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Roles of Wind Stress and Subsurface Cold Water in the Second-Year Cooling of the 2017/18 La Niña Event


doi: 10.1007/s00376-020-0028-4

  • After the strong 2015/16 El Niño event, cold conditions prevailed in the tropical Pacific with the second-year cooling of the 2017/18 La Niña event. Many coupled models failed to predict the cold SST anomalies (SSTAs) in 2017. By using the ERA5 and GODAS (Global Ocean Data Assimilation System) products, atmospheric and oceanic factors were examined that could have been responsible for the second-year cooling, including surface wind and the subsurface thermal state. A time sequence is described to demonstrate how the cold SSTAs were produced in the central-eastern equatorial Pacific in late 2017. Since July 2017, easterly anomalies strengthened in the central Pacific; in the meantime, wind stress divergence anomalies emerged in the far eastern region, which strengthened during the following months and propagated westward, contributing to the development of the second-year cooling in 2017. At the subsurface, weak negative temperature anomalies were accompanied by upwelling in the eastern equatorial Pacific, which provided the cold water source for the sea surface. Thereafter, both the cold anomalies and upwelling were enhanced and extended westward in the centraleastern equatorial Pacific. These changes were associated with the seasonally weakened EUC (the Equatorial Undercurrent) and strengthened SEC (the South Equatorial Current), which favored more cold waters being accumulated in the central-equatorial Pacific. Then, the subsurface cold waters stretched upward with the convergence of the horizontal currents and eventually outcropped to the surface. The subsurface-induced 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.
    摘要: 2015/16年强厄尔尼诺事件之后,热带太平洋海温呈冷异常状态,并在2017/18年出现二次变冷过程。许多耦合模型未能预测出2017年的海温冷异常。本文利用ERA5和全球海洋数据同化系统(GODAS)数据,研究了可能导致二次变冷的大气和海洋过程,包括表层风和次表层热力状态。文中给出了2017年后半年赤道中东部太平洋海温冷异常的完整演变过程。自2017年7月以来,太平洋中部的东风增强;与此同时,远东太平洋出现风应力辐散异常,随后风应力辐散增强并向西传播,促进了2017年二次变冷的发展。在次表层,弱的海温冷异常伴随着赤道东太平洋的上升流,为海面源源不断地提供冷水。随着时间推移,赤道中东部太平洋海温冷异常和上升流增强并向西扩展。这些变化与赤道潜流的季节性减弱和南赤道流的季节性增强有关,有利于在赤道中太平洋聚集更多的冷水。次表层冷水随着水平流场的辐合向上伸展,最终露出海面。次表层冷水上翻引起的海表温度冷异常激发局部的大气-海洋相互作用,产生大气-海洋异常,并进一步发展演化为2017年秋季的二次变冷。
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  • Figure 1.  (a) Time series of the Niño3.4 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.

    Figure 2.  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.

    Figure 3.  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.

    Figure 4.  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.

    Figure 5.  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.

    Figure 6.  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.

    Figure 7.  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.

    Figure 8.  Time series of the mixed-layer heat budget and optimum interpolation (OI) SSTA in the Niño3.4 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 (QnetQpen + 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.

    Figure 9.  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.

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Manuscript received: 13 February 2020
Manuscript revised: 11 May 2020
Manuscript accepted: 28 May 2020
通讯作者: 陈斌, bchen63@163.com
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Roles of Wind Stress and Subsurface Cold Water in the Second-Year Cooling of the 2017/18 La Niña Event

    Corresponding author: Rong-Hua ZHANG, rzhang@qdio.ac.cn
  • 1. National Marine Environmental Forecasting Center, Ministry of Natural Resources, Beijing 100081, China
  • 2. Key Laboratory of Marine Hazards Forecasting, National Marine Environmental Forecasting Center, Ministry of Natural Resources, Beijing 100081, China
  • 3. Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, and Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao 266071, China
  • 4. Pilot National Laboratory for Marine Science and Technology, Qingdao 266237, China
  • 5. Center for Excellence in Quaternary Science and Global Change, Chinese Academy of Sciences, Xi’an 710061, China
  • 6. Beijing Weather Forecast Center, Beijing 100089, China

Abstract: After the strong 2015/16 El Niño event, cold conditions prevailed in the tropical Pacific with the second-year cooling of the 2017/18 La Niña event. Many coupled models failed to predict the cold SST anomalies (SSTAs) in 2017. By using the ERA5 and GODAS (Global Ocean Data Assimilation System) products, atmospheric and oceanic factors were examined that could have been responsible for the second-year cooling, including surface wind and the subsurface thermal state. A time sequence is described to demonstrate how the cold SSTAs were produced in the central-eastern equatorial Pacific in late 2017. Since July 2017, easterly anomalies strengthened in the central Pacific; in the meantime, wind stress divergence anomalies emerged in the far eastern region, which strengthened during the following months and propagated westward, contributing to the development of the second-year cooling in 2017. At the subsurface, weak negative temperature anomalies were accompanied by upwelling in the eastern equatorial Pacific, which provided the cold water source for the sea surface. Thereafter, both the cold anomalies and upwelling were enhanced and extended westward in the centraleastern equatorial Pacific. These changes were associated with the seasonally weakened EUC (the Equatorial Undercurrent) and strengthened SEC (the South Equatorial Current), which favored more cold waters being accumulated in the central-equatorial Pacific. Then, the subsurface cold waters stretched upward with the convergence of the horizontal currents and eventually outcropped to the surface. The subsurface-induced 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.

摘要: 2015/16年强厄尔尼诺事件之后,热带太平洋海温呈冷异常状态,并在2017/18年出现二次变冷过程。许多耦合模型未能预测出2017年的海温冷异常。本文利用ERA5和全球海洋数据同化系统(GODAS)数据,研究了可能导致二次变冷的大气和海洋过程,包括表层风和次表层热力状态。文中给出了2017年后半年赤道中东部太平洋海温冷异常的完整演变过程。自2017年7月以来,太平洋中部的东风增强;与此同时,远东太平洋出现风应力辐散异常,随后风应力辐散增强并向西传播,促进了2017年二次变冷的发展。在次表层,弱的海温冷异常伴随着赤道东太平洋的上升流,为海面源源不断地提供冷水。随着时间推移,赤道中东部太平洋海温冷异常和上升流增强并向西扩展。这些变化与赤道潜流的季节性减弱和南赤道流的季节性增强有关,有利于在赤道中太平洋聚集更多的冷水。次表层冷水随着水平流场的辐合向上伸展,最终露出海面。次表层冷水上翻引起的海表温度冷异常激发局部的大气-海洋相互作用,产生大气-海洋异常,并进一步发展演化为2017年秋季的二次变冷。

1.   Introduction
  • El Niño–Southern Oscillation (ENSO) is the major mode of interannual variability in the tropical Pacific climate system. Its influences are not limited to the regional climate, but can induce worldwide climatic, ecological and societal anomalies. Since the 1980s, extensive focused studies have made essential progress in understanding, modeling and predicting El Niño events (e.g., Cane and Zebiak, 1985; Zebiak and Cane, 1987; Philander, 1992; Jin and Neelin, 1993; Wang et al., 2013; Ren et al., 2013, 2014, 2016; Zhang and Gao, 2016).

    After the strong 2015/16 El Niño 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 https://iri.columbia.edu/our-expertise/climate/forecasts/enso/current/) and new members keep joining the prediction group. The current forecast models can supply effective predictions of ENSO events 6–12 months ahead (Barnston et al., 2012). Hence, ENSO is thought to be the most predictable signal at the time scales of seasonal to interannual climate prediction. Figure 1 demonstrates the real-time model performance in predicting the 2017/18 La Niña event, collected at the International Research Institute for Climate and Society (IRI)/Columbia University. Figure 1 indicates that the observed SST evolution from autumn 2017 through spring 2018 was adequately captured when model predictions were initialized from September 2017 (Fig. 1b). However, these models failed to predict the Niño3.4 SST cooling when initialized from early-mid 2017. Indeed, there were large uncertainties in the predictions using these coupled models. For instance, the predicted magnitude exhibited a wide spread across these coupled models in fall and winter 2017. Predictions in 2017 and 2018 clearly reveal that the real-time prediction of ENSO remains problematic and challenging, even when state-of-the-art coupled models are used with data assimilation. This presents a challenge to ENSO prediction communities and an urgent need to study the processes responsible for the second-year cooling in 2017. Indeed, atmospheric and oceanic processes leading to the second-year cooling during the 2017/18 La Niña event are still poorly understood. Studies on factors determining the cooling in 2017, and understanding processes and improving real-time predictions, are clearly needed.

    Figure 1.  (a) Time series of the Niño3.4 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 Niño events. Zhang et al. (2015) further confirmed that the wind shift appears only during eastern-Pacific El Niño events rather than during central-Pacific El Niño 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 Niña, Zhang et al. (2013) discussed why an intermediate coupled model (ICM) gave a good prediction of the 2010/11 La Niña 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 Niña 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 Niña events are followed by another La Niña 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 Niña event.

    Here, we analyze processes that may have been responsible for the second-year cooling of the 2017/18 La Niña 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 Niña 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.

2.   Data and methods
  • The monthly data for temperature, sea level (SL), salinity, thermocline depth and currents are from GODAS (Behringer and Xue, 2004), which is operational at the National Centers for Environmental Prediction. The resolution is 1°×1/3° in the horizontal direction, with 40 layers in the vertical direction and a 10-m resolution in the upper 200 m. We use GODAS data that cover the period January 1980 to December 2018. Additionally, sea level pressure (SLP) and surface winds taken at the height of 10 m are from ERA5, which covers the globe on a 30-km grid (Copernicus Climate Change Service, 2017). We computed wind stress from wind velocity (Weisberg and Wang, 1997). The monthly ERSST.v5 dataset from NOAA with a 2°×2° grid is used for describing the SST evolution.

    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 Niña event.

3.   Observed evolution during 2016/17
  • Several variables from a range of datasets are used to represent different aspects of the La Niña evolution and to describe the processes thoroughly. Figure 2 displays the temporal and zonal evolutions of interannual variations in SST, SL, thermocline depth, and zonal and meridional wind stress in the equatorial Pacific (averaged between 2°S and 2°N) in 2016/17. The evolution of the 2017/18 La Niña event was obvious at the equator, and there was a close connection among these anomalous fields. As for the SSTA, a second-year cooling emerged over the equatorial central-eastern Pacific in mid-to-late 2017 (Fig. 2a), following the first cooling in 2016. After the weak 2016 La Niña event that was seen to end in early 2017, above-normal SSTAs presented in the eastern equatorial Pacific and extended westward with time. Above-normal SSTAs occupied almost the whole equatorial Pacific in May and June 2017. However, negative SSTAs re-emerged in the eastern equatorial Pacific in July, and propagated westward during the following months, and the second-year cooling condition formed in fall 2017. Corresponding to the SSTAs, the anomalies of SL showed similar evolution patterns over the central and eastern equatorial Pacific (Fig. 2b). More specifically, positive SL anomalies emerged in the eastern equatorial Pacific and negative SL anomalies declined in the central Pacific during the first half of 2017. Moreover, the anomalies of thermocline depth (Fig. 2c), represented by the 20°C isotherm depth, were highly correlated with the SSTAs (Fig. 2a): a negative SSTA corresponds to a shallow thermocline, and vice versa. As for the zonal wind stress, an easterly anomaly prevailed in the west-central Pacific, which corresponded to the westward extension of cold sea surface water and cold subsurface water upwelling in the eastern Pacific; this condition was favorable for the continuation of the La Niña condition. However, westerly wind stress anomalies exceeding 0.1 dyn cm−2 (0.01 N m−2) emerged during December 2016 to February 2017 in the eastern Pacific, which was unfavorable for the persistence of the La Niña condition. Anomalous westerly winds were strong during early 2017 in the eastern basin and propagated westward along the equator, acting to weaken the easterly wind anomalies in the central Pacific; thus, these processes played a dominant role in shifting SST conditions in the equatorial Pacific. As a result, the La Niña was interrupted during the first half of 2017. Consistent with the results of Zhang and McPhaden (2006, 2008, 2010), a zonal wind stress anomaly of 0.01 N m-2 in the eastern Pacific resulted in an SST anomaly of approximately 1°C over the Niño3 region (5°N–5°S, 150°–90°W), due to changes in local upwelling rates. From June 2017, the easterly anomalies re-strengthened in the central Pacific, which helped to establish the second-year cooling condition. In general, the meridional winds were northerly in the eastern equatorial Pacific and southerly in the western and central equatorial Pacific, and both the northerly and southerly winds weakened after March 2017 (Fig. 2e). Figure 2f demonstrates a predominance of the anomalous southeasterly winds over the central equatorial Pacific region, and northwesterly winds over the eastern equatorial Pacific region during the first three months of 2017. The persistent and westward propagation of the northwesterly winds along the equator blocked the maintenance of the La Niña in early 2017.

    Figure 2.  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. 3fh), 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.

    Figure 3.  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.

4.   Role of wind stress
  • ENSO is produced by interactions between the atmosphere and ocean in the tropical Pacific, in which wind stress plays a crucial role in ENSO evolution. Locally, anomalous easterly winds in the western tropical Pacific directly force anomalous ocean currents, which give rise to a negative SSTA through horizontal advection. In addition, anomalous easterly winds act to elevate the thermocline, which causes negative subsurface entrainment temperature (Te) anomalies in the central Pacific, and further enhances a negative SSTA in the central and eastern equatorial Pacific (Gao and Zhang, 2017).

    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 Niña event.

    Figure 4.  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.

5.   Role of subsurface cold waters
  • There are close relationships between upper-ocean thermal conditions and subsurface water entrainment into the mixed layer, with the variation of upper-ocean heat content leading Niño3.4 SST anomalies by one to three seasons (e.g., Meinen and McPhaden, 2000; Hu et al., 2014). The subsurface temperature anomalies evaluated on the 25.2 isopycnal surface [see Feng et al. (2015) for details] in some selected time periods in 2017 are presented in Fig. 5. Different from the SSTAs, the central tropical Pacific was occupied by warm water (160°E–150°W), which separated the cold water into west and east parts (Fig. 5a). The area with the western tropical Pacific cold temperature anomalies was small, and their strength was weak. As for the eastern tropical Pacific, the area with cold temperature anomalies was wide and their strength was strong. The amplitudes of the cold temperature anomalies on both sides of the equator were lower than −4°C. In March, warm water emerged in the eastern equatorial Pacific, and the cold water nearly disappeared in the western equatorial Pacific, so the anomaly pattern shifted westward as a whole (Fig. 5b). The distribution of temperature anomalies in May resembles that in March, with small amplitude (Fig. 5c). As analyzed above, the signs of subsurface temperature anomalies were very different from those of the SSTAs. While positive SSTAs gradually prevailed in the tropical Pacific during the first half of the year, negative temperatures persisted in the subsurface layers, which provided the potential for reversing the SSTA sign during the following months. Cold temperature anomalies strengthened again in July and occupied nearly the whole equatorial Pacific (Fig. 5d), with a cold core exceeding −2°C in the central-eastern Pacific (160°–120°W). This tendency continued during the following months (Figs. 5eg).

    Figure 5.  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. 6fh).

    Figure 6.  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. 7bd). 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 7eh suggest that the vertical currents in the upper layers were stronger than those in the lower layers (Figs. 7ad), and the cold anomalies emerged later than in the lower layer, which demonstrated that the cold water was coming from the subsurface.

    Figure 7.  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. 3fh). 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 Niño3.4 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 https://www.cpc.ncep.noaa.gov/products/GODAS. It can be seen that the SSTA tendency (dT/dt, dotted black line) and the total budget tendency (right-hand side, solid black line) kept the same sign but had different amplitudes during November 2016 to December 2017, which suggests that the mixed-layer heat budget closure is generally reasonable. The observed SSTA tendency switched to be positive in October 2016 and persisted to June 2017, consistent with the decay of the La Niña condition. The adjusted surface heat flux (Qq) was positive during November 2016 to February 2017, and played an important role in the decay of the La Niña condition. In August 2017, both the observed SSTA tendency and total budget tendency became negative. Accompanied by the autumn reversal of the SEC to be westward [Fig. 1b in Huang et al. (2010)], the contribution of zonal advection (Qu) was the largest to the cooling (about −0.3°C month−1) from August to November 2017. Meridional advection (Qv) contributed secondarily to the cooling (about −0.1°C month−1) from August to September 2017 when northerly currents were strong [Figs. 2f-g in Huang et al. (2010)], and exceeded that due to the combined cooling (about -0.1°C month-1) by entrainment and vertical diffusion (Qw + Qzz) in October 2017, which was associated with wind stress anomalies. These results are consistent with the aforementioned analysis; that is, cold waters upwelled to the mixed layer from the subsurface in the eastern Pacific (Fig. 7a) and then advected westward by the SEC to cool the Niño3.4 region. With time, the upwelling extended westward (Fig. 7) and gradually played a more important role in directly cooling the SST, as indicated in the Niño3.4 region (Fig. 8, Qw + Qzz, blue line).

    Figure 8.  Time series of the mixed-layer heat budget and optimum interpolation (OI) SSTA in the Niño3.4 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 (QnetQpen + 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.

6.   Summary and discussion
  • The reanalysis products from ERA5 and GODAS are used to describe and understand the processes leading to the second-year cooling of the 2017/18 La Niña event. We found that thermal anomalies originating at depth from the eastern tropical Pacific could have been responsible for initiating and sustaining negative SSTAs in the equatorial Pacific.

    A sequence of events is described that led to the second-year cooling in the 2017/18 La Niña 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 Niña 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. 4eh), which contributed to the development of the second-year cooling of the La Niña 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. 7bd). 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 Niña event? Compared with the 2010/12 La Niña 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 Niña event; however, cold waters persisted in the subsurface during early 2017. The break-off of the 2017 La Niña 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 Niña 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 Niña event (Fig. 9), with divergent wind stress anomalies in the eastern Pacific from July 2017.

    Figure 9.  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 https://www.cpc.ncep.noaa.gov/products/GODAS.

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