Low-frequency wind stress forcing reduces El Niño diversity in numerical model

  • ZHANG Qi , 1 ,
  • LIAN Tao , 1, 2, 3
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  • 1. State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310000, China
  • 2. School of Oceanography, Shanghai Jiao Tong University, Shanghai 200000, China
  • 3. Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519000, China
LIAN Tao. email:

ZHANG Qi (1997—), male, master student. email:

Copy editor: YAO Yantao

Received date: 2022-02-24

  Revised date: 2022-04-08

  Online published: 2022-04-21

Supported by

National Natural Science Foundation of China(42022043)

Zhejiang Provincial Natural Science Foundation of China(LR19D060001)

Abstract

The El Niño-Southern Oscillation (ENSO) includes both low-frequency ocean-atmosphere coupling and high-frequency processes, yet the nonlinearity in ENSO dynamics prevents any quantitative estimation of the contributions of the two to ENSO development. The online low-frequency filtering technique was proposed in a recent work to exclude the high-frequency part of wind stress during ocean-atmosphere coupling in model, thus can be used to scale the impact of low-frequency ocean-atmosphere interaction on the ENSO dynamics. By comparing model simulations with and without the online low-pass filtering module, we found that removing the high-frequency wind forcing prolongs ENSO period and decreases El Niño diversity. The results confirm that the high-frequency momentum processes play a crucial role in the genesis of El Niño diversity.

Cite this article

ZHANG Qi , LIAN Tao . Low-frequency wind stress forcing reduces El Niño diversity in numerical model[J]. Journal of Tropical Oceanography, 2023 , 42(1) : 1 -9 . DOI: 10.11978/2022038

El Niño-Southern Oscillation (ENSO) is the strongest climate variability at the interannual timescales, and places significant impacts on global climate (Rasmusson et al, 1983). Understanding the underlying dynamics of ENSO is one of the hot topics in climate research. The classic ENSO theory attributes the growth of ENSO to positive feedbacks among sea surface temperature (SST), trade wind, and upwelling in the equatorial eastern Pacific (Bjerknes, 1969). To the phase transition between El Niño and La Niña, it’s proposed that the tropical upwelling Rossby wave, equatorial Kelvin wave and poleward transport of upper ocean heat content along with El Niño development are the two dominant processes (Schopf et al, 1988; Jin, 1997).
Above theories based on the low-frequency ocean-atmosphere coupling perfectly explain the growth of SST anomaly(SSTA) during ENSO developing phase, as well as the quasi-periodicity of ENSO. The spatial patterns of El Niño and La Niña predicted by these classic theories are expected to be symmetric in space with comparable magnitudes. However, the observed ENSO events exhibit strong irregularity, asymmetry, and diversity. The strength of El Niño is in general greater than the La Niña (Burgers et al, 1999), whereas the La Niña lives longer than the El Niño (Wolter et al, 2011). In addition, El Niño usually peaks inboreal winter, but this phasing locking behavior is weaker for La Niña (Galanti et al, 2000).
More importantly, the El Niño exhibits strong diversity both in magnitude and spatial distribution than the La Niña (Kug et al, 2009). All of the extreme ENSO events in history are El Niño. The El Niño events are thus can be categorized into the extreme type and the moderate type (Takahashi et al, 2011). On the other hand, although the maximum SST anomaly during the La Niña events is confined in the eastern equatorial Pacific, the center of SST anomaly during the El Niño events can be found in either the equatorial central Pacific or the eastern Pacific. Therefore, the El Niño can be also grouped into another two types according to the longitude of the maximum SST anomaly. The one with maximum warming in the eastern equatorial Pacific, as predicted by the classic ENSO theory, is called the eastern-Pacific (EP) type, whereas the one with the SST warming center near the equatorial dateline is termed the central-Pacific (CP) El Niño (Ashok et al, 2007; Kao et al, 2009). Chen et al (2015) showed that the El Niño in fact has three distinct flavors. The moderate El Niño which locates in the EP area is symmetric to La Niña, both of which contribute the regularity of ENSO. The CP and extreme El Niño are the irregular ones, and contribute to ENSO nonlinearity.
Clearly the ENSO nonlinearity cannot be explained by the classic ENSO theory. The tropical-subtropical Pacific interactions, pantropical teleconnections, and multi-scale interactions are thus proposed to supplement the low-frequency ENSO dynamics (Fang et al, 2020). In particular, previous studies showed that the strong equatorial westerlies from the synoptic to intraseasonal timescales are crucial to the genesis of El Niño diversity. For example, Yu et al (2003) found that the strong equatorial westerlies in early 1997 are originated from the East Asian cold surge in late 1996, and this westerly event is important to the onset of 1997/98 El Niño. Harrison et al (1997) pointed out that the intensity of the springtime westerly wind bursts (WWBs) in the tropical western Pacific is significantly related to El Niño strength. Chen et al (2015) indicated that almost every El Niño in history are proceeded by the WWBs, and the interplay between WWBs and ocean heat content determines the pattern and magnitude of El Niño. Sobel et al (2005) suggested that tropical cyclone in the northwestern Pacific excites strong equatorial westerlies, and the intensity of tropical cyclone significantly leads ENSO by about 5 months. Lian et al (2018) further confirmed the possible influence of tropical cyclone on ENSO using numerical experiment. Wang et al (2019) also showed that summer-autumn tropical cyclone intensity leads the upcoming El Niño by 3 months.
The aforementioned works show that ENSO is resulted from both the low-frequency ocean-atmosphere coupling and atmospheric perturbation at the synoptic scales within the tropical Pacific. However, the nonlinearity in ENSO dynamics prevents any quantitative estimation of the two to ENSO evolution. Kang et al (2000) and Syu et al (2000) constructed a statistical atmospheric model using the singular vector decomposition (SVD) between SST and surface wind. They found that the main ENSO features can be reproduced using the first two coupled modes. Nevertheless, as the SVD technique cannot restrict the spectrum of the modes explicitly, the results from Kang et al (2000) and Syu et al (2000) cannot be fully interpreted as the results of the pure low-frequency coupling. To this end, Lian et al (2021) introduced a new method named as the online low-frequent filtering method (OLF). The OLF method was designed to exclude the high-frequency part of wind stress during ocean-atmosphere coupling in model, thus can be used to scale the impact of the pure low-frequent ocean-atmosphere interaction on ENSO development. Using this new technique, Lian et al (2021) showed that the strong WWB in March 1997 is the necessary condition for the genesis of the 1997/98 extreme El Niño.
Although Lian et al (2021) validated the role of WWB in the 1997/98 El Niño event, the impact of high-frequency wind stress forcing on ENSO from the statistical point of view is lacking. In this study, we aim to estimate the influence of the pure low-frequency coupling to the development of ENSO using the OLF method. The rest of the manuscript is arranged as follows: model and method are presented in Section 2. In Section 3, we compare model simulations with and without the OLF module, and analyze the change of ENSO caused by removing high-frequency wind, followed by the conclusion and discussion in Section 4.

Model and method

The model used here is the Community Earth System Model (CESM1.2.0) of standard resolution, developed by the National Center for Atmospheric Research (Vertenstein et al, 2012). The resolution in the atmospheric component is 0.9° × 1.25°. The oceanic resolution is set as gx1v6 which is 1.0° × 1.0° with finer latitudinal resolution near the equator. The model is restarted from an equilibrium climate from a 100-year spin-up state under the present-day forcing (i.e., the B2000 Compset). Two model experiments are conducted. One is the control run (Ctrl), and the other is the run using the OLF module termed the Online run. Because the Online run needs the historical model wind stress record to calculate the averaged wind stress anomaly, as will be introduced below, we integrate each experiment for 101 years, and the results from the last 100 years are used for analysis.
The OLF method is given as follows. On each model day, the wind stress anomaly on this day is replaced by the average wind stress anomaly in the previous k days when atmosphere module transports wind stress momentum to the model coupler. The high-frequency part in wind stress is thus excluded during model coupling. As Lian et al (2021), k is set to 60 to remove perturbations with period less than 60 days, including the tropical cyclone, WWBs, and a largeportion of the MJO. Moreover, the OLF module is used only in the tropical Pacific (30°S-30°N, 100°E-70°W). Wind stress in other regions is not explicitly changed. It is worth noting that the OLF method is different from the traditional offline low-frequency filtering process which is usually used to gain the low-frequency signal in a given record. In the late case, the impacts of high-frequency processes, if has, cannot be fully removed if the impacts are nonlinear (Lian et al, 2021). Also note is that the OLF module is applied only to the wind stress field. High-frequency variability in the heat flux and freshwater flux are not considered at present.
Although the observed El Niño shows three different types (Chen et al, 2015), the CESM only reproduced two of them. One is the EP type, and the other is the CP type (Tan et al, 2020). We therefore explore the impacts of high-frequency wind forcing on El Niño diversity with regarding to their capability in reproducing the CP and EP types. As shown in Tan et al (2020), the centers of EP and CP simulated in CESM are biased westward by about 20° in longitude. Thus the model EP and CP are defined using the SST anomaly averaged in the regions 20°westward of the Niño3 and Niño4 regions, which are (5°S-5°N, 170°W-110°W) and (5°S-5°N, 140°E-170°W), respectively. An El Niño is an event with the averaged SST anomaly in either of these two regions exceeding 0.5℃ for at least 5 successive months using a 3-months running mean. An event is grouped into the EP (CP) type if the maximum SST anomaly locates in the eastern (western) box.

Results

We first compare the climatological zonal wind stress in the two experiments. As shown in Fig. 1, the trade wind in the Online run is stronger than that in the Ctrl run, especially over the equatorial western Pacific. The maximum increase of the surface wind reaches to 5 m·s-1. The increase of the trade wind implies a shoaling of equatorial thermocline and a strengthening of the thermocline feedback. By the classic ENSO theory, the intensity of the EP El Niño is expected to be enhanced (Ren et al, 2013).
Fig. 1 Climatological zonal wind stress (unit of N·m-2) in the Ctrl run(a), Online run(b), and their differences (c). The red dashed line in (c) indicates the equator
To estimate the component of the increased trade wind in the Online run, Fig. 2 presents the probability distribution function of zonal wind stress over the entire equatorial Pacific (a-c) and the western equatorial Pacific (d-f). Over the entire equatorial Pacific, the OLF decreases strong wind stress of both westerly and easterly. However, over the western equatorial Pacific, reduction is more at the westerly tail. The western equatorial region is manifested by strong MJO, WWBs, and near-equator tropical cyclone, all of which are associated with strong equatorial westerly (Feng et al, 018; Lian et al, 2018, 2019). Therefore, the results shown in Fig. 2d-2f clearly validate that the OLF method can successfully reduce high-frequency signal during model coupling.
Fig. 2 The probability distribution function of zonal wind stress over the entire equatorial Pacific (left panel) and the western equatorial Pacific (right panel) in the Ctrl run (first row), Online run (second row), and their ratios (last row)
Previous studies showed that the strong high-frequency westerlies are closely related to El Niño genesis (McPhaden et al, 1988). Given that the strong westerly tail in the Online run is reduced, it is expected that El Niño occurs less frequent in the Online run. To this end, Fig. 3 compares the time-longitude evolutions of equatorial averaged SST anomaly simulated in the two experiments. Although ENSO still exhibits quasi-periodic behavior in the absence of the high-frequency wind forcing, the period is slightly changed. The spectrums of SST anomaly averaged in the central equatorial Pacific from the two runs are given in Fig. 4. The region used is 20° westward of the Niño3.4 region, that is, (5°S-5°N, 170°E-140°W). This region is selected to represent ENSO evolution of both EP and CP types. Compared with the Ctrl run, the spectrum in the Online run shifts to the low-frequency direction, with the maximum spectrum shifts from about 2.5 years to about 2.8 years. The prolonging of ENSO period is primarily due to the fact that high-frequency westerlies in the equatorial western Pacific favor the El Niño genesis. When these westerlies are excluded in the Online run, the occurrence of El Niño is reduced, leading to a long period of ENSO in this case.
Fig. 3 Evolution of SST anomaly(unit of ℃) along the equator in the Ctrl (a) and Online (b) runs
Fig. 4 The spectrum of the averaged SST anomaly in the central equatorial Pacific. Dashed line denote 95% confidence level
The high-frequency westerlies are also closely associated with El Niño diversity (Chen et al, 2015). It is thus expected that the El Niño shows less flavors once the high-frequency wind is removed. Fig. 5 gives the composite SST anomaly in the DJF season in EP and CP years simulated in the two experiments. In the Ctrl run, the numbers of CP and EP are 8 and 30, respectively. In the Online run, the members slightly reduce to 7 and 24, respectively. The decrease of CP and EP events are consistent with the prolonged period of ENSO in the Online run, as seen in Fig. 4. In addition, the variation of SST anomaly in the cold tongue region is also reduced as compared with that in the Ctrl run. The standard deviations of SST anomaly the EP region in the Online run is 0.97°C, and is slightly smaller than that in the Ctrl run, which is 1.05°C.
Fig. 5 Composite of SST anomaly(unit of ℃) in the DJF season in the EP (first row) and CP (second row) years simulated in the Ctrl (left panel) and Online (right panel) runs. The stippled regions denote statistical significance above the 95% confidence level(Student’s t-test)
More importantly, the patterns of CP and EP are significantly changed in the Online run. In the Ctrl run, the center of EP event is right on the far eastern equatorial Pacific near 120°W, and is distant to the center of CP event (Fig.5a-5b). In the Online run, however, the maximum SST anomaly spans from the equatorial dateline to 110°W (Fig. 5c). Excluding the high-frequency wind stress clearly weakens the distinction of the CP and EP types.
Notably, the Pacific Meridional Mode (PMM) is significantly enhanced in the Online run compared to the Ctrl run (Fig. 5c, d). Observational data show that El Niño events in the past ten years have been affected by the North Pacific meridional modal activity (Chang, 2007), and the origin of the abnormally warm SST of CP event may be the subtropical region of the Northeast Pacific (Yu et al, 2010). In addition, the PMM can transmit warm anomalous signals to the CP region through the enhancement of trade winds, and CP event can also affect the intensity of the PMM by exciting atmospheric Rossby waves (Fang et al, 2020). In the Online run, the amplitude of CP event was enhanced and the extreme value range was expanded, which promoted the interaction with the PMM, resulting in the enhancement of the PMM.
To further explore the change of El Niño diversity in the Online run, Fig. 6 presents the evolutions of the composite SST anomaly from the onset to the decay phase for the two El Niño types in different experiments. As can be seen, the maximum warm SST anomaly in the EP event simulated in the Ctrl run are almost confined to the east of 140°W in the entire lifetime (Fig. 6a). To the CP event, the warming centers are mostly confined west of 160°W. Moreover, cold SST anomalies are found in the eastern equatorial Pacific during the developing and decay phases (Fig. 6b). The difference between the spatial patterns of CP and EP runs in the Ctrl run is quite clear. To the Online run, on the other hand, the maximum warm SST anomalies in the EP event are evenly distributed in longitude from the central to eastern Pacific (Fig. 6c). The maximum SST anomaly in the CP event extents eastward to 150°W at the developing and mature phases, and SST in the eastern Pacific also shows weak warm anomaly (Fig. 6d). The results further confirm that El Niño diversity weakens in the Online experiment.
Fig. 6 Evolution of the equatorial averaged SST anomaly (unit of ℃) in the EP (first row) and CP (second row) years simulated in the Ctrl (left panel) and Online (right panel) runs. The stippled regions denote statistical significance above the 95% confidence level (Student’s t-test)
Worth noting is that in the Ctrl run, the EP event is in general followed by a La Nina event (Fig. 6a). From the classic ENSO theory, the transition between El Niño and La Niña is mainly due to the strong subtropical upwelling waves caused by surface westerlies during the development of El Niño (Ohba et al, 2009). It is natural that the reduced strong westerlies in the western equatorial Pacific reduces the overall Rossby wave upwelling, and thus decreases the possibility of the upcoming La Niña in the Online run (Fig. 6c).
To investigate the underlying physical mechanism, we perform a mixed-layer heat budget analysis. For EP events, zonal advection feedback (ZAF) and thermocline feedback (TCF) in both experiments play a major role (Fig. 7a). For CP event, the ZAF term in the Ctrl run was the main contributor, while in the Online run, TCF and MMAF are the main contributors (Fig. 7b). Due to the enhanced effect of the low-frequency circulation mechanism in the Online run, the TCF in the Online run is stronger than that in the Ctrl run.
Fig. 7 Heat budget of the equatorial averaged SST anomaly in the development of EP (a) and CP (b) years simulated in the Ctrl (blue bar) and Online (orange bar) runs

Discussion and conclusion

This study explored the impacts of pure low-frequency ocean-atmosphere coupling on ENSO dynamics via using the online low-frequency filtering technique in the CESM coupled model. This technique is designed to remove the high-frequency wind stress during model coupling, thus the influences from the high-frequency perturbation can be completely excluded in the system. By comparing model simulations with and without the online low-frequency filtering module, saying, the Online and Ctrl runs, it’s found that removing the high-frequency wind forcing strengthens the trade wind. As a result, the thermocline feedback increases, leading to stronger El Niño that matures in the eastern equatorial Pacific, known as the EP El Niño type. On the other hand, removing the strong high-frequency wind stress reduces one of the potential triggers of El Niño. Therefore, the occurrence of El Niño is slightly less than that in the control run, and the period of ENSO in this case shifts to the low-frequency direction.
The absence of strong high-frequency westerlies in the equatorial western Pacific greatly affects the El Niño diversity. Previous studies suggested that El Niño diversity is associated with the atmospheric perturbation to a large extent. Here we found that the center of EP El Niño in the Online run moved westward as compared with the control run, and cannot be separated substantially from the modeled CP El Niño. These results echo well with previous works in which the strong high-frequency surface westerlies in the equatorial western Pacific are found to be crucial for the genesis of El Niño diversity.
Not only tropical high-frequency signals have an impact on the diversity of ENSO, but also subtropical signals. The charged-discharged (CD) mechanism acts to reduce El Niño diversity, while the seasonal footprint (SF) mechanism played the opposite role (Yu et al, 2018). In the Online run, the effect of high-frequency signals weakens, the effect of low-frequency cycle (such as CD mechanism) enhances, and the diversity of El Niño reduces. This result is consistent with the conclusion of Yu et al (2018). In addition, we find that the subtropical signals (such as PMM) interact with El Niño events in this study. The PMM can transmit the warm anomalous signal of the PMM to the central pacific region through the enhancement of the trade wind, and CP event can also affect the intensity of the PMM by exciting the atmospheric Rossby wave (Fang et al, 2020). This theory may explain the phenomenon of enhanced PMM signal (Fig. 5d).
Our results indicated that improving model simulation of the high-frequency wind forcing such as the near-equator tropical cyclone, MJO, and cold surge is important for reproducing the general characteristics of ENSO. The relationship between MJO and WWBs in multi-model simulations has been estimated by Feng et al (2018), which showed that most state-of-the-art climate models are incapable in simulating MJO intensify and further the ENSO diversity (Feng et al, 2020). Nevertheless, the degree of model simulations of the near-equator tropical cyclone and East Asia cold surge, as well as their associations with WWBs in the current climate models have not been estimated. It is believed that model performance in simulating these two phenomena would be related closely to modeled ENSO irregularity and nonlinearity. This issue will be addressed in future studies.
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