El Niño Southern Oscillation in a Changing Climate

M. Mcphaden, A. Santoso, W. Cai
{"title":"El Niño Southern Oscillation in a Changing Climate","authors":"M. Mcphaden, A. Santoso, W. Cai","doi":"10.1002/9781119548164","DOIUrl":null,"url":null,"abstract":"The El Niño Southern Oscillation (ENSO) is characterized by being irregular or nonperiodic and asymmetric between El Niño and La Niña with respect to amplitude, pattern, and temporal evolution. These observed features suggest the importance of nonlinear dynamics and/or stochastic forcing. Both nonlinear deterministic chaos and linear dynamics subject to stochastic forcing and/or to non‐normal growth were introduced to explain the irregularity of ENSO, but no consensus has been reached to date given the short observational record. As a dominant source of stochastic forcing, westerly wind bursts play a role in triggering, amplifying, and determining the irregularity and asymmetry of ENSO, which are best treated as part of the deterministic dynamics or as a multiplicative noise forcing. Various nonlinear processes are responsible for the spatial and temporal asymmetry of El Niño and La Niña, which includes nonlinear ocean advection, nonlinear atmosphere‐ocean coupling, state‐dependent stochastic noise, tropical instability waves, and biophysical processes. In addition to the internal nonlinear processes, a capacitor effect of the Indian and Atlantic Oceans and atmospheric and oceanic teleconnections from extratropical Pacific could also contribute to the temporal and amplitude asymmetry of ENSO. Despite significant progress, most state‐of‐the‐art models are still lacking in simulation of the spatial and temporal asymmetry of ENSO. 1 Department of Atmospheric Sciences, Yonsei University, Seoul, Republic of Korea 2 Department of Earth and Planetary Sciences and School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA 3 Institute for Geophysics, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, USA 4 Department of Atmospheric Sciences/IPRC, University of Hawai’i at Ma ̄noa, Honolulu, HI, USA 154 EL NIÑO SOUTHERN OSCILLATION IN A CHANGING CLIMATE determine an atmosphere‐ocean coupled stability for ENSO system (T. Li, 1997b; An & Jin, 2000; Fedorov & Philander, 2000), and for example, depending on the coupling strength, ENSO system becomes a self‐sustained and possibly chaotic oscillator under a strong coupling and a damped oscillator under a weak coupling (An & Jin, 2001). It has been suggested that some decades may be characterized by a self‐sustained, possibly chaotic dynamics, while others show a damped ENSO cycle, excited by stochastic variability (Kirtman & Schopf, 1998). However, a bifurcation between stable and unstable regimes tends to be ambiguous in the presence of noise (e.g., Levine & Jin, 2010). Westerly wind bursts (WWBs) are episodic reversals of the equatorial trade winds with a strength of 5 to 7 ms–1, zonal extent of 20–40 degrees, duration of 5–30 days, and frequency of around 5 to 10 times per year (Harrison & Vecchi, 1997; L. Yu et al., 2003; Seiki & Takayabu, 2007a). These events, a dominant source of stochastic forcing, play a role in triggering, amplifying, and even determining the spatial pattern of ENSO events (Harrison & Vecchi, 1997; Eisenman et al., 2005; Levine & Jin, 2010; Rong et al., 2011; D. Chen et al., 2015; Hayashi & Watanabe, 2017). WWBs were initially considered as additive stochastic forcing (e.g. Moore & Kleeman, 1999), yet it became clear that they depend on the background SST and tend to occur more frequently during a developing El Niño (Verbickas, 1998; L. Yu et al., 2003; Eisenman et al., 2005). These events are thus best treated as part of the deterministic dynamics or as a state‐dependent multiplicative noise forcing, with important implications to amplitude and predictability of El Niño events. El Niño is not a simple mirror image of its opposite phase, La Niña. El Niño’s amplitude is on average greater than that of La Niña (Deser & Wallace, 1987; Burgers & tephenson, 1999; An & Jin, 2004). El Niño is often followed by a La Niña in the following year, but the opposite is much less common (Larkin & Harrison, 2002; M. Chen et al., 2016; An & Kim, 2017). After their mature phase, many La Niñas persist through the following year, but most of El Niños tend to decay rapidly by next summer (Ohba & Ueda, 2007; Okumura & Deser, 2010; Choi et al. 2013; DiNezio & Deser, 2014; An & Kim, 2018). Strong El Niños are mainly loaded over the eastern Pacific with focusing toward the equator, whereas strong La Niñas are mostly loaded over the central Pacific with a wider latitudinal extension (Hoerling et al., 1997; Kang & Kug, 2002; Takahashi et al., 2011; Dommenget et al., 2013). Such amplitude/duration/transition/pattern asymmetries between El Niño and La Niña may not be surprising given the nonlinear internal dynamics and/or selective external impacts (e.g., An & Kim, 2018). Asymmetrical internal nonlinear processes that are responsible for amplitude asymmetry include the vertical ocean temperature profile (Zebiak & Cane, 1986), ocean nonlinear advection (An & Jin, 2004; Su et al. 2010), asymmetric equatorial wind response to SST (Kang & Kug, 2002; Frauen & Dommenget, 2010; Choi et al., 2013), ocean wave response to the wind stress (An & Kim, 2017, 2018), outcropping thermocline nonlinearity (Battisti & Hirst, 1989; Galanti et al., 2002; An & Jin, 2004), state‐dependent stochastic forcing (Jin et al., 2007; Kug et al., 2008; Rong et al., 2011; Levine et al., 2016; Hayashi & Watanabe, 2017), tropical instability wave activity (J. Yu & Liu, 2003; An, 2008a, 2008b), biophysical feedback (Timmermann & Jin, 2002), shortwave feedback (Lloyd et al., 2012), etc. Transition/duration asymmetry has been attributed to a selective capacitor effect of the Indian and Atlantic oceans (Ohba & Ueda, 2007; Okumura & Deser, 2010; An & Kim, 2018), development of subtropical western Pacific atmospheric circulation during decaying phase of ENSO to boost ENSO transition (B. Wang et al., 1999; B. Wang et al., 2001; Y. Li et al., 2007; B. Wu et al., 2010a), and some of aforementioned internal nonlinear processes (Choi et al., 2013; Im et al., 2015; M. Chen et al., 2016; An & Kim, 2017, 2018; M. Chen & Li, 2018). This chapter focuses on the irregularity of ENSO and on its amplitude and evolution asymmetries. In section 7.2, the origin of irregularity will be addressed together with the role of westerly wind burst events. Mechanisms for amplitude asymmetry will be discussed in section 7.3. The cause of evolution asymmetry will be reviewed in section 7.4, and we include conclusion and discussion in section 7.5.","PeriodicalId":12504,"journal":{"name":"Geophysical Monograph Series","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"214","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geophysical Monograph Series","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/9781119548164","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 214

Abstract

The El Niño Southern Oscillation (ENSO) is characterized by being irregular or nonperiodic and asymmetric between El Niño and La Niña with respect to amplitude, pattern, and temporal evolution. These observed features suggest the importance of nonlinear dynamics and/or stochastic forcing. Both nonlinear deterministic chaos and linear dynamics subject to stochastic forcing and/or to non‐normal growth were introduced to explain the irregularity of ENSO, but no consensus has been reached to date given the short observational record. As a dominant source of stochastic forcing, westerly wind bursts play a role in triggering, amplifying, and determining the irregularity and asymmetry of ENSO, which are best treated as part of the deterministic dynamics or as a multiplicative noise forcing. Various nonlinear processes are responsible for the spatial and temporal asymmetry of El Niño and La Niña, which includes nonlinear ocean advection, nonlinear atmosphere‐ocean coupling, state‐dependent stochastic noise, tropical instability waves, and biophysical processes. In addition to the internal nonlinear processes, a capacitor effect of the Indian and Atlantic Oceans and atmospheric and oceanic teleconnections from extratropical Pacific could also contribute to the temporal and amplitude asymmetry of ENSO. Despite significant progress, most state‐of‐the‐art models are still lacking in simulation of the spatial and temporal asymmetry of ENSO. 1 Department of Atmospheric Sciences, Yonsei University, Seoul, Republic of Korea 2 Department of Earth and Planetary Sciences and School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA 3 Institute for Geophysics, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, USA 4 Department of Atmospheric Sciences/IPRC, University of Hawai’i at Ma ̄noa, Honolulu, HI, USA 154 EL NIÑO SOUTHERN OSCILLATION IN A CHANGING CLIMATE determine an atmosphere‐ocean coupled stability for ENSO system (T. Li, 1997b; An & Jin, 2000; Fedorov & Philander, 2000), and for example, depending on the coupling strength, ENSO system becomes a self‐sustained and possibly chaotic oscillator under a strong coupling and a damped oscillator under a weak coupling (An & Jin, 2001). It has been suggested that some decades may be characterized by a self‐sustained, possibly chaotic dynamics, while others show a damped ENSO cycle, excited by stochastic variability (Kirtman & Schopf, 1998). However, a bifurcation between stable and unstable regimes tends to be ambiguous in the presence of noise (e.g., Levine & Jin, 2010). Westerly wind bursts (WWBs) are episodic reversals of the equatorial trade winds with a strength of 5 to 7 ms–1, zonal extent of 20–40 degrees, duration of 5–30 days, and frequency of around 5 to 10 times per year (Harrison & Vecchi, 1997; L. Yu et al., 2003; Seiki & Takayabu, 2007a). These events, a dominant source of stochastic forcing, play a role in triggering, amplifying, and even determining the spatial pattern of ENSO events (Harrison & Vecchi, 1997; Eisenman et al., 2005; Levine & Jin, 2010; Rong et al., 2011; D. Chen et al., 2015; Hayashi & Watanabe, 2017). WWBs were initially considered as additive stochastic forcing (e.g. Moore & Kleeman, 1999), yet it became clear that they depend on the background SST and tend to occur more frequently during a developing El Niño (Verbickas, 1998; L. Yu et al., 2003; Eisenman et al., 2005). These events are thus best treated as part of the deterministic dynamics or as a state‐dependent multiplicative noise forcing, with important implications to amplitude and predictability of El Niño events. El Niño is not a simple mirror image of its opposite phase, La Niña. El Niño’s amplitude is on average greater than that of La Niña (Deser & Wallace, 1987; Burgers & tephenson, 1999; An & Jin, 2004). El Niño is often followed by a La Niña in the following year, but the opposite is much less common (Larkin & Harrison, 2002; M. Chen et al., 2016; An & Kim, 2017). After their mature phase, many La Niñas persist through the following year, but most of El Niños tend to decay rapidly by next summer (Ohba & Ueda, 2007; Okumura & Deser, 2010; Choi et al. 2013; DiNezio & Deser, 2014; An & Kim, 2018). Strong El Niños are mainly loaded over the eastern Pacific with focusing toward the equator, whereas strong La Niñas are mostly loaded over the central Pacific with a wider latitudinal extension (Hoerling et al., 1997; Kang & Kug, 2002; Takahashi et al., 2011; Dommenget et al., 2013). Such amplitude/duration/transition/pattern asymmetries between El Niño and La Niña may not be surprising given the nonlinear internal dynamics and/or selective external impacts (e.g., An & Kim, 2018). Asymmetrical internal nonlinear processes that are responsible for amplitude asymmetry include the vertical ocean temperature profile (Zebiak & Cane, 1986), ocean nonlinear advection (An & Jin, 2004; Su et al. 2010), asymmetric equatorial wind response to SST (Kang & Kug, 2002; Frauen & Dommenget, 2010; Choi et al., 2013), ocean wave response to the wind stress (An & Kim, 2017, 2018), outcropping thermocline nonlinearity (Battisti & Hirst, 1989; Galanti et al., 2002; An & Jin, 2004), state‐dependent stochastic forcing (Jin et al., 2007; Kug et al., 2008; Rong et al., 2011; Levine et al., 2016; Hayashi & Watanabe, 2017), tropical instability wave activity (J. Yu & Liu, 2003; An, 2008a, 2008b), biophysical feedback (Timmermann & Jin, 2002), shortwave feedback (Lloyd et al., 2012), etc. Transition/duration asymmetry has been attributed to a selective capacitor effect of the Indian and Atlantic oceans (Ohba & Ueda, 2007; Okumura & Deser, 2010; An & Kim, 2018), development of subtropical western Pacific atmospheric circulation during decaying phase of ENSO to boost ENSO transition (B. Wang et al., 1999; B. Wang et al., 2001; Y. Li et al., 2007; B. Wu et al., 2010a), and some of aforementioned internal nonlinear processes (Choi et al., 2013; Im et al., 2015; M. Chen et al., 2016; An & Kim, 2017, 2018; M. Chen & Li, 2018). This chapter focuses on the irregularity of ENSO and on its amplitude and evolution asymmetries. In section 7.2, the origin of irregularity will be addressed together with the role of westerly wind burst events. Mechanisms for amplitude asymmetry will be discussed in section 7.3. The cause of evolution asymmetry will be reviewed in section 7.4, and we include conclusion and discussion in section 7.5.
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El Niño气候变化中的南方涛动
El Niño南方涛动(ENSO)具有El Niño和La Niña在振幅、模式和时间演化上的不规则或非周期性和不对称特征。这些观测到的特征表明非线性动力学和/或随机强迫的重要性。引入了非线性确定性混沌和受随机强迫和/或非正常生长影响的线性动力学来解释ENSO的不规则性,但鉴于短时间的观测记录,迄今尚未达成共识。作为随机强迫的主要来源,西风爆发在触发、放大和决定ENSO的不规则性和不对称性方面发挥着作用,最好将其视为确定性动力学的一部分或作为乘法噪声强迫。各种非线性过程导致El Niño和La Niña的时空不对称性,包括非线性海洋平流、非线性大气-海洋耦合、状态依赖的随机噪声、热带不稳定波和生物物理过程。除了内部非线性过程外,印度洋和大西洋的电容效应以及来自热带外太平洋的大气和海洋遥相关也可能导致ENSO的时间和振幅不对称。尽管取得了重大进展,但大多数最先进的模式在模拟ENSO的时空不对称性方面仍然缺乏。1延世大学大气科学系,首尔,韩国2哈佛大学地球与行星科学系和工程与应用科学学院,剑桥,马萨诸塞州,美国3德克萨斯大学奥斯汀分校杰克逊地球科学学院地球物理研究所,奥斯汀,德克萨斯州,美国4夏威夷大学马诺阿分校大气科学系/IPRC,檀香山,夏威夷州,夏威夷美国154 EL NIÑO气候变化中的南方涛动对ENSO系统大气-海洋耦合稳定性的影响[T. Li, 1997b;安&金,2000;Fedorov & Philander, 2000),例如,根据耦合强度的不同,ENSO系统在强耦合下成为自维持的混沌振荡器,在弱耦合下成为阻尼振荡器(An & Jin, 2001)。有人认为,有些年代的特征可能是自我维持的,可能是混沌的动力学,而另一些年代则表现为受随机变率激发的受阻尼的ENSO循环(Kirtman & Schopf, 1998)。然而,在存在噪声的情况下,稳定和不稳定制度之间的分岔往往是模糊的(例如,Levine & Jin, 2010)。西风暴(WWBs)是赤道信风的偶发性逆转,强度为5至7 ms-1,纬向范围为20-40度,持续时间为5 - 30天,频率约为每年5至10次(Harrison & Vecchi, 1997;L. Yu等,2003;Seiki & Takayabu, 2007)。这些事件是随机强迫的主要来源,在触发、放大甚至决定ENSO事件的空间格局方面发挥作用(Harrison & Vecchi, 1997;Eisenman et al., 2005;Levine & Jin, 2010;Rong et al., 2011;D. Chen et al., 2015;Hayashi & Watanabe, 2017)。wbs最初被认为是一种加性随机强迫(例如Moore & Kleeman, 1999),但很明显,它们依赖于背景海温,并且在El Niño发展过程中往往更频繁地发生(verickas, 1998;L. Yu等,2003;艾森曼等人,2005)。因此,最好将这些事件视为确定性动力学的一部分,或作为与状态相关的乘法噪声强迫,对El Niño事件的振幅和可预测性具有重要影响。El Niño并不是它的对立面La Niña的简单镜像。El Niño的振幅平均大于La Niña (Deser & Wallace, 1987;Burgers & tephenson出版社,1999;an&jin, 2004)。El Niño之后往往是下一年的La Niña,但相反的情况要少见得多(Larkin & Harrison, 2002;M. Chen等,2016;an&kim, 2017)。在它们的成熟期之后,许多La Niñas会持续到第二年,但大多数El Niños会在明年夏天迅速腐烂(Ohba & Ueda, 2007;Okumura & Deser, 2010;Choi et al. 2013;DiNezio & Deser, 2014;an&kim, 2018)。强El Niños主要集中在东太平洋,向赤道方向移动,而强La Niñas主要集中在太平洋中部,纬度扩展范围更广(Hoerling et al., 1997;Kang & Kug, 2002;Takahashi等人,2011;Dommenget et al., 2013)。考虑到非线性内部动力学和/或选择性外部影响,El Niño和La Niña之间的这种振幅/持续时间/过渡/模式不对称可能并不令人惊讶(例如,An & Kim, 2018)。造成振幅不对称的不对称内部非线性过程包括海洋垂直温度剖面(Zebiak & Cane, 1986)、海洋非线性平流(An & Jin, 2004;苏等人。
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