change signals from internal variability varies across models and metrics. Here we analyze the mean, variance and skewness of precipitation and sea surface temperature in the eastern equatorial Pacific region often used to describe the El Niño–Southern Oscillation (ENSO), obtained from large ensembles of Coupled model intercomparison project phase 6 climate simulations. Leveraging established statistical theory, we develop and assess equations to estimate, a priori, the ensemble size or simulation length required to limit sampling‐based uncertainties in ENSO statistics to within a desired tolerance. Our results confirm that the uncertainty of these statistics decreases with the square root of the time series length and/or ensemble size. Moreover, we demonstrate that uncertainties of these statistics are generally comparable when computed using either pre‐industrial control or historical runs. This suggests that pre‐industrial runs can sometimes be used to estimate the expected uncertainty of statistics computed from an existing historical member or ensemble, and the number of simulation years (run duration and/or ensemble size) required to adequately characterize the statistic. This advance allows us to use existing simulations (e.g., control runs that are performed during model development) to design ensembles that can sufficiently limit diagnostic uncertainties arising from simulated internal variability. These results may well be applicable to variables and regions beyond ENSO.

ENSO phase locking, asymmetry and predictability in the INMCM Earth system model

Abstract Advanced numerical climate models are known to exhibit biases in simulating some features of El Niño–Southern Oscillation (ENSO), which is a key mode of interannual climate variability. In this study we analyze how two fundamental features of observed ENSO – asymmetry between hot and cold states and phase-locking to the annual cycle – are reflected in two different versions of the INMCM Earth system model (state-of-the-art Earth system model participating in the Coupled Model Intercomparison Project). We identify the above ENSO features using the conventional empirical orthogonal functions (EOF) analysis, which is applied to both observed and simulated upper ocean heat content (OHC) data in the tropical Pacific. We obtain that the observed tropical Pacific OHC variability is described well by two leading EOF-modes, which roughly reflect the fundamental recharge-discharge mechanism of ENSO. These modes exhibit strong seasonal cycles associated with ENSO phase locking while the revealed nonlinear dependencies between amplitudes of these cycles reflect ENSO asymmetry.We also assess and compare the predictability of observed and simulated ENSO based on linear inverse modelling. We find that the improved INMCM6 model has significant benefits in simulating described features of observed ENSO as compared with the previous INMCM5 model. The improvements of the INMCM6 model providing such benefits are discussed. We argue that proper cloud parameterization scheme is crucial for accurate simulation of ENSO dynamics with numerical climate models.

Atmospheric modes fiddling the simulated ENSO impact on tropical cyclone genesis over the Northwest Pacific

The El Niño-Southern Oscillation (ENSO) is crucial to the interannual variability of tropical cyclone (TC) genesis over the western North Pacific (WNP). However, most state-of-the-art climate models exhibit a consistent pattern of uncertainty in the simulated TC genesis frequency (TCGF) over the WNP in ENSO phases. Here, we analyze large ensemble simulations of TC-resolved climate models to identify the source of this uncertainty. Results show that large uncertainty appears in the South China Sea and east of the Philippines, primarily arising from two distinct atmospheric modes: the Matsuno-Gill-mode (MG-mode) and the Pacific-Japan-like pattern (PJ-mode). These two modes are closely associated with anomalous diabatic heating linked to tropical precipitation bias in model simulations. By conditionally constraining either of the modes, we can significantly reduce model uncertainty in simulating the dipole structure of the TCGF anomalies, confirming that it is the atmospheric circulation bias in response to tropical precipitation bias that causes uncertainty in the simulated WNP TCGF.

Variation in the Impact of ENSO on the Western Pacific Pattern Influenced by ENSO Amplitude in CMIP6 Simulations

AbstractThe Western Pacific pattern (WP) is one of the most consequential atmospheric teleconnections during boreal winter, as it profoundly influences weather extremes and climate variability across Eurasia and North America. The El Niño‐Southern Oscillation (ENSO) is suggested to be a crucial external forcing of WP variability. In this study, we meticulously evaluated the capability of 56 coupled climate models from the Coupled Model Intercomparison Project 6th phase (CMIP6) in replicating the winter ENSO‐WP connection. Our results reveal notable diversities in the portrayal of the winter ENSO‐WP relation across CMIP6 models. This model diversity in the ENSO‐WP connections primarily stems from the spread of the models' simulated ENSO amplitude. Specifically, models with enhanced ENSO amplitudes exhibit intensified sea surface temperature (SST) anomalies in the equatorial central‐eastern Pacific. This enhancement of SST anomalies faciliates stronger atmospheric convective anomalies, especially in the extratropical eastern Pacific and the tropical western North Pacific. Of particular note is the intensified atmospheric convective anomalies in the tropical western North Pacific, which exert a pivotal role in shaping the WP through initiating a distinct atmospheric teleconnection pattern.

The Andes Affect ENSO Statistics

Abstract Current coupled global climate models have biases in their simulations of the tropical Pacific mean-state conditions as well as the El Niño–Southern Oscillation (ENSO) phenomenon. Specifically, in the Community Earth System Model (CESM version 1.2.2), the tropical Pacific mean state has overly weak sea surface temperature (SST) gradients in both the zonal and meridional directions, ENSO is too strong and too regular, and El Niño and La Niña events are too symmetrical. A previous study with a slab-ocean model showed that a higher elevation of the Andes can improve the tropical Pacific mean-state simulation by adjusting the atmospheric circulation and increasing the east–west and north–south SST gradients. Motivated by the link between the mean tropical Pacific climate and ENSO variations shown in previous studies, here we explored the influence of the Andes on the simulation of ENSO using the CESM 1.2.2 under full atmosphere–ocean coupling. In addition to improving the simulated tropical Pacific mean state by increasing the strength of the surface easterly and cross-equatorial southerly winds, the Higher Andes experiment decreases the amplitude of ENSO, increases the phase asymmetry, and makes ENSO events less regular, resulting in a simulated ENSO that is more consistent with observations. The weaker ENSO cycle is related to stronger damping in the Higher Andes experiment according to an analysis of the Bjerknes index. Our overall results suggest that increasing the height of the Andes reduces biases in the mean state and improves the representation of ENSO in the tropical Pacific.

Robust Evaluation of ENSO in Climate Models: How Many Ensemble Members Are Needed?

AbstractLarge ensembles of model simulations require considerable resources, and thus defining an appropriate ensemble size for a particular application is an important experimental design criterion. We estimate the ensemble size (N) needed to assess a model’s ability to capture observed El Niño‐Southern Oscillation (ENSO) behavior by utilizing the recently developed International CLIVAR ENSO Metrics Package. Using the larger ensembles available from CMIP6 and the US CLIVAR Large Ensemble Working Group, we find that larger ensembles are needed to robustly capture baseline ENSO characteristics (N > 50) and physical processes (N > 50) than the background climatology (N ≥ 12) and remote ENSO teleconnections (N ≥ 6). While these results vary somewhat across metrics and models, our study quantifies how larger ensembles are required to robustly evaluate simulated ENSO behavior, thereby providing some guidance for the design of model ensembles.

ENSO phase-locking biases from the CMIP5 to CMIP6 models and a possible explanation

The El Niño-Southern Oscillation (ENSO) system is the most significant equatorial interannual climate variability pattern and has enormous global climate impacts. The ability to forecast ENSO accurately is crucially important to human livelihoods worldwide. ENSO is characterized by strong winter-peaking sea surface temperature (SST) anomalies in the central-eastern tropical Pacific during the mature phase. However, the bias in simulating ENSO phase-locking behavior persists in climate models. In this study, the ENSO seasonal phase-locking behaviors simulated in 42 Coupled Model Intercomparison Project Phase 6 (CMIP6) models are evaluated by comparing 43 CMIP5 models and observations. Only a few models (12 CMIP5 and 15 CMIP6) simulated ENSO with a majority proportion of winter-peaking events, which indicates that reasonable ENSO seasonal phase-locking is still a challenge for state-of-the-art climate models. Furthermore, the seasonal cycle of the zonal SST gradient along the equator can explain approximately 24% and 27% of the variance in the ENSO phase-locking for CMIP5 and CMIP6, respectively. In particular, the strengths of the zonal SST gradient in the central-eastern Pacific during boreal spring and autumn are crucial. The biases in simulating the seasonal changes in the zonal SST gradient influence the zonal advective feedback's strengths that respond to the anomalous SST of ENSO, therefore disturbing the simulation of ENSO phase-locking. Improvement of the simulated ENSO phase-locking should be realized by focusing on the zonal SST gradient's seasonal cycle.

Simulated Relationship between Wintertime ENSO and East Asian Summer Rainfall: From CMIP3 to CMIP6

El Nino–Southern Oscillation (ENSO) events have a strong influence on East Asian summer rainfall (EASR). This paper investigates the simulated ENSO–EASR relationship in CMIP6 models and compares the results with those in CMIP3 and CMIP5 models. In general, the CMIP6 models show almost no appreciable progress in representing the ENSO–EASR relationship compared with the CMIP5 models. The correlation coefficients in the CMIP6 models are relatively smaller and exhibit a slightly greater intermodel diversity than those in the CMIP5 models. Three physical processes related to the delayed effect of ENSO on EASR are further analyzed. Results show that, firstly, the relationships between ENSO and the tropical Indian Ocean (TIO) sea surface temperature (SST) in the CMIP6 models are more realistic, stronger, and have less intermodel diversity than those in the CMIP3 and CMIP5 models. Secondly, the teleconnections between the TIO SST and Philippine Sea convection (PSC) in the CMIP6 models are almost the same as those in the CMIP5 models, and stronger than those in the CMIP3 models. Finally, the CMIP3, CMIP5, and CMIP6 models exhibit essentially identical capabilities in representing the PSC–EASR relationship. Almost all the three generations of models underestimate the ENSO–EASR, TIO SST–PSC, and PSC–EASR relationships. Moreover, almost all the CMIP6 models that successfully capture the significant TIO SST–PSC relationship realistically simulate the ENSO–EASR relationship and vice versa, which is, however, not the case in the CMIP5 models.

Monitoring and predictive mapping of floristic biodiversity along a climatic gradient in ENSO's terrestrial core region, NW Peru

The tropical dry forests of NW Peru are heavily shaped by the El Niño Southern Oscillation (ENSO), where especially El Niño brings rain to arid to semi‐arid areas. However, the resulting effects on biodiversity patterns remain largely unknown as well as the effect of environmental variables on the floristic composition under varying rainfall patterns. Therefore, we studied the spatio‐temporal effects of different ENSO episodes on floristic biodiversity along a climatic gradient ranging from the coastal desert to the Andean foothills. We sampled 50 vegetation plots in four years representing different ENSO episodes. To highlight the spatio‐temporal changes in floristic composition and beta diversity across ENSO episodes, we predicted ordination scores with a Generalized Additive Model. We applied variation partitioning to test if topographic or edaphic variables gained in importance during more humid ENSO episodes. Additionally, we executed an irrigation–fertilization experiment to quantify the beneficial effects of the water–nutrient interaction under different simulated ENSO rainfall scenarios. Plant species richness increased under humid conditions during the humid La Niña (2012) and the moderate El Niño (2016), and slightly decreased under the very humid conditions during the coastal El Niño (2017). The spatial prediction revealed that specific vegetation formations became more pronounced with increasing water input, but that a large water surplus led to the disruption of the strict order along the climatic gradient. Edaphic and topographic variables gained in importance with increased water availability (2012 and 2016), however, this effect was not further amplified under very wet conditions (2017). The experiment showed that plant cover under Super Niño conditions was three times higher when fertilized. Overall, our spatial predictions concede detailed insights into spatio‐temporal ecosystem dynamics in response to varying rainfall caused by different ENSO episodes while the results of the experiment can support farmers regarding a sustainable agrarian management.

El Ni\xf1o/Southern Oscillation response to low-latitude volcanic eruptions depends on ocean pre-conditions and eruption timing

Proxy-based reconstructions of the past suggest that the Pacific ocean has often shown El Niño-like warming after low-latitude volcanic eruptions, while climate model simulations have suggested diverse responses. Here we present simulations from a coupled ocean–atmosphere model that illuminate the roles of ocean preconditioning, eruption magnitude and timing, and air–sea feedbacks in the El Niño/Southern Oscillation (ENSO) response to these eruptions. A deterministic component of the response, which dominates for boreal summer eruptions, leads to cooler tropical Pacific sea surface temperatures in the eruption year and El Niño-like warming the following year. A stochastic component is also important, especially for boreal winter eruptions. The simulated ENSO response depends nonlinearly on the eruption magnitude and the tropical Pacific conditions before the eruption. We conclude that adequate sampling is critical to accurately assess the ENSO responses in both models and observations.

Dynamics for El Ni\xf1o-La Ni\xf1a asymmetry constrain equatorial-Pacific warming pattern

The El Niño-Southern Oscillation (ENSO) results from the instability of and also modulates the strength of the tropical-Pacific cold tongue. While climate models reproduce observed ENSO amplitude relatively well, the majority still simulates its asymmetry between warm (El Niño) and cold (La Niña) phases very poorly. The causes of this major deficiency and consequences thereof are so far not well understood. Analysing both reanalyses and climate models, we here show that simulated ENSO asymmetry is largely proportional to subsurface nonlinear dynamical heating (NDH) along the equatorial Pacific thermocline. Most climate models suffer from too-weak NDH and too-weak linear dynamical ocean-atmosphere coupling. Nevertheless, a sizeable subset (about 1/3) having relatively realistic NDH shows that El Niño-likeness of the equatorial-Pacific warming pattern is linearly related to ENSO amplitude change in response to greenhouse warming. Therefore, better simulating the dynamics of ENSO asymmetry potentially reduces uncertainty in future projections.

A review of progress in coupled ocean-atmosphere model developments for ENSO studies in China

El Nino-Southern Oscillation (ENSO) is the strongest interannual signal that is produced by basinscale processes in the tropical Pacific, with significant effects on weather and climate worldwide. In the past, extensive and intensive international efforts have been devoted to coupled model developments for ENSO studies. A hierarchy of coupled ocean-atmosphere models has been formulated; in terms of their complexity, they can be categorized into intermediate coupled models (ICMs), hybrid coupled models (HCMs), and fully coupled general circulation models (CGCMs). ENSO modeling has made signifiscant progress over the past decades, reaching a stage where coupled models can now be used to successfully predict ENSO events 6 months to one year in advance. Meanwhile, ENSO exhibits great diversity and complexity as observed in nature, which still cannot be adequately captured by current state-of-the-art coupled models, presenting a challenge to ENSO modeling. We primarily reviewed the long-term efforts in ENSO modeling continually and steadily made at different institutions in China; some selected representative examples are presented here to review the current status of ENSO model developments and applications, which have been actively pursued with noticeable progress being made recently. As ENSO simulations are very sensitive to model formulations and process representations etc., dedicated efforts have been devoted to ENSO model developments and improvements. Now, different ocean-atmosphere coupled models have been available in China, which exhibit good model performances and have already had a variety of applications to climate modeling, including the Coupled Model Intercomparison Project Phase 6 (CMIP6). Nevertheless, large biases and uncertainties still exist in ENSO simulations and predictions, and there are clear rooms for their improvements, which are still an active area of researches and applications. Here, model performances of ENSO simulations are assessed in terms of advantages and disadvantages with these differently formulated coupled models, pinpointing to the areas where they need to be further improved for ENSO studies. These analyses provide valuable guidance for future improvements in ENSO simulations and predictions.

Effects of Tropical Cyclones on ENSO

AbstractNumerous studies have investigated the role of El Niño–Southern Oscillation (ENSO) in modulating the activity of tropical cyclones (TCs) in the western Pacific on interannual time scales, but the effects of TCs on ENSO are less discussed. Some studies have found that TCs sharply increase surface westerly anomalies over the equatorial western–central Pacific and maintain them there for a few days. Given the strong influence of equatorial surface westerly wind bursts on ENSO, as confirmed by much recent literature, the effects of TCs on ENSO may be much greater than previously expected. Using recently released observations and reanalysis datasets, it is found that the majority of near-equatorial TCs (simply TCs hereafter) are associated with strong westerly anomalies at the equator, and the number and longitude of TCs are significantly correlated with ENSO strength. When TC-related wind stresses are added into an intermediate coupled model, the simulated ENSO becomes more irregular, and both ENSO magnitude and skewness approach those of observations, as compared with simulations without TCs. Adding TCs into the model system does not break the linkage between the heat content anomaly and subsequent ENSO event in the model, which manifest the classic recharge–discharge ENSO dynamics. However, the influence of TCs on ENSO is so strong that ENSO magnitude and sometimes its final state—that is, either El Niño or La Niña—largely depend on the number and timing of TCs during the event year. Our findings suggest that TCs play a prominent role in ENSO dynamics, and their effects must be considered in ENSO forecast models.

Prominent Precession Band Variance in ENSO Intensity Over the Last 300,000 Years

AbstractThree transient National Center for Atmospheric Research Community Climate System Model, version 3 model simulations were analyzed to study the responses of El Niño–Southern Oscillation (ENSO) and the equatorial Pacific annual cycle (AC) to external forcings over the last 300,000 years. The time‐varying boundary conditions of insolation, greenhouse gases, and continental ice sheets, accelerated by a factor of 100, were sequentially added in these simulations. The simulated ENSO and AC amplitudes change in phase, and both have pronounced precession band variance (~21,000 years). The precession‐modulated slow (orbital time scales) ENSO evolution is dominated linearly by the change of the coupled ocean‐atmosphere instability, notably the Ekman upwelling feedback and thermocline feedback. In contrast, the greenhouse gases and ice sheet forcings (~100,000‐year cycles) are opposed to each other as they influence ENSO variability through changes in AC amplitude via a common nonlinear frequency entrainment mechanism. The acceleration technique could dampen and delay the precession signals below the surface ocean associated with ENSO intensity.

Atmospheric Convection Dominates Genesis of ENSO Asymmetry

AbstractObserved El Niño–Southern Oscillation (ENSO) events exhibit distinct amplitude and evolution asymmetries due to nonlinear interactions between sea surface temperature (SST), equatorial zonal wind stress, and thermocline depth anomalies. Establishment of atmospheric convection leads to a nonlinear response of zonal winds to SST, but its relative importance to nonlinear oceanic feedbacks remains unclear. Using a recharge oscillator model modified to incorporate various nonlinearities estimated from observations, we show that the nonlinear wind response to SST alone can induce a nonlinear response of the thermocline to winds and that of SST to the thermocline, as winds affect the growth of SST and damping of thermocline anomalies through the recharge/discharge process. Oceanic nonlinear feedbacks enhance the simulated ENSO asymmetries only when the nonlinear atmospheric feedback is present. Our result suggests that the observed strengthening of ENSO variability in the past century is attributable to an increase in the nonlinear atmospheric feedback.

The effect of the equatorial Pacific cold SST bias on simulated ENSO teleconnections to the North Pacific and California

Precipitation in California is modulated by variability in the tropical Pacific associated with El Nino/Southern Oscillation (ENSO): more rainfall is expected during El Nino episodes, and reduced rainfall during La Nina. It has been suggested that besides the shape and location of the sea surface temperature (SST) anomaly this remote connection depends on the strength and location of the atmospheric convection response in the tropical Pacific. Here we show in a perturbed physics ensemble of the Kiel Climate Model and CMIP5 models that due to a cold equatorial SST bias many climate models are in a La Nina-like mean state, resulting in a too westward position of the rising branch of the Pacific Walker Circulation. This in turn results in a convective response along the equator during ENSO events that is too far west in comparison to observations. This effect of the equatorial cold SST bias is not restricted to the tropics, moreover it leads to a too westward SLP response in the North Pacific and too westward precipitation response that does not reach California. Further we show that climate models with a reduced equatorial cold SST bias have a more realistic representation of the spatial asymmetry of the teleconnections between El Nino and La Nina.

Simulated ENSO's impact on tropical cyclone genesis over the western North Pacific in CMIP5 models and its changes under global warming

El Niño–Southern Oscillation (ENSO) plays an important role in modulating the location of tropical cyclone (TC) genesis over the western North Pacific (WNP). This study evaluated the simulation of the ENSO's impact on WNP TC genesis in 10 CMIP5 models based on a TC detection method, and projected its changes under global warming using the historical and the representative concentration pathway 8.5 (RCP8.5) simulations. The observed southeast–northwest shift role of ENSO in the WNP TC genesis location can be well reproduced in most of the models, although the strength of the ENSO's impact is underestimated as the underestimated climatological TC genesis frequency in these models. Moreover, we found the WNP TC during both El Niño and La Niña events shows an apparent eastwards shift under global warming. However, this eastwards shift of WNP TC genesis could be associated with the changes in climatological TC genesis but not the changes in the ENSO's impact. The projected changes in the ENSO's impact on WNP TC genesis is not as certain as we expected based on the previous conclusions of the robust changes in ENSO's impact on large‐scale environment. As a result, we suggest that both the TC genesis climatology and ENSO's impact on TC genesis simulated in the models need improvement in future to project the changes in ENSO's impact under global warming, and more models with 6‐hourly outputs used to detect TCs are needed to increase the confidence of multi‐model ensemble projections.

ENSO Features, Dynamics, and Teleconnections to East Asian Climate as Simulated in CAMS-CSM

This study evaluates the performance of CAMS-CSM (the climate system model of the Chinese Academy of Meteorological Sciences) in simulating the features, dynamics, and teleconnections to East Asian climate of the El Nino–Southern Oscillation (ENSO). In general, fundamental features of ENSO, such as its dominant patterns and phase-locking features, are reproduced well. The two types of El Nino are also represented, in terms of their spatial distributions and mutual independency. However, the skewed feature is missed in the model and the simulation of ENSO is extremely strong, which is found—based on Bjerknes index assessment—to be caused by underestimation of the shortwave damping effect. Besides, the modeled ENSO exhibits a regular oscillation with a period shorter than observed. By utilizing the Wyrtki index, it is suggested that this periodicity bias results from an overly quick phase transition induced by feedback from the thermocline and zonal advection. In addition to internal dynamics of ENSO, its external precursors—such as the North Pacific Oscillation with its accompanying seasonal footprinting mechanism, and the Indian Ocean Dipole with its 1-yr lead correlation with ENSO—are reproduced well by the model. Furthermore, with respect to the impacts of ENSO on the East Asian summer monsoon, although the anomalous Philippine anticyclone is reproduced in the post-El Nino summer, it exhibits an eastward shift compared with observation; and as a consequence, the observed flooding of the Yangtze River basin is poorly represented, with unrealistic air–sea interaction over the South China Sea being the likely physical origin of this bias. The response of wintertime lower-tropospheric circulation to ENSO is simulated well, in spite of an underestimation of temperature anomalies in central China. This study highlights the dynamic processes that are key for the simulation of ENSO, which could shed some light on improving this model in the future.

An Assessment of ENSO Stability in CAMS Climate System Model Simulations

We present an overview of the El Nino–Southern Oscillation (ENSO) stability simulation using the Chinese Academy of Meteorological Sciences climate system model (CAMS-CSM). The ENSO stability was quantified based on the Bjerknes (BJ) stability index. Generally speaking, CAMS-CSM has the capacity of reasonably representing the BJ index and ENSO-related air–sea feedback processes. The major simulation biases exist in the underestimated thermodynamic damping and thermocline feedbacks. Further diagnostic analysis reveals that the underestimated thermodynamic feedback is due to the underestimation of the shortwave radiation feedback, which arises from the cold bias in mean sea surface temperature (SST) over central–eastern equatorial Pacific (CEEP). The underestimated thermocline feedback is attributed to the weakened mean upwelling and weakened wind–SST feedback (μa) in the model simulation compared to observation. We found that the weakened μa is also due to the cold mean SST over the CEEP. The study highlights the essential role of reasonably representing the climatological mean state in ENSO simulations.

Error compensation of ENSO atmospheric feedbacks in climate models and its influence on simulated ENSO dynamics

Common problems in state-of-the-art climate models are a cold sea surface temperature (SST) bias in the equatorial Pacific and the underestimation of the two most important atmospheric feedbacks operating in the El Nino/Southern Oscillation (ENSO): the positive, i.e. amplifying wind-SST feedback and the negative, i.e. damping heat flux-SST feedback. To a large extent, the underestimation of those feedbacks can be explained by the cold equatorial SST bias, which shifts the rising branch of the Pacific Walker Circulation (PWC) too far to the west by up to 30°, resulting in an erroneous convective response during ENSO events. Based on simulations from the Kiel Climate Model (KCM) and the 5th phase of Coupled Model Intercomparison Project (CMIP5), we investigate how well ENSO dynamics are simulated in case of underestimated ENSO atmospheric feedbacks (EAF), with a special focus on ocean–atmosphere coupling over the equatorial Pacific. While models featuring realistic atmospheric feedbacks simulate ENSO dynamics close to observations, models with underestimated EAF exhibit fundamental biases in ENSO dynamics. In models with too weak feedbacks, ENSO is not predominantly wind-driven as observed; instead ENSO is driven significantly by a positive shortwave radiation feedback. Thus, although these models simulate ENSO, which in terms of simple indices is consistent with observations, it originates from very different dynamics. A too weak oceanic forcing on the SST via the positive thermocline, the Ekman and the zonal advection feedback is compensated by weaker atmospheric heat flux damping. The latter is mainly caused by a biased shortwave-SST feedback that erroneously is positive in most climate models. In the most biased models, the shortwave-SST feedback contributes to the SST anomaly growth to a similar degree as the ocean circulation. Our results suggest that a broad continuum of ENSO dynamics can exist in climate models and explain why climate models with less than a half of the observed EAF strength can still depict realistic ENSO amplitude.