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Journal ofAtmospheric and Solar-Terrestrial Physics

Journal of Atmospheric and Solar-Terrestrial Physics 71 (2009) 1463–1470

1364-68

doi:10.1

� Cor

E-m

journal homepage: www.elsevier.com/locate/jastp

A report on long-term trends and variabilities in middle atmospherictemperature over Gadanki (13.51N, 79.21E)

S. Sridharan �, P. Vishnu Prasanth, Y. Bhavani Kumar

National Atmospheric Research Laboratory, Gadanki 517 112, Pakala Mandal, Chittoor District, Andhra Pradesh, India

a r t i c l e i n f o

Article history:

Accepted 28 September 2008The present study reports long-term variabilities and trends in the middle atmospheric

temperature (March 1998–2008) derived from Rayleigh backscattered signals received

Available online 10 October 2008

Keywords:

Long-term trends

Temperature

Semiannual oscillation

Solar cycle

Middle atmosphere

Rayleigh lidar

26/$ - see front matter & 2008 Elsevier Ltd. A

016/j.jastp.2008.09.017

responding author. Tel.: +918585 272124; fax

ail address: SuSridharan@narl.gov.in (S. Sridh

a b s t r a c t

by the Nd:YAG lidar system at Gadanki (13.51N, 79.21E). The monthly mean temperature

compositely averaged for the years 1998–2008 shows maximum temperature of 270 K

in the months of March–April and September at altitudes between �45 and 55 km. The

altitude profile of trend coefficients estimated from the 10 years of temperature

observations using regression analysis shows that there exists cooling at the rate with

1s uncertainty of 0.1270.1 K/year in the lower stratospheric altitudes (35–42 km) and

0.270.08 K/year at altitudes near 55–60 km. The trend is nearly zero (no significant

cooling or warming) at altitudes 40–55 km. The regression analysis reveals the

significant ENSO response in the lower stratosphere (1 K/SOI) and also in mesosphere

(0.6 K/SOI). The solar cycle response shows negative maxima of �1.5 K/100F10.7 units at

altitudes 36 km, 41 km and 1 K/100F10.7 units at 57 km. The response is positive at

mesospheric altitude near 67 km (1.3 K/100F10.7 units). The amplitudes and phases of

semiannual, annual and quasi-biennial oscillations are estimated using least squares

method. The semiannual oscillation shows larger amplitudes at altitudes near 35, 45, 62

and 74 km whereas the annual oscillation peaks at 70 km. The quasi-biennial oscillations

show larger amplitudes below 35 km and above 70 km. The phase profiles of semiannual

and annual oscillations show downward propagation.

& 2008 Elsevier Ltd. All rights reserved.

1. Introduction

Temperature variations in the tropical lower andmiddle stratosphere are influenced by the mechanism ofthe regular seasonal cycle, the quasi-biennial oscillation(QBO) in zonal winds, the semiannual zonal windoscillation (SAO) at higher levels, El Nino-SouthernOscillation (ENSO) effects driven by the underlyingtroposphere, and radiative effects, including volcanicaerosol heating (Reid, 1994). Earlier observations showedthat the influence of ENSO cycle was stronger only atheights below 23 km (Reid et al., 1989, for example).

ll rights reserved.

: +918585 272018.

aran).

However, recent observations and model simulationssuggest that the ENSO signature should extend to themesosphere (Sassi et al., 2004; Li et al., 2008). In recentdecades, the release of trace gases from human activityand depletion of stratospheric ozone have the potentialfor causing change in the middle atmospheric tempera-ture. These temperature changes could influence thestratospheric microphysical–chemical processes (WMO,1999). Recognizing its importance, investigation of middleatmospheric temperature variabilities and trends hasbeen a subject of interest for the past two decades.

Using rocketsonde, radiosonde, lidar and satellitemeasurements, there have been many reports on tem-perature trends in the middle atmosphere. A completereview on stratospheric and mesospheric trends can befound in Ramaswamy et al. (2001) and Beig et al. (2003),

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respectively. The first trend results based on long-termrocket observations of mesospheric temperature overRussia show that there exists cooling at the rate upto10 K/decade for the mesosphere (Kokin and Lysenko,1994). Lubken (2000, 2001) reported no significant trendin the polar mesospheric temperature from rocketmeasurements in summer. The assessment of strato-spheric temperature changes undertaken by WMO(1990) shows that there exists largest cooling in theupper stratosphere and no significant cooling in the lowerstratosphere except over tropics and Antarctica.

In tropical latitudes, rocketsonde measurements showtemperature variations at the rate of 0.2 K/decade atThumba (8.51N) and �1 K/decade at Cape Canaveral(281N) at 50 km (Schmidlin, 1991). Keckhut et al. (2005)found a cooling trend of 1.770.7 K/decade at 40–50 kmreaching a maximum cooling 3.370.9 K/decade at 60 km.Over Thumba (8.51N), a negative trend of 2–3 K/decade inthe lower mesosphere and a rise in cooling to 5.6 K/decadeat 70 km is obtained. A decrease of the trend near thestratopause is noticed in an annual trend analysis. Thecooling is found to be slightly stronger in winter than insummer (Beig and Fadnavis, 2001).

Theoretical models predict stratospheric cooling byincrease in green house gases led by CO2. The coolingeffect due to depletion of ozone (�0.5–0.6 K/decade) islarger than that due to well-mixed green house gases(�0.15 K/decade) in the lower stratosphere. In the middleand upper stratosphere, there are differences betweenmodeled and observed cooling trends. Models predictcooling at the rate of 1 K/decade due to well-mixed greenhouse gases (Ramaswamy et al., 1992) and 0.3 K/decadedue to ozone (Schwarzkopf and Ramaswamy, 1993),while the observed cooling is greater than 1.5 K/decade.The underestimation of models is due probably to alack of reliable information on water vapour changes(Ramaswamy et al., 2001).

The 11-year modulation of the UV solar flux is expectedto influence stratospheric ozone through photochemistryand therefore stratospheric temperature. A number ofinvestigators have attempted to identify a signature of the11-year solar cycle in the temperature data set (Keckhutet al., 2005; Remsberg and Deaver, 2005; Fadnavis andBeig, 2006; Dunkerton et al., 1998; Clemesha et al., 1997;Keckhut et al., 1999; Golitsyn et al., 1996; Lysenko et al.,1997). Nearly 17 years of temperature data sets fromNOAA’s polar orbiting satellites (SSU and MSU) show astatistically significant solar component of the orderof 0.5–1.0 K throughout most of the low-latitude(301N–301S) stratosphere, with a maximum near 40 kmaltitude (Ramaswamy et al., 2001). The solar responseshows maxima over tropic and it is symmetric about theequator. A small solar response is observed in these dataat high latitudes. Dunkerton et al. (1998) found solarresponse with an amplitude of 1.1 K response in thealtitude range 29–55 km. Solar-induced temperaturechanges need not occur at the same latitudes as changesin ozone. The amplitude of the solar cycle has thepotential to introduce a bias in trend estimates in theupper stratosphere, if the number of cycles involved inthe time series is less (Ramaswamy et al., 2001).

Though there are considerable number of studies ontrends in stratosphere and mesospheric temperatures, it isimportant to continue these kind of studies, as the releaseof trace gases from human activity has been considered asthe reason for the change in the upper atmosphere climateand it would affect the lower atmosphere climate alsoin future.

The present study reports long-term variabilities andtrends in the Rayliegh lidar temperature in the strato-sphere and lower mesosphere over a tropical site, Gadanki(13.51N, 79.21E).

2. Data analysis

Rayleigh lidar, installed at Gadanki under Indo-Japanese collaboration has been operated during night-time under cloud-free conditions since March 1998. Thelidar employs a Nd:YAG laser, which operates at thesecond harmonic wavelength of 532 nm. The pulse energyis 550 mJ and pulse width is 7 ns. The lidar is operatedwith an altitude resolution of 300 m and pulse repetitionfrequency of 20 Hz. The system provides backscatteredsignals, which are integrated over 5000 transmittedpulses corresponding to a temporal averaging of 250 s.The temperature information is retrieved from thereceived photon counts using the method adopted byHauchecorne and Chanin (1980). There have been quite anumber of results reported from this site (Bhavani Kumaret al., 2000; Parameswaran et al., 2002 to state a few).Though the highest altitude is taken as 90 km and fromwhich temperature is derived using downward integra-tion, the standard error in the estimation of temperatureinformation above 70 km is larger and hence the data forthe heights 30 and 70 km are only considered. The lidaroperation limits to nighttime and cloud-free conditionsand hence the data for each night also varies. For thepresent study, all nights having lidar observations for atleast 3 h during the period March 1998–2008 areconsidered. The temperature data available for a particu-lar night are averaged for the entire night to get nightlymean data. These nightly mean data are averaged for eachmonth to obtain monthly averaged data, which are usedfor further analysis. All the data, which span a decade orthe length of a solar cycle, are considered eligible for trenddetection (Beig et al., 2003).

As the temperature variation contains natural periodicsignals, like the QBO, ENSO and 11-year solar cycle, aregression model is used to extract each signal quantita-tively (Randel and Cobb, 1994). The general expression forthe regression model equation is given by

Tðt; zÞ ¼ aðzÞ þ bðzÞt þ gðzÞQBOðtÞ

þ dðzÞsolarðtÞ þ �ðzÞENSOðtÞ þ residðtÞ,

where

aðzÞ ¼ A0 þX3

i¼1

½Ai � cosoit þ Aiþ1 � sinoit�,

where oi ¼ 2pi/12.The coefficients a, b, g, d, and e are determined in least-

square sense.

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We use Singapore monthly mean QBO zonal winds(m/s) at 30 hPa as a QBO proxy, F10.7 solar radio flux assolar proxy, and Southern Oscillation Index (SOI), which isthe Tahiti (181S, 1501W) minus Darwin (131S, 1311E)monthly mean sea-level pressures (hPa), as ENSO proxy,corresponding to the months t.

3. Results and discussion

3.1. Monthly mean temperature

Fig. 1 shows composite seasonal cycle of temperatureover Gadanki (13.51N, 79.21E). Maximum temperature of�270 K is observed in the months March–April andSeptember. Between 30 and 60 km, the semiannualvariation is predominant. In the stratosphere, thefirst cycle of the temperature SAO is stronger than thesecond cycle at heights around 45 km. However, ataltitudes �50–55 km, the second cycle is strongerthan first cycle. If thermal wind balance is assumed,warmer (colder) temperatures should coincide withthe regions of descending eastward (westward) verticalshear associated with the zonal wind SAO. Possibledifference in the descending rate with height maygive rise to the seasonal asymmetry in temperature.The asymmetry in the two SAO cycles is thought tobe due to the fact that the equatorial Eliassen-Palm fluxdue to planetary Rossby waves is stronger in NorthernHemisphere winter than in the Southern Hemispherewinter (Delisi and Dunkerton, 1988). At altitudes65–75 km, the temperature is nearly steady with noseasonal variation.

Fig. 1. Monthly mean temperature averaged for the y

3.2. Trends

Fig. 2 shows the monthly mean temperature plotted fordifferent heights as solid circles along with standard errorbars. These monthly values are subjected to regressionanalysis as described in Section 2. The fitted time series ofmonthly values are plotted as solid line. The timevariation of monthly values agrees fairly well with thefitted curve. The altitude profile of the estimated lineartrend coefficients is plotted in Fig. 3a as solid line. The 1sand 2s uncertainties are also plotted as dotted and dashedlines. The trend coefficients show cooling at the rate with1s uncertainty of 0.1270.1 K/year at altitudes 35–42 kmand �0.270.08 K/year at altitudes 55–60 km. At altitudesbetween 45 and 55 km, the mean trend coefficients arenearly zero with an uncertainty of 0.05 K/year. In thealtitude region 35–42 km, the largest cooling trendobserved at 37 and 41 km in the present study agreeswell with the results obtained by Beig and Fadnavis (2001)and Golitsyn et al. (1996). Fadnavis and Beig (2006)reported stronger cooling trend at slightly lower altitudenear 35 km. Trends reported in the present study as wellas trends reported by Beig and Fadnavis (2001) andGolitsyn et al. (1996) are over sites, which are closer to theequator (Thumba (8.51N) and Gadanki (13.51N)), whereasFadnavis and Beig (2006) presented results for 0–301Nbelt. As mentioned in Fadnavis and Beig (2006), thestronger cooling occurring at lower altitudes (35 km) is alow-latitude feature, whereas it occurs at slightly higheraltitudes 37–38 km over equatorial sites.

At 45–55 km altitudes, Beig and Fadnavis (2001) alsofound nearly a zero trend (neither cooling or nor heating)in annual trend analysis. However, they found that the

ears 1998–2007 over Gadanki (13.51N, 79.21E).

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Fig. 2. Monthly averaged temperature over Gadanki (small circles with error bars) and fitted temperature (solid line) for every 5 km from 35.1 to 60 km.

S. Sridharan et al. / Journal of Atmospheric and Solar-Terrestrial Physics 71 (2009) 1463–14701466

trend structure got modified on seasonal scales withslightly stronger cooling in winter as compared withsummer. Keckhut et al. (1999) observed a significantcooling of 1.770.7 K/decade in the altitude region 35 to50 km and the trend increases with height to 3.370.9 K/decade near 60 km.

The cooling trend near 57–58 km obtained in thepresent study is in agreement with the result obtained byBeig and Fadnavis (2001). Beig and Fadnavis (2001) found asteep rise in negative trend showing a stronger cooling of5.6 K/decade at 70 km. Semenov (2000) also noticed thehigh negative gradient above 65 km for mid-latitude.Lysenko et al. (1997) observed significant cooling trend inthe mesosphere. Beig and Fadnavis (2001) conducted asensitive test study performed in 2-D model where highlytemperature-sensitive reaction rates involving CH4 andH2O are varied and the feedback of nitric oxide variation totemperature is included. This study indicates a steepergradient (negative) in upper mesosphere (effect of increasein H2O density) from 1970 to 1995 followed by a suddendrop in cooling trend near the mesopause, which may bepartially attributed to the decrease in the concentration ofNO from 1970 to 1995 (Beig, 2000).

3.3. QBO, solar cycle and ENSO signals

The altitude profiles of temperature response to theproxies, QBO, ENSO and solar cycle are shown in Fig. 3b.

From the figure, we can infer that QBO temperatureresponse is more at heights below 35 km and above 70 km.Relatively smaller response is observed at altitudes near45 and 58 km. A strong ENSO reponse is observed in thelowermost stratosphere (�1 K/SOI). ENSO signature is alsoobserved in the mesosphere (0.6 K/SOI). Recently, Liet al. (2008) also reported ENSO signature in the meso-sphere. Recent model simulations also suggest that ENSOresponse should extend to the mesosphere. Temperatureresponse to ENSO at middle atmospheric altitudes can beproduced due to anomalous upward propagating plane-tary waves and gravity waves (Sassi et al., 2004). Thesudden stratospheric warming events occurring in polarregion during El Nino events due to planetary wavebreaking may facilitate the anomalous propagation ofeastward gravity waves into the mesosphere causingcooling in the polar mesosphere and tropical stratosphereand warming in the tropical mesosphere.

The temperature response to solar cycle (K/100F10.7) is�1.5,�1.2,�1, +1.4 and +1.3 at 36, 41, 58, 67 and 71 km,respectively. Li et al. (2008) obtained the coefficient values+1.4 and 1.3 at 55 and 35, respectively. They obtainedpositive solar response in the stratosphere and negativesolar response at heights near 70 km. Remsberg andDeaver (2005) observed 11-year solar cycle term ofamplitude 0.5–1.7 K in temperature versus pressure timeseries from the Halogen Occultation Experiment (HALOE)for the middle to upper mesosphere. Nearly 17 years of

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Fig. 3. (a) Altitude profiles of trend (K/year) obtained from long-term temperature observations over Gadanki (solid line). The 1s and 2s uncertainties are

also plotted as dotted and dashed curves, respectively. (b) Altitude profiles of temperature response to QBO (left panel), solar cycle (middle panel) and

ENSO (right panel). The 1s uncertainities are plotted as horizontal bars.

S. Sridharan et al. / Journal of Atmospheric and Solar-Terrestrial Physics 71 (2009) 1463–1470 1467

nadir viewing satellite observations available since 1979show solar component of the order of 0.4–1 K throughoutmost of the low-latitude (301N–301S) stratospherictemperature, with a maximum near 40 km (Ramaswamyet al., 2001). Keckhut et al. (2005) analyzed threeindependent temperature datasets covering upper strato-sphere and the mesosphere, where the direct photoche-mical effect is expected, for quantifying the influenceof the 11-year solar cycle modulation of the UV radiation.They found positive response of 1–2 K in the tropicsand negative but larger response at mid-latitudes. Severalnumerical model simulations (Garcia et al., 1984;Brasseur, 1993; Fleming et al., 1995; McCormack andHood, 1996; Shindell et al., 1999) indicate that themaximum of solar effect, allowing for ozone changes,

should be situated at the stratopause at all latitudes, witha value of around 1.5–2 K/cycle in the tropics. Haigh(1996)’s simulated study using a GCM shows thatchanges in stratospheric ozone may provide a mechanismwhereby small changes in solar irradiance can cause ameasurable impact on climate. The changes in the thermalstructure of the lower stratosphere could cause astrengthening of the low-latitude upper troposphericeastward winds. Haigh (1998) suggests that this westwardacceleration can come about as a result of a loweringof the tropopause and deceleration of the polewardmeridional winds in the upper portions of the Hadleycells. The global climate model by Shindell et al. (1999)shows that circulation changes initially induced in thestratosphere subsequently penetrate into the troposphere,

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demonstrating the importance of the dynamical couplingbetween the stratosphere and troposphere.

3.4. Long-period oscillations (SAO, AO and QBO)

To compute amplitudes and phases of annual, semi-annual, quasi-biennial oscillations and solar cycle, themonthly values of temperature are subjected to a sum ofsinusoidal and cosinusoidal curves having periods of 6, 12,28, 22.6 and 132 months and the amplitudes and phasesof SAO, AO and QBO are estimated using least squaresmethod and their profiles plotted in Fig. 4. As HALOEobservations show that subbiennial periodicity (�22.6months) dominates at mesospheric altitudes (Remsberget al., 2002), both 22.6-month periodicity QBO and28-month periodicity QBO, which is commonly observedat lower stratospheric altitudes are considered.

There are peaks in the profile of SAO amplitude ataltitudes �35, �45, �62 and 74 km. The peaks obtained at�35, �45 and 74 km agree with the results obtained by Xuet al. (2007) using TIMED-SABER temperature measure-ments for the latitude 201N. The present study shows SAO

Fig. 4. Altitude profiles of amplitudes and phases of SAO, AO, 28

peak at 62 km and a minimum at �70 km. The resultsfrom Sao Jose dos Campos, Brazil (231S, 461W) usingnearly 14 years of Rayleigh lidar temperature data showthat there is a peak in the amplitude of SAO near 60 km(Batista et al., 2008).

The phase profile shows downward phase progressionwith a downward descent at the rate of �10.7 km/radian(�11 km/month) and it nearly agrees with the descent rate�9 km/month estimated by Xu et al. (2007). The AOamplitude is less than 1 K at altitudes 30–60 km and above60 km, it begins to increase and maximizes at 70 km withamplitude of �2 K. Xu et al. (2007) also observedmaximum amplitude of AO at 70 km. The phase profileshows downward propagation with descent rate of�8.6 km/radian (�4.5 km/month). The 28-month periodi-city QBO amplitude decreases with altitude from nearly�2 K at 30–0.5 K near 40 km. Above 40 km, its amplitudesremain around 0.5 K. However, its amplitude againincreases sharply to 1.8 K at altitude near 73 km. Thephase profiles show regular, but smaller variation, withheight at heights 30–35 km, where QBO amplitude isconsiderably larger. The phase structure is irregular above

-month periodicity QBO and 22.6-month periodicity QBO.

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35 km. The 22.6-month QBO amplitude is comparablewith that of 28-month periodicity at lower stratosphericaltitudes (below 35 km) and at 45 km and it even exceedsat altitudes near 55 km. Though its amplitude is muchweaker at 73 km, where 28-month periodicity QBOamplitude maximizes (1.8 K), both amplitudes are com-parable near 75 km. Li et al. (2008) fitted lidar time seriesto two stratospheric QBO reference EOFs with approxi-mately 28-month periodicity and they suggested that itcould be a reason for weaker QBO response they obtainedin the middle mesosphere.

4. Conclusion

The long-term variation of temperature over Gadanki(13.51N, 79.21E) shows that there exits no trend in theupper stratosphere and a cooling trend in the lowerstratosphere and lower mesosphere. These results are ingood agreement with rocketsonde results from Thumba,India reported by Beig and Fadnavis (2001). Significanttemperature response to ENSO is observed in the lowerstratosphere (1 K/SOI) and also in mesosphere (0.6 K/SOI).The solar cycle response shows significant negativemaxima (1�1.4 K/100F10.7 units) at 37, 41 and 57 km.The response is positive at mesospheric altitude near67 km. This result is contradictory with the earlier reports.

The amplitudes and phases of semiannual, annual andquasi-biennial oscillations are estimated using least-quares method. The semiannual oscillation shows largeramplitudes at altitudes near 35, 45, 62 and 74 km whereasthe annual oscillation peaks at 70 km. The quasi-biennialoscillations show larger amplitudes below 35 km andabove 70 km. The phase profiles of semiannual and annualoscillations show downward propagation.

Acknowledgements

The authors would like to thank editor and the twoanonymous reviewers for their critical evaluation of themanuscript. This work was supported by Department ofSpace, Government of India. One of the authors (S.S.)would like to thank Prof. Toshitaka Tsuda of RISH, KyotoUniversity, Japan for the stimulating discussion on long-term variabilities of middle atmospheric winds andtemperature, when he visited NARL, Gadanki for a fewdays in the years 2006 and 2007. The QBO winds and SOIdata used in the present study were downloaded fromthe website http://www.cpc.ncep.noaa.gov/. The solar fluxdata were obtained from ftp://ftp.ngdc.noaa.gov/STP/SOLAR_DATA/SOLAR_RADIO/FLUX/MONTHLY.OBS.

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