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This paper presents the long – term observational studies on aerosol optical properties measured at Sri Krishnadevaraya University (SKU) campus (14° 62′ N, 77° 65′ E, 331m asl), Anantapur, in southern India during 2007–2013 using a ground based Multi – Wavelength solar Radiometer (MWR). Seasonal mean values of Aerosol Optical Depth (AOD) for the whole study period were observed to be 0.34 ± 0.03, 0.45 ± 0.04, 0.24 ± 0.04, and 0.31 ± 0.03 during the winter, summer, monsoon and post – monsoon, respectively. Annual mean values of Ångström exponent (α) (turbidity coefficient (β)) varied from 0.68 ± 0.25 (0.18 ± 0.03) to 1.1 ± 0.12 (0.32 ± 0.12) during 2007–2013. However, high values of α in the range of 0.8–1.1 were observed during the winter, while low values in the range 0.3–0.7 were noticed during the monsoon. The frequency distribution of AODs during winter in the range of 0.2–0.4 is about 78%, while summer these were shifted from 0.3 to 0.6 around ∼70%, which indicated the dust strongly affects this region. The accumulated frequencies of Ångström exponent (α) less than 1.0 and greater than 1.0 were about 69% and 31%, respectively, occurred in the summer months indicates the dominance of coarse particles. Columnar size distributions, retrieved from the spectral optical depths, in general, show a bimodal log normal distribution in the optically active size range. The seasonal mean effective radius (R eff ) was found to be high in monsoon (∼0.61 μm) and low in winter (∼0.38 μm). The highest mean mass loading values are lies between 475 ± 36 to 769 ± 49 mg m −2 during the summer, whereas the lowest value in the range 204 ± 19 to 278 ± 23 mg m −2 during the monsoon. The difference between α and curvature effect have been studied as a function of AOD on seasonal basis. Finally, to understand the contribution of long range transported aerosols, we have investigated this analysis making use of back trajectories obtained from the HYSPLIT model for different seasons. [ABSTRACT FROM AUTHOR]

Abstract: Every year during the winter and pre-monsoon periods most of the Indian peninsula, Bay of Bengal and the adjoining Indian Ocean are affected by a polluted regional haze, known as the South Asian Winter Haze (SAWH). This article is the first of a series of three papers collectively anticipated at the central idea of retrieving aerosol component type and effective radius of the SAWH by incorporating experimental data of ground-based solar radiometer into Mie theory, and validation by collocated in-situ measurements. The work presented in this paper provides an approach to retrieve optical depths and their spectral curvature for SAWH at a tropical coastal station, Visakhapatnam (17.7°N, 83.3°E). A dataset comprised of 92 wintertime atmospheric optical depths are obtained from spectral extinction measurements of direct solar flux by means of a Multi-Wavelength Solar Radiometer during the period of October 2002 to February 2004. The inter-channel correlations established a linear relation and the airmass conditions specific to this dataset suggested a two-component linear model; the stable and variable components of which are analysed to obtain the mentioned optical parameters. Results indicate that the spectral curvature is best represented by a Lorentz model with a central wavelength of 0.40425±0.02945μm, a width of 0.40382±0.10253μm, a constant of 0.92623±0.33793, and a wavelength independent component of 0.95778±0.15678. Resonance-like structure of the obtained spectral curvature resembles wavelength dependent extinction characteristic of absorbing soot particles; thereby supports the key findings from INDOEX campaign. [Copyright &y& Elsevier]

Abstract: In this paper we have studied variability and growth rate of surface observed atmospheric Carbon Dioxide (CO2) concentrations over Cape Rama, west coast of India and its association with rainfall and vegetation over this region. Cape Rama is a maritime site which experiences a seasonal reversal wind pattern receiving air masses having marine (continental) signatures during summer (winter) monsoon season. This study reveals that summer monsoon (JJAS) precipitation and monthly values of atmospheric CO2 concentration during the season are well correlated. Negative correlations are seen with CO2 concentrations of concurrent months of the season as well as subsequent months. However the magnitudes of correlation coefficients are decreased till hot pre-monsoon season (MAM). Annual cycle and interannual variability show negative relationship between CO2 concentration and vegetation over the region. CO2 concentration shows increasing trend and NDVI shows decreasing trend. However, the magnitude of increasing trend of CO2 concentration is higher. Amplitude of decreasing phase of vegetation is higher than the amplitude of increasing phase. Though the results show certain link between CO2 and climate variability, further examination with dense and longer data may be needed to confirm the result. [Copyright &y& Elsevier]

Abstract: The significant role of aerosol–cloud interaction during the large-scale drought producing breaks of 2009 Indian Summer Monsoon is investigated in the present paper. This mega drought had already been attributed to two long breaks, one in June and the other in July-August. While Central India (CI) and northern parts of the country experienced deficient rainfall, the rainfall over the southern Peninsular India (PI) remained close to normal. During the first break in June, which was associated with mid-latitude intrusion of dry air, the Twomey effect (positive aerosol indirect effect – AIE) was a dominant factor inhibiting efficient precipitation over CI region, as compared to that over PI. Moreover, the number of days that experienced significant (at 5% level of significance) positive AIE during the first break was more over CI compared to the same during the second break. The AIE on ice clouds was not as significant as that of the low-clouds. The resulting cloud properties during both break and active phases over CI differ significantly from that over PI for the corresponding periods. The positive AIE mentioned here is attributed to the large-scale deficit of moisture supply to the CI region due to dynamical reasons. However, it is shown that under ample availability of moisture, more aerosols could invigorate deep clouds over specific regions even during the break spells. [Copyright &y& Elsevier]

Abstract: Aerosol measurements over a tropical semi-arid site in Anantapur (14.62°N, 77.65°E, 331 m asl), India, provide the variabilities of aerosol characteristics for the period of January 2007–December 2008. The mean values of aerosol optical depth at 500 nm (AOD500 nm) over 2-year period are found to be 0.37 ± 0.11, 0.39 ± 0.13 and 0.30 ± 0.10 during winter, summer and monsoon seasons, respectively. A rather systematic variation is seen with AOD peaking in the month of March, falling off gradually to the lowest value in June and increasing slowly superposed with some modulations, which show a weak secondary peak in October. The mean and standard values of the Ångström exponent, α (turbidity coefficient, β), are found to be 1.06 ± 0.33 (0.17 ± 0.05) during winter, 0.97 ± 0.35 (0.22 ± 0.04) during summer and 0.85 ± 0.26 (0.16 ± 0.06) during monsoon. The frequency distribution of α is relatively broad with two modes for dusty (α < 1) and non-dusty (α > 1) situations. This frequency distribution of α reveals a great dispersion of a values in all seasons thus denoting variability in the aerosol-size distribution. In this study, spectral AOD and Ångström exponent data are analyzed to obtain information about the adequacy of the simple use of the Ångström exponent and its variation for characterizing optical properties of aerosols, and exploring possibilities for a more efficient characterization of them. Using the least-squares fit method, the Ångström parameter, α, is calculated in the spectral interval 380–850 nm, along with coefficients a1 and a2 of the second-order polynomial fit to the plotted logarithm of AOD versus the logarithm of wavelength. The correlations between the coefficients a1 and a2 with months and α are discussed in the paper. [Copyright &y& Elsevier]