Southern Oscillation Research Articles

The Strengthened Linkage between ENSO and the Eurasian Pattern since the Late 1980s

Abstract The Eurasian (EU) teleconnection pattern is an important atmospheric intrinsic mode over the extratropical Northern Hemisphere, and it has strong influence on the weather and climate over Eurasia and remote regions. Investigating factors for the EU variability is crucial and has important implications for regional climate prediction. This study reveals a remarkable influence of El Niño–Southern Oscillation (ENSO) on the EU in early winter and particularly a notable enhancement of this influence since the late 1980s. The results indicate that ENSO can lead to the vertical motion and atmospheric heating anomalies over the tropical Indian Ocean, triggering an atmospheric wave train propagating along the subtropical westerly jet and inducing an EU-like pattern over Eurasia in early winter. The interdecadal enhancement of the ENSO impact on the EU after the late 1980s may be attributable to the warming of the background mean sea surface temperature (SST) in the tropical Indian Ocean. In particular, ENSO can lead to stronger atmospheric heating and circulation anomalies over the tropical Indian Ocean via a strong air–sea interaction due to a warmer background mean SST after the late 1980s. A warmer background mean SST in the tropical Indian Ocean accelerates the subtropical westerly jet due to the thermal-wind balance, which is more favorable for the propagation of the atmospheric wave train forced by the atmospheric heating anomalies in the tropical Indian Ocean. The observed mechanisms for the enhanced impact of ENSO on the EU are also validated by numerical experiments. Significance Statement The Eurasian (EU) teleconnection pattern is an important atmospheric internal variability with significant influences on the Eurasian climate. The present study finds a remarkable relationship between the EU and ENSO in early winter, and this connection is significantly enhanced in recent decades. Thus, ENSO may serve as an important precursor signal for predicting the EU. Observational analysis and numerical experiments show that the warmer tropical Indian Ocean (TIO) plays a key role in this enhanced relationship. The warmer TIO may enhance the local air–sea interaction and accelerate the subtropical jet. The ENSO-induced anomalous disturbance over the TIO becomes stronger and can more easily propagate along the subtropical jet, exerting a strong influence on the EU especially after the late 1980s.

Climate-based modelling and forecasting of dengue in three endemic departments of Peru.

Amid profound climate change, incidence of dengue continues to rise and expand in distribution across the world. Here, we analysed dengue in three coastal departments of Peru which have recently experienced public health emergencies during the worst dengue crises in Latin American history. We developed a climate-based spatiotemporal modelling framework to model monthly incidence of new dengue cases in Piura, Tumbes, and Lambayeque over 140 months from 2010 to 2021. The framework enabled accurate description of in-sample and out-of-sample dengue incidence trends across the departments, as well as the characterisation of the timing, structure, and intensity of climatic relationships with human dengue incidence. In terms of dengue incidence rate (DIR) risk factors, we inferred non-linear and delayed effects of greater monthly mean maximum temperatures, extreme precipitation, sustained drought conditions, and extremes of a Peruvian-specific indicator of the El Niño Southern Oscillation. Building on our model-based understanding of climatic influences, we performed climate-model-based forecasting of dengue incidence across 2018 to 2021 with a forecast horizon of one month. Our framework enabled representative, reliable forecasts of future dengue outbreaks, including correct classification of 100% of all future outbreaks with DIR ≥ 50 (or 150) per 100,000, whilst retaining relatively low probability of 0.12 (0.05) for false alarms. Therefore, our model framework and analysis may be used by public health authorities to i) understand climatic drivers of dengue incidence, and ii) alongside our forecasts, to mitigate impacts of dengue outbreaks and potential public health emergencies by informing early warning systems and deployment of vector control resources.

El Niño-Southern Oscillation signals imprinted in stalagmite δ18O from 2005 to 2017

El Niño-Southern Oscillation (ENSO) is essential to the annual rainfall in the Pacific Rim, causing frequent floods and droughts in these regions. However, its relationship with precipitation in southeastern China on the interannual timescale remains uncertain. Here we reconstruct an ultra-high-resolution hydroclimate record from 2005AD to 2017AD using 301 sets of δ18O data, U/Th dates, and annual-layer counting on a stalagmite MG2 from Meiguang Cave, Jiangxi Province, southeastern China. We find that both calcite and precipitation δ18O records have negative correlations with local rainfall amount, with heavier rainfall correlating with negative excursions of δ18O, supporting the rainfall amount effects on calcite and precipitation δ18O signals on the seasonal timescale. On the interannual timescale, La Niña (El Niño) years are followed by positive (negative) rainfall years and decreased (increased) MG2 δ18O values, and all records have ∼3-year cyclicity. The antiphased correlation of medium coefficiency of the Southern Oscillation Index (SOI) with both precipitation δ18O and MG2 δ18O records implies that ENSO could modulate the calcite δ18O signals in the monsoonal region of China through circulation effects. Therefore, we suggest that changes in cave δ18O values in China can be controlled by both rainfall amount and circulation effects related with the ENSO activities, which provides a good reference for the paleoclimate studies on short timescales.

Assessing the forecast capability of the El Niño–Southern Oscillation with a one-year lead-time using the Global Atmospheric Oscillation based on the results of CMIP6 models

Assessing the forecast capability of the El Niño–Southern Oscillation with a one-year lead-time using the Global Atmospheric Oscillation based on the results of CMIP6 models

Climate, crops, and postharvest conflict

AbstractI present new evidence of the effects of climate shocks on conflict. Focusing on political violence in Africa, I find that El Niño Southern Oscillation shocks during the crop‐growing season affect harvest‐related conflict in croplands exposed to this climate phenomenon. Specifically, a 1°C warming of sea surface temperature in the tropical Pacific Ocean, a proxy for a moderate‐strength El Niño event, reduces political violence in exposed locations with crop agriculture, relative to other areas, by approximately 3%, during the early postharvest season. This effect attenuates toward zero as the crop year progresses. This effect can reach as much as 15% after a strong El Niño event, such as that of 1997 or 2015, in highly exposed croplands, such as parts of Southern Africa and the Sahel. Conversely, a La Niña event, which is a counterpart of an El Niño event, has the opposite effect and thus increases conflict in the exposed croplands during the early postharvest season. Because these events can be predicted several months in advance, the findings of this research can contribute to creating a platform for early warnings about transitory spatiotemporal shifts in political violence in predominantly agrarian societies.

Comment on “Resolving the Tropical Pacific/Atlantic Interaction Conundrum” by Feng Jiang et al. (2023)

AbstractJiang et al. (2023), https://doi.org/10.1029/2023gl103777 argue that the apparent impact of the equatorial Atlantic on El Niño‐Southern Oscillation (ENSO) is a statistical artifact, and that the 6‐month lead correlation reported in previous studies stems from early developing ENSO events driving the equatorial Atlantic zonal mode (AZM) in boreal summer and maturing in winter. Closer examination, however, reveals that most AZM events develop too early to be driven by developing ENSO, and that the influence of decaying ENSO events has to be considered too. Thus, while early developing ENSO events may play a role, they do not fully explain observed AZM behavior. Our aim is not to argue for or against an AZM influence on ENSO, but rather to show that Jiang et al.’s analysis is insufficient to resolve this issue. More analysis will be needed for a deeper understanding of Atlantic‐Pacific interaction.

Equatorial Pacific Cold Tongue Bias Degrades Simulation of ENSO Asymmetry due to Underestimation of Strong Eastern Pacific El Niños

Abstract El Niño–Southern Oscillation (ENSO) exhibits a considerable asymmetry in sea surface temperature anomalies (SSTa), as El Niño events tend to be stronger and centered further east than La Niña events. Here, we analyze ENSO asymmetry in observations and preindustrial control integrations of 32 models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Observations indicate a significant link between strong eastern Pacific (EP) El Niño events and the ENSO amplitude and asymmetry. The large CMIP6 database confirms this strong link. Most CMIP6 models suffer from an equatorial Pacific cold SST bias. This cold tongue bias hinders the southward migration of the ITCZ toward the equator over the eastern equatorial Pacific, which is characteristic of strong EP El Niño events in observations. Therefore, many models underestimate the eastern equatorial Pacific rainfall anomalies and simulate a wind stress feedback over the western Pacific that is too weak and too far west. As a result, the cold tongue bias exerts a strong control on the climate models’ ability to generate strong EP El Niño events and therefore on the ENSO overall amplitude and asymmetry. We discuss the relevance of these results in view of a potential increase of strong EP El Niño events under global warming. Significance Statement El Niño and La Niña are asymmetric, as El Niño events tend to be stronger and further east than La Niña events. Due to an equatorial Pacific cold tongue bias with too cold SSTs, the simulation of ENSO asymmetry is degraded in many climate models participating in CMIP6. Here, we show how the cold tongue bias influences ENSO asymmetry. The cold bias hampers the simulation of strong eastern Pacific El Niños by making it more difficult for SST to exceed the threshold for deep atmospheric convection over the eastern equatorial Pacific. Recent research indicates that climate models with a realistic ENSO asymmetry agree on the projected ENSO under global warming. The results of this study suggest that reducing the cold tongue bias has the potential to enhancing the reliability of future ENSO projections.

Insights of Dynamic Forcing Effects of MJO on ENSO from a Shallow Water Model

Abstract The Madden–Julian oscillation (MJO) is believed to play a significant role in triggering El Niño–Southern Oscillation (ENSO) events and affect the dynamics of ENSO. In this study, the dynamic forcing effects of MJO on the equatorial oceanic dynamic fields and the onsets of different types of ENSO events are investigated through sensitive experiments using spatiotemporally filtered forcing based on an anomalous shallow water model. The comparisons between observations and model responses provide meaningful insights into the extent of MJO’s impacts on sea surface dynamics relative to other atmospheric variabilities. The following conclusions are made. First, the MJO-forced perturbations on zonal currents are stronger and more significant than those on sea surface heights. Second, MJO is essential for improving zonal current simulation in the western-central Pacific and generating activity centers of zonal currents in the eastern Pacific in the model. Third, MJO tends to contribute to the onset of El Niño events rather than La Niña events. Strong intraseasonal oceanic Kelvin waves forced by MJO are confirmed in simulations during the onset stages of the 1997/98 and 2004/05 events. The 120-day running standard deviations of zonal current and sea surface height anomaly series forced by MJO exhibit positive skewness similar to those of the 20–100-day band-passed observational series. Yet, not all the onsets of historical ENSO events are in company with strong MJO-related perturbations. Additionally, the wind stress formula can amplify the responses of zonal current and sea surface height anomalies to synoptic forcings with periods shorter than 20 days through entraining lower-frequency variabilities. Significance Statement The Madden–Julian oscillation (MJO) is believed to be able to trigger El Niño–Southern Oscillation (ENSO) events and influence our understanding of the fundamental nature of ENSO. In this study, spatiotemporally filtered forcing experiments are implemented on an anomalous shallow water model. The results show that MJO is more important for improving the simulation of surface zonal currents rather than the sea surface heights and tends to contribute to the onset of El Niño events rather than La Niña events through triggering strong intraseasonal oceanic Kelvin waves.

Process-Based Evaluation of Intraseasonal Oceanic Kelvin Waves in the Pacific Ocean in CMIP6 Models

Abstract Oceanic intraseasonal Kelvin waves (KWs) help modulate upper-ocean thermal characteristics, providing feedbacks to important coupled air–sea phenomena in the tropics. The recent availability of daily thermocline depth fields from several phase 6 of the Coupled Model Intercomparison Project (CMIP6) models makes it possible to evaluate the performance of KWs and identify potential sources of bias. Most models fail to simulate a realistic spatial distribution of KW variability. Models simulate a large variability of KWs in the western or eastern Pacific rather than in the central Pacific as observed. The modeled KWs propagate slowly (about 1.5 m s−1) compared to observations (about 2.5 m s−1). This slow propagation is also identified in wavenumber–frequency spectra for KWs and meridional KW structures, which is more consistent with a second baroclinic mode structure in models compared to the first baroclinic mode structure in observations. An analysis of the relative contributions of the vertical wavenumber and background ocean stability to KW phase speeds indicates that the high vertical wavenumber bias in models contributes most to the slow propagation, in which the higher-than-observed vertical wavenumbers imply the biased incorporation of higher baroclinic modes in the model KW structure. This finding is further supported by the results of vertical mode decomposition that incorporates background density profiles. These results indicate that a realistic representation of the KW vertical structure is essential to produce realistic KW propagations in models. Significance Statement Oceanic intraseasonal Kelvin waves (KWs) play a significant role in regulating the heat content and temperature of the ocean, which provides feedbacks to coupled ocean–atmosphere phenomena in the tropics such as El Niño–Southern Oscillation (ENSO). Consequently, identifying the biases in KWs and the potential sources of those biases in state-of-the-art models is essential to improve simulations of ENSO and its diversity and advance forecasts of weather extremes around the globe induced by ENSO. We find that KWs in the models propagate slower than observations, mainly due to biases in their vertical structure, with secondary effects due to biases in model ocean stability. These issues may be potential sources for current imperfect ENSO model simulations and predictions.

Investigating the Relative Contribution from Tropical Indo-Pacific SST to Asian Monsoon Precipitation Variability Using LIM

Abstract A critical issue is determining the factors that control the year-to-year variability in precipitation over southern Asia. In this study, we employ a cyclostationary linear inverse model (CS-LIM) to quantify the relative contribution of tropical Pacific and Indian Ocean sea surface temperature anomalies (SSTAs) to the interannual variability of the Asian monsoon, especially Indian summer monsoon rainfall (ISMR). Through a series of CS-LIM experiments, we isolate the impacts of the direct forcing from Pacific SSTAs, Indian Ocean SSTAs, and their interaction on Asian monsoon rainfall variability. Our results reveal distinct patterns of influence with the direct forcing from the Pacific (Indian) Ocean tending to enhance (reduce) the magnitude of precipitation variability, while the Indo-Pacific interaction acts to strongly damp the variability of Asian monsoon precipitation, especially over India. We further investigate these specific impacts on ISMR by analyzing the relationship between tropical Indo-Pacific SSTAs and the leading three empirical orthogonal functions (EOFs) of ISMR. The results from our CS-LIM experiments indicate that the direct forcing from El Niño–Southern Oscillation (ENSO) enhances the variability of the first and third EOFs, while the Indian Ocean SSTA opposes ENSO’s effects, which is consistent with previous studies. Our new results show that the tropical Indo-Pacific interaction strongly damps ISMR variability, which is due to the ENSO-induced Indian Ocean dipole (IOD) opposing the direct impacts from ENSO on ISMR. Additionally, reduced ENSO amplitude and duration associated with the Indo-Pacific interaction may also contribute to the damping effect on ISMR, but this requires further study to understand the relevant mechanisms.

Cross-Seasonal Effect on Tropical Pacific Precipitation: Implication of South Pacific Quadrupole Simulation in CMIP6

Abstract The tropical Pacific convergence zone plays a crucial role in the global climate system. Previous research studies emphasized the cross-seasonal influence of the South Pacific quadrupole (SPQ) mode on the tropical Pacific climate. This study assesses the relationship between austral summer SPQ and austral winter tropical precipitation in phase 6 of the Coupled Model Intercomparison Project (CMIP6) models. The analysis emphasizes the historical experiments conducted within this time frame, spanning from 1979 to 2014. Our findings reveal that the SPQ is accurately represented in all CMIP6 models, but the connection between SPQ and precipitation is inadequately simulated in most models. To investigate the reasons behind these intermodel differences in reproducing SPQ-related processes, we categorize models into two groups. The comparisons demonstrate that the fidelity of model simulations in replicating the SPQ–tropical precipitation relationship hinges significantly on their capacity to reproduce the positive wind–evaporation–sea surface temperature (WES; SST) feedback over both the southwestern Pacific (25°–10°S; 150°E–160°W) and the southeastern Pacific (30°–10°S; 140°–80°W). This positive WES feedback propagates the SPQ signal into the tropics, intensifying the meridional gradient of SST anomaly in the tropical western-central Pacific, which consequently amplifies convection and rainfall in that area. In the group of models that failed to simulate this relationship accurately, the weakened WES feedback can be traced back to biases in wind speed and its variation. Furthermore, this WES feedback establishes a connection between SPQ and El Niño–Southern Oscillation (ENSO). A better rendition of the SPQ–tropical rainfall connection tends to result in a better simulation of the onset of SPQ-related ENSO events. As a result, this study advances our comprehension of extratropical impacts on the tropics, with the potential to enhance the accuracy of tropical climate simulation and prediction. Significance Statement Tropical rainfall plays an important role in the global climate system. Beyond the well-known influence of El Niño–Southern Oscillation (ENSO) on the tropical rainfall, the sea surface temperature (SST) anomaly in the South Pacific has a cross-seasonal impact on the precipitation over the tropical Pacific via air–sea coupled processes. Such SST anomaly pattern shows a quadrupole structure in the extratropical South Pacific, known as the South Pacific quadrupole (SPQ) mode. However, the relationship between SPQ and tropical precipitation remains poorly simulated in most state-of-the-art climate models. One primary reason for this gap between observed and simulated relationships is the underestimation of wind speed and its variation over the south tropical Pacific in these models. This limitation undermines their ability to accurately represent the air–sea interactions that drive tropical precipitation patterns, leading to inaccuracies in simulations. Our study aims to bridge this knowledge gap by enhancing our understanding of the extratropical effects on the tropical Pacific. By exploring the mechanisms underlying the SPQ–precipitation connection, we expect to improve the simulation and prediction capabilities of tropical climate models, thereby enhancing our ability to forecast and adapt to future climatic changes.

Coastal sea level rise at altimetry-based virtual stations in the Gulf of Mexico

A dedicated reprocessing of satellite altimetry data from the Jason-1/2/3 missions in the world coastal zones provides a large set of virtual coastal stations where sea level time series and associated trends over 2002-2021 can be estimated. In the Gulf of Mexico, we obtain a set of 32 virtual coastal sites, well distributed along the Gulf coastlines, completing the tide gauge network with long-term data that is currently limited to the northern part of the Gulf. Altimetry-based coastal sea level time series and associated sea level trends confirm previous published results that report a strong acceleration in tide-gauge based sea level rise along the US coast of the Gulf of Mexico since the early 2010s. In addition, our study shows that this acceleration also takes place along the western and southern coasts of the Gulf of Mexico. The coastal sea level trends estimated over 2012-2021 amounts to ∼10 mm/yr at most virtual stations. We note a slightly smaller rise on the western coast of Florida and at two sites of the Cuba Island. Good agreement in terms of sea level trends over 2002-2021 is found between coastal altimetry data and tide-gauge record corrected for vertical land motion. Good correlation is also found between coastal altimetry and tide gauge sea level time series at low-frequency time scales, with interannual fluctuations in sea level being indirectly linked to natural climate modes, in particular the El Nino Southern Oscillation (ENSO).

Reconstructed centennial precipitation-driven water storage anomalies in the Nile River Basin using RecNet and their suitability for studying ENSO and IOD impacts

While the Gravity Recovery And Climate Experiment (GRACE) and its Follow-On (GFO) missions have offered valuable observations for monitoring total water storage anomalies (TWSA), their short record constrains our ability to study the complete range and long-term variability of TWSA in the Nile River Basin (NRB). Previous studies reconstructing TWSA in this region either relied on specific hydrological models or did not consider spatial correlations among the TWSA grids. Here, we employ RecNet, a deep learning model capable of providing independent TWSA observations without relying on hydrological models while considering spatial correlations, to reconstruct precipitation-driven TWSA in the NRB from 1923 to 2022. The reconstructed data are validated by comparisons with the Global Land Data Assimilation System (GLDAS), the WaterGAP Global Hydrology Model (WGHM), the water balance budget, long-term runoff data, and GRACE-REC (i.e., a global reconstruction dataset freely available online). Subsequently, the suitability of the reconstructed data for studying El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) impacts within the NRB is assessed. Dividing the NRB into four sub-regions, i.e., the Lake Victoria Basin (LVB), the Bahr el Jebel and Bahr el Ghazal basins (BJBG), Ethiopian Highlands region (EH), and the Lower Nile River Basin (LNRB), it is shown that RecNet successfully reconstructs precipitation-driven TWSA over BJBG and EH, achieving correlation coefficient (CC), normalized root mean square error (NRMSE), and Nash–Sutcliffeefficiency (NSE) of 0.94/0.11/0.88 and 0.96/0.09/0.91 during the testing period, respectively. Additionally, RecNet’s reconstruction shows better agreement with GLDAS and WGHM than GRACE-REC, correlating well with runoff and the water balance budget in these regions. The relatively poor performance in the LVB and LNRB regions could be attributed to the substantial influence of Lake Victoria and the arid climate, respectively. Correlation analysis and wavelet coherence analysis identify significant coherence between ENSO/IOD and the reconstructed TWSA in BJBG and EH, with CC values of −0.68/0.34 and −0.82/0.56, respectively. This study provides centennial reconstructed TWSA data that could be useful in climate change/variability studies and water resource management within the NRB.

Investigating the role of ENSO in groundwater temporal variability across Abu Dhabi Emirate, United Arab Emirates using machine learning algorithms

Accurate prediction of groundwater levels is crucial for managing groundwater resources efficiently. The complex aquifer heterogeneity and groundwater abstraction variation present challenges to have accurate groundwater level models over Abu Dhabi emirate, United Arab Emirates. In the present study, two data-driven models are employed, which are the Long Short-Term Memory (LSTM) and the Random Forest (RF) to develop a model for the prediction of monthly groundwater level in the Abu Dhabi Emirate. The incorporated data in the models are precipitation, terrestrial water storage, soil moisture, evapotranspiration, and the El Niño-Southern Oscillation (ENSO) 3.4 index. The groundwater monitoring wells data are obtained for 263 monitoring wells distributed over Abu Dhabi emirate for the period 2000-2023 in a monthly temporal scale. The models’ performance was assessed using the Nash-Sutcliffe efficiency (NSE), root mean square error (RMSE) the coefficient of determination (R2) and Percent bias (PBIAS). An optimization technique was also applied to address the impact of the lags on enhancing the groundwater level model. The LSTM model outperformed the RF model during the testing period, achieving R2 =0.79, NSE=0.70, RMSE=0.38 meters and PBIAS= 0.2% with a 3-month lag. The global sensitivity analysis was applied to understand the importance of each parameter and its influence on the models’ output. This study highlights the potential use of data-driven models for the prediction of groundwater level which could aid water managers to monitor the groundwater resources at a regional scale. The developed model can serve as an alternative approach for predicting groundwater level change over the Abu Dhabi Emirate.

Wavelet analysis of discharge and sediment load for the Subarnarekha, Brahmani, and Mahanadi rivers of India

ABSTRACT This study aims to identify distinct small-scale temporary patterns between the river discharge and suspended sediment load for the main tropical rivers using continuous wavelet transform. Strong annual and irregular semi-annual variabilities, with few quarterly and interdecadal variabilities, are observed in river discharge and sediment load. The wavelet coherence reveals that the strongest in-phase coherence relationships exist between total suspended sediment and streamflow. The methodology for identifying the primary climate factors that integrate the partial wavelet coherence (PWC), multiple wavelet coherence (MWC), and quadruple wavelet coherence (QMWC) techniques is presented. The results show that the El-Nino/Southern Oscillation (ENSO) is the major regulator of streamflow followed by Indian Ocean Dipole (IOD) and Pacific Decadal Oscillation (PDO). The chosen rivers show a statistically significant ( p ≤ 0.05 ) descending trend in sediment load but no significant positive or negative trend in river discharge. This could be due to regional sediment storage and large-scale stream events affecting the sediment transport dynamics.

In search of non-stationary dependence between estuarine river discharge and storm surge based on large-scale climate teleconnections

Compound floods may happen in low-lying estuarine environments when sea level above normal tide co-occurs with high river flow. Thus, comprehensive flood risk assessments for estuaries should not only account for the individual hazard arising from each environmental variable in isolation, but also for the case of bivariate hazard. Characterization of the dependence structure of the two flood drivers becomes then crucial, especially under climatic variability and/or change that may affect their relationship. In this article, we demonstrate our search for evidence of non-stationarity in the dependence between river discharge and storm surge along the East and Gulf coasts of the United States, driven by large-scale climate variability, particularly El-Niño Southern Oscillation and North Atlantic Oscillation (NAO). Leveraging prolonged overlapping observational records and copula theory, we recover parameters of both stationary and dynamic copulas using state-of-the-art Markov Chain Monte Carlo methods. Physics-informed copulas are developed by modeling the magnitude of dependence as a linear function of large-scale climate indices, i.e., Oceanic Niño Index or NAO index. After model comparison via suitable Bayesian metrics, we find no strong indication of such non-stationarity for most estuaries included in our analysis. However, when non-stationarity due to these climate modes cannot be neglected, this work highlights the importance of appropriately characterizing bivariate hazard under non-stationarity assumption. As an example, we find that during a strong El-Niño year, Galveston Bay, TX, is much more likely to experience a coincidence of abnormal sea level and elevated river stage.

Plastic Behaviour Buffers Climate Variability in the Wandering Albatross.

Climate change has marked effects on global weather patterns and oceanic systems, impacting animal behaviour and fitness in potentially profound ways. Despite this, we lack detailed information about species' responses to climatic variation. Using an 11-year tracking dataset of over 300 individual birds, we explore the consequences of variation in the southern annular mode (SAM) and southern oscillation index (SOI) for individual behaviour and fitness in wandering albatrosses Diomedea exulans breeding in the Southern Indian Ocean. Our results reveal distinct responses between males and females to climatic variation that align with the impacts of each climatic index on the distinct foraging ranges of each sex. In positive SAM phases, linked to poorer foraging conditions in female ranges and better conditions in male ranges, females exhibited behaviour consistent with reduced foraging success: that is, fewer prey capture attempts and more movement between feeding patches. Males, on the other hand, showed no behavioural change. During positive SOI phases, associated with good foraging conditions in both male and female foraging ranges, both sexes showed evidence of more successful foraging, with birds engaging in more search behaviour, and taking shorter trips with fewer prey capture attempts, together indicating increased food intake per unit time. We found limited evidence for a role of individual variation, as measured through differences in personality, suggesting that plastic responses to climate are sufficiently important so as to obscure inter-individual variation. Supporting this was the finding that individual breeding success was unaffected by climatic variation, suggesting that plastic foraging behaviour allows albatrosses to mitigate climate impacts and maintain reproductive output.

Correction to: El Nin˜o-Southern Oscillation impacts on winter winds over Southern California

Correction to: El Nin˜o-Southern Oscillation impacts on winter winds over Southern California

Cross-scale causal information flow from the El Niño–Southern Oscillation to precipitation in eastern China

Cross-scale causal information flow from the El Niño–Southern Oscillation to precipitation in eastern China

Analysis of ENSO Event Intensity Changes and Time–Frequency Characteristic Since 1875

This study investigates the characteristics and intensity of El Niño–Southern Oscillation (ENSO) events from January 1875 to December 2023, employing an advanced method for intensity determination based on various ENSO indices defined as a continuous five-month period with temperatures exceeding 0.5 °C for warm events or falling below −0.5 °C for cold events. A total of 40 warm and 41 cold events were identified, with further classification revealing seven extreme warm events and five extreme cold events. The analysis shows a positive skewness in frequency distribution, indicating a predominance of strong warm events. The primary mode of variability is found to be interannual oscillation in the 3–8 year range, with significant decadal oscillations in the 10–16 year range. This study highlights the importance of methodological rigor in evaluating ENSO dynamics, contributing to a more comprehensive understanding of climate variability and offering a reliable framework for future research.