A Review of Research on Tropical Air–Sea Interaction, ENSO Dynamics, and ENSO Prediction in China

The atmosphere is the most active part of the climate system and closely related to human activities. Covering 71% of the earth’s surface and absorb about 70% of the total solar radiation reaching the top of the atmosphere, the oceans are also an important part of the climate system. Mainly through the interaction with the atmosphere, oceans can affect climate change. On the one hand, oceans drive the atmosphere by thermal effects like exchanges of sensible heat, latent heat, and longwave radiation. On the other hand, in addition to the heat and water flux transport, the atmosphere also transfers momentum to the oceans, mainly through wind stress, which influences ocean currents by dynamic effects. The atmosphere is always characterized by fast and high-frequency motions, while the oceans have relatively slow movements and changes due to their great inertia. Through the air–sea interaction, oceans can modulate the high-frequency variability in the climate system and have a “memory” of lower-frequency signals. There are seve-ral important interannual air–sea coupled modes, like El Niño–Southern Oscillation (ENSO), the Indian Ocean Basin-wide Mode (IOBM), Indian Ocean Dipole Mode (IOD), and Atlantic Niño, among which ENSO is the strongest and most influential mode in the global climate system.

ENSO is the combined name for El Niño and Southern Oscillation. Every 2–7 years, sea surface temperatures (SSTs) in the central and eastern tropical Pacific feature anomalous warming, which is called the El Niño and it corresponds to the relaxation of the zonal thermocline tilt and anomalous atmospheric circulation in the equatorial Pacific. Conversely, the phenomenon whereby SSTs feature anomalous cooling is called La Niña. The El Niño and La Niña are the warm and cold phase of ENSO, respectively, which often occur alternately. The Southern Oscillation is the anti-phase oscillation of air masses between the eastern and western tropical Pacific on the interannual timescale, which is coupled with the El Niño or La Niña. The El Niño and the Southern Oscillation are actually different manifestations of ENSO in the ocean and atmosphere. As the most important mode of tropical air–sea interaction, ENSO has become an important physical basis for short-term climate prediction.

In recent decades, with the increasing availability of oceanic and atmospheric observations in the tropics, especially in the tropical Pacific, as well as the improvements of climate models, our understanding of air–sea interaction and ENSO has correspondingly advanced, in which Chinese researchers have participated extensively and made important contributions. This paper reviews the main research achievements of Chinese researchers since the founding of the People’s Republic of China on tropical air–sea interaction and ENSO dynamics and prediction, and discusses some scientific issues that need further exploration.

The lower atmosphere of the tropical Pacific is characterized by prevailing easterly trade winds all year round, which blow from the northeast in the Northern Hemisphere and southeast in the Southern Hemisphere. Under the influence of easterly trade winds, ocean surface currents in the equatorial Pacific move mainly westward and drive the westward transport and accumulation of warm water near the equator and the upwelling of cold water in the coastal region along the eastern boundary of the equatorial Pacific. Meanwhile, driven by Ekman transport, the surface warm water moving poleward diverges on both sides of the equator and the subsurface cold water pumps to the surface in the equatorial Pacific. Finally, in the equatorial Pacific, the thermocline gradually deepens from east to west, corresponding to the SSTs being warm in the west and cold in the east. Large quantities of warm water accumulate in the tropical western Pacific and eastern Indian Ocean, and the area in which SSTs exceed 28°C is called the “eastern Indian Ocean–western Pacific warm pool,” while in the eastern equatorial Pacific a meridionally narrow region with low SSTs is referred to as the “cold tongue region.” The atmosphere above the warm pool is heated by locally warm SSTs, and therefore its ascending motion is strong and convective activity is vigorous. In the eastern tropical Pacific, due to the low SSTs, the atmosphere is relatively cold and its descending motion is strong. Moreover, the lower atmosphere features prevailing easterly winds, while the upper atmosphere has prevailing westerly winds. These atmospheric motions can combine into a closed loop, and this unique zonal atmospheric circulation in the tropics is called the Walker circulation.

The climatic status of the tropical Pacific is closely related to the development and maintenance of ENSO. The most important process in this relation is the Bjerknes positive feedback, i.e., the tropical air–sea interactions among the equatorial SST zonal gradient, easterlies, and zonal thermocline tilt over the tropical Pacific, which was first proposed by Bjerknes (1969). It is the most important mechanism for ENSO growth. When positive SST disturbance appears in the eastern equatorial Pacific for some reason, it will weaken the zonal SST gradient and the descending motion of the atmosphere above it, as well as the Walker circulation and equatorial easterlies. The weakened easterlies will in turn depress the upwelling in the equatorial region and cause a deepening of the thermocline in the eastern equatorial Pacific, and the SSTs in the eastern tropical Pacific will continue to rise. Through the Bjerknes positive feedback of air–sea interactions in the equatorial Pacific, the initial positive SST disturbance can eventually develop into a warm ENSO event, while negative disturbance can develop into a cold ENSO event. The growth of ENSO depends on the instability of the climatic background of the equatorial Pacific. However, it is impossible for unlimited rising SST anomalies (SSTAs) to occur in nature; due to negative feedback and nonlinear damping, SSTAs will finally fall back.

Chinese researchers have carried out a considerable amount of research on the relationship between ENSO and the background climate state by using observations and simulations. Since the late 1970s, El Niño has become stronger, the oscillation of the ENSO cycle has strengthened, and the asymmetry between cold and warm phases has been more obvious (Zhang and Ding, 2001; Ren et al., 2013). Affected by the enhanced ENSO activity, the Hadley circulation has changed obviously, and its response to ENSO has also enhanced (Guo and Tan, 2018). These phenomena may be caused by the enhanced air–sea coupling in the tropical Pacific after both the atmosphere and ocean in the tropical Pacific changed from a cold climate state before the late 1970s to a warm one (Zhang and Ding, 2001). Similarly, the interdecadal changes of ENSO properties (e.g., spatial pattern, amplitude, and frequency) around the year 2000 may also be connected with the changes whereby the El Niño-like background state of the tropical Pacific shifted into a La Niña-like state after 2000 (Xie et al., 2015; Wang and Ren, 2017). Furthermore, Rong and Yang (2003) and Li et al. (2011) both confirmed that the amplitude and frequency of ENSO are linked with the tropical Pacific background state. Changes in the background state of the tropical Pacific at interdecadal and longer timescales significantly affect the air–sea dynamics and possibly further modulate properties of ENSO (Chen et al., 2005; Xie et al., 2015; Zhong et al., 2017). However, the relationship between ENSO and the background state is complex, and the occurrence of ENSO events may in turn affect the background status of the tropical Pacific (Liang et al., 2012; Hua et al., 2015).

ENSO is also closely related to the off-equatorial air–sea system in the tropical Pacific. ENSO events with different amplitudes or spatial patterns correspond to different ITCZ changes (Xie and Yang, 2014; Xie et al., 2018). The developing and decaying stages of ENSO have different rainfall–SST relationships in the western North Pacific (Wu et al., 2009). The loop for the propagation of the thermocline signal, which includes the equator, the eastern boundary, both sides of the equator (10°N and 10°S), and the western boundary of tropical Pacific, is an important part of the ENSO cycle (Chen et al., 2003; Yu and Qiao, 2003; Meng et al., 2004; Qiao et al., 2004; Wang et al., 2012). Chinese researchers have also recognized the interaction between the East Asian winter monsoon and ENSO. Specifically, an anomalous East Asian winter monsoon plays an important role in the occurrence of ENSO events by causing subsurface ocean temperature anomalies in the western tropical Pacific warm pool, and then the ENSO-related subsurface ocean temperature anomalous signals propagate westward along the off-equatorial path and in turn affect the activity of the East Asian winter monsoon (Zhou and Li, 1999; Mu and Li, 2000; Li and Mu, 2002).

There are two main interannual modes in the tropical Indian Ocean SSTs: the IOBM and IOD. The former is characterized by basin-scale warming or cooling in the tropical Indian Ocean, usually occurring in boreal winter. The latter shows an anomalous dipole structure over the equatorial Indian Ocean, with its positive phase corresponding to anomalous warming in the tropical western Indian Ocean and anomalous cooling in the southeastern Indian Ocean. The IOD usually develops in spring and summer, matures in fall, and then quickly damps in winter before transforming into the IOBM. SSTAs in the tropical Indian Ocean have important effects on Asian monsoon activity and climate variability in East Asia, which have long captured the attention of Chinese researchers. After the dipole concept of SSTAs in the equatorial Indian Ocean had been proposed, Chao et al. (2003) found that, in most years, SSTAs usually exhibit the same sign in the tropical western Indian Ocean and southeastern Indian Ocean but with different intensity. The zonal reversal structure of the IOD is more obvious in subsurface ocean temperature anomalies of the tropi-cal Indian Ocean, and the zonal atmospheric circulation also exhibits anomalous ascending and descending motions that match with the subsurface ocean temperature, thus forming a large-scale air–sea interaction mode simi-lar to the tropical Pacific ENSO (Chao and Yuan., 2003, 2004; Chao et al., 2003, 2005). Lu et al. (2018b, c) found that the performance of climate models in the simulation and prediction of the IOBM is significantly better than that of the IOD. The former is mainly affected by ENSO, while the latter’s influence on extreme events is closely related to Indian Ocean thermocline feedback and wind–evaporation–SST feedback.

The independence of the IOD mode and its close connection to ENSO has been a controversial topic. Chinese researchers noted a significant positive correlation be-tween the Indian Ocean and the equatorial eastern Pacific SSTs (Ji and Chao, 1987; Wu et al., 1995). Wu and Meng (1998) clearly described the interaction of anomalous zonal circulation working in a way like a pair of gears operating between the equatorial Indian Ocean and the Pacific Ocean, which explains the above mentioned positive correlation and reveals the potential triggering mechanism of the zonal wind anomaly of the Indian Ocean on ENSO events (Meng and Wu, 2000; Deng B. S. et al., 2010). Li and Mu (2001) analyzed observations spanning nearly 100 years and found an obvious negative correlation between the equatorial IOD and the Pacific Ocean dipole (similar to ENSO). The evolution of SSTs from a dipole to unipolar pattern in the equatorial Indian Ocean is in good agreement with the evolution of El Niño from development to decay (Tan et al., 2004). The subsurface ocean temperature anomaly pattern in the eastern equatorial Pacific usually leads that in the Indian Ocean, and the two patterns are linked by a reverse Walker circulation over the two oceans (Chao and Chao, 2001; Chao et al., 2005; Qian and Hu, 2005; Cai et al., 2008). Yu et al. (2005) decomposed the atmospheric variabilities of the IOD and ENSO, and recognized that the range including position of the anomalous ocean response is slightly different, which indicates that the SST response of ENSO in the Indian Ocean is not completely consistent with the IOD. Based on numerical experiments, Luo et al. (2010) found that a strong interaction exists between the IOD and ENSO, and especially, strong positive IOD events contribute significantly to the development of Central-Pacific (CP) ENSO. Zhang et al. (2015b) indicated that the recent decadal El Niño regime shift in the zonal location of the SSTAs substantially changed the relationship between ENSO and the IOD. Yuan and Li (2008) found that the relative independence of the IOD was clearer before 1970, but the relationship between the IOD and ENSO then strengthened after 1970, possibly associated with the enhancement of the Walker circulation caused by the increase in local convective activity in the Maritime Continent after 1970. Luo et al. (2012) found that the continued warming of the Indian Ocean SSTs contributes to La Niña-like interdecadal changes in the tropical Pacific, affecting ENSO and rates of global warming. Moreover, Wang et al. (2003) analyzed the changes in ocean heat content around the warm pool during the 1997/98 El Niño events, and pointed out that the Indonesian throughflow plays an important role in the communication of sea temperatures between the two oceans, in addition to the coupling relationship of the reverse Walker circulation anomalies over the two oceans. In general, there are significant large-scale air–sea interactions between the tropical Indian Ocean and the tropical Pacific Ocean. The reverse gradient of the two oceans is modulated by the coupling of atmospheric and oceanic circulations and shows a positive feedback relationship. Based on this, Lian et al. (2014a) proposed the concept of an Indo-Pacific tripolar mode of the western tropical Indian Ocean–warm pool–eastern tropical Pacific, which helps understanding of the climate variability and its impact in the tropics based on inter-basin interactions.

The main modes of tropical Atlantic SSTAs include the ENSO-like dipole-type SSTAs in the equatorial Atlantic—namely, the Atlantic Niño, which is greatly affected by ENSO—and the SSTAs in the northern tropi-cal Atlantic, which may be closely related to the Pacific–North American (PNA) teleconnection pattern and the North Atlantic Oscillation. Many studies have shown that the tropical Atlantic SSTAs in the early stage can directly or indirectly cause tropical Pacific SSTAs by affecting atmospheric circulation in the tropics and mid–high latitudes, and the tropical Pacific response varies to different patterns of Atlantic SSTAs (Song, 1987; Wu et al., 2007; Wang et al., 2011; Wu and Lin, 2012; Ding et al., 2017b; Wang et al., 2017a; Nie et al., 2019; Zhang et al., 2019), which increase the complexity of ENSO. Wang et al. (2017a) proposed that there may be a “capacitor” effect in the tropical Atlantic basin, which can store signals of the equatorial Pacific SSTAs and re-release them into the tropical Pacific Ocean through subtropical teleconnections in the following year, thus modulating ENSO quasi-biennial periods. Luo et al. (2017) and Zhang et al. (2019) found that anomalous forcings in the tropical Atlantic SSTs may contribute to the emergence of a long-lasting La Niña. Moreover, there are interdecadal changes in the interaction between the tropical Atlantic and the Pacific. The impact of the tropical Atlantic on the Pacific Ocean increased significantly after the 1980s, which may have been related to the long-term trends of the tropical Atlantic climate (Chen and Wu, 2017). Jia et al. (2019) showed that ENSO’s response to the equatorial Atlantic SSTAs weakened, which was affected by global warming. Based on understanding of the interactions among the tropical Pacific, the tropical Indian Ocean, and the tropical Atlantic air–sea modes, Chinese researchers have proposed the importance of establishing the concept of a pan-tropical interaction. Based on this, prediction of global climate and climate change caused by human activities has been discussed (Liu and Fan, 2009; Cai et al., 2019; Wang, 2019).

Many studies have shown that the mid–high latitude air–sea system can also interact with ENSO, and Chinese researchers have carried out a considerable amount of research on this. The Pacific Decadal Oscillation (PDO) and ENSO have a good correlation on interannual and interdecadal scales (He et al., 2005; Wang et al., 2009). On the one hand, the positive phase of PDO is conducive to the occurrence of El Niño events, while the PDO negative phase is favorable for the occurrence of La Niña events. On the other hand, the amplitude of El Niño under the positive phase of PDO is significantly stronger than that under the PDO negative phase, and models simulate the former better than the latter (Lin et al., 2018). Moreover, the second mode of the North Pacific SSTAs (known as the Victoria Mode, VM), which is mainly dominated by the North Pacific Oscillation (NPO), affects the occurrence of ENSO events through affecting air–sea coupling processes, equatorial subsurface temperatures, and the thermodynamic coupling process between the ITCZ and SSTAs, and it might be one of the early signals of ENSO events (Ding et al., 2015b, c). Xie et al. (2016) found that the Arctic stratospheric ozone activity can affect the NPO, then the VM, and finally ENSO. In addition, anomalous atmospheric circulation in the North Pacific can produce SSTAs in the subtropical northeastern Pacific, which are maintained by the seasonal footprint mechanism, propagate to the central equatorial Pacific, and consequently trigger a CP El Niño event (Xie et al., 2013; Xu et al., 2019). The North Pacific subtropical high, which interacts with SSTs in the eastern equatorial region (Chen, 1982), might have connections with ENSO. The former can trigger subsequent ENSO events under certain conditions. Then, the developed ENSO events in turn affect the subtropical high (Li et al., 2010). The atmospheric variability of the Southern Hemisphere extratropical region can affect the occurrence and intensity of ENSO events independently or jointly with the Northern Hemisphere atmospheric variability (Ding et al., 2015a, 2017a). The Southern Hemisphere Annular Mode, as the main mode of the atmospheric circulation in the Southern Hemisphere extratropical region, may affect the ENSO amplitude in its decaying stage (Zheng, et al., 2017). Furthermore, the North and South Pacific meridional modes are beneficial to the development of SSTAs in the eastern and central Pacific, respectively, thus affecting the spatial patterns of ENSO events (Ma et al., 2017; Min et al., 2017).

ENSO is a quasi-periodic climate fluctuation. The air–sea coupled Bjerknes positive feedback can explain the growth mechanism of ENSO, which has been confirmed by many studies. Wyrtki (1975) proposed a theoretical model to describe the occurrence and development of El Niño, which emphasized the important role of trade winds in energy accumulation. When trade winds in the tropical Pacific weaken, the ocean’s potential energy is released, warm water tends to flow back and propagate eastward in the form of an internal equatorial Kelvin wave, and an El Niño event finally occurs. Subsequently, Gill (1980) interpreted the response of the tropical atmospheric circulation to the underlying surface diabatic heating as the motion caused by atmospheric Kelvin waves and the Rossby waves driven by the heat source. Then, Zebiak and Cane (1987) developed the Zebiak–Cane model, which successfully simulated the oscillation of the thermocline and SSTs in the whole equatorial Pacific during ENSO and has been widely used in ENSO research.

During the ENSO cycle, there must exist a negative feedback mechanism to make ENSO transfer between warm and cold phases. At present, several theories have been proposed to explain ENSO phase transition (Wang, 2018), two of which are generally accepted: the delayed oscillator theory (Suarez and Schopf, 1988; Battisti and Hirst, 1989) and the recharge–discharge oscillator (RO) theory (Jin, 1997a, b). The main mechanism described by the former theory is as follows. During El Niño, accompanied by the warming of SSTs in the eastern Pacific, the westerly wind anomalies, which are centered in the central Pacific, stimulate warm Kelvin waves in the central and eastern equatorial Pacific (with rising sea levels) and cold Rossby waves on both sides of the equator (descending sea levels). The Kelvin waves will weaken the upwelling of cold water in the eastern equatorial Pacific and cause a warm event. The Rossby waves reflect when they reach the western boundary of tropical Pacifc, and generate the eastward-propagating cold Kelvin waves, which reach the eastern Pacific and push ENSO to transfer into the cold phase. The main challenges faced by the delayed oscillator theory in observations are the insufficient reflection efficiency of waves at the western boundary and the excessive propagation speed of the equato-rial waves. In RO theory, the meridional transport of the upper-ocean heat content in the equatorial Pacific is the main cause of the interannual oscillation of the air–sea system; that is, the “recharge” and “discharge” processes of the equatorial ocean heat content dominate the ENSO cycle. The advantage of RO theory is that the wave reflection at the western boundary does not need to be considered. After the warm phase of ENSO matures in the central and eastern equatorial Pacific, the zonal reversal structure of thermocline anomalies will drive the equatorial heat off the equator (i.e., the “discharge” process), causing heat accumulation in the off-equatorial region during the warm event. Finally, the equator is occupied by a zonally uniform distribution of negative thermocline anomalies, and meanwhile, the SSTAs and westerly wind anomalies disappear and the cold phase of ENSO develops, meaning that the phase transition of ENSO is to be completed. When the cold phase of ENSO matures, the opposite process starts. The “recharge” and “discharge” processes lead to continuous phase transitions between warm and cold phases of ENSO, which produces the interannual oscillation of the air–sea coupled system in the equatorial Pacific.

Since Bjerknes proposed that ENSO is the product of large-scale air–sea interactions in the tropics, various coupled ocean–atmosphere dynamic theories and numerical models have been developed to explain the internal mechanisms of the ENSO phenomenon. Since the 1980s especially, Chinese researchers have carried out numerous studies on the dynamics of large-scale air–sea interactions, of which the mechanism associated with the unstable coupling between the atmosphere and ocean has been explained in great depth (Chao, 1993). In the early 1980s, by linearly tuning the different parameter conditions in an air–sea coupled model, both Ji and Chao (1979) and Zhu et al. (1981) suggested that, under certain circumstances, the dynamically unstable perturbations of SSTAs can result in the low-frequency oscillations at the monthly and interannual scales. Jin and Zhu (1988a, b) further utilized the spectral truncation technique to nonlinearize the air–sea coupled dynamic processes and solve the steady state and limited cycle solutions of the system, through which the long-term characteristics of anomalous circulation in the air–sea coupled system have been explained to some extent. Focusing on the ENSO phenomenon, many studies have shown that the instability of air–sea coupling plays an important role in the triggering, development, and propagation characteristics of ENSO events. In the late 1980s, in a study on tropical oceanic and atmospheric waves and their interactions, Miao and Liu (1989) found a kind of strongly unstable Kelvin-like wave, characterized by a very low frequency, resulted from the high background sea temperature, and through which the occurrence and development processes of the 1982/83 super El Niño event could be well explained. Besides, under certain background SST conditions and by filtering out the high-frequency atmospheric and oceanic waves while retaining the westward-moving Rossby waves, Chinese researchers have found that the coupling system can not only reproduce the classical Rossby wave propagating westward, but also robustly simulate an unstable, slow, eastward-propagating Rossby-like wave (Chao and Zhang, 1988; Ji and Chao, 1990; Zhang and Chao, 1992). Further analysis demonstrated that, compared with the Kelvin waves, the slow, eastward-propagating coupled waves may be more important in explaining some of the characteristics of ENSO’s development and propagation, which highlights that oceanic Rossby waves play a crucial role in understanding the tropical low-frequency air–sea coupled system and ENSO, as the occurrence of these slow coupled waves is predominately controlled by the oceanic low-frequency processes (Chao and Wang, 1993; Zhang and Chao, 1993, 1994). Based on the above studies, Zhang (1995) and Yang et al. (1995) systematically analyzed the genesis conditions and instability of various types of waves in the tropical air–sea coupled system, and further discussed the dynamical characteristics of the interactions among waves with different properties. These works have provided an important theoretical reference for understanding tropical air–sea interaction and the mechanisms of ENSO occurrence and propagation.

Besides theories of air–sea coupled waves, Chinese researchers have also put forward some possible explanations from other physical aspects (such as oceanic transport) about the maintenance and phase transition mechanism of ENSO. Chao (2002) and Chao et al. (2002) described a three-dimensional closed loop of sea temperature anomalies for signal propagation in the ocean subsurface to illustrate the ENSO cycle. Taking the subsurface sea temperature anomalies in the warm pool as the main body, the sea temperature anomalous signal firstly propagates eastward and to the surface layer along the curved surface of the maximum sea temperature anomaly, forming an ENSO event in the eastern Pacific. Then, the anomalous signal propagates northward along the eastern boundary of the tropical Pacific, and subsequently westward along 10°N, before finally reaching the western Pacific and returning to the warm pool to complete the loop. The whole process takes about 2–4 yr. Zhao et al. (2007) proposed that the ENSO cycle can be regarded as a counterclockwise inertial oscillation of the tropical Pacific mixed-layer water body between the equator and 12°N, which is produced by the combination of anomalous trade winds and air–sea coupling. Chen et al. (2016) pointed out that the basin-scale anomalous zonal transport in the thermocline has a sudden reversal from the eastward direction before the peak of ENSO, to the westward direction after the peak, which causes the reversal of the zonal advection feedback and reduces the zonal tilt of the equatorial thermocline, thereby suppressing the positive feedback process and contributing to the rapid decay of the ENSO event. At the western boundary of the tropical Pacific, horizontal transport of warm water plays an important role in the ENSO cycle and modulates the ENSO-related changes in warm water volume in the equatorial Pacific (Lu et al., 2017). In addition, Duan et al. (2013) indicated by using the conditional nonlinear optimal perturbation method that the interaction between the nonlinear temperature advection and the annual cycle can cause the El Niño phase-locking. The salinity is also an important factor in the oceanic evolution from seasonal to interannual timescales; its interannual variations significantly affect the density and mixed layers of the central and western tropical Pacific, thus affecting the sea temperature and the development of ENSO (Zheng and Zhang, 2015). Lu and Ren (2016) found that changes in cumulus convection have a significant impact on the periodic characteristics of ENSO. Lu et al. (2018a) developed a coupled dyna-mic index, namely, the Wyrtki index, to quantitatively analyze the main period of ENSO in reanalysis data and model simulations, based on the theoretical framework of RO theory.

The positive and negative phases of ENSO have significant asymmetry in amplitude and duration. Zhang W. J. et al., (2009) pointed out that the asymmetry of the positive and negative phases of ENSO at the meridional scale is due to the difference in the intensity of the trade winds. Su et al. (2010) analyzed contributions of nonlinear latitudinal, meridional, and vertical temperature advection terms in the mixed-layer heat budget equation to the asymmetry of ENSO amplitude, and found that the nonlinear zonal and meridional temperature advections mainly cause the positive skewness of sea temperature anomalies in the tropical eastern Pacific, while the nonlinear vertical advection has the opposite effect. Chen et al. (2014) found that the asymmetry between El Niño and La Niña is mainly affected by the asymmetry of their long-lasting events. Specifically, long-lasting El Niño events died in the winter of the following year, while long-lasting La Niña events strengthened again in the following winter while the westerly wind anomalies extended to the west of the dateline. Currently, the CMIP5 (phase 5 of Coupled Model Intercomparison Project) models have significant differences in their simulation of the characteristics and dynamic feedbacks of ENSO (e.g., Chen et al., 2013; Chen L. et al., 2015). Liang et al. (2017) found by using a simple model that the asymmetry of ENSO amplitude is related to the pulsed oscillation mode of strong warm events.

In recent years, the spatiotemporal complexity of ENSO has become a hot topic. Generally, El Niño events can be separated into two types according to their spatial structures: one is the Eastern-Pacific (EP) type with a center of matured positive SSTAs in the eastern equatorial Pacific, and the other is the CP type with its center in the central equatorial Pacific. Not only do these two types of ENSO have distinct characteristics, but their global impacts are also quite different, especially in East Asia (e.g., Weng et al., 2007; Kao and Yu, 2009; Kug et al., 2009; Ren and Jin, 2011, 2013; Wang and Wang, 2013; Wu et al., 2014; Yeh et al., 2014; Wang M. et al., 2018). Chinese researchers recognized the diversity of El Niño events after the 1980s (Fu and Fletcher, 1985; Fu et al., 1986; Tang and Liu, 1994), and have made remarkable contributions in studying the characteristics and mechanisms of the aforementioned two types of ENSO. For example, Lian and Chen (2012) suggested that using rotated EOF analysis to analyze the tropical Pacific climate variability is more likely to obtain modes with much better physical sense than by using basic EOF analysis, especially for the second mode. Ren and Jin (2013) found that both types of ENSO have clear “charging–recharging” processes of upper-ocean heat content, and that the RO mechanism plays an important role in both types of ENSO. The thermocline feedback makes contributions to both the growth and phase transition of ENSO, while the zonal advective feedback mainly contributes to the phase transition. Wang and Wu (2013) investigated the ocean circulation patterns of the two types of ENSO, which differ significantly. In the development stage of the two types of El Niño, due to the fact that the relationship between the zonal gradient of sea level pressure anomalies and the precipitation anomalies is different, the intensity of the Bjerknes positive feedback in the two types is also different, which is weaker in the CP type (Zheng et al., 2014). Chen D. et al., (2015) demonstrated that El Niño is caused by the interaction between self-sustaining oscillation and westerly wind bursts. The former provides the basic dynamic framework, and the latter leads to the diversity of El Niño. Li et al. (2015) pointed out that the vertical convection term in the ocean plays an important role in the asymmetry between the two types of ENSO events. Ren et al. (2016a) proposed a quantitative index of the ENSO persistence barrier, and found that the persistence barrier for the EP type is stronger than that for the CP type. Duan et al. (2017) emphasized the influence of nonlinearly induced temperature advection change on the intensity and spatial patterns of the two types of El Niño.

During 1980–1999, the characteristics of El Niño were dominated by the EP type, while after 2000 they have mainly been controlled by the CP type (Hu et al., 2013; Su et al., 2014; Wang and Ren, 2017). In addition to the interdecadal changes around the year 2000, ENSO also experienced significant changes in the late 1970s (Ren et al., 2013). After 1980, the properties of EP ENSO changed significantly, while CP ENSO occurred more frequently. These findings indicate that EP and CP ENSO may correspond to two independent modes with different periods. Furthermore, the two types of La Niña can be clearly distinguished by eliminating the background decadal signals. Xie and Jin (2018) obtained two physically independent ENSO-like modes from the modified Zebiak–Cane model; namely, the quasi-biennial and quasi-quadrennial modes. Furthermore, these two modes have close connections with the two types of El Niño. Chen et al. (2005) and Xu et al. (2012) suggested that the interannual and decadal variability of subsurface ocean temperature in the equatorial Pacific are related to the two types of ENSO events, and emphasized that the decadal variability is an important factor in generating CP ENSO events. Xu et al. (2017) obtained two interannual modes by decomposing the equatorial thermocline, which play crucial roles in the two types of El Niño. Jiang and Zhu (2018) discussed the influence of changes in the cold tongue mode on ENSO diversity under global warming. Several methods have been proposed to define the two types of ENSO, but a common defect is that these indices, which can describe CP ENSO, contain too many interdecadal signals, while their extraction of the interannual signals is relatively poor (Ren and Jin, 2013; Sullivan et al., 2016).

In the 1980s and 1990s, Chinese researchers made remarkable achievements in theoretical research on the occurrence and maintenance mechanisms of ENSO, in which the dynamical mechanisms of the ENSO cycle were systematically elaborated from the perspective of unstable air–sea interactions and equatorial wave propagation. These studies utilized different tropical air–sea coupled models and found that the occurrence and development of ENSO events are sensitive to background air–sea conditions; in other words, there may be some significant precursors or triggers for the occurrence and development of ENSO events. The capture of the key physical processes in the early stage of the coupled system is also one of the important prerequisites for a coupled model to predict ENSO events. Since the 1990s, Chinese researchers have published a series of research results on the triggering mechanism of ENSO events, pointing out possible factors in the air–sea coupled system involved in the triggering of ENSO, including zonal wind anomalies and subsurface sea temperature anomalies. Observational analysis shows that, before the occurrence of El Niño events, there are significant zonal westerly wind or wind stress anomalies in the lower layer of the tropical eastern Indian Ocean to western Pacific, propagating eastward from the warm pool area and corresponding to the increasing SSTs in the central and eastern equatorial Pacific (Fu and Huang, 1996; Huang et al., 1998; Zhang and Huang, 1998; Huang et al., 2001). Moreover, before the triggering of El Niño events, the warm pool SSTs also increase significantly and propagate eastward, which is directly related to the onset and propagation characteristics of El Niño events. The reason for the eastward propagation of subsurface warm water is just the occurrence and eastward expansion of westerly anomalies in the western Pacific (Li and Mu, 1999), the source of which may even be traced back to westerly wind anomalies over the equatorial Indian Ocean for two years ahead of the events (Chao and Chao, 2001). There are also corresponding equatorial easterly wind anomalies and cold sea temperature anomalies before the development of the La Niña events.

Dynamic analysis and model experiments have confirmed that the physical processes driving the SSTAs of ENSO associated with the early zonal wind and warm subsurface ocean temperature anomalies can be mutually verified, and the possible triggering mechanisms for ENSO events can be reproduced well in both simple and complex models (Fu and Huang, 1996; Chao and Zhang, 1998; Zhang and Huang, 1998; Zhou and Li, 1999; Yan et al., 2001; Chao and Chao, 2002; Yan and Zhang, 2002). Besides, different types of early zonal wind forcing and their evolutions in different sea areas may also lead to a diversity in the occurrence and evolution of ENSO events. Numerical experiments show that the westerly wind anomaly itself in the equatorial warm pool and the triggered eastward-propagating warm Kelvin waves can stimulate the generation and eastward migration of ENSO warm sea temperature anomalies, while the westward-propagating warm Rossby waves reflected by the eastern boundary of the tropical Pacific play an important role in the maintenance of the warm sea temperature anomalies in El Niño and the westward propagation (Yan and Zhang, 2002). In addition, the superposition of the two waves may also result in two peaks of warm sea temperature anomalies in some El Niño events (Yan et al. 2001). In contrast, the easterly wind anomalies may lead to the damping and phase transition of the El Niño events by exciting the corresponding cold upwelling waves. The relative strength of the responses to the two kinds of wind anomalies has an important influence on the duration of the ENSO events (Zhang and Huang, 1998). Chao and Zhang (1998) and Chao and Chao (2002) compared the dynamic processes of the responses over the eastern and western boundaries of the equatorial Pacific to the zonal wind fields through a simple theoretical model. It was pointed out that the tropical western Pacific can form a dynamic boundary layer structure under the excitation of the equatorial trade winds, which concentrate and maintain the energy from the wind stress near the warm pool. When the anomalous westerly winds occur, the initial SSTAs of the warm pool can further propagate eastward and develop with the instability of air–sea coupling; the eastern boundary does not have such characteristics, thus emphasizing the role of the tropical western Pacific in the triggering of ENSO events. In a certain sense, this theory also combines the role of the westerly winds with the early trigger mechanisms of the positive subsurface temperature anomalies over the warm pool.

Vigorous high-frequency westerly wind bursts (WWBs) usually occur in the early stage of ENSO events. Rong et al. (2011) demonstrated how westerly winds convert high-frequency anomalous signals into interannual-scale ENSO SSTAs through the rectification effect in the atmosphere and ocean. Lian et al. (2014b) compared the relationship between the two types of El Niño events and WWBs based on observations and numerical experiments, and pointed out that WWBs may play an important role in the diversity of El Niño SSTAs and the occurrence of extreme events. The specific impacts depend on the match between the timing of the WWB occurrence and the “recharge–discharge” phase in the equatorial Pacific. In addition to the above analyses of wind fields and SSTAs, Chinese researchers have also explored other possible factors involved in the triggering of ENSO. For example, the tropical cyclone activity in the western Pacific region has important implications for the development of ENSO events (Lian et al., 2019; Wang et al., 2019).

Since the 1980s, Chinese researchers have also carried out investigations on the interactions between ENSO and other phenomena, which has led to a gradual improvement in our understanding of the dynamics and physical mechanisms in these processes. Except for the climate state, the low-latitude atmospheric motions can be divided into high-frequency synoptic-scale systems, intraseasonal oscillation, and low-frequency variabilities (longer than interannual timescales), including responses to ENSO. The interactions and energy transmissions between ENSO and other phenomena have been clearly explained (Li, 1989, 1990; Li and Zhou, 1994; Li and Li, 1995). The results of observations and model simulations have shown that there is significant interaction between East Asian winter monsoon anomalies and ENSO (Li, 1990; Li and Mu, 1998, 2000). Under the background of a strong East Asian winter monsoon, the strong cold surges over the East Asian continent will induce frequent energy transmissions to the equatorial Pacific region, leading to weakened trade winds and enhanced convergence, which could be one possible reason for the triggering of El Niño (Li, 1989). Meanwhile, the broadscale strengthening of cumulus convection over the western Pacific can excite strong tropical intraseasonal oscillations by cumulus convective heating feedback (Li and Zhou, 1994). In terms of interannual variability, anomalous anticyclones over the southern Indian Ocean and western North Pacific have significant quasi-bien-nial signals and play an important role in the interaction between ENSO and the winter monsoon (Li et al., 2007). Furthermore, when an El Niño develops, it can also modulate other phenomena.

ENSO is phase-locked with the annual cycle, and the strength of its interactions with other climate systems also demonstrate seasonal changes. Aside from linear relations, the nonlinear interaction induced by ENSO and the annual cycle of the tropical Pacific can generate high-frequency derivatives, leading to an independent and meridionally asymmetric anomalous wind pattern, namely, the “ENSO combination mode” (Zhang et al., 2015a). Ren et al. (2016b) confirmed that the characteristics and mechanisms of this nonlinear interaction can be simulated well by the majority of contemporary climate models, which is also closely related to the simulation performance of ENSO. Based on this mode, Li et al. (2016) put forward a new understanding of the influence of a strong El Niño background on the northwestern Pacific anticyclones and precipitation in spring over East Asia.

As the availability of marine observations has increased and models have been developed and improved, our understanding of ENSO dynamics is no longer limited to conventional meteorological factors; rather, interactions with ocean salinity (Kang et al., 2014; Chi et al., 2019) and even marine biological systems (Kang et al., 2017) are taken into consideration. Zheng and Zhang (2012) and Zhang et al. (2015) demonstrated that significant positive feedbacks exist between changes in ocean salinity induced by freshwater flux and SSTs in the tropical Pacific. Zhang R. H. et al (2009, 2011) indirectly established the negative feedback process between oceanic biological activity and sea temperatures, and then its parameterization, by investigating the relationship be-tween the penetration depth of solar radiation and sea temperatures (Zhang, 2015a, b). Based on these results, Zhang (2015c) and Zhang et al. (2015) established air–sea coupled models that included the processes of freshwater-flux forcing and oceanic biological activity, and indicated that these two types of feedback processes could have important influences on the interannual variability of ENSO’s amplitude periodicity.

External forcings such as solar radiation, volcanic activity, and greenhouse gases influence ENSO activities, and Chinese researchers have performed relevant studies in these aspects. Solar activity has impacts on the intensity and spatial pattern of SSTAs of ENSO. In the fall of an ENSO developing year, SSTAs in the western tropical Pacific have been shown to be weakened in high solar years and strengthened in low solar years (Zhou and Chen, 2012). A tropical volcanic eruption will directly affect the evolution of ENSO by forcing the central and eastern tropical Pacific anomalous cooling in the year of eruption and anomalous warming in the following year (Li et al., 2013), to which ENSO has a negative–positive–negative response (Wang T. et al., 2018). The volcanic activities in the Northern Hemisphere and Southern Hemisphere have different effects on the tropical Pacific. Eruptions in the Northern Hemisphere will make EP El Niño develop and peak in the next winter, while eruptions in the Southern Hemisphere can lead to a CP El Niño-like response (Liu et al., 2018). In addition to the direct impacts on ENSO, the change in effective solar radiation caused by volcanic activity will also lead to the generation of decadal ENSO-like oscillations in the tropical eastern Pacific, which will further influence ENSO by affecting the background state of the tropical Pacific (Liu et al., 2015).

ENSO can stimulate anomalous atmospheric circulation and connect anomalous signals from the tropical Pacific to climate anomalies in various regions through teleconnections. For example, ENSO can influence the North Pacific and North America by forcing the PNA pattern. However, these teleconnections induced by ENSO are not static. Studies by Chinese researchers indicate that, with the increasing occurrence of CP El Niño events, the influence of ENSO teleconnections has changed significantly on the interdecadal timescale, which is closely related to the changes of the two types of ENSO (Zhang et al., 2012). The leading mode of precipitation variability over the tropical Pacific during boreal spring experienced a pronounced interdecadal change around the late 1990s, shifting from the EP type to the CP type. Under this heating condition, a significant teleconnection pattern is induced, extending from the tropics to the North Atlantic Ocean during boreal spring, while the teleconnection associated with the EP-type mode is inconspicuous. Therefore, the different diabatic heating patterns caused by the diversity of ENSO have a key impact on the subsequent development of teleconnections. This conclusion has been further confirmed in wave flux diagnostics and several model experiments (Guo et al., 2019).

Given the intensification of global warming and the expected climate change in the future, the background climate state over the tropical Pacific Ocean and the response of ENSO in both temporal and spatial attributes have become hot research topics. Based on simulation results for different climate change scenarios from coupled models, many studies have found that global warming has significant influences on the background state of the tropical Pacific areas and the temporal and spatial features of ENSO, which are induced through the tropical Pacific cold tongue mode and the change in temperature gradient over both tropical and extratropical areas (Deng L. et al., 2010; Chen L. et al., 2015; Chen et al., 2017; Jiang and Zhu, 2018). Zheng X. T. et al., (2016) recognized that large uncertainties exist in the response of the spatial distribution of tropical Pacific SSTAs to global warming in different models, and whether the equatorial eastern Pacific SSTs getting warmer or colder can lead to opposite changes of ENSO amplitude in the future. Cai et al. (2014, 2015, 2018) indicated inconsistent results among current models in simulating the intensity and center locations of SSTAs, but they also reported that the variability of equatorial eastern Pacific SSTs is likely to increase significantly under the influence of global warming, and super strong El Niño and La Niña events will occur more frequently.

Aside from the diversity in ENSO spatial structures, global warming trends might also induce changes in ENSO teleconnections. For instance, based on the results of numerical experiments, Zhou et al. (2014) discussed the changes in atmospheric teleconnections to ENSO over Pacific and North American areas under the global warming background, and indicated that deep convection tends to occur over the eastern Pacific under a warmer climate background since the precipitation anomaly over the tropical Pacific increases and shifts to the east driven by El Niño, and the corresponding position of the center of the PNA pattern also shifts eastward. Tao et al. (2015) investigated the interdecadal changes of the ENSO teleconnections to the Indian Ocean, and found that global warming could increase the saturation speci-fic humidity in the tropics, and thus strengthen the warming over the tropical Indian Ocean induced by El Niño events. Therefore, global warming would induce changes in the climate state and lead to shifts and changes in the intensity of ENSO teleconnections.

As the dominant mode of natural climate variability in the tropical Pacific on interannual timescales, ENSO has a major impact on global weather and climate. Monitoring the current status of ENSO and predicting its future evolution are of vital importance for the prediction of anomalies of climate variables such as temperature and precipitation. Therefore, ENSO prediction is a focus of international climate research (Luo et al., 2016). Tang et al. (2018) presented a detailed introduction to recent studies on ENSO prediction and predictability. Here, we concentrate on reviewing ENSO prediction methods and related applications conducted by Chinese researchers.

The basic methods for ENSO prediction mainly involve statistical models and dynamical models, in which Chinese researchers have made systematic contributions. In general, statistical models are established by linear and nonlinear relationships between ENSO signals and predictors. Widely used methods for statistical correction in prediction include persistence prediction, analog analy-sis, linear multiple regression, the linear Markov chain method, linear inverse modeling, canonical correlation analysis, the use of nonlinear neural networks, and machine learning. For many years, statistical prediction models based on the development of the ENSO-related dynamic mechanisms have been widely used in ENSO prediction, and are still used today, because of their clear physical meanings and simplicity (Clarke, 2014). Recently, Chinese researchers have developed statistical prediction models based on the RO theory of ENSO and comprehensive use of external precursors, which can effectively improve the prediction skill (Ren et al., 2019c; Wang et al., 2019). On the other hand, the dynamical models predict ENSO by solving the physical equations of the air–sea system, which include relatively simple air–sea coupled models (e.g., Chen et al., 2004), the intermediate coupled models (Zhang, 2015c; Zheng and Zhu, 2016), and coupled general circulation models or climate system models (e.g., Luo et al., 2005, 2008; Ren et al., 2016c; Bao et al., 2019). The China multi-model ensemble prediction system developed by National Climate Center/Beijing Climate Center of China Meteorological Administration incorporates several domestic climate models to achieve the release of real-time ENSO products (Ren et al., 2019b). The International Research Institute for Climate and Society (IRI) of the US has collected and released predictions of monthly Niño3.4 index from 20 models, including dynamical models and statistical models (Barnston et al., 2012). Their results show that most of these real-time ENSO prediction systems can provide prediction results for the next six months to one year, which has become the most influential ENSO prediction reference information in the world. In addition, Chinese researchers have proposed correction methods aimed at reducing the time-varying error of dynamic model prediction to empirically improve ENSO prediction performance in an operational climate model (Ren et al., 2014; Liu and Ren, 2017; Wang et al., 2017b).

Whether statistical or dynamical, an ENSO forecast will encounter the problem of the spring predictability barrier; that is, the forecast skill presents a sharp decline in spring, which causes many similar barriers in other fields of climate prediction. Chinese researchers have tried to explain the causes of the barriers and to overcome the barriers of prediction. For instance, Mu et al. (2007) and Duan et al. (2009) argued that spring predictability barriers are associated with specific types of initial errors. Chen D. et al., (2015) suggested that they may be related to the intensity of seasonal variations in the air–sea coupled system. Yang et al. (2018) analyzed possible causes of the ENSO spring predictability barrier from the perspective of instability in the air–sea system based on the seasonal phase-locking characteristics of ENSO and the Asian monsoon. Tian et al. (2019) pointed out that the intensity of ENSO persistence barrier is closely related to the seasonality of SST amplitudes in the tropical Pacific and the intensity of ENSO phase-locking. Ren et al. (2019c) further found that the conditional introduction of SSTs in the northern part of the tropical Atlantic as a new predictor in statistical prediction models can significantly impair the spring predictability barriers of EP ENSO and the summer predictability barriers of CP ENSO.

Over the past three decades, with the development of an in-depth understanding of tropical air–sea interaction and ENSO dynamics, the gradual establishment of tropical Pacific air–sea monitoring, and the rapid development of climate system modeling, ENSO prediction has become one of the focuses of contemporary climate research (Ren et al., 2017a). Supported by the national “Ninth Five-Year Plan” technology project entitled “research on China’s short-term climate prediction system” (1996–2000), the Beijing Climate Center (BCC) took the lead in launching ENSO forecasting operations and establishing the first ENSO prediction system based on a medium-complexity model (Ding et al., 2004). At the same time, the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, used the IAP coupled atmospheric–oceanic general circulation model to design a “climate anomaly” initialization scheme and conduct a systematic hindcast for a period of more than 10 years, and established the IAP ENSO prediction system (Zhou et al., 1998; Zhou and Zeng, 2001), which is one of several systems in China that use a CGCM for ENSO prediction. In addition, some studies have used statistical methods to predict ENSO (Song and Wang, 1997; Ding et al., 2002). Subsequently, based on an intermediate coupled model, the IAP developed a new large-scale ENSO ensemble prediction system by adopting a new method of coupled assimilation and embedding a stochastic model–error model in the system (Zheng et al., 2006, 2007; Zheng and Zhu, 2010, 2015, 2016), which is now widely used in China for climate prediction and disaster prevention (Zheng et al., 2016).

At present, for dynamic coupling and statistical prediction models of different complexity, ENSO prediction skill at leads of 6 to 12 months is of certain reference value. Nevertheless, accurately predicting the intensity and onset time of ENSO events is still a serious challenge (e.g., Barnston et al., 2012). For example, for the super El Niño event that broke out in 2015, among all the international ENSO prediction models with forecasts from March, only one model predicted that the El Niño intensity would exceed 2.0°C at the end of the year, with most models’ predicting results below 1.0°C and some even predicting an La Niña occurrence (Zheng and Zhu, 2016; Mu and Ren, 2017). For forecasts from June, most of the models predicted that the El Niño event might occur at the end of the year, and there were significant differences in predictions of El Niño intensity. Only four models predicted that the El Niño intensity would exceed 2.0°C at the end of the year (Tang et al., 2018). Therefore, how to further improve the accuracy of ENSO prediction and prolong the forecast lead time of ENSO is a challenging issue worldwide. Furthermore, with the frequent occurrence of CP ENSO events in the past three decades, the impacts of such events on the climate of East Asia and China need to be investigated as they are obviously different from those of EP ENSO events. However, there have been relatively few studies on the two types of ENSO. Current dynamical models are generally better at predicting EP- than CP-type ENSO (Yang and Jiang, 2014), but most mainstream operational model systems running across the world cannot effectively distinguish between the two types of ENSO events (Ren et al., 2019a). At the same time, the ENSO prediction skill has declined since the start of the current century (Barnston et al., 2012). Therefore, research on the dynamical and statistical predictability of the two types of ENSO events under different decadal backgrounds and the development of prediction technologies for the two types of ENSO are key targets for current climate prediction research.

With the increasing trend of ENSO diversity, original ENSO prediction systems in operation have gradually failed to meet growing demands. Since 2013, the BCC has been carrying out research on and development of a new-generation ENSO monitoring and prediction system that it intends to put into operation: the System of ENSO Monitoring, Analysis, and Prediction (SEMAP2.0) (Ren et al., 2016c, 2017a, b, 2018). Significant progress has been made in terms of key technologies and prediction skill, especially development of standards for monitoring the two types of ENSO (Ren et al., 2018), techniques for dynamic diagnostic analysis, statistical prediction models, climate model predictions (Ren et al., 2017a), and statistical correction prediction. Since the spring of 2013, the relevant prediction results have been reported at the BCC operational discussion meetings, providing reasonable references to ENSO real-time prediction. In December 2015, the system was officially put into operation for national and provincial climate monitoring and prediction. With the development of this national operational ENSO prediction system, the level of ENSO prediction skill has been continuously improved. The Niño3.4 index prediction skill has reached 0.8 for the lead time of half a year, which is on a par with the international efforts and has thus received global attention. In May 2017 and January 2019, two ENSO prediction products of SEMAP2.0 were included in the ENSO multi-model collective predicting framework released by IRI, and real-time products were released simultaneously with other ENSO operational predicting products, which improved the international influence of China’s ENSO prediction operations.

The present paper reviews and summarizes the relevant progress in meteorological and oceanographic research made by Chinese researchers in the past 70 years on three aspects: tropical air–sea interaction, ENSO dynamics, and ENSO prediction. China is significantly influenced by the ocean–atmosphere system of the tropical Indian and Pacific Oceans, and ENSO, as the strongest interannual variability, shows a deterministic role in this regard. Therefore, studying tropical air–sea interaction and ENSO is of great importance for Chinese climate prediction. In the past 70 years, Chinese research on ENSO has extended from an early stage of mainly focusing on wave dynamics into sophisticated subjects involving ENSO dynamics, its spatiotemporal diversity and complexity, interactions with the three tropical oceans and mid–high latitudes, and numerical simulations and predictions. Associated studies are becoming more and more comprehensive and in-depth, showing rapid development with a large number of outstanding achievements, especially since the 2000s.

However, as understanding of ENSO and its impacts has deepened, more new issues and challenges have gradually been exposed. There are no identical ENSO events in history, although nowadays they can be roughly classified into the EP and CP types based on their different spatial patterns; and the differences between their developing mechanisms, climate impacts, and responses to future climate change are required in further studies. Furthermore, ENSO is an oscillation phenomenon with a main period of 2–7 yr, while its evolution varies across different timescales from the synoptic, intraseasonal, seasonal, interannual, to even the multidecadal. A classification method has yet to be developed to fully explain ENSO’s spatial and temporal diversity. Moreover, there are many asymmetric and extreme features in the ENSO cycle and its impacts, whose mechanisms cannot be satisfactorily described with only linear theory. Thus, nonlinear processes constitute a key factor in the modulation of ENSO’s characteristics and require further study. In general, there is still a lack of sufficient understanding regarding the complexity of ENSO, as well as appropriate dynamic theories to describe it. Numerical simulations are also far from accurate in reproducing all the spatio-temporal features of ENSO.

The different components of the global climate system are interconnected. Interactions between ENSO and other climate variabilities at different locations and on different timescales, especially inter-basin interactions, are not only a focus in current research with regard to the mechanisms and impacts of ENSO, but also an important factor for model improvement. To date, the inter-basin influences on the tropical Pacific from the Atlantic Ocean and the Indian Ocean have been widely considered; and meanwhile, ENSO’s modulations of, and interactions with, intraseasonal variabilities (such as Madden–Jullian Oscillations), seasonal cycles, interannual variabilities (such as the IOD), and decadal variabilities (such as the PDO), have all been revealed to varying degrees. In the future, there remains a requirement to further our understanding of some of the specific processes and dynamic descriptions of these mechanisms, as well as their responses to different climate change scenarios.

Under global warming, the oceans absorb more heat, while there is great uncertainty about how the mean state of the tropical Pacific will shift. What is clear at present is that ENSO will inevitably be affected by the shifted background and exhibit complicated changes in characteristics and even dynamic mechanisms, resulting in the likelihood that the empirical parts of statistical and dynamical models based on existing understanding will degrade or even fail. This will lead to a huge influence on the prediction of ENSO and associated climate anomalies. Therefore, it is of great scientific and practical value to study the changes in the intensity, frequency, spatiotemporal characteristics, and climate impacts of ENSO under future climate change.

Finally, there are still many uncertainties in relation to ENSO prediction, and these can be attributed to a range of factors. With the increasing availability of observational data for the ocean–atmosphere system, such as that provided by the Tropical Pacific Observing System, it should be possible to improve our understanding of tropical air–sea interaction and ENSO dynamics, as well as the roles played by marine biological and chemical processes, and even to re-establish or refine certain theories. Besides, the development of coupled data assimilation technology for a complete climate model has become particularly important. Despite rapid development, current climate models remain unsatisfactory in terms of reproducing ENSO’s diversity and complexity. For instance, they usually perform poorly in distinguishing spatially between the two ENSO types. Therefore, there is an urgent need to improve and upgrade models and, on this basis, make full use of statistical tools (including traditional methods and new technologies such as machine learning) to correct model outputs as an effective way to improve the accuracy of predictions. In summary, Chinese researchers should persist with their efforts to make more innovative achievements.