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Schematic diagram of the delayed oscillator. Red shading represents positive SST anomalies and green arrows represent wind anomalies. K down and K up stand for downwelling and upwelling Kelvin waves that propagate eastward. R up and R down represent upwelling and downwelling Rossby waves that propagate westward.
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The El Niño and the Southern Oscillation (ENSO) occurrence can be usually explained by two views of (i) a self-sustained oscillatory mode and (ii) a stable mode interacting with high-frequency forcing such as westerly wind bursts and Madden-Julian Oscillation events.The positive ocean-atmosphere feedback in the tropical Pacific hypothesized by Bjer...
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... produce the equatorial westerly wind anomalies in the central Pacific that force westward-propagating Rossby waves. After the Rossby waves reach the ocean western boundary, they are reflected into Kelvin waves and the reflected Kelvin waves propagate eastward to the eastern Pa- cific, switching the sign of the anomalies in the east- ern Pacific (Fig. 1). The cubic term in Equation (1) is a damping term that is to limit SST anomaly growth, but does not change the oscillation feature of Equa- tion (1) [12,18]. The delayed oscillator overlooks the role of the ocean-atmosphere interaction in the western Pacific and also assumes that wave reflection at the ocean REVIEW Wang 3 eastern ...
Context 2
... produce the equatorial westerly wind anomalies in the central Pacific that force westward-propagating Rossby waves. After the Rossby waves reach the ocean western boundary, they are reflected into Kelvin waves and the reflected Kelvin waves propagate eastward to the eastern Pa- cific, switching the sign of the anomalies in the east- ern Pacific (Fig. 1). The cubic term in Equation (1) is a damping term that is to limit SST anomaly growth, but does not change the oscillation feature of Equa- tion (1) [12,18]. The delayed oscillator overlooks the role of the ocean-atmosphere interaction in the western Pacific and also assumes that wave reflection at the ocean REVIEW Wang 815 eastern ...
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As exemplified by El Niño, the tropical Pacific Ocean strongly influences regional climates and their variability worldwide1–3. It also regulates the rate of global temperature rise in response to rising GHGs⁴. The tropical Pacific Ocean response to rising GHGs impacts all of the world’s population. State-of-the-art climate models predict that risi...
Citations
... Southern Oscillation (ENSO), which has a preferred time scale of 2-7 years and is known to be driven by positive air-sea feedbacks and oceanic adjustment processes (Neelin et al., 1998;Wang, 2018;Wang et al., 2017). Therefore, how to assess the driving forcing from the SST-SHF relation for coupled oscillatory variability remains unclear. ...
The interaction between sea surface temperatures (SST) and surface heat flux (SHF) is vital for atmospheric and oceanic variabilities. This study investigates SST‐SHF relationship in the framework of a coupled oscillatory model, extending beyond previous research that predominantly used AR‐1 type simple stochastic climate models. In contrast to the AR‐1 type model, we reveal distinct features of SST‐SHF relationships in the oscillatory model: sign reversals occur in the imaginary part of SST‐SHF coherence and the low‐pass SST tendency‐SHF correlation. However, these sign reversals are absent in the real part of SST‐SHF coherence and in the low‐pass SST‐SHF correlation. We find these features are robust across both the twentieth Century Reanalysis and GFDL SPEAR model for El Niño‐Southern Oscillation (ENSO) variability. Furthermore, we develop a new scheme to assess ENSO's climate forcing magnitude and natural frequency. Our findings thus provide novel insights into understanding ENSO dynamics from the perspective of heat flux.
... El Niño Southern Oscillation (ENSO) is the dominant interannual mode of quasi-periodic climate variability in the tropical Pacific Ocean [1][2][3]. It oscillates between a warm state (El Niño) and a cold state (La Niña) with a period of two to seven years [4][5][6]. ENSO interacts with various climatic patterns like the Indian Ocean Dipole, Atlantic Zonal Mode, North Pacific Oscillation, and Pacific Decadal Oscillation at different timescales [7][8][9][10]. Such teleconnections involve oceanic tunnels and atmospheric bridges that link the tropics with the extra tropics and the oceans with the land regions, profoundly impacting global climate variability [11,12]. ...
El Niño Southern Oscillation (ENSO) is the leading interannual coupled climate mode in the tropical Pacific. The seasonal transition of ENSO from boreal winter to the following summer can significantly affect the global climate. One of the major hurdles in understanding the seasonal transition of ENSO is the spring predictability barrier. Here, we show that ENSO’s seasonal transition is modulated by a multidecadal climate mode of boreal spring sea-level pressure (SLP) in the extratropical Southern Hemisphere. This ENSO transition mode (ETM), when characterised by a decrease in SLP and associated clockwise circulation of the surface winds centred over the southeastern subtropical Pacific Ocean, produces westerly anomalies at the equator. These wind anomalies in the equatorial eastern Pacific aid the seasonal warming of Niño3.4 sea surface temperature anomalies (N34SST) from boreal winter to the following summer. The ETM time series shows prominent multidecadal variations at around 50 years. This creates a conducive environment for alternate cold and warm seasonal transitions leading to multidecadal variations in boreal summer N34SST. Thus, ETM provides a physical insight into the seasonal transition of ENSO and leads to a new paradigm for ENSO evolution beyond its peak. This has implications for seasonal ENSO forecasts and decadal climate predictions.
... As mentioned above, both tropical Pacific SST and Arctic sea ice experienced an interdecadal change around the early 2000s (Comiso et al., 2008;Hu et al., 2017;McPhaden et al., 2020;Qi & Xu, 2018;Yeh et al., 2009). ENSO is the most intense climate phenomenon involving ocean-atmosphere interaction in the tropical Pacific, it has the strongest signal in winter (Stein et al., 2014;Toniazzo & Scaife, 2006;Wang, 2018). Therefore, it is important to find out whether the connection between tropical Pacific SST and Arctic sea ice is also changed after the decadal change around 2000. ...
The present study investigates the interdecadal change in the interannual relationship between winter sea surface temperature (SST) in the tropical central‐eastern Pacific and the subsequent summer Arctic sea ice concentration (SIC) and its possible mechanism using 1979–2023 monthly SST and SIC data from Hadley Center and atmospheric reanalysis data from NCEP/NCAR. It is found that the relationship between the winter tropical Pacific SST and the subsequent summer SIC of Beaufort Sea experienced an obvious interdecadal change from a significant negative correlation to a weak and insignificant correlation before and after the early 2000s, respectively. Before the early 2000s, when winter SST warming (cooling) anomalies occurred in the central and eastern tropical Pacific, it could sustain into summer and enhance a Rossby wave propagating from Tropic to high latitude, forming negative (positive) pressure anomalies in the North Pacific. Influenced by such anomalies, it is conducive to maintaining negative (positive) SST anomalies in the North Pacific from winter to subsequent summer. The summer SST cooling (warming) in the North Pacific could form a favourable atmospheric circulation anomaly for less (more) SIC. In contrast, after the early 21st century, the strong SST anomalies in winter over the eastern tropical Pacific would weaken with time and subsequently diminish in spring, leading to the SST anomalies in the North Pacific persist to spring, which can hardly affect summer SIC anomaly in the Beaufort Sea. Therefore, the relationship collapses after the the early 2000s due to the weakened persistence of the eastern tropical Pacific SST anomaly.
... An anomalous an clone (cyclone) persists from the preceding winter to spring when an El Niño (a La N event occurs [9,19]. Therefore, the anomalous easterlies (westerlies) at the south p the anomalous anticyclone (cyclone) can generate equatorial upwelling (downwe oceanic Kelvin waves to weaken the existing El Niño (La Niña) [30,31]. During El decaying spring, such an anomalous WNP anticyclone and suppressed precipitatio also accompanied by the southward shift of westerly and positive precipitation anom On the other hand, spring precipitation over the MC can also influence the evolution of ENSO, particularly during the decay phase of El Niño. ...
... An anomalous anticyclone (cyclone) persists from the preceding winter to spring when an El Niño (a La Niña) event occurs [9,19]. Therefore, the anomalous easterlies (westerlies) at the south part of the anomalous anticyclone (cyclone) can generate equatorial upwelling (downwelling) oceanic Kelvin waves to weaken the existing El Niño (La Niña) [30,31]. During El Niño decaying spring, such an anomalous WNP anticyclone and suppressed precipitation are also accompanied by the southward shift of westerly and positive precipitation anomalies over the equatorial central Pacific [32][33][34][35], which result from the nonlinear interaction between ENSO and the annual cycle [20][21][22]. ...
Previous studies suggested that spring precipitation over the tropical western Pacific Ocean can influence the development of El Niño–Southern Oscillation (ENSO). To identify crucial precipitation patterns for post-spring ENSO evolution, a singular value decomposition (SVD) method was applied to spring precipitation and sea surface temperature (SST) anomalies, and three precipitation and ENSO types were obtained with each highlighting precipitation over the Maritime Continent (MC) or western north Pacific (WNP). High MC spring precipitation corresponds to the slow decay of a multi-year La Niña event. Low MC spring precipitation is associated with a rapid El Niño-to-La Niña transition. High WNP spring precipitation is related to positive north Pacific meridional mode and induces the El Niño initiation. Among the three ENSO types, ocean current and heat content behave differently. Based on these spring precipitation and oceanic factors, a statistical model was established aimed at predicting winter ENSO state. Compared to a full dynamical model, this model exhibits higher prediction skills in the winter ENSO phase and amplitude for the period of 1980–2022. The explained total variance of the winter Niño-3.4 index increases from 43% to 75%, while the root-mean-squared error decreases from 0.82 °C to 0.53 °C. The practical utility and limitations of this model are also discussed.
... Furthermore, we robustly identified the asymmetry in the contributions of El Niño and La Niña-induced changes in TWS or T to the variability in regional vegetation productivity variability over NA, AF or EU. The contributions from El Niño events consistently surpassed those from La Niña events over these regions, primarily attributed to the asymmetry in the TWS and T changes during the two phases of ENSO (Park et al., 2020;Wang, 2018). Our findings challenged the traditional notions that El Niño-induced drought reduces vegetation productivity while La Niña-induced wetness enhances it, primarily focusing on tropical regions (Bastos et al., 2013(Bastos et al., , 2018Liu et al., 2017). ...
The two phases of El‐Niño‐Southern Oscillation (ENSO) influence both regional and global terrestrial vegetation productivity on inter‐annual scales. However, the major drivers for the regional vegetation productivity and their controlling strengths during different phases of ENSO remain unclear. We herein disentangled the impacts of two phases of ENSO on regional carbon cycle using multiple data sets. We found that soil moisture predominantly accounts for ∼40% of the variability in regional vegetation productivity during ENSO events. Our results showed that the satellite‐derived vegetation productivity proxies, gross primary productivity from data‐driven models (FLUXCOM) and observation‐constrained ecosystem model (Carbon Cycle Data Assimilation System) generally agree in depicting the contribution of soil moisture and air temperature in modulating regional vegetation productivity. However, the ensemble of weakly constrained ecosystem models exhibits non‐negligible discrepancies in the roles of vapor pressure deficit and radiation over extra‐tropics. This study highlights the significance of water in regulating regional vegetation productivity during ENSO.
... There are notable regional TOE differences in the tropics. The east and west equatorial Pacific exhibit a 'seesaw' pattern in SST and thermocline depth, which is characteristic of the strongest oceanatmosphere coupling process known as El Niño-Southern Oscillation (ENSO) (Tsonis et al 2003, McPhaden et al 2006, Wang 2018. We revealed difference between two regional tropospheric temperature TOE. ...
In the 20th century, with the intensification of human activities, the Earth is experiencing unprecedented warming. However, there are certain differences in the sensitivity of temperature changes to anthropogenic forcings in different regions and at different altitudes of the troposphere. The time of emergence (TOE) is the key point at which the anthropogenic climate change signal exceeds from the internal climate variability serving as a noise. It is a crucial variable for climate change detection, climate prediction and risk assessment. Here, we systematically analyzed the spatiotemporal characteristics of the TOE of temperature changes over the past century by calculating the signal-to-noise ratio (SNR) based on the selected CMIP6 multi-model outputs. The results show that the temperature TOE, particularly in the lower and middle troposphere, shows distinct latitude dependence, displaying an "M-type" distribution from the Antarctic to the Arctic: it first appears in low-latitudes, followed by high-latitudes, and last appears in the two mid latitude bands. For the tropics, the TOE of tropospheric temperatures becomes earlier with increasing altitude: the TOE of air temperatures at the surface, mid-tropospheric 500hPa and upper-tropospheric 200hPa occurs in 1980±15, 1965±20, and 1930±30, respectively. The TOEs of tropospheric temperatures in eastern equatorial Pacific are 10~30 years later than those in the western equatorial Pacific. For the regional TOEs of surface air temperature diverse differences exist on land and ocean in various latitudes of two hemispheres.
... Interannual SST variability over the western tropical Pacific (WTP) is a topic of great interest for climate scientists, as it is closely related to the El Niño-Southern Oscillation (ENSO) phenomenon, which affects the global weather patterns and ocean circulation (Hoell & Funk, 2013;Wang, 2018;Zinke et al., 2021). Observational studies have used various data sources to describe and analyse the spatial and temporal patterns of SST anomalies over the WTP (Hu et al., 2017;Thunell et al., 1994;Wang et al., 1999). ...
Interannual sea surface temperature (SST) variability in the western Pacific is a critical research topic in climate change, as it can significantly impact regional and global weather patterns. Previous observational studies have shown that SST in the southwestern Pacific (SWP) can effectively serve as a precursor signal for SST in the western tropical Pacific (WTP). In this study, we evaluate and compare the modelling capabilities of 32 CMIP6 models to simulate the relationship between SWP and WTP SST. The results indicate that while some CMIP6 models can simulate the spatial connection and physical processes between the SWP and WTP, there are significant intermodel differences. Specifically, the models that best simulate the cross‐equatorial propagation of SWP SST anomalies are those that accurately simulate the cross‐equatorial wind anomalies induced by SWP SST anomalies, highlighting the key role of wind‐evaporation‐SST feedback in SST propagation. Further analysis reveals that the intermodel spread in cross‐equatorial SST propagation is attributable to model biases in simulating climatological SST and wind speed. Models with warm climatological equatorial SST and strong wind speeds provide favourable conditions for the cross‐equatorial propagation of SWP‐related SST anomalies towards the north. Warm SST and strong inter‐season wind speeds near the equator facilitate the northward propagation of the SWP warm signal, leading to increased warming in the WTP.
... These variables form a phase space that corresponds to the so-called recharge-discharge oscillator theory of ENSO [4,14,29]. According to it, the heat is accumulated in the central and eastern Pacific subsurface waters in cold or normal stages of ENSO due to strong easterlies along the equator, which cause equatorward Sverdrup transport. ...
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.
... ENSO refers to the irregular periodic air-sea interaction in the tropical eastern Pacific Ocean, which is manifested in the El Niño-La Niña transition in the ocean and the Southern Oscillation in the atmosphere Yeh et al., 2009;Timmermann et al., 2018;Wang, 2018). ENSO is one of the most important climatic phenomena on Earth (Wang, 1995;An and Jin, 2004;Cal et al., 2019), often causing global temperature and precipitation extremes, affecting Earth's ecosystems and human societies. ...
The El Niño–Southern Oscillation (ENSO) causes a wide array of abnormal climates and extreme events, including severe droughts and floods, which have a major impact on humanity. With the development of artificial neural network techniques, various attempts are being made to predict ENSO more accurately. However, there are still limitations in accurately predicting ENSO beyond 6 months, especially for abnormal years with less frequent but greater impact, such as strong El Niño or La Niña, mainly due to insufficient and imbalanced training data. Here, we propose a new weighted loss function to improve ENSO prediction for abnormal years, in which the original (vanilla) loss function is multiplied by the weight function that relatively reduces the weight of high-frequency normal events. The new method applied to recurrent neural networks shows significant improvement in ENSO predictions for all lead times from 1 month to 12 months compared to using the vanilla loss function; in particular, the longer the prediction lead time, the greater the prediction improvement. This method can be applied to a variety of other extreme weather and climate events of low frequency but high impact.
... There are other types of theoretical models to highlight different physical processes, such as the western Pacific oscillator model (Weisberg and Wang 1997), the advective-reflective oscillator model (Picaut et al. 1997), and the unified oscillator model (Wang 2001). The recent review by Wang (2018) explicitly compared the similarities and differences among these oscillator models. Specific to the RO framework, incorporating seasonality, nonlinearity, and multiscale processes, it allows for basic understanding Y. Li of how key physical processes determine ENSO's properties, such as its amplitude, periodicity, phase-locking, asymmetry, and nonlinear rectification onto the mean state . ...
A spatiotemporal oscillator model for El Niño/Southern Oscillation (ENSO) is constructed based on the thermodynamics and thermocline dynamics. The model is enclosed by introducing a proportional relationship between the gradient in sea surface temperature (SST) and the oceanic zonal current and can be transformed into a standard wave equation that can be decomposed into a series of eigenmodes by cosine series expansion. Each eigenmode shows a spatial mode that oscillates with its natural frequency. The first spatial mode, that highlights SST anomaly (SSTA) contrast between the eastern and western Pacific—a fundamental characteristic of the eastern Pacific (EP) El Niño events, oscillates with a natural period of around 4.6 years, consistent with the quasi-quadrennial (QQ) mode. The second spatial mode, that emphasizes SSTA contrast between the central and the eastern, western Pacific—a basic spatial structure of the central Pacific (CP) El Niño events, oscillates with a natural period of 2.3 years that is half of the first natural period. It is also consistent with the quasi-biennial (QB) modes. The combinations of the eigenmodes with different weights can feature complex spatiotemporal variations in SSTAs. In open ocean that is far away from the coastlines, the model can predict waves propagating both eastward and westward. Besides, the net surface heating further complicates the temporal variations by exerting forced frequencies. The model unifies the temporal and spatial variations and may provide a comprehensive viewpoint for understanding the complex spatiotemporal variations of ENSO.
