El Nino-Southern Oscillation Events Research Articles

Bioclimatic Zoning of the Pantanal

Human thermal perception, or thermal comfort, is a critical variable that directly influences the health, productivity, and well-being of populations. However, specific studies on thermal comfort in the Pantanal and its sub-regions are scarce. This study analyzes the distribution of thermal comfort classes in the Pantanal and its sub-regions using the Universal Thermal Climate Index (UTCI) for the period of 1979 to 2023. The main objective was to assess thermal discomfort in the region, identifying comfort classes and examining the influence of El Niño-Southern Oscillation (ENSO) events on this index. The analysis, based on reanalysis climatic data and statistical techniques, mapped the areas most susceptible to thermal stress. The central and southern regions of the Pantanal, such as Porto Murtinho, stood out as the most uncomfortable due to heat, while sub-regions in the north, such as Cáceres and Poconé, showed lower levels of thermal stress. Additionally, it was observed that the months of October and November present the highest UTCI values, indicating extreme thermal discomfort due to heat during the spring. Summer was identified as the most uncomfortable season in terms of heat, while winter showed moderate heat discomfort. The investigation of ENSO events revealed a tendency for greater thermal discomfort during La Niña years. It is concluded that there is a progressive increase in heat-related thermal discomfort in the Pantanal region, with a particularly pronounced trend in the spring.

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.

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.

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.

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.

Variability of ENSO teleconnections indices, and its impacts on moroccan agriculture

In Morocco, drought periods have become more frequent and severe due to climate change, which has had a substantial effect on freshwater supply and agricultural output. The El Niño-Southern Oscillation (ENSO) and the influence of climatic variability were the main subjects of the current study, which made use of daily precipitation, maximum and minimum temperature data collected at 50 locations around the nation from 1990 to 2022. The study analysed Palmer Drought Severity Index (PDSI) over Morocco to evaluate the impact of climate indices such as the Oceanic Niño Index (ONI) and the North Atlantic Oscillation (NAO) on drought severity. It also investigated the changes in precipitation, temperature, and extreme event-related indices. Rainfall is used as a proxy for El Nino and La Nina, supported by a negative and significant correlation between Oceanic Nino Index (ONI) and rainfall. Attempted to understand the impact of the NAO on Morocco's agricultural production, particularly during the winter months. During negative NAO phases, winter temperatures can lead to reduced wheat yields by 35–45% during the El Niño years and decreased by 4–7% during the La Niña years compared to the actual yield. Relying on the NAO plays a crucial role in modulating the precipitation patterns, which implies that crop requires adequate soil moisture with no extreme temperature during the growing season in order to produce higher yield. ENSO events can indeed lead to these extreme conditions in selected locations, potentially impacting crop yields.

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.

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.

ENSO predictive analytics based on layered rendering

El Niño-Southern Oscillation (ENSO) is a periodic climate phenomenon in the equatorial Pacific that significantly influences global climate patterns. Accurate prediction and monitoring of ENSO events are essential for meteorological agencies and governmental institutions. This study introduces a content-guided attention module within a convolutional neural network to improve prediction accuracy. This module models inter-channel relationships and enhances information interaction by integrating channel and spatial attention weights. These advancements substantially improve prediction accuracy and help overcome the spring prediction barrier in ENSO forecasting. The research emphasizes global feature modeling and proposes a novel content-guided ENSO prediction model. It also includes an ocean data generation model utilizing global attention. Furthermore, a layered rendering technique is employed to invert ocean data, facilitating detailed analysis and contributing to the development of an ocean synthetic dataset.

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

BackgroundIncreasingly 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 the incidence of BD, and to identify the potential meteorological pathways moderated by ENSO in the ENSO-BD connections.MethodsBD 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.ResultsIn 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 mediated the ENSO’s effect on BD, with mediation proportions of 38.58% and 34.97%, respectively.ConclusionsLong-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.

Impacts of El Niño-Southern oscillation on multi-scale morphodynamics of an embayed beach in southern China

Increased coastal erosion and extreme oceanographic forcing driven by El Niño-Southern Oscillation (ENSO) along the Pacific coast are increasingly receiving concerns. Despite considerable attention, the specific impact of these phenomena on Chinese shorelines, particularly along the South China beaches, remains inadequately understood. To address this gap, this study conducted high-frequency surveys on the Qing'an Bay beach in South China and employ a profile fitting model to refined waterline extraction from monthly satellite images. The goal was to investigate the relationship between high-frequency shoreline changes and interannual climate variability (such as ENSO). The findings indicate that the coastal evolution is intricately linked to a combination of strong wave events, summer storms, winter cold waves, and the amplifying effects of ENSO. During La Niña phase, the sea level in the western Pacific experiences a rise, with associated storms proving particularly destructive to the beach environment, leading to violent oscillations in the coastline. Specifically, in the strong La Niña phases, significant wave heights markedly surpass neutral conditions, precipitating intensified sediment movement. However, it is imperative to recognize that shoreline changes alone do not fully characterize coastal erosion. Assessment must also encompass alterations in beach volume. By calculating beach volume per unit width that accounts for the influence of ENSO variability on the beach, the seasonal characteristics of the beach showed sediment losses in summer and autumn, and gains in winter and spring, which was more obvious during strong La Niña. Additionally, conceptual model analysis reveals that during the La Niña phase, the bay is fully exposed, whereas during the El Niño phase, significant headland sheltering is observed.

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.

The history of the El Niño–Southern Oscillation and sea surface salinity during 1376–1500 CE reconstructed by Porites coral δ18O from Huangyan Island, South China Sea

The El Niño–Southern Oscillation (ENSO) is the most influential climatic phenomenon affecting global ecosystems, water use, and agriculture on an interannual scale. However, limited instrumental records make it difficult to fully understand the characteristics of ENSO events. In this study, we used both monthly-resolved Porites coral δ18O records, i.e., living Porites corals of δ18O–HYDL4 (1992–2015) and subfossil Porites corals of δ18O–HYD3 (1376–1500 CE), from Huangyan Island in the South China Sea (SCS), to reconstruct the moderate intensity ENSO and sea surface salinity (SSS) during 1376–1500 CE. The results show that the SSS was higher but the frequency of moderate-to-high intensity ENSO events was lower than the present during 1376–1500 CE. ENSO activity was generally similar to or slightly lower than that of today, but it included several very strong ENSO events in the first substage (1376–1450 CE), while it was relatively quiet in the second substage (1451–1500 CE). More moderate-intensity ENSO events may have occurred in the relatively warm climate. The variation in coral δ18O was dominated by multiple factors in this region. SST, ENSO and the Pacific Decadal Oscillation (PDO) may be the dominant factors influencing the changes in coral δ18O at different timescales.

Projected Changes to Characteristics of El Niño‐Southern Oscillation, Indian Ocean Dipole, and Southern Annular Mode Events in the CMIP6 Models

AbstractIn this study we analyse projections of future changes to the El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Southern Annular Mode (SAM) using the latest generation of climate models. Multiple future scenarios are considered. We quantify the fraction of models that project future increases or decreases in the frequency and amplitude of ENSO, IOD, and SAM events in the late 21st century. Changes to the frequency of co‐occurring and consecutive driver phases are also examined. We find that while there is large inter‐model spread, the most common pathways correspond to more frequent ENSO events; weaker, less frequent IOD events; and stronger, but less frequent austral spring SAM events. There is no clear consensus on the change to the frequency of concurrent events, though we find a significant increase in La Niña‐ and El Niño‐only events occurring with neutral IOD and SAM. We also find a significant increase to the frequency of consecutive positive IOD events under a high emissions scenario, but no significant change to the frequency of consecutive ENSO or negative IOD events. In most models, the correlation between drivers, that is, ENSO and IOD, and ENSO and SAM, does not significantly change between the late 20th and late 21st century. These results indicate a high degree of internal variability in the models.

Spatiotemporal pattern of ENSO-induced modulation on landscape fires over Pacific Rim from 2001‒2020

While El Niño-Southern Oscillation (ENSO) modulates landscape fire activities across the Pacific Rim, the detailed patterns and mode-specific variations of these effects remain poorly understood. This study aims to address that gap by systematically assessing the spatiotemporal variations in burned areas from 2001‒2020 during different modes of ENSO, namely, Eastern Pacific (EP) El Niño, EP La Niña, Central Pacific (CP) El Niño and CP La Niña. We evaluate the modulation patterns using classical correlation and cross-spectrum analyses, focusing on five hotspot regions: Temperate North America (TENA), Southern Hemisphere South America (SHSA), Northern Hemisphere South America (NHSA), Equatorial Asia (EQAS) and Australia and New Zealand (AUST). El Niño and La Niña exhibit asymmetrical opposite effects on burned areas, as expected. The findings reveal spatial non-uniformity in the impact of ENSO on landscape fires, with La Niña enhancing burned areas in TENA and SHSA, whereas El Niño predominantly affects AUST, EQAS and NHSA. CP and EP ENSO events differ in intensity and their large-scale circulation patterns. These differences cause notable variations in the regional burned area. Water vapour redistribution emerges as the key driver. The study emphasises the heterogeneity in ENSO modes in regulating landscape fires, providing insights for future landscape fire risk assessment and prevention efforts under climate change.

Revisiting the inconsistent influence of El Niño-Southern Oscillation on the equatorial Atlantic

Abstract The impact of El Niño-Southern Oscillation (ENSO) on the equatorial Atlantic Zonal Mode (AZM) is investigated using two atmospheric reanalysis products and 44 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6). While the impact of ENSO on equatorial Atlantic SST is inconsistent, as previously reported, there is a very robust influence of decaying ENSO events in boreal spring on the contemporaneous surface zonal winds over the equatorial Atlantic, with El Niño events associated with anomalous easterlies that cool the equatorial Atlantic. This dynamic impact is counteracted by a thermodynamic impact, in which El Niño events cause changes in surface heat fluxes that lead to warming over the tropical Atlantic. The thermodynamic influence is active throughout the lifecycle of the ENSO event, but the dynamic influence is highly seasonal with a pronounced peak in boreal spring. Thus, a quickly decaying El Niño event will lead to warming, while a slowly decaying event will lead to cooling in the equatorial Atlantic. The ENSO-AZM relation is further complicated by partially independent Atlantic variability, in particular that associated with the South Atlantic subtropical dipole (SASD). Prediction experiments with a simple linear regression model support the role of the SASD as an AZM precursor. Many CMIP6 models show skillful predictions of the June-July-August AZM based on SST indices in the preceding December-January-February, with correlations above 0.5. When predictions are restricted to ENSO years, even more models exceed this threshold, but skill in the reanalyses remains relatively low, possibly due to insufficient training data.

Exploring climate stabilisation at different global warming levels in ACCESS-ESM-1.5

Abstract. Under the Paris Agreement, signatory nations aim to keep global warming well below 2 °C above pre-industrial levels and preferably below 1.5 °C. This implicitly requires achieving net-zero or net-negative greenhouse gas emissions to ensure long-term global temperature stabilisation or reduction. Despite this requirement, there have been few analyses of stabilised climates, and there is a lack of model experiments to address our need for understanding the implications of the Paris Agreement. Here, we describe a new set of experiments using the Australian Community Climate and Earth System Simulator Earth system model (ACCESS-ESM-1.5) that enables the analysis of climate evolution under net-zero emissions, and we present initial results. Seven 1000-year-long simulations were run with global temperatures stabilising at levels in line with the Paris Agreement and at a range of higher global warming levels (GWLs). We provide an overview of the experimental design and use these simulations to demonstrate the consequences of delayed attainment of global net-zero carbon dioxide emissions. We show that there are substantial differences between transient and stabilising climate states and differences in stabilisation between GWLs. As the climate stabilises under net-zero emissions, we identify significant and robust changes in temperature and precipitation patterns including continued Southern Ocean warming and changes in regional precipitation trends. Changes under net-zero emissions differ greatly between regions, including contrasting trajectories of sea ice extent between the Arctic and Antarctic. We also examine the El Niño–Southern Oscillation (ENSO) and find evidence of reduced amplitude and frequency of ENSO events under climate stabilisation relative to projections under transient warming. An analysis at specific GWLs shows that significant regional changes continue for centuries after emission cessation and that these changes are stronger at higher GWLs. Our findings suggest substantial long-term climate changes are possible even under net-zero emission pathways. These simulations are available for use in the community and will hopefully motivate further experiments and analyses based on other Earth system models.

Impact of ENSO on Cloud Distribution and Rainfall Variability in Tangerang Regency

A type of climate variation in the Pacific Ocean known as El Niño Southern Oscillation (ENSO) is defined by an increase in sea surface temperature (SST) in the Central and Eastern equatorial areas, which affects the amount of rainfall that falls and increases. In Indonesia, the rainy season typically persists from October to March, whereas the dry season persists from April to September. Research on the influence of ENSO on rainfall has been carried out in several areas, but has not been carried out in the Tangerang area. This study aims to ascertain how the ENSO phenomena affect rainfall fluctuations and cloud distribution in the Regency of Tangerang. The secondary data, which includes information on rainfall, cloud cover, wind direction, and speed, was acquired from BMKG Meteorology Budiarto. In addition, data from the Australian Bureau of Meteorology (BOM) website's Southern Oscillation Index (SOI) was used. Surface weather analysis and Pearson correlation analysis are the data analysis techniques used. The results presented that based on surface weather study, ENSO events had a consequence on cloud distribution in Tangerang Regency. The clouds lead when the ENSO phenomenon occurs, namely Cumulus and Nimbostratus clouds with a 4-8 octa cloud cover. Meanwhile, the correlation test results show that ENSO influences seasonal and annual rainfall variations in the district of Tangerang. The largest correlation between SOI and annual rainfall occurred in 2015 with a correlation value of r-0.84 (very strong). Meanwhile, the greatest correlation between SOI and seasonal rainfall occurred in July-September with a correlation value of r=0.67 (strong).

Global Marine Heatwaves Under Different Flavors of ENSO

AbstractMarine heatwaves (MHWs) have caused devasting ecological and socioeconomic impacts worldwide. Understanding the connection of regional events to large‐scale climatic drivers is key for enhancing predictability and mitigating MHW impacts. Despite the reported connection between MHWs globally and El Niño–Southern Oscillation (ENSO), establishing statistically significant links between different types of ENSO events and MHWs remains challenging due to the limited duration of observational data. Here, we use 10,000 years of simulations from a Linear Inverse Model (LIM) to address this issue. Our findings reveal distinct connections between MHWs and ENSO, with diverging influences from different flavors of El Niño and La Niña events. In addition, under long‐lasting El Niño conditions, the likelihood of MHWs increases by up to 12‐fold in the Indian and Pacific Oceans. This study highlights the global connections between ENSO diversity and variations in MHW events.

Paired coral Sr/Ca and δ18O records reveal increasing ENSO influence on Malaysian Borneo's hydroclimate

The El Niño Southern Oscillation (ENSO) is a worldwide climate phenomenon impacting temperatures and precipitation regimes across the globe. Previous studies have shown this climate phenomenon to influence Malaysian Borneo's hydroclimate. In the context of a changing climate and increasingly strong extreme ENSO events, understanding the influence of ENSO on this region, and its evolution through time, is essential to better constrain the future impacts it will have on the Maritime Continent's hydroclimate. Here, we used coupled δ18O and Sr/Ca records from massive corals' carbonate calcium skeletons to build a proxy for past hydroclimate: δ18Oseawater (δ18Osw) and compensate for the limited dependable instrumental data in most of the 20th century. We assessed our two 90 and 60-year-long δ18Osw records' quality as proxies for regional hydroclimate by correlating them with different instrumental salinity datasets before performing moving windowed correlations with the NINO3.4 index, an indicator of ENSO state.Results show that agreement between geochemical proxies and instrumental data highly depends on the chosen dataset, study site location, period, and monsoon season, with stronger agreement with more recent data, pointing towards insufficient data quality when going far back in time. More importantly, when correlated against the NINO3.4 index, our δ18Osw records showed a growing correlation for most of their respective lengths. From the 1980s, we found an increasing influence of ENSO on the local hydroclimate with correlation coefficients r > 0.8 during the wet monsoon season. Our findings highlight the differences in results depending on the chosen observational dataset, time scale, or period of the year, and stress the importance of such geochemical archives to better understand the impacts of ENSO across periods predating reliable instrumental data. More importantly, our findings show how the concurrent evolution of the IOD, and the PDV affect ENSO and ultimately, northwestern Borneo's hydroclimate through their teleconnections.