El Nino-Southern Oscillation Cycle Research Articles

Investigating Convective Processes Underlying ENSO: New Insights Into the Fixed Anvil Temperature Hypothesis

AbstractInterannual variations provide insight into the sensitivity of convective processes. Thus, CloudSat and ERA5 are used to explore the relationship among convective cores, outflows and environmental conditions during El Niño‐Southern Oscillation (ENSO) cycles. Results reveal greater upper‐tropospheric stability during El Niño, resulting in a lower level of neutral buoyancy compared to La Niña. However, outflow levels remain relatively consistent across ENSO cycles. This suggests that, despite less favorable conditions for deep convection during El Niño, stronger convective intensity is required to achieve outflow levels comparable to those in La Niña. Indeed, our results suggest that convection observed during El Niño tends to have broader cores and lower entrainment rates, translating to greater intensity compared to La Niña. These findings emphasize the importance of considering both large‐scale and convective‐scale processes, providing an update to the fixed anvil temperature (FAT) and the proportionately higher anvil temperature (PHAT) hypotheses as originally proposed.

A new tool for studying seasonality and spatio-temporal structure of ENSO cycles in data and ESM simulations

Abstract In this work, we present a new diagnostic tool for El Niño Southern Oscillation (ENSO) simulations in Earth System Models (ESMs) based on the analysis of upper ocean heat content data. It allows us to identify the seasonally dependent structure of temperature anomalies in the equatorial Pacific Ocean in the form of a dominant spatio-temporal pattern. We demonstrate the results of applying a tool to analysis of real data as well as climate simulations in two versions of the Institute of Numerical Mathematics ESM. We find that the latest version of the model, with improved parameterizations of clouds, large-scale condensation, and aerosols, provides significantly better reproduction of ENSO-related structure of anomalies, as well as the phase locking of ENSO to the annual cycle. We recommend to use the tool for diagnostic analysis of ESMs regarding simulation of climate phenomena with strong seasonality.

PDO and AMO Modulation of the ENSO–Asian Summer Monsoon Teleconnection During the Last Millennium

AbstractObservations show that the teleconnection between the El Niño‐Southern Oscillation (ENSO) and the Asian summer monsoon (ASM) is non‐stationary. However, the underlying mechanisms are poorly understood due to inadequate availability of reliable, long‐term observations. This study uses two state‐of‐the‐art data assimilation‐based reconstructions of last millennium climate to examine changes in the ENSO–ASM teleconnection; we investigate how modes of (multi‐)decadal climate variability (namely, the Pacific Decadal Oscillation, PDO, and the Atlantic Multidecadal Oscillation, AMO) modulate the ENSO–ASM relationship. Our analyses reveal that the PDO exerts a more pronounced impact on ASM variability than the AMO. By comparing different linear regression models, we find that including the PDO in addition to ENSO cycles can improve prediction of the ASM, especially for the Indian summer monsoon. In particular, dry (wet) anomalies caused by El Niño (La Niña) over India become enhanced during the positive (negative) PDO phases due to a compounding effect. However, composite differences in the ENSO–ASM relationship between positive and negative phases of the PDO and AMO are not statistically significant. A significant influence of the PDO/AMO on the ENSO–ASM relationship occurred only over a limited period within the last millennium. By leveraging the long‐term paleoclimate reconstructions, we document and interrogate the non‐stationary nature of the PDO and AMO in modulating the ENSO–ASM relationship.

The Salinity of Coastal Waters as a Bellwether for Global Water Cycle Changes

AbstractWhile the global water cycle has been studied previously based on land and open ocean studies, here we use coastal satellite sea surface salinity (SSS) data to show that in global aggregate, SSS variations near coasts are strongly correlated with global water cycle variability driven by El Niño Southern Oscillation (ENSO). This is a significant finding as we demonstrate that open ocean SSS variability is not as sensitive to ENSO and global water cycle variability as the coastal oceans at interannual timescales. Aggregated global coastal SSS could therefore be used as a proxy for detection of changes in the large‐scale cycling of water between the oceans and continents. Moreover, we identify major potential “hotspots” on land and in the coastal ocean that tend to drive global coastal salinity variability, and which may consequently be most sensitive to future physical and biological impacts of water cycle changes on the coastal oceans.

Improved climate time series forecasts by machine learning and statistical models coupled with signature method: A case study with El Niño

The different phases of ENSO (El Niño Southern Oscillation) directly influence the occurrence of natural disasters and global warming. To limit the socio-economic impact, it is essential to develop simple and fast numerical models that can predict these different cycles. Here, we aimed to improve the predictive performance and extracting relevant information from climatic events by applying the signature method to time series models. After transforming the data using this signature method, we performed a comparative analysis of the statistical and machine learning models. In addition, we used PDP (Partial Dependence Plot) and SPRC (Standard Partial Regression Coefficient) to better understand the interactions between different climate indices.Our results showed that the best predictive performance was obtained when we use the signature method with the LSTM (R2 = 0.74) and Lasso (R2 = 0.79) models. Two complementary methods were used to highlight the influence of the following climate indices on ENSO cycle changes: NINO3, NINO3.4 and NPI (North Pacific Index). These methodologies also enabled us to determine the switchover thresholds, and order temporal variations. With this first application of the signature method to this type of time series, we obtained accurate forecasts on a 6-month scale with reduced computation time. This suggests that our methodology can be applied to many other fields of research that use multivariate time-series analyses.

Microbial shifts associated to ENSO-derived thermal anomalies reveal coral acclimation at holobiont level

The coral microbiome conforms a proxy to study effects of changing environmental conditions. However, scarce information exists regarding microbiome dynamics and host acclimation in response to environmental changes associated to global-scale disturbances. We assessed El Niño Southern Oscillation (ENSO)-derived thermal anomalies shifts in the bacterial microbiome of Pacifigorgia cairnsi (Gorgoniidae: Octocorallia) from the remote island of Malpelo in the Tropical Eastern Pacific. Malpelo is a hot spot of biodiversity and lacks direct coastal anthropogenic impacts. We evaluated the community composition and predicted functional profiles of the microbiome during 2015, 2017 and 2018, including different phases of ENSO cycle. The bacterial community diversity and composition between the warming and cooling phase were similar, but differed from the neutral phase. Relative abundances of different microbiome core members such as Endozoicomonas and Mycoplasma mainly drove these differences. An acclimated coral holobiont is suggested not just to warm but also to cold stress by embracing similar microbiome shifts and functional redundancy that allow maintaining coral’s viability under thermal stress. Responses of the microbiome of unperturbed sea fans such as P. cairnsi in Malpelo could be acting as an extended phenotype facilitating the acclimation at the holobiont level.

Enhanced multi-year predictability after El Niño and La Niña events

Several aspects of regional climate including near-surface temperature and precipitation are predictable on interannual to decadal time scales. Despite indications that some climate states may provide higher predictability than others, previous studies analysing decadal predictions typically sample a variety of initial conditions. Here we assess multi-year predictability conditional on the phase of the El Niño–Southern Oscillation (ENSO) at the time of prediction initialisation. We find that predictions starting with El Niño or La Niña conditions exhibit higher skill in predicting near-surface air temperature and precipitation multiple years in advance, compared to predictions initialised from neutral ENSO conditions. This holds true in idealised prediction experiments with the Community Climate System Model Version 4 and to a lesser extent also real-world predictions using the Community Earth System Model and a multi-model ensemble of hindcasts contributed to the Coupled Model Intercomparison Project Phase 6 Decadal Climate Prediction Project. This enhanced predictability following ENSO events is related to phase transitions as part of the ENSO cycle, and related global teleconnections. Our results indicate that certain initial states provide increased predictability, revealing windows of opportunity for more skillful multi-year predictions.

On the Impact of ENSO Cycles and Climate Change on Telescope Sites in Northern Chile

The Atacama desert stands as the most arid, non-polar, region on Earth and has accommodated a considerable portion of the world’s ground-based astronomical observatories for an extended period. The comprehension of factors important for observational conditions in this region, and the potential alterations induced by the escalating impact of climate change, are, therefore, of the utmost significance. In this study, we conduct an analysis of the surface-level air temperature, water vapour density, and astronomical seeing at the European Southern Observatory (commonly known by its acronym, ESO) telescope sites in northern Chile. Our findings reveal a discernible rise in temperature across all sites during the last decade. Moreover, we establish a correlation between the air temperature and water vapour density with the El Niño Southern Oscillation (ENSO) phases, wherein, the warm anomaly known as El Niño (EN) corresponds to drier observing conditions, coupled with higher maximum daily temperatures favouring more challenging near-infrared observations. The outcomes of this investigation have potential implications for the enhancement of the long-term scheduling of observations at telescope sites in northern Chile, thereby aiding in better planning and allocation of resources for the astronomy community.

Wind variability across the North Humboldt Upwelling System

Surface wind is taken as the primary driver of upwelling in the eastern boundary upwelling systems. The fluctuation of momentum flux associated with the variation in wind regulates the nutrient supply to the euphotic surface layer via changing the properties of oceanic mixed layer depth, the coastal and offshore upwelling, and horizontal advection. Here, the spatial and temporal variability of the surface wind field over the last seven decades across the Peruvian upwelling system is investigated. Strong fluctuations in seasonal to decadal timescales are found over the entire upwelling system. A semi-periodic wind fluctuation on an interannual timescale is found, which is closely related to the regional sea surface temperature and can be attributed to the El Niño Southern Oscillation (ENSO). However, the wind anomaly patterns during positive and negative phases of ENSO are not opposite, which suggests an asymmetric response of local wind to ENSO cycles. In addition, a semi-regular fluctuation on the decadal timescale is evident in the wind field, which can be attributed to the Interdecadal Pacific Oscillation (IPO). Our results show that the sea surface temperature over the Humboldt Upwelling System is closely connected to local wind stress and the wind stress curl. The SST wind stress co-variability seems more pronounced in the coastal upwelling cells, in which equatorward winds are very likely accompanied by robust cooling over the coastal zones. Over the past seven decades, wind speed underwent a slightly positive trend. However, the spatial pattern of the trend features considerable heterogeneity with larger values near the coastal upwelling cells.

ENSO phase space dynamics with an improved estimate of the thermocline depth

The recharge oscillator model of the El Niño Southern Oscillation (ENSO) describes the ENSO dynamics as an interaction between the eastern tropical Pacific sea surface temperatures (T) and subsurface heat content (thermocline depth; h), defining a dynamical cycle with different phases. h is often approximated on the basis of the depth of the 20 °C isotherm (Z20). In this study we will address how the estimation of h affects the representation of ENSO dynamics. We will compare the ENSO phase space with h estimated based on Z20 and based on the maximum gradient in the temperature profile (Zmxg). The results illustrate that the ENSO phase space is much closer to the idealised recharge oscillator model if based on Zmxg than if based on Z20. Using linear and non-linear recharge oscillator models fitted to the observed data illustrates that the Z20 estimate leads to artificial phase dependent structures in the ENSO phase space, which result from an in-phase correlation between h and T. Based on the Zmxg estimate the ENSO phase space diagram show very clear non-linear aspects in growth rates and phase speeds. Based on this estimate we can describe the ENSO cycle dynamics as a non-linear cycle that grows during the recharge and El Nino state, and decays during the La Nina states. The most extreme ENSO states are during the El Nino and discharge states, while the La Nina and recharge states do not have extreme states. It further has faster phase speeds after the El Nino state and slower phase speeds during and after the La Nina states. The analysis suggests that the ENSO phase speed is significantly positive in all phases, suggesting that ENSO is indeed a cycle. However, the phase speeds are closest to zero during and after the La Nina state, indicating that the ENSO cycle is most likely to stall in these states.

Model Hibrid Harmonik, ARMA dan Outlier Curah Hujan di Surabaya, Malang dan Banyuwangi

The main factors affecting the climate in Indonesia are monsoons, El Nino Southern Oscillation (ENSO) and sunspot cycles. Another influence is local characteristics, namely the geography and topography of each region. The harmonic model is an applied statistical model of Fourier series analysis. Because the harmonic model is a deterministic model with residuals that often still have autocorrelation, it is necessary to add a stochastic Autoregressive Integrated Moving Average (ARIMA) model. With the existence of 3 main factors that influence the climate in Indonesia with different seasonal periods, plus local influences, the bulk modeling with Seasonal ARIMA, Double S ARIMA is not enough so that a combination of harmonics, ARMA and Additive Outliers (AO) appears. The purpose of this study is to find the periodicity of rainfall and model rainfall time series data with hybrid harmonics, ARMA outliers. Periodogram analysis of monthly rainfall data for three cities in East Java shows a 1-year seasonal return period influenced by monsoons, an 11-year return period influenced by sunspots that cannot be detected. The monthly rainfall model for the city of Surabaya is the 2nd order Harmonic Hybrid Model, ARMA([1,9,11],0,0) and the outlier type , for the city of Banyuwangi is the 1st order Harmonic Hybrid Model, ARMA (1,0,0) and 2 outliers of type , , Malang city are first order Harmonic Hybrid models, ARMA([6,7],0,0) and outliers of type . First order Harmonic Hybrid models, ARMA and Outlier are better than ARIMA and Outlier models.
 Key words: Monsoon, ENSO, sunspot, harmonics, ARMA and outliers.

Utilization of El Niño–Southern Oscillation projected by climate models in improvement of seasonal precipitation predictability

AbstractImproved seasonal precipitation forecasts can enable more effective water resource management decisions in a number of sectors, including municipal supply, agriculture, hydropower generation, and tourism. This study develops an effective straightforward statistical approach to enhance the quality of seasonal precipitation forecasts through the utilization of El Niño–Southern Oscillation (ENSO) information projected by Coupled General Climate Models (CGCMs). A stochastic weather generation (WG) model is developed to predict seasonal precipitation condition on ENSO condition. The WG model links a nonhomogeneous Markov Chain representing ENSO occurrence model to a bivariate normal distribution for seasonal precipitation conditioned on ENSO phase. Two verification metrics are suggested to measure the degree of predictability of raw, calibrated and climatological seasonal precipitation forecasts over northwest Costa Rica as a case study. Results indicate the potential to narrow the uncertainty of seasonal precipitation forecasts by incorporating CGCMs ENSO cycle information. Precipitation during the late part of the wet season (LS) has more predictability than precipitation in the early part of the wet season (ES). In addition, the degree of predictability decreases with an increase in lead time for a given forecast. A lead time of 1 year maintains a moderate level of predictability likely to support tangible benefits to various decision‐making processes.

The Relationship between Chlorophyll Concentration and ENSO Events and Possible Mechanisms off the Changjiang River Estuary

More and more attention has been paid to the study of the impact of extreme climatic events on the ecological environment off the Changjiang River Estuary. In this study, the relationship between the chlorophyll concentration and ENSO (El Niño Southern Oscillation) events was studied. Several potential physical mechanisms between the ENSO and chlorophyll concentration were analyzed using observation and sensitivity experiments from a high-resolution ROMS-CoSiNE coupled model (Regional Ocean Modeling System-Carbon, Oxygen, Silicon, Nitrogen and Ecosystem) off the Changjiang River Estuary. Our results indicated that the April to August averaged chlorophyll concentration off the Changjiang River Estuary was significantly correlated with the December to February averaged ENSO indices in the previous winter. The 10 m wind speed and SST (Sea Surface Temperature) affected by an ENSO event had little effect on the chlorophyll concentration, while the discharge had a significant effect on the chlorophyll concentration off the Changjiang River Estuary, and the discharge was significantly and positively correlated with the ENSO indices. We tested the effect of interannual variations of the discharge and nutrients carried by discharge on the interannual variation in the chlorophyll concentration in the ENSO events. Two sensitivity experiments showed that when the nutrients in the freshwater discharge were kept as a constant seasonal cycle, the composite differences in the chlorophyll concentration between the positive and negative ENSO phases off the Changjiang River Estuary were reduced. When there were no nutrients in the freshwater discharge, the composite differences in the chlorophyll concentration between the positive and negative ENSO phases off the Changjiang River Estuary were reduced by one order of magnitude. The discharge can modify the stratification off the Changjiang River Estuary, and the nutrients carried by the discharge play a dominant role in determining the interannual variation of the chlorophyll concentration associated with the ENSO cycles.

The ENSO cycle and forecastability of global inflation and output growth: Evidence from standard and mixed‐frequency multivariate singular spectrum analyses

AbstractIn this paper, the role of the El Niño‐Southern Oscillation (ENSO), measured by the Equatorial Southern Oscillation Index (EQSOI), is used to formally forecast the inflation and GDP growth rates of the United States, advanced (excluding the United States) and emerging countries, as well as the world economy (barring the United States). We rely on univariate and multivariate singular spectrum analyses (SSA), as well as mixed‐frequency version of the latter since the EQSOI is monthly, while GDP is available only at quarterly frequency unlike monthly inflation rates. We find statistically significant evidence of the ability of the EQSOI in forecasting inflation and GDP growth rates of the four economic blocs, though there are exceptions in terms of forecasting gains associated with inflation rate of emerging economies and the growth rate of the United States. Our results have important implications for policymakers.

A self-attention-based neural network for three-dimensional multivariate modeling and its skillful ENSO predictions.

Large biases and uncertainties remain in real-time predictions of El Niño-Southern Oscillation (ENSO) using process-based dynamical models; recent advances in data-driven deep learning algorithms provide a promising mean to achieve superior skill in the tropical Pacific sea surface temperature (SST) modeling. Here, a specific self-attention-based neural network model is developed for ENSO predictions based on the much sought-after Transformer model, named 3D-Geoformer, which is used to predict three-dimensional (3D) upper-ocean temperature anomalies and wind stress anomalies. This purely data-driven and time-space attention-enhanced model achieves surprisingly high correlation skills for Niño 3.4 SST anomaly predictions made 18 months in advance and initiated beginning in boreal spring. Further, sensitivity experiments demonstrate that the 3D-Geoformer model can depict the evolution of upper-ocean temperature and the coupled ocean-atmosphere dynamics following the Bjerknes feedback mechanism during ENSO cycles. Such successful realizations of the self-attention-based model in ENSO predictions indicate its great potential for multidimensional spatiotemporal modeling in geoscience.

Currents off the Papua New Guinea Coast During and After the El Niño of 2015–2016

AbstractInterannual variation of New Guinea Coastal Undercurrent (NGCUC) along the Papua New Guinea (PNG) coast was investigated using mooring observations during 2015–2019 combined with eddy‐resolving simulations of the Ocean General Circulation Model for the Earth Simulator (OFES) during 1980–2019. Strong interannual variation appears in the upper 800 m of the currents recorded by the mooring, which is well reproduced by OFES outputs. On the interannual time scale, a relatively larger proportion (1.1 Sv) of the transport signals related to El Niño/Southern Oscillation (ENSO) in the Solomon Sea is transmitted through the Solomon Strait, while about 0.84 Sv of ENSO signal is through the Vitiaz Strait due to the topography constraint. As the NGCUC flows along the PNG coast, the mean transport above 400 m gradually increases while its relationship with ENSO rapidly weakens. This weakening is due to its merging with the westward South Equatorial Current (SEC). The westward SEC weakens (strengthens) during El Niño (La Niña) events, which weakens the interannual signal of NGCUC. The interannual variations of the currents above and below the thermocline off the PNG coast are opposite: a clockwise anomalous circulation straddling the equator appears above the thermocline, while a counterclockwise anomalous circulation appears below the thermocline during El Niño, which is connected to the recharge‐discharge oscillation during ENSO cycle.

Mainstreaming the Full ENSO: Linking Present Weather and Future Climate

In this article we propose that all countries that are striving to become a Weather-Ready Nation (WRN) would benefit greatly from including El Niño-Southern Oscillation (ENSO)-related research findings into their decision-making processes, not only when an El Niño or a La Niña forecast has been issued quasi-periodically. For an aspiring WRN, to benefit from ENSO information, such as disruptive or beneficial changes that could be foreseeably expected to occur in seasonal flow and in sub-seasonal hydrometeorological anomalies, requires its continuous mainstreaming about the status of the ENSO process into a WRN’s decision-making activities. The ENSO process provides a bridge between sub-seasonal weather anomalies and a sub-decadal climate phenomenon as well as a bridge between coping with weather extremes today and preparing for climate change-related hydrometeorological hazards in the future. ENSO extremes every few years provide a chance to evaluate a nation’s strategic and tactical responses to hydrometeorological hazard forecasts and disasters. Each successive ENSO extreme and its Neutral phase tests previously designed best practices. Involvement of today’s youth and young professionals on climate, water, and weather issues has been increasing and will do so in coming decades. Shifting awareness and attention to ENSO and away from ENSO extremes is crucial. The heightened urgency for understanding the full ENSO “cycle” especially by youth and young professionals today is because they will soon be in professional positions that enable them to advise decision makers about climate policy issues. Their understanding of the ENSO cycle is critically needed, as global warming is expected to continue to increase for the rest of the twenty-first century.

The Andes Affect ENSO Statistics

Abstract Current coupled global climate models have biases in their simulations of the tropical Pacific mean-state conditions as well as the El Niño–Southern Oscillation (ENSO) phenomenon. Specifically, in the Community Earth System Model (CESM version 1.2.2), the tropical Pacific mean state has overly weak sea surface temperature (SST) gradients in both the zonal and meridional directions, ENSO is too strong and too regular, and El Niño and La Niña events are too symmetrical. A previous study with a slab-ocean model showed that a higher elevation of the Andes can improve the tropical Pacific mean-state simulation by adjusting the atmospheric circulation and increasing the east–west and north–south SST gradients. Motivated by the link between the mean tropical Pacific climate and ENSO variations shown in previous studies, here we explored the influence of the Andes on the simulation of ENSO using the CESM 1.2.2 under full atmosphere–ocean coupling. In addition to improving the simulated tropical Pacific mean state by increasing the strength of the surface easterly and cross-equatorial southerly winds, the Higher Andes experiment decreases the amplitude of ENSO, increases the phase asymmetry, and makes ENSO events less regular, resulting in a simulated ENSO that is more consistent with observations. The weaker ENSO cycle is related to stronger damping in the Higher Andes experiment according to an analysis of the Bjerknes index. Our overall results suggest that increasing the height of the Andes reduces biases in the mean state and improves the representation of ENSO in the tropical Pacific.

Asymmetries in the ENSO phase space

El Niño Southern Oscillation (ENSO) dynamics are best described by the recharge oscillator model, in which the eastern tropical Pacific sea surface temperatures (T) and subsurface heat content (thermocline depth; h) have an out-of-phase relationship. This defines a 2-dimensional phase space diagram between T and h. In an idealized, stochastically forced damped oscillator, the mean phase space diagram should be a perfectly symmetrical circle with a clockwise propagation over time. However, the observed phase space shows strong asymmetries. In this study we illustrate how the ENSO phase space can be used to discuss the phase-dependency of ENSO dynamics. A normalized spherical coordinate system allows the definition of phase-depending ENSO growth rates and phase transition speeds. Based on these we discuss the implications of the observed asymmetries with regards to the dynamics and predictability of ENSO; with a particular focus on the variations in the growth rate and coupling of ENSO along the oscillation cycle. Using linear and non-linear recharge oscillator models we will show how dynamics and noise are driving ENSO at different phases of the ENSO cycles. The results illustrate that the ENSO cycle with positive phase transitions is present in all phases but has strong variations in its strength. Much of these variations result from presenting the ENSO phase space with estimates of h based on the iso-thermal depth, that is not ideal as it is not out-of-phase with T. Future work should address how h can be estimated better, including aspects such as the vertical temperature gradients and the meridional or zonal range. We further illustrated that a non-linear growth rate of T can explain most of the observed non-linear phase space characteristics.

El Niño–Southern Oscillation affects the species-level temporal variation in seed and leaf fall in a mixed temperate forest

El Niño–Southern Oscillation (ENSO), the variation between anomalously cold (La Niña) and warm conditions (El Niño), is one of the most prominent large-scale climate patterns with worldwide effects. Elevated seed and leaf fall has been found at the positive phase of ENSO (El Niño) in tropical forests. However, how seed and leaf fall respond to ENSO at species level is understudied, especially in temperate forests. In this study, we monitored seed and leaf fall at the species-level at 150 points across a 25-ha temperate forest in northeastern China over a span of 12 years. Using time series and wavelet analyses, we assessed three hypotheses: 1) temperate tree species' seed and leaf fall are strongly, but differently, correlated with ENSO and, 2) community synchrony in seed and leaf occurred both at seasonal and ENSO scales; finally, 3) local climatic modulated the effects of ENSO on seed and leaf fall. We found that ENSO was significantly correlated with seed and leaf fall of all species, although correlation strength varied across species (r = 0.206–0.658). Specifically, ENSO indices (ENSO12 or ENSO34) accounted for the most variation in seed and leaf fall of Acer pseudo-sieboldianum (40 % and 34 %, respectively) and ranged 4 %–31 % in all other species. Leaf fall was synchronous with ENSO cycles with a period of 2–7 years, but community synchrony of seed fall was only detected at seasonal scales. ENSO influenced seed fall of Fraxinus mandshurica and Tilla amurensis by mediating rainfall and relative humidity, respectively, highlighting the interactive effects of local climate and ENSO. Our findings highlight the potential effects of ENSO on ecosystems outside of tropical regions and improve our ability to predict regeneration dynamics and nutrient cycling of temperate forests under the context of global change.