chapter two – el niño/southern oscillation and selected...

CHAPTER TWO

El Ni~no/Southern Oscillationand Selected EnvironmentalConsequencesTomasz NiedzielskiInstitute of Geography and Regional Development, University of Wroc1aw, Wroc1aw, PolandE-mail: [email protected]

Contents

1. Introduction 782. Fundamentals of El Nieno/Southern Oscillation 793. What Triggers El Nieno/Southern Oscillation? 874. El Nieno/Southern Oscillation in the Past 905. El Nieno/Southern Oscillation versus Selected Geophysical Processes and Their

Predictions 955.1 Earth Orientation and ENSO 965.2 Climatological and Hydrological ENSO Teleconnections 1005.3 Sea Level Change and ENSO 106

5.3.1 Global and Local Mean Sea Level 1105.3.2 Site-Specific Sea Level 112

6. Concluding Remarks 114Acknowledgments 115References 116

Abstract

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The paper presents a review of El Ni~no/Southern Oscillation (ENSO) and selectedenvironmental consequences at a range of spatial scales. The fundamentals of ENSO aresummarized in a descriptive way, and the reader is provided with the key facts from thehistory of ENSO research as well as with recent developments in understanding theoscillation. Subsequently, a discussion on a potential initial driving force that begins thewarm ENSO episode is given, and the inference is limited to the Quasi-Biennial Oscil-lation which may be controlled by solar forcing. Later, the insight into the ENSO historyis provided, with a scrutiny about the most recent phenomena and the ENSO variabilityover the geological time. The core section of the paper focuses on three environmentalconsequences of ENSO: irregular fluctuations of the Earth Orientation Parameters(EOPs), climatic and hydrologic teleconnections that allow migration of the ENSO signalto remote regions of the Earth (the teleconnections are explained using the specificEuropean example), and sea level change in the equatorial Pacific and Indian Oceans.

nces in Geophysics, Volume 550065-2687

//dx.doi.org/10.1016/bs.agph.2014.08.002� 2014 Elsevier Inc.All rights reserved. 77 j

http://dx.doi.org/10.1016/bs.agph.2014.08.002

78 Tomasz Niedzielski

The instances explain that ENSO is a phenomenon that impacts the dynamics of theentire Earth and controls some geophysical and environmental parameters of theatmosphere and hydrosphere at regional and local scales.

1. INTRODUCTION

El Ni~no/Southern Oscillation (ENSO) is said to be one of the mostpowerful climatic and oceanic oscillations in the Earth. A repeat cycle ofENSO varies from two to seven years, but departures from this interval arealso probable. Uneven recurrence time implies considerable problems inforecasting El Ni~no episodes (warm ENSO phases) and La Ni~na events (coldENSO phases). The occurrence of ENSO is associated with the equatorialPacific and Indian Ocean, however, its impact on the environment has alsobeen confirmed for remote regions located far from these oceans. A keyfeature that drives the dynamics of ENSO is a strong ocean–atmospherecoupling. The oscillation in question influences numerous geophysical andenvironmental processes, acting both in global and regional scales. Suchprocesses include for instance: fluctuations of climate and weather, sea levelchange, fluctuations of sea surface temperature, variations in the Earth’srotation rate, and changes in hydrologic regimes. Due to irregularity ofENSO and dissimilar magnitudes of individual events, suchENSO-impacted processes cannot be accurately predicted, particularlyduring El Ni~no or La Ni~na. Although a considerable development inunderstanding and forecasting ENSO episodes is the case, there is noagreement as to the initial driving force of ENSO. The initial forcecommences a number of consecutive and interrelated atmospheric andoceanic processes in the equatorial Pacific. El Ni~no is usually preceded bya period of intensified tropical easterlies (trade winds) in the central equa-torial Pacific after which, approximately one year before the occurrence ElNi~no, these enhanced trade winds weaken (Wyrtki, 1975, 1979). Thisinitiates the transport of warm water from the Western Pacific Warm Pool(WPWP), the large warm pool of water where sea surface temperature(SST) is greater than 27.5 �C, toward the eastern equatorial Pacific. Theoccurrence of the above-mentioned initial condition commences the warmphase of ENSO. It is rather difficult to unequivocally define the mainprocess that controls the critical shift of the tropical easterlies and itsconsequences. External reasons are sought in solar activity, however theinvestigations into this topic are still in progress. It is thus possible todistinguish two specific fields of research that can strengthen investigations

El Ni~no/Southern Oscillation and Selected Environmental Consequences 79

into the ENSO impact on geophysical processes and their prognoses,namely:• progress in detecting physical and statistical relationships between ENSO

and the selected geophysical processes (mainly activities toward under-standing, modeling and forecasting ENSO),

• seeking initial driving force of El Ni~no and La Ni~na phenomena (mainlyactivities toward improving the ENSO prediction accuracy throughincorporating the potential new facts on ENSO driving processes).The remainder of this paper consists of five sections. The subsequent one

includes an extensive and descriptive overview of ENSO fundamentals, withan emphasis put on the phenomenological explanation. In the third section theforces thatmay trigger ENSOwarm and cold episodes are selectively discussed.The fourth section concerns ENSO history, and covers both ENSO dynamicsin geological time and its activity in a few last centuries. The fifth part of thepaper provides the reader with the insight into the selected relationshipsbetween ENSOand global/regional geophysical processes, the latter related tothe variable Earth’s rotation rate, regional-scale atmospheric and hydrologicphenomena, and sea level change. The last section summarizes the paper.

2. FUNDAMENTALS OF EL NI~NO/SOUTHERNOSCILLATION

This section is mainly based on two recent books on ENSO (Clarke, 2008;Sarachik & Cane, 2010) which led to a significant structuring of ourknowledge about the oscillation in question. I was inspired by the booksand was honored to be given an opportunity to prepare their reviews(Niedzielski, 2011a,b). The reader is also advised to study the classical bookon ENSO by Philander (1990).

The notion of ENSO was defined in the second half of the twentiethcentury. Before that time researchers considered two independent elements,oceanic and atmospheric components, and no link between the two wasinferred. The two parts may shortly be characterized in the following way.• Oceanic componentdEl Ni~no (La Ni~na) phenomenon which is

defined as warm (cold) oceanic current that may occasionally reachwestern coasts of South America. The current modifies SST in the waythat during El Ni~no the strongest positive SST anomalies occur in theeastern equatorial Pacific, however, during La Ni~na the most significantnegative SST anomalies occur in the central tropical Pacific and the


slightly weaker negative anomalies, but still detectable, may be observedin the eastern equatorial Pacific.

• Atmosphericdoscillation that controls the “see-saw” of atmosphericpressure observed over the equatorial Pacific, known as the SouthernOscillation, considered between Tahiti (Central Pacific) and Darwin(Australia).The El Ni~no phenomenon, understood as the warm ocean current, was

observedmuch earlier than the atmospheric component. The observation wasmade a few centuries ago by Peruvian fishermen who noticed that rapidincrease in the ocean temperature led to the lower number of fish in theirnets. Indeed, warm water contains less oxygen than cold water, and fisheswere forced to migrate toward the oxygen-rich places. In addition, thefishermen observed that the anomalous warming of the ocean water wasassociated with the increased rainfall. The excess of precipitation led to thetransformation of Peruvian coastal desserts (e.g., Sechura Desert) into pastures(e.g., in 1891) and the initiation of floods that washed out the nutrients fromthe slopes of the West Andes. The fishermen also observed that the anom-alous warm current did not appear every year. However, they noticed that theoccurrence time was locked to the end of year, usually around Christmas.Because of the latter finding, in the nineteenth century the phenomenon wascalled El Ni~no, which in Spanish means a little boy, and the name allowed theconnotation with the Baby Jesus and Christmas.

Some elements of the atmospheric component were first observed byBlanford (1884), but its existence was empirically confirmed at the end ofthe nineteenth century by Hildebrandsson (1897). A comprehensivedescription of the “see-saw” of atmospheric pressure was produced in 1920sby Sir G. Walker. His work (Walker, 1923, 1924) provided statisticalevidences for the existence of correlations between atmospheric pressurefluctuations over the equatorial Pacific, driven by irregular changes of tradewinds, and rainfall in various regions of the Pacific and Indian Oceans. Theterm “Southern Oscillation” was first used by G. Walker to characterize theaforementioned “see-saw” of atmospheric pressure over the remote areas ofthe tropical Pacific.

The above-mentioned oceanic and atmospheric components weresaid to be interrelated in the early 1930s by Leighly (1933), howeverthe hypothesis was not widely accepted until the 1950s. The scientificcommunity accepted the relationship between the components whenBerlage and de Boer (1960) identified a statistical correlation betweenSST anomalies and changes in atmospheric pressure in the eastern


tropical Pacific. Although that association was not explained in terms ofphysical fundamentals, at that time the phenomenon was called El Ni~no/Southern Oscillation, the name that unequivocally implied couplingbetween oceanic (El Ni~no) and atmospheric (the Southern Oscillation)components.

The researcher, whose contribution to the understanding of ocean–atmosphere coupling in ENSO was the most significant, was ProfessorJ. Bjerknes. He proposed the mechanism that led to the explanation of therelationship between SST anomalies and the dynamics of the tropical atmo-sphere (Bjerknes, 1969). As a tribute to G. Walker, the theoretical wind cellover the equatorial Pacificwas named theWalker Circulation. This circulationis based onmeaningful differences in SST values observed usually between theeastern and western tropical Pacific, the differences that influence atmosphericpressuredand hence air motiondover the equatorial Pacific. Assuming a fewsimplifications and incorporating several findings, which are known now butremained unknown to J. Bjerknes at that time, theWalker Circulationmay beexplained in the following way (Figure 1 helps to understand the phenome-nological description included in the itemized facts below).• During normal conditions or during La Ni~na the tropical easterlies

tend to transport cold and dry air (see below for explanation of the origin ofthis cold air *) and coldwater (see below for explanation of the origin of this

Figure 1 Sketch of the Walker Circulation acting in the equatorial plane during normalconditions and La Ni~na (a) and El Ni~no (b).


cold water **) from the eastern tropical Pacific westward toward theWPWP.While traveling over warmwaters of this pool, above which deepatmospheric convection occurs, this air is being heated up and its moistureincreases. As there exists atmospheric low over theWPWP, this warm andhumid air migrates upward toward the tropopause and, in the form of theconvection loop, is transported aloft toward east and descends colder anddrier in the eastern equatorial Pacificwhere atmospheric pressure is high (*).Stable or increased trade winds, that control water transport from east towest, intensify upwelling which lifts up cold water from the deep towardthe ocean surface in the eastern equatorial Pacific (**).

Tropical easterlies form a specific setting of the thermocline (the oceanlayer that separates cold water from warm water) in the Pacific. Duringnormal conditions the thermocline in the eastern equatorial Pacific isshallow, located approximately tens of meters below sea surface, and in thevicinity of theWPWPthe thermocline is deep and reaches 200 mbelow sealevel. This setting implies positive SST anomalies in the western tropicalPacific and the negative ones in the eastern equatorial Pacific. Changes inSST of the ocean lead to the above-mentioned heating of the air that istransported westward.

During LaNi~na episodes theWalker Circulation is strengthened due tothe positive feedback that is initiated by the increase in the velocity of tradewinds.

Both in normal conditions and during La Ni~na events in the easternequatorial Pacific, the high pressure center is observed. In contrast, thereexists the atmospheric low in the vicinity of the WPWP.

• During El Ni~no theWalker Circulation weakens and its spatial extent ismodified. The reason behind it is probably a much earlier (one yearbefore El Ni~no) increase in velocity of the south-east trade winds in thecentral Pacific and a subsequent rapid weakening of these winds (Wyrtki,1975, 1979). This fast decrease in velocity of the south-east trade windsin the central Pacific stops the transportation of water from the eastern towestern equatorial Pacific. Its initial reason is not entirely clear. It isknown that in the western tropical Pacific westerly winds are generatedand, as a result of the enhanced Kelvin waves (see below for explanation),push the WPWP eastward (Figure 2). Warm and humid zone of deepatmospheric convection, locked to the WPWP, migrates along with theconsiderable rainfall toward the east. The eastward transport of the watersdriven by Kelvin waves strengthened by westerly winds is concurrentlyeased by the ceased or weakened upwelling in the eastern equatorial

Figure 2 Locations of centers of low and high atmospheric pressure during normalconditions, La Ni~na and El Ni~no (left column) and locations of WPWP in these conditions(right column).


Pacific. Long-term weakening of trade winds causes the thermocline todeepen and, as a consequence, large volume of warm water may bestored below the surface of the eastern tropical Pacific. The easternmostlocation of theWPWP is controlled by the magnitude of a given El Ni~noepisode (Clarke, Wang, & Van Gorder, 2000). In the case of very strongwarm ENSO events, the WPWP may be moved to the western equa-torial coasts of South and North America. For instance, during El Ni~no1982/1983 (one of the strongest warm ENSO episodes over pastdecades) the eastern edge of WPWP reached 90� W. Its location is a keyelement in modeling of the Walker Circulation during El Ni~no.

During El Ni~no the low-pressure center migrates along with theWPWP, shrinking the longitudinal extent of the Walker Circulation. Asa result of this shift in the central and eastern equatorial Pacific atmo-spheric lows are stabilized. In contrast, the spatially large center of highatmospheric pressure is build up in the western tropical Pacific (Figure 2).The weakened Walker Oscillation acts between the central and easternequatorial Pacific, and the stronger El Ni~no becomes the spatially tighterWalker Circulation is.


It is worth noting that the components of the Walker Circulation areinterrelated, and the positive feedback controls their dynamics. Indeed, theintensified (weakened) activity of a given process is triggered by intensifi-cation (weakening) of its driving process. The Walker Circulation acts asa close loop, as a chain reaction, the fluctuations of which are controlled bythe irregular dynamics of trade winds. Recall that velocity fluctuations oftrade winds in the eastern equatorial Pacific are preceded by strong variationsof the south-eastern trades in the central Pacific (Wyrtki, 1975). However, itis difficult to unequivocally state which of the processes is initial as they forma cycle and are driven by the above-mentioned feedback (see pages 28–30 inthe book by Clarke (2008)). It is likely that weakening of the WalkerCirculation causes weakening of trade winds what subsequently causes nextelements of the aforementioned feedback. The causal relationships may besummarized as follows (in bold a potential initial phenomenon is empha-sizeddbut it is uncertain whether this phenomenon is really an initial onebecause may be triggered by another one).• Intensification (weakening) of the Walker Circulation/ increase

(decrease) in the velocity of trade winds/ intensification (weakening)of upwelling in the eastern equatorial Pacific/ increase (decrease) inthe SST difference between the eastern and western equatorialPacific/ intensification (weakening) of the deep atmosphericconvection in the western tropical Pacific, concurrent slight westwardmotion of the WPWP (concurrent eastward migration of the WPWP),increase (decrease) in the velocity of eastward air motion aloft just belowthe tropopause, intensification (weakening) of downward motion ofcold air from tropopause to the sea surface of the easternequatorial Pacific/ intensification (weakening) of the WalkerCirculation.Intensification of the Walker Circulation occurs when there is a shift

from El Ni~no (or normal) conditions to La Ni~na conditions. Conversely,weakening of the Walker Circulation takes place in the case of trans-formation from La Ni~na (or normal) conditions into El Ni~no conditions.

To build a fully coherent and comprehensive picture of the phenome-nological background of ENSO, J. Bjerknes needed to detect thegeophysical process that ceases the feedback. In other words, he wanted toknow what causes that the Walker Circulation stops weakening orstrengthening and, as a consequence, what drives the shift (from ElNi~no/ normal conditions/ La Ni~na into La Ni~na/ normal con-ditions/ El Ni~no). The numerical solutions are provided by coupled


ocean–atmosphere models which are based on mutual triggering betweenthe ocean and atmosphere. The knowledge about ocean waves that areresponsible for water transport in the equatorial Pacific is critical for buildinga conceptual framework of the ocean–atmosphere coupling.

Water transport in the equatorial Pacific is controlled by two specificwaves, the equatorial Kelvin waves and Rossby waves. The first ones actalong the Equator (lack of the Coriolis force) and remove excess of watermasses from the central tropical Pacific by transporting them eastward. Incontrast, Rossby waves are associated with the nonzero Coriolis force, andtheir biggest activity is along parallels 4� S and 4� N. Rossby waves areresponsible for shifting the zone of deficit of water from the central equatorialPacific westward. The two waves migrate at dissimilar speeds, Kelvin wavesneed 70 days to travel over the entire Pacific, whereas Rossby waves do thisthree times longer. Equatorial Kelvin waves (Rossby waves) may be reflectedfrom continents and the reflection results in their transformation into thereflected Rossby (reflected Kelvin) waves. After reflection, the transformedwaves inherit the sign of sea level anomalies from the waves before reflection.The latter setting is theoretical and holds for a single wind impulse that triggersthe system (IRI, 2010), hence the Kelvin/Rossby wave dynamics is morecomplex during El Ni~no, La Ni~na or even normal conditions (Kim & Kim,2002). In addition, the equatorial Kelvin waves, having reached the west coastof South America, are transformed into coastal Kelvin waves which transportthe water northward and southward along the shore.

The developing knowledge about Kelvin and Rossby waves supportedthe above-mentioned numerical studies that aimed to model ENSO with itsintrinsic turnabout and ocean–atmosphere coupling. The first coupled modelswere proposed by Cane and Patton (1984) and Cane, Zebiak, and Dolan(1986), but the latter approach (the Cane–Zebiak–Dolan model) utilized thesolution by Gill (1980) that was based on the previous results by Matsuno(1966) and Gill and Clarke (1974). The main concept of the aforementionedpaper by Cane et al. (1986) reads as follows “The key idea in our theoryrequires going beyond the vertical plane along the Equator and consideringthe north-south circulation in the ocean.” Hence, removing excess of waterfrom the Equator toward the poles (or conversely) partially explains theturnabout of the feedback that strengthens or weakens the Walker Circula-tion. The theoretical background of this approach was earlier proposedconcurrently and independently by Gill (1983) and McCreary (1983). Theauthors found that ocean water interacts with the atmospheric HadleyCirculation (the Hadley Cell) that acts along meridians, and changes in the


Hadley Circulation are associated with variations of the Walker Circulation(McCreary, 1983). This explains the following shifts: El Ni~no4 normalconditions4 LaNi~na. Anomalies of theWalker and Hadley Circulations arestrongly negatively correlated, and this means that weakening of the first(second) one intensifies the second (first) one (Oort & Yienger, 1996).

There are two approaches for modeling ENSO. The first one is referred toas the delayed oscillator theory (Schopf & Suarez, 1988), whereas the secondstrategy is known as the discharge–recharge oscillator theory (Jin, 1997a,b).The delayed oscillator is based on the delay which is generated when theabove-mentioned ocean waves travel at dissimilar speeds through the equa-torial Pacific. The name of the theory is associated with a delay that occurswhen Kelvin and Rossby waves move, reflect from ocean boundaries and aretransformed after reflection into Rossby and Kelvin waves, respectively. Thecontinuation of this delayed reflection process, acting in concert with theabove-mentioned reflections of waves and thus with transformations betweenKelvin and Rossby waves that occur after reflection, produces interannualoscillation between El Ni~no and La Ni~na events, namely ENSO. Thedischarge–recharge oscillator, however, uses a concept of the anomalousheating and cooling of the atmosphere in the western and central equatorialPacific. The heating and cooling are driven by SST anomalies, whilemeridional transport in the ocean drives the shift between El Ni~no and LaNi~na episodes. The name of this theory follows from the accumulation ofwarm water in the surface layer of the equatorial Pacific during the warmENSO event (positive SST anomaly), referred to as recharge, and thesubsequent discharge of the warm water before the cold ENSO event.

Finally, it is worth presenting the selected environmental consequencesof El Ni~no and La Ni~na, acting at a range of spatial scales.

During El Ni~no the following phenomena usually occur (in bracketsconsequences for human and economy are included).• The entire Earth:

• Earth’s rotation rate decreases (navigation in space);• jet streams increase their velocity (civil aviation).

• The west equatorial coast of South America:• rainfall is intensified (agriculture and water management);• waters of the eastern equatorial Pacific are warm (fishery);• sea level rise in the eastern equatorial Pacific (coastal management).

• Indonesia and Australia, particularly in the vicinity of the Equator:• droughts, fires, intensified dust spreading (safety and agriculture);• fall of sea level in the WPWP (coastal management).


• The Atlantic Ocean:• decrease in the number of tropical cyclones (safety and economy).However, during La Ni~na the following environmental phenomena

usually occur (in brackets consequences for human and economy are included).• The entire Earth:

• Earth’s rotation rate increases (navigation in space);• jet streams decrease their velocity (civil aviation).

• The west equatorial cost of South America:• shortage of rain (agriculture and water management);• waters of the eastern equatorial Pacific are cold (fishery);• fall of sea level in the eastern equatorial Pacific (coastal management).

• Indonesia and Australia, particularly in the vicinity of the Equator:• excessive rainfall and catastrophic floods (safety and economy);• sea level rise in the WPWP (coastal management).

• The Atlantic Ocean:• increase in the number of tropical cyclones (safety and economy).The above list consists of main ENSO-driven environmental impacts

and is definitely incomplete. More comprehensive picture is provided in thebooks, e.g., by Philander (1990) or Caviedes (2001).

3. WHAT TRIGGERS EL NI~NO/SOUTHERN OSCILLATION?

Following the above description of ENSO fundamentals, theresearchers are not entirely sure which of the elements of the feedbackoccurs first and thus is a triggering process. Understanding the couplingbetween the atmosphere and the ocean, through the delayed oscillatortheory and the discharge–recharge oscillator approach, may suggest thatENSO is a free oscillation in which one phase of the atmosphere–ocean stateevolves into the other. This is theoretically true as the coupled ocean–atmosphere models do not need the external forcing to produce the keyENSO features. However, there are numerous studies that explore thehypothesis that certain elements of the above-mentioned feedback areexternally triggered/enhanced from outside the atmosphere–ocean system.

This section concentrates on a potential role of solar activity and/orstratospheric processes in providing initial impulses that start a shift toward ElNi~no or La Ni~na. In other words, the scope of the discussion covers theselected potential external drivers that may trigger the ocean–atmospherecoupled system. The reader should treat the text below as an assortment of


statistically confirmed facts on relations between ENSO and solar forcing,complemented with the review of the most common hypotheses thatexplain how ENSO may be controlled by solar activity.

Statistically confirmed relationships between ENSO and solar activity orENSOand changes in the Earth’smagneticfieldwere scrutinized byNuzhdina(2002)whoused a few standardENSOindices alongwith theWolf number forquantifying solar activity and Ap index for characterizing magnetic field. Forlong-range oscillations, very weak correlations were found both betweenENSO and solar activity and between ENSO and the geomagnetic index.However, the time–frequency analysis showed that the Quasi-BiennialOscillation (QBO) and the Quasi-Annual Oscillation (QAO)dthe oscilla-tions characterized by the variable periods of two and one year, respective-lydwere found both within the time series of ENSO indices and the timeseries quantifying the Wolf number and the geomagnetic index. In addition,the 5.3-year oscillation was also identified in the aforementioned data.Nuzhdina (2002) formulated the hypothesis that the cyclic interannual ENSOvariability is driven by solar activity and changes in the Earth’s magnetic field.There are a few possible geophysical interpretations of such relationships.

Kodera (2003) argues that the impact of solar activity on the troposphereis generated in the equatorial stratosphere by modifications of the meridionalcirculation. Indeed, changes in the stratospheric Brewer–Dobson Circula-tion driven by solar activity may influence fluctuations of the HadleyCirculation (see Section 2 for details) which is negatively correlated with theENSO-related Walker Circulation.

Another interpretation is based on the relationships between solaractivity and cloudiness. Solar activity influences changes in the electric fieldof the atmosphere, and the latter impacts clouds and radiation (Kniveton,Tinsley, Burns, Bering, & Troshichev, 2008; Troshichev & Janzhura, 2004).The results of O. Troshichev and his coworkers prove relationships betweensolar activity and temperature in the Antarctica (Troshichev & Janzhura,2004) and link them with ENSO (Troshichev, Egorova, Janzhura, & Vovk,2005). Associations between ENSO and solar activity are explained in thefollowing way: fluctuations of solar wind modify the global electric field inthe troposphere and hence lead to changes in cloudiness and radiation. Suchan inference involves ENSO, as cloudiness and radiation are responsible foratmospheric processes in the equatorial atmosphere (see Figure 2.2(c) in thebook by Clarke (2008)).

A particular emphasis should be placed here on QBO. In atmosphericsciences, the notion of the QBO is usually equated with the stratospheric


oscillation which changes wind directions in the equatorial stratosphere fromwesterlies to easterlies and vice versa. The period of this shift, and the associatedchanges in wind velocity, is approximately 2 years. Concurrently, as discussedabove, the QBO-like oscillations, revealing the same z2-year period, aredetectable either in ENSO time series (Gray, Sheaffer, & Knaff, 1992;Nuzhdina, 2002) or in several data sets that characterize solar activity, namely insolar neutino flux (Sakurai, 1981), fluctuations of solar wind velocity (Kul�car &Letfus, 1988) and changes in the Wolf number (Nuzhdina, 2002).

Let us focus on the relationship between the stratospheric QBO itself andENSO, and omit solar forcing. The hypothetical mechanism that partiallyexplained the QBO-ENSO link was proposed by Gray et al. (1992) whoclaimed that the east (west) phase of the stratospheric QBO favorites theoccurrence of El Ni~no (La Ni~na) events. That findings were possible becauseof the authors’ mechanism that assumes a particular distribution of deepconvection within the WPWP that is controlled by the QBO-impactedwind shear processes.

However, the problem of what drives the stratospheric QBO is notentirely explained. Many authors are inclined to accept that the stratosphericQBO is triggered solely by solar activity (e.g., Sakurai, 1981). Thishypothesis is additionally strengthened by the fact that the 11-year solaractivity cycle is said to modulate the stratospheric QBO (Kodera, Chiba, &Shibata, 1991; Labitzke & van Loon, 1988). However, the competitiveapproach is based on atmospheric models that are shown to reveal the abilityto derive the stratospheric QBO without external forcing, hence withoutsolar activity (e.g., Baldwin & Dunkerton, 1989).

Recent results on solar forcing of ENSO, profoundly based on the QBOvariability, are due to Hocke (2009) who presents the following twopotential geophysical interpretations.• If QBO in fluctuations of solar wind is intensified, the variability of

electric field of the Earth and hence the cloudiness increase, andconsequently the warm ENSO phase begins.

• The Brewer–Dobson Circulation is driven by the stratospheric QBOwith the period of 1.75 year. Modulation of short-term fluctuations ofsolar activity may trigger weakening/strengthening of the stratosphericBrewer–Dobson Circulation. The latter, however, is associated with themeridional Hadley Circulation and, as a result, with the equatorialWalker Circulation that drives ENSO (see above for details).The above-mentioned hypotheses should be treated with caution as the

problem of a potential ENSO forcing by solar activity remains open.


Over the Earth’s history, and in long term, orbital variations were foundto be responsible for controlling the ENSO cycle, as mean climate respondsto a given orbital configuration. Not only climatic forcing but also volcanicprocesses impacted the occurrence of past ENSO episodes. Some of theseproblems will be raised in the next section.

4. EL NI~NO/SOUTHERN OSCILLATION IN THE PAST

Warm and cold ENSO episodes occurred with dissimilar magnitudes,durations, and frequencies over the history of the Earth. Much is knownabout the present-day ENSO characteristics, however, when our investi-gations look far into the past our knowledge becomes limited and is oftenformulated in terms of hypotheses.

The full list of ENSO events in the second half of the twentieth centuryand the beginning of the twenty-first century is juxtaposed in Table 1. Theyrevealed different magnitudes. It is worth emphasizing that a few episodeswere particularly extreme (El Ni~nos in 1972/1973, 1982/1983, 1997/1998,and La Ni~na in 1973/1974) or prolonged (El Ni~nos in 1968/1969, 1969/1970, 1986/1987, 1987/1988, La Ni~nas in 1954/1955, 1955/1956, 1956/1957, 1973/1974, 1974/1975, 1975/1976, 1998/1999, 1999/2000, 2000/2001). Environmental consequences of these events were considerable.

The occurrence of ENSO episodes juxtaposed in Table 1 should beinterpreted against a background of ENSO indices. There are severalquantitative measures of the ENSO dynamics, among which the SouthernOscillation Index (SOI) and the Ni~no 3.4 Index remain widely used, oftenfor defining ENSO episodes themselves (e.g., Trenberth, 1997). The SOI isdefined as a difference between atmospheric pressure values observed at sealevel in Tahiti (the Southern/Central Pacific) and Darwin (the NorthernAustralia). The Ni~no 3.4 Index is represented by sea surface temperatureanomalies in the Ni~no 3.4 region (5� S–5� N, 170�–120� W). Figure 3presents how the two indices have varied since 1951. The negative spikes inSOI values correspond to El Ni~no episodes whereas the positive onesrepresent La Ni~na events. The opposite situation holds for the Ni~no 3.4Index, the positive (negative) extremes of which correspond to El Ni~no(La Ni~na) episodes. It is apparent from Figure 3 that ENSO events gatheredin Table 1 occurred when the two indices attained their extreme values.

The book by Caviedes (2001), the publication dedicated to ENSOhistory, focuses not only on environmental issues but also discusses social,

Table 1 List of warm and cold ENSO episodes based on the Oceanic Ni~no Index (ONI)published by NOAA Climate Prediction Center at http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ensoyears.shtml (date of access: 12/08/2012).Extreme events (at least one ONI �2.0) are underlined and typed in bold, whereasstrong episodes (at least one ONI �1.5) are underlined

Year Type of event Year Type of event

1950/1951 La Ni~na 1983/1984 La Ni~na1951/1952 El Ni~no 1984/1985 La Ni~na1953/1954 El Ni~no 1986/1987 El Ni~no1954/1955 La Ni~na 1987/1988 El Ni~no1955/1956 La Ni~na 1988/1989 La Ni~na1957/1958 El Ni~no 1991/1992 El Ni~no1958/1959 El Ni~no 1994/1995 El Ni~no1963/1964 El Ni~no 1995/1996 La Ni~na1964/1965 La Ni~na 1997/1998 El Ni~no1965/1966 El Ni~no 1998/1999 La Ni~na1968/1969 El Ni~no 1999/2000 La Ni~na1969/1970 El Ni~no 2000/2001 La Ni~na1970/1971 La Ni~na 2002/2003 El Ni~no1971/1972 La Ni~na 2004/2005 El Ni~no1972/1973 El Ni~no 2005/2006 La Ni~na1973/1974 La Ni~na 2006/2007 El Ni~no1974/1975 La Ni~na 2007/2008 La Ni~na1975/1976 La Ni~na 2009/2010 El Ni~no1976/1977 El Ni~no 2010/2011 La Ni~na1977/1978 El Ni~no 2011/2012 La Ni~na1982/1983 El Ni~no


economical, and political consequences of ENSO. Although such problemsare outside the scope of this paper, it is worth mentioning that El Ni~no andLa Ni~na episodes influenced the world history. In particular, the majority ofsuch instances are driven by large-scale geophysical processes that act in theupper troposphere, known as teleconnections, and propagate the ENSOsignal to places that are located far from the equatorial Pacific.

Our story begins with the most recent and significant ENSO-controlledphenomenon, the topic of which was present in headlines throughout theworld. In January 2011 catastrophic floods in Queensland, particularly inBrisbane, in Australia devastated large areas of the state. It was found that theflooding was triggered by strong La Ni~na 2010/2011 acting in concert withthe negative mode of the Indian Ocean Dipole (IOD) (Giles, 2012), which isthe irregular oscillation of sea surface temperature in the Indian Ocean, or

Figure 3 Monthly time series of the Southern Oscillation Index (SOI) defined asanomalous sea level pressure difference between Tahiti and Darwin (a) and Ni~no 3.4Index defined as sea surface temperature anomaly in Ni~no 3.4 region (5� S–5� N, 170�–120� W) (b), both spanning the interval 1951–2012. Data courtesy of the ClimatePrediction Center of NOAA, USA.


being modulated by the Pacific Decadal Oscillation (PDO) or the Inter-decadal Pacific Oscillation (IPO) (Cai & van Rensch, 2012). The latter twopatterns of sea surface temperature variation in the Pacific act at much longertime scales than those typical for ENSO.

Going back in time and focusing on Europe, it is worth mentioning thatthe history of theWorldWar II is said to be significantly impacted by ENSO.Indeed, in 1940–1942 the prolonged El Ni~no built up in the tropical Pacific.Through the tropospheric bridge the ENSO signal migrated over theAtlantic Ocean eastward toward Europe and Africa and, what had not beendiscovered at that time, modified weather in a few parts of those remotecontinents. It is now know, and will be explained in detail later in Section5.2, that just after a peak of El Ni~no the weather in parts of continentalEurope in winters and early spring becomes severe, with negative temper-ature anomalies. The prolonged warm ENSO episode was said to be one ofkey causes of Germans’ misfortune in Moscow and the subsequent Hitler’sdefeat in Stalingrad (now Volgograd) in January 1943 (Caviedes, 2001).

Likewise, according to the book by Caviedes (2001), Napoleon’sCampaign to Russia in 1812 was also influenced by the ENSO-controlled


weather in the eastern Europe. In particular, the Napoleon’s troops werebeing weakened by severe winter conditions on their way back fromMoscow westward. The retreat commenced in October 1812 and not muchlater the temperatures plummeted and reached even �35 �C. Both theweather and Russian troops led to Napoleon’s defeat. In fact, the NiemenRiver was reached by 10,000 French soldiers, i.e., slightly over 2% of theFrench men participating in the Campaign in Russia. From the meteoro-logical perspective, 1812 was an El Ni~no year (see Table 1.1 in the book byCaviedes (2001)), and the severity and early occurrence of the winter weresaid to be controlled by ENSO-impacted shift of the winds over Europe dueto the above-mentioned teleconnections (see Section 5.2 for details).

The aforementioned three instances provide evidences for complex, and infact spatially and temporally uneven, ENSO forcing and stimulate thediscussion on whether El Ni~no events occur as frequent and strong as La Ni~naepisodes. This question begins our retrospective look into ENSO history.Following Gergis and Fowler (2009), in the twentieth century there existedasymmetry in El Ni~no/La Ni~na frequency, and warm episodes were moreprobable that the cold ones. In addition, El Ni~nos were identified to be moreextreme than La Ni~na episodes. However, that situation was not the case over

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a few past centuries. Figure 4 presents trends for frequencies of ENSO events,the lines cover the sixteenth–twentieth century interval and are based on thefindings ofGergis and Fowler (2009).Rough and statistically simplified analysisshows that from sixteenth to around nineteenth century there was asymmetrytowardmore frequent LaNi~na events whichwere usually strong or extreme inthe sixteenth and seventeenth centuries.Hence, observations and data from thelast millennium allow us to provide a picture of temporal dynamics of ENSO.

However, going back in time, within the entire Holocene the picturebecomes more uncertain. It was found that early-to-mid Holocene(approximately 11,000–5000 years BP) was characterized by less intensiveENSO fluctuations than we observe today, and that effect was caused by themodification of orbital configuration. The maximum variability of ENSO inHolocene was estimated to occur between 3000 and 1000 years BP, and thefinding was confirmed both by proxy records (Moy, Seltzer, Rodbell, &Anderson, 2002) and modeling exercises (Cane et al., 2006).

In fact, rare occurrence of El Ni~no events in the early Holocene waspreceded by the non-ENSO period in late Pleistocene, namely in theYounger Dryas (12,800–11,650 BP). The driving force of ENSO stopping atthat time was also associated with the Milankovitch theory that predicts howthe Earth’s movementsdsuch as precession, axial tilt and eccentricitydinfluence climate variability. The Milankovitch cycles determine glacial/interglacial shifts as well. Although climate variability in Pleistocene is ratherwell understood, the overall ENSO variability in the entire Pleistocene is notprecisely known. Our knowledge is fragmental as the coupled modelsproduce dissimilar results (Sarachik & Cane, 2010). However, it is possible tolist a few facts such as: (1) over the Last Glacial Maximum (LGM) thepermanent El Ni~no state occurred in the eastern equatorial Pacific (Koutavas,Lynch-Stieglitz, Marchitto, & Sachs, 2002), (2) ENSO stopping, similar tothose in the Young Dryas and driven by the orbital variability, occurred also450,000–400,000 years BP (Clement, Cane, & Seager, 2001).

Going further back in time into Cenozoic, our knowledge about ENSOvariability becomes very limited and is based on often contradictinghypotheses. Such changes should be scrutinized against a background ofclimate variability in Cenozoic. Indeed, there were a few periods inCenozoic in which the Earth’s climate was both warmer than today andrevealed local (in time) maximum of temperature. Hence, the knowledgeabout ENSO variability in such relatively short and specific periods mayserve as a key for building prognoses or scenarios of ENSO dynamics duringglobal warming. The profound episodes are: Eocene Optimum, Oligocene

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Warming (Antarctic Thawing), Miocene Optimum, Pliocene Warming.Figure 5 gives an overview of global mean temperatures of the Earth duringthose periods. It is apparent that they correspond to upward peaks in thetemperature curve. In addition, in Figure 5 the most probable hypotheses ofENSO variability in the aforementioned periods, along with their authors(Galeotti et al., 2010; Huber & Caballero, 2003; Lenz, Wilde, Riegel, &Harms, 2010; Watanabe et al., 2011), are stated. Although the periodsare unlike each other, they are not found to reveal the permanent El Ni~no(or La Ni~na) state, and hence warm–cold shifts of the tropical climate seemto be a typical feature acting over geological time.

5. EL NI~NO/SOUTHERN OSCILLATION VERSUS SELECTEDGEOPHYSICAL PROCESSES AND THEIR PREDICTIONS

As clearly stated in the introduction, there are numerous geophysical andenvironmental processes being influenced by ENSO, particularly by itsextreme warm or cold episodes. They are not reviewed in this paper. Insteadof reviewing such associations, the reader is provided with the selection ofthem, the choice that proves the geophysical importance of ENSO atvarious spatial scales. We begin with global consequences of ENSO, and the


variable Earth rotation driven by ENSO extremes is described in detail.Subsequently, but in fact in close relation to the Earth rotation, we focus onthe regional scale by characterizing processes that control remote ENSOteleconnections, both climatological and hydrological ones. Having listedkey teleconnections that act in a global scale, our detailed explanation ofthem is based on the European example, as Europe is located far from whereENSO is generated. Finally, sea level change is shown as the geophysicalvariable that, at certain regional or local scales, is driven by ENSO.

5.1 Earth Orientation and ENSOFluctuations of Earth Orientation Parameters (EOPs)dpole coordinates(xp,yp), Earth rotation rate expressed as the change of Universal TimeUT1-UTC or its derivative Length of Day (LOD) and corrections to theprecession-nutation model (dX,dY)dare driven by the exchange ofmomentum between the solid Earth and the fluids. The theory behind itmay be found in numerous papers (e.g., Barnes, Hide, White, & Wilson,1983; Brzezi�nski, Bizouard, & Petrov, 2002; Dickey, Marcus, Steppe, &Hide, 1992; Eubanks, 1993; Hide, Birch, Morrison, Shea, & White, 1980;Hide & Dickey, 1991; Nastula & Salstein, 1999). The ENSO impact onfluctuations of EOPs has been investigated by many authors (e.g., Dickey,Marcus, Hide, Eubanks, & Boggs, 1994; Gross, Marcus, Eubanks, Dickey,& Keppenne, 1996). It is known that the most meaningful is the influenceof ENSO on UT1-UTC or LOD, hence on the parameters driven by theatmosphere that reflect irregular spin of the Earth. El Ni~no and La Ni~naphenomena reveal rather weak impact on pole coordinates xp or yp, whichquantify polar motion within the figure of the Earth, and have no impacton long-term variation of dX or dY that are due to precession andnutation.

Associations between ENSO and pole coordinates have been analyzedby many authors. In a few papers, B.F. Chao found that correlationsbetween SOI (see Section 4 for details) and the polar motion geodeticexcitation functionJ¼J1þ iJ2 are weak, and this may be confirmed bya visual assessment of plots for the following pairs, [J1,SOI] and [J2,SOI](see Section 2 and Figure 1 in the paper by Chao & Zhou (1999)). Theequatorial components J1 and J2 of the geodetic excitation function ofpolar motion, the latter also known as the observed excitation function, aredetermined from pole coordinates following the equation of motion (Barneset al., 1983). In contrast, the relation between North Atlantic Oscillation


(NAO), which is the atmospheric large-scale pattern of westerly windstriggered by the pressure difference between the Icelandic Low and theAzores High, and the excitation function J is more significant. It has beenfound that, when there exist meaningful NAO–J correlations, the rela-tionship between ENSO and J becomes weak and vice versa (Chao &Zhou, 1999). This means that both NAO and ENSO impacts should betaken into account for better understanding of what controls polar motionand explaining its interannual variations. Ko1aczek, Nuzhdina, Nastula, andKosek (2000), who analyzed relatively short time spans, identified strongerlag-correlations between ENSO and J as well as between ENSO and theequatorial components c1 and c2 of the atmospheric angular momentum(AAM), also referred to as AAM c1 and AAM c2. The two quantitiesinclude pressure and wind terms, and time series of AAM c1 and AAM c2are computed using the meteorological observations collected at sitesdistributed in the entire world. Ko1aczek et al. (2000), however, argued thatthe El Ni~no impact on polar motion occurs as individual impulses that leadto irregularity of xp and yp time series over warm or cold ENSO episodes.Thus, ENSO was found to modify the correlation between the atmosphericand geodetic excitation functions (Ko1aczek et al., 2000; Ko1aczek, Nastula,& Salstein, 2003). Although the strongest excitation of polar motion isdriven by the atmosphere, other fluids may also have certain role inmodifying its coordinates (e.g., Brzezi�nski & Nastula, 2002). For instance,the eastward migration of the WPWP during El Ni~no has a significantimpact on polar motion (Zhou et al., 2004), however many researchersperceive this process as minor, but statistically significant.

There are numerous papers on ENSO impact on the variable Earthrotation rate (e.g., Abarca del Rio, Gambis, & Salstein, 2000; Chao, 1984,1988; Dickey et al., 1994; Gross et al., 1996; Hide & Dickey, 1991; Rosen,Salstein, Eubanks, Dickey, & Steppe, 1984; Zheng, Ding, Zhou, & Chen,2003; Zhou, Zheng, & Liao, 2001). Statistical investigations confirm thepresence of strong correlations between ENSO indices and LOD time series,reaching even 0.7 at the 2-month lag (Hide & Dickey, 1991). These authorsexplicitly state that “The maximum cross correlation in the modern data(0.72) is found with the MSOI leading variations in Lb (and in the transferof angular momentum to the solid Earth) by about 2 months” (see page 636in the paper by Hide & Dickey (1991)), where MSOI is the modified SOIindex andLb is the interannual component of LOD. It is worth emphasizingthat the atmosphere is the main fluid that drives fluctuations of the Earth’srotation rate. The correlation coefficients computed between LOD and

Figure 6 Influence of El Ni~no events in 1982/1983 and 1997/1998 on AAM c3 variation(a) and LOD fluctuation (b).


AAM c3 (the axial component of the atmospheric angular momentum) maybe around 1. Figure 6 shows the most powerful two El Ni~no episodes of lastthree decades recorded as upward spikes within the AAM c3 and LOD timeseries. The following geophysical processes explain the occurrence of theENSO signal in LOD time series.• At the beginning of El Ni~no the atmosphere over the equatorial

Pacific begins to heat up, and the reasons behind it are described inSection 1. The main driving force is a significant fluctuation of tradewinds, namely the collapse of the tropical easterlies and the change fromeasterlies to westerlies in the central and western equatorial Pacific.Consequently, velocities of westward trade winds over the entire tropical


Pacific, considered as average values, are decreased. Hence, the WalkerCirculation weakens. Further heating of the equatorial atmospherecontinuous as El Ni~no grows and leads to strengthening of thesubtropical jet streams which flow eastward in the upper troposphere andare controlled by the Hadley Circulation. These processes cause AAM c3to increase as the westerly wind component in the equation for atmo-spheric angular momentum (see Eqn (1) in the paper by Dickey et al.(1994)) of the entire atmosphere, thus flowing eastward at variousheights, increases. As the total momentum must be conserved, theEarth’s rotation rate decreases and LOD reveals positive anomalies. Theabove-mentioned feedback is also described in the papers by Rosen et al.(1984) and Dickey et al. (1994).

• During La Ni~na a reverse situation occurs. The atmosphere over theequatorial Pacific becomes cooler, speed of tropical easterlies increases,and the Walker Circulation strengthens. Following Oort and Yienger(1996), Walker and Hadley Circulations are strongly negatively corre-lated, and thus the latter is weakened during La Ni~na conditions. Thisleads to weakening of the subtropical jet streams. Given the intensifiedtropical easterlies and weakened subtropical jet streams, the westerlywind component in the equation for atmospheric angular momentum(see Eqn (1) in the paper by Dickey et al. (1994)) decreases, and thiscauses AAM c3 to decrease over La Ni~na episodes. Following the theoryof conservation of momentum, the Earth’s rotation rate increases andequivalently LOD decreases.Associated with the relationship between LOD and ENSO is the

stratospheric QBO which allows us to better explain ENSO/LOD inter-actions. Indeed, if the QBO signal and the LOD data are both taken asexplanatory variables for explaining ENSO fluctuations, the ENSO/LODcorrelations become higher than in the case of pure ENSO/LOD analysis(Chao, 1989; Dickey et al., 1994). Hence, the stratospheric QBO wasdetected in LOD time series, and recalling Section 3, in ENSO variability(Gray et al., 1992) and solar activity (Djurovic & Paquet, 1993). Sucha coherence may lead to investigations into an external solar forcing ofENSO.

It is also worth noting a certain influence of theWPWPmigration on thevariable Earth’s rotation rate (Yan et al., 2002).

ENSO itself reveals a meaningful impact on the accuracy of the selectedEOP predictions. Weak but statistically significant influence of ENSO onpolar motion was detected. That effect was identified as the change of phase


of the annual oscillation in the pole coordinates time series as well as weakbut statistically meaningful correlations between ENSO and xp or yp (Kosek,McCarthy, & Luzum, 2001). In contrast, ENSO reveals much strongerimpact on the accuracy of the Earth’s rotation rate predictions (Schuh,Ulrich, Egger, Mueller, & Schwegmann, 2002; Niedzielski & Kosek, 2008).It is known that ENSO controls irregular spikes in the LOD/UT1-UTCtime series, and such peaks are difficult to forecast. The diagnosis of irreg-ularity of the EOP residual time series, causing problems in the process ofdetermining predictions, was performed by Niedzielski, Sen, and Kosek(2009). Although ENSO influences LOD and xp,yp, stochastic linear modelsseem to suitable for predicting the irregular components of these EOP. Thisis due to the fact that the probability distributions of LOD and xp,yp data donot significantly depart from the normal distribution.

5.2 Climatological and Hydrological ENSO TeleconnectionsTeleconnections are understood as processes that transfer certain signals ofa given oceanic and/or atmospheric oscillation to remote locations, leadingto various modifications of climate, weather, or hydrologic processes.Likewise, ENSO teleconnections are based on the remote transfer of theENSO interannual signal from the equatorial Pacific to places around theworld. How is it possible that ENSO may control weather in the selectedregions of almost all continents? The answer is that jet streams, the eastwardupper troposphere strong wind paths mentioned in the previous section,through modifications of their spatial setting influence air flow directionsand relocate atmospheric high or low pressure centers.

It is assumed that the deep convection in the western/central equatorialPacific, the intensity of which is not constant over time, generate a diver-gence zone in the upper troposphere, leading to creation of anticyclonesover the areas located north and south from the Equator. Stationary Rossbywaves in the atmosphere (see Chapter 9 in the book by Clarke (2008)) areresponsible for setting up a cyclone/anticyclone series (see Figure 4 in thepaper by Trenberth et al. (1998)) and hence convergence zones. Thus, theways that jet streams follow may be modified due to variable deep seaconvection in the western/central equatorial Pacific. This explains thegeneral process that triggers ENSO teleconnections, and the process acts inconcert with various atmospheric and/or oceanic oscillations.

Teleconnections between ENSO and climate are identified for manyregions located in the entire Earth. Several authors published maps of spatial


distribution of such areas, and they included both global, regional and localscales. Ropelewski and Halpert (1987) presented the spatial distribution ofthe ENSO-driven precipitation in the entire Earth. These authors identifiedcore regions in the world in which there exist a consistent ENSO precipi-tation signal. Although their Figure 21 (Ropelewski & Halpert, 1987) didnot include all areas where precipitation is meaningfully influenced byENSO, the authors provided a global picture, with times of occurrence ofeach teleconnection in respect to year 0 and with the information on dry/wet episodes. The generalized picture of such areas includes: (1) the westernand central tropical Pacific, the eastern Australia and Indonesia, (2) CentralAmerica, the Caribbean, the northern parts of the South America, (3) thesouthwestern parts of South America, (4) the western parts of the NorthAmerica, (5) the tropical and southern Africa, and (6) Indian subcontinent.Similar maps were produced by the same authors for temperature patternsdriven by ENSO (see Figure 13 in the paper by Halpert & Ropelewski(1992)). The set of core regions where temperature teleconnections occur isbigger. In general, the following areas were detected: (1) Indonesia andsoutheastern Asia including Indian subcontinent, eastern Australia, thesouthwestern Pacific, eastern subtropical Asia, (2) Central America, theCaribbean, the northern parts of the South America, (3) the western as wellas eastern parts of South America, (4) the northwestern as well as easternparts of the North America, (5) the tropical and southern Africa, westernequatorial Africa as well as northwestern Africa and western Europe. Thesimilar maps for temperature and precipitation were shown by Kiladis andDiaz (1989). More recently, Soden (2000) produced the comparisonbetween the ENSO-driven precipitation patterns and simulations from theGeneral Circulation Model (GCM).

Not uncommonly, ENSO climatological teleconnections may impacthydrological processes as atmospheric variables remain key elements thatform river discharge. However, it should be remembered that riverflow iscontrolled not only by hydrometeorological conditions (mainly: precipita-tion, evaporation, thawing of snow cover, groundwater level, soil moisture)but also by numerous variables that describe state of the system (mainly: soiltype, topography, geological setting, land use, land cover). In addition,human interventions and hence artificial modifications of river channels,through regulation, may amend hydrological signal. This causes thatdetecting hydrological ENSO teleconnections is not a straightforward task.There are numerous papers on such teleconnections, and they also focus onremote regions located around the world. However, in the case of the


relationship between ENSO and hydrologic processes, the presence of suchteleconnections is site-specific as the above-mentioned local state variablescontribute to formation of the discharge. The spatial distribution of signif-icant ENSO hydrological teleconnections for the Earth was presented byseveral authors, for instance by Dettinger and Diaz (2000, Figure 12),Dettinger, Cayan, McCabe, and Marengo (2000, Figure 2), and Chiew andMcMahon (2002).

The above list of areas where the climatic and hydrologic ENSO tele-connections occur should be treated as a historical base for further investi-gations, hence is incomplete, and thus should be steadily expanded alongwith our growing knowledge about this problem. The remainder of thissubsection focuses on one of the regions that were incompletely representedin the papers by Ropelewski and Halpert (1987) and Halpert andRopelewski (1992), namely on Europe and the climatic and hydrologicENSO teleconnections in this continent.

European climate is significantly influenced by NAO. Inferred from theabove-mentioned papers on teleconnections are also certain relationshipsbetween ENSO and the European weather. Our current knowledge aboutENSO impact on European continent, including detection and geophysicalinterpretation, is due to Professor K. Fraedrich who in 1990s in cooperationwith his coworkers published a series of papers (Fraedrich, 1990; Fraedrich &M€uller, 1992; Fraedrich, 1994). In the twenty-first century, the results of K.Fraedrich were confirmed using GCMs (Merkel & Latif, 2002; Mathieu,

Figure 7 Generalized maps of Fraedrich and M€uller (1992) showing positive andnegative anomalies of pressure, temperature and precipitation in Europe after occur-rence of El Ni~no or La Ni~na.


Sutton, Dong, & Collins, 2004). Fraedrich’s findings can concisely becharacterized as follows (Figure 7 helps to understand the interpretationgiven below).• The relationship between ENSO and the European climate may be

present only during such winters in the Northern Hemisphere whenEl Ni~no or La Ni~na episodes occur. More precisely, the forcing takesplace in December, January, and February (DJF) (Merkel & Latif, 2002),hence just after the occurrence of the warmest (coldest) phase of El Ni~no(La Ni~na) in the equatorial Pacific (see Figure 8.1 in the book by Clarke(2008)). Oldenborgh, Burgers, and Klein (2000) extended the time ofpotential teleconnections to early spring in the NorthernHemisphere.

• In parts of Western and Central Europe there are negative (positive)atmospheric pressure anomalies during winters in the Northern Hemi-sphere (DJF) at the end of year (0) and the beginning of year (þ1) afterthe warmest (coldest) phase of the El Ni~no (La Ni~na) episode1. Thisimplies positive (negative) temperature anomalies and positive (negative)precipitation anomalies for the above-mentioned winter season after thewarmest (coldest) phase of El Ni~no (La Ni~na)2.

• In Northern Europe positive (negative) atmospheric pressure anoma-lies are observed during winters in the Northern Hemisphere (DJF) at theend of year (0) and at the beginning of year (þ1) after the warmest(coldest) phase of El Ni~no (La Ni~na). This causes negative (positive)temperature and precipitation anomalies for the aforementioned winterseason after the warmest (coldest) phase of the El Ni~no (La Ni~na)episode3.

• Modification of the atmospheric pressure setting over Europe isassociated with a shift of main cyclone track, in particular their eastern

1 In ENSO terminology three specific years are distinguished, (�1): year before ENSOevent, (0): year when ENSO event occurs along with its maximum/minimum, (þ1): yearafter maximum/minimum ENSO activity (see Figure 8.1 in the book by Clarke (2008)).ENSO teleconnections in Europe occur usually in year (þ1).

2 Note that this does not hold for the entire area of Western and Central Europe. There aresignificant site-specific features of the spatial distribution of pressure, temperature andprecipitation anomalies. For detailed analysis, Figure 1 in the paper by Fraedrich andM€uller (1992) should be interpreted.

3 Note that this also concerns the selected located south of Northern Europe. As pressure,temperature, and precipitation anomalies reveal a complex spatial distribution, Figure 1 inthe paper by Fraedrich and M€uller (1992) should be used for a detailed scrutiny.


tails. In La Ni~na conditions cyclonic winds bend northward, towardNorthern Europe (GreenlanddIslanddNorwegian SeadnorthernScandinaviadNovaya Zemlya), whereas during El Ni~no episodes thewind flow is moved southward (GreenlanddScotlanddsouthernBalticdRussia) (see Figure 2 in the paper by Fraedrich &M€uller (1992)).Eastern tails of cross-Atlantic cyclone tracks are more vulnerable toexternal meteorological forcing than their source areas.The most important large-scale atmospheric oscillation that drives

discharges of the European rivers is NAO (Pociask-Karteczka, 2006). Theinfluence of ENSO on formation of hydrological process in Europe is notunequivocally identified. Dettinger and Diaz (2000) and Chiew andMcMahon (2002) present different views of this problem. In the first articlethe authors argue that there exists such a relationship, whereas in the latterwork weak teleconnections are said to be likely, however they may even notexist at all. Inferred from the aforementioned global studies is a picture ofmissing knowledge about the ENSO–riverflow teleconnections in Europe,particularly in local or regional scales. Indeed, the cartographic visualizationof climatological teleconnections published by Fraedrich and M€uller (1992)clearly shows that the ENSO impact on European climate is spatiallyinconsistent whatdalong with state variables that also control river-flowdleads to a significant complexity of investigations into ENSO–riv-erflow teleconnections for Europe. Thus, there is a need to produce thedetailed studies for specific countries or regions. There are a few instances ofthe analyses focusing on ENSO impact on riverflow of the Danube River(Rimbu, Dima, Lohmann, & Stefan, 2004), the rivers in the European partof Turkey (Karab€ork & Kahya, 2009) or the rivers in the southwesternPoland in the Odra River basin (Niedzielski, 2011c). The importance ofresearch into the ENSO–riverflow relationship for Europe was emphasizedby Kundzewicz et al. (2005) who argued that flood risk in Europe may besomehow related to ENSO.

In order to present an example of how search for the ENSO–riverflowteleconnection looks, a case study from Poland is concisely discussed here.Niedzielski (2011c) analyzed the residuals of discharge time series along withvarious ENSO indices (atmospheric indices: AAM x3, SOI; oceanic indices:Ni~no 3.4 index, global SST index; geodetic index: LOD; combined index:Multivariate ENSO Index known as MEI). The riverflow time series wasearlier investigated by Sen and Niedzielski (2010), and the impact ofregulation on riverflow was found not to undermine the ENSO-streamflowanalysis. Niedzielski (2011c) identified weak but statistically significant


relations between discharges of rivers in the Southwestern Poland and theabove-mentioned ENSO indices. Statistically, the relationship was detectedusing cross-correlation and wavelet coherence. To verify and test the results,an experiment was conduced, and the simulated data were used instead ofutilizing real data. The experiment strengthened our confidence as to thedetected occurrence of the ENSO-driven modifications of riverflow in theSouthwestern Poland. For time lags corresponding to the setting whenextremes of the hydrologic signal at the studied gauges were preceded byextreme fluctuations of ENSO indices (ENSO episode occurs and subse-quently the response of the hydrological system is expected), weak andnegativedbut statistically significantdENSO–riverflow correlations wereidentified. After El Ni~no (La Ni~na) episode having its peak at the end of year(0) there are negative (positive) discharge anomalies for rivers in theSouthwestern Poland. Following Fraedrich and M€uller (1992) andOldenborgh et al. (2000), the geophysical interpretation was limited towinters in the Northern Hemisphere and early springs. We again relate toFigure 7 to interpret the statistical results on the ENSO–riverflow rela-tionship in the light of climatic ENSO teleconnections for Europe, and thefollowing explanation was proposed in the paper by Niedzielski (2011c).• Inwinters duringElNi~no4 there are negative temperature anomalies in

the Southwestern Poland, with rather no precipitation anomalies.Colder-than-usual winter may lead to an increase in retention in snowalong with ground freezing, consequently reducing riverflow and leadingto low flow situations. This justifies negative ENSO–riverflow correla-tions, as after El Ni~no low flow is likely to occur. Hence, during DJFdischarge is kept low, with excess water storage in snow and no potentialway for water to infiltrate to the ground. When temperature rises rapidlyin late winter or spring, due to meteorological factors other than ENSOitself, the excess water is released and the flow occurs over the frozenground (thawing of ground is a slow process). Thus, the increasedretention in snow driven by ENSO, when it acts in concert with latewinter or early spring thawing, may lead to snow-melt peak flows.

• In winters during La Ni~na5 there exist positive temperature andprecipitation anomalies in Poland (see Figure 1(b) in the paper by

4 Usually just after the occurrence of the maximum magnitude of El Ni~no, i.e., at the endof year (0) and at the beginning of year (þ1).

5 Usually after the coldest period over the La Ni~na episode, i.e., at the end of year (0) and atthe beginning of year (þ1).


Fraedrich & M€uller (1992)). Warmer-than-usual winters with extraprecipitation cause that snow retention is decreased due to thawing what,along with the excessive rainfall or snowfall, may trigger peak riverflow.Hence, the negative correlation between ENSO and riverflow mayagain be phenomenologically interpreted, as after the occurrence ofminimum of the ENSO cold episode, discharge increases. Both thereduced snow retention and the excess precipitation, theENSO-influenced phenomena, may be potential factors that directly andthrough the teleconnection control late winter or early spring peakflows. Hence, the two may trigger certain hydrological processes,including peak flow generation.In the above example, the identified hydrologic teleconnections are

weak, and hence the characterized hypothetical mechanisms serve as rathercomplementary factors that drive late winter or early spring peak flows inPoland. However, the proposed mechanisms may help to improveprediction models that have never used the ENSO signal as the explanatoryfactor controlling peak flows in Poland (e.g., De Roo, Wesseling, & VanDeursen, 2000; De Roo, Odijk, Schmuck, Koster, & Lucieer, 2001;Niedzielski, 2007).

5.3 Sea Level Change and ENSOSea level change is driven by various processes that may be classifiedaccording to whether they can be modeled with high accuracy. The firstgroup consists of such effects that are now well known and models are ableto predict their variability, e.g., ocean tides and inverted barometer (IB)effect. The second group comprises: eustatic processes, steric processes, andcrustal motions (which in fact do not drive sea level change but influence sealevel measurements through movements of the benchmark). In general,eustatic sea level is controlled by glacial-eustasy, tectono-eustasy,sedimento-eustasy, and geoidal-eustasy (e.g., M€orner, 1980). Unlike theeustatic effect, steric processes do not allow mass exchange to occurdthussea level varies as a result of purely volumetric changes of the water. Thismay occur due to temperature (thermosteric effect) and/or salinity fluctu-ations (halinosteric effect) of the ocean. These processes are superimposed oncrustal movements of the Earth, which indeed impact sea level observationsat tide gauges but do not influence measurements carried out from space byaltimetric satellites.

ENSO plays an important role in modifying sea level, which throughsome of the above-mentioned processes may force local sea surface


topography. The following explanation may be provided for the equatorialPacific, both for La Ni~na and normal conditions as well as for El Ni~noepisodes.• During normal or La Ni~na conditions sea level in the eastern

tropical Pacific is much lower than in the western equatorial Pacific. Onaverage, the difference reaches 50–60 cm. The Walker Circulation, andprecisely trade winds that remain part of this circulation over the surfaceof the tropical Pacific Ocean, piles up the water westward, from theeastern equatorial Pacific toward the WPWP (see Section 1 for details).The water masses transported in this fashion near the ocean surface arebeing gradually heated up, to attain the maximum temperature withinthe WPWP. Strong upwelling in the eastern equatorial Pacific ismaintained and causes that sea surface temperature in the east isrelatively low.

The differences in sea surface temperatures that occur betweenwestern and eastern equatorial Pacific are driven by ENSO and maycause local thermosteric effect, which additionally modifies sea surfacetopography of the tropical Pacific (increase in water temperature causesdensity to decrease and volume to increase). As a consequence, duringnormal or La Ni~na conditions sea level in the eastern equatorial Pacificmay additionally fall due to thermosteric contribution whereas in thevicinity of the WPWP sea level may rise in respect to the long-termmean.

Wyrtki (1975) observed that fluctuations of sea level in the Pacificin the vicinity of the western coast of South America reveal similarpattern to the variability of sea surface temperature in this area.Antonov, Levitus, and Boyer (2005) have shown that thermosteric sealevel change, spatially limited to 15� S–15� N in the Pacific Ocean,reveal interannual oscillations controlled by ENSO. The thermostericcomponent driven by ENSO influences short-term trends of sea levelvariation, which is well seen in the case of El Ni~no 1997/1998(Cazenave, Cabanes, Dominh, Gennero, & Le Provost, 2003).

In addition, due to IB effect, centers of atmospheric pressure overthe equatorial Pacific during normal or La Ni~na conditions lead tofurther lowering of sea level in the east and the concurrent increase ofsea surface in the vicinity of the WPWP, and the variation is oforder of 1 cm per 1 mbar (Wunsch & Stammer, 1997). However, theIB contribution is usually removed from the sea level change timeseries.


• Before a transition to El Ni~no conditions trade winds flowing formthe southeastern sector strengthen, since the thermocline is additionallydeepen in the western tropical Pacific (greater volume of warm water arestored in the west) and sea level in the WPWP increases along with theconcurrent fall of sea level in the eastern equatorial Pacific. This situationis said to be a necessary condition that precedes El Ni~no (Wyrtki, 1975,1979). Afterward, there is usually a sudden decline in the velocity oftrade winds observed in the central equatorial Pacific, and these windsbegin to flow eastward forcing the equatorial Kelvin waves that transportthe water toward the eastern tropical Pacific. This causes a migration ofwarm water eastward, and hence the entire WPWP starts to move.Along with the growth of El Ni~no (weakening of the Walker Circula-tion) these processes lead to a significant sea level rise in the easternequatorial Pacific. In addition, coastal Kelvin waves, those that travelalong west coasts of North and South America, are intensified. They areresponsible for transporting water from the Equator poleward and drivelocal sea level rise along coasts in the vicinity of the eastern Pacificboundary in the tropical zone. The greater volume of water is stored inthe east, anddas the water is warmdlocal thermosteric effect adds itscontribution to the overall sea level change driven by El Ni~no (Antonovet al., 2005; Cazenave et al., 2003; Lombard, Cazenave, Le Traon, &Ishii, 2005).

Since during El Ni~no episodes locations of key centers of atmosphericpressure over the equatorial Pacific are reversed, IB effect additionallyleads to lowering (rising) sea level in the western (eastern) tropical Pacific.This contribution, however, is well modeled anddas in the La Ni~nacasedremoved from common sea level change data.Sea level fluctuations driven by ENSO are visible both in tide gauge

observations and in time series obtained by altimetric satellites. To analyzedynamic variation of sea surface topography, sea level anomalies (SLAs) areused, and they reflect sea surface height in respect to the long-term mean.For instance, during El Ni~no 1997/1998 SLAs in the eastern equatorialPacific exceeded 40 cm. Figure 8 shows the impact of warm and coldENSO events on sea level fluctuations. The ENSO forcing is strongindeed, as local and regional sea level variations in the equatorial Pacificand the Indian Oceans influence an average global SLA signal. Fluctuationsof sea level in the equatorial Pacific are controlled by equatorial Kelvin andRossby waves as well as coastal Kelvin waves (Figure 9), the dynamics ofwhich is incorporated in the delayed oscillator theory. One of the first

Figure 8 Maps of Sea Level Anomalies at Christmas time during: El Ni~no 1997/1998 (a),La Ni~na 1998/1999 (b), El Ni~no 2009/2010 (c), La Ni~na 2010/2011 (d). Data (updatedMSLA merged multisatellite altimetric products) courtesy of the Archiving, Validationand Interpretation of Satellite Oceanographic data (AVISO), France.


Figure 9 Sketch of causal relationships that are responsible for sea level change afteroccurrence of El Ni~no.


researchers who found that sea level change in the tropical Pacific was dueto Kelvin waves, enhanced in the central Pacific by westerlies, was Cane(1984).

Predictions of sea level change can be classifies according to:• spatial coverage (mean global, nonaveraged global, mean local, non-

averaged local);• lead time (long, medium, and short term).

Prognoses of sea level change based on empirical models reflect a natureof variability considered (linear and nonlinear trends, harmonic oscillationswith dissimilar periods, irregular stochastic terms). Predictions calculatedusing physically based models are even more promising, however they arestill imperfect as physics and its complexity are still not known enough(Rahmstorf, 2007).

5.3.1 Global and Local Mean Sea LevelForecasting global or local mean sea level change aims to predict the vari-ability of a single univariate time series, which not uncommonly is averagedover space.

Linear or nonlinear trends for global and local mean sea level change areoften utilized to compute the rate of sea level change or to capture a general


tendency of the variability. Linear functions fitted to the SLA data(Niedzielski & Kosek, 2007), when extrapolated into the future, offer thesimplest prognoses of mean sea level. Long-term linear trends in mean globalsea level in the twentieth century range from 1 to 2 mm/year (Douglas,1991; Church & White, 2006; Jevrejeva, Grinsted, Moore, & Holgate,2006; Miller & Douglas, 2004; Peltier, 1988; Peltier & Tushingham, 1989;Trupin & Wahr, 1990). Recent findings suggest that the eustatic effectsdominated thermosteric processes in forcing global mean sea level rise in thetwentieth century (Miller & Douglas, 2004). However, the correspondingtrends limited to the two-decade interval including the 1990s and the 2000sare of 1.5–3.5 mm/year (Ablain, Cazenave, Valladeau, & Guinehut, 2009;Beckley, Lemoine, Luthcke, Ray, & Zelensky, 2007; Kosek, 2001;Leuliette, Nerem, & Mitchum, 2004). It was argued that the rate of3.2 � 0.2 mm/year in 1993–1998 were entirely driven by the thermostericeffect (Cabanes, Cazenave, & Le Provost, 2001). In contrast, others claimedthat various processes contributed to the global sea level rise in the 1990s(Chen, Wilson, Chambers, Nerem, & Tapley, 1998; Lombard et al., 2005).However, the most likely hypothesis is that the 1993–2003 global sea levelrise was caused by both eustatic and thermosteric components, and thecontributions of the two were equal to 50% (Cazenave, Lombard, & Llovel,2008).

Over the last two centuries, the rate of global mean sea level variedfrom �2 to over 2 mm/year, hence revealing the long-term nonlinearity(see Figure 5 in the paper by Jevrejeva et al. (2006)). In short term, thedecelerated global mean sea level variation was observed in 2005–2008(1.1 mm/year) (Ablain et al., 2009) anddless significantlydin 2003–2008 (2.5 mm/year) (Cazenave et al., 2008). Those episodes of thereduced rate of global sea level rise in the 2000s were confirmed by thecomprehensive trend and acceleration analysis carried out by Niedzielskiand Kosek (2011), whodexcept from those individual eventsdconfirmed using TOPEX/Poseidon, Jason-1, and Jason-2 time series thatthere was no apparent acceleration/deceleration in 1993–2010. In thelong term, predictions of sea level change may include nonlinear trends,for instance, the Intergovernmental Panel on Climate Change (IPCC)assumes various environmental scenarios and the resulting extrapolationsmay evolve in a nonlinear fashion (Meehl et al., 2007).

Predictions of global mean sea level based on linear or nonlinear trendscannot properly forecast irregular or harmonic changes, including thosedriven by ENSO. In fact, slopes of global trends are not profoundly


impacted by this oscillation. In contrast, local mean sea leveldparticularly inthe equatorial Pacific and the tropical Indian Oceansdresponds to ENSO,and thus for short time spans the oscillation may control rates of sea levelchange. However, it is impossible to extrapolate such trends to get reliableprognoses of El Ni~no or La Ni~na episodes.

Trends combined with harmonic models for global or local mean sealevel change are used to predict the general tendency and regular periodicvariations. Indeed, along with linear and nonlinear trends there are alsoharmonic components, with various frequencies, driven by variousgeophysical processes (e.g., Niedzielski & Kosek, 2005). Prognoses of thesedeterministic terms are based on extrapolation of polynomial-harmonicmodels. However, ENSO events may modify the polynomial-harmonicfunctions, and hence if the amplitudes and phases of harmonic compo-nents are fit globally (constant over time) the resulting predictions cannot beused to anticipate the occurrence of El Ni~no or La Ni~na episodes.

Deterministic models with stochastic models for global or local mean sealevel change may much better capture the variability. Stochastic residuals(data minus model) describe the irregular fluctuations around thepolynomial-harmonic model. Within such residuals weak (for global meansea level) or strong (for local mean sea level limited to the tropical Pacific andIndian Oceans) ENSO signal is present. Modeling global mean sea levelchange was carried out for instance by Niedzielski and Kosek (2005) andIz (2006).

5.3.2 Site-Specific Sea LevelPredictions of global and local sea level determined as a function of latitudeand longitude are more complex and difficult to compute. Depending ona particular location different geophysical processes modify sea surfacetopography. In particular, the intensity of thermosteric effect varies alongwith latitude and longitude due to large-scale atmospheric and/or oceanicoscillations, such as ENSO, Pacific Decadal Oscillation (PDO), or NorthAtlantic Oscillation (NAO) (Lombard et al., 2005). Models and prognoses ofsite-specific sea level change reveal various properties that depend onmethods applied.

Linear and nonlinear trends fitted to sea level change time series at everysingle location in the Earth’s oceans are unlike each other. A few authorspublished maps presenting spatial distribution of the rates of sea level changeas functions of latitude and longitude. For instance, Kosek (2001) found thatthe largest rates (over 20 mm/year) were observed in the western equatorial


Pacific (Indonesia) and at higher latitudes (east of Japan). The lowest values(below�20 mm/year) occurred in the Indian Ocean (south of the Equator),in the Black Sea and some parts of the eastern and western Pacific.Niedzielski and Kosek (2010) noticed that the rates in question are notmeaningfully influenced by ENSO.

Numerous papers focused on the analysis of site-specific trends in sealevel change and their driving processes. Cabanes et al. (2001) and Cazenaveet al. (2003) argued that steric effect explained the entire sea level variationobserved by TOPEX/Poseidon in 1993–1998. However, trends fitted toSLA data in such a short time span and in the equatorial Pacific or IndianOcean may be modified by ENSO. This is confirmed by the analysis of10-year thermosteric trends (see Figure 8 in the paper by Lombard et al.(2005)). Thus, data span has to be long enough to obtain reliable trends, andNiedzielski and Kosek (2007) proposed a technique to estimate theminimum time span to be used. Cazenave et al. (2008) found that since 2003the fraction of various contributions to sea level change has been amended.

Maps showing the rates of sea level change were published by manyauthors (Kosek, 2001; Cazenave et al., 2003, 2008; Niedzielski & Kosek,2010). It was noticed that the rates are approximately equal to zero in theeastern equatorial Pacific. Although the ENSO impact on the sea surfacetemperature (and very often sea level as well) is the strongest in this area (seepage 14 in the book by Clarke (2008)), the linear trend remains a constantfunction with values around zero. Within the WPWP, however, the rates ofsea level change (6.0 mm/year) are higher than those for the global mean sealevel (Cheng, Qi, & Zhou, 2008). In contrast, within the warm pool in theequatorial Indian Ocean the trends are approximately equal to 1.6 mm/year,the value that is lower that the global mean estimates. The most likelyexplanation is that the thermosteric contribution is not the same in the twoareas,with the greater impact in theWPWPand lower in the latterwarmpool.

Trends combined with harmonic models, both as functions of latitudeand longitude, account for a deterministic variation of sea level which ishighly site specific. Apart from the above-mentioned linear trends that varyalong with location, there are many harmonic terms with periods rangingfrom 30 to 365 days (see Table 1 in the paper by Kosek (2001)). Amplitudesof harmonic oscillations may vary in time. Indeed, the semiannual oscillationduring El Ni~no 1997/1998 revealed much higher amplitude in the easternequatorial Pacific than it used to have during normal conditions (see Figure 7in the paper by Kosek (2001)). Using the Fourier transform band pass filter(FTBPF), maximum amplitudes of annual and semiannual oscillations in


SLA time series during El Ni~no 1997/1998 reached 20 and 14 cm,respectively (Niedzielski & Kosek, 2009). Predictive models with amplitudeswhich do not vary over time may thus be inaccurate during ENSO episodes.

Within data-based empirical approaches to predict sea level change,deterministic models combined with stochastic ones considered as functionsof latitude and longitude were found to be the most suitable. This is due tomodeling irregular variations that are recorded in residual time series. Notonly trends and harmonic terms fitted to sea level change data depend onlocation but also irregular components do. As the interannual ENSO signalis the strongest in the equatorial Pacific and Indian Oceans, in these areassignificant ENSO-driven sea level irregularities are the most likely to occur.Inaccuracies of prognoses of the residual sea level change signal were foundto be driven by El Ni~no/La Ni~na asymmetry, through the nonlinear heatingof the sea surface associated with the local thermosteric effect (Niedzielski,2010; Niedzielski & Kosek, 2010), given that departures from the normaldistribution are signatures of nonlinear variations (Burgers & Stephenson,1999). The nonlinear expression occurs in the heat budget equation for thesurface ocean layer (see Eqn (1) in the paper by Jin et al. (2003)), and thenonlinear term may depart from zero. Such a departure holds for strongENSO episodes causing the nonlinear heating of the ocean surface, whereasduring weak or medium ENSO events the heating is rather linear. Thedynamic nonlinear heating strengthens El Ni~no and weakens La Ni~na, andhence the asymmetry between the two occurs.

6. CONCLUDING REMARKS

A key message that may be inferred from this review paper is thatENSO properties change over time and its impact on geophysical orenvironmental processes varies at a range of spatial scales. Indeed, thedynamics of ENSO itself was reported to change both in geological time andin several recent centuries. That concerned not only the magnitudes,frequencies, or durations of individual events but also the asymmetrybetween warm and cold ENSO episodes. Although the main characteristicsof ENSO variability during a few past centuries seem to be identified (e.g.,current asymmetry toward El Ni~nos and their increased severity, with almostthe opposite situation in the sixteenth century), when one goes back in timethe picture becomes less certain (various hypotheses on the existence ofpermanent ENSO over some climatic optima in Cenozoic, with the mostwidely accepted claim that, over long time spans and except from the


sporadic situations when the phenomenon stopped, ENSO acted similarlyto the today’s oscillation but revealed dissimilar amplitudes). Likewise, evenif ENSO itself is created and grows in the equatorial Pacific and IndianOceans, its consequences reach places located remotely in respect to theseoceans or impact the entire Earth.

In order to show a profound strength of ENSO and its impact ongeophysical processes acting at global as well as regional and local spatialscales, three specific problems were described and discussed in detail. Firstly,the reader is provided with the explanation of why ENSO controls extremefluctuations of the Earth’s rotation rate, and the discussiondcovering theproblem of modifications of jet streamsdconfirms global consequences ofthe oscillation in question. Secondly, remote climatic and hydrologic ENSOteleconnections for Europe, namely the processes that transport the El Ni~noand La Ni~na signal from the tropical Pacific to Europe, are characterized. Theinstance proves that ENSO modifies regional climate and does it throughthe atmospheric bridge. Thirdly, regional and local sea level change of theequatorial Pacific and Indian Oceans is scrutinized, with an emphasis placedon the fluctuations of sea surface topography triggered by ENSO and theirunderstanding based on equatorial Kelvin and Rossby waves. Although thechoice of the examples is subjective, and one may easily extend the list, theyallow me to explain the role of ENSO is controlling various geophysicalprocesses that in turn impact the environment, life, and economy.

The phenomenological explanation of ENSO, along with externalforcing, was offered in the paper. I find such an explanation important forpostgraduate students and those who are inclined to start their research intothe ENSO-related problems. Therefore, fundamentals are conciselyexplaineddand the Quasi Biennial Oscillation, both excited in the strato-sphere without external forcing and controlled by solar activitydis discussedas a potential force that may be an initial triggering factor.

ACKNOWLEDGMENTSThe data used to produce Figures 3 and 8 are provided courtesy of (1) the Climate PredictionCenter of NOAA, USA, and (2) the Archiving, Validation and Interpretation of SatelliteOceanographic data (AVISO), France. A few parts of this work were supported by theMinistry of Science and Higher Education, Poland.


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chapter two – el niño/southern oscillation and selected...

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