1. Introduction
El Niño–Southern Oscillation (ENSO) is an oscillatory mode of the coupled atmosphere–ocean system that provides a major source of interannual climate variability and influences the global climate system (Philander 1985; Jin 1996; Wang et al. 2017). Extreme El Niño events, which are characterized by exceptional warming in the central-eastern tropical Pacific, can disrupt global weather patterns and can cause much destruction to society from catastrophic floods, extreme droughts, disappearance of marine life, and large financial loss (Philander 1983; Valle et al. 1987; Huang et al. 2000; Jimenez-Munoz et al. 2016). Global warming is causing extreme El Niño events to occur with increasing frequency (Cai et al. 2014; L. Chen et al. 2015; Chen et al. 2017b). Thus, investigating the underlying physical mechanisms of extreme El Niño events is of great importance to the global climate and society.
Extreme El Niño events can be triggered by low-frequency deterministic processes and high-frequency stochastic forcings (Wang and Wang 2021). The first includes the intrinsic nonlinear dynamic heating in the far eastern tropical Pacific (Jin et al. 2003) and zonal advection feedback in the central-eastern tropical Pacific (Kim and Cai 2014), and the latter includes westerly wind bursts (WWBs) (D. Chen et al. 2015; Peng et al. 2020). The WWBs over the western-central Pacific play a key role in ENSO dynamics, leading to strong zonal currents and eastward downwelling Kelvin waves that eventually cause warming in the central-eastern tropical Pacific (McPhaden 1999; Fedorov and Philander 2000; Vecchi and Harrison 2000; McPhaden 2004; Eisenman et al. 2005; Nakamura et al. 2006; Jin et al. 2007; Lian et al. 2014; D. Chen et al. 2015; Fedorov et al. 2015; Peng et al. 2019). Several studies have indicated that strong WWBs are responsible for the genesis of the 2015/16 extreme El Niño event (S. Chen et al. 2016; Chen et al. 2017a; Ren et al. 2017). Lian et al. (2017) compared the roles of equatorial upper ocean heat content and WWBs in the generation and development of three extreme El Niño events. They found that a large anomaly in the former was dominant in the 1982/83 El Niño event and the latter contributed to the 2015/16 event, while both were important in the 1997/98 El Niño event. Yu and Fedorov (2020) investigated the relative role of seasonal ocean initial heat recharge and WWBs in the developing years of three extreme El Niño events and found that midyear WWBs played a critical role in the development of the El Niño events.
The studies above showed that congregated WWBs can give rise to extreme El Niño events. Therefore, it is of great significance to understand the sources of WWBs. Previous studies have found many sources of WWBs, such as cold surges, equatorial Rossby waves, the Madden–Julian oscillation (MJO), and tropical cyclones (TCs). The East Asian cold surge passing through the Philippine Sea could contribute to strong equatorial surface westerly anomalies, and thus efficiently trigger WWBs and El Niño events (Li 1990; Feng et al. 2022). Puy et al. (2016) indicated that most WWBs are associated with convectively coupled Rossby waves and the MJO. Many studies emphasized the role of the MJO in WWBs (McPhaden 1999; Seiki and Takayabu 2007b; Puy et al. 2016; Liang and Fedorov 2021). Feng and Lian (2018) found that anomalous westerly winds usually prevail in and west of the center of convective MJOs, which could provide favorable conditions for the generation of WWBs. Moreover, Liang and Fedorov (2021) recently examined the sources of WWBs during the El Niño onset. They suggested that the MJO convective activity in the Southern Hemisphere moves to the equator under the impacts of a warming anomaly over the central-western equatorial Pacific with westerly anomalies to its west. As a result, approximately 74% of WWBs are triggered by the MJO together with the embedded TCs from December to April. TCs are usually considered to be one of the sources of WWBs over the west-central equatorial Pacific (Keen 1982; Harrison and Giese 1991; Ferreira et al. 1996; Sobel and Camargo 2005; Lian et al. 2018, 2019). However, TC activity is greatly associated with the MJO (Liebmann et al. 1994; Camargo et al. 2009; Lian et al. 2018). Seiki and Takayabu (2007a) discussed how the MJO creates a favorable environment for TCs and therefore generates WWBs. Although TC activity and WWBs may result from the MJO, this study focuses on the roles TCs play in WWBs since approximately 69% of WWBs are closely associated with TCs in the western tropical Pacific (Lian et al. 2018), and TCs could provide significant cross-scale feedback to ENSO (Wang et al. 2019).
Several studies have revealed the impact of TCs on El Niño events in recent years. TCs can sharply increase equatorial surface westerlies and warm the sea surface near and east of the international date line on a short time scale of one or two weeks; the accumulated cyclone energy (ACE) in the western North Pacific (WNP) in summer and autumn appears to lead ENSO indices by approximately 6 months (Sobel and Camargo 2005). Wang et al. (2019) indicated that ACE at 10°–20°N and 135°–170°E leads the Niño-3 index by approximately 3 months. By using an intermediate ocean–atmosphere coupled model, Lian et al. (2019) found that simulated ENSO approaches reality more closely in terms of asymmetry and diversity with TC-related wind stresses added to the model, with the magnitude largely depending on the number and duration of TCs. They indicated that TC activity in the WNP, including more frequent genesis, longer duration, and tracks close to the equator, appears to subsequently excite a stronger El Niño event mainly through thermocline feedback, Ekman feedback, and zonal advection feedback. Wang et al. (2019) recognized that WNP TCs in July–September could significantly weaken Walker circulation, raise the thermocline in the western tropical Pacific, and excite downwelling Kelvin waves carrying warm water eastward. These processes further deepen the thermocline in the eastern tropical Pacific, thereby leading to an intensified El Niño in October–December. In addition, they also found that El Niño appears to be stronger with greater WNP ACE, and ENSO intensity can be better forecasted with a new physics-based empirical model that combines both the WNP ACE and Niño-3.4 sea surface temperature (SST). However, the specific relationship between WNP TCs and extreme El Niño events is still unknown.
In this study, a novel dynamic mechanism for the onset and evolution of extreme El Niño events is investigated by using observational and reanalysis data and a coupled model. The study focuses on strong March–May (MAM) and June–August (JJA) TCs in the WNP and prominent SST anomalies in the eastern tropical Pacific and aims to discover the interactions between TC activity and extreme El Niño events. The rest of this paper is arranged as follows. Section 2 describes the data and methods used in this study. Section 3 analyzes the interactions between the WNP TCs and extreme El Niño events during MAM and JJA. Several experiments are conducted by using a coupled model to verify the dynamic mechanism in section 4. The conclusions and discussion are presented in section 5.
2. Data and methods
The analyses in this study use different observational and reanalysis datasets extending from 1979 to 2016. Monthly and daily winds, monthly relative humidity, and monthly absolute vorticity come from the 0.5° × 0.5° resolution European Centre for Medium-Range Weather Forecasts (ECMWF) interim dataset (ERA-Interim; Dee et al. 2011), and monthly sea temperature is from the EN4.2.1 analyses provided by the Met Office Hadley Centre (Good et al. 2013). The best track dataset used here is from the U.S. Joint Typhoon Warning Center (JTWC) for the 1979–2016 period. The dataset includes the location (longitude and latitude) and intensity (maximum wind, minimum sea level pressure, and radius of maximum wind) at 6-h intervals for each recorded TC.
El Niño, based on observations, is defined as an event during which the 3-month running mean of the Niño-3 index is greater than 0.5°C for at least five successive months in boreal autumn and winter. The Niño-3 index is defined as the average SST anomaly within the Niño-3 region (150°–90°W, and 5°S–5°N). Based on the El Niño definition, extreme El Niño, based on observations, is defined as an event with a peak of the Niño-3 index greater than 2°C, and moderate El Niño is defined as an event with peak Niño-3 index values ranging from 0.5° to 2°C. ACE is defined as 10−4 times the sum of the square of the estimated 6-hourly surface maximum wind (in m s−1) for all TCs occurring in the WNP:
In this study, the global coupled Community Earth System Model (Hurrell et al. 2013), version 1.1.2 (CESM1.2.2), is used to verify the dynamic mechanism of the interactions between TCs and extreme El Niño events. The CESM, released by the National Center for Atmospheric Research (NCAR), combines seven modules: atmosphere, ocean, land, runoff, sea ice, land ice, and ocean waves. The atmosphere component used here is CAM4, with POP2 for the ocean module. The horizontal resolution of the model is set at f09_g16, with atmospheric and oceanic grids at 0.9° × 1.25° and 1° × 1°, respectively. The designs and results of the model experiments are introduced in detail in section 4.
3. Interactions between TCs and extreme El Niño events
Lag correlations between the Niño-3 index and 3-month running ACE anomaly in the WNP after removing the effect of ENSO in the previous winter. Colors indicate the corresponding months of lagged Niño-3. Diagonals mark the coefficients exceeding the 95% confidence level. The (0) and (1) indicate developing and decaying years of El Niño events, respectively.
Citation: Journal of Climate 36, 8; 10.1175/JCLI-D-21-1014.1
Scatter diagram of the standardized (a) MAM and (b) JJA ACE in the WNP from JTWC after removing the effect of ENSO in the previous winter and the following DJF Niño-3 index from EN4.2.1. Colored numbers mark extreme El Niño events. Colored lines are the fitted lines. RG is the regression coefficient.
Citation: Journal of Climate 36, 8; 10.1175/JCLI-D-21-1014.1
Although the relationships of ENSO with TC genesis and duration in developing spring and summer are significant, there is clear inconsistency for the three extreme El Niño events (Figs. S1 and S2 in the online supplemental material), which is different from the performances of ACE (Fig. 2). Therefore, the present study analyzes ACE instead of other indices describing TC activity.
The remarkable results in Fig. 2 show that, except for a moderate El Niño (2004/05), three extreme El Niño events (1982/83, 1997/98, and 2015/16) were all accompanied by a stronger MAM and JJA ACE (with standardized values greater than 1.0). For the 1987/88 and 1991/92 El Niño events, stronger ACE anomalies could be found only in boreal spring (1991/92 El Niño) or summer (1987/88 El Niño). It seems that the stronger TC activities in the WNP during both spring and summer were favorable for the development of extreme El Niño events. However, the 2004/05 El Niño did not grow into an extreme event with stronger WNP ACE anomalies in spring–summer as in the three extreme El Niño events. We will discuss the 2004/05 El Niño event in more detail later.
Except for the intensity of SST anomalies, the distinct difference between extreme El Niño events and moderate El Niño events is that the former usually appears earlier than the latter (L. Chen et al. 2016; Takahashi and Dewitte 2016; Xu et al. 2020; Wang and Wang 2021). From the composite analysis, the Niño-3 index of extreme El Niño events exceeds 0.5°C in May, which is earlier than that of moderate El Niño events in October (Fig. 3). Given the stronger WNP TC activities in spring, it is assumed that the extreme El Niño events could be triggered by these TC activities and could be intensified with TC activity in summer. In the following section, the relationships between the WNP TC activity and three extreme El Niño events in spring and summer are examined.
Evolution of the Niño-3 index (°C) in the developing year (0) and decaying year (1) of extreme El Niño events (blue) and moderate El Niño events (red) from EN4.2.1. Shading represents one standard deviation.
Citation: Journal of Climate 36, 8; 10.1175/JCLI-D-21-1014.1
a. Spring: TC activity triggers earlier warming of extreme El Niño events
It is well known that TC activity can sharply increase westerly winds over the western tropical Pacific for a few days (Camargo and Sobel 2005). Due to the influence of TCs, strong westerly winds could appear in the WNP during boreal spring. TC-induced winds are calculated by Eqs. (1) and (2). The circular tangential wind fields of each TC on a 0.5° × 0.5° grid for each 6-h record during the developing spring of extreme El Niño events are first calculated, and then the daily and monthly averages of TC-induced tangential winds are calculated. Here, Fig. 4 only shows the westerly winds (above 2.0 m s−1) of the monthly tangential wind in the developing spring of the three extreme El Niño events. It is noted that the cold wake, which represents the cooling SST anomalies after the TCs pass, may contribute to the changes of wind in the western tropical Pacific (Sobel and Camargo 2005; Lian et al. 2019). Kessler and Kleeman (2000) indicated that this cold wake contributes to Bjerknes feedback. However, these winds associated with cold wakes cannot be calculated by Eqs. (1) and (2) and are not of concern here.
Monthly TC-induced westerly winds calculated by Eqs. (1) and (2) (vectors; m s−1) and TC tracks (colored lines) in the WNP in the developing spring of extreme El Niño events. Only values greater than 2 m s−1 are plotted.
Citation: Journal of Climate 36, 8; 10.1175/JCLI-D-21-1014.1
In the 1982/83 and 1997/98 El Niño events (Fig. 4), the westerly winds were located mostly south of 10°N, with an irregular longitude corresponding to the track of each TC. The westerly winds mainly occurred in March during the 1982/83 El Niño event, with a duration of 18 days. Here, duration represents the maximum number of days with TC-induced westerly winds occurring over the WNP. For the 1997/98 El Niño event, the westerly winds were strong in both April and May, with durations of 17 days and 15 days, respectively. In the 2015/16 El Niño event, there were westerly winds in almost the entire western tropical Pacific, with long durations of 16 days and 17 days in March and May, respectively. To better understand the durations of TC-induced westerly winds over equatorial regions (0°–10°N, 130°E–180°), a probability density function of the westerly wind lifetime during the developing spring of extreme El Niño events is calculated. The 6-h TC-induced winds are first calculated by Eqs. (1) and (2). The components of westerly winds are chosen, and the daily average westerly winds are given. Finally, the probability density of the longest duration (in days) of these pointwise westerly winds is calculated. Additionally, the cumulative probability of lifetimes greater than 5 days is calculated for each month. For the 1982/83 El Niño event, TC-induced westerly winds in March were stronger than those in the other two months. Of all TC-induced westerly winds over 2.0 m s−1 in March, 83.6% lasted longer than 5 days. In the other two months, the proportion was zero and 31%, respectively. In the 1997/98 El Niño event, TC-induced westerly winds with durations longer than 5 days accounted for large proportions, 91.4% and 77.9%, in April and May, respectively. There were no TC-induced westerly winds in March, as no TC occurred in March. During the developing spring of the 2015/16 El Niño event, relatively large proportions of westerly winds with long durations occurred in March and May, whose percentages were 83.8% and 94.5%, respectively. In April, 42.3% of the westerly winds over 2.0 m s−1 lasted longer than 5 days, with a maximum duration of 7 days. Generally, this illustrates that TC activity over the WNP can generate strong and long-duration westerly winds during boreal spring of all extreme El Niño events.
Westerly winds can develop into a WWB event with a maximum speed exceeding 7.0 m s−1, an anomalous speed of at least 2.0 m s−1, and a duration of 5–30 days (Harrison and Vecchi 1997). WWB events are regarded as an important trigger of El Niño events (Moore and Kleeman 1999; Thompson and Battisti 2000; Kessler 2002; Lengaigne et al. 2004). Thus, WWBs associated with TC-induced westerly winds are further analyzed. According to Harrison and Vecchi (1997) and Liang and Fedorov (2021), the WWBs are identified based on the following four criteria: 1) the maximum surface zonal wind between 0° and 5°N is stronger than the 7 m s−1 threshold; 2) the average surface zonal wind anomalies between 0° and 5°N are stronger than the 2 m s−1 threshold; 3) the first two criteria are met for at least 5 days with a zonal extent of at least 5° of longitude; and 4) two WWBs that are identified by the first three criteria and are separated by less than 3° of longitude and 3 days are considered as one WWB.
Figure 5 shows the maximum surface zonal wind between 0° and 5°N during the developing spring of extreme El Niño events and all identified WWBs. Here, TC-related WWBs are those WWBs in which the average surface TC-induced westerlies between 0° and 5°N are stronger than the 2 m s−1 threshold. In the developing spring of the 1982/83 El Niño event (Fig. 5a), two significant WWBs occurred in late March, both of which were associated with TCs (the TC-associated part lasted for a total of 18 days). The average TC-induced westerly wind speed in these two WWBs was as high as 6.58 m s−1. It is noted that there was another WWB in May that occurred without a WNP TC influence. As we will show in the discussion part, this WWB was actually generated by the MJO and embedded TCs in the Southern Hemisphere; the role of the MJO in the other two extreme El Niño events will also be discussed. Figure 5b shows three significant WWBs over the WNP during the developing spring of the 1997/98 El Niño event, two of which were in control of WNP TCs. The duration and average wind speed of TC-related WWBs were 23 days and 5.23 m s−1, respectively (raw wind speed: 7.93 m s−1). Here, the average wind speed of TC-related WWBs was an anomaly induced by TCs and the raw wind speed was the total anomaly. In the 2015/16 El Niño event (Fig. 5c), two significant WWBs occurred over the western tropical Pacific during boreal spring, both of which were associated with TCs. The total duration and average TC wind speed of TC-related parts were 26 days and 5.65 m s−1, respectively (raw wind speed: 7.71 m s−1). In Fig. 5, it is suggested that WWBs are mostly associated with WNP TCs in terms of both duration and intensity, which could facilitate the rapid growth of the warming anomaly in the eastern tropical Pacific.
Time–longitude Hovmöller diagram (along 0°–5°N) of maximum zonal wind anomalies (shading; m s−1) during the developing spring of extreme El Niño events from ERA-Interim. Grids mark all WWBs that occurred in 0°–5°N, with purple semitransparent areas indicating TC-related WWBs due to TC-induced westerly winds.
Citation: Journal of Climate 36, 8; 10.1175/JCLI-D-21-1014.1
To reveal the contributions of spring TCs to the earlier warm SST anomalies of extreme El Niño events and the associated physical mechanism, the lag-regressed SST and SSH anomalies against the WNP ACE in spring (MAM) are calculated and compared with composite SST anomalies during extreme El Niño events. Figure 6a shows the lag regression of the tropical Pacific SST anomalies on the MAM ACE in the WNP. The strengthening of MAM TCs could give rise to sea surface warming (0.9°–1.2°C) in the central-eastern tropical Pacific in boreal summer (Fig. 6a), which accounts for approximately 2/3 of the composite SST anomalies of extreme El Niño events (Fig. 6b). This indicates that TCs are one of the contributors to surface warming in the eastern tropical Pacific in boreal summer during extreme El Niño events. In addition to warm SST anomalies, warm subsurface sea temperature anomalies regressed by the MAM ACE are seen in the central and eastern tropical Pacific during the developing summer (Fig. 6c). The east–west tilted thermocline in the tropical Pacific is thus changed and the thermocline in the central-eastern tropical Pacific is deeper, which is favorable for the development of extreme El Niño events. Such TC-induced anomalous warm SST in the central-eastern tropical Pacific in summer results from downwelling Kelvin waves (Fig. 6d). The TC-induced positive SSH anomalies in the western tropical Pacific in spring could propagate to the central and eastern tropical Pacific within 3–4 months.
(a) Lag-regressed SST anomalies (averaged over 5°S–5°N) against the MAM ACE, composited for the three extreme El Niño events. (b) Composite evolution of SST anomalies averaged over 5°S–5°N during developing years of extreme El Niño events. (c) Regressed upper sea temperature averaged over 5°S–5°N in boreal summer against the MAM ACE, composited for the three extreme El Niño events. (d) As in (a), but for SSH anomalies. All values are greater than the 95% confidence interval based on Student’s t test.
Citation: Journal of Climate 36, 8; 10.1175/JCLI-D-21-1014.1
b. Summer: Interactions between developing El Niño and TC activity
Numerous studies have revealed that El Niño events greatly influence the variability of TCs, including their intensity, frequency, and lifetime (Chan 1985, 2000; Chia and Ropelewski 2002; Webster et al. 2005; Camargo et al. 2007; Zhan et al. 2011; Li and Zhou 2012; Wang and Wang 2013; Jin et al. 2014; Wang et al. 2014). TCs appear to be more intense and longer-lived in El Niño years than in La Niña years; ENSO strongly modulates TCs on interannual time scales, as shown by the significant and positive correlation between ACE and ENSO indices (Camargo and Sobel 2005). Wang and Chan (2002) found that the background low-level vorticity increases in the southeastern quadrant of the WNP during El Niño years, helping moisture to converge and TCs to spin up. As a result, the frequency of TCs increases remarkably during summer and fall in El Niño years, and the positions of TC genesis in the WNP present a southeastward shift during El Niño years. Chan (2008) also showed that more TCs are generated over the southeastern quadrant, with a longer duration and a stronger intensity during El Niño years. Patricola et al. (2018) indicated that TCs over the WNP tend to be enhanced more effectively by the central Pacific El Niño than the canonical one in regard to ACE and frequency. Wu et al. (2018) found that TC activities over the WNP show stronger sensitivity to the intensity of central Pacific El Niño and extreme El Niño events.
With the impacts of MAM TCs over the WNP, the anomalous SST rapidly increases in the eastern tropical Pacific, explaining the Niño-3 index exceeding 0.5°C in the earlier summer of extreme El Niño events (Fig. 3). These warm SST anomalies in the eastern tropical Pacific could lead to moisture convergence (Fig. 7a) accompanying positive lower-level absolute vorticity anomalies (Fig. 7b) in the southeastern quadrant of the WNP in boreal summer, which influences TC activities, as suggested by the above studies. Compared to moderate El Niño events, the atmospheric environment during extreme El Niño events is more favorable for the generation and intensification of TCs due to higher relative humidity and absolute vorticity in the southeastern quadrant of the WNP (Figs. S4 and S5). The summer TC activities in terms of genesis, duration, and ACE in the southeastern quadrant of the WNP during extreme El Niño events are shown and compared with moderate El Niño events in Fig. 8. TC activities during extreme El Niño events were clearly higher than those during moderate El Niño events. The ACE anomaly was 1.32, 2.02, and 2.23 for the 1982/83, 1997/98, and 2015/16 El Niño events, respectively. The composite ACE anomaly during moderate El Niño events was 0.49, which is negligible compared to that of extreme events. The TC genesis anomalies of the 1982/83 El Niño event (0.95) and 2015/16 El Niño event (1.51) were superior to those of the 1997/98 El Niño event (0.52) and others (0.35). The TC duration anomalies were 0.71, 2.66, and 1.90 for the 1982/83, 1997/98, and 2015/16 El Niño events, respectively. The composite duration anomaly, 0.28, during moderate El Niño was relatively shorter. The earlier warm SST anomalies in the eastern tropical Pacific resulting from TCs in the preceding spring could in turn enhance TC activities during the summer of extreme El Niño events.
Composite (a) 500-hPa relative humidity and (b) 850-hPa absolute vorticity (s−1) in the developing summer of El Niño events. Dotted areas show anomalies greater than the 95% confidence interval.
Citation: Journal of Climate 36, 8; 10.1175/JCLI-D-21-1014.1
Histogram of the standardized ACE anomaly, TC genesis anomaly, and TC duration anomaly in the developing summer of extreme (composite and individual) and moderate (composite) El Niño events. The dashed line indicates 0.8 standard deviations. Here, the anomalies of ACE, genesis and duration indicate the differences with the climatology of TC ACE, genesis, and duration, respectively.
Citation: Journal of Climate 36, 8; 10.1175/JCLI-D-21-1014.1
These enhanced WNP TC activities in summer could result in WWBs, as in spring. Figure 9 presents all WWBs during the developing summer of the three extreme El Niño events, with TC-related WWBs colored. More than half of the WWBs were associated with TCs in the 1982/83 and 1997/98 El Niño events. The duration and TC-induced westerly wind speed of TC-related WWBs in the developing summer of the 1982/83 El Niño event were 39 days and 4.61 m s−1 (raw wind speed: 7.42 m s−1), respectively. In the developing summer of the 1997/98 El Niño event, 52 days were covered with TC-related WWBs with an average TC wind speed of 3.69 m s−1 (raw wind speed: 7.06 m s−1). For the 2015/16 El Niño event, approximately half of the WWBs were associated with TCs. TC-related WWBs had a total duration of 28 days and a TC wind speed of 4.60 m s−1 (raw wind speed: 7.47 m s−1). It is clear that the enhancement of TC activity due to earlier warming of extreme El Niño events could induce the generation and development of WWBs accordingly during boreal summer, which would be further helpful for increasing SST anomalies in the eastern tropical Pacific as in spring. This indicates that the intensity of SST anomalies in the eastern tropical Pacific during summer could be partly contributed by TC-related WWBs, which work together with Bjerknes feedback (Bjerknes 1969).
Time–longitude Hovmöller diagram (along 0°–5°N) of maximum zonal wind anomalies (shading; m s−1) during developing summers of extreme El Niño events from ERA-Interim. Grids mark all WWBs that occurred at 0°–5°N, with purple semitransparent areas indicating TC-related WWBs due to TC-induced westerly winds.
Citation: Journal of Climate 36, 8; 10.1175/JCLI-D-21-1014.1
In addition to the three extreme El Niño events, Fig. 2 shows that ACE of TCs in the WNP was stronger in several moderate El Niño events, that is, in the developing summer of the 1987/88 and 2004/05 El Niño events and in the developing spring of the 1991/92 and 2004/05 El Niño events. In the developing spring of the 1987/88 El Niño event, TC-induced westerly winds only occurred in April and lasted for 13 days, which was distinct from those in extreme El Niño events in terms of intensity and duration (Figs. 4 and 5). The TC-induced westerly winds during the developing spring of the 1991/92 and 2004/05 El Niño events were significant and lasted longer than 5 days. However, most locations of westerly winds and WWBs in moderate El Niño events were west of 150°E (Figs. S6 and S7), which were different from those in extreme El Niño events (Figs. 4 and 5). The westward-displaced westerlies and WWBs may result from TC genesis located west of 150°E (Fig. S6) and the strong anomalous easterlies in the eastern and central tropical Pacific (Fig. S7). In the developing spring and summer of the 1987/88 El Niño event, three WWBs occurred, two of which were independent of TCs. For the 1991/92 El Niño event, only one prominent WWB induced by a TC appeared during spring and summer. That is, although the WNP ACEs were stronger during the 1987/88 and 1991/92 El Niño events, the WWBs, especially the TC-induced WWBs in terms of number, intensity, and durations, were not comparable with those during extreme El Niño events (Figs. 5 and 9). Different from the 1987/88 and 1991/92 El Niño events, TC-induced WWBs were prominent during the developing spring and summer of the 2004/05 El Niño event, which were similar to those in extreme El Niño events (Figs. 5 and 9). However, the strong easterly wind lasted to approximately 160°E–180° in spring and summer of 2004, which limited the development of the El Niño event. Therefore, the 1987/88, 1991/92, and 2004/05 El Niño events failed to develop into extreme events even with strong spring or summer TC activities.
4. Simulated roles of TC activity on extreme El Niño events
As mentioned above, strong TCs over the WNP during boreal spring facilitate the generation and development of El Niño events earlier. With the favorable conditions during El Niño events, TCs are significantly strengthened during boreal summer, and could in turn intensify El Niño events as in spring. CESM is used here to verify these interactions between the WNP TC activity and El Niño events. Similar to observations, El Niño events in model simulations are defined as events during which the 3-month running mean of the Niño-3 index is greater than one standard deviation of the simulated Niño-3 index (0.45°C) for at least 5 successive months in boreal autumn and winter. Here, extreme El Niño events are events with a peak of the Niño-3 index exceeding four standard deviations of the simulated Niño-3 index (1.8°C), and moderate El Niño events are events with Niño-3 index values ranging from one to four standard deviations (0.45°–1.8°C).
Three sets of experiments are conducted in this study. The first is the control run (Ctrl run), which runs for 200 years to reach climatological equilibrium and then runs for 100 more years for analysis. Simulated El Niño events are similar to the observations in terms of frequency and magnitude (Fig. S8). However, the intensity of extreme events is slightly weaker than the observations. Simulated El Niño events are also similar to the observations in terms of persistence and seasonality. However, there is no difference in the onset of the extreme and moderate events in the model (both start in June), which may result from the absence of TCs in the model (Fig. S9). In general, the model could reproduce ENSO events in terms of magnitude, persistence, and seasonality. Ten moderate El Niño events occurred in the last 100 years of the Ctrl run. The second set of experiments (Spring-TC run) is designed to evaluate the impacts of MAM TCs on El Niño events via TC-induced westerlies. Here, each selected moderate El Niño event restarts from the developing January and runs to the decaying February. The TC-induced westerly winds from March to May (Figs. 10a–c) based on Eqs. (1) and (2) are added to the forcing field to the ocean, with a random start date and a random duration of 10–15 days. Ten members are conducted for each moderate El Niño event, and thus, the total 100-member ensemble mean is examined. Figure S10 shows the surface wind anomaly composite in the selected 10 cases from the Ctrl run and the Spring-TC run as well as the observed wind anomaly composite in extreme El Niño events during spring. Compared with the observations, the westerly anomalies in the western tropical Pacific in the Ctrl run are weaker and shift westward west of 160°E (Figs. S10a,c). However, the westerly anomalies in the western tropical Pacific in the Spring-TC run simulations are similar to the observations in terms of intensity and location.
(a)–(c) TC-induced westerlies (vectors) in boreal spring of extreme El Niño events in the WNP averaged over the period for which TC-induced westerlies exist. (d)–(f) Regression of TC-induced westerlies (vectors) in boreal summer of extreme El Niño events in the WNP against the JJA Niño-3 index. Shading denotes wind speed values. All values are greater than the 95% confidence interval.
Citation: Journal of Climate 36, 8; 10.1175/JCLI-D-21-1014.1
The third set of experiments (Summer-TC run) is used to examine the interaction between the JJA TCs and El Niño. The experiments are restarted in the developing June of each Spring-TC run and end in the decaying February. Here, the expected forcings of the Summer-TC run include the TC-induced winds during June and August in the Spring-TC run, which results from the anomalous SST warming in the eastern tropical Pacific. Figure 11 shows that the model could reproduce the positive 500-hPa relative humidity and 850-hPa absolute vorticity anomalies in the southeastern quadrant of the WNP during the developing summer, which is similar to the observations (Fig. 7) and may favor the generation and intensification of the WNP TCs. However, the TCs cannot be captured one by one due to low spatial resolution and long temporal resolution in the CESM simulation experiments. Therefore, the regressed TC-induced westerly winds against the JJA Niño-3 index from the observations are added to force the model during June to August in the Summer-TC run, with a random start date and a random duration of 10–15 days, as the Spring-TC run (Figs. 10d–f). Moreover, to investigate whether the model experiments could have TCs internally, Fig. S11 shows the differences in the TC genesis potential index (GPI) of the Ctrl run with the Spring-TC and Summer-TC runs. The formulation of the GPI is as follows (Emanuel and Nolan 2004):
Composite simulated (a) 500-hPa relative humidity and (b) 850-hPa absolute vorticity (s−1) in the developing summer of all El Niño events in the Ctrl run. Dotted areas show anomalies greater than the 95% confidence interval.
Citation: Journal of Climate 36, 8; 10.1175/JCLI-D-21-1014.1
Figure 12 presents the evolution of the simulated Niño-3 index for each case. In the Spring-TC run, the ensemble mean of Niño-3 indices for all 10 cases shows a prominent increase from the developing summer in comparison to those in the Crtl run, indicating that strong TCs in the WNP during boreal spring lead to an enhanced El Niño event in summer (Fig. 12a). However, these cases do not grow into an extreme event in the next autumn and winter. Table 1 shows that less than half (38%) of the 100 runs produce extreme El Niño events in the Spring-TC run. This indicates that having only MAM TCs in the WNP is not enough for the appearance of extreme El Niño events. Different from those in the Spring-TC run, the ensemble-mean El Niño develops into an extreme event in each case in the Summer-TC run, characterized by a peak Niño-3 index greater than 2°C in the developing autumn and winter (Fig. 12b; red lines). From Table 1, 94% of the experiments in the Summer-TC run can simulate an extreme El Niño event, indicating that the enhanced TCs in spring and resulting TCs in summer work together to strengthen an El Niño event into an extreme event.
Evolution of the simulated Niño-3 index (°C) of the (a) Spring-TC run and (b) Summer-TC run from developing summer to winter for 10 cases. Markers indicate the ensemble mean of the Niño-3 index of 10 runs of each case. Black and red lines denote the ensemble mean of the Niño-3 index of 10 cases in the Crtl run and two sensitivity experiments, respectively. Shading indicates one standard deviation.
Citation: Journal of Climate 36, 8; 10.1175/JCLI-D-21-1014.1
Statistics of the number of extreme El Niño events in two sets of sensitivity experiments.
These model results show the interaction between TCs and extreme El Niño events. According to the differences between the Spring-TC run and Ctrl run, the forcing of TC-induced westerly winds in boreal spring leads to strong westerly wind anomalies in the western tropical Pacific (Fig. 13a). These anomalous westerlies could induce prominent eastward downwelling Kelvin waves, which reach the eastern tropical Pacific in summer and thus facilitate the growth of El Niño events characterized by a significant warm SST anomaly in boreal summer. The influences of the TCs clearly weaken after summer, while the Bjerknes feedback begins to work with warm SST anomalies in the eastern tropical Pacific accompanied by significant westerly anomalies in the tropical Pacific. Although the intensity of El Niño events continues to enhance during autumn and winter via Bjerknes feedback, extreme events do not occur (Figs. 12a and 13a).
Time–longitude Hovmöller diagram (along 5°S–5°N) of differences in average zonal wind anomalies (vectors; m s−1), SSH anomalies (shadings; cm), and SST anomalies (contour lines; °C) between the (a) Spring-TC run and Ctrl run, as well as between the (b) Summer-TC run and Spring-TC run. Dots mark SSH anomalies greater than the 95% confidence interval. For wind and SST anomalies, only values greater than the 95% confidence interval are plotted.
Citation: Journal of Climate 36, 8; 10.1175/JCLI-D-21-1014.1
Once westerly winds induced by the TC associated with the El Niño event in summer are used to force the model in the Summer-TC run, an eastward downwelling Kelvin wave is simulated again as that in the Spring-run and thus results in the warmer SST anomalies in the eastern tropical Pacific in autumn compared with the Spring TC-run (Fig. 13b). Coupled with the stronger zonal wind in the western tropical Pacific via Bjerknes feedback (Fig. 13b), such warmer SST anomalies could continue to develop into an extreme El Niño event in winter (Fig. 12b). Therefore, based on model results, it is suggested that the interactions of the WNP TCs in spring and summer with the SST anomalies in the eastern tropical Pacific could result in extreme El Niño events.
5. Conclusions and discussion
Several studies have revealed that TCs in summer and fall can influence subsequent El Niño events (Sobel and Camargo 2005; Wang et al. 2019). Based on the lagged relationship, the WNP ACE is significantly related to the Niño-3 index in the following months (Fig. 1). Moreover, TCs in spring can also influence the strength of El Niño events after 3 months. In particular, all three extreme El Niño events (1982/83, 1997/98, and 2015/16) were accompanied by the anomalous strong ACE in spring and summer (Fig. 2). Thus, the present study investigated how strong TCs in the WNP in boreal spring and summer are favorable for the generation and development of extreme El Niño events and revealed the important roles of interactions between TCs in the WNP and the SST anomalies in the eastern tropical Pacific.
It was found that TC-induced westerly winds are located in the western tropical Pacific in spring with long duration (Fig. 4), and several WWBs could be developed (Fig. 5). According to the observations and atmosphere–ocean coupled model experiments, it is suggested that TC-induced westerly winds in spring facilitate the prominent warming SST in the central and eastern tropical Pacific by downwelling Kelvin waves and thus lead to an earlier onset of El Niño events in summer (Figs. 14a,b).
Schematic diagram of the interactions between WNP TCs and El Niño. (a),(b) MAM TCs induce significant westerly anomalies (blue vectors) and downwelling Kelvin waves (black vectors), leading to the earlier onset of the El Niño event and anomalous Walker circulation (brown circle). (c) Enhanced relative humidity and absolute vorticity (yellow shading) occur under the influence of the weakening of Walker circulation as well as the Bjerknes feedback in the southeastern quadrant of the WNP, which can help TCs spin up. (d) Intensified TCs further enhance the SST in the central-eastern Pacific and eventually promote an extreme El Niño event.
Citation: Journal of Climate 36, 8; 10.1175/JCLI-D-21-1014.1
The resulting surface warming in the tropical Pacific then excites strong westerlies over the western tropical Pacific through Bjerknes feedback, which could enhance the intensity of the El Niño events. On the other hand, this contributes to the intensification of the WNP TC activity by increasing moisture convergence and lower-level vorticity over the southeastern quadrant of the WNP in summer (Fig. 14c). More active TCs in terms of intensity (ACE), genesis and duration could lead to strong WWBs with large extension and wind speed in the developing summer. The enhanced summer TCs in turn promote the intensity of an El Niño event in autumn and winter by exciting prominent downwelling Kelvin waves again (Fig. 14d), which is verified by the model simulations. Therefore, together with Bjerknes feedback, the interactions between TCs and the SST anomalies in the eastern tropical Pacific in spring and summer could lead to an extreme El Niño event. In general, this study revealed the interaction between TCs and extreme El Niño events: TCs in spring could trigger El Niño occurrence, while the developing El Niño in summer could be favorable for the intensification of JJA TCs in the southeastern quadrant of the WNP, which could enhance the eastern tropical Pacific warming and thus an extreme El Niño event appears.
This paper analyzes the effect of TCs on extreme El Niño events. However, several questions remain to be addressed. The future changes in extreme El Niño events with global warming are controversial. What will happen to the changes in extreme El Niño events if future changes in TC activity are considered is still an open question. In addition, the number of samples used in this study is limited and the resolution of the model is low. A high-resolution model will need to be used for subsequent studies. The present study focuses on the WNP TC-induced WWBs, while the WWBs favorable for extreme El Niño may result from TCs in the southern Pacific and MJO, that is, the WWBs in March 1997 and March 2015. As shown in Fig. 4, no TCs were observed in the WNP in March 1997, while a TC in the southern Pacific could induce westerly winds in the WNP (Fig. S3b), whose intensity was weaker than that in the northern Pacific in April and May 1997 (Figs. 4e,h). However, a strong WWB occurred in the western tropical Pacific in March 1997 (Fig. 6b). The strong WWB was associated with intense MJOs (Yu and Rienecker 1998; Hendon et al. 1999; Slingo et al. 1999; Liang and Fedorov 2021). Yu and Rienecker (1998) found that the strong WWB in March 1997 was embedded within the active phase of the MJO, but its amplitude was greatly enhanced in the western Pacific sector. They suggested that equatorial twin cyclones induced by northerly cold surges from East Asia/WNP into the tropical Pacific contributed to the local enhancement of the WWB. In March 2015, TCs in the northern Pacific and southern Pacific could induce westerly winds in the WNP, and the former westerlies were stronger than the latter (Fig. 4c and Fig. S3c). However, the WWBs in March 2015 could not be totally explained by these TCs (Fig. 6c). Lian et al. (2018) suggested that the WWBs were mainly caused by the MJO and TCs embedded in the southern Pacific. Therefore, the roles of WWBs associated with the MJO in El Niño or extreme El Niño events need to be further investigated in the near future.
Acknowledgments.
This work was supported by the National Natural Science Foundation of China (Grants 41925024 and 41876021), the Strategic Priority Research Program of Chinese Academy of Sciences (Grant XDB42000000), the Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (GML2019ZD0306), Development fund of South China Sea Institute of Oceanology of the Chinese Academy of Sciences (SCSIO202208), Innovation Academy of South China Sea Ecology and Environmental Engineering, Chinese Academy of Sciences (ISEE2021ZD01), and China-Sri Lanka Joint Center for Education and Research, Chinese Academy of Sciences. The numerical simulations are supported by the High Performance Computing Division in the South China Sea Institute of Oceanology, Chinese Academy of Sciences.
Data availability statement.
Reanalysis data used during the current study are available in the European Centre for Medium-Range Weather Forecasts (ECMWF), the Met Office Hadley Centre, and the U.S. Joint Typhoon Warning Center (JTWC). These datasets were derived from the following public domain resources: ERA-Interim, https://apps.ecmwf.int/datasets/data/interim-full-moda/levtype=sfc/; EN.4.2.1, https://www.metoffice.gov.uk/hadobs/en4/download-en4-2-1.html; best track, http://www.metoc.navy.mil/jtwc/jtwc.html?western-pacific.
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