**14. Long term variations of** τ**p in the LS region**

Zonal mean values of τp in the altitude region 18–28 km averaged for the four latitude belts, each of width 15°, in each month are used to examine the temporal variations in both the hemispheres. Time series plots of these for the equatorial (0–15°S and 0–15°N) and offequatorial regions (15–30°N and 15–30°S) are shown in Figures 21a and 21b, respectively, along with a similar plot of τp obtained from lidar at Gadanki in Figure 21c. In the equatorial region the temporal variations in τp are very similar in both the hemispheres. The mean level of τp shows an abrupt increase after 2002 [88] though the oscillations around this mean level is fairly similar to those before 2002. Over the off-equatorial regions the mean level of τ<sup>p</sup> shows a rather steady (gradual) increase from 1998 to 2005. A sharp increase in τp is observed towards the trailing edge of the data in the year 2005. During the period 1998– 2002, the value of τp in the equatorial region is a minimum and is close to ~0.0025. The mean τp in the altitude region 18–28 km obtained from lidar at Gadanki also shows similar feature as that observed from SAGE-II over the equatorial region. In general the value of τp in the LS region obtained from lidar data is larger than that obtained from SAGE-II. This could be due to the fact that the lidar observation is a single point measurement while the SAGE-II data used in this analysis is zonally and meridionally averaged for the equatorial and offequatorial regions.

All the plots in Figure 21 show a general increasing trend in stratospheric particulate (aerosol) optical depth during the period 1998–2005 in addition to the periodic variations. On the basis of lidar observations during the period 2000–2009, a similar increase in the integrated stratospheric backscatter coefficient (in the altitude region 20–25 km) at the rate

process could be different at various occasions.

equatorial regions.

**14. Long term variations of** τ**p in the LS region** 

very close to that of the molecules. In general, it is in the range 0.03 to 0.04. But, during major volcanic eruption abundant amount of precursor gases will be injected into the lower stratosphere along with a few fine particulates. Because of this influx of particles and gases there will be an increase in the number density of particles as well as an increase in the size of these particles. The size spectrum of the stratospheric particles also shifts toward the larger size regime following the volcanic eruption [92]. As some of those particles that are directly injected into the lower stratosphere during volcanic eruption could be non-spherical

Figure 20c shows a contour plot of δ at different altitude in the lower stratosphere over Gadanki during the period 1998–2005. This plot generated adopting the same procedure as that used for generating Figure 20b from αp profiles, clearly shows a few short-lived δ enhancements in the lower stratosphere. The sporadic increase in δ is associated with the eruption of a few moderately intense volcanic eruptions. The duration of the increase in α<sup>p</sup> also matches well that of δ. The disturbances caused by eruption of volcanoes Ruang (eruption e) and Reventador (eruption f) are relatively stronger (δ ranging from 0.05 to 0.2 in the altitude region 18–21 km during November 2002 to February 2003). In a few cases the enhancements in αp and δ does not match exactly. This could be due to the fact that the volcanic locations are at different distance from Gadanki as well as the prevailing transport

Zonal mean values of τp in the altitude region 18–28 km averaged for the four latitude belts, each of width 15°, in each month are used to examine the temporal variations in both the hemispheres. Time series plots of these for the equatorial (0–15°S and 0–15°N) and offequatorial regions (15–30°N and 15–30°S) are shown in Figures 21a and 21b, respectively, along with a similar plot of τp obtained from lidar at Gadanki in Figure 21c. In the equatorial region the temporal variations in τp are very similar in both the hemispheres. The mean level of τp shows an abrupt increase after 2002 [88] though the oscillations around this mean level is fairly similar to those before 2002. Over the off-equatorial regions the mean level of τ<sup>p</sup> shows a rather steady (gradual) increase from 1998 to 2005. A sharp increase in τp is observed towards the trailing edge of the data in the year 2005. During the period 1998– 2002, the value of τp in the equatorial region is a minimum and is close to ~0.0025. The mean τp in the altitude region 18–28 km obtained from lidar at Gadanki also shows similar feature as that observed from SAGE-II over the equatorial region. In general the value of τp in the LS region obtained from lidar data is larger than that obtained from SAGE-II. This could be due to the fact that the lidar observation is a single point measurement while the SAGE-II data used in this analysis is zonally and meridionally averaged for the equatorial and off-

All the plots in Figure 21 show a general increasing trend in stratospheric particulate (aerosol) optical depth during the period 1998–2005 in addition to the periodic variations. On the basis of lidar observations during the period 2000–2009, a similar increase in the integrated stratospheric backscatter coefficient (in the altitude region 20–25 km) at the rate

in nature, an increase in δ in the stratospheric aerosol would be expected.

**Figure 21.** Time series of zonal mean monthly average τP in the altitude region 18–28 km obtained from SAGE-II for (a) the equatorial region (0°–15°N, 0°–15°S) and (b) the off-equatorial region (15°–30°N and 15°–30°S), along with (c) the mean τP obtained from lidar at Gadanki.

of 4.8% and 6.3% per year (with respect to its value in 2002) was reported [26] at Hawaii (19.5°N, 155.6°W) (Mauna Loa Laboratory) as well as at Boulder (40°N) (Colorado). The increase in τp at Hawaii and Boulder was attributed to the increase in global coal consumption since 2002, mainly from China, and subsequent increase in emission of SO2. Anthropogenic aerosols produced through gas-to-particle conversion of precursor gases like sulfates and ammonia transported to the upper troposphere [5] through intense convection [93] in the tropics and subsequently across the tropopause also could possibly be a contributing factor for this increase. An increase in tropical upwelling (Brewer- Dobson circulation) because of global warming also was suggested to be a plausible mechanism for the observed increasing trend [93,94] in stratospheric βp after 2002.

Even though on an average the stratospheric particulate loading is in its background level during the period 1998–2005, it was influenced particularly by a few moderate volcanic eruptions mainly after September 2002. While the period before September 2002 was absolutely quiet (with low particulate loading), the later period was mildly disturbed. The variation in stratospheric particulate loading need not solely be represented by a corresponding variation in tephra emissions Their could be some other causative mechanisms, such as increase in anthropogenic emissions as well as the increase in tropical upwelling, which could influence the stratospheric particulate loading.

## **15. Periodic variation of** τ**p in the LS region**

In addition to the general increasing trend, the values of τp in Figure 21 shows a seasonal cycle with winter maximum and summer minimum modulated by a long-period oscillation. These oscillations could primarily be due to the influence of large-scale atmospheric waves. The time series data of τp is spectrum analyzed to bring out the characteristics of the prevailing periodic variations. Before subjecting the data to spectral analysis, the linear trend is removed from the original data. The residual part is Fourier analyzed and the resulting amplitude spectra for different latitude bands (0–15°N, 0–15°S, 15–30°N and 15– 30°S) are presented in Figures 22a and 22b. These amplitude spectra reveal the presence of a strong annual component (~12 months) along with a quasi-biennial component (~30 month) both in the equatorial and off-equatorial regions [88]. The spectral amplitude of QBO is as strong (significant) as that of annual oscillation (AO). Figure 22c shows the amplitude spectrum obtained from the lidar derived values of τp (at Gadanki). Even though Figure 22c shows more significant peaks in the short-period regime, the spectral amplitude is more pronounced for semi-annual (SAO) and annual (AO) components. This spectrum also shows a secondary peak around 46 months followed by troughs at 23 and 92 months. The spectral amplitude for 30 month periodicity is larger than those at the troughs on either side of this secondary peak. Though the period for the peak amplitude (46 months) is much larger than that expected for the stratospheric QBO, on the basis of the inference derived from Figures 22a and 22b, as well as owing to the fact that the spectral amplitude at 30 months is not a minimum, the characteristics of the 30 month periodicity is examined in the later part to Distribution of Particulates in the Tropical UTLS over

the Asian Summer Monsoon Region and Its Association with Atmospheric Dynamics 145

delineate its altitude structure in the lidar data. The SAGE-II data did not show the signature of SAO, which could be due to the inherent smoothing out of this component while taking the zonal mean. The higher spectral amplitude of AO compared to that of QBO

For this study the high resolution Radiosonde data of zonal wind in the lower stratosphere from an equatorial station (where the quasi-biennial oscillation, QBO, signature is expected to be maximum), Singapore (1°22″N, 103°55″E), obtained from Web site http://www.geo.fuberlin.de/en/met/ag/strat/produkte/qbo/ are used. The time series data of monthly mean zonal wind at Singapore at 20 hPa and 30 hPa levels during the study period are presented in Figure 23. This figure shows that the quasi-biennial oscillation in zonal wind (QBOU) is in the easterly phase during the 1998, 2000–2001, 2003 and 2005. The westerly phase during 1999 and the easterly phase during 2000–2001 are relatively broad. Different phases of QBOU are indentified from this time series to study the influence of QBOU in lower stratospheric

**Figure 23.** Time series of monthly mean zonal wind at Singapore at 20 and 30 hPa levels during the period 1998-2005. E1, E2, E3, and E4 are the periods in which QBOU was in its easterly phase, and W1, W2,

**16.1. Latitude variation of** τ**p in LS region over the Indian longitude sector in two** 

The latitude variation of τp in the altitude range 21–28 km in the band 0–30°N (averaged for every 5°) over the Indian longitude sector (70–90°E) is examined during the consecutive easterly and westerly phases of QBOU in 1998 and 1999 separately. Figure 24 shows the latitudinal variation of τp during these two phases of QBOU. This mean τp is obtained by averaging the particulate optical depth in individual months when the QBOU phase has reversed completely (the wind speed has reached its highest value). While the value of τp is

**16. Quasi-biennial oscillations in** τ**p and zonal wind in the LS region** 

is quite expected (as it is true for the wind field also).

and W3 are those in which QBOU was in its westerly phase.

**different phases of QBOU** 

aerosols.

**Figure 22.** Amplitude spectra of τP in the altitude region18–28 km during the period 1998–2005 derived from the time series of zonal mean monthly average τP in this altitude region obtained from SAGE‐II data for (a) the equatorial region and (b) the off-equatorial-region, along with (c) that obtained from lidar data at Gadanki

delineate its altitude structure in the lidar data. The SAGE-II data did not show the signature of SAO, which could be due to the inherent smoothing out of this component while taking the zonal mean. The higher spectral amplitude of AO compared to that of QBO is quite expected (as it is true for the wind field also).
