Indian Journal of Radio & Space Physics
Vol 42, October 2013, pp 298-308
Long term variability in temperature in the upper troposphere and lower
stratosphere over Indian and Indonesian region using Atmospheric Infrared
Sounder (AIRS) observations
A Gupta1,2,$,*, V Kumar1,2, V Panwar1, R Bhatnagar1 & S K Dhaka1
1
Department of Physics, Rajdhani College (University of Delhi), Raja Garden, New Delhi 110 015, India
2
Department of Physics and Astrophysics, University of Delhi, Delhi 110 007, India
$
E-mail: [email protected]
Received 2 July 2012; revised 25 February 2013; accepted 28 March 2013
The spatio-temporal patterns and vertical structure of the temperature anomalies, obtained from Atmospheric
Infrared Sounder (AIRS), spanning over 9 years (2003-2011) over Indian and Indonesian regions in the upper
troposphere and lower stratosphere (UTLS) region, have been examined. An equatorial biennial oscillation with amplitude
ranging ~4-6 K and having a period of ~24 months was observed in lower stratosphere (LS) from 100 to 50 hPa,
whereas it was not seen in the upper troposphere (UT) from 150 to 200 hPa over both the Indian and Indonesian regions.
At 50, 70 and 100 hPa, the annual oscillations (AO) with amplitude ~1-3.5 K were observed near equator in the
UT region (at 150 and 200 hPa). However, near subtropics, the nature and amplitude of AO over Indian and Indonesian
region was found to be different at different pressure levels. The amplitude of AO at 50 and 70 hPa was larger by ~1.0-1.5 K
over Indonesian region as compared to Indian region. But at 100 and 200 hPa, the amplitude of AO over Indian
region was larger by ~2-3 K, as observed over Indonesian region. It was also observed that the subtropical AO over
both the regions was found to be out of phase with the equatorial AO. The subtropical warm temperature anomalies
at 100 hPa were found to be typically collocated with subtropical higher values of ozone (using AIRS data) present
in the LS. It was also noted that the temperature anomalies at 100 hPa were also found to be anti-correlated with those at 200
hPa.
Keywords: Upper troposphere and lower stratosphere (UTLS) region, Temperature anomaly, Subtropical temperature
anomaly, Total column ozone
PACS Nos: 92.60.hd; 92.60.hf; 92.60.hv
1 Introduction
Temperature in the troposphere and lower
stratosphere in the Earth’s atmosphere plays an
important role in the radiation budget and in
understanding the variation of various chemical
species1,2. The important aspect of studying the
tropospheric and lower stratospheric temperature and
its trends would help in better understanding of the
exchange of the trace constituents between
troposphere and stratosphere. Tropopause marks the
transition between the troposphere and the
stratosphere and plays an important role in
stratosphere-troposphere exchange (STE) and wave
propagation between the regions3-5. Therefore, study
of dynamical features near and above the tropopause
is important.
Temperature controls the rates of chemical
reactions and thus the ozone (O3) abundance, and it is
one of the most important parameters in terms of its
influence on dynamical and radiative processes in the
terrestrial atmosphere, particularly, in the upper
troposphere – lower stratosphere (UTLS) region.
Observational studies of the UTLS thermal structure
have traditionally been based on the global radiosonde
network with large data sparse regions6-9 or modeldependent analysis and reanalysis products with
relatively low vertical resolution and attendant
biases7,10,11. A significant advancement in the
understanding of the UTLS thermal structures has
recently come from the satellite observations. The
thermal structure of tropical tropopause based on the
GPS/MET data have been studied12,13. Observations
of the global tropopause became possible with the
launch of the Challenging Mini-satellite Payload
(CHAMP)14 and Satellite de Apllicaciones
Cientificas-C (SAC-C) missions15 that increased the
GUPTA et al.: LONG TERM VARIABILITY IN TEMPERATURE IN UTLS OVER INDIAN AND INDONESIAN REGION 299
spatial and temporal sampling of the Global
Positioning System Radio Occultation (GPS RO)
data. Some of the studies have characterized the
global tropopause parameters using the CHAMP and
SAC-C data16-20. These have focused mainly on the
time-mean thermal structure of the UTLS instead of
its variability.
The main purpose of this work is to characterize
and quantify on long term basis, the spatio-temporal
patterns and vertical structure of the temperature
variability in the UTLS and also to examine the role
of ozone in influencing this temperature variability
using Atmospheric Infrared Sounder (AIRS)
observations. The advantage of AIRS data is that it
provides very high spatial and temporal resolution
(1° × 1°) and the number of profiles, available in each
day is of the order of 324,000, which gives high
confidence in using such a high resolution data.
Gupta et al.21 have shown the details of AIRS data in
their recent study on meridional temperature gradient
over Indian region.
In this paper, long term variability in temperature
anomalies in the lower stratosphere and upper
troposphere region at equator and subtropics has been
analysed, i.e. from 40°N to 40°S over Indian and
Indonesian region. In addition, the role of total
column ozone has also been analysed in influencing
the variation in temperature at equator and near
subtropics in the UTLS region.
2 Data analysis
The AIRS/Advanced Microwave Sounding Unit
(AMSU) sounding system22,23 on the NASA Aqua
platform has been operational since 01 September
2002. The AIRS and AMSU instruments are
each cross-track scanning nadir sounders that are
co-aligned and have a swath roughly 1650 km wide.
The AIRS instrument is a 2378-channel grating
spectrometer measuring infrared radiance at
wavelengths in the range 3.7–15.4 µm with a
horizontal resolution of about 13.5 km at nadir22. The
AMSU instrument is a 15-channel microwave
radiometer with a horizontal resolution of about 45
km at nadir24. Nine AIRS fields of view are contained
within each AMSU field of view. The AIRS/AMSU
geophysical retrieval method uses an iterative, leastsquare physical inversion of cloud-cleared infrared
radiances, obtained from a combination of infrared
and microwave observations. The algorithm is
referred to as the AIRS/AMSU combined retrieval25.
Following common practice, any discussion of AIRS
in this work implicitly refers to the AIRS/AMSU
system. The AIRS sounding system produces about
324,000 temperature profiles every day, separately by
ascending and descending orbits. The horizontal
resolution is about 45 km and the vertical resolution is
about 1 km for AIRS temperature profile retrievals,
referred to as Level-2 (L2) products25.
AIRS
(AIRX3STM)
temperature
data
(http://airs.jpl.nasa.gov/) has been used for the present
analysis. The AIRS Level-3 (L3) temperature profile
product is the gridded averages of the AIRS
L2 temperature profiles on horizontal 1°× 1° grids and
24 pressure levels from 1000 hPa to 1 hPa. It may
also be noted that only high quality measurements
from the level 2 products are used to derive the level
3 products to avoid the fallback cases26,27. Monthly
averaged temperature data at 5 different pressure
levels 200, 150, 100, 70, and 50 hPa over Indian and
Indonesian region for 9 years (over 2003-2011) have
been used. Hereafter, levels 200 hPa and 150 hPa will
be referred to as tropospheric and levels with pressure
less than 100 hPa as stratospheric. According to a
study11 based on European Centre for Medium Range
Forecast (ECMWF), United Kingdom Meteorological
Office (UKMO) and National Centre for
Environmental Prediction (NCEP) data, the 100 hPa
height tracks nearly identically the tropopause height.
Hence, the 100 hPa level will be referred to as the
tropopause level. Validation of AIRS temperature
retrievals over various regions of high latitudes have
already been performed28-30.
To find the influence of ozone on temperature in
UTLS region, AIRS (L3) version 5, monthly
averaged, total column ozone data have been used. An
evaluation of the Atmospheric Infrared Sounder
(AIRS) version 5 (V5) retrieved ozone profiles with
total column ozone has already been performed using
collocated ozonesonde (O3SND) profiles and total
ozone measurements from the World Ozone and
Ultraviolet Radiation Data Centre (WOUDC)
archives31. The V5 retrieval biases with global
O3SNDs are less than 5% for both the stratosphere
and the troposphere. The root mean square (RMS)
differences are less than 20% for the upper
stratosphere and are close to 20% for the lower
stratosphere and the troposphere. Total ozone
amounts from V5 versions agree well with the global
Brewer Dobson (BD) station measurements with a
bias of less than 4% and an RMS difference of
approximately 8%. Analysis of V5 total ozone
300
INDIAN J RADIO & SPACE PHYS, OCTOBER 2013
monthly maps reveals that the V5 ozone retrievals
depict seasonal trends and patterns in concurrence
with ozone monitoring instrument (OMI) and Solar
Backscatter Ultra-Violet Experiment (SBUV/2)
observations.
3 Results and Discussion
3.1 Latitudinal and vertical variability in the annual and
biennial oscillations over Indian region
The temperature anomalies of AIRS data spanned
over 2003-2011 ranging 40°N-40°S are analysed at
five different pressure levels, i.e. at 200, 150, 100,
70 and 50 hPa over Indian and Indonesian region.
Figures (1 and 2) represent the latitude-time sections
of temperature anomalies for 9 years at 50, 70 and
100 hPa and at 100, 150 and 200 hPa, respectively
over Indian region. The temperature anomalies
contour in Fig. 1 shows the presence of equatorial
biennial oscillations (BO) of amplitude ranging 4-6 K
with period ~ 2 years in the LS (50, 70 hPa) and at
100 hPa. These BO (of period ~ 2 years) are similar to
as observed by Pillai32,33 over tropical Indian region.
They named these oscillations as tropospheric
biennial oscillations (TBO) and extensive work has
been done in associating these oscillations with the
Indian monsoon, Indian dipole moment, El Nino
southern oscillations (ENSO), etc. They have
highlighted the role of ocean system in maintaining
the TBO. In the present study, similar oscillations
have also been observed with a period of ~ 2 years in
the lower stratosphere (LS). The BO observed in LS
appears to be influenced by the changes in
temperature occurring in the troposphere.
Besides observing BO near equator, annual
oscillations (AO) (indicating seasonal variability)
have also been observed in the temperature anomalies
as shown in Fig. 1 at 50, 70, 100 hPa and
the amplitude of the oscillations is of the order of
~1.0-3.5 K. As one moves below in the upper
troposphere (UT) region (at 150 and 200 hPa
shown in Fig. 2), the AO turns weak with amplitude
of ~1.0-1.5 K [Fig. 3(a)]. From Figs (1 and 2), it can
also be noticed that AO presents different nature near
equator and in subtropics in the UTLS region. At
50 hPa, the equatorial temperature anomalies show
AO with amplitude of the order ~1.0-2.0 K; while at
Fig. 1 — Latitude time section of temperature anomalies for 9 years (represented as 108 months) over Indian region at 50, 70 and 100 hPa
GUPTA et al.: LONG TERM VARIABILITY IN TEMPERATURE IN UTLS OVER INDIAN AND INDONESIAN REGION 301
Fig. 2 — Latitude time section of temperature anomalies for 9 years (represented as 108 months) over Indian region at 100, 150 and 200 hPa
Fig. 3 (a) — Time series of temperature anomalies at different pressure levels (200, 150, 100, 70, 50 hPa) for 9 years (2003-2011) at
equator over Indian region
302
INDIAN J RADIO & SPACE PHYS, OCTOBER 2013
70 and 100 hPa, the amplitude rises to ~2.0-3.5K.
However, in the UT region (at 150 and 200 hPa), the
amplitude of AO reduces (~1.0-1.5K) and are not very
prominent as well [Fig. 3(a)]. In the subtropics, at
50 and 70 hPa, AO of amplitude ~1-2 K is found
similar to equatorial region. But at 100 and 200 hPa
(pronounced over northern hemisphere), the
amplitude of AO becomes stronger (~5.0-6.0 K) as
shown in Fig. 2 and Fig. 3(b). Thus, analysis suggests
that in subtropics, AO prevails with large amplitude
than in equatorial region.
It was, further, noticed that at 100, 150 and
200 hPa, the equatorial AO were found to be out of
phase with the AO observed near subtropics, i.e. the
warm anomalies in subtropics are found adjacent to
the cold anomalies of equatorial region [Fig. 2 and
Fig. 3(a,b)]. It is known that in subtropics 100 and
150 hPa lie in the stratosphere and ozone is the key
component for radiative balance in stratosphere.
To observe any influence of ozone on subtropical
temperature anomalies, total column ozone data from
AIRS has been analysed. Since the ozone data are
also taken from AIRS, having the same resolution and
retrieval procedure as temperature data, therefore, the
association between temperature and ozone can be
easily made.
About nine years of monthly averaged total column
ozone data has been analysed from 40°N to 40°S over
Indian region (Fig. 4), which represents the variation
in ozone near equator (20°N-20°S) and subtropics.
A very strong annual oscillation in ozone is observed
in subtropics, which is not seen in the equator. The
higher values [~350-400 Dobson unit (DU)] of ozone
during winter months (in northern hemisphere (NH)]
are observed to be collocated with the subtropical
warm anomalies in temperature for the same latitude
Fig. 3 (b) — Time series of temperature anomalies at different pressure levels (200, 150, 100, 70, 50 hPa) for 9 years (2003-2011) at
subtropics over Indian region
GUPTA et al.: LONG TERM VARIABILITY IN TEMPERATURE IN UTLS OVER INDIAN AND INDONESIAN REGION 303
Fig. 4 —Latitude time section monthly averaged total column ozone data for 9 years (represented as 108 months) over Indian region
range [Figs (2 and 4)]. Increased ozone (in the
subtropics) could have possibly caused the
enhancement in temperature and hence, the warm
anomalies appear over these latitudes. The other
possibility of this difference is coming from the fact
that pressure levels of 100 and 150 hPa are the
representative of stratosphere, while these levels are
the part of troposphere in the equatorial region.
From Fig. 2, it is also noticed that the subtropical
temperature anomalies (in NH) at 100 hPa are anticorrelated with anomalies at 200 hPa. The results
reported here are found similar to the observations
made by Bencherif et al.34 over Durban, South Africa
(30°S, 30.9°E), a subtropical site in southern
hemisphere (SH). The authors have analysed 22 years
of temperature data in the UTLS region and found
that the seasonal cycle in temperature at 250 hPa is
anti-correlated with the seasonal cycle at 100 hPa.
Similar behaviour has also been observed between
100 and 200 hPa in subtropical temperature
anomalies, which is more pronounced in NH.
It is apparent from the above observations that the
temperature changes, which take place at 200 hPa, are
reflected at 100 hPa level, but with a time delay and
could be the possible reason for the anti-correlation.
Observations of delayed response above 200 hPa level
in temperature indicate that strong horizontal
transport35 could have a role in controlling the
temperature. Panwar et al.36 have shown that the
transport of water vapour from 215 hPa to 68 hPa
takes about 3-4 months.
3.2 Latitudinal and vertical variability in the annual and
biennial oscillations over Indonesian region
Figures (5 and 6) show the latitude - time plots for
the temperature anomalies observed over Indonesian
region at 50, 70 and 100 hPa, and at 100, 150 and
200 hPa, respectively. Figure 5 shows the presence of
equatorial BO of amplitude ~4.0-6.0 K of period
~2 years in temperature anomalies at 50, 70 and
100 hPa. Besides, observing BO near equator, AO has
also been observed with amplitude of ~1.0-3.5 K, as
observed over Indian region. As one moves down to
150 and 200 hPa, the amplitude of AO becomes
less ~1.0-1.5 K [Fig. 6 and Fig. 7(a)]. It can be
noticed from the above observations that the nature
and variations in BO and AO near equator have
similar behaviour as observed over Indian region.
However, near subtropics, the behaviour of AO over
Indonesian region is different from Indian region.
At 50 and 70 hPa, over Indonesian region, amplitude
of AO is found larger (~2.0-3.0 K at 50 hPa and ~3.54.5 K at 70 hPa), as compared to the Indian region
[Fig. 7(b)]. The variation in amplitude of
AO over Indonesian region is more, as it is highly
convective region as compared to Indian region, and
partly it may be due to the effect of walker circulation
in this region, which is not examined here.
However, at 100, 150 and 200 hPa (over
Indonesian region), besides observing AO of
amplitude ~3.0-4.0 K, ~1.0-2.0 K and ~2.0-3.0 K,
respectively, semi-annual oscillations (SAO) of weak
amplitude (~1.0-2.0 K) are also observed [Fig 6 and
304
INDIAN J RADIO & SPACE PHYS, OCTOBER 2013
Fig. 5 —Latitude time section of temperature anomalies for 9 years (represented as 108 months) over Indonesian region at 50, 70 and 100 hPa
Fig. 6 — Latitude time section of temperature anomalies for 9 years (represented as 108 months) over Indonesian region at 100, 150 and 200 hPa
GUPTA et al.: LONG TERM VARIABILITY IN TEMPERATURE IN UTLS OVER INDIAN AND INDONESIAN REGION 305
Fig. 7 (a) —Time series of temperature anomalies at different pressure levels (200, 150, 100, 70, 50 hPa) for 9 years (2003-2011) at
equator over Indonesian region
Fig. 7 (b) — Time series of temperature anomalies at different pressure levels (200, 150, 100, 70, 50 hPa) for 9 years (2003-2011) at
subtropics over Indonesian region
306
INDIAN J RADIO & SPACE PHYS, OCTOBER 2013
Fig. 8 — Latitude time section monthly averaged total column ozone data for 9 years (represented as 108 months) over Indonesian region
Fig. 7(b)]. Bencherif et al.34 have shown similar
observations for SAO in their study over Durban
which is also a subtropical site.
Over Indonesian region too, the equatorial AO are
found to be out of phase with the subtropical AO.
Similar analysis, as conducted over Indian region, is
being performed in Indonesian region. It has been
found that total column ozone from AIRS (Fig. 8)
is higher near subtropics (20°-40°) as compared to the
equator in both the hemisphere. The high value
(~350-400 DU) of ozone, during winter months,
observed to be collocated with the subtropical warm
anomalies in temperature, which is evident from
Figs (6 and 8). High values of ozone (in the
subtropics) could have possibly caused the increase in
temperature (and hence the warm anomalies appear)
over these latitudes.
4 Summary and Conclusions
The temperature anomalies over a period
2003-2011 from AIRS are analysed at different
pressure levels at 200, 150, 100, 70 and 50 hPa in the
range of 40°N-40°S over Indian and Indonesian
region to observe long term latitudinal and vertical
structure of temperature variability in the UTLS
region. The salient features are:
(i) Biennial oscillations (BO) of period ~2 years with
amplitude ~4.0-6.0 K were observed in the
equatorial temperature anomalies at 50, 70 and
100 hPa both over Indian and Indonesian region.
(ii) Besides observing BO near equator, annual
oscillations (AO) in the temperature anomalies
were also observed at 50, 70, 100 hPa with
amplitude ~1.0-3.5 K, which reduces to ~1.0 K in
the UT region (at 150 and 200 hPa) both over
Indian and Indonesian region.
(iii) In the subtropics, the behaviour of AO over
Indian and Indonesian region is found to be
different. At 50 and 70 hPa, over Indian region,
the amplitude is ~1.0-2.0 K but over Indonesian
region, the amplitude increases to 2.0-3.0 K at 50
hPa and 3.5-4.5 K at 70 hPa. At 100 and 200 hPa,
over Indian region, the amplitude of AO is large
(~5.0-6.0 K) as compared to Indonesian region
(~2.0-3.0 K). The variation in amplitude over
Indonesian region in LS is more as it is highly
convective region and the upward flux may be
more intense that reaches in LS as compared to
Indian region.
(iv) Over Indonesian region at 100, 150 and 200 hPa,
besides observing AO, SAO of weak amplitude
(~1.0-2.0 K) is also observed (Fig. 6).
(v) It was, further, noted that at 100 hPa and in UT,
the equatorial AO were found to be out of phase
with the AO observed near subtropics, i.e. the
warm anomalies in subtropics are found to lie
adjacent to the cold anomalies of the equatorial
region (both over Indian and Indonesian region).
Large values (~350-400 DU) of ozone during
winter months (in NH) were found to be
collocated with the subtropical warm anomalies in
temperature. Therefore, it appears that seasonal
variations in ozone (in the subtropics) have
caused the warm anomalies in temperature.
(vi) In addition, temperature anomalies at 100 hPa are
also found to be anti-correlated with temperature
GUPTA et al.: LONG TERM VARIABILITY IN TEMPERATURE IN UTLS OVER INDIAN AND INDONESIAN REGION 307
anomalies at 200 hPa, suggesting slow upwelling
due to strong horizontal wind in the UT region.
Acknowledgement
Satellite
data
are
obtained
from
http://airs.jpl.nasa.gov/. The present work is supported
by ISRO/DOS, Government of India, through a
research project under CAWSES-India Program. The
authors would also like to thank Dr Thomas Hearty,
Dr S Wong and Dr C K Liang for their helpful
suggestions regarding the retrievals of temperature
profiles using AIRS data.
References
1
Pan L L, Randel W J, Gary B L, Mahoney M J & Hinsta E J,
Definitions and sharpness of the extratropical tropopause: A
trace gas perspective, J Geophys Res (USA), 109 (2004)
D23103, doi: 10.1029/2004JD004982.
2
Rosenlof K H, Kley D, Russell III J M, Chiou E W, Johnson
D G, Kelly K K, Michelsen H A, Nedohula G E, Remsberg
E E, Toon G C & McCormick M P, Stratospheric water
vapour increases over the past half century, Geophys Res Lett
(USA), 28 (2001) pp 1195–1199.
3
Holton J R, Haynes P H, McIntyre M E, Douglass A R, Rood
R B & Pfister L, Stratosphere-troposphere exchange,
Rev Geophys (USA), 33 (1995) pp 403–439.
4
Baray J L, Ancellet G, Taupin G, Bessafi M, Baldy S &
Keckhut P, Subtropical tropopause break as a possible
stratospheric source of ozone in the tropical troposphere,
J Atmos Sol-Terr Phys (UK), 60 (1998) pp 27–36.
5
Sorensen J H & Nielsen N W, Intrusion of stratospheric
ozone to the free troposphere through tropopause folds: A
case study, Phys Chem Earth (UK), 26B (2001) pp 801–806.
6
Gettelman A & Forster P M D, A climatology of the tropical
tropopause layer, J Meteorol Soc Jpn (Japan), 80 (4B)
(2002) pp 911-924, doi: 10.2151/jmsj.80.911.
7
Kiladis G N, Straub K H , Reid G C & Gage K S, Aspects of
inter-annual and intra-seasonal variability of the tropopause
and lower stratosphere, Q J R Meteorol Soc (UK), 127 (576)
(2001) pp 1961-1983, doi: 10.1256/smsqj.57605.
8
Seidel D J, Ross R J, Angell J K & Reid G C, Climatological
characteristics of the tropical tropopause as revealed by
radiosondes, J Geophys Res (USA), 106 (D8) (2001)
pp 7857-7878, doi: 10.1029/2000jd900837.
9
Seidel D J & Randel W J, Variability and trends in the global
tropopause estimated from radiosonde data, J Geophys Res
(USA), 111 (D21), (2006) D21101, doi: 10.1029/2006
jd007363.
10 Highwood E J & Hoskins B J, The tropical tropopause, Q J R
Meteorol Soc (UK), 124 (1998) pp 1579–1604, doi:
10.1002/qj.49712454911.
11 Randel W J, Wu F & Gaffen D J, Inter-annual variability of
the tropical tropopause derived from radiosonde data and
NCEP reanalysis, J Geophys Res (USA), 105 (D12) (2000)
pp 15509–15523.
12 Nishida M, Shimizu A, Tsuda T, Rocken C & Ware R H,
Seasonal and longitudinal variations in the tropical
tropopause observed with the GPS occultation technique
(GPS/MET), J Meteorol Soc Jpn (Japan), 78 (6) (2000)
pp 691-700.
13 Randel W J, Wu F & Rios W R, Thermal variability of the
tropical tropopause region derived from GPS/MET
observations, J Geophys Res (USA), 108 (D1) (2003) 4024,
doi: 10.1029/2002jd002595.
14 Wickert J, Reigber C, Beyerle G, Konig R, Marquardt C,
Schmidt T, Grunwaldt L, Galas R, Meehan T K, Melbourne
W G & Hocke K, Atmosphere sounding by GPS radio
occultation: First results from CHAMP, Geophys Res Lett
(USA),
28
(17)
(2001)
pp
3263-3266,
doi:
10.1029/2001GL013117.
15 Hajj G A, Ao C O, Iijima B A, Kuang D, Kursinski E R,
Mannucci A J, Meehan T K, Romans L J, Juarez M D &
Yunck T P, CHAMP and SACC atmospheric occultation
results and intercomparisons, J Geophys Res (USA),
109 (D6) (2004) D06109, doi: 10.1029/2003jd003909.
16 Kishore P, Namboothiri S P, Igarashi K, Jiang J H, Ao C O
& Romans L J, Climatological characteristics of the
tropopause parameters derived from GPS/CHAMP and
GPS/SAC-C measurements, J Geophys Res (USA),
111 (D20) (2006) D20110, doi: 10.1029/2005jd006827.
17 Randel W J & Wu F, Kelvin wave variability near the
equatorial tropopause observed in GPS radio occultation
measurements, J Geophys Res (USA), 110 (D3) (2005)
D03102, doi: 10.1029/2004jd005006.
18 Schmidt T, Heise S, Wickert J, Beyerle G & Reigber C, GPS
radio occultation with CHAMP and SAC-C: Global
monitoring of thermal tropopause parameters, Atmos Chem
Phys (Germany), 5 (2005) pp 1473-1488.
19 Schmidt T, Beyerle G, Heise S, Wickert J & Rothacher M, A
climatology of multiple tropopauses derived from GPS radio
occultations with CHAMP and SAC-C, Geophys Res Lett
(USA), 33 (4) (2006) L04808, doi: 10.1029/2005gl024600.
20 Schmidt T, Wickert J, Beyerle G & Heise S, Global
tropopause height trends estimated from GPS radio
occultation data, Geophys Res Lett (USA), 35 (11) (2008)
L11806, doi: 10.1029/2008gl034012.
21 Gupta A, Dhaka S K, Panwar V, Bhatnagar R, Kumar V &
Dash S K, AIRS satellite observations of seasonal variability
in meridional temperature gradient over Indian region at
100 hPa, J Earth Sys Sci (India), 122 (1) (2013) pp 201-213.
22 Aumann H H, Chahine M T, Gautier C, Goldberg M D,
Kalnay E, McMillin L M, Revercomb H, Rosenkranz P W,
Smith W L & Staelin D H, AIRS /AMSU /HSB on the
aqua mission: Design, science objectives, data products,
and processing systems, IEEE Trans Geosci Remote Sens
(USA), 41 (2) (2003) pp 253-264, doi: 10.1109/tgrs. 2002.
808356.
23 Chahine Moustafa T, Pagano Thomas S, Aumann Hartmut
H, Atlas Robert, Barnet Christopher, Blaisdell John, Chen
Luke, Divakarla Murty, Fetzer Eric J, Goldberg Mitch,
Gautier Catherine, Granger Stephanie, Hannon Scott, Irion
Fredrick W, Kakar Ramesh, Kalnay Eugenia, Lambrigtsen
Bjorn H, Lee Sung-Yung, Le Marshall John, McMillan W
Wallace, McMillin Larry, Olsen Edward T, Revercomb
Henry, Rosenkranz Philip, Smith William L, Staelin Did,
Strow L Larrabee, Susskind Joel, Tobin David, Wolf Walter
& Zhou Lihang, Improving weather forecasting and
providing new data on greenhouse gases, Bull Am Meteorol
Soc (USA), 87 (2006) pp 911–926.
24 Lambrigtsen B H, Calibration of the AIRS microwave
instruments, IEEE Trans Geosci Remote Sens (USA), 41 (2)
(2003) pp 369-378, doi: 10.1109/tgrs.2002.808247.
308
INDIAN J RADIO & SPACE PHYS, OCTOBER 2013
25 Susskind J, Barnet C, Blaisdell J, Iredell L, Keita F, Kouvaris
L, Molnar G & Chahine M, Accuracy of geophysical
parameters
derived
from
Atmospheric
Infrared
Sounder/Advanced Microwave Sounding Unit as a function
of fractional cloud cover, J Geophys Res (USA), 111 (D9)
(2006) D09S17, doi: 10.1029/2005jd006272.
26 Olsen E T, Susskind J, Blaisdell J & Rosenkranz P,
AIRS/AMSU/HSB version 5 level 2 quality control and error
estimation, JPL/NASA (California Institute of Technology,
Pasadena, USA), 2007a, 15.
27 Olsen E T, Granger S, Manning E & Blaisdell J,
AIRS/AMSU/HSB version 5 level 3 quick start, JPL/NASA
(California Institute of Technology, Pasadena, USA), 2007b, 25.
28 Divakarla M G, Barnet C D, Goldberg M D, McMillin L M,
Maddy E, Wolf W, Zhou L & Liu X, Validation of
Atmospheric Infrared Sounder temperature and water vapor
retrievals with matched radiosonde measurements and
forecasts, J Geophys Res (USA), 111 (2006) D09S15, doi:
10.1029 /2005JD006116.
29 Gao W, Zhao F & Gai C, Validation of AIRS retrieval
temperature and moisture products and their application in
numerical models, Acta Metorol Sin (China), 64 (2006) pp
271–280.
30 Fetzer E J, Preface to special section: Validation of
Atmospheric Infrared Sounder observations, J Geophys Res
(USA), 111 (2005) D09S01, doi: 10.1029/2005JD007020.
31 Divakarla M, Barnet Christopher; Goldberg Mitchell, Maddy
Eric, Irion Fredrick, Newchurch, Mike, Liu Xingpin, Wolf
32
33
34
35
36
Walter, Flynn Lawrence, Labow Gordon, Xiong Xiaozhen,
Wei Jennifer & Zhou Lihang, Evaluation of Atmospheric
Infrared Sounder ozone profiles and total ozone retrievals
with matched ozonesonde measurements, ECMWF ozone
data, and Ozone Monitoring Instrument retrievals, J Geophys
Res
(USA),
113
(2008)
D15308,
doi:
10.1029/2007JD009317.
Pillai P A & Mohankumar K, Interannual variability of
Indian summer monsoon: Role of TBO (VDM Verlag
Publishers, Germany), 2010.
Pillai P A & Mohankumar K, Individual and combined
influence of El Ni˜no–Southern oscillation and Indian Ocean
dipole on the tropospheric biennial oscillation, Q J R
Meteorol Soc (UK), 136 (2010) pp 297–304, doi:
10.1002/qj.579.
Bencherif H, Diab R D, Portafaix T, Morel B, Keckhut P &
Moorgawa A, Temperature climatology and trend estimates
in the UTLS region as observed over a southern subtropical
site, Durban, South Africa, Atmos Chem Phys (Germany), 6
(2006) pp 1301–1320.
Holton J R & Gettelman A, Horizontal transport and the
dehydration of the stratosphere, Geophys Res Lett (USA),
28 (2001) pp 2799-2802.
Panwar V, Jain A R, Goel A, Mandal T K, Rao V R & Dhaka
S K, Some features of water vapour mixing ratio in tropical
upper troposphere and lower stratosphere: Role of
convection, Atmos Res (USA), 108 (2012) pp 86-103,
doi: 10.1016/j.atmosres.2012.02.003.