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Spatio-Temporal Distribution of Aerosol and Cloud Properties Over Sindh Using MODIS Satellite Data and a HYSPLIT Model

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Spatio-Temporal Distribution of Aerosol and Cloud Properties Over Sindh Using MODIS Satellite Data and a HYSPLIT Model Aerosol and Air Quality Research, 15: 657–672, 2015 Copyright © Taiwan Association for Aerosol Research ISSN: 1680-8584 print / 2071-1409 online doi: 10.4209/aaqr.2014.09.0200 Spatio-Temporal Distribution of Aerosol and Cloud Properties over Sindh Using MODIS Satellite Data and a HYSPLIT Model Fozia Sharif1, Khan Alam2,3*, Sheeba Afsar1 1 Department of Geography, University of Karachi, Karachi 75270, Pakistan 2 Institute of Space and Planetary Astrophysics, University of Karachi, Karachi 75270, Pakistan 3 Department of Physics, University of Peshawar, Peshawar 25120, Pakistan ABSTRACT In this study, aerosols spatial, seasonal and temporal variations over Sindh, Pakistan were analyzed which can lead to variations in the microphysics of clouds as well. All cloud optical properties were analyzed using Moderate Resolution Imaging Spectroradiometer (MODIS) data for 12 years from 2001 to 2013. We also monitored origin and movements of air masses that bring aerosol particles and may be considered as the natural source of aerosol particles in the region. For this purpose, the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model was used to make trajectories of these air masses from their sources. Aerosol optical depth (AOD) high values were observed in summer during the monsoon period (June–August). The highest AOD values in July were recorded ranges from 0.41 to 1.46. In addition, low AOD values were found in winter season (December–February) particularly in December, ranges from 0.16 to 0.69. We then analyzed the relationship between AOD and Ångström exponent that is a good indicator of the size of an aerosol particle. We further described the relationships of AOD and four cloud parameters, namely water vapor (WV), cloud fraction (CF), cloud top temperature (CTT) and cloud top pressure (CTP) by producing regional correlation maps of their data values. The analyses showed negative correlation between AOD and Ångström exponent especially in central and western Sindh. The correlation between AOD and WV was throughout positive with high correlation values > 0.74 in whole Sindh except eastern most arid strip of the Thar Desert in the region. The correlation between AOD and CF was positive in southern Sindh and goes to negative in northern Sindh. AOD showed a positive correlation with CTP and CTT in northern Sindh and a negative correlation in southern Sindh. All these correlations were observed to be dependent on the meteorological conditions for all of the ten sites investigated. Keywords: AOD; CTT; CTP; CF; Ångström exponent. INTRODUCTION significant role in the climatic system (Balakrishnaiah et al., 2012; Alam et al., 2014). Aerosols demonstrate both Aerosols are minute solid and liquid particles suspended spatial and temporal variations, which may lead to variations in the atmosphere. These may occur in the form of natural in the cloud optical properties (Alam et al., 2010). Their dust particles, volcanic dust, mist, clouds, fog, sea salts, ability to absorb or scatter solar radiations have direct impact anthropogenic aerosols, oceanic sulphates, industrial to increase or decrease the temperature of the atmosphere sulphates, soot (Black carbon), organic particles and some (Ichuku et al., 2004; IPCC, 2013). In addition, their indirect toxic pollutants after various physical and chemical processes affect modifies the cloud lifetime, albedo, and the that have several effects on our atmosphere ( Gupta et al., precipitation by changing the size and density of cloud 2013). droplets in the atmosphere (Lohmann., 2002; Alam et al., Interactions between aerosols and clouds have become a 2010; Balakrishnaiah et al., 2012). In addition, as smaller key topic of scientific research due to the importance of cloud droplets are less efficient to produce precipitation, an clouds in controlling climate (Mahowald and Kiehl, 2003; increased aerosol population will cause to a longer cloud life. Alam et al., 2010, 2014). Aerosols and clouds play a very Cloud formation requires super-saturation with aerosol that also explains the importance of aerosols in our atmosphere (Alam et al., 2010). These particles also emitted and reflected radiation from the earth in different directions depending * Corresponding author. on their physical and chemical properties (Ichuku et al., Tel.: +92-91-9216727 2004). Therefore, the description of atmospheric aerosols E-mail address: [email protected] is important to understand global solar heat budgets, water 658 Sharif et al., Aerosol and Air Quality Research, 15: 657–672, 2015 cycle and various dynamics of climate change (Ichuku et al., year i.e., 2008 with highest AOD concentrations in the 2004). Increasing anthropogenic aerosol concentrations lead atmosphere. Alam et al. (2014) examined AOD and cloud to form cloud condensation nuclei (CCN) that ranges from parameters such as water vapor, cloud top temperature, cloud smaller effective radii to longer-lived clouds, affecting the top pressure and cloud fraction over five cities in Pakistan hydrological cycle (Ramanathan et al., 2001; Balakrishnaiah during the period (2001–2011). The AOD and cloud optical et al., 2012). A wide range of studies has shown aerosol and properties correlations changes with changing seasons in cloud interactions with large uncertainties in the magnitude Pakistan e.g., AOD showed a positive correlation with CTP of radiative forcing (e.g., Twomey et al., 1984; Coakley et and CTT for the spring season and a negative correlation al., 1987; Kaufman and Nakajima, 1993; Kaufman and was observed in summer in all investigated regions. Fraser, 1997a, b; Ackerman et al., 2000; Rosenfeld, 2000; This study focused on three objectives. The first objective Ramanathan et al., 2001; Rosenfeld et al., 2002; Schwartz was to understand the spatio-temporal distribution of AOD et al., 2002; Kim et al., 2003; Andreae et al., 2004; Koren over Sindh, Pakistan. The second objective was to investigate et al., 2004; Penner et al., 2004; Kaufman et al., 2005; Koren the relationship between AOD and cloud parameters (i.e., et al., 2005; Alam et al., 2010; Balakrishnaiah, 2012; Alam Cloud fraction, cloud-top pressure, cloud-top temperature et al., 2014). and water vapor). The third objective was to analyze the Alam et al. (2010) and Balakrishnaiah et al. (2012) have influence of air mass trajectory on AOD concentrations. examined the spatial and temporal variations in aerosol Aerosols spatio-temporal distributions, seasonal variations particles and the impact of these variations over different and physical properties may be determined within a short locations in Pakistan and India. They found highest AOD span of time from land, aircraft, or satellite remote sensing values during the monsoon period (June–August). Their (Ichoku et al., 2004). The analysis of air mass trajectories analysis also showed a strong positive correlation for AOD helps to determine natural source of aerosols in southern and cloud parameters in some regions and a negative Pakistan. The months of January (winter), July (summer), correlation in other regions. Ramachandran and Jayaraman April (spring) and October (autumn) were chosen as these (2003) investigated AOD values for February–March 2001 are considered as representatives of four seasons in the over the Bay of Bengal. They found higher AODs on 21 study region. In particular, AOD-cloud parameter correlation February influenced by the air masses originating either study acquired for thirteen years (2001–2013) suggests new from India or Bangladesh at different heights, indicating findings in a region. the anthropogenic sources. They concluded the difference in AOD values over Chennai that is a coastal urban station MATERIALS AND METHODS of India with that of clean continental land. Reasons may be due to the difference of anthropogenic activities and Site Description meteorological conditions, wind patterns and subsequently Sindh (23°42′–28º29′N; 67°24′–71°05′E) is the third loading of aerosol particles. Kaufman et al. (2002) observed largest province of Pakistan with a population of strong link of anthropogenic aerosols with the climate approximately 42 million. It is bounded by Balochistan to system and the hydrological cycle. A region with a clean the west, Punjab to the north, Indian states (Gujarat and atmosphere (with no pollutant) has relatively large cloud Rajasthan) to the east and the Arabian Sea to the south of its droplets to form clouds for precipitation, although natural location (Fig. 1(b)). The landscape of Sindh is diversified, aerosols are required to condense upon; a cloud does not having Kirthar Mountains to the west, Thar Desert to the form otherwise. In contrast, urban smoke and pollutants east, and Piedmont Plains to the north of Sindh. The affect cloud radiative properties and reduce precipitation at climate of Sindh is hot and semi-arid. It has a variation in the same time. Thus, anthropogenic aerosols impact the temperature as inland extreme temperatures to maritime hydrological cycle with a change in cloud cover, cloud moderate temperatures. For an inland Sindh, the temperature property and rainfall patterns in a region. Gupta et al. (2013) rises above 46°C in May and falls up to 2°C in January. In examined the quantity and quality of MODIS data over addition, the coastal region has temperature not more than urban areas of Pakistan. They found a lack of availability 40°C and less than 10°C for summer and winter months, of MODIS data over Karachi due to the presence of bright respectively. Mainly rainfalls
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