Latitudinal dependence of the seasonal variation of particulate extinction in the UTLS over the Indian longitude sector during volcanically quiescent period based on lidar and SAGE-II observations

Parameswaran, K.; Thampi, Bijoy V.; Sunilkumar, S. V.

doi:10.1016/j.jastp.2010.06.004

Cited by 7 publications

(8 citation statements)

References 56 publications

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“…Earlier comparison studies by Parameswaran et al (2010) over Gadanki using SAGE II and lidar extinction profiles found fairly good agreement when the radial distance is of the order of a few hundreds of kilometres, while deviation increases with an increase in radial distance. In the present study, to have a sizeable number of data sets, coincident criteria are followed.…”

Section: Sage II and Lidar Percentage Difference And Integrated Aerosmentioning

confidence: 88%

Comparison of aerosol extinction between lidar and SAGE II over Gadanki, a tropical station in India

Kulkarni

Ramachandran

2015

Ann. Geophys.

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Abstract. An extensive comparison of aerosol extinction has been performed using lidar and Stratospheric Aerosol and Gas Experiment (SAGE) II data over Gadanki (13.5 • N, 79.2 • E), a tropical station in India, following coincident criteria during volcanically quiescent conditions from 1998 to 2005. The aerosol extinctions derived from lidar are higher than SAGE II during all seasons in the upper troposphere (UT), while in the lower-stratosphere (LS) values are closer. The seasonal mean percent differences between lidar and SAGE II aerosol extinctions are > 100 % in the UT and < 50 % above 25 km. Different techniques (point and limb observations) played the major role in producing the observed differences. SAGE II aerosol extinction in the UT increases as the longitudinal coverage is increased as the spatial aerosol extent increases, while similar extinction values in LS confirm the zonal homogeneity of LS aerosols. The study strongly emphasized that the best meteorological parameters close to the lidar measurement site in terms of space and time and B a (sr −1 ), the ratio between aerosol backscattering and extinction, are needed for the tropics for a more accurate derivation of aerosol extinction.

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Section: Sage II and Lidar Percentage Difference And Integrated Aerosmentioning

confidence: 88%

Comparison of aerosol extinction between lidar and SAGE II over Gadanki, a tropical station in India

Kulkarni

Ramachandran

2015

Ann. Geophys.

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“…The backscattered lidar signal received using a 350 mm diameter telescope, is separated into two orthogonal polarized components and acquired in photon counting mode with a basic altitude resolution of 300 m and time resolution of 4 min. The data acquired in these two channels are used to estimate [ Parameswaran et al , 2010] the altitude profile of particulate backscatter coefficient ( β p ), the particulate extinction coefficient ( α P ) and the volume depolarization ratio (VDR). The method of estimation of these parameters from the lidar signal and the associated uncertainties are discussed in earlier publications [ Sunilkumar and Parameswaran , 2005; Thampi et al , 2009; Parameswaran et al , 2010].…”

Section: Sage‐ii and Lidar Datamentioning

confidence: 99%

“…The data acquired in these two channels are used to estimate [ Parameswaran et al , 2010] the altitude profile of particulate backscatter coefficient ( β p ), the particulate extinction coefficient ( α P ) and the volume depolarization ratio (VDR). The method of estimation of these parameters from the lidar signal and the associated uncertainties are discussed in earlier publications [ Sunilkumar and Parameswaran , 2005; Thampi et al , 2009; Parameswaran et al , 2010]. The lidar signal is inverted using Fernald 's [1984] method taking the reference altitude at 30 km, where the aerosol contribution is assumed to be negligible.…”

Section: Sage‐ii and Lidar Datamentioning

confidence: 99%

“…An appropriate value of lidar ratio applicable for the tropics [ Omar et al , 2010; Pedrós et al , 2010] especially for the southern part of the Indian peninsula [ Müller et al , 2007] is used for the inversion. Accordingly a value of 40 Sr is adopted for the lidar ratio at the reference altitude and its variation below this altitude is incorporated using the method detailed in earlier publication [ Parameswaran et al , 2010]. The value of VDR at each altitude is obtained by taking the ratio of the backscattering coefficient of the cross‐polarized component to that of the copolarized component [ Sunilkumar et al , 2003].…”

Section: Sage‐ii and Lidar Datamentioning

confidence: 99%

“…The altitude profile of β p is estimated from the altitude profile of backscattering coefficient estimated from the lidar data by subtracting the corresponding molecular backscattering coefficient estimated from the altitude profile of molecular number density. The altitude profile of β p is multiplied by the lidar ratio corresponding to the respective altitude [ Parameswaran et al , 2010] to derive the altitude profile of α P .…”

Section: Sage‐ii and Lidar Datamentioning

confidence: 99%

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Variability in background stratospheric aerosols over the tropics and its association with atmospheric dynamics

Sunilkumar¹,

Parameswaran²,

Thampi³

et al. 2011

J. Geophys. Res.

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[1] Spatiotemporal variability of background stratospheric aerosols over the tropics (30°S-30°N) and its association with atmospheric dynamics are studied using the zonal-averaged Stratospheric Aerosol and Gas Experiment II (SAGE-II) derived aerosol extinction at 525 nm along with lidar data at 532 nm from Gadanki (13.5°N, 79.2°E) during the period 1998-2005. In general, a pronounced increase in aerosol loading is observed in the spatial distribution of aerosols over the equatorial region compared to the off-equatorial regions. The particulate optical depth (t P ) in the lower stratospheric region showed an increasing trend particularly after 2002 in both these regions. This increase could partly be attributed to a corresponding increase in the number of feeble/minor volcanic eruptions. Over and above this steady increase, the t P also showed significant periodic variations. In addition to the prominent short-period variations, the stratospheric t P showed a significant biennial variation (with a period of ∼30 months) in association with stratospheric quasi-biennial oscillation in zonal wind (QBO U ). During the westerly phase of stratospheric QBO U , the mean particulate optical depth decreases rapidly with increase in latitude on either side of equator in both the hemispheres, while it remains fairly steady around the equator up to 15°in latitude on either side with a small bite-out around the equator during the easterly phase, particularly during the very quiet period of 1998-2002. During the latter half (after 2002), when the stratosphere was mildly disturbed, the latitudinal variation of t P was fairly similar in both phases of QBO U with a higher value of t P near the equator during the westerly phase. The QBO signal in aerosol extinction around 25 km is found to be in opposite phase with that observed in the upper regime (28-32 km) and lower regime (18-22 km), depicting the influence of the secondary meridional circulation produced owing to vertical shear of QBO U in the equatorial region.Citation: Sunilkumar, S. V., K. Parameswaran, B. V. Thampi, and G. Ramkumar (2011), Variability in background stratospheric aerosols over the tropics and its association with atmospheric dynamics,

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Mean structure of the tropical tropopause and its variability over the Indian longitude sector

2012

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Latitudinal dependence of the seasonal variation of particulate extinction in the UTLS over the Indian longitude sector during volcanically quiescent period based on lidar and SAGE-II observations

Cited by 7 publications

References 56 publications

Comparison of aerosol extinction between lidar and SAGE II over Gadanki, a tropical station in India

Comparison of aerosol extinction between lidar and SAGE II over Gadanki, a tropical station in India

Variability in background stratospheric aerosols over the tropics and its association with atmospheric dynamics

Mean structure of the tropical tropopause and its variability over the Indian longitude sector

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