Embed Size (px)
Citation preview
Ionospheric quasi-biennial oscillation in global TEC observations
W. Tang a, X.-H. Xue a,b,n, J. Lei a,b, X.-K. Dou a,b
a CAS Key Laboratory for Geospace Environment, School of Earth & Space Sciences, University of Science & Technology of China, Hefei, Chinab Mengcheng National Geophysical Observatory, School of Earth & Space Sciences, University of Science & Technology of China, Hefei, China
a r t i c l e i n f o
Article history:Received 21 July 2013Received in revised form1 November 2013Accepted 4 November 2013Available online 9 November 2013
Keywords:Quasi-biennial oscillationsIonospheric QBOTECSolar activities
a b s t r a c t
The total electron content (TEC) observations were analyzed for the ionospheric quasi-biennialoscillations (QBO) during the period of 1999–2011 in a global perspective. Zonal and monthly meansof TEC data were calculated to reveal the global characteristics and long-period variations in ionosphere.The Lomb–Scargle periodogram methods and wavelet spectral analysis were applied to the residuals ofTEC, which are obtained from subtracting the fittings with solar index, F10.7. The ionospheric QBO signalonly appears during solar maximum, existing in all latitudes from 501S to 501N, and the period is within22–34 months. In the equatorial region, the QBO exhibits a significant feature of equatorial ionosphericanomaly (EIA), where the transition of phases occurs 2–6 months later than in high latitude. Thecorrelation coefficient with the stratospheric QBO reaches 0.704. It can be assumed that stratosphericQBO influences the QBO phenomenon in ionosphere; nevertheless, the present results do not permit oneto conclude the mechanism.
& 2013 Elsevier Ltd. All rights reserved.
1. Introduction
The term quasi-biennial oscillation (QBO) was first introducedby Reed et al. (1961) and Ebdon and Veryard (1961), who noticedthat the zonal equatorial stratospheric winds alternate betweenwestward and eastward repeatedly with an averaged period ofslightly more than 28 months. This tropical phenomenon alsoaffects the global atmospheric circulation at latitudes and altitudesoutside the tropical stratosphere. There is strong evidence that theQBO influences the temperature and circulation in extratropicsand polar region, and accounts for the stratospheric suddenwarming (Holton and Tan, 1980; Labitzke and van Loon, 1988;Naito and Hirota, 1997; Hamilton, 1998). A comprehensive reviewof QBO has been given by Baldwin et al. (2001). Labitzke and vanLoon (1988) first found that the polar observations are signifi-cantly correlated with solar cycle when the observations arestratified according to the phase of QBO in equatorial stratosphere.Since then, similar investigations were extended to other regionsand to other parameters. Chen (1992) provided evidence of iono-spheric response to the QBO, and proposed that the day-to-dayvariations of the equatorial ionospheric anomaly (EIA) weremainly resulted from the upward propagating waves from the
lower atmosphere. The mechanism of natural wind dynamo effect(fountain effect) seems to be the main cause responsible forionospheric QBO, albeit the existence of a relationship betweensolar and geomagnetic activities cannot be discarded (Neumann,1990; Chen, 1992; Labitzke, 2005; Echer, 2007; Lu et al., 2009),given that the QBO variation has been identified in several solarand geomagnetic parameters (Apostolov, 1985; Chanin et al., 1989;Kane, 2005). Up to now, previous investigations of QBO in theionosphere were conducted using data obtained from severalstations. In this work, the observations of ionospheric totalelectron content (TEC) were utilized to study the characteristicsof the QBO variation in the ionosphere during the period of 1999–2011. This TEC data with global coverage provides a differentperspective on the spatial and temporal characteristics of iono-spheric QBO. The causes responsible for ionospheric QBO arefurther discussed.
2. Data and methods
The global ionosphere maps (GIMs) have been produced on adaily basis by Center for Orbit Determination in Europe (CODE),University of Berne, Switzerland, using the data from about 200GPS/GNSS sites of the IGS (International GNSS Service) and otherinstitutions. The extending IGS network has generated an increas-ing amount of data regarding the ionosphere state, which can beused to extract information about the total electron content (TEC)on the global scale with a high average spatial resolution. SlantTEC is the integrated electrons along the path from the satellite to
Contents lists available at ScienceDirect
journal homepage: www.elsevier.com/locate/jastp
Journal of Atmospheric and Solar-Terrestrial Physics
1364-6826/$ - see front matter & 2013 Elsevier Ltd. All rights reserved.http://dx.doi.org/10.1016/j.jastp.2013.11.002
n Corresponding author at: CAS Key Laboratory for Geospace Environment,School of Earth & Space Sciences, University of Science & Technology of China,Hefei, China. Tel.: þ86 551 63600048.
E-mail addresses: [email protected] (W. Tang), [email protected](X.-H. Xue), [email protected] (J. Lei), [email protected] (X.-K. Dou).
Journal of Atmospheric and Solar-Terrestrial Physics 107 (2014) 36–41
the receiver. To convert line-of-sight TEC into vertical TEC, amodified single-layer model mapping function is adopted. VerticalTEC is modeled by CODE, and the details can be found in the workof Schaer (1999). The TEC data have been interpolated into 51�12:51 (longitude� latitude) grid from 87.51S to 87.51N with tem-poral resolution of 2 h (UT), which is archived at the website ftp://ftp.unibe.ch/aiub/CODE/.
Depending on the longitude and the universal time of eachlongitude, we first classified the TEC data by the local time(LT ¼UTþLon=15, in hours). Then, the data for the same localtime were averaged by longitude in each geomagnetic latitude binso that the effect of non-migrating tides can be minimized.According to Chanin et al. (1987), we average the data over amonth instead of the 27 days to remove the short-term variabilityfrom the solar rotation. Those monthly and zonally averaged datawere further interpolated into the grid of geomagnetic longitude(Lon, in degrees) and geomagnetic latitude (Lat, in degrees). Thus,the resulting TEC were analyzed as a function of month, geomag-netic latitude and local time. Taken into account that TEC back-ground varies widely with local time, we chose two typical pointsat local time (LT) of 12 and 18, to represent ionospheric variabilityin the daytime and during the period of the pre-reversal enhance-ment (PRE). Given the fact that these TEC variations share thesame periodic features as solar activities, the monthly mean solarflux at 10.7 cm (F10.7) has been introduced as a solar index. Inorder to eliminate the impact of solar activities, we modeled the11-year solar cycle as a second order polynomial, and the 6 and 12months period as sinusoid. The regression equation becomes
TECðtÞ ¼ A0þA1 � F107ðtÞþA2 � F2107ðtÞþðB0þB1 � F107ðtÞÞ
� sin 2πtT1
þθ1
� �þðC0þC1 � F107ðtÞÞ � sin
2πtT2
þθ2
� �ð1Þ
where TEC(t) and F107ðtÞ are the time serials of the monthly andzonally averaged TEC data and monthly mean solar activity index,respectively; T1 and T2 denote the period of 6 and 12 monthpresenting seasonal variation of the ionosphere; A, B and C
represent the regression coefficients. With the calculated regres-sion coefficients and monthly mean F10.7, the fitted curves can beeasily obtained.
3. Results
Fig. 1 illustrates the monthly averaged TEC data (shown in blackwith solid lines) and the fitting curves (shownwith dotted lines) atdifferent geomagnetic latitudes of 151N (red), 01 (green) and 151S(blue). The two columns depict the ionospheric conditions at localtime of 12 (Fig. 1(a)–(c)) and 18 (Fig. 1(d)–(f)), representing thedaytime and the period of pre-reversal enhancement (PRE). Thecurves are fitted well with the TEC observations. The averaged TECdata reach the highest values during 2001–2002 and drop to thelowest during 2008–2009, which are corresponding to the max-imum and the minimum of the solar activities. The highest valueof averaged TEC data is 120 TECU, and the lowest value is around10 TECU. And the general variation trend accords with the 11-yearsolar cycle. Besides the period of 11 years, the most prominentperiodic features are the annual and semiannual oscillations. It isreasonable to presume that the main factor affecting the variationsof TEC is the solar activities. As seen from the two columns inFig. 1, the amplitudes of the averaged TEC observations are largerat local time (LT) of 12 than that at 18, i.e. the TEC values are higherin the daytime than during the PRE, due to the intense solarionization at noon. However, the quasi-biennial variations are notobviously visible in this monthly averaged TEC values.
In order to concentrate on the influence of quasi-biennialoscillation, each fitting TEC is subtracted from the correspondingaveraged TEC value, to remove the main cause responsible for theTEC variations, as shown in Fig. 2. The local time and geomagneticlatitudes chosen are the same as described above. Comparing theresults in the two columns, the residual values at 18 LT are higherthan at 12 LT, which is different from the situation of the monthlyaveraged TEC observations as shown in Fig. 1. The highest value isabout 17 TECU and the residuals account for about 7.3% of the
Fig. 1. Monthly and zonally averaged TEC observations at local time of 12 (shown in (a)–(c)) and 18 (shown in (d)–(f)), at geomagnetic latitudes of 151N (red), 01 (green), 151S(blue). The solid lines present time series of averaged TEC from 1999 to 2011, and the dotted lines present the fitted TEC with F10.7. (For interpretation of the references tocolor in this figure caption, the reader is referred to the web version of this article.)
W. Tang et al. / Journal of Atmospheric and Solar-Terrestrial Physics 107 (2014) 36–41 37
monthly averaged TEC data. As for the latitudinal distributions, theamplitudes at geomagnetic latitudes of 151N (red) and 151S (blue)are larger than that at 01 (green), which should be the signature ofthe modulation of the EIA, identified by a trough at the magneticequator and two humps at about7151 of magnetic latitudes.During the solar minimum, the residuals are too small to clearlysee the periodic features. However, during the solar maximum, aslight trend of the QBO-like component can be seen from theperiod of 2000–2001 and the period of 2002–2003.
To examine whether the ionosphere is modulated by QBO, theTEC residuals are further analyzed with Lomb–Scargle period-ogram methods (Lomb, 1976; Scargle, 1982). The correspondingLomb–Scargle spectra with period from 1 to 36 months are shownin Fig. 3. These spectra illustrate that residuals contain a compo-nent with a period from 22 to 34 months, which is responsible forthe QBO-like signal during the solar maximum observed fromFig. 2. This signal shares similar period with the stratospheric QBO.
The amplitude of this component is around 2 TECU, and about 10%of the TEC residuals. There are two peaks within the period relatedto the stratospheric QBO, one is around 24 months and the other isaround 30 months. From our analysis results at all the latitudes,this feature of two peaks, shows up only in the equatorial region.Note that the peaks at the periods of 6 and 12 months are absentsince the annual and semiannual variations of TEC are filtered inthe fitting. Also, a period of 4 months exists in the residuals. Sincethis spectrum illustrates clearly that the possible effect of strato-spheric QBO is included in TEC, the residual variations will beanalyzed subsequently.
Fig. 2. The variations of residuals after subtracting the fitted TEC with F10.7 from the monthly and zonally averaged TEC data, on local time of 12 (shown in (a)–(c)) and 18(shown in (d)–(f)), at geomagnetic latitudes of 151N (red), 01 (green), 151S (blue) from 1999 to 2011. (For interpretation of the references to color in this figure caption, thereader is referred to the web version of this article.)
Fig. 3. Lomb–Scargle periodogram for the TEC residuals. The spectrum at geomag-netic latitudes of 151N, 01, 151S are presented in red, green and blue, respectively.
Fig. 4. Wavelet spectrum of the TEC residuals at geomagnetic latitude of 151S. Thesolid curves reveal the confidence level. The dashed curve is the cone of influence.The three arrows from top to bottom denote the period of 18, 28 and 36 months.
W. Tang et al. / Journal of Atmospheric and Solar-Terrestrial Physics 107 (2014) 36–4138
Fig. 4 shows the wavelet analysis result of the TEC residuals fromthe software package of Torrence and Compo (1998). The geomag-netic latitude of 151S is selected as the QBO component is conspic-uous at this latitude (blue line in Fig. 3). The three arrows from top tobottom represent the period of 18, 28 and 36 months. The period ofthe QBO-like signal is limited within 18–36 months and centeredaround 28 month at 95% confidence level. At 99% confidence level,the period is limited within 22–34 months. This result agrees withthe Lomb–Scargle periodogram in Fig. 3. This ionospheric quasi-biennial variation appears during the period of 1999–2005, and thedata also show an oscillation around 2 years after 2009. During thesolar minimum, the QBO-like signal is not evident in the TEC.
Since the residuals contain the QBO-like signal, a band-passfilter is applied in the TEC residuals after the TEC backgroundsare removed by Eq. (1). Owing to the variable period of QBO withan average of 28 months, we use a band-pass filter centeredat 28 months with half-power points at 24 and 32 months.To consider the effect of ionospheric background, the obtainedresults are displayed as a percentage of the fitting TEC shown byEq. (1) , representing the solar background, as shown in Fig. 5.The distributions at three different local times (LT¼12, 18, 03) areselected to present the daytime, period of pre-reversal enhance-ment (PRE) and night conditions, respectively.
From Fig. 5, it is seen that the distributions of the relative valuesstrongly depend on local time and geomagnetic latitude.It is observed at all latitudes from 501N to 501S where the QBOcomponent exists, in agreement with the results of Echer (2007),who acquired from several ionosonde stations. As illustrated in Fig. 4,the QBO-like component appears during 1999–2005 and 2 yearsafter 2009; subsequently, we mainly focus on the period from 1999to 2005. During such period, the EIA feature is shown clearly at 18 LTand 03 LT, which can be distinguished by the characteristics that therelatively higher values of QBO-like signal are confined within7201.At 12 LT, the EIA feature is not evident. Only the trough remains inthe equatorial region, where QBO signal has the lowest ratio of 4.84%,which is on the magnetic equator at 12 LT. As the background TEC at3 LT is low, there is a higher percentage of 9.8%, appearing at 7201during solar maximum. On the other hand, the phases, i.e., the timeof transition from positive to negative (or from negative to positive)are different between high and low latitudes. The transition in highlatitude occurs approximately 6 months earlier than that in equator-ial region during the night. At 12 LT and 18 LT, the transition at thegeomagnetic equator occurs approximately 2 months later thanother region. Also, the periodicity seems to accord. However, duringthe solar minimum, there exists one more profound at high latitudethan in the equatorial region.
Fig. 5. The relative residuals of TEC observations after applying a band-pass filter, centered at 28 months with the passing periods within 24 and 32 months. The plotspresent the relative residuals at (a) 12, (b) 18 and (c) 3 LT, respectively.
W. Tang et al. / Journal of Atmospheric and Solar-Terrestrial Physics 107 (2014) 36–41 39
4. Discussion and conclusion
The ionosphere responds to both solar activities and forcingoriginating from the lower atmosphere. Although the sun is themajor source of ionospheric variations, there is a nonnegligiblesource from lower atmosphere, which forms through the verticalcoupling of atmosphere and ionosphere. It is notable that theoscillation with periods of �2 years has been observed in almostall indices of solar activity (Apostolov, 1985; Soukharev and Hood,2001; Zaqarashvili et al., 2010). It is reasonable to believe that thequasi-biennial variation in ionosphere is modulated by �2 yearoscillation in solar activities, but the significance of this modula-tion cannot be validly concluded (Neumann, 1990; Echer, 2007).Nevertheless, Kane (1991, 1995) ruled out the solar origin becausea spectrum analysis of sunspot series did not show significantperiodicities in the similar period as QBO. On the other hand, theimpact from lower atmosphere through vertical coupling issignificant. In order to examine the associated dynamic effect,we further investigated the relationship between the QBO-likesignal in TEC residuals and the QBO in stratospheric zonal winds.
Fig. 6 compares the band-filtered TEC observations with thezonally averaged winds from the CDAS Reanalysis data (availableat the website http://www.cpc.ncep.noaa.gov/data/indices/). Theobservations at 18 LT are chosen for its relatively higher valueduring PRE. The stratospheric zonal QBO winds at 50 hPa(�20 km) taken from over the equator and the filtered resultsfrom solar index are shown in black. Since Fig. 4 shows that theionospheric quasi-biennial variations exist during the period of1999–2005, this period becomes our main focus. As seen fromFig. 6, during such period, the QBO-like signal in TEC observationsis highly related to the QBO phenomenon in stratosphere. Thecorrelation coefficient between them is 0.704.
The results from Fig. 4 and Fig. 6 show that the QBO-like signalin TEC observations appears during solar maximum, which coin-cides with the QBO in stratospheric zonal winds. This phenom-enon implies that stratospheric QBO has an impact on ionosphericquasi-biennial variations through the dynamic coupling betweenstratosphere and ionosphere. On the other hand, there is evidencethat the stratospheric QBO is modified by the 11-year solarperiodicity (Salbe and Callaghan, 2000; Lu et al., 2009). Since thequasi-biennial component in solar activities cannot affect theionospheric QBO, the modulation of solar activities in ionosphericQBO might be through the dynamic coupling as well. Also,geomagnetic parameters have peaks in QBO region (Kane, 1995,2005; Echer, 2007). Considering that the geomagnetic field caninfluence the ionospheric variations through solar, magnetosphere
and ionosphere interactions, the impact from geomagnetic fieldcannot be eliminated and should be further explored.
In summary, we have analyzed the existence and variations ofthe quasi-biennial in ionosphere, characterized by the monthlyand zonally means of the total electron content during the years of1999–2011. The results can be summarized as follows:
(1) The QBO-like signal in ionosphere appears during the periodof 1999–2005 and 2 years after 2009. During solar minimum,the ionospheric QBO is not found in TEC observations. Theperiod of this component is from 22 to 34 months, centeredat 28 months, which shares the periodic similarity withstratospheric QBO.
(2) The quasi-biennial variations in ionosphere is found in alllatitudes from 501S to 501N, showing a significant feature ofEIA, and the transition of QBO phases occurs earlier in highlatitudes than in equatorial region, which can be as early as 2–6 months.
(3) During the period of high solar activities, the ionospheric QBOexhibits a positive correlation with the stratospheric QBO, andthe correlation coefficient reaches 0.704.
Acknowledgments
We wish to thank the Center for Orbit Determination in Europe(CODE) for their ionospheric data and the NCEP/NCAR ReanalysisProject for the data of zonal winds. This work is supported by theproject (KJCX2–EW–J01, KZZD–EW–0101, KZCX2–EW–QN509) ofChinese Academy of Sciences, the National Natural Science Foun-dation of China (41322029, 41174132, 41121003, and 41025016),A Foundation for the Author of National Excellent DoctoralDissertation of PR China (201025).
References
Apostolov, E.M., 1985. Quasi-biennial oscillation in sunspot activity. Bull. Astron. 36,97–102.
Baldwin, M.P., Gray, L.J., Dunkerton, T.J., Hamilton, K., Haynes, P.H., Randel, W.J.,Holton, J.R., Alexander, M.J., Hirota, I., Horinouchi, T., Jones, D.B.A., Kinnersley,J.S., Marquardt, C., Sato, K., Takahashi, M., 2001. The quasi-biennial oscillation.Rev. Geophys. 39, 179–229.
Chanin, M.L., Smires, N., Hauchecorne, A., 1987. Long-term variation of thetemperature of the middle atmosphere at mid-latitude: dynamical and radia-tive causes. J. Geophys. Res. 92, 10933–10941.
Chanin, M.L., Keckhut, P., Hauchecorne, A., Labitzke, K., 1989. The solar activity—Q.B.O.effect in the lower thermosphere. Ann. Geophys. 32, 225–230.
Chen, P., 1992. Evidence of the ionospheric response to the QBO. Geophys. Res. Lett.19, 1089–1092.
Ebdon, R.A., Veryard, R.G., 1961. Fluctuations in equatorial stratospheric winds.Nature 189, 791–793.
Echer, E., 2007. On the quasi-biennial oscillation (QBO) signal in the foF2 iono-spheric parameter. J. Atmos. Sol. Terr. Phys. 69, 621–627.
Hamilton, K., 1998. Effect of an imposed quasi-biennial oscillation in a compre-hensive troposphere–stratosphere–mesosphere general circulation model.J. Atmos. Sci. 55, 2393–2418.
Holton, J.R., Tan, H.-C., 1980. The influence of the equatorial quasi-biennialoscillation on the global circulation at 50 mb. J. Atmos. Sci. 37, 2200–2208.
Kane, R.P., 1991. Spectral analysis of annual sunspot series—an update. Pure Appl.Geophys. 135, 463–474.
Kane, R.P., 1995. Quasi-biennial oscillation in ionospheric parameters measured atJuliusruch (55N, 13E). J. Atmos. Sol. Terr. Phys. 57, 415–419.
Kane, R.P., 2005. Differences in the quasi-biennial oscillation and quasi-triennialoscillation characteristics of the solar, interplanetary and terrestrial parameters.J. Geophys. Res. 110, A01108.
Labitzke, K., van Loon, H., 1988. Association between the 11-year solar cycle, theQBO and the atmosphere, part I. The troposphere and stratosphere in theNorthern Hemisphere in winter. J. Atmos. Terr. Phys. 50, 197–206.
Labitzke, K., 2005. On the solar cycle–QBO-relationship: a summary. J. Atmos. Sol.Terr. Phys. 67 (Special Issue), 45–54.
Lomb, N.R., 1976. Least-squares frequency analysis of unequally spaced data.Astrophys. Space Sci. 39, 447–462.
Fig. 6. The comparison of band-filtered TEC observations and the stratosphericQBO at 50 hPa. The Fourier filtered component at the geomagnetic latitude of 151N,01, 151S at 18 LT is plotted in red, green and blue, respectively. As an indicator of thestratospheric QBO, the zonally averaged winds from the CDAS Reanalysis data at50 hPa (�20 km) are shown (black).
W. Tang et al. / Journal of Atmospheric and Solar-Terrestrial Physics 107 (2014) 36–4140
Lu, H., Gray, L.J., Baldwin, M.P., Jarvis, M.J., 2009. Life cycle of the QBO-modulated11-year solar cycle signals in the Northern Hemispheric winter. Q. J. R.Meteorol. Soc. 135, 1030–1043.
Naito, Y., Hirota, I., 1997. Interannual variability of the northern winter strato-spheric circulation related to the QBO and the solar cycle. J. Meteorol. Soc. Jpn.75, 925–937.
Neumann, A., 1990. QBO and solar activity effects on temperatures in themesopause region. J. Atmos. Terr. Phys. 52, 165–173.
Reed, R.J., Campbell, W.J., Rasmussen, L.A., Rogers, R.G., 1961. Evidence of adownward propagating annual wind reversal in the equatorial stratosphere.J. Geophys. Res. 66, 813–818.
Salbe, M., Callaghan, P., 2000. Connection between the solar cycle and the QBO: themissing link. J. Clim. 13, 2652–2662.
Scargle, J.D., 1982. Studies in astronomical time series analysis. II. Statistical aspectsof spectral analysis of unevenly spaced data. Astrophys. J. 263, 835–853.
Schaer, S., 1999. Mapping and Predicting the Earth's Ionosphere Using theGlobal Positioning System. Ph.D. Dissertation, Astron. Inst. Univ. of Bern,Switzerland.
Soukharev, B.E., Hood, L.L., 2001. Possible solar modulation of the equatorial quasi-biennial oscillation: additional statistical evidence. J. Geophys. Res. 106,14855–14868.
Torrence, C., Compo, G.P., 1998. A practical guide to wavelet analysis. Bull. Am.Meteorol. Soc. 79, 61–78.
Zaqarashvili, T.V., Carbonell, M., Oliver, R., Ballester, J.L., 2010. Quasi-biennialoscillations in the solar tachocline caused by magnetic Rossby wave instabil-ities. Astrophys. J. Lett. 724, L95–L98.
W. Tang et al. / Journal of Atmospheric and Solar-Terrestrial Physics 107 (2014) 36–41 41
