Southern Oscillation Research Articles

Counteracting Impacts of ENSO and the Aleutian Low on Winter Surface Air Temperature over Japan Sea Rim Region

Abstract Exploring the mechanisms modulating Japan Sea Rim (JSR) winter surface air temperature (JSRWT) holds significant scientific and societal importance. The present study unravels the counteracting impacts of El Niño–Southern Oscillation (ENSO) and the Aleutian low (AL) on JSRWT. Although ENSO and the AL have a significant positive correlation on interannual timescale, they exert totally opposite impacts on JSRWT. The positive Niño-3.4 sea surface temperature anomalies (SSTAs) usually lead to positive JSRWT anomalies, while an enhanced AL often results in negative JSRWT anomalies. The tropical convection anomalies associated with the positive Niño-3.4 SSTA induce two tropical to extratropical Rossby wave trains, leading to a barotropic anomalous anticyclone over northeast Asia, and thereby positive JSRWT anomalies. Conversely, the strengthened AL perturbs the westerly jet and induces an eastward-propagating Rossby wave train, leading to a barotropic anomalous cyclone over northeast Asia and negative JSRWT anomalies. The northeastward-propagating Rossby wave induced by the ENSO-related tropical convection anomalies over the Indian Ocean offsets the downstream Rossby wave induced by the strengthened AL, leading to counteracting impacts of ENSO and the AL on JSRWT. Finally, a novel index for monitoring JSRWT is proposed based on the indices of ENSO and AL. Significance Statement Despite the advantage of ENSO as a well-known predictability source, the seasonal predictability of Japan Sea Rim winter surface air temperature (JSRWT) is far from satisfactory. Here, we discovered that the Aleutian low (AL) has an independent influence on JSRWT contrasting with that of ENSO. When the AL and ENSO are in-phase, JSRWT shows no significant anomalies, but the JSRWT anomalies are largely amplified when AL and ENSO are out-of-phase. Therefore, a novel index for monitoring JSRWT is proposed based on the indices of ENSO and AL. These findings shed light on the low capacity of the seasonal prediction of JSRWT when only considering ENSO as the precursor.

Revisiting the Role of Atmospheric Initial Signals in Predicting ENSO

Abstract El Niño–Southern Oscillation (ENSO) provides an important source of global seasonal–interannual predictability, while its prediction encounters bottlenecks. Besides the slow-varying air–sea feedbacks, high-frequency atmospheric signals (HFASs) act on ENSO evolution. This study revisits the role of atmospheric initial signals in ENSO prediction using an atmosphere–ocean coupled model. Two sets of sensitivity hindcasts are conducted. One utilizes a pure sea surface temperature (SST) nudging for initialization so that no observed atmospheric internal signal is assimilated. The other applies a combination of the SST nudging and spectral nudging of JRA-55 reanalysis, which not only assimilates the observed atmospheric states and hence realizes skillful predictions of HFAS at the initial stage but also improves the oceanic initial conditions (ICs), especially around the thermocline. Unexpectedly, the better atmosphere–ocean ICs neither improve ENSO prediction nor overcome the spring prediction barrier. Further analysis of Bjerknes stability index suggests that underestimated negative feedbacks and insufficient responses of ocean currents and thermocline slope to atmospheric internal winds may account for the failure. Nevertheless, assimilating the atmospheric information partly improves the prediction of El Niño onset, especially for two recent extreme cases (i.e., 1997/98 and 2015/16). This improvement is associated with better representations of initial westerly wind bursts (WWBs) that excite subsequent downwelling equatorial Kelvin waves. However, due to unpredictable WWBs and underestimated wind response to the SST warming owing to the cold tongue biases in boreal summer, the zonal advective feedbacks are underestimated and thus further development of El Niño cannot be well predicted. This study suggests the importance of initial atmospheric signals despite the limitation, prompting further efforts to improve model physics.

Distinct impacts of the El Niño–Southern Oscillation and Indian Ocean Dipole on China's gross primary production

Abstract. Gross primary production (GPP), a crucial component in the terrestrial carbon cycle, is strongly influenced by large-scale circulation patterns. This study explores the influence of the El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) on China's GPP, utilizing long-term GPP data generated by the Boreal Ecosystem Productivity Simulator (BEPS). Partial correlation coefficients between GPP and ENSO reveal substantial negative associations in most parts of western and northern China during the September–October–November (SON) period of ENSO development. These correlations shift to strongly positive over southern China in December–January–February (DJF) and then weaken in March–April–May (MAM) in the following year, eventually turning generally negative over southwestern and northeastern China in June–July–August (JJA). In contrast, the relationship between GPP and IOD basically exhibits opposite seasonal patterns. Composite analysis further confirms these seasonal GPP anomalous patterns. Mechanistically, these variations are predominantly controlled by soil moisture during ENSO events (except MAM) and by temperature during IOD events (except SON). Quantitatively, China's annual GPP demonstrates modest positive anomalies in La Niña and negative IOD years, in contrast to minor negative anomalies in El Niño and positive IOD years. This outcome is due to counterbalancing effects, with significantly larger GPP anomalies occurring in DJF and JJA. Additionally, the relative changes in total GPP anomalies at the provincial scale display an east–west pattern in annual variation, while the influence of IOD events on GPP presents an opposing north–south pattern. We believe that this study can significantly enhance our understanding of specific processes by which large-scale circulation influences climate conditions and, in turn, affects China's GPP.

Tropical Interbasin Interaction as Effective Predictors of Late-Spring Precipitation Variability in the Southern Great Plains

Abstract The southern Great Plains experience fluctuating precipitation extremes that significantly impact agriculture and water management. Despite ongoing efforts to enhance forecast accuracy, the underlying causes of these climatic phenomena remain inadequately understood. This study elucidates the relative influence of the tropical Pacific and Atlantic basins on April–May–June precipitation variability in this region. Our partial ocean assimilation experiments using the Community Earth System Model unveil the prominent role of interbasin interaction, with the Pacific and Atlantic contributing approximately 70% and 30%, respectively, to these interbasin contrasts. Our statistical analyses suggest that these tropical interbasin contrasts could serve as a more reliable indicator for late-spring precipitation anomalies than El Niño–Southern Oscillation. The conclusions are reinforced by analyses of seven climate forecasting systems within the North American Multi-Model Ensemble, offering an optimistic outlook for enhancing real-time forecasting of late-spring precipitation in the southern plains. However, the current predictive skills of the interbasin contrasts across the prediction systems are hindered by the lower predictability of the tropical Atlantic Ocean, pointing to the need for future research to refine climate prediction models further. Significance Statement Agriculture and infrastructure in the southern plains face challenges from severe late-spring precipitation extremes. Traditional predictors like El Niño–Southern Oscillation (ENSO) lose effectiveness during the critical spring-to-summer transition, creating a forecasting gap. This study introduces the concept of tropical interbasin interactions, known to enhance seasonal predictability for late-spring precipitation in the southern plains. Novel climate model experiments highlight contributions from the tropical Pacific and Atlantic, offering a promising predictability that potentially surpasses the limitations of ENSO-based predictions. These outcomes hold the potential for developing operational forecasts of late-spring precipitation anomalies in the southern plains, enabling proactive risk management.

Stronger Westerly Wind Bursts in a Warming Climate: The Effects of the Pacific Warming Pattern, the Madden–Julian Oscillation, and Tropical Cyclones

Abstract Westerly wind bursts (WWBs) in the western–central equatorial Pacific are critical in El Niño–Southern Oscillation (ENSO) dynamics. Understanding how they may change with global warming has important implications for future projections of El Niño. In this study, we investigate how the enhanced eastern equatorial Pacific warming pattern, emerging in future climate projections, can influence WWB characteristics in an atmospheric general circulation model, CAM6. Changes in three main factors affecting WWBs—El Niño-conditions mean westerly wind stress anomalies, the Madden–Julian oscillation (MJO), and tropical cyclones (TCs)—are analyzed. We find that during El Niño onset (December–April), the WWB wind stress intensity remains largely unchanged but WWBs shift westward by about 20° of longitude. In contrast, during El Niño development (May–November), the WWB intensity increases by 41% or 79% in two warming scenarios considered [shared socioeconomic pathways (SSP5-8.5) and SSP2-4.5, respectively], which is mainly caused by a higher frequency of TC occurrence in the central tropical Pacific within 15°N/S. Further, we find that westerly wind speed anomalies associated with El Niño and the MJO also increase during El Niño development. However, as trade winds weaken in the central-eastern equatorial Pacific, the mean strength of the resulting westerly wind stress anomalies does not change much, and no significant eastward shift of WWBs is observed. Thus, our atmospheric model simulations suggest a strong TC-driven increase in WWB wind stress anomalies during El Niño development and hence a more important role of TCs in WWB generation, which in a coupled system could lead to stronger ENSO events, enhanced TC–ENSO coupling, and even greater intensification of WWBs.

Evolution and Drivers of Extreme Subsurface Marine Heatwaves in the Western Tropical Pacific Ocean during 2008 and 2010–11

Abstract Marine heatwaves (MHWs) have adverse impacts on marine ecosystems and fisheries, yet extreme MHWs in the western tropical Pacific Ocean remain largely unexplored. Here, we investigate the evolution and drivers of the two strongest subsurface MHWs in the western tropical Pacific Ocean on record, in 2008 (MHW-08) and 2010–11 (MHW-11). The two events have similar evolutions, as they were both initiated and developed locally in tropical regions during their onset phase and gradually dissipated with multiple cores during the decay phase. We examined the physical processes during the evolution of MHW-08 and MHW-11 and performed a heat budget analysis for the subsurface layer in each case. We find that the onset of both events were mainly controlled by convergence and vertical heat advection due to anomalous Ekman downwelling, while the decay of both events was mainly controlled by horizontal heat advection due to anomalous horizontal currents and withdrawal of anomalous convergence. The relationship between the subsurface MHWs and El Niño–Southern Oscillation is discussed. We suggest that the anomalous heat advections plus the La Niña–related background warming lead to the extreme subsurface MHW events. Our findings may have important implications for environmental change and marine life in the western tropical Pacific Ocean.

Extremes of Temperature and Precipitation Under CMIP6 Scenarios Projections Over Central Hokkaido, Japan

ABSTRACTClimate extreme events are intensifying globally, posing increasing risks across various sectors. Understanding climate extremes' spatiotemporal patterns and responses to climate change is crucial for effective management, especially on a regional scale. This study examines temperature and precipitation extremes, as well as compound dry‐hot events (CDHEs), in the Ishikari River basin (IRB) of Northeastern Japan, an area of significant socioeconomic importance. We focus on spatiotemporal analysis under multiple scenarios of temperature/precipitation extremes and CDHEs based on statistical downscaled datasets from the Coupled Model Intercomparison Project Phase 6. Results indicate that IRB underwent increased trends of extreme hot periods, extreme droughts, and heavy rainfalls during 1985–2014, which are significantly affected by the North Pacific Oscillation and Southern Oscillation Index. Future projections show that warming temperatures and less rainfall shift asymmetrical impacts on temperature and precipitation extremes, expecting increased warm spells and CDHEs but increased wet durations and less heavy rainfalls. Emission scenarios analysis suggests low‐emission scenarios (SSP1‐2.6) could mitigate their exacerbations, especially for CDHEs (decreased by 139%). Moreover, spatial‐pattern analysis reveals regional heterogeneity in temperature and precipitation extremes, with northern mountainous regions more susceptible to thermal extremes and southern plain regions (e.g., Sapporo city) experiencing prolonged drought and CDHEs. This study provides valuable insights into climate risk management and adaptation strategies.

El Niño southern oscillation, weather patterns, and bacillary dysentery in the Yangtze River Basin, China.

Increasingly intense weather anomalies associated with interannual climate variability patterns, like El Niño-southern oscillation (ENSO), could exacerbate the occurrence and transmission of infectious diseases. However,research in China remains limited in understanding the impacts and intermediate weather changes of ENSO on bacillary dysentery (BD). This study aimed to reveal the relationship between ENSO, weather conditions, and theincidence of BD, and to identify the potential meteorological pathways moderated by ENSO inthe ENSO-BD connections. BD disease data and meteorological data, as well as ENSO index, from 2005 to 2020 were obtained for 95 cities in the Yangtze River Basin. We first established the associations between ENSO events and BD, ENSO and weather, as well as weather and BDs using two-stage statistical models. Then, we applied a causal mediation analysis to identify the specific meteorological changes in the ENSO-BD relationship. In the Yangtze River Basin, both El Niño (IRR: 1.06, 95%CI: 1.04 ~ 1.08) and La Niña (IRR: 1.03, 95%CI: 1.02 ~ 1.05) events were found to increase the risk of BD. Variations of ENSO index were associated with changes in local weather conditions. Both the increases in regional temperatures and rainfall were associated with a higher risk of BD. In the casual mediation analyses, we identified that higher temperatures and excessive rainfall associated with La Niña and El Niño events mediatedthe ENSO's effect on BD, with mediation proportions of 38.58% and 34.97%, respectively. Long-term climate variability, like ENSO, can affect regional weather conditions and lead to an increased risk of BD. We identified the mediating weather patterns in the relationship between ENSO and BD, which could improve targeted health interventions and establish an advanced early warning system in response to the BD epidemic.

New northernmost distribution records of the Eastern South Pacific southern right whale (Eubalaena australis), including the first cases from Ecuador and northern Peru.

The Eastern South Pacific Right Whale (SRW) (Eubalaena australis) population has gained interest due to its Critically Endangered conservation status. So far, this population has been confirmed only along the coasts of Chile (18°20'S to 56°30'S) and from southern to central Peru (17°38'S to 12°11'S). Recent records have extended the species' known range, highlighting its geographic distribution, now reaching 1500 km north. Here, we report six recent records, consisting of five sightings and one stranding, that expand the documented range to northern Ecuador (0.6°N). The northern extension of the population may be associated with the unusual three-year-long cold phase (La Niña) of the El Niño Southern Oscillation (ENSO) in the eastern South Pacific, population expansion, movement and re-distribution of the species, increased monitoring effort, or a combination of these factors. These observations raise hope for the Critically Endangered SRW population, as the occurrence of mother-calf pairs may indicate a potential for population recovery. Nevertheless, these findings intensify concerns for what is still the least abundant SRW population, underscoring the urgency for more targeted research and conservation measures.

Climate Extremes in the New Zealand Region: Mechanisms, Impacts and Attribution

ABSTRACTAs global surface temperatures have increased with human‐induced climate change, notable compound climate extremes in the New Zealand (NZ) region associated with atmospheric heatwaves (AHWs) and marine heatwaves (MHWs) have occurred in the past 6 years. Natural modes of variability that also played a key role regionally include the Interdecadal Pacific Oscillation (IPO), El Niño/Southern Oscillation (ENSO) and changes in the location and strength of the westerlies as seen in the Southern Annular Mode (SAM). Along with mean warming of 0.8°C since 1900, a negative phase of the IPO, La Niña phase of ENSO and a strongly positive SAM contributed to five compound warm extremes in the extended austral summer seasons (NDJFM) of 1934/35, 2017/18, 2018/19, 2021/22 and 2022/23. These are the most intense coupled ocean/atmosphere (MHWs/AHWs) heatwaves on record with average temperature anomalies over land and sea +0.8°C to 1.1°C above 1991–2020 averages. The number of days above 25°C and above the 90th percentile of maximum temperature has increased, while the number of nights below 0°C and below the 10th percentile has decreased. Coastal waters around NZ recently experienced their longest MHW in the satellite era (1982‐present) of 289 days through 2023. The estimated recurrence interval reduces from 1 in 300‐years for the AHW event during the 1930s climate to a 1 in 25‐year event for the most recent decade. Consequences include major loss of ice of almost one‐third volume from Southern Alps glaciers from 2017 to 2021 with rapid melt of seasonal snow in all four cases. Above‐average temperatures in the December/January grape flowering period resulted in advances in veraison (the onset of ripening); and higher‐than‐average grape yields in 2022 and 2023 vintages. Marine impacts include widespread sea‐sponge bleaching around northern and southern NZ.

Extreme hydroclimatic events and response of vegetation in the eastern QTP since 10 ka

Abstract Climate variations during the Holocene significantly impacted vegetation dynamics in the eastern Qinghai-Tibet Plateau (QTP). However, vegetation evolution in response to regional climatic trends and events during this interval remains controversial. Here, we present well-dated decadal-resolution loss on ignition (LOI) and grain size records from the Xing Co Lake on the eastern QTP. The records show an overall drying trend since 10 thousand years ago (ka), with multiple extreme precipitation events observed during 10 to 7 ka. An extreme drought event occurred at around 5.5 ka, after which the climate was drier and unstable with several drought events. In comparison with the hydroclimate, insolation, and El Niño Southern Oscillation records, our data show a close correspondence with the summer insolation differential between 30°N and 30°S and El Niño events on orbital-millennium timescales. This suggested that the increased rainfall during the early Holocene on the eastern QTP can be attributed to the high insolation differential between 30°N and 30°S and low El Niño events. Conversely, the drying trend in the late Holocene appears to correlate with a low insolation differential and high El Niño events. Whenever ice-rafted debris events occurred in the North Atlantic, there was a corresponding occurrence of drying events in the late Holocene in the Zoige Basin. This suggested that teleconnection between the precipitation on the eastern QTP and the North Atlantic climate exists in the Holocene. When compared to independent hydroclimatic and arboreal pollen (AP%) records on the eastern QTP, the evolutionary trends and events of AP% align closely with local hydroclimate changes. This suggested that arboreal coverage could rapidly respond to climate change during the Holocene, but further studies are needed.

Thermal Characteristics of the Extreme Cases of Tropopause Over the Tropics

ABSTRACTThe anomalous variability of extreme cases of the tropical tropopause provides insight into the stratosphere‐troposphere exchange process crucial for understanding climate change. The present study analyses the extreme variability of the tropopause and its thermal structure over the tropics using GPS radio occultation data over the period 2006–2019. The extremely cold and warm tropopauses and extremely high and low tropopauses are identified based on the cold point tropopause temperature and height, respectively, when their values exceed two standard deviations with respect to their climatological means. The analyses revealed frequent occurrence of extreme cases of tropopause over the Atlantic Ocean compared to the Western Pacific Ocean. Individually, extremely warm and low cases occur more frequently over the subtropics, while extremely cold and high cases occur frequently over the deep tropics. These extreme cases pose different thermal structures bounded within the extremely low and high tropopauses throughout the tropics. The height difference between the extremely high and low tropopause cases is wider over the Atlantic Ocean and adjoining areas compared to the western Pacific Ocean. The temperature difference between the extremely warm and cold tropopause cases is higher in the Atlantic, Central Pacific, and Indonesian regions compared to the American, Indian Ocean, and western Pacific Ocean regions. The relationship between the El Niño Southern Oscillation (ENSO) phases and extreme tropopause cases is also investigated which reveals a higher occurrence of extremely high tropopause cases during the El Niño phase while low tropopause cases during the La Niña phase. Our analysis also revealed the thermal patterns of the extreme cases characterising colder and sharper tropopause over the convective regions compared to subsidence regions.

Lag-WALS approach incorporating ENSO-related quantities for altimetric interannual SLA forecasts in the South China Sea

A novel approach using lag weighted-average least squares (Lag-WALS) is proposed to forecast the interannual sea level anomaly (SLA) in the South China Sea (SCS) using lagged equatorial Pacific El Niño–Southern Oscillation (ENSO)-related quantities. Through empirical orthogonal function (EOF) and wavelet coherence method, we first investigated the relationships between sea surface temperature (SST) and SLA (both steric sea level (SSL) and non-steric sea level (NSSL)) in the equatorial Pacific, and then explored their cross-correlations with the interannual SCS SLA. A robust alignment was found between the first spatiotemporal mode of EOF (i.e. EOF1 and first principal component (PC1)) from SLA/SSL and SST across the equatorial Pacific, both of which exhibited a typical ENSO horseshoe spatial pattern in EOF1. Good consistency between the SCS SLA and the SST/SLA/SSL PC1 was revealed, with the SCS SLA lagging behind the SST, SLA, and SSL by several months at most grid locations. In contrast, the NSSL exhibited large disparities with the SST PC1 or the interannual SCS SLA. The lag-WALS model performed better at the SCS boundaries than in the central region, with an average STD/MAE/Bias (RMSE/MAE/Bias) for internal (external) accuracies of 1.01/0.80/–0.002 cm (1.39/1.13/–0.08 cm), respectively. The altimetric-observed SLA seasonal patterns agreed with the Lag-WALS model-forecasted SLA. A similar situation applies to regionally-averaged SLA time series. These results underscore the ability of the Lag-WALS model to accurately forecast the SCS SLA at the interannual scale, which is crucial for early warning of abnormal sea level changes in the SCS.

Identifying gene-level mechanisms of successful dispersal of Vibrio parahaemolyticus during El Niño events.

El Niño events, the warm phase of the El Niño Southern Oscillation, facilitate the movement of warm surface waters eastwards across the Pacific Ocean. Marine organisms transported by these waters can act as biological corridors for water-borne bacteria with attachment abilities. El Niño events have been hypothesized as driving the recent emergence of Vibrio parahaemolyticus (Vp) variants, marine bacterium causing gastroenteritis, in South America, but the lack of a robust methodological framework limited any further exploration. Here, we introduce two new analysis approaches to explore Vp dynamics in South America, which will be central to uncovering Vp dynamics in the future. Distributed non-linear lag models found that strong El Niño events increase the relative probability of Vp detection in Peru, with a 3-4-month lag time. Machine learning found that the presence of a specific gene (vopZ) involved in attachment to plankton in a pandemic Vp clone in South America was temporally associated with strong El Niño events, offering a possible strategy for survival over long-range dispersal, such as that offered by El Niño events. Robust surveillance of marine pathogens and methodological development are necessary to produce resolute conclusions on the effect of El Niño events on water-borne diseases.

Multi-parameter study of Aculeo lagoon (Chile)

Abstract. The Aculeo Lagoon, located in the Santiago Metropolitan Region, was one of the main water reservoirs of central Chile. It has experienced a decline in water levels since 2009 and completely dried up in 2018. It was unable to recover until 2023 due to sustained demand for water resources associated with population growth, changes in land use, and years of drought. The objective of this study is to estimate how anthropogenic factors and climate change have influenced the drying of the lagoon. Parameters considered include population growth, housing increases, changes in land use within the Aculeo basin, local temperature and precipitation variations, and global El Niño Southern Oscillation (ENSO) phenomena. Input data included multi-year Landsat images, census data, and a systematic review of the literature on the study area. Furthermore, applying geospatial data analysis techniques such as satellite image processing, supervised classification of land cover/use, and calculation of spectral indices, it is possible to conclude that the Aculeo Lagoon dried out due to a significant precipitation deficit over nearly a decade, exacerbated by the overexploitation of land for agricultural activities.

Subseasonal-to-seasonal (S2S) prediction of atmospheric rivers in the Northern Winter

Atmospheric rivers (ARs) are characterized by intense lower tropospheric plumes of moisture transport that are frequently responsible for midlatitude wind and precipitation extremes. The prediction of ARs at subseasonal-to-seasonal (S2S) timescales is currently at a low level of skill, reflecting a need to improve our understanding of their underlying sources of predictability. Based on 20 year hindcast experiments from the Geophysical Fluid Dynamics Laboratory’s SPEAR S2S forecast system, we evaluate the S2S prediction skill of AR activities in the northern winter. Higher forecast skill is detected for high-frequency AR activities (3–7 days/week) compared to low-frequency AR activities (1–2 days/week), even though the occurrence rate of high-frequency ARs exceeds that of low-frequency ARs. For the first time, we have applied the Average Predictability Time technique to the SPEAR system to identify the three most predictable modes of AR in the North Pacific sector. These modes can be attributed to the influences of the El Niño–Southern Oscillation, the Pacific North American pattern, and the Arctic Oscillation. S2S AR forecast skill in western United States is modulated by various phases of large-scale variability. This study highlights potential windows of opportunity for operational S2S AR forecasting.

A probabilistic forecast for multi-year ENSO using Bayesian convolutional neural network

Abstract A robust El Niño Southern Oscillation (ENSO) prediction is essential for monitoring the global climate, regional monsoons, and weather extremes. Despite dedicated efforts spanning decades, the precise prediction of ENSO events through numerical modeling beyond a couple of seasonal lead times remains a daunting challenge. The advent of deep learning-based approaches marks a transformative era in climate and weather prediction. However, many machine learning-based studies attempting ENSO prediction are confined to singular estimates, lacking adequate quantification of uncertainty in learned parameters and overlooking the crucial need for a nuanced understanding of ENSO prediction confidence. Here, we introduce a deep learning-based Bayesian convolutional neural network model that provides robust probabilistic predictions for ENSO with a lead time of up to 9–10 months across all seasons. The Bayesian layers within the convolutional neural network maintain the capability to predict a distribution of learned parameters. Augmented with bias correction, our model reproduces the amplitude of the Niño 3.4 index with fidelity for lead up to 9–10 months. The inherent capacity for uncertainty modeling enhances the reliability of bayesian neural networks (BNNs), making them particularly valuable in operational services. This research holds substantial socio-economic implications as it enhances our forecasting capabilities and rigorously quantifies forecast uncertainties, providing valuable insights for planning and policymaking.

Asymmetric ENSO teleconnections in a symmetric CO2 concentration pathway

Abstract El Niño-Southern Oscillation (ENSO) is the strongest interannual phenomenon occurring in the tropical Pacific, significantly affecting the entire world. The ENSO response to increasing CO2 concentrations have been extensively studied, but the reverse scenario is still not well understood. Here, we investigate the hysteresis of ENSO teleconnections in a CO2 removal simulation of an earth system model. During the ramp-up period of CO2 concentrations, Pacific-North American and Pacific-South American patterns are intensified, with the eastward shift of their poles, which are even further intensified during the ramp-down period. This ENSO teleconnection hysteresis is closely linked to the tropical-origin hysteresis, in which, during the ramp-down periods, the prevalence of the eastern-Pacific type El Niño leads to the hysteresis in the eastern Hemispheric ENSO teleconnections and the enhanced ENSO skewness and the eastward shift of ENSO-induced tropical atmospheric convection do to that in the western Hemispheric ENSO teleconnection. The alterations by the tropical origin are predominantly associated with intensified southward migration of the Intertropical Convergence Zone, along with a stronger El Niño-like warming trend. We also demonstrate that the hysteretic change in the mid-latitude mean state over the North Pacific region could lead to hysteresis of the ENSO teleconnection without invoking a tropical origin.

Widening of wind-stress anomalies amplifies ENSO in a warming climate

Abstract Climate change simulations generally indicate the strengthening of El Niño Southern Oscillation (ENSO) sea surface temperature (SST) variability through the 21st century, yet a robust physical mechanism explaining this change across different models is still lacking, and the projections for ENSO amplitude exhibit a large spread. Most commonly, changes in the background state of the tropical Pacific are invoked to explain these changes of ENSO. Here we show that changes in the structure of wind-stress anomalies associated with ENSO are potentially as important as these background state changes. Specifically, changes in the magnitude, meridional width, and zonal structure of wind-stress anomalies can explain approximately 53% of the inter-model variance in the projected change of ENSO magnitude through the 21st century as well as 43% in ENSO periodicity changes. Among these changes in the wind structure, the meridional widening of wind anomalies plays the most important role. To demonstrate that these changes are indeed critical, we develop a hybrid model of ENSO based on the Community Earth System Model version 2, which incorporates a dynamical ocean coupled to a simplified statistical atmosphere within the tropical Pacific. In the absence of external forcing and corresponding mean-state changes, the imposed changes in wind stress anomalies in this hybrid model result in an increase of ENSO amplitudes of nearly 10% along the equator. Our results are also theoretically supported by a recharge-oscillator model that incorporates the meridional wind structure. Thus, changes in the structure of wind-stress anomalies, together with changes in the mean state, likely play a critical role in the projected strengthening of ENSO.

Comparative Evaluation of Niño1+2 and Niño3.4 Indices in Terms of ENSO Effects Over the Euro‐Mediterranean Region

ABSTRACTGlobal or regional impacts of El Niño Southern Oscillation (ENSO) have predominantly been investigated through the Niño3.4 index, representing the sea surface temperature (SST) variations in the central Tropical Pacific. In this study, we comparatively evaluated the usefulness of Niño1+2, a relatively less utilised index that represents SST variability in the Eastern Tropical Pacific. In our analyses, we focused on ENSO impacts on Euro‐Mediterranean (EM) climate variability during boreal winter, using data from the NCEP/NCAR Reanalysis. The correlation analysis involving Niño1+2 depicts more distinct temperature and precipitation patterns over the EM region. Amongst the SST‐based Niño indices, it has the highest correlation with the East Atlantic index (0.47, statistically significant at > 99% confidence level), a prominent regional teleconnection associated primarily with the strength of the East Atlantic ridge, which produces dipole‐type climate patterns between East Atlantic/Western Europe and Central/Eastern Mediterranean. Moreover, its lagged correlations with the following spring (0.39), summer (0.31), and autumn (0.36) are all statistically significant at ≥ 99% confidence levels. The composite analysis shows that different Niño regions have distinct effects on atmospheric circulation and climate in the EM region. The Niño1+2 index is particularly helpful in identifying the years when warm SST anomalies of El Niño extend to the Eastern Equatorial Pacific, which results in a reversal of temperatures across the EM region. Thus, this study suggests that Niño1+2 is a useful index for studying climate variability and predictability in the EM region, especially when used in conjunction with other Niño indices, as it captures some ENSO features that they may not encompass.