Signatures of Tibetan Plateau heating on Indian summer monsoon

JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES, VOL. 118, 1170–1178, doi:10.1002/jgrd.50124, 2013
Signatures of Tibetan Plateau heating on Indian summer
monsoon rainfall variability
Balaji Rajagopalan1,2 and Peter Molnar2,3
Received 23 August 2012; revised 16 December 2012; accepted 17 December 2012; published 7 February 2013.
[1] Despite recent challenges, conventional wisdom has held that heating over the Tibetan
Plateau leads to increased Indian summer monsoon rainfall via enhancement of
cross-equatorial circulation aloft, and a concurrent strengthening of both the Somali Jet and
westerly winds that bring moisture to southern India. We show that such heating, quantified
by monthly estimates of moist static energy in the atmosphere just above the surface,
correlates with summer monsoon rainfall, but only in the early (20 May to 15 June) and
late (September 1 to 15 October) monsoon season. Correlations during the main monsoon
season (15 June to 31 August) are small and insignificant. The positive correlations with early
and late monsoon season, however, allow for heating over Tibet to modulate as much as
~30% of the total rainfall. Furthermore, we demonstrate that heating over Tibet is independent
of the El Niño Southern Oscillation, so that together they explain a substantial portion of
variability in the early and late season rainfall, providing potential predictability. These links
may also explain the wet conditions over India during early Holocene time and provide a
quantitative link between a rise of Tibet and stronger Somali Jet.
Citation: Rajagopalan, B., and P. Molnar (2013), Signatures of Tibetan Plateau heating on Indian summer monsoon
rainfall variability, J. Geophys. Res. Atmos., 118, 1170–1178, doi:10.1002/jgrd.50124.
1. Introduction
[2] A long tradition has associated the South Asian
monsoon with heating of the atmosphere directly over the
Tibetan Plateau [e.g., Flohn, 1968; Yanai and Wu, 2006],
but recent theoretical [e.g., Emanuel, 1995, 2007; Lindzen
and Hou, 1988; Neelin, 2007; Plumb and Hou, 1992; Privé
and Plumb, 2007a] and numerical calculations [e.g., Boos
and Kuang, 2010; Bordoni and Schneider, 2008; Privé and
Plumb, 2007a, 2007b] have challenged this view. Both views,
however, rest on strong theoretical foundations, and the question posed by these differing views may not be, which view is
correct?, but rather, how does heating of the atmosphere over
Tibet affect the strength of the South Asian monsoon?
[3] Although the monsoon is clearly tied to the seasonal
cycle, measures of its strength do not smoothly follow the
gradual annual march of seasons. Rather the monsoon begins
abruptly in a period as short as two weeks, as measured not
only by precipitation [e.g., Ananthakrishnan and Soman,
1988, 1989; Joseph et al., 2006; Pai and Nair, 2009; Soman
1
Department of Civil Environmental and Architectural Engineering,
University of Colorado, Boulder, Colorado 80309, USA.
2
Cooperative Institute for Research in Environmental Sciences,
University of Colorado, Boulder, Colorado 80309, USA.
3
Department of Geological Sciences, University of Colorado, Boulder,
Colorado 80309, USA.
Corresponding author: B. Rajagopalan, Department of Civil Environmental and Architectural Engineering, University of Colorado, Boulder,
CO 80309 USA. ([email protected])
©2013. American Geophysical Union. All Rights Reserved.
2169-897X/13/10.1002/jgrd.50124
and Krishna Kumar, 1993], but also by reversals in both
low-level winds [e.g., Boos and Emanuel, 2009; Fieux and
Stommel, 1977; Halpern and Woiceshyn, 1999; Krishnamurti
et al., 1981] and upper troposphere circulation [e.g., He et al.,
1987, 2003; Li and Yanai, 1996; Wu and Zhang, 1998; Yanai
and Wu, 2006; Yanai et al., 1992]. Moreover, Goswami et al.
[1999] showed that the reversal in winds aloft correlates with
onsets of monsoons defined by various rainfall indices. Thus,
insofar as heating over the Tibetan Plateau affects the temperature structure above it, surface conditions over Tibet would
seem to be important for the South Asian monsoon.
[4] Several arguments do support an association of a warm
upper troposphere with a high plateau. The General Circulation Model (GCM) runs consistently show a stronger monsoon
for a higher Tibetan Plateau than for lower elevations in
that region [e.g., Hahn and Manabe, 1975; Kutzbach et al.,
1989, 1993, 1997; Prell and Kutzbach, 1992; Yasunari et al.,
2006], and analyses of recent GCM runs show that heating
is an essential element to these calculated circulations
[Chakraborty et al., 2002; Wu et al., 2012a]. More simply,
calculations for radiative-convective equilibrium over surfaces
of different elevations call for a warmer upper troposphere
over higher surfaces, warmer by ~6 C per kilometer of surface
elevation [Molnar and Emanuel, 1999]. Thus, it is difficult to
deny that the heating of the atmosphere over Tibet has a role in
the South Asian monsoon.
[5] Arguments that contradict that view include the observation that the warmest area in the upper troposphere is not
centered over Tibet, but overlies northern India and the
southern slope of the Himalayas [e.g., Boos and Kuang,
2010]. This contradictory view also accords with two theoretical arguments. First, Lindzen and Hou [1988] inferred that
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RAJAGOPALAN AND MOLNAR: TIBETAN PLATEAU AND INDIAN MONSOON
(a)
the maximum temperature in the upper troposphere should
overlie the poleward edge of the cross-equatorial
circulation, which commonly develops in a monsoon.
Second, the maximum temperature aloft should overlie the
region of maximum subcloud moist entropy or, virtually
equivalently, the maximum subcloud moist static energy
[e.g., Clift and Plumb, 2008, Chapter 1; Emanuel, 1991;
Emanuel et al., 1994; Neelin, 2007; Plumb, 2007]. Both
modern data [Bordoni and Schneider, 2008; Hurley and
Boos, 2013; Nie et al., 2010] and numerical calculations
[Bordoni and Schneider, 2008; Privé and Plumb, 2007a,
2007b] corroborate these relationships among subcloud
moist entropy or moist static energy, maximum temperature
aloft, and the poleward edge of the cross-equatorial circulation. Thus, the observed maximum in moist static energy
over northern India at the monsoon onset [Bordoni and
Schneider, 2008] and its relation to the large-scale circulation would seem to make the heating over Tibet unimportant,
and perhaps not necessary. In fact, Boos and Kuang [2010]
showed that a key role of Tibet is to block cool dry air, with
low moist entropy and low moist static energy, from mixing
with hot, moist air from the Indian Ocean. Such blockage,
however, does not require a vast high plateau; rather, the
Himalayas, the southern edge of Tibet, suffices. Finally,
GCM runs with an idealized plateau suggest that such topography can enhance precipitation east and southeast of it, but not
over terrain analogous to where India lies [e.g., Liu et al., 2012;
Wu et al., 2012b].
[6] Given the two different views, we ask the question:
Does heating over the Tibetan Plateau correlate with the
strength of the monsoon as measured in different ways?
Toward that end we sought correlations of moist static
energy (MSE) in the atmosphere just above the surface over
Tibet with different measures of monsoon strength. Moist
static energy is given by
MSE ¼ Cp T þ Lv q þ gZ
(b)
(c)
(1)
where Cp is the heat capacity at constant pressure, T is
temperature in Kelvin, Lv is latent heat of vaporization, q is
specific humidity, g is gravity, and Z is height. Because Z
does not change with time, we ignored it in calculations of
time variations in MSE.
[7] We briefly describe the data used in the analysis,
followed by results and conclusions.
2. Data
Figure 1. (a) Topographic map of the Tibetan Plateau and
immediate surroundings showing the region (30 N–36 N;
75 E–90 E) in white box for which we examined moist static energy (MSE). The first eigenvector from a principal
component analysis of MSE over this region for May (solid
contours) and September (dashed contours). Time series of
the first principal component (black) along with box average
of MSE over the region (red) for (b) May and (c) September.
[8] We estimated annual variations in moist static energy for
different seasons or portions of the annual cycle using values
of monthly and daily temperature and specific humidity in
the atmosphere just above the surface given by National
Centers for Environmental Prediction (NCEP) Reanalysis
[Kalnay et al., 1996] averaged over the region 30 N–36 N;
75 E–90 E, which comprises the high central portion of the
Tibetan Plateau (Figure 1a). We performed principal component analysis [Wilks, 1995] of MSE over this region during
May, June through August, and September, the early, middle,
and late monsoon seasons, respectively. For the early and late
seasons, we found the leading mode of variability not only to
capture 50–60% of the variance, but also to be highly correlated (r > 0.9) with the regional average MSE (Figures 1b
and 1c). (Because of the poor correlation with monsoon
rainfall, we omit presentation of such plots for the middle, or
main, monsoon season.) This suggests that the box average
captures the dominant variability. We carried out similar
analyses for other portions of Tibet, including extending the
region northward to 38 N, northwestward as far as 75 E,
and eastward to 100 E, and all shared large variance with that
shown in Figure 1a. We selected the region shown in Figure 1a
because it correlated slightly better than the others with rainfall
over India and winds over the Arabian Sea.
[9] We used NCEP Reanalysis [Kalnay et al., 1996] to
obtain large-scale atmospheric variables such as 850 mb
wind velocities and upper troposphere (200–400 mb average) temperatures. We used monsoon onset and withdrawal
dates based on tropospheric temperatures by Goswami and
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RAJAGOPALAN AND MOLNAR: TIBETAN PLATEAU AND INDIAN MONSOON
(a)
Xavier [2005] and Xavier et al. [2007]. For rainfall we used
the gridded (1 1 ) daily rainfall data over India developed
by Rajeevan et al. [2006]. Monthly sea surface temperatures
(SSTs) and El Niño Southern Oscillation (ENSO) indices were
from Kaplan et al. [1998]. A common period of all the data
sets, 1951–2009, was used in the analysis.
[10] As discussed below, we sought correlations with
monsoon rainfall and ocean and atmospheric variables to
understand the role of Tibetan Plateau heating in modulating
the Indian monsoon.
30°N
-0.1
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0
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0.3
20°N
0.4
0.4
0.5 0.3
0.2
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0
10°N
-0.1
3. Results
90°E
80°E
70°E
100°E
(b)
30°N
0.1
-0.2 -0.1
0.1
0.2
0
20°N
0
0.1
0.1
10°N
0
90°E
80°E
70°E
100°E
30°N
(c)
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-0.1
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20°N
0.4
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0
10°N
[11] We correlated average MSE of surface air in the
region 30 N–36 N; 75 E–90 E, hereafter “Tibet MSE” with
gridded daily rainfall of [Rajeevan et al., 2006] over India
during early, middle, and late periods of the monsoon season
(Figure 2). Correlations between rainfall and MSE were
made for the same period. Rainfall in the early period
(20 May to 15 Jun), exhibits significant positive correlations
exceeding 0.4 over central India and its west coast
(Figure 2a). The correlation weakens markedly to become
insignificant during the peak monsoon season (15 June to
31 August, Figure 2b) before reappearing quite strongly
during the late monsoon period (1 September to 15 October,
Figure 2c). This raises the interesting suggestion that the
heating over the Tibetan Plateau correlates with the Indian
monsoon only during the early and late periods of the
monsoon season.
[12] Consistent with this suggestion, the Tibet MSE in the
early season is negatively correlated (r = –0.47) with monsoon onset, and that in the late season is positively correlated
(r = 0.62) with withdrawal dates given by Goswami and
Xavier [2005] and Xavier et al. [2007], which suggests that
Tibet heating facilitates a lengthening of the monsoon
season and thus the rainfall amount (Figure 3). Following
others, Goswami and Xavier [2005] and Xavier et al. [2007]
suggested that the monsoon season should be defined by a
north-south gradient in temperature aloft. Specifically, they
compared temperatures in the longitude band between
50 E and 90 E in two latitude bands, 15 S–10 N and
10 N–35 N. They defined the monsoon onset as when the
average temperature between 700 and 200 mb in the
northern region exceeded that in the southern region and
withdrawal when that temperature difference reversed.
Because the northern region overlies part of Tibet, we might
expect heating over Tibet to affect temperature aloft in that
region.
[13] To understand the mechanism responsible for the correlations in Figures 2 and 3, we first correlated Tibet MSE
with upper tropospheric temperature, in the pressure range
of 200–400 mb (Figure 4). For the early season, correlation
coefficients exceed 0.6 for the upper troposphere directly
over Tibet. For the late season, correlation coefficients are
yet higher, and the band of high correlation extends southwest from Tibet. These correlations suggest a direct relationship between heating of the atmosphere directly above
Tibet’s surface, and the temperature in the upper troposphere, which many link both to the strength of the monsoon
[e.g., Goswami et al., 1999; He et al., 1987, 2003; Li and
Yanai, 1996; Wu and Zhang, 1998; Yanai and Wu, 2006;
Yanai et al., 1992] and, as Chakraborty et al. [2006]
70°E
-0.6
-0.4
-0.1
90°E
80°E
-0.2
0.0
0.2
100°E
0.4
0.6
Figure 2. Correlations of rainfall over India from Rajeevan
et al. [2006] with MSE over Tibet in different seasons:
(a) the early monsoon period (20 May to 15 June); (b) 15 June
to 31 August; and (c) the late monsoon period (September 1 to
15 October). Correlations in excess of 0.22 and 0.26 are
significant at 90% and 95% confidence.
suggested, to its onset [e.g., Goswami and Xavier, 2005;
Xavier et al., 2007; Webster and Yang, 1992].
[14] Among distinctive features of monsoon circulation
are the band of easterly winds just south of the equator, the
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RAJAGOPALAN AND MOLNAR: TIBETAN PLATEAU AND INDIAN MONSOON
(a)
20°N
40°N
(a)
0.4
0°
0.2
0
0
(b)
40°E
60°E
100°E
80°E
120°E
(b)
40°N
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0.6
20°N
0.6
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0.2
-0.2
cross-equatorial Somali Jet, and the strong westerlies across
the Arabian Sea and southern India [e.g., Hoskins and
Rodwell, 1995; Rodwell and Hoskins, 1995]. Accordingly,
we correlated Tibet MSE with 850 mb wind speed for early
and late periods of the monsoon season (Figure 5). For both
periods, significant correlations that exceed 0.3 for the early
season and 0.5 for the late season are seen in the canonical
wind pattern. The combination of these winds and temperatures aloft are consistent with heating over Tibet that results
in ascent and a corresponding descent over Indian Ocean to
produce a strong monsoon jet.
[15] Given the link between early and late monsoon rainfall with ENSO [e.g., Rajagopalan and Molnar, 2012], we
ask the question—could the links between Tibet heating
and monsoon identified above be manifestations of ENSO’s
influence on both? To answer this, we correlated Tibet MSE
with global SST (Figure 6). In the early season there is no
coherent correlation pattern (Figure 6a), but a weak ENSOlike pattern emerges during the peak monsoon season
(Figure 6b), and becomes more distinct and significant
during late monsoon period (Figure 6c). These differing
correlations suggest that during the early monsoon period,
heating over Tibet exerts an influence on the monsoon rainfall independent of that associated with ENSO, but in the late
period, heating over Tibet and ENSO somehow reinforce
one another. To assess the importance of heating over Tibet,
we regressed early and late monsoon rainfall at each grid
0°
Figure 3. Scatterplot of scaled MSE over Tibet with best
for (a) the early monsoon period (20 May to 15 June) and
(b) the late monsoon period (September to 15 October)—
onset and withdrawal dates, given by Goswami and
Xavier [2005], with best-fitting linear regressions given as
Onset Date = 149 – 5.8 * (scaled MSE for 20 May to 15 June)
and Withdrawal Date = 278 + 7.1 * (scaled MSE for September 1
to 15 October), respectively.
0
-0.2
0
40°E
-0.6
-0.4
0.2
0.4
0.6
60°E
-0.2
80°E
0.0
100°E
0.2
120°E
0.4
0.6
Figure 4. Correlations of average upper tropospheric temperature in the pressure range of 200–400 mb with Tibet
MSE for (a) the early monsoon period (20 May to 15 June)
and (b) the late monsoon period (September 1 to 15 October).
Correlations in excess of 0.22 and 0.26 are significant at 90%
and 95% confidence.
point of Rajeevan et al. [2006] with the NINO4 index for
May and for September, respectively. We do not have daily
SST data for the period of 1951–2009 to compute the ENSO
indices. Hence, this part of the analysis was performed using
monthly index, but given the persistence in the SSTs we
expect the results to be similar for the early and late seasons.
Rajagopalan and Molnar [2012] found early and late
monsoon rainfall to correlate better with the NINO4 index
than either the NINO3 or NINO3.4 indices. We then
removed the variability associated with those regressions
and correlated the residuals with Tibet MSE (Figure 7).
The correlation patterns in the early (Figure 7a) and late
monsoon (Figure 7b) periods are similar to correlation
patterns in Figures 2a and 2c, respectively, but slightly weaker.
Those for the early season remain as high as 0.4, and for the
late season, they reach 0.5, but not 0.6 as in Figure 2c.
[16] A multiple linear regression of early season all-India
monsoon rainfall (computed as the average of all of the
grid-point daily rainfall amounts) with May NINO4 and
May Tibet MSE yields R2 = 0.23, but the same regression
with just NINO4 gives R2 = 0.08. For the late season rainfall,
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RAJAGOPALAN AND MOLNAR: TIBETAN PLATEAU AND INDIAN MONSOON
(a)
0
40°N
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0.1
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-0.3
-0.1
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20°N
rainfall. The multiple regressions yield the following relationships between perturbations to mean daily all-India
rainfall ΔAIR in the early (20 May to 15 June) and late
(1 September to 15 October) periods to the NINO4 index
and to Tibet MSE in May and in September, respectively:
-0.2
0
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-0.1 0.3
0
0 0.2
0.3
0.3
-0.3
0 -0.1
0°
0
-0.2
ΔAIR ðmm=dÞ ¼ 0:24 NINO4ð C Þ
þ0:39 MSEðkJ=kgÞðMayÞ
(2)
ΔAIR ðmm=dÞ ¼ 0:23 NINO4ð C Þ
þ0:58 MSE ðkJ=kgÞðSeptemberÞ
(3)
0.2
0.2
0.1
0.1
0.1
0.2
0
40°E
60°E
80°E
0.1
[19] Therefore, ignoring ENSO, if MSE were greater by
1 kJ/kg, we would expect 10 mm more precipitation in the
early period, and 26 mm more in the late, or 36 mm more
annual precipitation.
00
100°E
120°E
(b)
40°N
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40°E
4. Discussion: Possible Relevance to Paleoclimate
0
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60°E
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0
0.3
0.2
80°E
0.0
100°E
0.2
0.4
0.2
120°E
0.4
0.6
Figure 5. Correlations of wind speeds at 850 mb with
Tibetan MSE for (a) the early monsoon period (20 May to
15 June) and (b) the late monsoon period (September 1 to
15 October). Correlations in excess of 0.22 and 0.26 are significant at 90% and 95% confidence.
the R2 values are 0.48 and 0.17, respectively (Figure 8).
Clearly, Tibet MSE correlates with, and therefore might
explain, a substantial fraction of early and late season
rainfall independently of ENSO in the early season and in
conjunction with it at the end.
[17] To the best of our knowledge, this analysis indicates a
hitherto unknown finding, that heating over Tibet could
modulate Indian summer monsoon rainfall, but only in
specific windows, the early and the late monsoon season, not
the main monsoon season. We found this connection to be
insensitive to rainfall data sets used; the Aphrodite gridded
(0.5 ) daily precipitation data set over Asia [Xie et al., 2007]
and Climate Research Unit precipitation data [Mitchell and
Jones, 2005] yield similar results.
[18] At present, all-India mean daily rainfall over the
26 days in the early period from 20 May to 15 June is
3.8 1.2 mm/d and that over the 45 days from September
1 to October 15 in the late period is 5.3 1.2 mm/d. The
total for early and late seasons averages to be 337 mm/yr,
comprising of about 33% of the total monsoon season
[20] The correlations and regressions above do not, by
themselves, assign cause and effect. In fact, if the atmosphere
is in a quasi-equilibrium state, as many assume for large-scale
monsoon circulation [e.g., Bordoni and Schneider, 2008;
Emanuel, 2007; Emanuel et al., 1994; Neelin, 2007; Plumb,
2007; Privé and Plumb, 2007a, 2007b], cause and effect have
no meaning. Nevertheless, changes in Tibet’s surface elevation
and surface properties have occurred in geologic time, and it
seems possible that such changes have altered atmospheric
circulation over South Asia. With these considerations in mind
and using the regressions and correlations presented above, we
address possible impacts of changes in surface conditions over
Tibet on the South Asian monsoon.
[21] Let us consider two time periods in the geologic past
for which these regressions might be relevant. In early Holocene time, not only were lakes widespread in northern India
where desert conditions now prevail [e.g., Bryson and
Swain, 1981; Enzel et al., 1999; Prasad and Enzel, 2006;
Prasad et al., 1997; Singh et al., 1972, 1990; Sinha et al.,
2004], but winds associated with the Somali Jet seem to
have been stronger [e.g., Gupta et al., 2003]. By contrast,
before ~10 Ma, winds associated with the Somali Jet seem
to have been weaker than today, and some have inferred that
the monsoon strengthened since that time [e.g., Harrison
et al., 1992; Kroon et al., 1991; Molnar et al., 1993; Prell
and Kutzbach, 1992].
[22] In early Holocene time at ~6 ka, summer radiation on
Tibet during the monsoon season, from early May to the end
of September, was higher than present by a maximum of
~24 W/m2 [e.g., Braconnot et al., 2000]. Huybers [2006]
showed that for latitudes of 35 or higher, summer surface air
temperatures vary linearly with insolation, at ~ 1 C per W/m2,
with temperature lagging insolation by 30 days. Because
of Kepler’s second law, the duration of summer, and
therefore the monsoon season, should have been shorter in
the period of enhanced insolation due to precession
[Huybers, 2006]. Consequently, determining the early and
late monsoon periods that correspond to those today requires
somewhat aribitrary decisions, but as an example let us
assume that average summer radiation was 5 W/m2 greater
than it is today. Following Huybers’s [2006] correlation,
the surface of Tibet would have been warmer by ~5 C than
today. Also, specific humidity at saturation increases with
1174
RAJAGOPALAN AND MOLNAR: TIBETAN PLATEAU AND INDIAN MONSOON
90°N
(a)
60°N
0.1
30°N
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90°S
60°S
30°S
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60°E
30°E
90°E
120°E 150°E
180° 150°W 120°W 90°W
60°W
0°
30°W
90°N
(b)
60°N
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30°N
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0 -0.1
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30°S
0.2 0.3
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90°S
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60°E
30°E
90°E
120°E 150°E
180° 150°W 120°W 90°W
60°W
30°W
0°
30°N
60°N
90°N
(c)
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0°
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0.1 0
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30°S
0.4
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90°S
60°S
0
30°E
60°E
-0.6
90°E
120°E 150°E
-0.4
-0.2
180° 150°W 120°W 90°W
0.0
0.2
60°W
0.4
30°W
0°
0.6
Figure 6. Correlations of SST with Tibet MSE (a) for May, (b) for July–August, and (c) for September.
Correlations in excess of 0.22 and 0.26 are significant at 90% and 95% confidence.
1175
RAJAGOPALAN AND MOLNAR: TIBETAN PLATEAU AND INDIAN MONSOON
(a)
(a)
-0.1
30°N
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0
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0
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20°N
0
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0.4
0.3
(b)
10°N
0.2
0.1 0
-0.1
70°E
80°E
90°E
100°E
(b)
Figure 8. Multiple linear regression fits of scaled observed
all-India rainfall for (a) the early monsoon season (20 May
to June) and (b) for the late monsoon season (September 1 to
15 October). Black lines show observed all-India rainfall,
and red lines values predicted from the linear regressions.
The all-India rainfall is computed using the gridded rainfall
values given by Rajeevan et al. [2006]. Predicted values use
Tibet MSE and the NINO4 indices for May and September,
respectively.
0.4
30°N
0.4
0.2
0.3
-0.1
0
0.1
0.2
20°N
0.4
0.3
0.4
0.2
0
0.1
10°N
0.4
-0.1
0
70°E
-0.6
0.3
-0.4
80°E
-0.2
90°E
0.0
0.2
100°E
0.4
0.6
Figure 7. Correlations of rainfall over India from Rajeevan
et al. [2006] after removing the variance associated with
ENSO with Tibet MSE, (a) for the early monsoon season
(20 May to 15 June) with May MSE and (b) for the late
monsoon season (September to 15 October) with September
MSE. Rainfall consists of values given by Rajeevan et al.
[2006] minus those obtained from a regression with the
monthly average NINO4 index (a) for May and (b) for
September. Correlations in excess of 0.22 and 0.26 are
significant at 90% and 95% confidence.
temperature by ~7%/ C [e.g., Held and Soden, 2006]. If we
assume that relative humidity changed little from today’s average, then if early and late monsoon season temperatures
in Tibet were warmer than today by 5 C, q at saturation
should have been greater by 1.4 times than today’s values
of 0.51 g/kg and 0.67 g/kg in May and September, respectively. Thus, q would have been greater by 0.7 g/kg and
0.9 g/kg in those seasons, and from (1), with surface air warmer by 5 C and enhanced moisture, Tibetan MSE would have
been greater by 5.7–5.9 kJ/kg. The regressions in (2) and (3)
would then call for 212 mm/yr more rainfall than today. Moreover, at ~6 ka, the eastern tropical Pacific Ocean was cooler
than today by ~1 C [e.g., Kienast et al., 2006; Koutavas et
al., 2002, 2006; Leduc et al., 2007, 2010; Pahnke et al.,
2007]. If we assume a NINO4 index of –1 C, this could correspond to 17 mm/yr more rainfall early and late monsoon
seasons than today, and the combination of a warmer Tibet
by 5 C and a cooler NINO4 region by 1 C would lead to
~230 mm, or ~23%, more annual rainfall than today. Thus,
perhaps insolation over Tibet at ~6 ka, plus the more La Niña
like conditions in the eastern Pacific, account for the wetter
northern India then than now.
[23] Much evidence suggests that the tectonic evolution of
Tibet underwent some kind of change near 10–15 Ma. One
explanation for these changes is that at that time the surface
of the plateau rose abruptly 1000 m or more [e.g., Harrison
et al., 1992; Molnar et al., 1993], but much less than the full
5000 m present-day elevation of the plateau. Estimates of
paleo-elevations of southern Tibet do not support, but rather
contradict, this idea; essentially all such estimates show little
change since 10 Ma to perhaps 25–35 Ma [Currie et al.,
2005; DeCelles et al., 2007; Garzione et al., 2000a, 2000b;
Rowley and Currie, 2006; Rowley et al., 2001; Saylor et al.,
2009; Spicer et al., 2003]. Because uncertainties in all are
~1000 m, however, let us consider the possibility that the
average elevation of Tibet was 1000 m lower at 10–15 Ma
than today.
[24] If Tibet had risen by 1000 m, MSE of the air directly
over it would have increased by 9.8 kJ/kg, ignoring any
change in surface temperature or specific humidity. The
regressions, ignoring ENSO, would suggest an increase in
annual rainfall of nearly 350 mm, or from ~35% less than
today’s average to present-day amounts. More importantly,
the correlation of winds over the Arabian Sea with early and
late monsoon season Tibet MSE (Figure 5) are consistent with
the geologic inference of stronger winds today than earlier
when Tibet might have been 1000 m lower. Because we lack
a quantitative estimate of the change in wind strength, however,
we cannot perform a more quantitative analysis of such a
relationship, but the present-day correlations do concur with
1176
RAJAGOPALAN AND MOLNAR: TIBETAN PLATEAU AND INDIAN MONSOON
the inference that a modest rise of Tibet led to a strengthening
of monsoon winds [e.g., Harrison et al., 1992; Kroon et al.,
1991; Molnar et al., 1993; Prell and Kutzbach, 1992].
5. Conclusions
[25] Recently, Boos and Kuang [2010] argued that the
principal role that Tibet plays in affecting the Indian monsoon
is to block cool dry air from northwest of Tibet. Although they
did not deny a warming over Tibet a role in the monsoon, their
work implies that such warming has a modest influence. We
found an insignificant correlation between Tibetan heating,
as quantified by moist static energy of surface air, and rainfall
in the main monsoon period (15 June to 31 August)
(Figure 2b). We show, however, that heating over the Tibetan
plateau does correlate with, and therefore may modulate Indian
monsoon rainfall in the early (20 May to 15 June) and late
(1 September to October 15) monsoon seasons, which together
contribute about a third of the seasonal rainfall. Simple regressions suggest that variations in heating over Tibet might
account for as much as 20% of seasonal total rainfall.
Furthermore, we demonstrate that heating over Tibet is largely
independent of ENSO, so that together they can explain a
substantial portion of variability in the early and late season
rainfall, and therefore provide potential predictability at crucial
times of crop management—sowing and harvesting, respectively. These links between heating over Tibet and ENSO with
rainfall over India may explain the wet conditions over India
during early Holocene time and provide a quantitative link
between a rise of Tibet and a stronger Somali Jet. They might
also provide some insights into mechanisms that could play a
role in the monsoon variability under a warmer climate that
the current crop of dynamical models need to capture better.
[26] Acknowledgments. This research was supported in part by the
National Science Foundation under grants EAR-0507730, EAR-0909199,
and EAR-1211378. Thanks are also due to Chinese colleagues with
whom one of us, PM, collaborates on the National Science Foundation of
China grant 40921120406. We thank two anonymous reviewers for
constructive comments.
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