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--> --> -->After the strong 2015/16 El Ni?o event, the tropical Pacific experienced a cold condition during 2016–18. That is, a cold sea surface temperature (SST) anomaly (SSTA) appeared in mid-2016 and persisted through late 2016; then, a slightly warmer condition occurred in early 2017, but a cold SST condition re-emerged in late 2017. We refer to it as the second-year cooling of late 2017.
At present, there are about 27 models that are used for real-time ENSO forecasts (see
Figure1. (a) Time series of the Ni?o3.4 SST anomalies in 2017 predicted from the initial condition in mid-March 2017 (colored lines) using different models. Each colored line indicates forecasts in nine overlapping three-month periods (FMA represents February–March-April). (b) As in (a) but the anomalies are predicted from the initial condition in mid-September. The black stars indicate the observation. This figure is taken from the IRI website at http://iri.columbia.edu/our-expertise/climate/forecasts/enso.There are several theories developed to explain the evolution of ENSO. A well-known one is the recharge/discharge theory (e.g., Wyrtki, 1985; Jin, 1997), which emphasizes the water exchange on and off the equator in the ocean. Another was proposed by Suarez and Schopf (1988), known as the delayed oscillator theory, which can be used to explain ENSO dynamics and its interannual oscillation within the tropical Pacific climate system (Battisti and Hirst, 1989). This theory focuses on wave processes (the equatorial Rossby wave and its reflection along the western boundary into a Kelvin wave). Some previous studies have focused on the quick termination of ENSO. For example, Stuecker et al. (2013) suggested that the southward shift of westerly wind anomalies during boreal winter and spring triggers the termination of large El Ni?o events. Zhang et al. (2015) further confirmed that the wind shift appears only during eastern-Pacific El Ni?o events rather than during central-Pacific El Ni?o events. Chen et al. (2016) demonstrated the sudden basin-wide reversal of anomalous equatorial zonal transport above the thermocline at the peaking phase of ENSO triggers rapid termination of ENSO events, and the anomalous equatorial zonal transport is controlled by the concavity of anomalous thermocline meridional structure across the equator. As for second-year cooling (also named “double dip” evolution) during La Ni?a, Zhang et al. (2013) discussed why an intermediate coupled model (ICM) gave a good prediction of the 2010/11 La Ni?a event when most models failed in the IRI-collected prediction products, and revealed that the thermocline feedback represented by the relationship between entrainment temperature into the mixed layers (Te) and SL in the ICM was a crucial factor affecting the second-year cooling in 2011. Based on the Global Ocean Data Assimilation System (GODAS), Feng et al. (2015) analyzed the entire evolution processes of the 2011/12 La Ni?a event and emphasized the role of tropical South Pacific cold water. Zheng et al. (2015) further confirmed the importance of South Pacific cold water and southern wind in the developing of the 2011 negative SST anomalies. By using an ICM, Gao and Zhang (2017) suggested that the intensity of interannual wind forcing was equally important to SST evolution during 2010/11 compared with that of the thermocline effect. Hu et al. (2014) investigated why some La Ni?a events are followed by another La Ni?a but others are not. Their results show that both the surface wind in the far-eastern equatorial Pacific and the recharge/discharge of the equatorial Pacific waters are indicators for the possible occurrence of a follow-up La Ni?a event.
Here, we analyze processes that may have been responsible for the second-year cooling of the 2017/18 La Ni?a event. By using reanalysis data, the roles played by wind stress and subsurface thermal anomalies in the tropical Pacific are diagnosed. Since subsurface temperature anomalies tend to propagate along density surfaces, we adopted isopycnal analyses by using three-dimensional temperature and salinity fields (Zhang and Rothstein, 2000; Feng et al., 2015).
The remainder of this paper is organized as follows: The data and methods used in this work are introduced in section 2. Section 3 describes the onset and evolution of the 2017/18 La Ni?a event. Sections 4 and 5 illustrate the role that wind stress and subsurface cold water played during the second-year cooling. Section 6 presents a summary and discussion.
Long-term climatological fields were calculated for the periods January 1980 to December 2018. Then, interannual anomalies for SST, temperature, SL, thermocline depth, SLP and wind stress were formed relative to their climatological fields. Isopycnal surface depths were calculated using temperature and salinity data; both the climatological current and anomalous temperature at level depths were interpolated to constant density surfaces by using a cubic spline. In this work, climatological and interannual anomaly fields on isopycnal surfaces are used to investigate the 2017/18 La Ni?a event.
Figure2. Temporal evolutions of interannual anomalies along the equator (averaged between 2°S and 2°N) in 2016/17 for (a) SST (units: ℃), (b) SL (sea level; units: cm), (c) thermocline depth (units: m), (d) Taux (zonal wind stress), (e) Tauy (meridional wind stress), and (f) total wind stress. The units for the wind stresses are dyn (1 dyn = 10?5 N) cm?2.To better describe the SSTA evolution during 2017, the horizontal distributions of SSTAs at some selected time intervals are shown in Fig. 3. In January, cold SSTAs prevailed in the central-eastern tropical Pacific, where ocean temperatures were about 0.6°C cooler than the average along the equator between 160°–170°W (Fig. 3a). SSTAs were positive in the west-central and far-eastern Pacific. Thereafter, cold waters extended westward and shrinked dramatically, and the central-eastern tropical Pacific was later occupied by warm SSTAs (Fig. 3b). This warming tendency was sustained during the following months, and then almost the entire tropical Pacific was covered by positive SSTAs, and the negative SSTAs nearly disappeared (Fig. 3c). From July, weak negative SSTAs reappeared in the southeast equatorial Pacific (Fig. 3d), and soon prevailed in the central-eastern equatorial Pacific in August (Fig. 3e). Subsequently, the cold SSTAs further strengthened and extended westward quickly (Figs. 3f–h), leading to the occurrence of the second-year cooling. However, how the cold SSTAs were produced in the central-eastern equatorial Pacific during mid-late 2017 have not been fully understood. In the following sections, some possible factors, such as the effects of wind forcing and subsurface thermal anomalies will be examined.
Figure3. Horizontal distributions of SSTAs (from ERSST.v5) during 2017 for (a) January, (b) March, (c) May, (d) July, (e) August, (f) September, (g) October, and (h) November. Units: °C.Wind stress and SLP anomalies were calculated from the ERA5 data (Fig. 4). Positive SLP anomalies were seen in the tropical central-eastern Pacific, which were consistent with the distribution of negative SSTAs. Southerly wind anomalies prevailed in the tropical western Pacific and northerly wind anomalies occupied the tropical eastern Pacific. Positive SLP anomalies induced wind stress divergence anomalies in the tropical central-eastern Pacific, which was favorable for cold water upwelling from the subsurface to sustain the negative SSTAs. In March (Fig. 4b), the positive SLP anomalies weakened, but southerly wind anomalies in the tropical western Pacific and northerly wind anomalies in the tropical eastern Pacific persisted. The wind stress anomalies changed direction in May (Fig. 4c), with northeasterly wind stress anomalies in the tropical western Pacific and weak southerly wind stress anomalies in the tropical eastern Pacific. Weak wind stress divergence anomalies re-emerged in the far-eastern tropical Pacific in July (Fig. 4d), accompanied by weak negative SSTAs (Fig. 3d). The wind stress divergence anomalies strengthened during the following months and propagated westward (Figs 4e-h), which contributed to the development of the second-year cooling of the La Ni?a event.
Figure4. Horizontal distributions of SLP (shading) and wind stress anomalies (vectors) during 2017 for (a) January, (b) March, (c) May, (d) July, (e) August, (f) September, (g) October and (h) November. Units: hPa for SLP; dyn cm-2 for wind stress.
Figure5. Temperature anomalies evaluated on the σ = 25.2 isopycnal surface in 2017 for (a) January, (b) March, (c) May, (d) July, (e) August, (f) September, (g) October, and (h) November. Superimposed are climatological ocean currents (vectors) for the corresponding months. Units: ℃ for temperature; cm s?1 for currents.The vertical distribution of anomalous temperature in the upper ocean along the equator can reveal the connection between the surface and subsurface thermal condition (Fig. 6). In January, most of the eastern equatorial Pacific was occupied by cold anomalies while the western and central equatorial Pacific was occupied by warm anomalies. Then, cold water in the far-eastern equatorial Pacific was replaced by large warm anomalies in March, and the remaining large anomaly region concentrated in the central-eastern equatorial Pacific and outcropped only in the central Pacific. From May, nearly all the negative anomalies were confined in the subsurface, which formed three cold centers (at 150°E, 150°W and 110°W, separately) that then merged into one in July (but still dominantly seen below the sea surface). From August, the negative temperature anomalies in the eastern equatorial Pacific became strong and outcropped to the surface, causing negative SSTAs. This tendency continued during the following months and caused the second-year cooling (Figs. 6f–h).
Figure6. Zonal sections of upper-ocean temperature anomalies in 2017 along the equator (averaged between 2°S and 2°N) displayed on isopycnal surfaces as a vertical axis for (a) January, (b) March, (c) May, (d) July (e) August, (f) September, (g) October, and (h) November. Units: °C.As analyzed above, there are close relationships between the subsurface temperature anomalies and SSTAs. Figure 7 presents the temperature anomalies, horizontal and vertical velocity fields evaluated on 23.4 and 25.2 isopycanls. It is evident that the convergence pattern of horizontal currents was similar to the vertical velocity field. As an example, the convergence center was located on the equator near 100°W, where the Equatorial Undercurrent (EUC) met with the South Equatorial Current (SEC), producing a strong upwelling (Fig. 7a). In July, weak negative subsurface temperature anomalies were accompanied by upwelling in the eastern-equatorial Pacific (Fig. 7a), which provided the subsurface source for cold water that was seen to entrain into the surface layer. Then, both cold anomalies and upwelling enhanced and extended westward in the eastcentral equatorial Pacific on the 25.2 isopycnal (Figs. 7b–d). These changes were generated by the seasonally strengthened SEC and weakened EUC, which favored more cold water to accumulate in the central equatorial Pacific. Figures 7e–h suggest that the vertical currents in the upper layers were stronger than those in the lower layers (Figs. 7a–d), and the cold anomalies emerged later than in the lower layer, which demonstrated that the cold water was coming from the subsurface.
Figure7. Temperature anomalies (shading) evaluated on the σ= 25.2 (left-hand panels) and σ =23.4 (right-hand panels) isopycnal surfaces in 2017 for (a, e) July, (b, f) August, (c, g) September, and (d, h) October. Superimposed are climatological ocean currents (vectors) and vertical velocity 103w (contours) for the corresponding months. Units: °C for temperature; cm s?1 for ocean currents.Negative SSTAs dominated in the central and eastern equatorial Pacific in late 2017 (Figs. 3f–h). Cold SSTAs in the east induced wind responses to the west, which in turn had influences on the SST and thermocline in the east. The interactions among SSTAs, winds and thermocline anomalies formed a coupling loop; the second-year cooling during 2017 emerged in the tropical Pacific.
To quantify the roles different physical processes played in the second-year cooling, we examined the mixed-layer heat budget in the Ni?o3.4 region (5°S–5°N, 170°–120°W) during November 2016 to December 2017 (Fig. 8), which was obtained from GODAS pentad-averaged outputs (Huang et al., 2010); this figure was downloaded from the Climate Prediction Center Ocean Briefing at
Figure8. Time series of the mixed-layer heat budget and optimum interpolation (OI) SSTA in the Ni?o3.4 region (5°S–5°N, 170°–120°W) during November 2016 to December 2017, which was downloaded from the GODAS pentad-averaged outputs at https://www.cpc.ncep.noaa.gov/products/GODAS in the Climate Prediction Center Ocean Briefing. In the figure, Qu represents zonal advection; Qv represents meridional advection; Qw represents vertical entrainment; Qzz represents vertical diffusion; Qq represents (Qnet – Qpen + Qcorr)/ρcph; Qnet = shortwave radiation (SW) + longwave radiation (LW) + latent heat flux (LH) + sensible heat flux (SH); Qpen represents SW penetration; Qcorr represents flux correction due to relaxation to the OI SST.A sequence of events is described that led to the second-year cooling in the 2017/18 La Ni?a event. Pronounced anomalous westerly winds emerged in December 2016 over the eastern Pacific and propagated westward, which counteracted the easterly wind anomalies in the central Pacific and the cold water upwelling in the eastern equatorial Pacific. As a result, the La Ni?a event was interrupted during the first half of 2017. From July 2017, the easterly anomalies re-strengthened in the central Pacific; meanwhile, wind stress divergence anomalies re-emerged in the far-eastern tropical Pacific (Fig. 4d), accompanied by weak negative SSTAs (Fig. 3d). The wind stress divergence anomalies strengthened during the following months and propagated westward (Figs. 4e–h), which contributed to the development of the second-year cooling of the La Ni?a event. As for the subsurface, weak negative temperature anomalies were accompanied by strong upwelling in the eastern Pacific (Fig. 7a), providing the cold water source that could be entrained into the surface layer. Thereafter, both negative temperature anomalies and upwelling enhanced and extended westward in the central-eastern equatorial Pacific on the 25.2 isopycnal (Figs. 7b–d). These changes were generated by the seasonally weakened EUC and strengthened SEC, which contributed to more cold water being accumulated in the central equatorial Pacific. Then, cold water stretched upward with the convergence of horizontal currents and eventually appeared on the surface. These subsurface-generated SSTAs acted to induce local coupled air–sea interactions, which generated atmospheric–oceanic anomalies developing and evolving into the second-year cooling in the fall of 2017.
What new physical processes can be learned from the analyses of the 2017/18 La Ni?a event? Compared with the 2010/12 La Ni?a event, we found that there are notable differences between them:
(1) The effects of the western Pacific warm waters in 2017 were weaker than those in 2011 during the break off of the first year cooling. Subsurface warm waters in the western Pacific extended eastward across the equator in early 2011 (Feng et al., 2015) and interrupted the La Ni?a event; however, cold waters persisted in the subsurface during early 2017. The break-off of the 2017 La Ni?a resulted from the western wind stress anomalies in the eastern Pacific during early 2017.
(2) The negative SSTAs first emerged in the central equatorial Pacific in mid-2011 (Feng et al., 2015), while they presented in the far-eastern equatorial Pacific in fall 2017. Thus, the 2017/18 cooling was of eastern equatorial Pacific origin.
(3) During the second-year cooling of the 2010/12 La Ni?a event, the negative subsurface temperature anomalies in the tropical South Pacific stretched northward and invaded the equatorial region at the thermocline depth, accompanied by southerly wind anomalies from July 2011 (Zheng et al., 2015); whereas cold anomalies on both sides of the equator played the same role during the 2017/18 La Ni?a event (Fig. 9), with divergent wind stress anomalies in the eastern Pacific from July 2017.
Figure9. Meridional sections of upper-ocean temperature anomalies (shading) and climatological v and 103w (vectors) displayed on isopycnal surfaces as a vertical axis for 2011 (left-hand panels, averaged between 120°W and 160°W) and 2017 (right-hand panels, averaged between 80°W and 180°W) in (a, e) June, (b, f) July, (c, g) August, and (e, f) September. Units: ℃ for temperature; cm s-1 for ocean currents.This work provides an observational basis for process understanding and model validation. Results can be used to understand ways coupled models predict this second-year cooling and offer guidance for analyses of other multi-year cooling events. Further study on the origin of easterly wind anomalies, which played an important role in the second-year cooling, are needed. For example, higher-frequency atmospheric variability over the western-central Pacific, such as easterly wind surges (Chiodi and Harrison, 2015) and Madden–Julian Oscillation (Madden and Julian, 1994). In addition, signals from the extratropical Pacific (Ding et al., 2017) and the Southern Indian/Atlantic oceans (Terray, 2011; Sun et al., 2017) may also play important roles. Results in this paper are based on one piece of data analysis, and there are some noticeable disagreements among different reanalyses (Xue et al., 2011; Kumar and Hu, 2012). Thus, more reanalysis data need to be used to confirm the results in the future.
Acknowledgements. We thank the three anonymous reviewers for their valuable comments. This work was jointly supported by grants from the National Natural Science Foundation of China [Grant Nos. 41576029 and 41690122(41690120)], the National Program on Global Change and Air–Sea Interaction (Grant No. GASI-IPOVAI-03), the National Key Research and Development Program (Grant No. 2018YFC1505802), and the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant Nos. XDA19060102 and XDB 40000000). We thank the Climate Prediction Center Ocean Briefing group for providing the mixed-layer heat budget analyses in Fig. 8, which were downloaded from
