The interannual variability of sea surface temperature (SST) in the South China Sea (SCS) exhibits two peaks around January and August in the subsequent year of the El Niño. We show that the second basin-scale summer SST warming feature peaked in August [+1] is only distinct after strong El Niño events, not regular El Niño events. The upper ocean heat budget analysis demonstrates that the abnormal Ekman advection (Eka) dominants the second warming features during the whole developing stages from June [+1] to August [+1], while the abnormal geostrophic advection (Goa) leads to the warm tendency in June [+1], by reducing the Vietnam coastal upwelling. The local dynamical effects of abnormal Eka and Goa in the SCS are attributed to the advanced abnormal easterly wind breakout in the western Pacific, coincided with the development of West North Pacific anomalous anticyclone (WNPAC) in response to strong El Niño. Our results suggest that the second warming features of SCS SST during the next summer are the footprints of strong El Niño events via the establishment of the WNPAC, which is tightly related to Indo-Pacific remote processes.
Research Article
Summer Surface Warming Driven by the Strong El Niño in the South China Sea
https://doi.org/10.21203/rs.3.rs-2439314/v1
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Strong El Niño
Summer SST warming
Easterly wind breakout
West North Pacific anomalous anticyclone
The El Niño and Southern Oscillation (ENSO), is either a self-sustained and naturally oscillatory mode of the coupled ocean-atmosphere system or a stable mode triggered by stochastic forcing (Wang et al. 2017). It has a significant impact on the climate of the South China Sea (SCS) and East Asia and triggers abnormal phenomena such as summer monsoon outbreaks (Ding et al. 2004), abnormal typhoons and rainfall et al (Zhou et al. 2010).
The sea surface temperature (SST) in the SCS, which is crucial for coral reef ecosystems (e.g., DeCarlo et al. 2017; Hughes et al. 2017), is significantly modulated by ENSO events (He et al. 1997; Wang and Zhang 2002; Xie et al. 2003; Liu 2004; Wang et al. 2006a; Zhang et al. 2010; Liu et al. 2014; Tan et al. 2016; Xiao et al. 2018, 2020). Induced by the changes of atmospheric circulation in El Niño events, the net heat flux from atmosphere to ocean increases and leads to significant ocean surface warming, (Klein et al. 1999; Wang et al. 2000), fitting the concept of the “atmospheric bridge”. Furthermore, the ENSO signals can be conveyed from the Pacific Ocean into the SCS through the Luzon Strait (Qu et al. 2004; Tian et al. 2006), which is known as the “oceanic bridge”.
Wang et al. (2006a) first revealed that the interannual SST anomalies over the SCS showed a double-peak feature following an El Niño event. The shortwave radiation and latent heat flux anomalies are major contributions to the first peak of the SCS SST anomalies and the geostrophic advection contributes significantly to the second peak in August [+ 1]. In summer 1998, the monsoon is weaker and the thermocline develops deeper than normal, which is favorable for maintaining the warm event (Wang and Zhang 2002). Two extreme subsurface warm events can be identified during 1998/99 and 2006/07 (Xiao et al. 2018). They further illustrate that warm advection from the southern SCS in 1998/99 and from the Kuroshio intrusion in 2006/07 is likely the major contributor to cause the subsurface warming.
The diversity of ENSO events has a different impact on the SCS SST anomalies. Liu et al. (2014) and Tan et al. (2016) explored the differences and mechanisms of the SCS SST anomalies evolution under eastern Pacific (EP) and central Pacific (CP) El Niño events. They confirmed that the latent heat flux change was a major contributor to the SCS SST anomalies for the first warming peak during different El Niño events. In the mature stage of EP El Niño, the Philippine anticyclone (PAC, Wang et al. (2000)) weakens and thus takes an effect on the latent heat flux to cause north-south discrepancy of the SCS SST anomalies (Liu and Li 2020).
Few studies have emphasized the impacts of different intensities of El Niño events on the SCS SST anomalies. Distinct from regular El Niño events (McPhaden 2015), strong El Niño events have a longer duration and more intense warming in eastern Pacific (Cai et al. 2014, 2018; Chen et al. 2016), leading to an eastward propagation of SST anomalies in Pacific and a much wider range of rainfall effects (McPhaden and Zhang 2009; Santoso et al. 2013, 2017). Furthermore, strong El Niño is closely related to the interaction with other oceans and their jointed effects may cause the unprecedented marine heat waves in the SCS (Wang and Wang 2021; Yao and Wang 2021).
Under the background of global warming (Cai et al. 2015), the extreme El Niño events will occur more frequently and persist longer in the coming century, which will exert stronger and distinct remote impacts (Cobb et al. 2013; McGregor et al. 2013). Therefore, the impact of strong El Niño events on SCS SST anomalies will be strengthened (Wang et al. 2000; Xie et al. 2003), and need more attention. In this study, we will identify the unique influence of strong El Niño events on SCS SST anomalies and investigate its related mechanisms.
The rest of the paper is organized as follows. Section 2 gives a brief description of the datasets and the methods. Section 3 presents the unique second warming features in the post strong El Niño events and their contributor factors. Section 4 emphasizes the physical processes controlling the second warming in decaying summer. The features of cold filament, abnormal easterly wind anomalies and the establishment of the West North Pacific anomalous anticyclone (WNPAC) in decaying summer of strong El Niño events are discussed in Section 5, and conclusions are given in Section 6.
2.1 Data description
a. SST datasets
The monthly Optimum Interpolation Sea Surface Temperature (OISST) v2.1 with 0.25° high resolution dataset from 1982 to 2021 (Huang et al. 2020) and Extended Reconstructed Sea Surface Temperature (ERSST) v5 dataset from 1850 to now (Huang et al. 2017) are mainly used in this study from the NOAA/Climate Prediction Center. The Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) analysis dataset (Rayner et al. 2003) is also used to do a comparison with the global warming trend of ERSST v5. In additional, ERSST v4 (Huang et al. 2015a) and Centennial in situ Observation-based Estimates (COBE) (Ishii et al. 2005) are used to classify strong El Niño events.
b. Atmospherics datasets
To diagnose the atmospheric response, the monthly reanalysis data of horizontal winds at 850 hPa and 12-level vertical velocity (Omega) are derived from National Centers for Environmental Prediction/ National Center for Atmospheric Research (NCEP/NCAR) reanalysis 1 (NCEP/NCAR1), with spatial resolution 2.5 º×2.5 º (Kalnay et al. 1996). The 850 hPa wind is then converted to wind stress based on the bulk formula with drag coefficients in the SCS suggested by Xie et al. (2001). Monthly precipitation data of CPC merged analysis of precision (CMAP) is adopted with spatial resolution of 2.5 º×2.5 º from a variety of satellite observations and rainfall observation stations (Xie and Arkin 1997) from the NOAA/Climate Prediction Center. The monthly heat flux data of ERA5 (Hersbach et al. 2020) are obtained from the European Centre for Medium-Range Weather Forecasts (ECWMF), including the longwave radiation, shortwave radiation, sensible heat net flux and latent heat flux. The net heat flux is calculated by summarizing these four terms, and a positive value indicates the input of heat from the atmosphere to the ocean.
c. Surface geostrophic current
The surface geostrophic current is based on Archiving, Validation, and Interpretation of Satellite Oceanographic Data (AVISO) from 1993 to now, which is derived from Copernicus Marine Environment Monitoring Service (CMEMS), at L4-level processing with 1/4º of horizontal resolution.
The seasonal cycle is removed before obtaining the monthly anomalies. [0] and [+ 1] are referred to the development and subsequent year of each El Niño event, respectively.
2.2 Strong and regular ENSO events
Following the method of Santoso et al. (2013), four SST reanalysis datasets are combined primarily to construct a more generalized event classification, including ERSST v4, ERSST v5, HadISST and COBE, respectively. The ENSO events are categorized according to their strength, which is typically measured by the Niño3.4 index (averaged SST anomalies in 5ºN-5ºS, 170ºW-120ºW) in the boreal winter (Santoso et al. 2017). The Niño 3.4 index in November [0] to January [+ 1] (NDJ) is used to detect the strength of ENSO variability. If the standard deviation exceeds 1, it is a strong El Niño; If the standard deviation is between 0.5 and 1, it is a regular El Niño. According to this definition, there are five strong El Niño events (1982/83, 1991/92, 1997/98, 2009/10, 2015/16) and six regular ones (1986/87/88, 1994/95, 2002/03, 2004/05, 2006/07, 2018/19) since 1980s.
Philander (1983) and Torrence and Webster (1998) pointed out that the ENSO events were phase-locked to the annual cycle, with their peaks occurring in boreal winter. However, the 1986/88 event lasted three years and experienced distinctive evolution features, compared with the typical El Niño events (Chen and Li 2017). In addition, the duration time of 1991/92 event is relatively short and the SCS SST is abnormally cold (Wang et al. 2006a). Therefore, the 1986/88 and 1991/92 El Niño events are excluded from this study.
2.3 Empirical Orthogonal Functions of SCS SST anomaly
In this study, the Empirical Orthogonal Function (EOF) is applied to two global SST datasets of OISST v2.1 and ERSST v5 to derive the leading modes of the SCS SST variability.
OISST v2.1 has the advantage of higher resolution (0.25° horizontally), and this data is favorable for us to investigate the SCS SST anomalies. However, OISST starts from 1982. The data range is too short to identify the transition from the cold phase (1977–1998) of the Pacific Decadal Oscillation (PDO) to the warm phase (1999-present), with the long-term global warming trend. If the linear trend is removed before EOF analysis, the contributions of the phase change of PDO, which is usually in phase with the interdecadal variability of ENSO, on the SCS SST anomalies will be weakened.
In order to eliminate the mode mixing between the global warming and the phase change of the decadal variability, we use ERSST v5, which starts from early 19th century, to derive the long-term global warming trend following the technology proposed by Chen et al. (2017), and then subtract it from the OISST v2.1 (hereafter referred as rOISST). The EOF modes of the ERSST v5 and the rOISST fields are shown in Fig. 1. The characteristics of global warming and typical ENSO are shown in EOF1 and 2, respectively. Figure 1c and 1e indicate that there is still an inherent warming pattern in SCS SST, but it is mostly unrelated with the long-term global warming, but the decadal variability in the whole Pacific. Figure 1d shows that PC3 of the rOISST is highly correlated with PC2 of ERSST characterized by the ENSO variability, but the latter has much high spatial resolution in the SCS region (Fig. 1f).
3.1 Unique second warming features after strong El Niño events
Figure 2 displays the SST anomalies in the SCS (5.5°N-24.5°N, 105°E-120°E) during all El Niño, strong El Niño, and regular El Niño events using rOISST after removing the trend of global warming signals. Consistent with the finding of Wang et al. (2006a), the characteristics of “double-peak” is obvious during all El Niño events (Fig. 2a), but it is discernible that this “double peaks” structure is only significant during strong El Niño events, especially the second summer SST warming signals (Fig. 2b, c). During strong El Niño events, two abnormal warming peaks can reach 0.39 ± 0.43 ºC and 0.4 ± 0.31 ºC, respectively.
Figure 2b shows that during strong El Niño events, the SCS SST anomalies starts warming in October [0] following the development of El Niño, reaches its first peak around January and February [+ 1], and then decays to the minimum around April [+ 1] and bounces to the second warming peak around August [+ 1]. However, the first warming peak still exists while the second warming signal is hard to discern for regular El Niño events (Fig. 2c).
Figure 3 presents the composite fields of the SCS SST anomalies averaged over latitudes for strong and regular El Niño events, respectively. During the development and mature stages of strong El Niño events (Fig. 3a), the first warming peak is stronger in the western SCS, but the second warming peak locates at the central (around 115ºE, 13ºN) and eastern SCS. The second warming event can last for up to six months, and end in October [+ 1]. The composite field of Fig. 3b also shows that there is no second warming for the regular El Niño events.
Comparisons of Fig. 2 and Fig. 3 show that the first abnormal warming of the SCS SST anomalies peaked around January [+ 1] is the common feature during the development and mature stages of all El Niño events, whereas the second abnormal warming peaked around August [+ 1] is unique during strong El Niño events. This finding is different from that of Xiao et al. (2022), in which the SCS SST is anomalous warm in regular El Niño decaying summer even warmer than that in strong El Niño events. There are two reasons to cause the difference with Xiao et al. (2022). One is that they used the linear detrend method to remove the global warming effect, and the other is that they only chose the center basin of the SCS (10°N–20°N, 109°E–118°E) to do the composite field.
3.2 Heat budget analysis for strong/regular El Niño events
We further quantify the relative role of dynamic factors controlling the change of SST anomalies using mixed layer heat budget, as follows (Wang et al. 2006a):
(1)
Where T is mixed-layer temperature, h the climatological mean mixed-layer depth (here taken as 40 m), \({Q_{NET}}\) the net surface heat flux, \(\rho\)= 1025 \(kg/{m}^{3}\) is the density of seawater, \({C_P}=3999.2J/(kg \cdot {}^{^\circ }C)\) the specific heat capacity of seawater, \(\overrightarrow {{u_E}}\)=\((\overrightarrow \tau \times \overrightarrow k )/(\rho f\overline {h} )\) the Ekman velocity vector, \(\overrightarrow {{u_G}} = - g\nabla h \times \overrightarrow k /f\) the surface geostrophic current velocity, which can be calculated using AVISO sea level dataset, \({w_E}\) the Ekman pumping (entrainment) velocity, which is related to the wind stress vector. The overbar denotes the climatological mean and the prime denotes anomaly. The eight terms in Eq. (1) are referred to as temperature anomaly tendency, surface heat flux anomaly forcing, mean Ekman heat advection, anomalous Ekman heat advection, mean geostrophic heat advection, anomalous geostrophic heat advection, anomalous entrainment heat flux, and mean entrainment heat flux, respectively.
The tendency of monthly SST anomaly is computed as the difference between two neighboring months (next month minus this month). The last two terms, anomalous entrainment heat flux and mean entrainment heat flux, will not be considered in this paper, because there are no reliable datasets to calculate the vertical gradient of temperature anomaly and the amplitude of the anomalous vertical entrainment heat flux is smaller than the other terms in the SST equation (Liu et al. 2014). Regions with water depth shallower than 100 m are ignored when the geostrophic heat convection is calculated.
For the first abnormal warming tendency averaged in Oct-Nov-Dec [0], Fig. 4a and 4c demonstrate that the net heat flux contributes most responding to all El Niño events, consistent with previous studies of Wang et al. (2006a) and Liu et al. (2014). There exists a slight difference between strong and regular El Niño events: for strong El Niño events, the net heat flux is the main reason for the warming in Oct [0] and Nov [0], while anomalous Ekman advection and mean geostrophic advection began to play major roles in the continued warming in Dec [0]; for regular El Niño events, the mean geostrophic advection is significant in the beginning and then the net heat flux in Nov [0] and Dec [0].
For the second abnormal warming peak of the SCS SST, Fig. 4d shows that though warming trend in June [+ 1] is also appeared during the regular El Niño events, an abrupt recession process happens in July [+ 1]. The SCS SST behaves as cold anomalies during the summer associated with the decaying stage of regular El Niño events. As described in Section 3.1, the second warming peaked from June [+ 1] to August [+ 1] (JJA [+ 1]) is identified as the special characteristic that only occurred in strong El Niño events. The heat budget analysis suggests that the anomalous Ekman heat convection and net heat flux are the major driving factors for the warming development of the SCS SST anomalies in the early summer (June [+ 1] and July [+ 1]). And the abnormal heating that occurred in July [+ 1] is especially attributed to anomalous geostrophic heat convection, while its averaged effect is greatly weakened in JJA [+ 1] (Fig. 4b).
The analysis above suggests that for the first abnormal warming of the SCS SST, the effects of all El Niño events are relatively consistent, and the first warming development is mainly driven by net heat flux, affected by latent heat flux and atmospheric short-wave radiation (not shown). The second abnormal warming peak from June [+ 1] to August [+ 1] is identified as the special response in strong El Niño events, which is especially attributed to anomalous Ekman heat convection during JJA [+ 1], and the anomalous geostrophic heat convection. We will further explain why the second warming is only responding to strong El Niño events, and the key dynamic process specifically accompanied by strong El Niño events.
4.1 EOFs of the second warming
In order to investigate the physical processes contributing to the second warming of the SCS SST during the strong El Niño events, we apply the EOF analysis of the rOISST in the SCS region (105°E-120°E, 5°N-25°N). Figure 5 shows the three leading EOFs and their corresponding PCs. While the rOISST still exhibits warming trend related to the change of PDO from its cold phase to warming phase, the trend transfer (Chen et al. 2017) is applied to merge the warming trend into the PC1. The corresponding EOF1 explains around 9.1% of the total variance. This mode can be regarded as the footprint of the PDO on the SCS SST anomalies. The correlation coefficient between PC1 and Niño 3.4 index is quite low (R = -0.05) and not discussed henceforth.
The EOF3 explains about 15.5% of the total variance. The correlation coefficient between the corresponding PC3 and the Niño 3.4 index is 0.75, suggesting that this the instant response of the SCS SST anomalies to the general El Niño events. Its spatial pattern is dominated by the characteristics of warm in the west and cold in the east, reflecting the west-east discrepancy during the winter season through the net heat flux and thermocline adjustment, suggested by Liu et al. (2014). We can also find that during the four strong El Niño events, the maxima of PC3 usually occurs several months earlier than the second warming evens (pink bars in Fig. 5), indicating that the PC3 contributes little to the second warming events in the SCS.
The EOF3 explains about 19.3% of the total variance. The peak of the corresponding PC2 is synchronous with the time from May [+ 1] to August [+ 1] in strong El Niño events, except the 2015–2016 event with an early and extreme warming (Xiao et al. 2020). The lead-lag correlation analysis shows that the Niño 3.4 leads PC2 by 7–8 months with the max correlation coefficient 0.54 (Fig. 6a). These results suggest that the EOF2 can well represent the second warming of the SCS SST in JJA [+ 1] responding to the strong El Niño events. Its spatial pattern features a cooling anomaly in the southern coast of China and a typical warming in the central SCS extending from the Vietnam coast to the east. We will focus on EOF2 to analyze the possible reasons for the second abnormal warming peak of the SCS SST occurring from June [+ 1] to August [+ 1] under the impact of strong El Niño events.
To further confirm the relationship between the SCS SST anomalies and the Indo-Pacific Oceans, we regressed global rOISST onto PC2,3, respectively (Fig. 7). The regression map of PC3 (Fig. 7b) exhibits a fundamental pattern of ENSO with dominant warming/cooling occurring in the eastern/western Pacific, indicating that the first abnormal warming of the SCS SST intensified in the west is a mostly common feature associated with all typical El Niño events. The regression map of PC2 shows that the regressed anomalies are positive in the SCS, the Indian Ocean and the western Pacific (Fig. 7a), indicating that the second warming process in the SCS is closely related to abnormal warming of Indo-Pacific Oceans. Xie et al. (2009) proposed that the tropical Indian Ocean (TIO) warming acts like a capacitor anchoring atmospheric anomalies over the Indo–western Pacific Oceans and then takes an effect on Indo–western Pacific climate during the summer following El Niño events. The regression maps of PCs in the SCS onto global SST anomalies can reveal the remote changes of Indo-Pacific on the SCS SST anomalies, which will be further discussed later in Section 5.
4.2 Physical processes related to the SCS SST anomalies in JJA [+ 1]
The heat budget analysis aforementioned in Section 3.2 provides that the anomalous Ekman heat convection and geostrophic heat convection contribute mostly to the development of the second abnormal warming that occurred from June [+ 1] to August [+ 1]. Accordingly, aiming at the second warming peak (JJA [+ 1]) for strong and regular El Niño events, the composite fields anomalous geostrophic currents, wind stress (curl), and net heat flux onto PC2 are given in Fig. 8. Comparisons between Fig. 8a, c, e, g and Fig. 8b, d, f, h show that only the amplitudes of fields during strong El Niño events are particularly noteworthy, and further confirm that the second warming peaked in August [+ 1] is the unique significant feature responding to strong El Niño events.
4.2.1 Geostrophic Current Changes
For strong El Niño events, the regressed SST anomalies upon the PC2 (Fig. 8a, shading colors) are featured with the basin-scale warming in JJA [+ 1] besides the cooling along the coast of China, consistent with the fundamental patterns depicted by Figs. 5 and 7a. We also notice that the location of warming signals center (Fig. 8a, black box) is similar to “cold filament” (Xie et al. 2003). This unusual development of warm signals centered around (113°E, 12°N) in the basin-scale of the SCS is mainly accompanied by the abnormal cyclonic/anticyclonic geostrophic currents along the coast of Vietnam (Fig. 8a, vectors), which has been diagnosed as the major reason for the rapid warming in July [+ 1] (Fig. 4a).
The summer atmospheric circulation in the SCS often has a dipole structure associated with a summertime eastward jet (SEJ), appearing off central Vietnam (e.g., Hu et al. 2000; Wang et al. 2006). The interannual variability of basin circulation is associated with the joint effect of the wind anomalies and the water exchange through Luzon Strait (Wang et al. 2020). The dipole gyres have an anticyclonic eddy south of the jet and a cyclonic eddy north of the jet (Bold solid purple lines, illustrated in Fig. 8a), and play important roles in the sea surface temperature variability of the basin (Liu et al. 2008). Numerous of efforts had revealed that this jet and associated gyres are tightly regulated by ENSO (e.g., Xie et al. 2003, 2007; Chen et al. 2010; Wang et al. 2013; Chen and Wang 2014; Fang et al. 2014; Li et al. 2014; Quan et al. 2016; Chu et al. 2016, 2020; Zu et al. 2020; Sun and Lan 2021). The occurrence of abnormal cyclonic/anticyclonic southern/northern gyres shown in Fig. 8a (vectors) indicates that the SEJ around 11–12°N accompanied with a dipole structure is greatly weakened in the JJA [+ 1], El Niño decaying summers (Bold dashed red lines, illustrated in Fig. 8a). The decrease of SEJ in El Niño decaying summers had revealed by previous studies (Li et al. 2014; Sun and Lan 2021). The weakening of the SEJ and related anticyclonic eddy south of the jet and a cyclonic eddy north of it can inhibit the processes of coastal upwelling and the advection of the cold coastal water offshore into the open SCS (Xie et al. 2003), then give rise to a strong basin-wide surface warming in the El Niño decaying summers. Li et al. (2014) further pointed out that the strengthening and migration of SEJ are predominantly contributed by the geostrophic current component that is linked to a meridional dipole pattern of sea level variations induced by local wind changes associated with ENSO. The dipole circulation is an almost perfect nutrient pump for new production, and the basin-wide horizontal circulation can explain the interannual changes of the vertical nutrient uplift during the summer (Hein et al. 2013).
4.2.2 Wind Stress and its Curl
The monsoonal forcing over the SCS is widely acknowledged as the major driving factor responsible for ocean circulation (e.g., Hu et al. 2000; Gan et al. 2006). In summer, as the southwesterly monsoon winds impinge on the mountains range on the east coast of Indochina, a strong wind jet occurs at its southern tip offshore east of Saigon, resulting in strong wind curls that are important for ocean upwelling off the coast (Xie et al. 2003). The summer monsoon exhibits a southward shift in its major components (Li et al. 2010). In JJA [+ 1] at the decaying stage of an El Niño event, it is largely reduced and behaves weaker such that a strong easterly (northeasterly) wind stress anomaly occurs in the southern SCS (Fig. 8c, vectors). The wind stress curl of monsoon is the major driving factor responsible for the SEJ and concomitant dipole gyres (Wang et al. 2006b; Cai et al. 2007). The weakened southwest monsoon at the decaying stage of an El Niño event can cause a weaker SEJ located north of its mean position (Li et al. 2014). In consequence, the weaker southwesterly summer monsoon favors generating anomalous cyclonic and anticyclonic gyres in the southern and northern basins respectively. and benefits the abnormal warming of the SCS SST in JJA [+ 1].
The qualitative diagnosis shows that anomalous Ekman heat advection plays an important role in the warm tendency of the SCS SST anomalies developing from June [+ 1] to July [+ 1]. Besides the notable easterly anomaly of wind stress over the southern SCS, there is discernible anomalous anticyclone circulation existing over the SCS (Fig. 8c, vectors). The abnormal easterly in southern SCS is one part of this anticyclone circulation, which will be talked about later as a uniform western North Pacific anticyclone (WNPAC). This anticyclonic atmospheric circulation anomaly over the SCS during 1998 summer is the major factor to results in a different response of scale upwellings in the SCS (Jing et al. 2011). The weakened summer monsoon, resulting in abnormal negative wind stress curls (Fig. 8e) is unfavorable for the coastal upwelling off the Vietnam coast by inhabiting the offshore Ekman transport. The anomalous negative wind stress curls mean the downward anomalous Ekman pumping, leading to the vertical movement of seawater, by accelerating seawater mixing basin-wide downwelling. The downward anomalous Ekman pumping and the positive mean vertical temperature gradient (Wang et al. 2006a) produce a warming trend of the SCS SST in July [+ 1].
4.2.3 Net Heat Flux and Latent Heat Flux
Besides the anomalous Ekman heat advection and anomalous geostrophic heat convection, the net heat flux is another reason for producing the SCS SST warming in June [+ 1] and July [+ 1]. Figure 8c and 8g shows that the latent heat flux is the major component of net heat flux. During JJA [+ 1] of strong El Niño events, the latent heat flux presents north-south discrepancy, and increases abnormally in the southern SCS, decreases in the northern SCS respectively, consistent with the pattern of net heat flux. In the northern basin, the latent heat flux is negative and the ocean loses heat to the atmospheres; therefore the warming phenomenon in this region principally depends on ocean advection processes, including anomalous geostrophic and Ekman heat advection. In the southern SCS, the positive latent heat flux can partly contribute to the warming signals in this region.
5.1 Relationship between cold filament index and PC2
Cold filament denotes the eastward extension of cold water from the Vietnamese coast, and has a profound effect on the cross-shelf transport of heat and nutrients (Xie et al. 2003; Li et al. 2017). If defining the cold filament index (CFI hereafter) as the averaging SST anomalies in the region of 10°N-13°N, 110°E -118°E (Fig. 8a, black box), similar to the approach taken by Xie et al. (2003), we can find that the summer CFI (for June to August) is correlated with the Niño 3.4 at a half-year lag, with a correlation coefficient of 0.67 (Xie et al. 2003). The interannual variability of cold filament related to ENSO is widely acknowledged (e.g., Xie et al. 2003; Zhao and Tang 2007; Liu et al. 2012; Hein et al. 2013; Li et al. 2017; Ngo and Hsin 2021). CFI is highly correlated with the PC2 with the zero-lag correlation coefficient 0.72. This means the CFI is significantly weakened in the decaying summer of strong El Niño events, corresponding to the second warming of the SCS SST anomalies. In regular El Niño decay summers, while the vertical process of coastal upwelling off the Vietnam coast is reduced, the SCS SST anomalies are still negative. Here, we show that the weakening of cold filament only happened in strong El Niño events. This result improves Xie et al. (2003) cool filament theory in discussing discrepant El Niño intensity and suggests the large variance of cool filament is caused by strong El Niño influences. Horizontal advection explains the substantial contributions of the strong ENSO signal in the region, and the basin-scale circulation controls the upwelling in the offshore area (Hein et al. 2013). The abnormal easterly induced by the sharp weakening of the summer monsoon is favorable for the decreasing of coastal upwelling, SEJ, and concomitant dipole gyres, then gives rise to the second warming reflected by PC2. Thus, the anomalous horizontal ocean advection contributing to the second SCS SST anomalies warming only happens in strong El Niño events.
5.2 Early onset of abnormal easterly wind anomalies
Figure 8c also shows that there is a strong easterly (northeasterly) wind stress anomaly occurring in the southern SCS, which is responsible for anomalous geostrophic and Ekman advection accompanied by the anomalous weakening of cold filament missing due to the benefit of the abnormal warming of the SCS SST in the decaying summer of strong El Niño events. If projecting the 850 hPa wind anomalies in Indo-Pacific upon the PC2 (Fig. 10), we can find that the abnormal easterly wind anomalies over the SCS (Fig. 8c) mostly origins from the western Pacific (Fig. 10a, blue box, 0°N-10°N, 120°E -160°E). The time series of the wind anomalies averaged in the western Pacific, along with Niño3.4 index (Fig. 10c), has a leading significant correlation with the Niño3.4 index (0.44 leads by 4 months for unfiltered data, and 0.77 leads by 5 months after one-year running mean). This suggests a moderately strong relationship between the zonal wind anomalies over the western Pacific and SST anomalies in the ENSO region. The early abnormal wind anomalies break out in the western Pacific means that the westerly/easterly winds intensify over the western equatorial Pacific and can efficiently force downwelling equatorial Kelvin waves and lead to a mature El Niño or La Niña event during the subsequent winter (e.g., McPhaden 1999, 2004; Lian et al. 2014), or vice versa.
One question arises here: between the subsequent summer, following the strong El Niño and regular El Niño events, is there a dominant difference of this abnormal wind anomalies over the western Pacific existing between them? Then, the composite time series of regressed zonal winds anomalies averaged over the western Pacific during strong El Niño and regular El Niño events are given in Fig. 10d. The strong El Niño event in 1997 was followed by a strong La Niño event in 1998 (Trenberth and Fasullo 2012). Of course, not all strong La Niño follow strong El Niño events reflecting the asymmetry between the amplitude of El Niño and La Niño (An and Jin 2004). From Fig. 10d, we can see that there is an earlier onset and longer duration of abnormal easterly wind anomalies that occurs following the subsequent strong El Niño events, compared with regular El Niño events. This means that the equatorial trade winds are strengthened in advance, and maintain throughout the mature and decaying phases of strong El Niño period for around one year from August [0] to December [+ 1]. However, for regular El Niño events, the abnormal westerly wind anomalies are obvious during the whole period of regular El Niño events. Following the subsequent year of regular El Niño events, the easterly wind anomalies are very weak and only last for a short time about two months from June [+ 1] to July [+ 1]. The strong and early onset of abnormal easterly wind anomalies can induce the weakening of the normal southwesterly monsoon in the southern SCS and then result in the warming of SST anomalies in the SCS during the subsequent year of strong El Niño events due to the disappearance of the cold filament along the Vietnamese coast, which is coupled with WNPAC (Xie et al. 2003).
In JJA [+ 1], the decaying of strong El Niño means the La Niño is developing meanwhile. The second warming of the SCS SST anomalies at this time is highly related to the large-scale atmospheric circulation changes. Corresponding to abnormal easterly wind on the equator (Fig. 8c, vectors), Fig. 11a indicates the vertical distribution of general circulation along the equator above the SCS and Pacific in strong El Niño decaying summer related to PC2. In strong El Niño JJA [+ 1], the sinking branch of Hadley circulation is around 160ºE and the convection ascent above SCS is significantly strong (Fig. 11a, c). The significant rising above the SCS is coherent with the abnormal rainfall in the SCS. Besides, it is noteworthy that the Meiyu-baiu region is abnormally rainy in JJA [+ 1], which means the SCS SST anomalies increasing in strong El Niño JJA [+ 1] is highly related to southern China’s extreme precipitation. As a teleconnection discussed by Nitta (1987), when a warm SCS event occurs, convection and precipitation tend to be suppressed in the western North Pacific while enhanced over Japan (Xie et al. 2003). Over the tropical Northwest (TNW) Pacific, rainfall variability is better correlated with ENSO in JJA [+ 1] than JJA [0], and there are fewer tropical cyclones (TCs) in post-El Niño summers (Du et al. 2011).
Wang et al. (2006a) have emphasized the local ocean dynamic processes to control the second warming during the subsequent El Niño events. This paper further illustrates that the abnormal early onset and long duration of easterly wind anomalies occurring in the western Pacific well denoted by the EOF2 is an important factor to induce the ocean dynamic factor to cause the second warming of the SCS SST anomalies.
5.3 The abnormal WNPAC in post strong El Niño summers
The advanced abnormal easterly wind anomalies over the western Pacific Ocean play an important role to regulate the ocean circulation and can induce the anomalous Ekman/geostrophic heat advection to warm the SCS SST in JJA [+ 1]. The easterly wind anomalies, can be considered as a branch of WNPAC, locate in the warm pool region of the western Pacific Ocean. El Niño affects the SCS SST through the anomalous Pacific East Asia teleconnection and the WNPAC (Wang et al. 2000). Therefore, we will discuss the impact of different El Niño events on the WNPAC further, especially focusing on the variation of WNPAC during the decaying summer of strong El Niño events.
The anomalous WNPAC develops rapidly in the late fall of the year when a strong ENSO event matures via wind-evaporation-SST feedback (Wang et al. 2000). During strong El Niño decaying summer JJA [+ 1], the abnormal WNPAC persists and is remarkably emerged in the regression pattern of the 850 hPa wind upon the PC2 (Fig. 10a). In JJA [+ 1], though the strong El Niño is decaying, it can exert an important impact on the East Asian summer monsoon (EASM) via regulating the variabilities of WNPAC (e.g., Wang et al. 2000; Wu et al. 2003; Feng et al. 2011). Here, we use a WNPAC index to qualify the intensity of the anomalous WNPAC defined as 10°N-30°N, 110°E-160°E regional mean vorticity anomaly (He et al. 2019). Its time series along with the wind anomalies averaged in the western Pacific (Fig. 10a) and the PC2 are shown in Fig. 12. The correlation coefficient between the WNPAC index with the easterly wind anomalies over the western Pacific is -0.72 after one-year running mean. Both of them also correlate to the PC2, with coefficients 0.47 and − 0.43, respectively. This shows that the easterly wind onset in the strong El Niño mentioned in Section 5.1 contributes to the second warming of the SCS SST anomalies in post strong El Niño summers.
The western Pacific subtropical high (WPSH) had great influences on the East Asian summer climate with the lower-level southerlies or southwesterlies at its western and southern edge (Huang et al. 2015b). In Fig. 12, we also show the WPSH index as the average of three definitions (Zuo et al. 2019; Wang and Fan 1999; Huang et al. 2010): first, the regional average of stream function anomalies in domain 15°N-25°N, 120°E-150°E (Zuo et al. 2019); second, the geopotential height anomalies averaged 15°N-25°N, 120°E-150°E (Wang and Fan 1999); and third, the wind anomalies difference averaged between 5°N-15°N, 100°E-130°E, and 20°N-30°N, 110°E-140°E (Huang et al. 2010). It shows that the WPSH is well correlated with WNPAC with the correlation of 0.67, which means that the establishment of WNPAC in summer climate is significantly regulated by the WPSH.
Following an El Niño event, the tropical Indian Ocean warming induces robust climatic anomalies in the summer Indian Ocean-west Pacific region, prolonging the El Niño influence (Yang et al. 2007). The Indo-Western Pacific Ocean Capacitor (IPOC) can keep the maintenance of the WNPAC in the decaying summer of El Niño events (Xie et al. 2009, 2016). The tropical Indian Ocean warming associated with El Niño events anchors a large-scale anomalous anticyclone via exciting an atmospheric Kelvin wave propagating into the western Pacific, and then takes an effect on East Asia during the following summer (Xie et al. 2016). Figure 12b shows that the WNPAC index in strong El Niño decaying summer is stronger than that in regular El Niño decaying summer, except 1994/95 and 2015/16, indicating that the El Niño events with distinct intensities can regulate the WNPAC and then warm the SST anomalies through weakening the southwest monsoon in the decaying summer (Yang et al. 2007). The inter-basin SST gradient between the Indian Ocean warming and the central Pacific cooling due to La Niño developing can also further favor the maintenance of WNPAC in the decaying El Niño summer (Terao and Kubota 2005; Ohba and Ueda 2006). The Indian Ocean warming and western Pacific cooling are caused by the easterly wind anomalies on the southern flank of the anomalous anticyclone that weaken the westerly summer monsoon (Du et al. 2009).
Considering the second warming of the SCS SST anomalies inferred by the PC2 is highly correlated with the Indian Ocean and tropical Northwest (TWN) Pacific, as inferred by Fig. 7, the tropical Indian Ocean and TWN Pacific SST anomalies are given to further explore the abnormal formation of the WNPAC in post summers associated with various intensity of the El Niño. Figure 13 shows the Niño3.4 index, SST anomalies averaged in the SCS (5.5ºN-24.5ºN, 105ºE-120ºE), TIO (20ºS-20ºN, 40–100ºE), and TWN-Pacific (10–20ºN, 150–170ºE), respectively, corresponding to strong and regular El Niño events. Figure 13b shows that the TIO warming is built up obviously in the strong El Niño events and the warming peak is much higher than that of regular El Niño events. The TIO warming peak (JJ [+ 1]) is about one month ahead of the second warming peak of the SCS SST anomalies, therefore, the TIO warming can be deducted as the major remote control factor to generate the second warming of the SCS SST anomalies via anchoring the abnormal formation of WNPAC. Figure 10a has also suggested that the anomalous Indian Ocean warming could anchor the abnormal formation of WNPAC in JJA [+ 1] via IPOC effects. The strong El Niño can excite robust IPOC mode with enhanced Pacific-Japan (PJ) variance (Chowdary et al. 2012; Kubota et al. 2015). Besides the Indian Ocean contributing, the Pacific Ocean can also promote the WNPAC existing in summer. Yun et al. (2013) have suggested the WNPAC in the strong El Niño decaying summer is related to La Niño developing with obvious cooling signals occurring in the central Pacific. The Niño 3.4 index reduces sharply in the JJA [+ 1] following strong El Niño events (Fig. 13a, red bold line), and the SST anomalies in the TNW-Pacific are also remarkably cooling (Fig. 13c, red bold line). It is revealed that the TIO warming, TNW-Pacific cooling, and related effects of IPOC are significantly influenced by the strength of El Niño events (Fig. 13), and this explains why a strengthened WNPAC can be maintained in strong El Niño decaying summer and finally take an effect on the second SCS SST anomalies warming.
In this paper, we study the physical mechanisms of the SCS SST anomalous warming in the subsequent summer of the strong El Niño events, especially from July [+ 1] to August [+ 1]. We show that the impacts of strong and regular El Niño events on the SCS SST anomalies are significantly different. The SCS SST anomalies in strong El Niño events can represent the abnormal warming peak twice around January [+ 1] and August [+ 1] with 0.39 ± 0.43 ºC and 0.4 ± 0.31 ºC respectively, whereas the regular El Niño events only have a weaker influence on this second warming events. Our results indicate that the abnormal second warming in the SCS is the unique response to the strong El Niño events, which is major affected by anomalous geostrophic and Ekman heat convection based on heat budget analysis.
Figure 14 assembles the mechanism driving the second abnormal warming during the strong El Niño events. In the decaying year of strong El Niño, the abnormal easterly winds, as part of the lower branch of the WNPAC, emerges in winter and sustains in summer, maintained by the Indian Ocean warming and TNW-Pacific cooling. This unique abnormal wind weakens southwest monsoon above the SCS and drives abnormal oceanic circulation in the SCS. Firstly, the geostrophic heat advection caused by the weakened coastal upwelling in the Vietnamese coast contributes most to the center of SCS basin warming in the decaying summers of strong El Niño events. Secondly, the anomalous Ekman pumping induced by negative wind stress curls warms the SCS SST in the central basin. Finally, the WNPAC drives abnormal upper branch atmospheric circulation in the southern basin and lower branch in the northern basin, which increases latent heat flux in the southern SCS and warms the SCS via atmospheric response. Our finding presents a new perspective of the SCS SST variability in response to ENSO, which is helpful for the prediction of the SCS and the East Asian climates.
Ethics approval and consent to participate
Not applicable.
Consent for publication
All authors gave their consent for publication.
Availability of data and material
This study has been conducted using E.U. Copernicus Marine Service Information (Sealevel anomalies and geostrophic velocity anomalies). Insert all relevant DOIs links here: https://doi.org/10.48670/moi-00148. OISST v2.1 data, ERSST data, CMAP Precipitation data and NCEP/NCAR Reanalysis 1 data provided by the NOAA PSL, Boulder, Colorado, USA, from their website at https://psl.noaa.gov.
Competing interests
The authors declare no competing interests.
Funding
This work is funded by the National Natural Science Foundation of China (Grant 42176027, 41876017, 41576012), State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology Chinese Academy of Sciences (Grant LTOZZ2101).
Authors' contributions
Qin-Yan Liu led this research. Hanwen Bi performed all of the analysis, draw the figures, and led the draft of this manuscript. Xianyao Chen provided constructive suggestions for improving the research and writing. Authors contribute substantially to the writing and the revision.
Acknowledgement
This work is supported by the National Natural Science Foundation of China (Grant 42176027, 41876017, 41576012), State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology Chinese Academy of Sciences (Grant LTOZZ2101).
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No competing interests reported.