Clim Dyn (2016) 46:1841–1860
DOI 10.1007/s00382-015-2679-x
How sensitive are the Pacific–tropical North Atlantic
teleconnections to the position and intensity of El Niño‑related
warming?
A. S. Taschetto1 · R. R. Rodrigues2 · G. A. Meehl3 · S. McGregor1 · M. H. England1 Received: 28 July 2014 / Accepted: 20 May 2015 / Published online: 4 June 2015
© Springer-Verlag Berlin Heidelberg 2015
Abstract The atmospheric teleconnections associated
with the Eastern Pacific El Niño and El Niño Modoki
events onto the tropical Atlantic Ocean are investigated.
The Eastern Pacific El Niños drive significant warming of
the tropical North Atlantic basin during boreal spring after
its peak via the atmospheric bridge and tropospheric temperature mechanisms. However, the tropical Atlantic does
not show a robust response to El Niño Modoki events. Here
our results suggest that the preconditioning of the tropical
North Atlantic sea surface temperature (SST) anomalies
in boreal winter plays an important role in the following
season, not only during Eastern Pacific El Niños but also
during El Niño Modoki events. Additionally, we examine three other factors that could explain potential differences in the tropical Atlantic teleconnections from El Niño
Modoki and Eastern Pacific El Niño events: (1) The distant
location of the maximum SST warming in the Pacific; (2)
The weak warming associated with this pattern; and (3)
The SST pattern including a cooling in the eastern Pacific.
Using numerical experiments forced with idealised SST in
the equatorial Pacific, we show that the location of the El
Niño Modoki SST warming during its mature phase could
be favourable for exciting atmospheric teleconnections in
boreal winter but not in the following spring season due to
* A. S. Taschetto
[email protected]
1
Climate Change Research Centre, ARC Centre of Excellence
for Climate System Science, University of New South Wales,
Sydney, NSW, Australia
2
Department of Geosciences, Federal University of Santa
Catarina, Florianópolis, Brazil
3
National Center for Atmospheric Research, Boulder,
CO, USA
the seasonal shift of the Inter-Tropical Convergence Zone
that modulates deep convection over the anomalous SST.
This demonstrates the importance of the mean seasonal
atmospheric circulation in modulating the remote teleconnections from the central-western Pacific warming in the
model. However, it is suggested here that the cooling in the
eastern Pacific associated with El Niño Modoki counteracts the atmospheric response driven by the central western
Pacific warming, generating a consequent weaker connection to the tropical Atlantic compared to the stronger link
during Eastern Pacific El Niño events. Finally we show that
the modeled Pacific–tropical Atlantic teleconnections to an
eastern Pacific warming depends strongly on the underlying seasonal cycle of SST.
Keywords El Niño · El Niño Modoki · Tropical Atlantic ·
Atmospheric teleconnections
1 Introduction
El Niño–Southern Oscillation (ENSO) events are wellknown to affect climate variability in remote ocean basins
(Enfield and Mayer 1997; Chambers et al. 1999; Klein
et al. 1999; Chiang and Lintner 2005). In the Atlantic
Ocean, the response from the Pacific warming events is
generally to warm the tropical northern basin a few months
after its mature phase during boreal spring and early summer (e.g. Curtis and Hastenrath 1995; Chiang and Sobel
2002; Kumar and Hoerling 2003; Huang 2004). This tropical North Atlantic warming has important implications for
the regional climate of Atlantic rim nations in West Africa
and northeast South America. For instance, the southward position of the Atlantic Inter-Tropical Convergence
Zone (ITCZ), which is responsible for the rainy season
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1842
of Northeast Brazil (March–May) (Hastenrath and Heller 1977; Moura and Shukla 1981), is modulated by this
tropical North Atlantic warming (Nobre and Shukla 1996;
Chiang et al. 2002; Giannini et al. 2004; Hastenrath 2006).
A warmer tropical North Atlantic Ocean can also lead to
wetter conditions over the Sahel and a deficit of rain over
the Guinea Coast region via a strengthened and/or northward displaced ITCZ (Rowell et al. 1995; Ward 1998; Janicot et al. 1998; Nicholson 2009). Therefore, improving the
prediction of tropical Atlantic SST associated with El Niño
events is fundamental to enhancing seasonal forecasts in
those Atlantic rim countries dependent on rainfall from the
ITCZ. In this study we will present evidence that different
types of El Niño events can have a subsequent effect on the
tropical North Atlantic. Thus, the purpose of this paper is to
assess the remote impact on the tropical Atlantic to varying
locations and intensities of El Niño events.
The tropical North Atlantic warming caused by El Niño
events can be partially explained via the tropospheric temperature mechanism (Yulaeva and Wallace 1994; Chiang
and Sobel 2002; Chiang and Lintner 2005; Chang et al.
2006) and the atmospheric bridge teleconnections (Lau and
Nath 1996; Curtis and Hastenrath 1995; Alexander et al.
2002). In the tropospheric temperature mechanism, the
anomalous SST warming associated with El Niño events
translates into atmospheric heating locally and remotely
via propagation of Kelvin and Rossby waves as in the
Gill–Matsuno theory. Thus the troposphere warms over
the tropical Atlantic leading to a more stable environment.
This reduces moist convection and circulation, increasing
clear-sky shortwave radiation and latent heat flux into the
ocean related to the reduced evaporative cooling at the surface (Chiang and Sobel 2002). As a consequence, the sea
surface warms, usually approximately 3 months after the
El Niño peak phase (Enfield and Mayer 1997; Huang et al.
2002).
The atmospheric bridge mechanism involves changes in
the Walker and Hadley circulations and the modulation of
the Pacific–North American (PNA) stationary wave pattern
linking ENSO to the North Atlantic mid-latitudes (Wallace
and Gutzler 1981; Nobre and Shukla 1996). The PNA net
effect is to weaken the trade winds in the tropical North
Atlantic by reducing the climatological downward motion
over the equatorward side of the subtropical high-pressure
system (Hastenrath 2000). The weakening of the wind
velocity reduces the associated evaporation rates and leads
to an anomalous warming over the tropical North Atlantic
during boreal winter, subsequent to the mature phase of the
Pacific events at the end of the calendar year.
In contrast, the relationship between El Niño events and
the equatorial and tropical South Atlantic is less robust than
the response seen in the tropical North Atlantic. Chang
et al. (2006) noted that, for some El Niño events, oceanic
13
A. S. Taschetto et al.
processes in the Atlantic compete with the tropospheric
temperature warming mechanism resulting in either warming or neutral conditions in the equatorial and South Atlantic. Generally, perturbations in the Walker cell induced
by El Niño events produce anomalous subsidence and
increased sea level pressure in the eastern and southern part
of the tropical Atlantic, thus enhancing the zonal pressure
gradient at the surface. The anomalous subsidence directly
reduces convection and inhibits precipitation in the equatorial Atlantic (Sasaki et al. 2014). The anomalous surface
pressure gradient strengthens the trade winds on and to the
south of the equator, intensifying the local Walker circulation (Chiang et al. 2002; Sasaki et al. 2014) and giving rise
to the Bjerknes feedback mechanism in the Atlantic sector.
The consequence is a shoaled thermocline in the eastern
side of the basin, and cool conditions in the central/eastern
equatorial Atlantic and Benguela upwelling regions during
boreal spring and summer following the peak of the Pacific
El Niño event. The cool SST in the tropical South Atlantic in conjunction with relatively warm SST conditions in
the tropical North Atlantic give rise to a positive meridional SST gradient (Servain 1991; Nobre and Shukla 1996).
This SST gradient induces an anomalous south-to-north
interhemispheric flow that weakens the trade winds in the
northern basin, thus reinforcing the remote El Niño influence on the tropical North Atlantic (Giannini et al. 2004).
In addition, because of the positive meridional SST gradient the climatological southward excursion of the Atlantic
ITCZ by boreal spring is inhibited, consequently causing
a rainfall deficit during the Northeast Brazil rainy season
(Saravanan and Chang 2000; Pezzi and Cavalcanti 2001;
Giannini et al. 2004; Hastenrath 2006).
The consistency of the ENSO–tropical Atlantic teleconnections has been questioned recently due to changes
in El Niño since the late 70′s. The increased frequency
of warm events in the central equatorial Pacific over the
past few decades (Ashok et al. 2007; Lee and McPhaden
2010; McPhaden et al. 2011) has drawn much attention
in the recent literature. Several studies have reported distinct atmospheric teleconnections and contrasting climate
impacts worldwide, in which severe floods and droughts
are associated with the spatial asymmetries in El Niño
events affecting important economic activities for many
nations (Larkin 2005; Wang and Hendon 2007; Weng et al.
2007, 2009; Ashok et al. 2009; Hill et al. 2009; Taschetto
and England 2009; Taschetto et al. 2010; Hill et al. 2011;
Tedeschi et al. 2013; among others).
Rodrigues et al. (2011) demonstrated that the wind stress
anomaly in the western equatorial Atlantic varies between
El Niño events. Strong El Niño events peaking in December in the eastern Pacific are associated with easterly wind
anomalies in the western equatorial Atlantic from January
to April that lead to cold anomalies in the eastern equatorial
How sensitive are the Pacific–tropical North Atlantic teleconnections to the position and…
Atlantic by March to May. Conversely, weak El Niño
events peaking in the central Pacific result in a weakening
of the subtropical high system driving westerly wind anomalies in the western equatorial Atlantic instead. The weakening of trade winds reduces evaporation from the ocean
allowing the tropospheric temperature mechanism to warm
the ocean. Rodrigues et al. (2011) also found that eastern
Pacific events cause a strong warming of the tropical North
Atlantic whereas central Pacific events induce a weak
warming. The asymmetries in the Pacific–tropical Atlantic
teleconnections were later revisited by Amaya and Foltz
(2014), in the context of the so-called El Niño Modoki
(Ashok et al. 2007). The authors have shown a cooling in
the northeastern tropical Atlantic (where it was previously
thought to warm) and near-neutral conditions elsewhere in
the tropical Atlantic associated with El Niño Modoki. They
show that the PNA pattern derived from Modoki events is
much weaker than that excited by eastern Pacific El Niños.
Here we show that during El Niño Modoki the PNA pattern is not only weaker but also shifted compared to eastern
Pacific El Niños.
The reason why the atmosphere responds differently to
distinct Pacific SST anomalies (SSTA) remains unclear.
Mayer et al. (2013) demonstrate that the net energy
exchanges between ocean and atmosphere are relatively
weak for El Niño Modoki compared to eastern Pacific El
Niño conditions. Banholzer and Donner (2014) show that,
unlike traditional El Niño events, the mature phase of
central Pacific El Niños is not strong enough to warm the
global average surface temperature significantly. Amaya
and Foltz (2014) suggest that the weaker SST anomalies
associated with El Niño Modoki would force weaker teleconnections to the tropical Atlantic. However the authors
also acknowledge that this can be a more complex process,
as the proximity of Modoki-related SST warming to the climatological warm pool would force a stronger atmospheric
response than the same magnitude of SST anomaly in the
eastern equatorial Pacific. Here we use numerical experiments to explore the role of these two factors, i.e. location
and strength, in driving atmospheric teleconnections.
In addition, asymmetries in the teleconnections can
also arise from the temporal evolution of El Niño cycles.
Lee et al. (2008) showed that when El Niño events terminate before April, the atmospheric bridge is not persistent
enough to force tropical North Atlantic warming. We show
that even in the presence of a continuous El Niño Modoki
pattern, the remote teleconnection tend to vanish in boreal
spring because the atmospheric response to a warming in
the central-western Pacific is phase-locked to the background seasonal cycle.
Finally, as the El Niño Modoki pattern evolves to
anomalously cold SST conditions in the eastern Pacific
by boreal spring, the associated weak teleconnections
1843
could be related with the development of a La Niña event
instead of being a response to warming in the central equatorial Pacific. The compensating role of the eastern Pacific
cooling relative to the warming in the central Pacific is
discussed here. Rodrigues and McPhaden (2014) have
recently shown that asymmetric atmospheric and oceanic
responses in the tropical Atlantic also arise from different
types of La Niña events.
In this study we explore the sensitivity of El Niño–tropical Atlantic teleconnections to varying locations and intensities of warm SSTA along the equatorial Pacific using idealized experiments with an atmospheric general circulation
model. We will show that the atmospheric circulation is
sensitive to the location of warm SST anomalies particularly in the central-western Pacific.
The rest of this paper is organized as follows: Sect. 2
outlines the datasets, presents the selection of El Niño years
in observations and details the numerical experiments. Section 3 examines the tropical Atlantic SST and atmospheric
circulation response in observations. Section 4 describes
the atmospheric circulation patterns in response to different intensities and location of SST warming. Finally Sect. 5
presents the discussion and summarizes the main findings
of this study.
2 Data and methods
2.1 Data analysis
The SST fields used in this study are from the Hadley
Centre Global Sea Ice and Sea Surface Temperature (HadISST1) dataset (Rayner et al. 2003). HadISST1 has a spatial resolution of 1° latitude × 1° longitude. The precipitation dataset is from the Global Precipitation Climatology
Project (GPCP) available from 1979 to the present. This
dataset combines rain gauge measurements and satellite
precipitation data on a regular 2.5° × 2.5° latitude by longitude grid (Adler et al. 2003). The atmospheric fields of
Sea Level Pressure (SLP), geopotential height and multilevel winds, are provided by the National Center for Environmental Prediction–National Center for Atmospheric
Research (NCEP–NCAR) Reanalysis I (Kalnay et al.
1996). The NCEP–NCAR reanalysis is available over a
2.5° × 2.5° grid. All fields include global monthly data
from December 1949 through November 2012. The analyses shown here were compared with the precipitation products from CPC Merged Analysis of Precipitation (CMAP;
Xie and Arkin 1997) and Global Precipitation Climatology
Center (GPCC) over land (Schneider et al. 2013) and SST
data from ERSSTv3 (Smith et al. 2008). The results have
shown robustness across those datasets, unless otherwise
discussed in the text.
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Table 1 Summary of criteria
employed for classifying
observed El Niño events using
the standardized Niño3 and
Niño4 indices
A. S. Taschetto et al.
Event
Criteria
Years selected
Eastern Pacific El Niño Niño3 > 1 SD for > = 6 months and
Niño3 > Niño4
1952, 1958, 1973, 1983
1987, 1998
El Niño Modoki
1966, 1968, 1978, 1991, 1995, 2003,
2005, 2010
EMI > 1 SD for > = 6 months
Years refer to the decaying phase of the El Niño cycle, i.e. 1998 refers to the 1997/1998 El Niño event. The
years selected here are robust between the HadISST and ERSSTv3b datasets. The Eastern Pacific El Niño
years marked in italics match those in Trenberth (1997)
SD standard deviation
To examine the interannual variability in the time-series,
the datasets were firstly detrended using a 30-year running mean filter. This eliminates variability associated with
multi-decadal periods (e.g. different phases of Pacific Decadal Oscillation) and diminishes issues related with shifts
in mean climate states as for example recently reported in
the 1990s over the North Atlantic (Robson et al. 2012).
The anomalies are then calculated as the departure from
the corresponding monthly means spanning the observation period. Where needed the anomalies are aggregated
into 3-months averages, i.e. December to February (DJF),
March to May (MAM), June to August (JJA), and September to November (SON). A two-tailed student t test is used
to assess where observations or experiments are statistically
different from the observed climatology or control run.
In this study we adopt the ‘‘Eastern Pacific’’ (EP) terminology to refer to El Niño events with SST anomalies peaking in the eastern equatorial Pacific. The selection of EP El
Niño events is based on the standardized SST anomalies
over the Niño-3 region. For each grid-point of the domain
of interest, the SST data is firstly detrended using a 30-year
running mean filter; secondly the anomalies are calculated
by removing the long-term monthly climatology over the
entire period analyzed here; thirdly the monthly SST anomalies are averaged over the equatorial Pacific areas bounded
by 5°N–5°S, 150°W–90°W to create the Niño-3 index;
then the resulting Niño index is normalized by the corresponding monthly standard deviation; and finally smoothed
by a 5-month running mean filter. To guarantee that the
selected El Niño events have a proper initiation, peak and
termination cycles, and to avoid the selection of random
warming events, we base our criteria not on a single month
or season, but on the persistence of the index above a certain threshold. In this case, an El Niño event is selected
when the normalized Niño index remains above 1 standard deviation threshold for at least six consecutive months.
The first month that matches this criteria defines Year(0)
when the event develops, and the subsequent year defines
Year(+1) when the event generally dissipates. In addition
to this criterion, we distinguish EP events from those with a
maximum SST warming in the central Pacific by verifying
13
where the index is higher. Specifically, an EP El Niño year
is selected when the normalized Niño-3 index exceeds one
standard deviation for six or more months and the Niño-3
index is larger than Niño-4 (SST anomalies averaged over
5°N–5°S, 160°E–160°W) during all those months. Unless
otherwise specified in the text, we refer to boreal winter,
i.e. December (Year 0)–January–February (Year +1), as the
season when El Niño peaks, and boreal spring, i.e. MAM
(Year +1), as the season of its decay.
For El Niño events with a maximum SST warming in the
central Pacific, we use the classification of El Niño Modoki
(EM) created by Ashok et al. (2007).The EM Index (EMI)
C
B
A
,
is defined as EMI = EMISSTA
+ EMISSTA
− 0.5 EMISSTA
where EMISSTA represent the average of SST anomalies over the central Pacific region A (165°E–140°W,
10°S–10°N), eastern Pacific region B (110°W–70°W,
15°S–5°N), and western Pacific region C (125°E–145°E,
10°S–20°N). To be consistent with EP events, the EMI
is normalized by the monthly standard deviation and
smoothed with a five-points running mean filter. Similar
to the above criteria, a warming event is selected when the
EMI exceeds 1 standard deviation threshold for at least six
consecutive months.
The years that match our selection criteria for EP and
EM events are shown in Table 1. The respective regions
associated with El Niño indices are shown in Fig. 1a.
2.2 Model experiments
To examine the importance of different types of El Niño
SST in modulating the Pacific–tropical Atlantic teleconnections, perturbation experiments were conducted using the
National Centre for Atmospheric Research (NCAR) Community Atmosphere Model (CAM3), which has a T42 horizontal resolution (approximately 2.8° latitude–longitude)
with 26 hybrid sigma/pressure vertical levels. A detailed
description of this model is given by Collins et al. (2006).
A 50-year integration was forced by idealized, temporally fixed, warming anomalies imposed over different
regions across the tropical Pacific (see Fig. 1b), bounded
between 10°N and 10°S and longitudinally located in: (1)
1845
How sensitive are the Pacific–tropical North Atlantic teleconnections to the position and…
Fig.  1 a Regions of interest:
Niño3 (green), Niño3.4 (dashed
beige), Niño4 (purple), El
A
NiñoModoki (EMI = EMISSTA
C
B
−0.5 EMISSTA + EMISSTA ,
dashed brown), tropical North
Atlantic (red) and PNA
(yellow). The PNA Index follows the definition on http://
www.esrl.noaa.gov/psd/data/
timeseries/daily/PNA/ and is
calculated using the geopotential centers-of-action averaged
over the regions (15°–25°N,
180°–140°W) − (40°–50°N,
180°–140°W) + (45°–60°N,
125°W–105°W) − (25°–35°N,
90°W–70°W). b Regions of
SST forcing for the sensitivity
experiments. Eastern Pacific
(EPac, blue), Central-Eastern
Pacific (CEPac, green), Central
Western Pacific (CWPac,
red), Western Pacific (WPac,
orange), ECEPac (dashed
purple) and MODOKI (dashed
brown)
(a) Indices and regions of interest
o
50 N
o
25 N
C
o
0
A
120oE
B
180oW
EMI
Niño4
120oW
60oW
0o
PNA
Niño3.4
Niño3
tNA
(b) SST forcing regions
20oN
WPac
ECEPac
CEPac
EPac
CWPac
0o
MODOKI
o
20 S
150oE
the eastern Pacific (EPac), from 120°W to 80°W; (2) the
central-eastern Pacific (CEPac), from 160°W to 120°W;
(3) the central-western Pacific (CWPac), from 160°E to
160°W; and (4) the western Pacific (WPac), from 120°E
to 160°E. The SST anomalies were linearly tapered to zero
over a 10° latitude/longitude band and elsewhere the SST
forcing is taken to be the climatological monthly mean. Initially, the SST anomalies in each of these four regions was
set to 0.5 °C, and these experiments were repeated gradually increasing the SST anomaly magnitudes to 0.75, 1.0
and 1.5 °C.
Note that the imposition of these SST anomalies
is highly idealized and was not selected to reflect the
exact position of anomalies associated with the different types of El Niños. Instead the locations merely span
the zonal extent of the equatorial Pacific and provide
a broad means of comparing the resultant atmospheric
circulation and rainfall impacts associated with warm
SST anomalies at various longitudes across the region.
The magnitudes of these anomalies are also idealized,
as typically the eastern Pacific El Niños can be much
warmer than the central Pacific events. Nevertheless, this
set of experiments can provide a better understanding
of the sensitivity of circulation response to SST anomalies as a function of geographic location and strength of
forcing along the tropical Pacific. Where possible, the
responses within these experiments are compared with
the climate response observed during El Niño events. To
160oW
110oW
60oW
further facilitate this comparison, two additional “semirealistic” experiments were carried out: (1) one forced
by a temporally fixed 3 °C SSTA over the combined
EPac and CEPac regions (ECEPac); and (2) forced with
a temporally fixed Modoki pattern as defined by Ashok
et al. (2007). This semi-realistic Modoki pattern has a
1 °C warming over the central Pacific at 165°E–140°W,
10°S–10°N, and a 0.5 °C cooling on both sides along the
equator at 110°W–70°W, 15°S–5°N and 125°E–145°E,
10°S–20°N (MODOKI; see Fig. 1a for El Niño Modoki
region). Similarly to the previous experiments, the
anomalies were linearly tapered to zero over a 10°
latitude/longitude.
To assess the atmospheric response to an even more realistic representation of the different types of El Niño events,
we also analyze two experiments forced by the observed
El Niño composites (ELNINO and ENMOD, respectively). The anomalous SST perturbations were applied
over the Pacific region from 30°N to 30°S and meridionally bounded by 120°E longitude and the American Continent. To reduce spurious atmospheric circulation set up by
unrealistic gradients at the edges of the SST perturbation,
the introduced anomalies were tapered to zero over the 10°
latitude/longitude band.
The anomalies described above were then superimposed
onto the monthly varying climatology. All the experiments
were performed for 50 years. A summary of the experiments used in this study is shown in Table 2.
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A. S. Taschetto et al.
Table 2 Summary of the
numerical experiments used in
this study
Idealised SST anomaly varying
(0.5, 0.75, 1.0 and 1.5 °C)
Experiment
Description
EPac
SST anomaly superimposed in the
climatology over the eastern Pacific at
80°W–120°W, 10°S–10°N
SST anomaly superimposed in the climatology over the central-eastern Pacific at
120°W–160°W, 10°S–10°N
SST anomaly superimposed in the
climatology over the central-western Pacific
at 160°E–160°W, 10°S–10°N
SST anomaly superimposed in the climatology
over the western Pacific at 120°E–160°E,
10°S–10°N
3.0 °C SST anomaly superimposed in the
climatology over the eastern Pacific at
80°W–160°W, 10°S–10°N
SST anomaly as in EMI superimposed in
the climatology: 1 °C at 165°E–140°W,
10°S–10°N, −0.5 °C at 110°W–70°W,
15°S–5°N and −0.5 °C at 125°E–145°E,
10°S–20°N
CEPac
CWPac
WPac
Semi-realistic SST anomaly
ECEPac
MODOKI
Observed SST anomaly
DJF
o
30 N
o
180 W
o
120 W
o
60 W
o
0
o
0
(b)
o
o
30 S
o
180 W
o
120 W
o
o
60 W
0
30 N
(d)
o
0
180oW
120oW
60oW
o
30 N
0o
o
o
30 S
180oW
120oW
60oW
0o
o
30 N
(f)
o
0
o
180 W
−1.2
120oW
60oW
0o
−0.6
30oS
0
180oW
120oW
0.6
60oW
tNA
(e)
0
30oS
MAM
o
30 N
EM
(c)
o
o
Observed composite of El Niño Modoki over
the tropical Pacific between 30°S and 30°N
o
30 N
30 S
ENMOD
0
o
30 S
Observed composite of EP El Niño over the
tropical Pacific between 30°S and 30°N
EP
(a)
o
0
ELNINO
0o
1.2
Fig. 2 Composites of observed SST anomalies during boreal winter (left panels) and spring (right panels) for (a, b) Eastern Pacific
El Niños, (c, d) El Niño Modoki, and (e, f) tropical North Atlantic
warming above 0.4 °C (see red dashed line in Fig. 4): 1958, 1966,
1969, 1970, 1980, 1981, 1983, 1998, 2005, 2010. Grey contours show
regions that are statistically different from climatology, while hatched
areas in (c) and (d) depict where El Niño Modoki is statistically different from Eastern Pacific El Niño, both at the 90 % confidence level
according to a two-tailed Student t test. Units in Celsius
3 Tropical Atlantic response to Eastern Pacific El
Niño and El Niño Modoki events in observations
anomalies using observations. The composite of EP El
Niño and EM events during DJF and MAM is shown in
Fig. 2a–d. During the EP El Niño mature phase (DJF), the
Pacific warming extends from the dateline to the west coast
of South America, in contrast to the EM events where the
In this section we examine the relationship between the
two types of El Niño events and the tropical Atlantic SST
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How sensitive are the Pacific–tropical North Atlantic teleconnections to the position and…
Feb−Mar Winds &
Feb−Apr
Mar−Apr LHFLX Geopotential Height
Mar−Apr Winds &
Mar−May SST
Eastern Pacific El Niño
50oN
30 N
o
30 N
o
o
El Niño Modoki
50oN
30 N
o
30 N
o
10 N
o
10 N
50
25
o
(a)
10oS
o
110 W
6.5 m/s
o
70 W
o
30 W
2
o
0
(b)
10oS
10 E
o
110 W
30 N
o
30 N
o
10 N
6.5 m/s
o
70 W
o
30 W
−25
2
o
10 E
o
−50
50
25
o
10 N
(c)
o
10 S
o
80 W
o
o
20 W
(d)
o
2
10 S
o
o
10 E
80 W
2.2 m/s
50 W
0
2.2 m/s
o
50 W
o
20 W
−25
2
o
10 E
o
10 N
0.8
0.4
10 N
(e)
o
10 S
o
80 W
o
50 W
o
20 W
0
(f)
o
10 S
o
o
80 W
10 E
2.2 m/s
−50
2
2.2 m/s
o
50 W
o
20 W
−0.4
2
o
10 E
−0.8
Mar−May
Precipitation
3
o
o
1.5
10 N
10 N
0
10oS
(g)
o
80 W
10 S (h)
o
o
50 W
o
20 W
o
10 E
o
80 W
−1.5
o
50 W
o
20 W
o
10 E
−3
Fig. 3 Composites of anomalous (a, b) Feb–Apr geopotential height
and Feb–Apr winds at 500 hPa, (c, d) Mar–Apr latent heat flux and
Feb–Mar surface winds, (e, f) Mar–May SST and Mar–Apr surface
winds, and (g, h) Mar–May precipitation. Left column Eastern Pacific
El Niño. Right column El Niño Modoki. Grey contours and black
vectors are statistically different from climatology and hatched areas
(on right column) depict where El Niño Modoki is statistically different from Eastern Pacific El Niño, both at the 90 % confidence level
according to a two-tailed Student t test. Units are m, m/s, W/m2, Celsius, and mm/day respectively
warming is confined to west of 120°W (Fig. 2a, c). The
tropical North Atlantic (tNA) basin warms in the following
season (MAM) in the presence of an EP El Niño (Fig. 2b).
However, when EMI is used to select El Niño events, the
tNA basin warming in the following boreal spring after
EM peak is much less pronounced (Fig. 2d). It should be
noted that the comparison of the tNA warming between
these two types of El Niño does not show statistically significant differences, most likely due to the smallness of the
sample size. However, the results are suggestive enough to
motivate the exploration of this possibility using controlled
model experiments. It is also worth noting that in the EM
composite the El Niño warming is weaker and the eastern Pacific is cooler than the EP case especially by MAM
(Fig. 2c–f).
The associated condition of the tropical Atlantic during EP and EM events is shown in the composites of
Fig. 3. Anomalous negative geopotential is observed over
the United States during EP (Fig. 3a), but weaker and
non-significant anomalies occur in the EM case (Fig. 3b).
The EP anomalous geopotential pattern is companied by
negative latent heat flux and westerly wind anomalies over
tNA, which is not robust in the EM composite (Fig. 3d).
Warming in the tNA (Fig. 3e) and reduced precipitation
over ITCZ (Fig. 3g) are observed during EP events, while
a weaker tNA warming (Fig. 3f) and virtually no change in
ITCZ precipitation (Fig. 3h) occur during EM.
The responses of anomalous atmospheric circulation, heat
flux, SST and precipitation are consistent with the mechanisms by which EP El Niño are proposed to affect the tropical Atlantic (Fig. 3, left column). EP El Niño in its mature
phase modulates the PNA pattern (e.g. Wallace and Gutzler
1981), generating below-average heights over the southeastern United States extending toward the North Atlantic
(Fig. 3a). This anomalous height and its associated cyclonic
circulation act to weaken the subtropical high system from
February to April, reducing the trade winds in the tropical
region from February to April (Fig. 3c, e) thus diminishing
13
1848
MAM Tropical North Atlantic SSTA x DJF Nino3.4 Index
1
1969
0.8
0.6
2010
1958
1970
1980
1981
0.4
tNA SSTA (Celsius)
Fig. 4 Scatter plot between the
MAM SST anomalies averaged
over the tropical North Atlantic
(5°N–25°S, 55°W–15°W) and
the DJF Niño3.4 region. El
Niño years and years when the
tNA warmed more than 0.4 °C
(above the red dashed line) are
marked in the plot. Red circles
Eastern Pacific El Niños (EP).
Blue circles El Niño Modoki
(EM) events
A. S. Taschetto et al.
1998
1966
2005
1983
1987
1978
0.2
0
1952 1995
1968
1973
−0.2
2003
1991
−0.4
−0.6
tNA
EP
EM
−0.8
−1
−2.5
−2
−1.5
−1
−0.5
0
0.5
1
1.5
2
2.5
Nino3.4 (Celsius)
the evaporative cooling at the surface from March to April
(Fig. 3c). On top of that, the tropospheric temperature mechanism acts in favor of the PNA pattern, reinforcing the El
Niño–tropical North Atlantic teleconnection. The result is a
warming of the tNA basin by boreal spring, one season after
EP El Niño’s peak (Fig. 3e). In the equatorial region, anomalous subsidence driven by changes in the Walker circulation
directly inhibits convection along the Atlantic ITCZ (Sasaki
et al. 2014) causing a deficit of rainfall over a zonal band
from northeastern South America to West Africa in MAM
(Fig. 3g). This rainfall deficit seems worsened by the warm
tNA SST conditions that sustain the ITCZ northward from
its climatological position (Chiang et al. 2002).
During EM events, in contrast, the Pacific–North Atlantic teleconnections via the PNA appear to be too weak
(Fig. 3b) to drive significant changes in the tNA surface
fluxes (Fig. 3d). Therefore, we suggest that the atmospheric
bridge during EM events is not efficient enough to generate
the robust tNA warming seen in the EP case. Nevertheless,
the tNA experiences a certain degree of warming in boreal
spring after EM mature phase concentrated in a smaller
region than in the EP case, which due to the lack of a significant PNA pattern, we suspect is a response from the
tropospheric temperature mechanism rather than the atmospheric bridge. The anomalous ocean warming feeds back
to the underlying atmosphere, changing the surface fluxes
and producing significant wind anomalies above the positive SST area (Fig. 3f).
13
This leads us to question whether the inefficiency of the
atmospheric bridge during EM events is due to the strength
of those events, to the positioning of the maximum SST
warming in the equatorial Pacific or the entire EM pattern
involving the cooling in the eastern Pacific. To address the
first question, we investigate the tNA warming events by
using a single Niño index to represent the warm events in
the equatorial Pacific regardless of the type of El Niño. We
use the SSTA from the Niño3.4 as both types of El Niño
produce SST changes in this region.
Figure 4 exhibits the MAM tNA SST anomaly versus
the Niño3.4 SST anomaly during DJF, i.e. the season when
El Niño events peak. As expected, the tNA basin tends to
warm (cool) in the presence of El Niño (La Niña) events.
There is an overall linear relationship between the DJF
Niño3.4 and the MAM tNA SST anomaly, with a significant correlation coefficient of 0.60. Correlation analysis of
the MAM tNA SST anomaly with the DJF values of the
other Niño indices reveals a 0.63 coefficient with Niño4,
0.56 with Niño3 and 0.49 with the EMI, with all correlations statistically significant at the 95 % confidence level.
All EP events generate anomalously warm SST in
the tNA during MAM except for the 1973 event. For EM
cases, however, three out of eight events produce negative
SST anomalies in tNA, i.e. 1968, 1991 and 2003. On average, the EP El Niños are associated with a 0.34 °C warming in the tNA in MAM (statistically different from zero
at the 95 % level), while the EM cases are associated with
1849
How sensitive are the Pacific–tropical North Atlantic teleconnections to the position and…
a statistically non-significant warming of 0.20 °C over the
same region and season.
While we found mild warming in the MAM tNA during EM years, Amaya and Foltz (2014) obtained significant
cooling in the northeastern tropical Atlantic and near-neutral conditions elsewhere in the tropical Atlantic. The difference between our selected years and those chosen by
Amaya and Foltz (2014) lies in the distinct definitions of
EM years, detrending techniques, and different datasets
used. Firstly, our criterion involves a one standard deviation threshold for EMI and the persistence of the EM SST
anomalies for at least 6 months, while theirs is based on
a 0.5 standard deviation threshold for DJF EMI plus the
condition that the standardized DJF SST in region A
should exceed the same threshold to distinguish EM from
La Niña events, as defined by Tedeschi et al. (2013). Secondly, SST data was linearly detrended in Amaya and
Foltz (2014) while we use a 30-year running mean filter
to remove the long-term trend in the dataset. And finally,
they use ERRST.v3b from 1880 while we use HadISST
from December 1949. The use of a shorter time span may
limit the sample size of El Niño events, but on the other
hand it covers a more reliable and accurate measurement
period. Notwithstanding these differences, the main result
from the SST composite analysis agrees with Amaya and
Foltz (2014) in the sense that EM years are associated with
a weaker tNA response compared to EP El Niños.
The Pacific–tropical Atlantic relationship is further
tested here by compositing the SST anomalies when the
tNA basin is unusually warm. Figure 2e, f shows the DJF
and MAM SST patterns for the years when tNA exceeded
0.4 °C. According to our classification, 60 % of the cases
where the tNA SST was above 0.4 °C co-occur with El
Niño events (Fig. 4, events above red dashed line). The
years 1970 and 1980/1981 were unusually warm in the tNA
basin, however, the equatorial Pacific was not persistently
warm enough for those years to be classified as El Niño
events by our criteria.
The composites of Fig. 2e, f reveal a strong El Niño pattern in DJF followed by a weaker signature in MAM with
maximum SST anomalies in the central Pacific and off the
South American coast. The greatest difference in the SST
pattern between Fig. 2f and the EM composite from Fig. 2d
B ,
is the cooling in the region B of the EMI index (EMISSTA
see Fig. 1). As such, we hypothesize that the signal of
B
EMISSTA
can modulate the response of the tNA SST. This
seems a priori an obvious hypothesis since it is well known
that La Niña events lead to a cooling of the tNA basin.
However, in EM cases, the warming in the central Pacific
can act as a competing factor, so the outcome in tNA may
not be so clear.
Another important feature from Fig. 2e is the mild
warming in the tNA region in DJF. Previous studies
Table 3 Correlation coefficient resultant from multilinear regression
analysis between the tNA during MAM and the predictors as follow
Predictors
Correlation coefficient
DJF tNA
DJF Niño3
DJF Niño3.4
DJF EMI
A
DJF EMISSTA
0.674
0.566
0.605
0.495
0.633
B
DJF EMISSTA
0.491
DJF
DJF tNA + DJF Niño3.4
0.298
B
DJF tNA + DJF Niño3.4 + DJF EMISSTA
0.807
DJF tNA + DJF EMI
A
DJF tNA + DJF EMISSTA
0.737
0.807
A + DJF EMI B
DJF tNA + DJF EMISSTA
SSTA
0.811
C
EMISSTA
0.807
have demonstrated that the tNA warming during El Niño
events is dependent on the precondition of the local tropical Atlantic SST (Saravanan and Chang 2000; Pezzi and
Cavalcanti 2001; Huang et al. 2002; Giannini et al. 2004).
When the tNA is anomalously warm relative to the tropical
South Atlantic basin as the El Niño evolves, it produces
positive interhemispheric SST and pressure gradients such
that there is a deceleration in the trade winds in the warm
hemisphere and an acceleration in the opposite hemisphere. This acts to enhance the weakened trade winds in
tNA caused by the remote El Niño teleconnection, reinforcing the cross-equatorial atmospheric flow and thus
producing a positive air-sea feedback that intensifies the
SST warming condition. In our analysis, we note that the
tNA SST anomaly in DJF maintained the same signal in
the following MAM season in ten out of 14 events classified either as Eastern Pacific El Niño or El Niño Modoki
(not shown).
We have also tested Fig. 4 using a more flexible classification of ENSO by Karnauskas (2013). The author
discusses the challenge of studying ENSO diversity and
proposes an index that eliminates any assumptions on the
geographic location of SST anomalies. The index, called
Niño-Infinity, is created by averaging only the positive
SST anomalies in the equatorial Pacific. For consistency
with our method, we selected the years when the NiñoInfinity index exceeded one standard deviation threshold
persistently for 6 months. 15 out of 18 years classified as
Niño-Infinity events were associated with positive SST
anomaly in tNA during MAM. The remaining three events
that resulted in negative MAM SSTA in tNA experienced
anomalously cold conditions in the previous season (not
shown). Therefore, the Niño-Infinity method also supports
our results regarding the precondition of the tNA in DJF
both during Eastern Pacific El Niño and El Niño Modoki.
13
1850
To investigate this further, we use a multiple linear
regression analysis to assess the potential predictability of
the tNA in MAM by the following factors (or predictors):
the precondition of SST anomalies over the tNA in DJF, the
strength of Niño3, Niño3.4 and EMI in DJF and the magB
nitude of EMISSTA
in DJF. Table 3 shows the correlation
coefficient between the observed MAM tNA and the MAM
tNA predicted with the linear model constructed with the
predictors.
The strongest predictor of the tNA in MAM is the SST
anomalies in the previous season, which is expected given
the thermal memory of the ocean. DJF Niño3.4 is the second
most important predictor for MAM tNA. When they are both
considered in the linear model, DJF tNA and DJF Niño3.4
markedly enhances the predictability for MAM tNA. The
DJF EMI provides some predictability for MAM tNA, however to a lesser degree than the Niño3.4. Interestingly, when
the EMI is decomposed into the regions A and B (see Fig. 1),
B
damps the predictive power
it becomes clearer that EMISSTA
A
B
of EMISSTA. As DJF EMISSTA is positively correlated with
MAM tNA, a cooling in the eastern Pacific in DJF would be
associated with a cooling in the tNA in MAM. However, it
is currently unclear whether the reduced predictive power
A
B
of EMISSTA
by EMISSTA
is a statistical artifact of simply
damping the Niño3.4 region SSTA in the EMI, or whether
it represents a truly damped atmospheric response due to the
B
competing effects of the Niño3.4 warming and the EMISSTA
C
cooling. Region C in the EMI (EMISSTA) is not considered
here as it is non-significantly correlated to MAM tNA and
does not add predictability for the remote region.
The results so far confirm that a warm SST anomaly in
the Niño3.4 region in conjunction with the precondition of
the tNA SST in DJF has a fundamental role in establishing the tNA SST warming in the following season. The
multilinear regression analysis also suggests that the SST
B
anomalies observed in EMISSTA
during EM events act to
reduce predictability of the central Pacific warming. It is
however uncertain if the SST cooling in the eastern Pacific
interferes in the teleconnections or is just a result of the statistics used here, where linear assumption is made. In order
to investigate whether this is a thermodynamic response
of the atmosphere to a zonal gradient of SST anomalies in
the equatorial Pacific or an artifact of the statistics, we will
further examine the atmospheric circulation response to the
equatorial Pacific SST warming using a suite of AGCM
experiments in the next section.
4 Sensitivity of teleconnections to Pacific SST
warming
In this section we examine the importance of the strength
and location of the maximum SST anomalies in the
13
A. S. Taschetto et al.
equatorial Pacific for the tropical North Atlantic teleconnections using the set of idealized experiments WPac,
CWPac, CEPac and EPac (Table 2). Figure 5 shows the
simulated response of upper-level winds and geopotential
height at 200 hPa to the varying locations of 1 °C SST perturbations along the equatorial Pacific. The perturbed SST
warming on the equator creates an area of low pressure
above it that drives an inflow toward the pressure gradient. Therefore, convergence near the surface and upward
motion are generated above the SST forcing. The ascending motion enhances deep convection producing diabatic
heating in the troposphere. The response of tropical atmosphere to diabatic heating occurs as in the Gill–Matsuno
theory (Matsuno 1966; Gill 1980). The low-level easterlies
generated east of the heating source are associated with
Kelvin waves and the Walker circulation. The westerlies to
the west of the forcing are associated with planetary waves
that manifest as a pair of anticyclonic (cyclonic) anomalies in the upper (lower) troposphere off the equator in
accordance with vorticity conservation theory. The upperlevel highs off the equator are seen in all the experiments
in Fig. 5, e.g. distinctly during MAM in the EPac case
(Fig. 5h). As Kelvin waves propagate faster than planetary
waves, the information is carried farther eastward than to
the west. This results in the tropical tropospheric warming
extending eastward through South America and into the
Atlantic Ocean even in the experiments forced with distant
SST perturbations, i.e. CWPac and WPac (Fig. 5a–d). The
mid-latitude atmospheric response to the pair of anomalous
anticyclones either side of the equator is a quasi-stationary
Rossby wave train arching toward North America. This is
seen in all experiments, regardless of the warm SST anomaly location (it can be seen clearly, e.g., during MAM in the
CEPac experiment; Fig. 5f).
It is important to note that the anomalous 200 hPa height
centers display modulation by the seasonal cycle (Yulaeva
and Wallace 1994), which is dependent on the climatological SST background and the mean flow. This modulation
allows for an asymmetric response about the equator in
some cases (e.g. stronger anticyclone center in the southern hemisphere, Fig. 5g) despite the equatorial symmetry
of the forcing SSTA. In our experiments, the atmospheric
response to the equatorial heating source is larger in DJF
than in MAM (Fig. 5).
Zonal variations of the mean flow are known to strongly
affect the location and strength of teleconnections (Branstator
1983; Karoly 1983; Hoskins and Ambrizzi 1993). The atmospheric response to the same 1 °C warming along the equatorial
Pacific produces varying teleconnection strengths as seen in
Fig. 5. In principle, one would expect a stronger atmospheric
response to a given SST warm anomaly applied in the western Pacific than the same forcing applied in the eastern Pacific
because the climatological background SST is already high in
1851
How sensitive are the Pacific–tropical North Atlantic teleconnections to the position and…
MAM
2
10 m/s
50 N
20oN
o
(a)
10 S
(b)
2
2
10 m/s
o
CWPac1.0
CWPac1.0
10 m/s
50 N
o
20 N
o
(c)
10 S
(d)
2
2
10 m/s
o
50 N
CEPac1.0
CEPac1.0
10 m/s
o
20 N
10oS
(e)
(f)
2
10 m/s2
10 m/s
o
50 N
EPac1.0
EPac1.0
2
10 m/s
o
WPac1.0
WPac1.0
DJF
o
20 N
o
(g)
o
100 E
10 S
o
160 W
−30
o
o
60 W
−15
(h)
100 E
0
15
o
160 W
o
60 W
30
Fig. 5 200 hPa wind and geopotential height differences between the
experiments forced with 1 °C SST anomaly and the control run. Grey
contours and black vectors represent statistically significant values
at the 95 % confidence level according to a two-tailed Student t test.
Green boxes show the location of the SST anomaly forcing. Left DJF.
Right MAM. a, b WPac1.0, c, d CWPac1.0, e, f CEPac1.0, and g, h
EPac1.0
the warm pool. Therefore, the WPac experiment would likely
drive the largest atmospheric response. However, Fig. 5 shows
that this is not the case, as the strongest impact on atmospheric
circulation is seen when the forcing is located around the dateline (i.e. CWPac) and not in the warm pool (i.e. WPac). This is
consistent with the non-linear response to ENSO reported by
Frauen et al. (2014). The link between surface warming and
atmospheric teleconnections is not obvious as the SST forcing needs to translate into deep convection and diabatic heating necessary for exciting the upper-tropospheric response.
Furthermore, the relationship between SST warming and
deep convection is non-linear. For instance, Graham and Barnett (1987) found that deep tropical convection rarely occurs
over water colder than 27.5 °C, however further increases in
that SST have only little effect on convection strength. Additionally, Zhang (1993) showed that deep convection is rarely
observed for SST below 26 °C, increases from 26 °C to 29.5–
30 °C, and then decays for SST above 30 °C. This is clearly
seen in the WPac experiment where the largest precipitation
does not align with maximum SST (Fig. 6a). Thus, the largest SST does not necessarily produce the greatest impact on
atmospheric circulation. In addition, the SST-deep convection relationship also depends on several processes, such as
the large-scale surface moisture convergence induced by the
SST gradients (Graham and Barnett 1987; Kiladis et al. 1989).
Despite high SST in the Pacific warm pool, winds are generally weaker there due to less spatial variation and thus weaker
SST gradients. On the other hand, the stronger relative SST
gradients in the eastern Pacific favor anomalous wind convergence, so deep convection occurs there over a relatively lower
SST threshold compared to the warm-pool region for the same
SST (e.g. Taschetto et al. 2010).
Therefore, the location of the equatorial SST forcing is
essential for determining the strength of the local atmospheric response in the Pacific. The position of SST warming is also important in producing the remote teleconnections that eventually lead to the warming of the tNA region.
This is evidenced by the fact that the Pacific teleconnections through the North Atlantic mid-latitudes are displaced
westward from the EPac to WPac experiment (Fig. 5). We
emphasize here that these are sensitivity experiments forced
by idealized SST anomalies and that their response may not
be representative of observed El Niño events. However,
the idealized experiments can be instructive for evaluating
the overall sensitivity of atmospheric circulation to applied
uniform magnitude SST anomalies. Furthermore, as will be
13
1852
SST and Precipitation
SST & 850hPa Zonal Wind
(a)
20N
(b)
10N
J
10S
A
20S
O
J
F
M A
M
J
J
A
S
O
N
100E
150E
160W
(c)
20N
110W
(d)
J
10S
A
20S
O
J
F
M A
M
J
J
A
S
O
N
100E
150E
160W
(e)
20N
110W
(f)
J
10S
A
20S
O
J
F
M A
M
J
J
A
S
O
N
100E
150E
160W
(g)
20N
110W
(h)
D
F
A
0
J
10S
A
20S
EPac1.0
10N
O
J
F
M A
M
J
J
22
shown later, the modeled teleconnection patterns approach
the observed patterns when more realistic SST anomalies
are considered in the AGCM simulations.
To investigate how important is the strength of the SST
warming for the Pacific–North Atlantic teleconnections, we
analyze the response of the tropospheric temperature mechanism. Figure 7 shows the response of the DJF and MAM
200 hPa tropospheric temperature over an area extending
10° latitude and 20° longitude from the SST forcing. For
example, the boxed region for the WPac experiment, which
has SSTA applied to 120°E–160°E, 10°S–10°N, covers
100°E–180°E, 20°S–20°N. This area is chosen to account for
13
F
A
0
20
D
CEPac1.0
10N
30S
D
F
A
0
30S
D
D
CWPac1.0
10N
30S
D
F
A
0
30S
D
D
WPac1.0
Fig. 6 Left latitudinal variation
of the annual cycle of SST
averaged over the forcing
domain of the idealized experiments. Hatched areas denote
precipitation over 10 mm/
day. Right annual cycle of SST
averaged between 5°S and 5°N
for each idealized experiment.
Hatched areas denote 850 hPa
zonal wind anomaly averaged
between 5°S and 5°N of greater
than 2 m/s. Dashed blue lines
in both left and right panels
represent the 28 °C isotherm.
Top to bottom panels show (a,
b) WPac1.0, (c, d) CWPac1.0,
(e, f) CEPac1.0, and (g, h)
EPac1.0, respectively
A. S. Taschetto et al.
A
S
O
24
N
100E
150E
26
160W
28
110W
30
the shape of the Gill–Matsuno response. As expected, each
experiment shows that the larger the forcing, the stronger the
tropospheric response. However, the response of the tropical warming is non-linear with the varying strengths of the
SST forcing, particularly during DJF. A comparison among
the experiments reveals that for a 0.5 °C SST anomaly, the
DJF tropospheric warming in WPac and CWPac are of similar magnitude, while there is little warming in the CEPac
and virtually no response in the EPac experiment. However,
when the magnitude of the warm SST anomaly increases to
1.5 °C, the response in the CWPac clearly stands out from
the other experiments (Fig. 7a).
How sensitive are the Pacific–tropical North Atlantic teleconnections to the position and…
(a) DJF 200hPa Temperature
3
0.5
0.75
1.0
1.5
2
Celsius
Observations
2.5
1.5
1
EP
(b) MAM 200hPa Temperature
3
Observations
2.5
0.5
0.75
1.0
1.5
2
Celsius
EM
ENMOD
ELNINO
MODOKI
ECEPac
EPac
CEPac
CWPac
0
WPac
0.5
1.5
1
EP
EM
ENMOD
ELNINO
MODOKI
ECEPac
EPac
CEPac
CWPac
0
WPac
0.5
Fig. 7 200 hPa tropospheric temperature anomaly response to varying SST forcing in (a) DJF and (b) MAM for the experiments and
observations (EP and EM). EP Eastern Pacific El Niño, EM El Niño
Modoki. Temperature is averaged over the SST forcing plus 10° latitude/20° longitude band to account for the Gill–Matsuno response in
the atmosphere
Interestingly, the simulated tropospheric temperature
varies seasonally and reveals a more linear response over
CWPac in MAM than in DJF (Fig. 7b). The reason why
the atmosphere responds so strongly to a surface heating
around the dateline region in DJF but less strongly during
MAM is related to the climatological background in this
region. During boreal winter, the ITCZ in the central-west
Pacific moves southward while the South Pacific Convergence Zone strengthens in the Southern Hemisphere
(Fig. 8c). The equatorward shift of the ITCZ during the
northern winter months is conducive for the development
of increased deep convection and heavy rainfall in the
central west Pacific. The anomalously warm SST in the
central west Pacific enhances the supply of latent heat to
the overlying atmosphere, thereby optimizing the conditions for enhanced deep convective processes that occur in
the ITCZ. In addition, the idealized SST forcing imposed
around the dateline in the CWPac experiment drives a
1853
further southward displacement of the ITCZ over the
region (Fig. 8a, b), intensifying deep convection right over
the anomalous warming. This results in a relatively strong
DJF tropospheric response in the CWPac experiment even
for an SST threshold as small as 0.5 °C (Fig. 7a). This supports the result from observations (Fig. 3f) that weak El
Niños, such as EM events, may be able to produce significant tropospheric warming in the tropical Pacific.
The anomalous southward shift of the ITCZ during
El Niño Modoki events is also clear in the observations
(Fig. 8c). During MAM, the ITCZ draws back northward
naturally reducing deep convection over the strongest
underlying SST warming in the central Pacific (Fig. 8a).
This results in a weakened atmospheric warming and circulation response in MAM compared to DJF in the CWPac
experiment (Figs. 5c–d, 7). Therefore, due to the seasonal
cycle of the ITCZ, the tropospheric temperature mechanism
naturally weaken from boreal winter to spring, resulting in
a reduced teleconnection over the tNA (Fig. 9) even in the
presence of a persistent SST anomaly in the central-western
Pacific. This is not the case for the EPac and CEPac experiments, where the teleconnections continue to grow through
MAM (Figs. 7b, 9). In those experiments, the atmospheric
response appears to be less dependent on the background
circulation. The simulated ITCZ over those regions is
located north of the SST anomaly forcing (Fig. 8b). The
SST warming however produces a strong pressure gradient that drives equatorial easterly wind anomalies toward
the forcing region particularly from February to April when
the climatological SST is increased over the eastern Pacific
(Fig. 6g, h). Therefore, the anomalous SST in conjunction
with strong low-level wind convergence and the lower relative SST threshold for deep convection in the cold tongue
compared to the warm pool region are ideal factors for
the persistence of teleconnections through MAM in the
EPac experiment. In the CEPac experiment, the edge of
the warm pool is extended eastwards to approximately
170°W–140°W especially during boreal spring (as shown
by the shift of the 28 °C isotherm in Fig. 6e) when the
background SST is warmest at the equator there. Perhaps
a nonlinear response would occur for larger SSTA forcing
over the CEPac region. The ITCZ is displaced southward
when the SSTA forcing is 1.5 °C over the CEPac region
(not shown), especially in February–April when climatological SST are warmest at the equator. Thus, for a SSTA
forcing similar to extreme El Niño events as in 1982–83
and 1997–98 we would likely see a nonlinear intensification of the atmospheric teleconnections for the CEPac
experiment.
Here, we analyze the response of the atmospheric bridge
process via the PNA index to investigate how important is
location of the SST warming is for the Pacific–North Atlantic teleconnections. As, for instance, the preference for the
13
1854
A. S. Taschetto et al.
(a) Simulated Precipitation averaged over 160E−160W
15
12
10
8
latitude
10
6
5
4
CTRL
CWPac0.5
CWPac0.75
CWPac1.0
CWPac1.5
0
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
2
Nov
(b) DJF Simulated Precipitation
30oN
0
12
10
o
15 N
8
6
0o
4
2
15oS
120oE
160oE
160oW
CNTRL
120oW
80oW
MODOKI
ENMOD
(c) DJF Observed Precipitation
o
0
12
30 N
10
15oN
8
6
o
0
4
2
15oS
120oE
160oE
160oW
120oW
80oW
CLIM
Fig.  8 a Seasonal cycle of precipitation averaged over the CWPac forcing region (160°E–160°W) simulated in the CTRL experiment. Position
of maximum precipitation as a proxy for the ITCZ in the CTRL (black
line), CWPac0.5 (blue), CWPac0.75 (green line), CWPac1.0 (pink line)
and CWPac1.5 (red line). b DJF precipitation simulated by the CTRL
13
0
EM
simulation. Black dashed line represents maximum precipitation in
the CTRL; blue dashed line in the MODOKI; red dashed line in the
ENMOD experiments. c DJF precipitation from GPCP dataset. Black
dashed line is the maximum precipitation in climatology (CLIM) and
the blue dashed line is during El Niño Modoki (EM) events
1855
How sensitive are the Pacific–tropical North Atlantic teleconnections to the position and…
tNA 200hPa Temperature Difference (MAM minus DJF)
0.5
0.4
ELNINO
ECEPac
−0.1
CEPac1.0
EPac1.0
ENMOD
0
MODOKI
0.1
CWPac1.0
0.2
WPac1.0
Celsius
0.3
−0.2
WEST SSTA
Experiments
EAST SSTA
Experiments
Fig. 9 Change in seasonal 200 hPa temperature over the tropical
North Atlantic (see Fig. 1a for region) from DJF to MAM. For easier
visualization, experiments are grouped into those perturbed with SST
anomalies in western Pacific and eastern Pacific
(a) DJF 200hPa PNA
300
0.5
0.75
1.0
1.5
200
Celsius
Observations
250
150
100
50
ENMOD
ELNINO
EM
EP
ENMOD
ELNINO
EM
EP
MODOKI
ECEPac
EPac
CEPac
CWPac
−50
WPac
0
(b) MAM 200hPa PNA
300
Observations
250
0.5
0.75
1.0
1.5
200
Celsius
150
100
50
MODOKI
ECEPac
EPac
CEPac
−50
CWPac
0
WPac
atmosphere to respond strongly to the underlying SST anomaly around the dateline does not necessarily translate into an
equally strong response that reaches the remote North Atlantic.
The distant location of the SST forcing produces a westward
shifted PNA pattern (Fig. 5b) that may not be favorable for
warming the tNA basin. The shift in the PNA associated with
the tropical heating sources of El Niño and La Niña has been
described in previous studies (e.g. Hoerling et al. 1997). Figure 10 shows the response of the PNA to the varying locations
and strengths of SST warming (see Fig. 1 for the definition
of the PNA index). Although the PNA pattern is an independent mode of climate variability driven by internal atmospheric
dynamics, it is modulated by external factors such as warming
events in the tropical Pacific (e.g. Hoerling and Kumar 2002).
The internal variability of the PNA is evident in the non-linear
response of the idealized experiments (Fig. 10). Nevertheless,
there is a preference for a stronger response of the PNA with
an SSTA located in the CEPac region (Fig. 10), as the forcing
perturbs the circulation over the exit region of the East Asian
jet stream, where the main center of action is located (Fig. 5c).
The PNA response in the idealized experiments is stronger
during DJF and decreases considerably in MAM (Figs. 5, 10),
which is consistent with the natural migration of the centers of
action with changes in the circumpolar vortex over the course
of the annual cycle. The PNA reduction in MAM is particularly evident in the experiments forced by SSTA located in the
western side of the Pacific (i.e. WPac and CWPac, Fig. 10),
consistent with the effect of the seasonal migration of the
ITCZ discussed above.
However, the SST spatial pattern of observed El Niño
events is more complex than those applied in the idealized
Fig. 10 200 hPa PNA response to varying SST anomaly forcing in
the experiments and observations (EP and EM) during (a) DJF and
(b) MAM. EP Eastern Pacific El Niño, EM El Niño Modoki
experiments. In observations, the warm SST anomalies that
occur during El Niño years are about three times larger in
the eastern than the central-western Pacific. To account for
a magnitude of forcing closer to the observed, we examine
another set of simulations here referred to as semi-realistic experiments (see Table 2): one forced by a +3 °C SST
anomaly over the EPac plus CEPac region (ECEPac); and
another forced by an idealized Modoki pattern as defined
by EMI (MODOKI). As expected, the stronger SSTA magnitude in the eastern Pacific simulated in ECEPac produces
a larger response in the 200 hPa geopotential height compared to the semi-realistic MODOKI (Fig. 11). Nevertheless, the semi-realistic Modoki forcing is still able to drive
mid-latitude teleconnections in the North Pacific and North
Atlantic during DJF (Fig. 11c).
Curiously, the remote response in MODOKI disappears
from the North Atlantic by MAM, but it is still present in
the ECEPac experiment (Fig. 11b, d). This is similar to the
simulations with the idealized forcing, i.e. while the remote
teleconnections over the North Atlantic are weakened
13
1856
ECEPac
o
50 N
o
20 N
10oS
100oE
2
30 m/s
160oW
−60
0
160oW
60
(c) DJF
60oW
2
30 m/s
120
(d) MAM
o
MODOKI
MODOKI
50 N
o
20 N
o
10 S
2
10 m/s
160oW
60oW
−30
100oE
−15
(a) DJF
0
160oW
15
60oW
30
(b) MAM
20 m/s2
2
10 m/s
20 m/s2
ELNINO
ELNINO
o
50 N
o
20 N
10oS
100oE
160oW
100oE
60oW
−120
−60
(c) DJF
0
160oW
60
60oW
120
(d) MAM
2
10 m/s
2
10 m/s
o
ENMOD
ENMOD
50 N
o
20 N
10oS
o
100 E
o
o
160 W
o
60 W
−60
during MAM compared to the previous DJF season in the
CWPac and WPac experiments, the signal remains strong
in the EPac and CEPac cases, regardless of the magnitude
of the SST forcing (Figs. 5, 6, 7, 8, 9). A previous study
by Lee et al. (2008) suggests that the atmospheric bridge
to the North Atlantic fails if an El Niño event terminates
before April. While our results corroborate Lee’s findings,
we further find that even with the persistence of an EM
signature, the Pacific–North Atlantic teleconnections vanish by MAM. As discussed above, this is due to seasonal
change in the mean background flow that does not favor
remote mid-latitude teleconnections in the northern hemisphere, in conjunction with the northward shift of the ITCZ
that weakens deep convective processes around the dateline
in the equatorial Pacific.
13
100oE
60oW
−120
100oE
Fig. 12 200 hPa geopotential
height response for the experiments forced by the observed
SST anomaly composite of
(a, b) Eastern Pacific El Niño
(ELNINO) and (c, d) El Niño
Modoki (ENMOD). (a, c) DJF.
(b, d) MAM. Grey contours and
black vectors represent statistically significant values at the
95 % confidence level according
to a two-tailed Student t test
(b) MAM
(a) DJF
ECEPac
Fig. 11 200 hPa geopotential
height response in the experiments forced by (a, b) +3 °C
SST anomaly in the ECEPac
region and (c, d) semi-realistic
MODOKI with maximum
warming of 1 °C. (a, c) DJF. (b,
d) MAM. Grey contours and
black vectors represent statistically significant values at the
95 % confidence level according
to a two-tailed Student t test.
Green boxes show the location
of the SST anomaly forcing
A. S. Taschetto et al.
−30
o
100 E
0
160 W
30
o
60 W
60
To further investigate the response of the remote teleconnection to even more realistic SSTA patterns, we analyze the experiments forced by the observed composites of
EP and EM events (ELNINO and ENMOD, respectively).
Figure 12 reveals a notably weaker atmospheric response to
an EM pattern compared to that from an EP El Niño, both
in the tropical tropospheric warming in the Pacific (Fig. 7)
and in the PNA index (Fig. 10). This occurs due to the difference in the magnitude of the SSTA forcing, where the
EP El Niño composite is about three times larger than the
EM pattern. Interestingly, these experiments also support
the weakening of the teleconnections to the North Atlantic
by MAM after the peak of EM events (Fig. 12c, d).
An interesting point to note is that the pattern of the teleconnections to the tNA basin gradually improves as the
How sensitive are the Pacific–tropical North Atlantic teleconnections to the position and…
complexity of the SSTA forcing increases i.e., from the idealized experiments with warming in box patterns, through
the semi-realistic experiments to the observed SSTA patterns (Figs. 5, 11, 12). The PNA pattern simulated in the
idealized experiments is stronger in the CEPac and CWPac
(Fig. 10a) because they excite a stronger pair of anticyclonic and cyclonic circulations over the tropical and subtropical North Pacific sector (Fig. 5). The propagation of the
PNA signal to the remote tropical North Atlantic, however,
is better simulated in the EPac experiment and improves in
the ECEPac to ELNINO experiment (see center of negative geopotential height over southeastern North America,
Figs. 5a, b,11a, b,12a, b). The PNA signal over southeastern North America (Figs. 11b, 12b) simulated in the semirealistic MODOKI and the observed EM composite experiments is clearly weaker than the semi-realistic ECEPac and
the observed EP composite experiments.
Note finally that while the CWPac experiment drives a
strong PNA signal during DJF (Figs. 5e, 10a), the semirealistic MODOKI has no effect on the PNA pattern
(Figs. 10a, 11c). This supports our hypothesis that the
cooling signal on both sides of the equatorial Pacific associated with El Niño Modoki events counteracts the atmospheric perturbation excited by the warming over the central
Pacific. Moreover, it supports the finding that the observed
B
region plays a role in modulating
cooling in the EMISSTA
the Pacific–tropical North Atlantic teleconnections during
EM events.
5 Summary and conclusions
We investigate the Pacific–tropical Atlantic teleconnections in the context of the strength and location of SSTA
warming between different types of El Niño events. We use
observations from HadISST and the NCEP reanalysis data
spanning December 1949 to November 2012, GPCP from
1979, in conjunction with a suite of numerical experiments
forced by idealized and observed SST anomalies in the
tropical Pacific.
Previous studies have shown that EP El Niños drive
strong atmospheric teleconnections to the tropical Atlantic
via the atmospheric bridge and a tropospheric temperature
mechanism that leads to a warming of the tropical North
Atlantic basin during MAM after the peak of the Pacific
event. However, the tropical North Atlantic experiences
near neutral SST conditions in the presence of an El Niño
Modoki signature in the Pacific (Amaya and Foltz 2014).
The reason why tropical North Atlantic SST is relatively
insensitive to El Niño Modoki events is unclear. In this
study, we find that the preconditioning in tNA in boreal
winter, known to be an important factor during Eastern
Pacific El Niños (e.g. Giannini et al. 2004), also plays a
1857
strong role during El Niño Modoki events. Additionally, we
attempt to address whether the weak teleconnections associated with El Niño Modoki could be related to the weak
strength, the location of the maximum SST anomalies or
the cooling SST in the eastern Pacific that occur in those
events.
The main conclusions of this study can be summarized
as follow:
1. Although El Niño Modoki events are able to drive
weak tropospheric temperature anomalies, we propose
that the atmospheric bridge is inefficient essentially
due to a weaker and westward shifted PNA pattern that
moves the teleconnection pattern farther away from the
North Atlantic, thus weakening the influence from the
Pacific to the Atlantic.
2. We suggest that this inefficiency occurs because the
cooling developed in the eastern Pacific region during
El Niño Modoki events counteracts the atmospheric
response to the warming over the central Pacific. The
evidence for this conclusion are as follows:
(a)When forcing the AGCM with the same idealized
SSTA strength along the equator, the region around the
dateline (where El Niño Modoki warming is located)
produces the strongest atmospheric response in the
Pacific compared to the eastern and western Pacific
regions, even for relatively small magnitudes of the
forcing (e.g. 0.5 °C).
(b)However, when forcing the AGCM with the semirealistic El Niño Modoki pattern (which includes the
warming flanked by cooling regions), the Pacific–tropical Atlantic teleconnections are significantly weakened
compared to the idealized CWPac warming.
3. We note the importance of the background conditions
for generating teleconnections during El Niño Modoki
events in the model. In particular, the reason why the
CWPac experiment produces the strongest teleconnections is due to the convective activity associated with
the ITCZ during DJF over the SSTA forcing region.
The extra heat supply from the SSTA forcing enhances
deep convection and diabatic heating, leading to an
overly strong atmospheric response.
4. When the ITCZ convective activity decreases during
MAM, the atmospheric response in the CWPac is also
reduced, for the same strength of SSTA forcing as in
DJF. This suggests that even in the presence of an El
Niño Modoki pattern during MAM, the atmospheric
teleconnections gradually weaken by MAM. On the
other hand, the EP El Niño teleconnections remain
strong during MAM, as it is not as strongly dependent on the background atmospheric circulation as in the
EM case, but on the stronger underlying SST conditions. In reality, however, EP El Niños tend to termi-
13
1858
nate during MAM as the westerly wind anomalies in
the central west Pacific shift south of the equator thus
weakening the Bjerknes feedback on the equator (Harrison and Vecchi 1999; Spencer 2004; McGregor et al.
2012) and discharging equatorial region warm water
volume (McGregor et al. 2012, 2013).
5. The evidence shown above (i.e. the strong atmospheric
response to a weak SST forcing and the role of the
background conditions around the dateline) leads us
to conclude that location rather than strength of SST
warming in the central-western Pacific is more important for producing atmospheric teleconnections that
affect the tropical Atlantic. However, the cooling in the
eastern Pacific during El Niño Modoki events plays a
role in weakening this teleconnection.
It is finally important to highlight a few cautionary notes
about this study. Firstly, it involves numerical experiments
with an AGCM where there is no feedback with the ocean.
Previous studies have discussed the role of the ocean for
producing the correct teleconnections with the tropical
Atlantic (Chang et al. 2006, Rodrigues et al., 2011; Luebbecke and McPhaden 2012). While the oceanic feedback
may be important, it also adds complexity to the simulations that complicates the interpretation of the results. For
the questions proposed here, we found that the sensitivity
experiments performed with the AGCM were adequate.
In addition, the use of a coupled climate model for assessing the Pacific–North Atlantic teleconnections would not
guarantee a better approach for the purpose of this study,
since biases in ENSO amplitude and spatial pattern (e.g.
Taschetto et al. 2014) and SST biases in the eastern tropical Atlantic (Richter and Xie 2008; Richter et al. 2014)
can produce errors in this relationship. Coats et al. (2013)
show that the fidelity of the ENSO-North America teleconnections in coupled climate models differ considerably in
their spatial patterns and strength, and suggest that any
analysis that assumes stationarity of the observed teleconnections (e.g. seasonal forecasting) would benefit from
AGCM experiments forced by SST. Zou et al. (2014) further demonstrate that CMIP5 models are not able to simulate the Pacific–North American pattern to central Pacific
El Niños due to biases in the associated Pacific SST
anomalies.
Secondly, the experimental design imposes a constant
fixed SST anomaly pattern superimposed onto the seasonal cycle in the tropical Pacific. In nature, SST anomalies
evolve with the course of El Niño events, generally developing in boreal autumn, peaking in the end of the calendar year and phasing out during boreal spring of the following year. While our experimental design does not allow
the natural evolution of El Niño types, it provides useful
information about non-linear interactions between the SST
13
A. S. Taschetto et al.
anomalies and the seasonal cycle. We show that even in the
presence of a persistently strong warming located around
the dateline, the background seasonal atmospheric circulation in MAM acts to diminish the tropospheric temperature
mechanism. Thus, the weakening of the remote teleconnections originated from a central-western Pacific warming
can arise solely in response to the mean seasonal cycle with
no changes in SST anomalies. Conversely, the tropospheric
temperature mechanism strengthens in MAM with a constant SST anomaly in the eastern equatorial Pacific due to
the stronger underlying mean SST. Therefore, the experimental design also demonstrates that the Pacific–tropical Atlantic teleconnections to an eastern Pacific warming
depends strongly on the underlying seasonal cycle of SST.
Thirdly, as previously mentioned, the data period and
selection criteria for El Niño events can lead to slightly
different results to those presented here. While our study
includes the period of SST data with more reliable measurements (from 1949), it also limits the number of El Niño
events in our analysis. Thus, the small sample size for the
observed events does not allow for statistically significant
differences in the Atlantic response to EP and EM El Niño
events. The numerical experiments, however, supports our
findings with observations, thus alleviating the issue of the
limited number of observed El Niños. Nevertheless, the main
conclusion that the Pacific–tropical Atlantic teleconnections
are weaker in the presence of an El Niño Modoki event is a
robust result, regardless of different methodologies.
Finally, as mentioned in Sect. 3, the precondition of
the tNA SST in DJF during El Niño Modoki events is an
important factor that can determine the resultant signal
in the following season. This factor is commonly known
from previous studies (Giannini et al. 2004) for EP El Niño
events; here we show that the precondition of tNA SST is
particularly important in El Niño Modoki cases.
Acknowledgments This research was supported by the Australian
Research Council (ARC) including the ARC Centre of Excellence
for Climate System Science (ARCCSS). This work is also part of
the research conducted by the INCT-MC, INCT-Mar COI, and Rede
CLIMA. The numerical experiments were undertaken on the NCI
National Facility at the ANU, Australia, via the provision of computing resources. Use of NCAR’s CCSM3 model is gratefully acknowledged. We thank all the Institutions responsible for the observations
and reanalysis products for having made their data available. Observational and reanalysis data provided by the NOAA/OAR/ESRL
PSD, Boulder, Colorado, USA, is from their web site at http://www.
esrl.noaa.gov/psd/. We thank Kris Karnauskas and one anonymous
reviewer for their comments on the manuscript.
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