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JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 116, D03102, doi:10.1029/2010JD014340, 2011
Occurrence of extremely low cold point tropopause temperature
during summer monsoon season: ARMEX campaign
and CHAMP and COSMIC satellite observations
A. R. Jain,1 Vivek Panwar,1,2,3 C. J. Johny,1,4 T. K. Mandal,1 V. R. Rao,5 Rishu Gautam,1
and S. K. Dhaka2
Received 8 April 2010; revised 8 November 2010; accepted 19 November 2010; published 3 February 2011.
[1] Extreme low cold point tropopause (CPT) temperatures (T ≤ 191 K) are often
observed during the monsoon season over the Bay of Bengal (BOB) and adjoining areas.
This paper reports frequent occurrences of extreme low CPT temperature over the
Arabian Sea (AS) and adjoining areas using radiosonde observations during the Arabian
Sea Monsoon Experiment (ARMEX) from 24 June to 15 August 2002. Day‐to‐day
variations in temperature at CPT and at the 100 hPa level observed during the ARMEX
campaign show modulation by the wave activity with a period of ∼15 days, and it is
observed to be closely associated with the Tropical Easterly Jet (TEJ). Characteristics of
wave modulating the temperature at the CPT and at the 100 hPa level are brought out
and discussed. Spatial and temporal distribution of low CPT temperature over a wide
scale is examined using CHAMP and COSMIC satellite temperature data. These
observations show occurrences of low CPT temperatures during the early period of the
monsoon season over BOB, AS, and adjoining areas, which often extend to Africa’s Horn
region. An enhanced low CPT temperature occurrence during the early part of the
monsoon appears to be due to the modulation of outgoing long wave‐radiation (OLR),
CPT temperature, and height by intraseasonal oscillation. Modulation of CPT by
intraseasonal oscillation suggests that this oscillation could contribute to dehydration of
the lower stratosphere. In addition, a close association is noted between the seasonal
variations of the latitude of low CPT temperature and low OLR, which is similar to the
anticipated seasonal movement of the Intertropical Convergence Zone (ITCZ).
Citation: Jain, A. R., V. Panwar, C. J. Johny, T. K. Mandal, V. R. Rao, R. Gautam, and S. K. Dhaka (2011), Occurrence of
extremely low cold point tropopause temperature during summer monsoon season: ARMEX campaign and CHAMP and
COSMIC satellite observations, J. Geophys. Res., 116, D03102, doi:10.1029/2010JD014340.
1. Introduction
[2] To explain the observed low water vapor mixing ratio
in the lower stratosphere over southern England, Brewer
[1949] postulated a stratospheric circulation of air and
suggested that the observed stratospheric air must have
passed through the tropical tropopause where the temperatures are cold enough to “freeze‐dry” the air entering the
stratosphere. This is called the “freeze‐dry mechanism.”
This mechanism envisages that air is dried out as it passes
1
Radio and Atmospheric Sciences Division, National Physical
Laboratory, New Delhi, India.
2
Department of Physics and Electronics, Rajdhani College, University
of Delhi, New Delhi, India.
3
Department of Physics and Astrophysics, University of Delhi, New
Delhi, India.
4
Department of Physics, Rayalseema University, Kurnool, India.
5
Satellite Meteorology Division, India Meteorological Department,
Mausam Bhavan, New Delhi, India.
Copyright 2011 by the American Geophysical Union.
0148‐0227/11/2010JD014340
through the cold tropopause region and would be effective
when (1) the tropopause temperature is cold enough to
freeze the vapor content of the air and (2) the air stays for a
sufficient time in the region of low temperature so that water
vapor is removed through condensation and freezing.
Newell and Gould‐Stewart [1981] examined the spatial
distribution of tropopause temperature and concluded that
during winter months (November–March) the tropospheric
air could enter the lower stratosphere through the Indonesian
region where the tropopause temperatures are the lowest.
These authors have also shown that the region of cold tropopause temperature expands toward the Bay of Bengal
(BOB) and the Indian tropical region during premonsoon
and monsoon months, suggesting that the Indian tropical
region may be participating in the stratospheric dehydration.
However, the dry air could have entered the stratosphere
either by overshooting convective turrets making the tropopause region much colder than the surroundings [Sherwood
and Dessler, 2001] or by the freeze‐dry mechanism coupled with horizontal transport [Holton and Gettelman, 2001].
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Highwood and Hoskins [1998] have shown, mainly on the
basis of the European Centre for Medium‐Range Weather
Forecasts (ECMWF) analysis, that during summer (June–
August) months the tropopause can be high and cold in the
Asian monsoon region and therefore, it plays a significant
role in dehydration of the lower stratosphere. They have also
mentioned that it is difficult to compare the ECMWF and
radiosonde climatology because of missing data over the
Asian region. Randel et al. [2000] presented global variability and trends in tropopause temperature on the basis of
National Center for Environmental Prediction (NCEP)
reanalysis and noted that in July the tropical tropopause
temperature minimum occurs over the Indian monsoon
region centered near 20°N. Analysis by Highwood and
Hoskins [1998] and by Randel et al. [2000] highlighted the
significance of the Asian monsoon region in dehydration
of lower stratosphere. Ratnam et al. [2005] presented features related to the structure and variability of the tropopause
using radio occultation measurements by the Challenging
Minisatellite Payload (CHAMP) and GPS during May 2001
to December 2004. They observed a cold tropopause over
∼20°N and 0°E–120°E, which includes the Arabian Sea (AS)
region, during the northern summer (June–August) months.
Jiang et al. [2004] have shown that most of the deep convection events occur in the western Pacific and Indian
monsoon regions and discussed that low temperatures in
the tropical tropopause layer (TTL) are associated with, but
often drift away from, the center of deep convection. This
again brings in the Indian‐Asian summer monsoon region
into focus.
[3] Recently, Jain et al. [2006] examined the spatial distribution of temperature in the tropopause region using
various sets of observations during the Bay of Bengal
Monsoon Experiment (BOBMEX) and showed that low
cold point tropopause (CPT) temperature (T ≤ 191 K) occurs
during the summer monsoon over the northeastern region of
India, the north central Bay of Bengal, Bangladesh, northern
Myanmar, and adjoining areas. In their study, the role of the
tropical convection and of the Kelvin wave activity in
modulating the temperature field at levels close to the tropopause is also discussed. Several studies have also reported
that Kelvin waves have large effect on the temperature of
the tropopause, cloud top height, and dehydration of the
lower stratosphere [Jensen and Pfister, 2004; Shimizu and
Tsuda, 1997]. Planetary‐scale and quasi‐stationary Rossby
waves also modulate the tropopause layer near the equator
[Matsuno, 1966; Dima and Wallace, 2007] and control entry
of trace gases, e.g., ozone and water vapor, from troposphere to stratosphere by modulating the tropopause height
and structure.
[4] As mentioned earlier, it may be noted that net transport of water vapor into the stratosphere is linked to spatial
and seasonal distribution of temperature in the TTL. The air
entering into the stratosphere may be dehydrated through the
freeze‐dry mechanism or the freeze‐dry mechanism coupled
with horizontal transport [Holton and Gettelman, 2001]. A
temperature of 191 K, which is taken here as a reference
temperature for dehydration of lower stratosphere, corresponds to a water vapor mixing ratio of ∼3.5 ppmv at the
100 hPa level [Newell and Gould‐Stewart, 1981; Tsuda
et al. 1994; Jain et al., 2006]. The seasonal variation of
entry of water vapor mixing ratios ranges from ∼2.5 ppmv
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during January–February to ∼4.5 ppmv during September–
October [Fueglistaler et al., 2005]. Fueglistaler et al.
[2005] and Fueglistaler and Haynes [2005] have suggested that seasonal variation of the entry of water vapor
mixing ratios may be explained by using both large‐scale
dynamics and temperature only. Asian monsoons are significantly influenced by the 30–60 day intraseasonal oscillation. Several studies reported the influence of
intraseasonal oscillation on outgoing long‐wave radiation
(OLR) [Kiladis and Weickmann, 1992; Fukutomi and
Yasanuri, 1999]. Recently, Mote et al. [2000] have shown
the signature of intraseasonal oscillation in temporal variations of water vapor in the tropical upper troposphere and
tropopause region. The Intertropical Convergence Zone
(ITCZ) is also associated with convection activity, and
seasonal migration of the ITCZ could also change the
spatial distribution of temperature in the tropopause region
[Fueglistaler et al., 2009]. In a recent review Fueglistaler
et al. [2009] discussed various characteristic features of
the TTL and emphasized that convection plays an important
role in determining thermodynamic properties and chemical
composition of the TTL. They emphasized that processes
related to convection (i.e., including the overshooting convection) need to be better understood. Jain et al. [2010]
examined the processes of how the tropospheric air may
enter the stratosphere, particularly in association with the
tropical mesoscale convection system, which is considered
to be one of the causative mechanisms for extreme low
tropopause temperatures over the tropics. Observations
reported by these authors point out that both the mechanisms, namely, one suggested by Danielsen [1982] and the
other one suggested by Sherwood [2000], have a role in
troposphere to stratosphere transport of the air.
[5] Observations on CPT temperature distribution over
the tropical Indian region by Jain et al. [2006, 2010] were
confined mainly over the BOB and adjoining areas.
Although Ratnam et al. [2005] showed the distribution of
the cold tropopause over ∼20°N and 0°E–120°E covering
the AS region, during northern summer (June–August),
further analysis of its causes has not been reported so far.
The influence of large‐scale wave phenomena, intraseasonal
oscillation, and seasonal movement of the ITCZ on upper
troposphere and lower stratosphere (UTLS) temperature
distribution over the monsoon region remains to be investigated. It is important to note that the southeastern AS
has sea surface temperature (SST) in excess of 303 K for 2–
3 months (April, May, and June) preceding the summer
monsoon onset over India [Vinayachandran et al., 2007].
Warm pool regions with SST in excess of 301 K in the
ocean occupy a special place in the tropical climate owing to
their impact on tropical convection. This motivated us to
extend studies on CPT temperature by Jain et al. [2006]
over the AS region. In the present study the variations of
tropopause temperature are examined using radiosonde
data collected during June–August 2002 as part of the
Arabian Sea Monsoon Experiment (ARMEX) campaign. In
addition to ARMEX data, CHAMP and Constellation
Observing System for Meteorology, Ionosphere and Climate
(COSMIC) satellite data are also used to examine the spatial
coverage by areas of extreme low CPT temperature over
AS, BOB regions, and adjoining areas. To understand
the dehydration of the lower stratosphere over the Indian
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Figure 1. Cruise track and time series positions of ORV
Sagar Kanya. The time series positions are TS1 at 71.2°E,
10.9°N from 30 June to 10 July and TS2 at 72.2°E, 15.5°N
from 22 July to 5 August 2002 [after Bhat, 2006].
tropical region, CPT temperature variability is examined
with a focus on the Indian‐Asian monsoon region over the
following time scales: (1) day‐to‐day variations (∼5–20 day
period) to understand the characteristics of large‐scale
waves, (2) seasonal variation, and (3) intraseasonal oscillation of 30–60 day period. This would help to understand the
role of such variability in producing low tropopause temperature and dehydration of the lower stratosphere.
2. Database
[6] Upper air observation data obtained during the ARMEX campaign (24 June to 15 August 2002) from ocean
research vessel (ORV) Sagar Kanya using Vaisala RS80‐
15G radiosondes, with radiation correction program RSN96,
are used. The ship ORV Sagar Kanya was positioned for
time series observations at two locations: (1) at 16.9°N,
71.2°E during 30 June to 10 July 2002 (hereinafter referred
to as TS1) and (2) at 15.5°N, 72.2°E during 22 July to 5
August 2002 (hereinafter referred to as TS2) as shown in
Figure 1. Details of the ARMEX campaign were presented
by Bhat [2005, 2006]. The accuracy of temperature measurements using radiosonde near the tropopause level was
found to be better than 1 K. The height resolution near the
altitude of the tropopause is better than 50 m [Jain et al.,
2006]. Each of the sounding data sets is used for the
determination of CPT temperature, termed here as the
coldest point on the temperature profile. Soundings carried
out at 0000 and 1200 UT on each day are used for the
present study.
[7] The CHAMP satellite observations provide a much
broader view of the spatial distribution of temperature
[Schmidt et al., 2004]. CHAMP satellite atmospheric temperature data during April–August in the years 2002–2006
are used. CHAMP satellite data of atmospheric temperature
for the year 2002 overlap with the data of the ARMEX
campaign period. The COSMIC satellite observations of
atmospheric temperature during April–September in the
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years 2006–2008 are also examined to confirm the CHAMP
observations [Rocken et al., 2000].
[8] In order to further extend the study, monthly mean
outgoing long‐wave radiation (OLR) data [Liebermann and
Smith, 1996] for the period January–December 2007 over
the Indian longitude zone are used to examine the linkage
between the occurrence of extreme low CPT temperature
and enhanced convection (i.e., low OLR values). In addition, daily mean values of OLR for the period 1 May to 30
September 2007 obtained from satellite Kalpana‐1 are used
to examine intraseasonal variations in OLR and COSMIC
satellite observations of CPT temperature. Satellite Kalpana‐
1, with a meteorological payload of a very high resolution
radiometer, provides images in three channels, namely,
visible (0.55–0.75 mm), infrared (10.5–12.5 mm), and water
vapor (5.7–7.1 mm). The spatial resolution at the subsatellite
point is 2 km in the visible channel and 8 km in infrared and
water vapor channels. The daily mean OLR is derived from
half‐hourly images (∼48 images per day).
3. Results and Discussion
3.1. A Case of Large‐Scale Waves
[9] In the present study, radiosonde temperature profiles
corresponding to 0000 and 1200 UT have been used to
determine the CPT temperature. Observations of CPT temperature, as mentioned in section 2, are used to construct the
time series for the ARMEX campaign period during 24 June
to 15 August 2002 as shown in Figure 2a. A total number of
26 cases of low CPT temperature values (T ≤ 191 K) were
detected which constitute ∼30% of the total number of
soundings in the present study. To identify the features of
the wave activity in modulating CPT temperature, the
missing points in CPT temperature time series are filled
using linear interpolation. A 5 day running mean is then
employed. The smoothed time series thus obtained is shown
in Figure 2a. Similar analysis has been carried out for
temperature at the 100 hPa level (T100), which is considered
as the averaged tropopause level over the tropics. Time
series of T100 is shown in Figure 2b. Plots of temperature
time series in Figures 2a and 2b show clear modulation by
wave activity with temperature minimum around Julian days
178, 190–195, and 212–217 and temperature maximum
around Julian days 185, 196–205, and 220–225. Quasiperiodic minima and maxima show modulation of temperature
by wave activity with a period of 12–17 days. Time series of
zonal and meridional wind at the 100 hPa level also show
similar wave modulation. Figure 3a shows an anomaly
time series of zonal (DU) and meridional (DV) wind at the
100 hPa level obtained from ARMEX campaign data collected on board Sagar Kanya during 24 June to 14 July
2002. It may be noted from Figure 3a that anomaly
amplitudes in zonal and meridional winds are comparable.
Figure 3b shows plots of the 100 hPa temperature anomaly
(DT) and that of DU for the above mentioned period. In
Figures 3a and 3b only 5 day smoothed data are plotted. A
cross‐correlation analysis has been carried out between DT
and DU time series as shown in Figure 3c, which suggests
that period t of the modulating wave is ∼15 days with DT
leading DU by ∼4 days. Three important points may be
noted here: (1) Sagar Kanya was located at the latitude
range of 15.5°N–16.9°N during the ARMEX observation
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Figure 2. Plots of time series of temperature measurements on board ORV Sagar Kanya. (a) CPT
temperature time series and (b) 100 hPa level temperature time series. Data gap points are joined by
dashed lines. The smoothed points of time series, after 5 day running mean, are joined by a thin solid
line. Horizontal lines indicate the period of TS1 and TS2 time series as shown in Figure 1.
period, which is higher than the e‐folding latitude of Kelvin
waves; (2) wave amplitudes in zonal and meridional wind are
comparable; and (3) the temperature led in phase by ∼4 days,
i.e., ∼t/4.
[10] ARMEX observations covered a very limited spatial
region (Figure 1), and wind observations, at a level close to
the tropopause, were available only for a period of 20 days
(24 June to 14 July 2002). Therefore, to identify and discern
the types of waves (i.e., Kelvin waves, Rossby waves,
mixed Rossby‐gravity waves, etc.) that can modulate CPT
temperature, NCEP reanalysis data for temperature and
wind at 100 hPa are used. The NCEP reanalysis provided
global air temperature, humidity, pressure, sea surface
temperature, etc., every 6 h with 2.5° × 2.5° resolution.
NCEP reanalysis used a state‐of‐the‐art analysis method to
perform data assimilation with ground weather station data
and satellite data. In the present study, reanalysis data of the
mean daily temperature and horizontal wind at the 100 hPa
level over the eastern tropics (0°E–180°E) are examined for
the ARMEX campaign period. This reanalysis reveals the
following salient features.
[11] 1. The perturbations in temperature and zonal wind
are prominent over the latitude range of 10°N–20°N and
5°N–20°N, respectively.
[12] 2. The perturbations in temperature and zonal wind
seem to originate in the region around 100°E–140°E and
terminate over the region of 70°E–50°E longitude range (see
auxiliary material, Text S1).1 These perturbations seem to
move westward and northwestward. These features show
that observed perturbations are closely linked to the variability in the Tropical Easterly Jet (TEJ), which starts in late
June and continues until early September [Koteswaram,
1958]. This strong flow of air that develops in the upper
troposphere during the Asian monsoon season usually
locates at 15°N, 50°E–80°E and extends from Southeast
Asia to Africa. The strongest development of the jet takes
place at an altitude of ∼15 km with wind speed of 40 m s−1
over the Indian zone. Figure 4 depicts the contour maps of
DT and DU from NCEP reanalysis at the 100 hPa level for
the longitude range of 0°E–180°E drawn as a function of
longitude and day number covering the period of ARMEX
campaign observations. The thin vertical line in Figure 4
shows the longitudinal location of ORV Sagar Kanya during the ARMEX campaign period for reference. These
contour maps show a westward movement of temperature
and wind perturbations as denoted by arrows in Figure 4.
1
Auxiliary materials are available in the HTML. doi:10.1029/
2010JD014340.
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Figure 3. Plots of time series of temperature (DT), zonal wind (DU), and meridional wind (DV) anomalies from ARMEX campaign observations during the period 24 June to 14 July 2002. (a) Time series of
DU and DV. (b) Corresponding plots for DT and DU. In Figures 3a and 3b only 5 day smoothed data are
shown. (c) Plot of cross‐correlation function between DT and DU time series.
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Figure 4. Contour maps of (a) temperature anomaly (DT)
and (b) zonal wind anomaly (DU) computed using NCEP
reanalysis data for the ARMEX campaign period. To draw
these contour maps, anomaly values for each day and for
each longitude point are averaged over the latitude range
of 10°N–20°N and maps are drawn as a function of longitude and day number. Maps of DT and DU are drawn with
a resolution of 1 K and 3.0 m s−1, respectively. Positive
values of anomalies are represented by gray. Arrows shows
the direction of motion of the perturbations. Thin vertical
line in Figures 4a and 4b shows the longitudinal position
of ORV Sagar Kanya during the ARMEX campaign observation period for reference.
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[13] 3. Figure 5a shows the time series of the zonal wind
anomaly (DU), meridional wind anomaly (DV), and temperature anomaly (DT) determined using NCEP reanalysis
over the AS and Indian west coast (ASIWC) (10–20°N, 70–
75°E) region. Time series of DT, DU, and DV are first
obtained by averaging the anomaly for each of these parameters over the ASIWC region for each day. These time
series are then plotted after taking the running mean over
5 days to remove the short‐period oscillations (Figure 5a). It
is noted that the amplitudes of DU and DV are of the same
order. We have also verified the same using ECMWF
(ERA‐Interim) reanalysis data (Text S2). Spectrum analysis
using fast Fourier transform (FFT) has been carried out for
DT and DU time series, which is shown in Figure 5b. The
FFT algorithm used in this analysis applies detrending and
also the necessary Hanning window before taking FFT. The
spectra of both DT and DU show broad peaks. These time
series are passed through a band‐pass filter with a width of
14–18 days to determine the phase shift, if any, between
the two time series. The cross‐correlation functions between
DT and DU time series and between DV and DU time
series are shown in Figure 5c. It is noted that DT is
advanced in phase with respect to DU by ∼3 days, and DU
is advanced in phase with respect to DV by 3–4 days.
Results from two different data sets are in good agreement
and confirm the presence of wave activity with a period of
∼15 days.
[14] Characteristics of the observed wave perturbations
can be summarized as follows.
[15] 1. The observed wave perturbations are confined to
the latitude range of ∼10°N–20°N. These perturbations are
westward propagating and appear to be closely linked to the
TEJ and convection, which appear over the Asian monsoon
region during summer months, as the observed perturbations
originate in the region of ∼100°E–140°E and terminate over
the region 50°E–70°E. The amplitude of zonal (DU) and
meridional (DV) wind perturbations are of the same order.
[16] 2. An examination of DU time series from ARMEX
campaign observations at 200, 150, and 100 hPa levels
shows downward phase propagation (figure not shown).
[17] 3. The observed period of these waves is ∼15 days
(i.e., 12–17 days). An examination of the longitudinal
distribution of DT and DU for different Julian days yields
a value of ∼4300 km for horizontal wavelength (lX) of
the wave.
[18] 4. Temperature perturbation (e.g., warm phase) leads
zonal wind perturbation (e.g., eastward phase) by ∼t/4.
However, temperature perturbation (e.g., warm phase) is
opposite in phase with meridional wind perturbation (e.g.,
northward wind phase) as shown in Figure 2.
[19] 5. Some of these characteristics are similar to those
observed for Rossby‐gravity waves (RGW). RGW with n =
0, antisymmetric mode, and zonal wave number ≥7 are
feasible [Ern et al., 2008]. These waves are also westward
propagating. The dispersion relation for RGW [Holton,
2004; Andrews et al., 1987] is examined at the 100 hPa
level. The value of lX is taken from NCEP reanalysis, and
mean values of lZ and Brunt‐Vaisala period (t B) are taken
from ARMEX measurements. Taking zonal wave number
(k) corresponding to lX of 4500 km, lZ ∼ 1.75 km, Brunt‐
Vaisala period (t B) ∼ 7.1 min, and scale height H = 7 km,
dispersion relation yields a value of intrinsic wave period of
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Figure 5. (a) Plots of time series of temperature (DT), zonal wind (DU), and meridional wind (DV)
anomalies obtained using NCEP reanalysis data for the period of ARMEX observations (24 June to 15
August 2002). To draw these anomaly time series, values for each day are averaged over the ASIWC
(10°N–20°N, 70°E–75°E) region. Time series of DT, DU, and DV thus obtained are then smoothened
by taking running mean over 5 days. (b) Spectra of DT and DU time series shown in Figure 5a, obtained
using FFT analysis. (c) Plots of cross‐correlation functions between DT and DU and DU and DV time
series. These time series were passed through a band‐pass filter of 14–18 days before obtaining the cross‐
correlation functions.
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Figure 6a. Diagrams showing locations of cold point tropopause (CPT) ≤191 K observed using
CHAMP and COSMIC satellite missions during summer monsoon months. The pluses denote CHAMP
observations, and circles denote COSMIC observations. The COSMIC data set contains very little
retrieval near the equator in April and May 2007 compared to other latitudes.
about 10.1 days. It may be mentioned here that strong zonal
mean wind (∼30 m s−1) prevailed, associated with TEJ,
during observations. This wind introduces a Doppler shift
and modifies a wave period that comes out to be 8.6 days,
i.e., about 9 days.
[20] 6. Other types of wave such as (1) Rossby wave with
n = 1 and symmetric mode with zonal wave number ≥7 and
(2) Rossby wave with n = 2 and antisymmetric mode with
zonal wave number ≥7 [Ern et al., 2008] are also examined.
Both of these types of wave modes are westward propagating. Solution of the dispersion relation for these wave
modes [Matsuno, 1966] at the 100 hPa level using the same
values of parameters as used for Rossby‐gravity waves
yields a value of period of (1) ∼40 days and (2) ∼65 days,
respectively. These values of wave period are significantly
larger than the observed wave period.
[21] The possibility of gravity waves is also examined.
These waves do not have any predefined specific direction
and can have horizontal wavelength of about a few hundred
to a few thousand kilometers. Using a simple dispersion
relation [Gossard and Hooke, 1975], we have computed the
wave period (using the same parameters as used for RGW),
which comes out to be ∼13 days, which is in good agreement with the observed wave period of ∼15 days. Still, there
is a possibility that observed wave disturbances belong to
the gravity wave category but with a constraint that such
large‐period gravity waves are not commonly reported.
[22] To summarize, it appears that some of the observed
wave characteristics are close to the RGW (with horizontal
wave number ≥7). The computed period from the dispersion
relation is somewhat shorter than the actual observed period
of the wave (i.e., ∼15 days). It appears that observed waves
are not pure RGW, but rather they are a combination of
wave systems such as RGW and some other long‐period
waves. There is also a possibility that the observed wave is
an equatorial slow‐moving (computed phase velocity is
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Figure 6b
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Figure 7. Plot of height profile of ∣DT∣, which is the
mean value of absolute difference in CHAMP satellite
and COSMIC satellite temperature measurements (i.e.,
CHAMP minus COSMIC) at various height levels. Horizontal bars show the standard deviation in ∣DT∣ for the
simultaneous temperature measurements by the two satellites (see text).
∼−3.5 m s−1 for the observed 15 day period) gravity wave
associated with convection and the TEJ. Dhaka et al. [1993]
have also reported similar waves using satellite images over
the Indian region, with similar period (∼18 days), which had
a link with the convection activity on the same scale.
[23] ARMEX data support the view that the occurrence of
low CPT temperature extends over AS as well. The
CHAMP and COSMIC satellite observations of atmospheric
temperature are now examined for a broader view of spatial
and temporal distribution of temperature.
3.2. Spatial Distribution of Extreme Low CPT
Temperatures
[24] To examine spatial distribution of CPT temperature,
CHAMP‐ and COSMIC‐derived temperature profiles are
used. Out of all the CPT points, low CPT temperature points
(T ≤ 191 K) are then plotted against the geographic location
of the satellite at the time of measurement. Plots of low CPT
temperature obtained from the CHAMP satellite during
April–August 2002 are shown in Figure 6a. We have chosen
CHAMP satellite data for the year 2002 as they overlap with
the ARMEX campaign period. It may be mentioned here
that geospatial samplings of CHAMP satellite observations
are limited. Since COSMIC satellite provides a large number of sampling points of CPT temperature, available
COSMIC satellite observations are also used to supplement
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CHAMP satellite observations. In Figure 6a (middle and
right) COSMIC satellite observations of low CPT temperature on each day during the periods April–September 2007
and April–September 2008 are also plotted. Table 1 presents
statistics of low CPT temperature deduced from CHAMP
and COSMIC observations over the region 0°N–30°N and
40°E–120°E. The following important features may be
noted from Figure 6a. First, a number of cases of low CPT
temperature (T ≤ 191 K) do occur during the early part of
monsoon (May and June) season. This is also confirmed
from data presented in Table 1. Second, areas of the low
CPT temperature (T ≤ 191 K) are often seen to extend up to
Africa’s Horn region, especially during May–June. These
features are noted more clearly in Figure 6b, which shows
the contour plots of the occurrence ratio of the cases of low
CPT temperature to the total number of CPT observations in
each grid area of 2.5° × 2.5°. An enhanced number of
observations (Figure 6b) of low CPT temperature over the
Asian monsoon region can be clearly noted during June–
August. To check if any bias exists between temperature
profiles obtained from CHAMP and those obtained from
COSMIC, simultaneous measurements of atmospheric
temperature by the two satellites are compared. For this
comparison, 68 temperature profiles from each satellite
taken during August–September 2006 are selected in such a
way that the two satellites colocate with less than ±1° separation in latitude and longitude and have the same tropopause height and that the pass of the two satellites is within
±3 h. Figure 7 shows the height profile of the mean absolute
difference between temperature measurements made by the
two satellites in the vicinity of the tropopause. The mean
absolute temperature difference at the height of 16.5 km is
found to be 0.3 K with a maximum value of 0.6 K. This is
consistent with the analysis of Liou et al. [2007]. They have
compared the COSMIC and CHAMP radio occultation (RO)
temperature profile with NCEP data and noted that in the
height range of 12–20 km, the COSMIC and CHAMP RO
temperature profiles and NCEP data agree within ±0.5 K.
3.3. Seasonal Oscillations in the Occurrence of Low
CPT Temperature
[25] In addition to the geospatial distribution of low CPT
temperature during monsoon season it would be interesting
to see how low CPT temperature is spatially distributed
during other seasons and also to find out whether there is
any association between the spatial distribution of the low
CPT temperature and convection activity. Generally, low
values of OLR indicate enhanced convection activity.
COSMIC satellite observations are therefore used to
examine the monthly variation during the year 2007 for
observing spatial occurrence of the area of low CPT
temperature and that of low OLR. Figure 8a shows the
contour plots of monthly mean OLR from January 2007 to
December 2007. The crosses shown in Figure 8a denote
the low CPT temperature (≤191 K) observed by the
COSMIC satellite. In the summer monsoon season (May–
September) both the low CPT temperature and low OLR
Figure 6b. Contour maps of the occurrence ratio of the number of low CPT observations to the total number of CPT
observations for the monsoon months drawn using COSMIC satellite observations for the years 2007 and 2008. The ratio
(r) is computed for each grid area of 2.5° × 2.5°. White represents grid areas where observations are not available.
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Table 1. Tropopause Temperature Characteristics in the Region 0°N–30°N, 40°E–120°E Deduced From CHAMP and COSMIC Satellite
Missionsa
CHAMP
Tropopause
Month Temperature (K)
April
May
June
July
August
<191
>191
<191
>191
<191
>191
<191
>191
<191
>191
2002
2003
2004
57 (37%)
96
79 (55%)
64
13 (15%)
71
35 (35%)
65
23 (19%)
97
42 (38%)
67
56 (64%)
32
40 (32%)
83
17 (15%)
99
10 (10%)
89
56 (53%)
49
No Data
3
22 (23%)
75
24 (20%)
97
19 (13%)
129
COSMIC
2005
2006
44 (31%) 15 (45%)
96
18
28 (52%) 73 (40%)
26
111
55 (47%) 22 (26%)
63
64
24 (15%) no data
140
no data
12 (8%)
7 (7%)
128
97
Mean Occurrence of
CPT <191 K (%)
39.6
50.3
30.8
20
11.6
2006
2007
19 (40%)
28
121 (41%)
172
148 (45%)
183
64 (17%)
304
83 (8%)
146
563 (37%)
949
500 (30%)
1115
588 (41%)
839
395 (25%)
1166
339 (17%)
1598
Mean Occurrence of
CPT <191 K (%)
37
32
45
24
14
a
Values in parentheses represent percentage occurrences of cases with tropopause temperature <191K.
occur at the northern latitudes. In the postmonsoon season
(i.e., October) almost similar patterns prevail though locations of low OLR and low CPT temperature move closer
to the equator. In northern winter season (November–
February), the area of low OLR is observed south of the
equator and the area of low CPT also moves southward.
Almost a similar pattern is observed in March and April.
Thus, these observations show a close association between
the latitudinal movement of the area of low OLR and that
of low CPT temperature. Enhanced occurrences in the
cases of low CPT temperature over the ASIWC, Indian
landmass (ILM) (10°N–20°N, 72.5°E–85°E) and Bay of
Bengal (BOB) (10°N–20°N, 85°E–90°E) regions during
May–July can be noted in Figure 8b, which shows the
plots of monthly mean OLR and occurrence ratio of low CPT
temperature over these regions. The enhanced occurrence
ratio appears to precede the appearance of low OLR which
represents enhanced convection and passage of the ITCZ
over these regions. This may be due to the influence of
intraseasonal oscillation as discussed in section 3.4. It may
Figure 8a. Monthly mean OLR for the months of January 2007 to December 2007. Crosses represent
the points of low CPT temperature (≤191 K) observed by COSMIC satellite each month during this
period. The COSMIC data set contains very little retrieval near the equator from March to May compared
to other latitudes.
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Figure 8b. Plots of time series of monthly mean OLR and monthly mean occurrence ratio of the number
of low CPT observations to the total number of CPT observations from COSMIC satellite observations
over the ASIWC, ILM, and BOB regions for the year 2007.
be mentioned here that the ITCZ in the month of January is
normally located at 12°S–15°S. In the months of summer
monsoon, the ITCZ merges with the monsoon trough, and in
the month of July, the ITCZ lies at the 20°N–24°N latitude
range [Holton et al., 2003]. Seasonal movement of low OLR
or the convection activity is an indicator of the seasonal
movement of the ITCZ. Therefore, it may be concluded that
the Indian region shows latitudinal variability of low CPT
temperature due to the movement of the ITCZ.
3.4. Intraseasonal Oscillation in OLR and CPT
Temperature
[26] Another important oscillation observed during the
Asian summer monsoon (June–September) period is known
as intraseasonal oscillations with a period of ∼30–60 day
[Krishnamurti and Bhalme, 1976; Yasanuri, 1979; Krishnamurti
and Subrahmanyam, 1982]. These intraseasonal oscillations
are known to be closely associated with the active and break
monsoon conditions over India. Convective activity (represented
Figure 9. Plots of time series of daily mean OLR over the Arabian Sea and Indian west coast (ASIWC)
region and zonal wind (U) at the 850 hPa level (U850) measured on board Sagar Kanya during the
ARMEX campaign. OLR time series is smoothed after taking the 5 day running mean. The missing points
in U850 observations are filled using linear interpolation. The smoothed time series of U850 is then
obtained after taking the running mean over 5 days. Horizontal bars show the break monsoon period over
India as reported by the India Meteorological Department.
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Figure 10. Time series plots of anomaly (a) OLR measurement (DOLR), (b) CPT temperature measurements by the COSMIC satellite (DT), and (c) CPT height (Dh) plotted over the ASIWC, ILM, and BOB
regions for the period 1 May to 30 September 2007. To examine modulation by intraseasonal oscillation,
DT and DOLR time series plots are drawn after taking the running average over 13 days. Thin horizontal
bars and thick horizontal bars represent the periods of active and break monsoon, respectively, over India.
by low OLR values) and the low‐level jet (LLJ) with its
core at 850 hPa level are known to show intraseasonal variability during June–September. During the active monsoon
periods, when there is an eastward band of stray convective
heating in the latitudes ∼10°N–20°N and longitudes 70°E–
120°E, the LLJ axis passes through peninsular India. This
provides moisture for the increased convection in the BOB
and for the formation of monsoon associated depressions in
this region [Joseph and Sijikumar, 2004]. Association
between OLR and LLJ is examined using 850 hPa level
zonal wind U850 measured using radiosondes launched on
board ORV Sagar Kanya during the ARMEX campaign
period and daily mean OLR from NOAA over the ASIWC
region for the same period. Figure 9 shows the smoothed
time series of OLR after taking the running average over
5 days and time series of zonal wind U850 measured on board
Sagar Kanya during the ARMEX campaign. Missing
observations were filled using linear interpolation, and
smoothed time series of U850 was obtained after taking the
running average over 5 days, and the same is also plotted in
Figure 9. Figure 9 shows that both the parameters, namely,
OLR and U850, are modulated by a wave with a period of
15–20 days and the intraseasonal oscillation with a periodicity of ∼40 days. Horizontal bars denote the break monsoon
period over India as reported by the India Meteorological
Department. It may be noted that U850 is weak during
the first monsoon break period as expected but moderate
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Figure 11. (a) Plots of time series of DT and DOLR over the ILM region for the period of Julian days
180–268. (b) Corresponding time series after passing through a band‐pass filter of 14–60 days. (c) Cross‐
correlation function obtained using DT and DOLR time series shown in Figure 11b.
winds are observed during the second break period, indicating that LLJ is passing close to Sagar Kanya.
[27] It may be noted that intraseasonal oscillation in
convection activity (represented by OLR) could also result
in similar wave modulation of temperature in the tropopause
region as intense convection activity is considered to be one
of the source mechanisms for its cooling. Therefore, an
attempt is made to delineate the intraseasonal oscillation in
CPT temperature measurements by the COSMIC satellite
and to determine the association of the same with observed
similar oscillations in OLR. For this aspect, daily mean OLR
data for the period 1 May to 30 September 2007 are taken
from Kalpana‐1 satellite measurements and the CPT temperature data are used from COSMIC satellite observations
for the same period. COSMIC data for the year 2007 are
selected for this study as a sufficient number of profiles are
available during this period. Figure 10 shows the time series
of anomaly in OLR (DOLR, Figure 10a), CPT temperature
(DT, Figure 10b), and CPT height (Dh, Figure 10c) over
the ASIWC, ILM, and BOB regions. To examine the
intraseasonal oscillation, time series plots in Figure 10 are
smoothened by taking the running average over 13 days
so as to remove the short‐period oscillations of period
<13 days. Figure 10 show that intraseasonal oscillation
modulates OLR, CPT temperature, and CPT height over the
three regions, namely, the ASIWC, ILM, and BOB. This
particular oscillation can be seen moving eastward as the
signatures appear first over the ASIWC and later over the
BOB (Figure 10a), and therefore it needs to be distinguished
from the shorter period oscillation (∼15 days) discussed
earlier. A careful examination of Figure 10a reveals that
DOLR over the ILM region attains maxima at Julian days
137, 190–195, and 225–230. Similar periodicity can also be
noted in DT time series (Figure 10b) with maxima at Julian
days 150, 195–220, and 228–250. The time series of
Dh (Figure 10c) also shows a similar modulation. Figure 10
thus shows that (1) the period of intraseasonal oscillation
has varied from 25 to 55 days as the monsoon has progressed
and (2) intraseasonal oscillation in OLR also modulates CPT.
A period of 26–32 days tend to modulate OLR and CPT
temperature between Julian days 180–268 (Figure 11a).
Figure 11b shows the corresponding time series after passing
through a band‐pass filter of 14–60 days. Figure 11c shows
the cross‐correlation function between DOLR and DT series
in Figure 11b which indicates that DOLR is advanced in
phase. Enhanced occurrences of the events of low CPT
temperature over the AS during the early monsoon season
appears to be due to the modulation of OLR, CPT temperature, and height by the intraseasonal oscillation, as this
oscillation appears to begin quite early during the monsoon
season (Figure 10a). The observed intraseasonal modulation
of the tropopause temperature could be one of the contributing factors for the intraseasonal oscillation in the water
vapor of the upper troposphere over the Asian monsoon
region as discussed by Zhan et al. [2006].
4. Summary and Conclusions
[28] Present studies show that low CPT temperature (T ≤
191 K) occurs frequently over the AS and adjoining areas in
addition to the BOB region. Areas of low CPT temperature
extend even to Africa’s Horn region. Occurrence of low CPT
temperature is also confirmed using recent observations
obtained from COSMIC and CHAMP satellites. Wide geographical coverage by extreme low tropopause temperature
occurs during the early part of monsoon season. ARMEX
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campaign and CHAMP‐COSMIC satellite observations have
confirmed the wider spatial coverage of the phenomenon of
low CPT temperature.
[29] An interesting point to be noted from the present
study is the observation of a modulation of tropopause
temperature over the Asian monsoon region by three oscillations with different sources and spatial and temporal
scales. First, a large‐scale westward propagating wave with
a period of ∼15 days with origin in longitudinal fluctuations
in the TEJ and convection has been identified. Second,
seasonal variation of low tropopause temperatures over the
Asian monsoon region is noted to be closely linked to the
latitudinal movement of the ITCZ and associated convection
activity. Third, eastward propagating intraseasonal oscillation with a period of 25–55 days is also noted to modulate
the tropopause (CPT) temperature and height. The
intraseasonal oscillation is known to originate near the
African east coast and is closely linked to the passage of
the LLJ over the Indian tropical belt. Modulation of CPT by
intraseasonal oscillation could be one of the contributing
factors for the recently reported intraseasonal variation of
water vapor of the upper troposphere over the Asian monsoon region reported recently by Zhan et al. [2006].
[30] Acknowledgments. Authors are thankful to G. S. Bhat for making the radiosonde data for the ARMEX campaign period available and to
the India Meteorological Department (IMD) for providing daily mean OLR
data for the monsoon season 2007 and dates of active and break monsoon
periods. ARMEX project was funded by the Department of Science and
Technology, government of India. The authors are grateful to the Information System Data Centre (ISDC) for CHAMP data and the COSMIC Data
Analysis and Archive Center (CDAAC) for COSMIC data used for this
study. NCEP reanalysis data are provided by the NOAA OAR/ESRL PSD,
Boulder, Colorado, United States. Sincere thanks are due to M. Fujiwara
and G. S. Bhat for their valuable suggestions. The research work
reported here is funded by the CAWSES‐India program sponsored
by ISRO/DOS, government of India. Two of the authors (C. J. Johny and
Vivek Panwar) are thankful to CSIR, New Delhi, India, for awarding a senior
research fellowship. The authors are thankful to the director, National Physical
Laboratory, New Delhi and HOD, Radio and Atmospheric Sciences Division,
NPL, for their continuous support.
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R. Gautam, A. R. Jain, C. J. Johny, T. K. Mandal, and V. Panwar, Radio
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