Download A Gill-Matsuno-type mechanism explains the tropical Atlantic

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY
Q. J. R. Meteorol. Soc. 135: 569–579 (2009)
Published online 9 April 2009 in Wiley InterScience
(www.interscience.wiley.com) DOI: 10.1002/qj.406
A Gill–Matsuno-type mechanism explains the tropical
Atlantic influence on African and Indian monsoon rainfall
F. Kucharski,a * A. Bracco,b J. H. Yoo,a A. M. Tompkins,a L. Feudale,a P. Rutic and
A. Dell’Aquilac
a
The Abdus Salam International Centre for Theoretical Physics, Earth System Physics Section, Trieste, Italy
b
EAS, Georgia Institute of Technology, Atlanta, USA
c
ENEA, Rome, Italy
ABSTRACT: Recent studies using coupled atmosphere–ocean models have shown that the tropical Atlantic has a
significant impact on the Indian monsoon. In this article, the observational basis for this teleconnection is examined
and the physical mechanism responsible for bridging sea-surface temperatures (SSTs) in the Atlantic and precipitation over
India is investigated with idealized atmospheric general circulation model (AGCM) experiments in which constant SST
anomalies are prescribed and ‘switched on’ in the tropical Atlantic region. A simple Gill–Matsuno-type quadrupole response
is proposed to explain the teleconnection between the tropical Atlantic and the Indian basin, with an enforcement of the
eastward response likely due to nonlinear interactions with the mean monsoon circulation. The simplicity of this mechanism
c 2009 Royal Meteorological Society
suggests the reproducibility of this result with a broad range of AGCMs. Copyright KEY WORDS
climate variability; African monsoon; Indian monsoon; teleconnection mechanisms
Received 21 August 2008; Revised 1 December 2008; Accepted 19 February 2009
1.
Introduction
Sea-surface temperature (SST) anomalies in the tropical
Atlantic affect interannual rainfall variability over Africa.
As shown by, for example, Trzaska et al. (1996), Janicot
et al. (1998), Fontaine et al. (1998), Vizy and Cook
(2001), Giannini et al. (2003) and Reason and Rouault
(2006), there is a direct correlation between ocean
temperatures and precipitation along the Gulf of Guinea
coast. More recently, Kucharski et al. (2007, 2008a)
(referred to as K2007/8 in the following) have found that
the influence of tropical Atlantic SSTs extends to precipitation over India on interannual time-scales, contributing
to the decadal modulation of the El Niño Southern Oscillation (ENSO)–Indian monsoon relationship, according
to which a weaker than normal monsoon precedes peak
El Niño conditions and vice versa during summers
preceding La Niña events. K2007/8 have shown that the
atmospheric general circulation model (AGCM) in this
study, coupled to an ocean model in the Indian basin
and forced by imposed SSTs elsewhere, can simulate
a dominant portion of the Indian monsoon interannual
variability, with a 0.62 correlation between modelled
rainfall and Climate Research Unit (CRU; New et al.,
1999) data over India for the period 1950–1999 only if
observed tropical Atlantic SST anomalies are included.
Before 1975, the equatorial Atlantic SSTs were slightly
∗
Correspondence to: F. Kucharski, The Abdus Salam International
Centre for Theoretical Physics, Earth System Physics Section, Strada
Costiera 11, 34014 Trieste, Italy.
E-mail: [email protected]
c 2009 Royal Meteorological Society
Copyright warmer than climatological values, corresponding to positive ENSO events, and contributed to reinforcing the El
Niño–monsoon anticorrelation. After 1975, on the other
hand, a substantial cooling in the tropical Atlantic Ocean
intensified the monsoonal circulation and thus weakened
the ENSO–Indian monsoon relationship. If climatological
SSTs are imposed over the tropical Atlantic, the simulated El Niño-Indian monsoon anticorrelation remains
constant over the whole 50 year period (see Table 1
in Kucharski et al., 2007) and the correlation between
observed and modelled rainfall over India drops to 0.42.
Here we investigate the physical mechanism by which
south tropical Atlantic SSTs impact precipitation in
adjacent areas with a focus on the implication for seasonal
predictability in remote regions. While the atmospheric
response to a heating anomaly in the tropical Pacific has
been analyzed, e.g. in Jin and Hoskins (1995) (referred to
as JH95 in the following), Lintner and Chiang (2007) and
Seager et al. (2008) by performing targeted integrations,
an analogous study in the Atlantic is currently lacking,
with the exception of a multimodel analysis limited to the
effect of North Atlantic SSTs on the surrounding regions
(Rodwell et al., 2004).
We find that the teleconnection over Africa and the
Indian Ocean can be understood, to a first approximation,
as a simple Gill–Matsuno-type quadrupole response of
the atmosphere to a heating anomaly in the equatorial
Atlantic region (Matsuno, 1966; Gill, 1980). Equatorial
Kelvin waves transport the signal from the heating
region to the east, whereas equatorial Rossby waves
are responsible for the westward propagation. Further
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F. KUCHARSKI ET AL.
supporting K2007/8, we also show that the tropical
Atlantic influence on the Indian monsoon is robust and
physically sound and, as such, potentially reproducible
by AGCMs.
In Section 2 we present observational evidence for
the tropical Atlantic–Indian monsoon teleconnection. The
AGCM used in this study and the numerical experiments
performed are described in Section 3. The analysis of the Figure 1. Composite SST anomaly (EXP1–EXP2), derived from a
results follows in Section 4. Section 5 contains a summary regression of the re-analysis SST dataset provided by the Hadley Centre
on to a tropical Atlantic index (mean JAS SST anomaly in the region
and conclusions.
30◦ W–10◦ E and 20◦ S–Equator). The units are K.
2.
Observational evidence
In K2007/8, observational support for the tropical
Atlantic–Indian monsoon teleconnection has been presented using CRU precipitation data and the All-Indian
Rainfall Index (AIR: Parthasarathy et al., 1995). Furthermore, in an independent analysis using a central India
rainfall index, Yadav (2008; see Figure 5(b) therein)
has shown that the south tropical Atlantic is significantly correlated with the Indian monsoon in non-ENSO
years. Here we extend the analysis to Climate Prediction
Center Merged Analysis of Precipitation (CMAP; Xie
and Arkin, 1997) and Global Precipitation Climatology
Project (GPCP; Adler et al., 2003) precipitation datasets
and to the National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research
(NCAR) wind re-analysis (Kalnay et al., 1996), focusing
on the July-to-September season (JAS).
Following Kucharski et al. (2008a), the Atlantic SST
anomalies significantly correlated with the Indian monsoon rainfall are located between 30◦ W–10◦ E and 20◦ S–
0◦ S, and are usually referred to as the southern tropical
Atlantic (STA) pattern (Huang et al., 2004). The existence
of a teleconnection between STA anomalies and ENSO
has been proposed in several studies (Zebiak, 1993; Latif
and Grötzner, 2004). Recent works, however, pointed out
that ENSO influences the tropical Atlantic mainly north of
the equator (Chang et al., 2006), while SST anomalies in
the southern hemisphere result from air–sea interactions
along the coast of Africa with intensification by local
physical processes, including slow Rossby wave propagation, Ekman pumping and Bjerknes feedbacks (Hu
and Huang, 2007). With a simple correlation analysis,
the occurrence of a stable link between ENSO and STA
anomalies cannot be established. The correlation coefficient (CC) between the STA index (area-averaged SST
anomalies in the STA domain) and the NINO3.4 index
(averaged SST anomalies in the region 190◦ E–240◦ E and
5◦ S–5◦ N) is non-significant over the period 1950–2002
(CC = −0.05), but its magnitude varies from 0.18 over
the period 1950–1979 to −0.42 during the last twenty
years of the record (1980–2002), which is 90% statistically significant (see figure 4 in Kucharski et al., 2007).
The standard deviation of the STA index is about 0.3 K
for both periods, compared with about 0.7 K for the
NINO3.4 index. Figure 1 shows the regression of SSTs
from the HadISST dataset (Rayner et al., 2003) on to
the STA index for the period 1950–2002 in the tropical
c 2009 Royal Meteorological Society
Copyright Atlantic region, multiplied by 2 (SSTs outside the tropical
Atlantic are set to zero in this figure, see Section 3).
Given the strong influence exerted by the ENSO on
the surrounding areas, and in particular over the Indian
basin (e.g. Rasmusson and Carpenter, 1983; Webster and
Yang, 1992; Ju and Slingo, 1995), a first step to isolate the
ENSO-independent contribution of the tropical Atlantic
on the Indian monsoon variability consists of assuming
that the ENSO has a linear impact on STA SSTs. Under
this assumption, we can remove the component linearly
related to the ENSO from the STA index by calculating
the residual time series:
where
STARES (t) = STA(t) − STAENSO (t),
(1)
STAENSO (t) = b NINO34(t).
(2)
b is calculated with a least-squares linear regression
between the STA and Nino3.4 indexes. The standard
deviation of STARES is only marginally reduced with
respect to STA for the period 1980–2002 (0.28 instead of
0.3 K), and the same (0.3 K) over the 1950–2002 interval.
The SST regression on to the STARES index is almost
identical to one on to the full STA index, supporting
the conclusions of Chang et al. (2006). Focusing on
the impact of tropical Atlantic SSTs on precipitation,
Figure 2(a) shows the regression of CRU rainfall on
to the STARES index for the period 1950–2002, while
Figure 2(b) and (c) display the regression of CMAP and
GPCP rainfall for the period 1980–2002, respectively
(CMAP and GPCP are available only after 1979). The
regressions are per standard deviation of the STARES
index. Regions with anomalies that are 90% statistically
significant according to a t-test are shaded. The rainfall
responses in Figure 2 share many common features:
increased rainfall over the Gulf of Guinea coast; reduced
rainfall to the north in the Sahelian region and further to
the east, particularly in the CRU data; reduced rainfall
over west India. For rainfall indexes defined as area
averages in the Indian region (70◦ E–85◦ E and 10◦ N–
30◦ N), the standard deviations for the CRU, CMAP and
GPCP indexes are 1.0, 1.0 and 0.9 mm day−1 , whereas
the averages of the regressions in Figure 2 over the
same regions are −0.38, −0.38 and −0.29 mm day−1 .
Therefore, the contribution of the STARES teleconnection
to rainfall in the Indian region is in the order of 0.4
standard deviations. The rainfall regressions on to the
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GILL RESPONSE TO TROPICAL ATLANTIC SST FORCING
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Figure 3. Correlations of (a) NCEP IMI and (b) NCEP IMIRES with
SSTs from the HadISST dataset for the period 1950–2002. See text for
definition of the indexes. Shading indicates regions of 95% statistically
significant anomalies (positive: orange/light grey, negative: blue/dark
grey). Contour intervals are 0.15. This figure is available in colour
online at www.interscience.wiley.com/journal/qj
variability of which is dominated by the ENSO signal.
To interpret the correlation seen in other regions, we
apply the same technique described above and we define
the residual IMI, IMIRES , as the IMI component that is
not linearly related to ENSO according to
IMIRES (t) = IMI(t) − IMIENSO (t),
(3)
IMIENSO (t) = b NINO34(t).
(4)
where
Figure 2. Regressions of (a) CRU (1950–2002), (b) CMAP (1980–
2002) and (c) GPCP (1980–2002) rainfall on to the JAS STARES index,
as defined in the text. Shading indicates regions of 90% statistically
significant anomalies (positive: orange/light grey, negative: blue/dark
grey). The units are per standard deviation of the STARES index.
Contour intervals are 0.3 mm day−1 . This figure is available in colour
online at www.interscience.wiley.com/journal/qj
Nino3.4 index averaged over the same region are of
comparable magnitude for CMAP and GPCP (−0.34 and
−0.35 mm day−1 , respectively) and 30% larger for CRU
(−0.52 mm day−1 ).
The existence of a teleconnection between the STA
region and the Indian monsoon is further demonstrated
by an analogous analysis performed on the dynamical
Indian monsoon index (IMI). The IMI is defined as the
meridional 850 hPa zonal wind difference averaged over
the domains 40◦ E–80◦ E, 5◦ N–15◦ N minus 60◦ E–90◦ E,
20◦ N–30◦ N, and provides a measure of the Indian
monsoon strength (Wang et al., 2001). Figure 3(a) shows
the correlation coefficients (CCs) of the IMI derived
from the NCEP/NCAR reanalysis with the SSTs from
the HadISST dataset for the period 1950–2002. Shading
indicates a 95% statistically significant correlation
according to a t-test. Unsurprisingly, we find a strong
anticorrelation between the Indian monsoon strength
and the eastern Pacific SST anomalies, the interannual
c 2009 Royal Meteorological Society
Copyright Again, b is calculated with a least-squares linear regression. Figure 3(b) shows the CCs of IMIRES with SSTs.
Clearly, SST anomalies in the Gulf of Guinea display
the largest correlations, while all other regions are characterized by barely statistically significant CCs. Overall,
these results further support the findings of K2007/8.
Even though we removed the component of the STA
index linearly related to the ENSO in the above precipitation regression maps, we cannot rule out the suggestion
that SST anomalies in other regions influence the outcome. The only way to quantify the STA influence on the
Indian monsoon is to perform targeted, idealized experiments that isolate the contribution of the STA anomalies.
3.
Model and experimental design
The model adopted in this study is the International
Centre for Theoretical Physics (ICTP) AGCM (Molteni,
2003). It is based on a hydrostatic spectral dynamical
core (Held and Suarez, 1994), and uses the vorticitydivergence form described by Bourke (1974). The
parametrized processes include short- and long-wave
radiation, large-scale condensation, convection, surface
fluxes of momentum, heat and moisture, and vertical diffusion. Convection is represented by a mass-flux
scheme that is activated where conditional instability
is present, and boundary-layer fluxes are obtained by
stability-dependent bulk formulae. Land and ice temperature anomalies are determined by a simple one-layer
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F. KUCHARSKI ET AL.
thermodynamic model. In this study the AGCM is configured with eight vertical (sigma) levels and with a spectral
truncation at total wavenumber 30. Applications of the
ICTP AGCM can be found in Bracco et al. (2004) and
Kucharski et al. (2006a, 2006b).
The model climatology for boreal summer, the season
in which we concentrate our analysis, is compared with
observations in Figure 4. Figure 4(a) and (b) show the
CMAP and GPCP JAS rainfall and the 925 hPa wind
climatology from the NCEP/NCAR reanalysis for the
period 1980–2002, Figure 4(c) displays the CRU JAS
rainfall and NCEP/NCAR 925 hPa winds over the period
1950–2002, and Figure 4(d) shows the corresponding
climatological fields for the model from 1950–2002.
Overall the ICTP AGCM captures the main features of
precipitation and low-level winds for both the African and
Asian monsoon systems, although the rainfall over Africa
extends too far northward compared with observations.
The Indian monsoon precipitation, on the other hand,
is concentrated over the ocean and is weaker than that
observed over land. This is due to the inability of most
(if not all) AGCMs to represent correctly the relationship
between surface fluxes and SSTs over the Indian basin
(Wang et al., 2005; Wu and Kirtman, 2005; Bracco et al.,
2007). A dramatically improved simulation of the Indian
monsoon can be obtained by regionally coupling the ICTP
AGCM to an ocean model over the Indian basin (Bracco
et al., 2007; K2007/8). In this work, however, we are
interested in keeping the experimental set-up as simple as
possible, to allow for easy reproducibility of the results,
and we do not adopt the coupled configuration.
We conduct five sets of experiments. In the control run,
the ICTP AGCM is forced by climatological SSTs. In
the two further sensitivity experiments, EXP1 and EXP2,
an SST anomaly is superimposed on the climatological
values in the tropical Atlantic, in the region between 30◦ S
and 30◦ N. Following K2007/8, this anomaly has been
derived by computing a regression of the SST on to the
JAS STA index for the period 1950–2002, and is confined
almost entirely to the southern hemisphere (see Figure 1
for twice the anomaly). In Section 2 and in K2007/8 we
have shown that SSTs in this region influence the Indian
summer monsoon, with warmer (cooler) than normal
SSTs favouring a decrease (increase) in precipitation over
India. The derived anomaly is added to the climatological
SSTs in EXP1 to provide a warm anomaly, while it is
subtracted in EXP2 to cool the tropical Atlantic. Applying
anomalies of equal magnitude and opposite sign allows
us to assess the existence of significant nonlinearities in
the response to the tropical Atlantic SSTs. In fact, we
Figure 4. Precipitation and 925 hPa wind climatology for JAS from (a) CMAP and NCEP/NCAR (1980–2002) re-analysis, (b) GPCP and
NCEP/NCAR (1980–2002) re-analysis, (c) CRU and NCEP/NCAR (1950–2002) re-analysis and (d) the model (1950–2002). Units are mm day−1
for precipitation and m s−1 for wind. This figure is available in colour online at www.interscience.wiley.com/journal/qj
c 2009 Royal Meteorological Society
Copyright Q. J. R. Meteorol. Soc. 135: 569–579 (2009)
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GILL RESPONSE TO TROPICAL ATLANTIC SST FORCING
Figure 5. Composite SST anomaly for EXP3–EXP4. The units are K.
find that in the region extending from Central America to
South Asia, the responses to positive and negative SST
anomalies are fairly similar in both amplitude and pattern,
but of opposite sign, suggesting that nonlinearities are
negligible, at least in our runs. In the following the
response in any chosen field is defined as the difference
between EXP1 and EXP2.
A second set of sensitivity experiments has been
performed to assess the possibility that the reduced
rainfall and heating induced by the tropical Atlantic
teleconnection in the Indian basin feed back to the
response seen in EXP1 and EXP2. We prescribe in
the northern Indian Ocean (60◦ E–95◦ E and 5◦ N–25◦ N)
a SST anomaly scaled to produce a rainfall (heating)
perturbation comparable in strength to that induced in
the Indian region by the remote response to the tropical
Atlantic. In EXP3 the anomaly is subtracted from the
climatological SSTs to provide a cold pattern, while in
the partner experiment EXP4 it is added to warm the
northern Indian Ocean. The resulting EXP3–EXP4 SST
anomaly is shown in Figure 5 and has a magnitude of
about 0.25 K.
For all sensitivity experiments the model is run for 100
JAS seasons. The atmosphere at each season is initialized
using the state generated from a continuous 100 year
run of the ICTP AGCM forced by the observed SST.
As a note of caution, the reader should consider that
there may be possible imbalances between the initial
conditions of the modelled atmosphere derived from the
run forced by observed SSTs and the idealized cases
described above. The assumption we made is that such
imbalances do cancel out when considering the difference
between EXP1 and EXP2, or between EXP3 and EXP4.
4.
Results
4.1. Time-mean responses to south tropical Atlantic
anomalies
Figure 6 shows the time-mean responses of (a) precipitation and 925 hPa wind, (b) surface pressure, (c) 925 hPa
streamfunction and (d) 200 hPa eddy streamfunction to
the tropical Atlantic SST anomalies shown in Figure 1.
The responses are calculated as the means from days 20–
90, with the first 19 days discarded as transient. Shaded
regions are 95% statistically significant according to a
t-test under the assumption that the 100 realizations are
independent.
Over Africa the precipitation signal consists of an
increase near the Coast of Guinea, in the area within
c 2009 Royal Meteorological Society
Copyright 573
10E–10W and 5N–10N, and a weak decrease further
to the east. This is in agreement with Figure 2 and
previous results by Vizy and Cook (2001) and Giannini
et al. (2003). Vizy and Cook (2001) analyzed AGCM
experiments performed on an idealized planet including
only the land mask of the African continent with flat
topography and forced by prescribed SST anomalies in
the Gulf of Guinea. According to this work, precipitation
near the Guinean Coast increases following a Gill-type
response to the positive SST anomalies. Those numerical
simulations differ from ours because the prescribed
anomalies extend over a smaller area over the tropical
Atlantic. More importantly, the aqua-planet set-up outside
the African Continent inhibits interactions with the Indian
monsoon system, which is the focus of the present
work. The influence of south tropical Atlantic SSTs on
West African rainfall has been confirmed by the realistic
AGCM experiments of Giannini and co-authors.
Our runs further support the interpretation of the
rainfall pattern over Africa as part of a Gill–Matsuno-type
response: a warming over the tropical Atlantic induces
a pressure gradient extending from the north-east to
the south-west over Africa (Figure 6(b)). The surface
winds are driven from the higher pressure over northeast Africa to the lower pressure over south-west Africa
and the Atlantic Ocean. This induces an overall lowlevel convergence and increased rainfall over western
equatorial Africa, and low-level divergence to the east
of the gradient associated with reduced rainfall. The
opposite happens for a cold tropical Atlantic anomaly.
Further to the east, the patterns depicted in Figure 6 are
consistent with a weakening (strengthening) of the Indian
monsoon in case of a warm (cold) tropical Atlantic SST
anomaly, as derived from the observations in Figure 2.
Focusing on the Indian monsoon region, the outcome of
our idealized experiments agrees with that of Kucharski
et al. (2007; see their figure 6) and Kucharski et al.
(2008a; see their figure 3). In summary, the pattern of
the upper-level response in streamfunction of Figure 6(d)
is a quadrupole with an upper-level trough (ridge) over
India and the Arabian Sea related to a positive (negative)
anomaly in SST over the Atlantic. The vertical structure
of the response is baroclinic with a positive (negative)
surface pressure and low-level streamfunction anomaly
over India (Figure 6(b) and (c)) that favours low-level
divergent (convergent) flow, causing a decrease (increase)
in monsoon rainfall.
When comparing Figure 6(a) in this article with figure 3(b) of Kucharski et al. (2008a), a small but noticeable difference is that here the precipitation response in
the Indian basin appears to be slightly shifted to the
east, over the ocean. Furthermore, the increase of rainfall
over Bangladesh corresponding to warm south tropical
Atlantic SSTs seen in Figure 2 of this article and in figure 3(b) of Kucharski et al. (2008a) is not reproduced in
the precipitation response seen in our Figure 6(a). It is
likely that the lack of coupling in the Indian Ocean in
the present idealized experiments may account for such a
shift (see Chiang and Sobel (2002), Bracco et al. (2007)
and Lintner and Chiang (2007) for a discussion of the
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Figure 6. Response to the SST anomaly in Figure 1 (EXP1–EXP2) of (a) precipitation and 925 hPa winds, (b) surface pressure, (c) 925 hPa
stream function and (d) 200 hPa eddy streamfunction, averaged from days 20–90. Shading indicates regions of 95% statistically significant
anomalies (positive: orange/light grey, negative: blue/dark grey). Contour intervals are 0.6 mm day−1 for precipitation in (a), 0.2 hPa in (b),
0.2 × 106 m2 s−1 in (c) and 0.3 × 106 m2 s−1 in (d). The unit of the wind response in (a) is m s−1 . This figure is available in colour online at
www.interscience.wiley.com/journal/qj
possible influence of ocean mixed-layer adjustment processes on the atmospheric flow).
The precipitation signal extends also to the west, over
Central America and North Brazil, where positive STA
anomalies cause a significant increase in boreal summer
rainfall. The response in the Central America/Caribbean
region is consistent with the observed late summer/early
autumn correlations of rainfall with tropical Atlantic SSTs
(Taylor et al., 2002).
We can interpret the precipitation response to the
STA SST anomaly as a proxy for the heating one,
and compare it with the work of JH95. Obviously, this
response is more complicated than in baroclinic models
where the heating can be directly prescribed, as in JH95.
Nevertheless, the upper-level streamfunction response
depicted in Figure 6(d) is broadly consistent with the
one shown in JH95 for a heating anomaly in the Pacific
(their figure 2(c)). As in the idealized case of a Gill–
Matsuno-type response in the absence of a mean flow, the
waves are equatorially trapped and there is no Rossbywave propagation into the extratropics. This is confirmed
by Figure 7(a) and (b), where the 200 hPa zonal winds
in JAS are displayed for the NCEP/NCAR re-analysis
and the model, respectively. Indeed, in the regions just
north of the Equator in the Atlantic basin and over Africa
and the Indian Ocean, the zonal winds mostly have a
negative sign, favouring a purely equatorially trapped
Gill–Matsuno response. In comparison with JH95 results,
however, our experiments display a slightly stronger
eastward response in the upper level streamfunction field.
Figure 8(a) and (b) show the vertically integrated
moisture flux and moisture flux convergence (see e.g.
Hagos and Cook (2008) for a discussion of the relevance
of the moisture flux). The local redistribution of moisture
c 2009 Royal Meteorological Society
Copyright Figure 7. Zonal wind climatology for JAS (derived from averaging over
years 1950–2002) at 200 hPa for (a) NCEP and (b) the model. Contour
intervals are 8 m s−1 .
is strongly confined in two regions, one between northeast Sahelian Africa and the Gulf of Guinea Coast, the
other between the Indian region and the equatorial Indian
Ocean, with a small net exchange of moisture between
the Indian peninsula and the Gulf of Guinea Coast. This
may be interpreted as part of the total climate adjustment
process to the heating in the south tropical Atlantic
region, and does not imply that the west African rainfall
and Indian rainfall are inherently connected.
The mechanism we advocate for the rainfall reduction over the Indian region is dynamical. The northeastern part of the baroclinic quadrupole response favours
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GILL RESPONSE TO TROPICAL ATLANTIC SST FORCING
575
descending motion over the Indian region; at the same
time subsidence and precipitation anomalies change in
concert as part of the total atmospheric adjustment to the
tropical Atlantic heating, and the net result is a moisture flux divergence and suppressed precipitation. The
reader should bear in mind that there is a possible thermodynamic interpretation for the reduction (increase) of precipitation in regions remote from the warm (cold) SST
anomaly. Lintner and Chiang (2007) have recently shown
in idealized numerical experiments with an ENSO-type
SST anomaly that an important contribution to the reduction of rainfall in remote tropical regions is the warming
of the total atmospheric column away from the heating
itself, which induces a stabilization of the atmosphere.
Figure 8(c) shows the response of the vertically averaged
atmospheric temperature profile. As suggested in Lintner
and Chang (2007), the atmospheric column warms to the
east of the warm SST anomaly over eastern Africa and in
the equatorial Indian Ocean, but not over the Indian subcontinent, where a cooling occurs instead. Thus in our
simulations the stabilization of the atmosphere may be
relevant to reducing rainfall in the eastern African region,
but dynamical processes dominate over thermodynamic
ones in the Indian peninsula. The cooling is likely due
to the reduced atmospheric moisture caused by a sinking
motion that minimizes the amount of heat trapped in the
atmosphere. Interestingly, the vertically averaged temperature response shows a rather symmetric structure north
and south of the equator in the Indian Ocean region, with
cooling at about 20◦ N–30◦ N and 30◦ S–20◦ S. The 200 hPa
eddy streamfunction response in Figure 6 shows a similar symmetry. This is indeed suggestive of forced sinking
motion in both regions, and is confirmed by the analysis
of the 500 hPa omega field (not shown). We also verified
that the cooling in both regions is due to reduced downward long-wave radiation. The main difference between
the northern and the southern regions is that the southern
one is dry and without precipitation in the climatological
mean (see Figure 4), and thus displays a very limited Figure 8. Response (EXP1–EXP2) of (a) vertically integrated moisture
flux, (b) vertically integrated moisture flux convergence and (c)
precipitation response.
−1 −1
vertically averaged atmospheric temperature. Units are kg m s for
(a), contour intervals are 0.6 mm day−1 for (b) and 0.05 K for (c).
4.2. The role of heating over the Indian region
The time-mean responses to SST anomalies in the south
tropical Atlantic show considerable rotational structures
to the east of the anomalies, particularly near the Indian
region (see Figure 6). Although JH95 also found some
rotational structure to the east of their heating anomaly,
this effect seems to be more pronounced in our simulations. Furthermore, although the upper-level structure of
the eddy streamfunction is fairly (anti-)symmetric north
and south of the equator, the surface pressure response
clearly is not.
To investigate a potential cause for the differences
between our experiments and those of JH95, we performed EXP3 and EXP4. In those runs a SST anomaly
is imposed over the Indian Ocean and its intensity
(−0.25 K, see Figure 5) is scaled such that the resulting
precipitation anomalies in the Indian region are similar to
the ones found in the responses of EXP1 and EXP2 (see
c 2009 Royal Meteorological Society
Copyright Figure 6). Those simulations allow us to assess whether
and how reduced rainfall and heating in the Indian region
influence the structure of the response, possibly enhancing it and causing the pronounced rotational structure.
Those are the only goals of these simulations, because
the existence of an isolated SST anomaly in the northern Indian Ocean cannot be justified in any way, owing
to the strong teleconnections of the SSTs in the northern Indian Ocean with the equatorial Indian and eastern
Pacific Ocean SSTs (Annamalai and Murtugudde, 2004).
Furthermore the response to such an SST anomaly may
be overestimated; many studies have indeed shown that
SST forcing in the Indian Ocean region induces spurious
responses in AGCM simulations (Krishna Kumar et al.,
2005; Bracco et al., 2007; Kucharski et al., 2008b) and
may lead to the breakdown of the correct representation
of the ENSO–Indian monsoon relationship in the models.
Q. J. R. Meteorol. Soc. 135: 569–579 (2009)
DOI: 10.1002/qj
576
F. KUCHARSKI ET AL.
Figure 9. Response to the SST anomaly in Figure 5 (EXP3–EXP4) of (a) precipitation and 925 hPa winds, (b) surface pressure, (c) 925 hPa
stream function and (d) 200 hPa eddy streamfunction, averaged from days 20–90. Shading indicates regions of 95% statistically significant
anomalies (positive: orange/light grey, negative: blue/dark grey). Contour intervals are 0.6 mm day−1 for precipitation in (a), 0.2 hPa in (b),
0.2 × 106 m2 s−1 in (c) and 0.3 × 106 m2 s−1 in (d). The unit of the wind response in (a) is m s−1 . This figure is available in colour online at
www.interscience.wiley.com/journal/qj
Figure 10. Response to SST anomaly of Figure 1 (EXP1–EXP2) of 200 hPa eddy streamfunction, averaged from days (a) 1–2, (b) 3–4, (c) 5–6,
(d) 7–8. Units are 106 m2 s−1 . This figure is available in colour online at www.interscience.wiley.com/journal/qj
Figure 9 shows the time-mean responses for EXP3
and EXP4, analogous to those of Figure 6. In the Indian
region the resulting patterns are strikingly similar to those
of Figure 6. In both cases a high surface pressure is
under development and the structure of the response
is baroclinic, with a reduction in the streamfunction at
200 hPa. Interestingly, although the rainfall anomaly
is of similar magnitude in the Indian region to that
in EXP1 and EXP2, the pressure response is only
about half of the response found in EXP1 and EXP2.
c 2009 Royal Meteorological Society
Copyright Overall, EXP3 and EXP4 support the hypothesis that
the high pressure over India is dynamically induced
and is subsequently enhanced by the development of
negative heating anomalies in that region. Furthermore,
the negative heating over India appears to weaken the
Kelvin-wave response further to the east, limiting its
propagation into the Pacific basin, as indicated by the
upper-level streamfunction response to the east of the
heating anomaly shown in Figure 9, which has the
opposite sign to that of Figure 6.
Q. J. R. Meteorol. Soc. 135: 569–579 (2009)
DOI: 10.1002/qj
GILL RESPONSE TO TROPICAL ATLANTIC SST FORCING
577
Figure 11. Response to SST anomaly of Figure 1 (EXP1–EXP2) of 200 hPa velocity potential, averaged from days (a) 1–2, (b) 3–4, (c) 5–6,
(d) 7–8. Units are 106 m2 s−1 . This figure is available in colour online at www.interscience.wiley.com/journal/qj
4.3. Transient response
We now describe the time evolution of the atmospheric
response to the SST anomaly in the tropical Atlantic
during the first eight days or transient period, to illustrate how the signal is propagated by Kelvin and Rossby
waves. One shortcoming of our runs is that SSTs change
in a discontinuous way (the full SST anomaly is imposed
at the start of the integrations on 1 July) and the initial
imbalance in the atmospheric model state may potentially
bias the results. Nonetheless, we think we can gather valuable information from this exercise by considering the
differences between EXP1 and EXP2. Figure 10 shows
the 200 hPa eddy streamfunction response averaged over
(a) the first two days, (b) days 3–4, (c) days 5–6 and (d)
days 7–8. By day 8 the response has reached into the
western Pacific to the east and the eastern Pacific to the
west. The classical quadrupole structure becomes evident
at days 3–4, in agreement with more idealized results (e.g.
figure 2(c) of JH95).
The time evolution of the 200 hPa velocity potential
response (Figure 11), shown again for (a) the first 2 days,
(b) days 3–4, (c) days 5–6 and (d) days 7–8, hints at how
the Walker circulation connecting the African and Asian
monsoons is modified by the presence of a SST anomaly
in the Atlantic. The upper-level divergence (i.e. velocity
potential minimum) over the tropical Atlantic and Africa
is compensated for mainly by upper-level convergence
(i.e. velocity potential maximum), initially over the Indian
Ocean/western Pacific region and later extending into the
central Pacific. This indicates that the relative position of
the response to the initial SST anomaly in the tropical
Atlantic is modified by the location and strength of the
Walker circulation associated with the main monsoon
systems, as proposed by JH95.
c 2009 Royal Meteorological Society
Copyright A good description of the propagation of the equatorially trapped responses to the east and to the west
is provided by the longitude–time plot of the zonal
wind responses averaged from 5◦ S–5◦ N (Figure 12). The
resulting picture again matches very closely figure 4 in
JH95. The warm (cold) SST anomaly in the equatorial
Atlantic causes upper-level divergence (convergence) and
leads to upper-level westerly (easterly) wind perturbations
that propagate as Kelvin waves to the east of the anomaly
with a speed of about 20◦ per day, in agreement with
analogous idealized experiments by Lintner and Chiang
(2007). Such a speed is about half of the propagation
velocity in the Gill–Matsuno solution (about 45 m s−1 ,
corresponding to about 40◦ per day). Such a reduction
is due to the inclusion of moist dynamics, which modifies the Kelvin wave propagation with respect to the dry
Gill–Matsuno model (Neelin and Su, 2005). Mekonnen
et al. (2008), in a recent article, showed the existence of
such Kelvin waves in the African region in observations
and found that their activity is positively correlated with
tropical eastern Pacific and Atlantic, including Gulf of
Guinea, SSTs (their figure 9). The upper-level divergence
(convergence) also leads to upper-level easterlies (westerlies) to the west that propagate as equatorial Rossby
waves with a speed of about 6◦ per day.
5.
Discussion and conclusions
In this work we investigated the physical mechanism by
which tropical Atlantic SSTs teleconnect to the Indian
Ocean basin in boreal summer. To first order, the response
to a heating anomaly in the tropical Atlantic is a classic
Gill–Matsuno-type quadrupole. Kelvin waves transport
the signal from the tropical Atlantic to the Indian Ocean
Q. J. R. Meteorol. Soc. 135: 569–579 (2009)
DOI: 10.1002/qj
578
F. KUCHARSKI ET AL.
Acknowledgements
We wish to thank three anonymous reviewers as well
as the Editor and the Associate Editor for their valuable comments and suggestions, which improved the
manuscript. We are grateful to Sara Rauscher, who helped
us in interpreting the Central America response in the
simulations. The experiments in this article were performed as a contribution to the ENSEMBLES project
funded by the European Commission’s 6th Framework Programme, contract number GOCE-CT-2003505539, and also to the AMMA project funded by
the European Commission’s 6th Framework Programme
Figure 12. Longitude–time picture, starting from 1 July, of (https://www.amma eu.org). AB is supported by NSFthe 200 hPa zonal wind response, averaged from 5◦ S–5◦ N. ATM 0739323.
−1
Units are m s . This figure is available in colour online at
www.interscience.wiley.com/journal/qj
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