Oscillation Events Research Articles

Analisis Korelasi Statistikal Fenomena Kejadian ENSO dan MJO terhadap Kondisi Klimatologis di Provinsi Riau

El Nino-Southern Oscillation (ENSO) and Madden-Julian Oscillation (MJO) events are significant factors in the global climate system. Riau Province, located on the island of Sumatra, is highly influenced by these phenomena. This study collects climate data from weather stations in Riau Province and reliable sources for ENSO and MJO indices. Statistical analyses, including correlation and regression, are employed to determine the relationship between climate variables in Riau Province and ENSO and MJO. Based on data from 2001-2019, the results reveal a medium category correlation value (r = 0.452) with coefficients a and b of 1.288 and 0.089, respectively. The increased MJO value contrasts with the rainfall during the 2001-2019 timeframe. This information serves as a reference for understanding the ENSO and MJO phenomena in the Riau region.

Small-Signal Stability Analysis and MOSMA-Based Optimization Control Strategy of OWF with MMC-HVDC Grid Connection.

The recent oscillation events in offshore wind farms (OWFs) connected via a modular multilevel-converter-based HVDC (MMC-HVDC) system are developing towards a wider frequency band, which causes complex a small-signal interaction phenomenon and difficulties in the stability analysis and control. In this paper, the wideband dynamic interaction mechanism is investigated based on the impedance analysis method and an improved control strategy using an optimization algorithm is proposed to improve the small-signal stability and reduce the oscillation risks. First, the detailed impedance models of the grid-connected system are established considering the distribution characteristics of the submarine cable, control delay and frequency coupling effect. Then, combined with the active damping control method, the wideband resonance mechanism is analyzed, and the stability constraints of controller parameters are obtained using the impedance stability criterion. Finally, an improved multi-objective slime mold algorithm (MOSMA)-based coordinated optimization control strategy is proposed to enhance the adaptability of the controller parameters and the wideband damping ability of a grid-connected system, which can improve the wideband stability of the system. The simulation and experimental results verify the proposed control strategy.

An Extreme Marine Heatwave Event in the Yellow Sea during Winter 2019/20: Causes and Consequences

Increasing evidence has shown that marine heatwaves (MHWs) have destructive impacts on marine ecosystems, and understanding the causes of these events is beneficial for mitigating the associated adverse effects on the provision of ecosystem services. During the 2019/20 boreal winter, a long-lasting extreme MHW event was recorded (over 90 days) in the Yellow Sea (YS). Observations and numerical experiments revealed that the unprecedented winter MHW event was initiated and sustained by a significant decrease in ocean heat loss in the YS, which may be associated with the pronounced weakening of the Siberian high system induced by an extreme positive Arctic Oscillation (AO) event. A weakened northerly wind is the essential prerequisite, while the extreme AO event is only a trigger for the winter MHW in the YS. It was also found that the extreme winter MHW event is likely to substantially affect the seasonal evolution of the vertical thermal structure, which may have a great impact on the whole ecosystem in the YS. This study provides new insights for the prediction of winter MHWs in the YS, as well as their effects on marine ecosystems in a changing climate.

ATTRIBUTION ANALYSIS OF CLIMATE CHANGE AND HUMAN ACTIVITIES TO WATER VOLUME VARIATION IN LARGE LAKES

Abstract. Lakes are important components of the Earth's surface water bodies, and their fluctuating water levels and changing water volumes can have an important impact on ecological processes and landscape patterns within a watershed. Climate change and human activities are the main drivers of water volume changes in lakes. We applied a long time series analysis approach using classical statistics and geographic information system (GIS) technics to quantitatively attribute water volume variations in Lake Victoria from 2000 to 2019. We examined several drivers of lake water volume variations: meteorological factors including regional climate change (precipitation, evaporation) and global climate change (El Niño/Southern Oscillation events), and anthropogenic factors including socio-economic development and land use/cover change. The results show that regional climate change has a greater impact on lake water volume variations than global climate change; among them, the correlation coefficient between precipitation and lake water volume variations is the largest (0.410), with an impact lag of 1 month. For anthropogenic factors, variations in lake water volume are more pronounced in areas with rapid economic development and high population growth, with correlation coefficients greater than 0.440. Different types of land use/cover have varying impacts on Lake Victoria's water volume variations. Overall, the influence of anthropogenic factors is greater than that of meteorological factors. This study results not only provides a scientific basis for exploring the hydrological changes and their drivers in the world's large transboundary lakes, but also be great scientific significance to rational use of water resources and sustainable regional development.

Observed Anomaly of Temperature and Mixed Layer Depth Associated with the Madden Julian Oscillation (MJO) Active Phase in the Banda Sea, Indonesia

The eastward propagation of atmospheric waves along the equatorial band from the central equatorial Indian Ocean to the western Pacific Ocean passing through the Indonesian Maritime Continent (IMC), known as the intraseasonal Madden Julian Oscillation (MJO) event, plays an important role on modulating both atmospheric and upper ocean dynamics along its path. This study aims to investigate the MJO active phase dynamics and its impact on changes in near-surface seawater temperature and mixed layer depth (MLD) anomaly in the Banda Sea Indonesia, using multi-datasets of atmospheric reanalysis, satellites derived sea surface temperature (SST), and Argo float between 2017 - 2018. This study revealed that the MJO waves propagate eastward along the southern equator-line over the IMC and pass through the Banda Sea, associated with significant decreased on Outgoing Longwave Radiation (OLR) and increased in zonal wind speed at 850hPa. The study result shows anomalous increased on surface wind speed and SST cooling during of MJO active phase. The amplitude peaks of filtered ocean-atmosphere variables range between 30 – 60 days. Argo float datasets in the Banda Sea for the first time captured upper ocean responses to the arrival of the MJO active phase, as characterized by a negative temperature anomaly of ~0.3°C in the surface mixed layer, large temperature anomaly of ~0.8°C in the thermocline layer and the deepening of the MLD of ~25 m. Hence, the MJO active phase impacts significantly on surface and vertical temperature cooling and regulate upper ocean mixing intensity in the Banda Sea.

Variability, cycles, and trends of mean air temperature north of Colombia

Climate variability is of global interest due to its socioeconomic and environmental effects on the world’s population. In Colombia, temperature changes affect food security, especially for the most vulnerable people in the Caribbean region. We analyzed monthly air temperature in northeastern Colombia (Cesar, La Guajira, and Magdalena departments). We reconstructed time series with missing data using nonlinear principal component analysis. Subsequently, temporal variability, associations with events of climatic variability, and temporal trends were evaluated. Periodicity analyses indicate the dominance of annual variability, although statistically significant associations with periods between 3 and 7 years show the influence of El Niño-Southern Oscillation (ENSO) events. The Spearman correlation coefficient with N = 360 and 95% significance shows a better association with the Multivariate ENSO Index (rsp mean = 0.38) and the Southern Oscillation Index (rsp mean = –0.32). The multi-year monthly analysis shows positive trends, with maximum values between March (1.04 ºC month–1), and June (1.07 ºC month–1) in the valley of the Cesar department, and a minimum in March, at the northernmost La Guajira (0.2 ºC month–1).

Impacts of Strong El Niño–Southern Oscillation Events on Wintertime Northern Hemisphere Storm Tracks in Two Pacific Decadal Oscillation Phases during 1950–2010

Northern Hemisphere storm track activities (NHSTs) not only influence the weather and climate along their paths, but they also play a crucial role in climate systems by systematically transporting heat, momentum, and moisture. Distinguish from previous studies focusing on atmospheric circulation anomalies, this study provides further evidence of wintertime NHSTs variation under the influence of strong El Niño–Southern Oscillation (ENSO) events and Pacific Decadal Oscillation (PDO) variation with ERA-20C reanalysis data, from two mathematical aspects of linear superposition and nonlinear modulation. While ENSO warm/cold events lead the entire NHSTs to a general south/north shift, the ENSO impact in two PDO phases exhibits a remarkable difference with the PDO phase. The Pacific storm track (PST) anomalies largely strengthen equatorward and downstream when both ENSO and PDO are in phase, but its anomalies tend to be weakened when ENSO and PDO are out of phase. Generally, the opposite situation occurs with Atlantic storm track (AST) anomalies, which display a strengthening dipole pattern when ENSO and PDO are out of phase. Apparently, the result is roughly a linear superposition of ENSO and PDO-only impacts. Nevertheless, further analyses indicate that the nonlinear modulation of PDO on the ENSO impact on NHSTs exists. With respect to the PST, it exhibits approximately parallel bands of south-north dipole anomalies when ENSO is in the PDO positive phase, but only the south branch remains when ENSO is in the PDO negative phase. Generally, a similar situation occurs to AST anomalies over the Atlantic Ocean. The modulation may be mainly associated with the atmospheric mean flow anomalies and the midlatitude sea surface temperature anomalies to ENSO in different PDO phases. To some extent, the results may be beneficial for understanding the variation of extreme weather events brought by NHSTs.

Impact of El Niño Southern Oscillation on CO2 and Solar‐Induced Fluorescence Over the Indo‐Pacific Region

AbstractOver the tropical Indo‐Pacific, we explore the variations of Solar‐Induced Fluorescence (SIF), CO2, and precipitation during El Niño Southern Oscillation (ENSO) events verse other times. Based on various data sets, we analyze the time series of deseasonalized precipitation, vertical velocity, SIF, and CO2 across the Indo‐Pacific region. Our analysis reveals that there is less precipitation, more sinking air, lower SIF, and higher carbon dioxide over the Indo‐Pacific region during the El Niño events compared to other times. We also explore the spatial patterns of different variables to gain a deeper understanding of their relationships. The spatial analysis suggests that less precipitation resulting from predominant sinking air not only leads to lower SIF values by reducing photosynthetic activities but also triggers more biomass burning, which contribute to an increase in atmospheric CO2 levels across most areas of the Indo‐Pacific region. The comparative study between observational analyses and numerical simulation by the NOAA CarbonTracker model indicates that the model can simulate the increase of atmospheric column CO2 during the El Niño event, although there are some difficulties in capturing the correct spatial pattern. The results of this study can significantly enhance our understanding of the spatial‐temporal variabilities of atmospheric CO2 concentration and the observational characteristics can be used to enhance models. Furthermore, the complex interactions between ENSO and other variables revealed in this study improve our understanding of how ENSO influences the biosphere and carbon cycle.

Seasonal Variation of Rainfall in Indonesia under Normal Conditions without ENSO and IOD Events from 1981-2021

This study explores the seasonal rainfall variation in Indonesia under normal conditions, excluding the influence of El-Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events. Monthly rainfall data is sourced from the CHIRPS dataset, and wind and atmospheric movement data are obtained from the ECMWF ERA-5 dataset. Identification of normal conditions relies on the ONI and DMI indices. Results reveal that the seasonal rainfall patterns during these normal conditions align with previous studies encompassing all atmospheric conditions. Indonesia typically witnesses one or two peaks in rainfall annually, notably in December-January-February (DJF), May-June (MJ), and March-April-May (MAM), consistent with established rainfall zone classifications in earlier research. A nuanced discrepancy emerges in the timing of the May-June peak, previously noted in June-July. The congruence in peak rainfall patterns during normal conditions, as observed in prior comprehensive research, implies a negligible influence of ENSO and IOD on the timing of seasonal rainfall peaks. Although ENSO and IOD may impact the amplitude of seasonal variation, particularly in Indonesia's eastern and western regions, they do not alter the temporal occurrence of rainfall peaks. Consequently, the timing of rainfall peaks in Indonesia predominantly reflects the combined influence of the Asian and Australian monsoons.

The possibility of rainfall nowcasting using atmospheric electric field

The possibility of rainfall nowcasting using a new parameter — atmospheric electric field (potential gradient, PG) — is investigated. The temporal behavior of the PG measured by a ground-based electric field mill before rainfall was analyzed at the University of Reading Atmospheric Observatory (51.441°N, 0.938°W, 66 m) in 2007–2021 and the Nor Amberd research station (40.367°N, 45.258°E, 2000 m) in 2013–2018. The PG tend to show abnormal oscillations before the precipitation cloud arrived at the PG measuring site. Several rules were applied to determine rainfall and PG oscillation events. Statistical analysis was conducted, and the results showed that PG oscillations occurred before and overlap with 48% (54%) of rainfall events, and PG oscillations occurred in one hour before 68% (77%) of rainfall events started at the University of Reading Atmospheric Observatory site (Nor Amberd research station site). A PG-based rainfall nowcasting model is proposed, which is constructed using machine learning techniques Fully Connected Neural Network and Tree-based Pipeline Optimization Tool. The hit rate, false alarm rate, missed detection rate, TS score of the model reached 93.8% (94.6%), 36% (37.4%), 37.7% (39.3%), 46.1% (44.5%) respectively, which is comparable to that of the state-of-the-art rainfall nowcasting methods. And the heavy rainfall hit rate reached 41.5% (36.4%). PG show a great potential to be used as a new parameter for rainfall nowcasting. And the effect of rainfall nowcasting method that proposed in this paper is barely affected by the weather conditions and the PG measuring range of different sites. Moreover, PG stands out among many other parameters because long-term and stable PG measurements can be obtained at a very low cost using an electric field mill.

Nonlinear time series analysis of coastal temperatures and El Niño–Southern Oscillation events in the eastern South Pacific

Abstract. We carry out a nonlinear time series analysis motivated by dynamical systems theory to investigate the links between temperatures on the eastern South Pacific coast, influenced by the Humboldt Current System, and El Niño–Southern Oscillation (ENSO) events. To this aim, we use a set of 16 oceanic and atmospheric temperature time series from Chilean coastal stations distributed between 18 and 45∘ S. The spectral analysis indicates periodicities that can be related to both internal and external forcing, involving not only ENSO, but also the Pacific Decadal Oscillation, the Southern Annual Mode, the Quasi-Biennial Oscillation and the lunar nodal cycle. The asymptotic neural network test for chaos based on the largest global Lyapunov exponent indicates that the temperature dynamics along the Chilean coast is not chaotic. We use local Lyapunov exponents to characterize the short-term stability of the series. Using a cross-entropy test, we find that two stations in northern Chile, one oceanic (Iquique) and one atmospheric (Arica), present a significant positive cross-dependence between local Lyapunov exponents and ENSO. Iquique is the station that presents the greater number of regional characteristics and correlates with ENSO differently from the rest. The unique large-scale study area, combined with time series from hitherto unused sources (Chilean naval records), reveals the nonlinear dynamics of climate variability in Chile.

Energy balance closure and evapotranspiration hysteresis in central Amazon under contrasting conditions during the GoAmazon project in 2014 and 2015

The Amazon region stands out as Earth's largest and most prominent terrestrial convective center, significantly influencing precipitation patterns through the substantial net radiation at the Earth's surface (Rn). This radiation is further divided into sensible heat (H) and latent heat (LE) fluxes, underscoring the critical need to investigate the intricate exchanges of energy between ecosystems and the atmosphere while also scrutinizing the closure of the energy balance (EBC). Such studies are of paramount importance for gaining a comprehensive understanding of natural process dynamics. This research was undertaken to refine our comprehension of the temporal variability of energy fluxes, energy balance closure, and the phenomenon of evapotranspiration (ET) hysteresis in relation to key atmospheric variables, namely, Rn, air temperature, and vapor pressure deficit (VPD), within the central Amazon region. This investigation spanned a typical year (2014) and accounted for the influence of an El Niño Southern Oscillation (ENSO) event (2015). The findings illuminated that LE constituted the predominant component of the energy balance in both years, comprising approximately 70% of the total energy flux, except during the dry season of 2015 when H took precedence, accounting for 55% of the total energy exchange due to the ENSO event. The EBC exhibited an underestimation of turbulent fluxes (H + LE) of around 24% relative to the available energy (Rn - G). A more robust closure was observed during the dry period of 2015, reaching 82%, suggesting heightened uncertainty in LE estimates. In the context of ET, clockwise hysteresis loops were observed concerning air temperature and VPD. The relationship between ET and Rn displayed a linear response to solar radiation, with the intensity of ET hysteresis becoming more pronounced when correlated with air temperature and VPD.

Analysis of ENSO influence on the solar and wind potential of the department of La Guajira

ABSTRACT This study explores how solar radiation and wind speed in La Guajira vary in response to El Niño/Southern Oscillation (ENSO) events. Climatic data were collected and analysed at three iconic locations: Upper Guajira, Middle Guajira, and Lower Guajira, over a span of three decades. The data were obtained from reliable sources such as IDEAM and NASA stations. To identify El Niño and La Niña periods, Southern Oscillation Index (ONI) data were utilised. Subsequently, the data underwent detailed statistical analyses, including hypothesis testing. During El Niño, solar radiation is altered solely in Lower Guajira; for La Niña, no significant changes in solar radiation across the region are observed. Wind speed, for the most part, remains unaffected by the studied climatic phenomena in these areas, with an exception in Middle Guajira during La Niña, where it is notably influenced.

Multiscale Spatio‐Temporal Variations of Suspended Sediment Fronts in the Semi‐Enclosed Bohai Sea, China

AbstractSuspended sediment fronts (SSFs) significantly affect water quality, ecology, and geomorphological evolution of estuarine and coastal waters. Based on 10‐year suspended sediment concentration data derived from satellite images, the multiscale spatio‐temporal variability of SSFs in the Bohai Sea was studied. Frontal probability (FP) was used to quantify the intensity of frontal activity. The 10‐year averaged FP was higher near the coast and decreased with increasing offshore distance. The arc‐shaped distributions of FP near the Yellow River Estuary revealed two tidal shear frontal zones. In the eastern Bohai Sea, 13 finger‐shaped high‐FP areas reflected the spatial pattern and fine structures of tidal sand ridges. The complex topography and strong tidal dynamics provided the essential conditions for frontogenesis. The seasonality of frontal activity was dominantly regulated by the change in wind waves associated with monsoons and stratification. The direct or indirect effects of sediment discharges from the Yellow River and Liaohe River on seasonal and annual variations of frontal activity only existed within close proximity to the estuaries. Frontal activity generally showed an interannual weakening trend, especially in the Laizhou Bay (−0.27%/yr), while an opposite trend was identified in the Liaodong Bay (0.10%/yr). This phenomenon was related to the interannual variations of wind speeds. Meanwhile, wind speed anomalies caused by El Niño‐Southern Oscillation events could explain the significant interannual fluctuations in frontal activity such that, frontal activity was significantly enhanced (suppressed) when El Niño (La Niña) events occurred, especially during 2015–2016 (2017–2018).

Generalized Turbine Model Based Analysis and Simulation of Ultra-Low Frequency Oscillation of Hydropower Units

The occurrence of ultra-low frequency oscillation (ULFO) events in the power grid has a significant number of hydropower units in recent years. Considering this aspect, relevant studies have shown that the turbine model has an important impact on the ULFO behavior of hydropower units. Based on the study of the generalized turbine model, the flow factor closely related to the inherent parameters of the turbine and the variation of the generating flow is defined in this paper. The ULFO model of the hydropower unit with full consideration of the flow factor is established. Based on the frequency characteristics of the system and the Routh stability criterion, the mechanism of the influence of the flow factor on the ULFO behavior of the hydropower unit is analyzed. The simulation results of single-machine and multi-machine systems show that, compared with the ideal turbine model, the generalized turbine model considering the flow factor can increase the stability margin of the system. It can provide greater damping torque and restrain the ULFO behavior of hydropower units. The flow factor is larger, and the suppression effect of the ULFO is more obvious.

Evaluating the impacts of environmental and fishery variability on the distribution of bigeye tuna in the Pacific Ocean

Abstract Climate change-induced variabilities in the environment and fishing pressure affect the distribution and abundance of bigeye tuna in the Pacific Ocean. Understanding the causal relationships among these factors is complicated and challenging. We constructed a multi-output neural network model based on data from four types of bigeye tuna fisheries (longline and purse seine in the west-central and eastern Pacific Ocean, respectively) and marine environmental data, aiming to analyse the response of bigeye tuna to natural and anthropogenic factors from 1995 to 2019 in the Pacific Ocean. The input layer weights were used to explore the importance of environmental variable, while the output layer weights evaluated the contribution of fishing operations. These factors determined the final spatiotemporal distribution and abundance dynamics for bigeye tuna. The optimal model predicted a strong correlation between the locations of major habitats and El Niño southern Oscillation (ENSO) events, indicating that bigeye tuna abundance dynamics respond to the intensity of climate variability. During El Niño events, suitable conditions lead to an expansion of the main habitats east of 170°W, while during La Niña events, the strengthening of the westward advection leads to the contraction of major habitats west of 170°W. Furthermore, the resource abundance of bigeye tuna is predicted to be higher during moderate to weak El Niño events than during strong El Niño events. The abundances in purse seine and longline-dependent fisheries demonstrate significant different distribution patterns under different ENSO events, reflecting the unique environmental preferences at different life stages of bigeye tuna. Given the increasing frequency of climate variability and escalating fishing pressures, our findings provide beneficial insights for the sustainable development of bigeye tuna resource in the Pacific Ocean.

Data-driven multiscale model of macaque auditory thalamocortical circuits reproduces in vivo dynamics

We developed a detailed model of macaque auditory thalamocortical circuits, including primary auditory cortex (A1), medial geniculate body (MGB), and thalamic reticular nucleus, utilizing the NEURON simulator and NetPyNE tool. The A1 model simulates a cortical column with over 12,000 neurons and 25 million synapses, incorporating data on cell-type-specific neuron densities, morphology, and connectivity across six cortical layers. It is reciprocally connected to the MGB thalamus, which includes interneurons and core and matrix-layer-specific projections to A1. The model simulates multiscale measures, including physiological firing rates, local field potentials (LFPs), current source densities (CSDs), and electroencephalography (EEG) signals. Laminar CSD patterns, during spontaneous activity and in response to broadband noise stimulus trains, mirror experimental findings. Physiological oscillations emerge spontaneously across frequency bands comparable to those recorded invivo. We elucidate population-specific contributions to observed oscillation events and relate them to firing and presynaptic input patterns. The model offers a quantitative theoretical framework to integrate and interpret experimental data and predict its underlying cellular and circuit mechanisms.

Multi‐Year Predictability of Global Sea Surface Temperature Using Model‐Analogs

AbstractThe multi‐year predictability of global sea surface temperature (SST) is examined by applying a model‐analog method to four control simulations to make forecasts at leads of 1–36 months over 1961–2015. The forecasts are found to have skill for annual mean SST at Year 2 (i.e., leads of 13–24 months) or even Year 3 (i.e., leads of 25–36 months) in the tropical Pacific, the North and South Pacific, the southwest Indian Ocean, and the northwestern tropical Atlantic. The seasonality in forecast skill suggests that July is the best time to initialize multi‐year forecasts. The evolution of forecast skill for tropical Pacific SSTs indicates that the predictability of some El Niño Southern Oscillation events is nearly the same at leads of 6 and 18 or 24 months. Further, these El Niño and La Niña events can be predicted at leads of up to 24 and 30 months, respectively.

Analysis of Extreme Precipitation Variation Characteristics and the Influencing Factors in the Yunnan-Guizhou Plateau Region, China

The increase of extreme precipitation (EP) frequency and the aggravation of disasters have seriously disrupted the normal economic and social development of human beings. The complex topography of the Yunnan-Guizhou Plateau region (YGPR) and the fact that moisture originates from two different directions, the Pacific Ocean and the Indian Ocean, make the mechanism of EP more complicated. Exploring the variation characteristics and influencing factors of EP in YGPR is of great significance for regional disaster prevention and mitigation and water resources management. In this study, 11 extreme precipitation indices (EPIs) defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) were calculated based on daily precipitation data of 1960–2020 from 83 national meteorological stations in the study area. The Mann–Kendall test and Wavelet analysis were used to analyze the variation characteristics of EP and explore the influence mechanisms of geographical factors and atmospheric circulation on EP in the spatial and temporal perspective. The conclusions are as follows: (1) The EP of the study area has an overall increasing trend in the research period, with the increase of persistent dry days, the precipitation concentration, intensity, and extreme heavy precipitation (EHP); (2) It shows the obvious spatial difference in the study area, with the high-value areas of extreme drought (ED) in the northwestern region and the total annual precipitation, EHP, and intensity in the southeastern region. In addition, ED and EHP tends to increase in the western region of the study area as well as in the middle east and southeast; (3) EHP is significantly positively correlated with longitude and highly negatively with latitude. Meanwhile, EHP shows a correlation with altitude (negative at low altitude and positive at high altitude); (4) The degree of drought change is greatly affected by North Atlantic Oscillation/El Niño-Southern Oscillation (ENSO) events. The variation of extreme heavy precipitation is greatly influenced by the summer monsoon of South Asian, East Asian, and South China Sea; (5) All the EPIs show persistence. The study results can contribute to the understanding of EP variation in the study area and provide some scientific references for regional water resource management, meteorological warning, and agricultural production safeguard.

Enhanced joint impact of western hemispheric precursors increases extreme El Niño frequency under greenhouse warming

Sea surface temperature variability over the north tropical Atlantic (NTA) and over the subtropical northeast Pacific (SNP), which is referred to as the North Pacific Meridional Mode, during the early boreal spring is known to trigger El Niño–Southern Oscillation (ENSO) events. The future changes of the influence of those northwestern hemispheric precursors on ENSO are usually examined separately, even though their joint impacts significantly differ from the individual impacts. Here, we show that the impacts of both NTA and SNP on ENSO significantly increase under greenhouse warming and that the degrees of enhancement are closely linked. The wetter mean state over the off-equatorial eastern Pacific is a single contributor that controls the impacts of both NTA and SNP on ENSO. The enhanced joint impacts of the northwestern hemispheric precursors on ENSO increase the occurrences of extreme El Niño events and the ENSO predictability under greenhouse warming.