El Nino-Southern Oscillation Events Research Articles

The sampling method for optimal precursors of El Niño–Southern Oscillation events

Abstract. The El Niño–Southern Oscillation (ENSO) is a significant climate phenomenon that appears periodically in the tropical Pacific. The intermediate coupled ocean–atmosphere Zebiak–Cane (ZC) model is the first and classical one designed to numerically forecast the ENSO events. Traditionally, the conditional nonlinear optimal perturbation (CNOP) approach has been used to capture optimal precursors in practice. In this paper, based on state-of-the-art statistical machine learning techniques1, we investigate the sampling algorithm proposed in Shi and Sun (2023) to obtain optimal precursors via the CNOP approach in the ZC model. For the ZC model, or more generally, the numerical models with a large number O(104−105) of degrees of freedom, the numerical performance, regardless of the statically spatial patterns and the dynamical nonlinear time evolution behaviors as well as the corresponding quantities and indices, shows the high efficiency of the sampling method compared to the traditional adjoint method. The sampling algorithm does not only reduce the gradient (first-order information) to the objective function value (zeroth-order information) but also avoids the use of the adjoint model, which is hard to develop in the coupled ocean–atmosphere models and the parameterization models. In addition, based on the key characteristic that the samples are independently and identically distributed, we can implement the sampling algorithm by parallel computation to shorten the computation time. Meanwhile, we also show in the numerical experiments that the important features of optimal precursors can still be captured even when the number of samples is reduced sharply.

Influence of El Niño on parameters of the middle and upper atmosphere over Eastern Siberia according to reanalysis and model data in winter

One of the most important climate-forming phenomena in the ocean—atmosphere system is the El Niño Southern Oscillation (ENSO) events, which manifest themselves with varying intensity in almost all regions of the globe. The central regions of Eurasia are farthest from the tropics of the Pacific Ocean, the regions where ENSO originates. There are different points of view regarding the nature of the ENSO effect on these regions. In the presented work, the influence of ENSO on the upper atmosphere of the Northern Hemisphere and, in particular, on the upper atmosphere of Eastern Siberia is estimated using model calculations and reanalysis data. The results of the analysis show that the large-scale structures of the atmospheric response to the ENSO events in the Northern Hemisphere are similar according to modeling and reanalysis, yet the regions of Eastern Siberia are on the periphery of the main signal and there are significant differences in estimated effects from one case of El Niño and La Niña to another. In January, ENSO has the greatest impact on the middle atmosphere of the polar regions of the Northern Hemisphere. Over Eurasia and Eastern Siberia, the atmospheric response to the ENSO events turned out to be weak or absent.

Влияние Эль-Ниньо на параметры средней и верхней атмосферы над Восточной Сибирью по данным реанализа и моделирования в зимний период

One of the most important climate-forming phenomena in the ocean—atmosphere system is the El Niño Southern Oscillation (ENSO) events, which manifest themselves with varying intensity in almost all regions of the globe. The central regions of Eurasia are farthest from the tropics of the Pacific Ocean, the regions where ENSO originates. There are different points of view regarding the nature of the ENSO effect on these regions. In the presented work, the influence of ENSO on the upper atmosphere of the Northern Hemisphere and, in particular, on the upper atmosphere of Eastern Siberia is estimated using model calculations and reanalysis data. The results of the analysis show that the large-scale structures of the atmospheric response to the ENSO events in the Northern Hemisphere are similar according to modeling and reanalysis, yet the regions of Eastern Siberia are on the periphery of the main signal and there are significant differences in estimated effects from one case of El Niño and La Niña to another. In January, ENSO has the greatest impact on the middle atmosphere of the polar regions of the Northern Hemisphere. Over Eurasia and Eastern Siberia, the atmospheric response to the ENSO events turned out to be weak or absent.

Deep learning with autoencoders and LSTM for ENSO forecasting

El Niño Southern Oscillation (ENSO) is the prominent recurrent climatic pattern in the tropical Pacific Ocean with global impacts on regional climates. This study utilizes deep learning to predict the Niño 3.4 index by encoding non-linear sea surface temperature patterns in the tropical Pacific using an autoencoder neural network. The resulting encoded patterns identify crucial centers of action in the Pacific that serve as predictors of the ENSO mode. These patterns are utilized as predictors for forecasting the Niño 3.4 index with a lead time of at least 6 months using the Long Short-Term Memory (LSTM) deep learning model. The analysis uncovers multiple non-linear dipole patterns in the tropical Pacific, with anomalies that are both regionalized and latitudinally oriented that should support a single inter-tropical convergence zone for modeling efforts. Leveraging these encoded patterns as predictors, the LSTM - trained on monthly data from 1950 to 2007 and tested from 2008 to 2022 - shows fidelity in predicting the Niño 3.4 index. The encoded patterns captured the annual cycle of ENSO with a 0.94 correlation between the actual and predicted Niño 3.4 index for lag 12 and 0.91 for lags 6 and 18. Additionally, the 6-month lag predictions excel in detecting extreme ENSO events, achieving an 85% hit rate, outperforming the 70% hit rate at lag 12 and 55% hit rate at lag 18. The prediction accuracy peaks from November to March, with correlations ranging from 0.94 to 0.96. The average correlations in the boreal spring were as large as 0.84, indicating the method has the capability to decrease the spring predictability barrier.

Unveiling the role of tropical Pacific on the emergence of ice-free Arctic projections

The observed sea ice concentration (SIC) over the Arctic has receded substantially in recent decades, and future model projections predict a seasonally ice-free Arctic in the second half of this century. Nevertheless, the impact of the Pacific on Arctic sea ice projections has yet to receive much attention. Observations show that summertime Arctic SIC growth events are related to the weakening of the Aleutian low and cooling events over the equatorial Pacific, and vice versa. We demonstrate that under various Coupled Model Intercomparison Project Phase 6 projections, the models in which the impact of El Niño-driven SIC loss is significantly higher than the La Niña-related SIC growth tend to turn seasonally ice-free by about 10–20 years ahead of the ensemble mean under high-emission future scenarios. We show how the non-linear impact of the El Niño Southern Oscillation (ENSO) on Arctic SIC resulted in a faster decline of summertime sea ice. The ENSO-related SIC changes in the multi-model ensemble mean of Arctic SIC are considerably lower than the internal variability and anthropogenic-driven changes. However, the asymmetric interannual ENSO effects over several decades and the resultant changes in surface heat fluxes over the Arctic lead to significant differences in the timing of sea ice extinction. Our results suggest that climate models must capture the realistic tropical Pacific–Arctic teleconnection to better predict the long-term evolution of the Arctic climate.

On The Interannual Variability of Indonesian Monsoon Rainfall (IMR): A Literature Review of The Role of its External Forcing

The IMR variability is notorious for its hydrometeorological disasters. This paper examines recent studies on IMR and the main factors controlling its variability. The focus of this study is to investigate the impact of the atmosphere-ocean interaction that acts as the external forcing of IMR in the tropical Indian and Pacific Oceans. Specifically, the study will examine the influence of two climate phenomena, namely the El Nino Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) and their interdecadal changes associated Pacific Decadal Oscillation (PDO), on the IMR. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach. Furthermore, data sets (such as rainfall, wind field, and SST) spanning 1990-2020 were used to verify the key findings. In general, this study concludes that the majority of the authors coincided with the following conclusion: ENSO and IOD events impact IMR by changing its amplitude, duration, intensity, and frequency of mean and extreme rainfall. Additionally, it has been shown that their impacts on IMR are most substantial during the dry seasons, specifically in June, July, and August (JJA), and not as strong as during the wet seasons, specifically in December, January, and February (DJF). Spatially, the effects of ENSO and IOD on IMR variability are clearly found more eastward and westward of the region, respectively. The expansions towards the east and west directions were facilitated by the displacement of the ascending and descending of Walker circulation patterns in the Indonesian region, respectively. Given the interannual fluctuations in IMR, caused mainly by ocean-atmosphere interactions, the knowledge gap of atmospheric factors like the Quasi-Biennial Oscillation (QBO) must be investigated in the future, as suggested by previous research and our preliminary study.

Quantifying ENSOs Impact on Australia's Regional Monthly Rainfall Risk

AbstractThe El Niño‐Southern Oscillation (ENSO) is considered an important driver of rainfall variability in Australia, amongst many other global locations. Despite knowledge of the expected modulation of seasonal rainfall by ENSO, there is no consistently used method to quantify the role that specific ENSO events play in driving the observed anomalous rainfall. In this manuscript we adapt the Fraction of Attributable Risk (FAR) method, commonly used to identify the anthropogenic impact on a particular event, to quantify the impact of ENSO on the occurrence of monthly rainfall anomalies. We also explicitly calculate the ENSO induced change in risk and the FAR for all observed spring rainfall rates for our eastern Australian regions. A prominent role for ENSO in driving the large spring 2022 rainfall anomalies is identified. Though we choose to focus on ENSOs impact on rainfall in various Eastern Australian regions, the results are applicable to other climate modes, regions and climatic variables.

The dynamics of the El Niño–Southern Oscillation diversity in the recharge oscillator framework

This study investigates the observed El Niño-Southern Oscillation (ENSO) dynamics for the eastern Pacific (EP) and central Pacific (CP) events in reference to the canonical ENSO (T). We use the recharge oscillator (ReOsc) model concept to describe the ENSO phase space and polar coordinate statistics, based on the interaction of sea surface temperature (T) and thermocline depth (h), for the different types of ENSO events. We further look at some important statistical characteristics, such as power spectrum and cross-correlation as essential parameters for understanding the dynamics of ENSO. The results show that the dynamics of the EP and CP events are very different from each other and from the canonical ENSO events. The canonical ENSO (T) events fit closest to the idealised ReOsc model and has the most clearly oscillating ENSO phase space, suggesting it is the most predictable ENSO index. The EP phase space evolution is similar to the canonical ENSO, but the phase transitions are less clear, suggesting less of an oscillatory nature and that the index is more focussed on extreme El Niño and discharge states. The CP phase space, in turn, does not have a clear propagation through all phases and are strongly skewed towards the La Niña state. The interaction between CP and h are much weaker, making the mode less predictable. Wind forced shallow water model simulations show that the CP winds spatial pattern do not force significant h tendencies, strongly reducing the delayed negative feedback, which is essential for the ENSO cycle.

Strengthened impact of boreal winter North Pacific Oscillation on ENSO development in warming climate

The North Pacific Oscillation (NPO), an important mode of atmospheric variability, is a crucial trigger for the development of El Niño-Southern Oscillation (ENSO) via the seasonal footprinting mechanism. How the NPO effect on ENSO changes in response to greenhouse warming remains unclear, however. Here, using climate model simulations under high-emission scenarios, we show that greenhouse warming leads to an enhanced influence of NPO on ENSO as is manifested by enhanced responses of winter sea surface temperature (SST), precipitation and wind anomalies in the equatorial Pacific to the preceding winter NPO. The strengthened NPO impact is also reflected in an increased frequency of NPO events that are followed by ENSO events. Warmer background SST enhances the wind-evaporation-SST feedback over the subtropical North Pacific due to a nonlinear SST-evaporation relationship. This strengthens the NPO-generated surface zonal wind anomalies over the equatorial western-central Pacific, which trigger ENSO. Increased impact of winter NPO on ENSO could enable prediction of interannual variability at longer leads.

A hot Spring for Mexico in 2024

Hot days observed during February 2024, reaching 30oC in Mexico City, have made its inhabitants forget that it was the winter season, characterized by dry and cool weather. While such extreme events are often associated with climate change, the current state of the coupled ocean-atmosphere system indicates the last months of an El Niño state, after an expectation of this to be within the top 5 El Niño – Southern Oscillation (ENSO) events (https://cutt.ly/rw1h4T26). The effects of ENSO on the seasonal climate have been widely studied (Philander 1990), and their impacts on Mexico have also been documented (Magana, 2004). Recent seasonal forecasts suggest a progression towards a neutral state for the April-June 2024 season. And further projections indicate a 55% of chance of La Niña developing during the rainy season of 2024. This suggests an end to dry and warm conditions and the possibility of increased rainfall. (Magaña et al. 2003). However, with an ongoing drought over most of the Mexican region, and a water crisis affecting central Mexico, it seems that the seasonal forecasts based on ENSO projections set up the stage for a critical situation for most of the country during the Spring season.

Variability of Fine‐Scale Chlorophyll Fronts in the Tīkapa Moana Te Moananui ā Toi Hauraki Gulf, Aotearoa New Zealand

AbstractAotearoa New Zealand's marine environment is heavily impacted by El Niño Southern Oscillation (ENSO). Little is known about the effect of ENSO on oceanographic properties in the area or their consequences on the distribution of marine organisms. Here we characterize the spatio‐temporal variability of fine‐scale fronts (<10 km) in the area of the Tīkapa Moana Te Moananui ā Toi Hauraki Gulf (HG) and investigate how it is impacted by dominant wind direction, seasonality, and ENSO phase. We processed satellite Ocean‐Land Color Instrument images from 2016 to 2022 with a fit‐for‐purpose version of the Belkin and O'Reilly frontal detection algorithm. We find coherent shifts in the position of fine‐scale features depending on the ENSO phase, with El Niño isolating the gulf sub‐regions and La Niña connecting them together. Overall, fronts tend to co‐locate with the 70 and 40 m isobaths in the outer and inner HG respectively, and their locations shift close or away from shore in response to changes in dominant wind direction. Furthermore, offshore frontal occurrences increase during winter and spring, and nearshore ones increase during summer and autumn. Our results sketch a first assessment of the distribution of fine‐scale features in a biologically important yet understudied region.

Multi-scale spatial features and temporal attention mechanisms: advancing the accuracy of ENSO prediction

The exponential progression in oceanic observational technology has fostered the accumulation of substantial time series data pivotal for predictions in ocean meteorology. Foremost among the phenomena observed is El Niño-Southern Oscillation (ENSO), a critical determinant in the interplay of global ocean atmosphere interactions, with its severe manifestations inducing extreme meteorological conditions. Therefore, precisely predicting ENSO events carries immense gravitas. Historically, predictions hinged primarily on dynamic models and statistical approaches; however, the intricate and multifaceted spatiotemporal dynamics of ENSO events have often impeded the accuracy of these traditional methodologies. A notable lacuna in contemporary research is the insufficient exploration of long-term dependencies within oceanic data and the suboptimal integration of spatial information derived from spatiotemporal data. To address these limitations, this study introduces a forward-thinking ENSO prediction framework synergizing multiscale spatial features with temporal attention mechanisms. This innovation facilitates a more profound exploration of temporal and spatial domains, enhancing the retention of extensive-period data while optimizing the use of spatial information. Preliminary analyses executed on the global ocean data assimilation system dataset attest to the superior efficacy of the proposed method, underscoring a substantial improvement over established methods including SA-convolutional long short-term memory, particularly in facilitating long-term predictions.The source code and datasets are provided. The code is available at https://github.com/tse1998/ENSO-prediction.

ENSO effects on the relationship between aerosols and evapotranspiration in the south of the Amazon biome

The effects of the El Nino-Southern Oscillation (ENSO) events have local, regional, and global consequences for water regimes, causing floods or extreme drought events. Tropical forests are strongly affected by ENSO, and in the case of the Amazon, its territorial extension allows for a wide variation of these effects. The prolongation of drought events in the Amazon basin contributes to an increase in gas and aerosol particle emissions mainly caused by biomass burning, which in turn alter radiative fluxes and evapotranspiration rates, cyclically interfering with the hydrological regime. The ENSO effects on the interactions between aerosol particles and evapotranspiration is a critical aspect to be systematically investigated. Therefore, this study aimed to evaluate the ENSO effect on a site located on the southern portion of the Amazonian region. In addition to quantifying and testing possible differences between aerosols and evapotranspiration under different ENSO classes (El Niño, La Niña and Neutrality), this study also evaluated possible variations in evapotranspiration as a function of the aerosol load. A highly significant difference was found for air temperature, relative humidity and aerosol load between the El Niño and La Niña classes. For evapotranspiration, significant differences were found for the El Niño and La Niña classes and for El Niño and Neutrality classes. Under the Neutrality class, the aerosol load correlated significantly with evapotranspiration, explaining 20% of the phenomenon. Under the El Niño and La Niña classes, no significant linear correlation was found between aerosol load and evapotranspiration. However, the results showed that for the total data set, there is a positive and significant correlation between aerosol and evapotranspiration. It increases with a quadratic fit, i.e., the aerosol favors evapotranspiration rates up to a certain concentration threshold. The results obtained in this study can help to understand the effects of ENSO events on atmospheric conditions in the southern Amazon basin, in addition to elucidating the role of aerosols in feedback to the water cycle in the region.

A Relative Sea Surface Temperature Index for Classifying ENSO Events in a Changing Climate

Abstract El Niño–Southern Oscillation (ENSO) is often characterized through the use of sea surface temperature (SST) departures from their climatological values, as in the Niño-3.4 index. However, this approach is problematic in a changing climate when the climatology itself is varying. To address this issue, van Oldenborgh et al. proposed a relative Niño-3.4 SST index, which subtracts the tropical mean SST anomaly from the Niño-3.4 index and multiplies by a scaling factor. We extend their work by providing a simplified calculation procedure for the scaling factor, and confirm that the relative index demonstrates reduced sensitivity to climate change and multidecadal variability. In particular, we show in three observational SST datasets that the relative index provides a more consistent classification of historical El Niño and La Niña oceanic conditions that is more robust across climatological periods compared to the nonrelative index. Forecast skill of the relative Niño-3.4 index in the North American Multimodel Ensemble (NMME) and ACCESS-S2 is slightly reduced for targets during the first half of the year because subtracting the tropical mean removes a source of additional skill. For targets in the second half of the year, the relative and nonrelative indices are equally skillful. Observed ENSO teleconnections in 200-hPa geopotential height and precipitation during key seasons are sharper and explain more variability over Australia and the contiguous United States when computed with the relative index. Overall, the relative Niño-3.4 index provides a more robust option for real-time monitoring and forecasting ENSO in a changing climate. Significance Statement The goal of this study is to further explore a relative sea surface temperature index for monitoring and prediction of El Niño–Southern Oscillation. Sea surface temperature indices are typically computed as a difference from a 30-yr climatological average, and El Niño and La Niña events occur when values exceed a certain threshold. This method is suitable when the climate is stationary. However, because of climate change and other lower-frequency variations, historical El Niño and La Niña events are reclassified depending on which climatological period is selected. A relative index is investigated to ameliorate this problem.

Spatiotemporal characteristics of meteorological drought events in 34 major global river basins during 1901–2021

Meteorological drought is a crucial driver of various types of droughts; thus, identifying the spatiotemporal characteristics of meteorological drought at the basin scale has implications for ecological and water resource security. However, differences in drought characteristics between river basins have not been clearly elucidated. In this study, we identify and compare meteorological drought events in 34 major river basins worldwide using a three-dimensional drought-clustering algorithm based on the standardised precipitation evapotranspiration index on a 12-month scale from 1901 to 2021. Despite synchronous increases in precipitation and potential evapotranspiration (PET), with precipitation increasing by more than three times the PET, 47 % (16/34) of the basins showed a tendency towards drought in over half their basin areas. Drought events occurred frequently, with more than half identified as short-term droughts (lasting less than or equal to three months). Small basins had a larger drought impact area, with major drought events often originating from the basin boundaries and migrating towards the basin centre. Meteorological droughts were driven by changes in sea surface temperature (SST), especially the El Niño Southern Oscillation (ENSO) or other climate indices. Anomalies in SST and atmospheric circulation caused by ENSO events may have led to altered climate patterns in different basins, resulting in drought events. These results provide important insights into the characteristics and mechanisms of meteorological droughts in different river basins worldwide.

Impact of Solar Activity and ENSO on the Early Summer Asian Monsoon During the Last Millennium

AbstractThe Asian Monsoonal rainfall accounts for the majority of annual regional precipitation in East and South Asia and could be remotely regulated by El Niño‐Southern Oscillation (ENSO). Besides, several paleoclimate records and simulations have indicated solar signals in the Asian Monsoon, implying the impact of solar activity on the regional monsoon precipitation. By conducting multi‐linear regression analysis to the solar irradiance forced single‐forcing experiment in the last millennium, this study presents the comparison of solar and ENSO effects on monsoonal precipitation in South and East Asia during early summer (May–June). Increased total solar irradiance during high solar activity years tends to trigger a favorable environment for developing monsoon onset, leading to more precipitation against ENSO‐related patterns over Southeast and South Asia before peak‐summer (July–August). The result supports reconstructed terrestrial records and underlines considerable influences of the solar cycle on the variation of the Asian Summer Monsoon.

Enso influence on water vapor transport and thermodynamics over Northwestern South America

The interannual variability of hydroclimatic conditions in Northwestern South America, especially precipitation, is mainly influenced by the El Niño–Southern Oscillation (ENSO). We explore potential mechanisms that affect precipitation occurrence in Northwestern South America during El Niño and La Niña events over the period 1980–2019, using data from the ERA5 reanalysis. We look at the atmospheric moisture contribution from different sources using the Dynamic Recycling Model to track water vapor trajectories. Interestingly, conditions with reduced precipitation during El Niño events can take place along with increased precipitable water. To understand this, we analyze thermodynamic conditions in the atmosphere that are necessary for precipitation to occur over the region, such as convective available potential energy, convective inhibition, lifting condensation level, and low-level relative humidity. With this approach, we find more favorable thermodynamic conditions for the occurrence of precipitation during La Niña events, even if the content of water vapor is equal or even less than during El Niño events. We also look at the structure of the regional Hadley and Walker circulation in both types of events and find that a weaker ascending motion during El Niño events also inhibits convection. This study provides an integral picture of how precipitation anomalies over Northwestern South America during ENSO events are related to dynamic and thermodynamic conditions and sources of atmospheric moisture.

Evaluating the Performance of the North Pacific Victoria Mode as an ENSO Predictor Based on Multimodel Ensemble Hindcasts

Abstract The Victoria mode (VM), similar to the Pacific meridional mode (PMM), is forced by North Pacific Oscillation atmospheric variability. Both the boreal spring VM and PMM can trigger the onset of El Niño–Southern Oscillation (ENSO) events in the following winter. Previous studies have examined the precursor relationship between the PMM and ENSO based on a subset of models drawn from the North American Multimodel Ensemble (NMME) system. They suggested that the PMM can act as a precursor to El Niño events, whereas it fails to predict La Niña events. Utilizing the hindcasts of these models from NMME, this study further investigates the role of the VM as an ENSO predictor to examine the real usefulness of the VM for ENSO prediction. When compared with the PMM, the VM can predict both El Niño and La Niña events with some skill, showing that the VM seems to be a more reliable predictor of ENSO. We found that the unique role of the VM in ENSO prediction originates from the symmetric impact of the VM on ENSO events. The VM, as a basin-scale sea surface temperature (SST) pattern, combines the role of the SST over the subtropical northeastern Pacific that is similar to the PMM in initializing El Niño events with that of the SST over the western North Pacific that is different from PMM in initializing La Niña events, resulting in the symmetric effect of the VM on ENSO prediction. Thus, it is useful to consider VM variability as a reference for ENSO prediction. Significance Statement We aim to investigate whether the robust relationship between the boreal spring Victoria mode (VM) and the following winter ENSO in observations and climate models has any real predictive use, thus bridging the gap between theory and practical application. Our analyses based mainly on model hindcast datasets examine the forecasting skill of the VM for El Niño and La Niña events. We also reveal the symmetric impact of VM on ENSO through the analysis of observations, which explains the VM’s skill in predicting both El Niño and La Niña events. This study deepens our understanding of the effect of North Pacific SST variability on ENSO.

Interannual Variations of the North Equatorial Current Across the Pacific Ocean

AbstractThe interannual variation of the North Equatorial Current (NEC) across the North Pacific Ocean and the modulation of the Pacific Decadal Oscillation (PDO) are investigated based on both observations and reduced gravity model experiments. Results reveal that the interannual variation of the NEC is highly related to El Niño‐Southern Oscillation (ENSO) with unsynchronized variations both in zonal and meridional structure. The tropical and subtropical gyre branches of the NEC (NEC‐S and NEC‐N) behave antiphase variation during El Niño events with the transport of the former being enhanced and the latter being weakened across the Pacific. The NEC axis in the western/eastern Pacific shifts northward/southward during El Niño events, consistent with the meridional shift of the zero‐line of wind stress curl. Model experiments indicate that Rossby waves mainly modulate the NEC near the western boundary and the NEC‐N, while Ekman pumping modulates NEC‐S in the western basin. Meanwhile, the relationship between the interannual variation of the NEC and ENSO events is significantly modulated by different PDO phases. The PDO cold phase favors a much closer connection between the NEC and the Niño 3.4 index. The dynamics lie in that PDO‐related wind stress curl and sea level anomalies are consistent with that of El Niño, favoring the enhanced correlation between NEC and El Niño. The reverse is true for the warm phase. These results will contribute to a better understanding of the behavior of the tropical Pacific Ocean circulation and its role in climate change.

Diagnosing the Quasi-Equilibrium Response of ENSO Variability under a Range of CO2 Levels

Abstract Several recent studies have highlighted differences in simulated properties of El Niño–Southern Oscillation (ENSO) under transient and equilibrium responses to increasing CO2. However, the reasons behind these disparate responses and the extent to which they are robust to different scales of CO2 forcing remain unclear. In this study, we adopt a climate system model with reduced SST bias in the eastern tropical Pacific and incrementally apply abrupt increases in CO2, analyzing outputs after each simulation reaches quasi-equilibrium with the imposed forcing. The results suggest that ENSO activity under quasi-equilibrium first increases and then decreases with increasing CO2, peaking in simulations with CO2 concentrations similar to the present day. Bjerknes–Jin stability analysis indicates that changes in the ENSO growth rate result primarily from changes in the thermocline feedback and thermodynamic damping terms. While thermodynamic damping increases monotonically with increasing CO2, the positive thermocline feedback varies within the range of internal variability up to twice the preindustrial value of CO2 and then weakens sharply with further increases. The mechanisms behind these changes include weaker mean ocean upwelling and weaker dynamical coupling between the atmosphere and subsurface ocean associated with substantial near-surface freshening at higher levels of CO2. These changes steepen the thermodynamic barrier to mixing between the surface and subsurface, weakening the east–west temperature gradient in the mean state and suppressing variability in the cold tongue. Analysis of similar model simulations from the Coupled Model Intercomparison Project (CMIP6) archive indicates that changes in the Bjerknes–Jin stability index are robust but do not establish a consensus as to the mechanisms behind them. Significance Statement This study investigates how El Niño–Southern Oscillation changes with increasing CO2 forcing by using a global model with improved tropical Pacific climate. The simulations roughly correspond to scenarios in which emissions are reduced to maintain CO2 concentrations at near-constant values over a long period, with levels ranging from about 2/3 to more than 5 times the present-day concentration. Analysis of these simulations suggests that ENSO activity is strongest when CO2 concentrations are similar to the present-day and becomes substantially weaker when CO2 is more than double its present-day value. Reduced ENSO activity with further increases in CO2 is caused by weaker interactions between the atmosphere and the subsurface ocean. Both the amplitude of warm (El Niño) events and the occurrence frequency of warm and cold (La Niña) events decrease as ENSO events become first more difficult to grow and then more difficult to trigger with increasing CO2.