Long-term (2003–2013) climatological trends and variations in aerosol optical parameters retrieved from MODIS over three stations in South Africa

Kumar, K. Raghavendra; Sivakumar, Venkataraman; Yin, Yan; Reddy, R.R.; Na, Kang; Diao, Yiwei; Adesina, Joseph A.; Yu, Xiangyao

doi:10.1016/j.atmosenv.2014.07.001

Cited by 63 publications

(38 citation statements)

References 29 publications

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“…While Durban in the Kwazulu-Natal province has three geographical regions of lowland, midland and plateau with the surrounding coastal region having subtropical forest has the highest AOD 550 close to 0.2. Similar observations with high AOD values in north and low in south has been reported by earlier researchers over SA and other parts of world (Alam et al, 2010;Balakrishnaiah et al, 2012;Kumar et al, 2014;Kang et al, 2015). In terms of temporal variation, the mean AOD 550 for the study period (2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)) is noticed to be the lowest at Bloemfontein 0.06 ± 0.04 followed by Cape Town 0.08 ± 0.02, then Potchefstroom 0.09 ± 0.05; Pretoria and Skukuza had 0.11 ± 0.05 each and with the highest observed at Durban 0.13 ± 0.05.…”

Section: Spatial and Temporal Variations Of Aod And Aesupporting

confidence: 78%

“…4(a)-4(h) reveals that airmasses reached SA from the South Atlantic Ocean (SAO), Indian Ocean (IO), biomass burning and forest fires from Botswana, Namibia, Mozambique, and Madagascar and also from the Sahara deserts, and subsequently passed over the various cities in SA. Kumar et al (2014) found that most of the back trajectories identified airmass flow originating either from the Sahara desert dust or from the biomass burning/forest fire events occurred over north and northeast parts of SA and consequently, a significant increase in AOD values during the summer and spring seasons. On 15 th January the air parcels at all levels over Skukuza, Pretoria, Potchefstroom, Bloemfontein and Durban originated from the marine environment of IO and traversing through Madagascar Island before reaching sites, except in Cape Town, where all the trajectories travelled a long distance from far SAO.…”

Section: Identification Of Aerosol Sources Using Trajectory Analysismentioning

confidence: 99%

“…These locations are diverse in population, climate and topographic variation; make SA geographically unique for any study of spatio-temporal patterns. The description of each region was described by several earlier researchers (Adesina et al, 2010;Sivakumar et al, 2010;Queface et al, 2011;Kumar et al, 2013;Adesina et al, 2014;Kumar et al, 2014;Hersey et al, 2015). …”

Section: Study Locationsmentioning

confidence: 99%

“…Although many researchers have carried out investigations on the aerosol optical depth (AOD) over some parts or the whole of South Africa (SA) using both ground-based instruments (Kumar et al, 2013 and references therein; Adesina et al, 2014;Hersey et al, 2015) and satellite-based instruments (Tesfaye et al, 2011;Kumar et al, 2014), but aerosol-cloud-precipitation interactions has not been reported to the best of our knowledge. A number of studies have been conducted to address the spatial and temporal variability of aerosols and clouds and its impact on rainfall (e.g., Alam et al, 2010;Balakrishnaiah et al, 2012;Alam et al, 2014;Kang et al, 2015 and references therein).…”

Section: Introductionmentioning

confidence: 99%

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Aerosol-Cloud-Precipitation Interactions over Major Cities in South Africa: Impact on Regional Environment and Climate Change

Adesina

Kumar

Sivakumar

2016

Aerosol Air Qual. Res.

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In this study, we have used the Terra satellite onboard of the Moderate Resolution Imaging Spectroradiometer (MODIS) to investigate the spatial and temporal relationship between aerosol optical depth (AOD) and cloud parameters namely, water vapor (WV), cloud optical depth (COD), cloud fraction (CF), cloud effective radius (CER), cloud top pressure (CTP), and cloud top temperature (CTT) based on 10 years (from January 2004 to December 2013) of dataset over six locations in South Africa (SA). The obtained results indicated seasonal variation in AOD, with high values during spring (September to November) and low values in winter (June to August) in all locations of study. In terms of temporal variation, AOD was lowest at Bloemfontein 0.06 ± 0.04 followed by Cape Town 0.08 ± 0.02, then Potchefstroom 0.09 ± 0.05, Pretoria and Skukuza had 0.11 ± 0.05 each and with the highest at Durban 0.13 ± 0.05. The mean Angstrom exponent (AE) values for each location showed a general prevalence of fine-mode particles which dominates the AOD for most parts of the year. A hybrid single particle Lagrangian integrated trajectory (HYSPLIT) model was used for trajectory analysis in order to determine the origin of airmasses and to understand the variability of AOD. We then studied the relationship between AOD, cloud parameters and precipitation over selected locations of SA so as to provide a better understanding of aerosol-cloud-precipitation interactions. All these correlations examined over six sites were observed to be depended on the large-scale meteorological variations.

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Section: Spatial and Temporal Variations Of Aod And Aesupporting

confidence: 78%

Section: Identification Of Aerosol Sources Using Trajectory Analysismentioning

confidence: 99%

Section: Study Locationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Aerosol-Cloud-Precipitation Interactions over Major Cities in South Africa: Impact on Regional Environment and Climate Change

Adesina

Kumar

Sivakumar

2016

Aerosol Air Qual. Res.

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“…As variações das propriedades óticas dos aerossóis atmosféricos in uenciam fortemente os processos de transferência da radiação solar ao longo da atmosfera (Wright et al, 2010;Alam et al, 2011;Kumar, 2014;Kumar et al, 2014). Os aerossóis atuam diretamente sobre o clima por meio da absorção e do espalhamento da radiação solar e indiretamente através da atuação como núcleos de condensação, o que pode modi car as propriedades físicas das nuvens e alterar os regimes de precipitação (Artaxo et al, 2006;Wright et al, 2010;Murthy et al, 2014).…”

Section: Introductionunclassified

Variabilidade Espaço-Temporal Da Profundidade Ótica De Aerossóis Atmosféricos Sobre a Amazônia

Costa

Palácios

Menezes³

et al. 2018

R. Ci. Amb.

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RESUMOAs propriedades físicas de aerossóis atmosféricos, entre elas a sua profundidade ótica (AOD), possuem importância para os processos de interação entre a superfície e a atmosfera. A atmosfera da Amazônia brasileira sofre mudanças signi cativas em termos das propriedades físicas de aerossóis devido a grandes quantidades de partículas emitidas pela queima de biomassa, porém, carece de estudos que avaliem sua variabilidade espacial e temporal. Nesse sentido, esse trabalho objetivou analisar e quanti car a AOD na faixa de 550 nm (AOD 550 nm), a partir dos produtos de sensoriamento remoto, MOD04_L2 e MOD08_D3, para aerossóis do sensor MODIS, para o período de 2010 a 2014, sobre as regiões de Manaus, Santarém, Porto Velho, Rio Branco, Ji Paraná e Cuiabá. Foi constatado que, em todas as regiões analisadas, a AOD 550 nm apresentou variação sazonal com os máximos atingidos na estação seca. A variabilidade espaço-temporal evidenciou que as regiões de Manaus e Santarém são menos impactadas pelo aumento da AOD 550 nm que as demais regiões. Em Manaus, as médias para todo o período de estudo foram de 0.24 ± 0.26 e 0.20 ± 0.16 para as estações seca e chuvosa respectivamente, enquanto que para Ji Paraná as médias de todo o período de estudo foram de 0.34 ± 0.43 e 0.14 ± 0.08, chegando a atingir uma média de 0.75 ± 0.69 para a estação seca de 2010. Foi constatado que a variabilidade espacial e temporal estão diretamente relacionadas em todas as regiões. Palavras-chave: AOD; Sensor MODIS; MOD04_L2, MOD08_D3; Variação Sazonal. ABSTRACTSpatio-temporal variability of aerosols optical depth over Amazon. e physical properties of atmospheric aerosols, among them the optical depth (AOD) has importance for the processes of interaction between the surface and the atmosphere. e atmosphere of the Brazilian Amazon su ers signi cant changes in terms of the physical properties of aerosols due to large quantities of particles emitted by biomass burning, however, lack of studies that assess their spatial and temporal variability. In this sense this study aimed to analyze and quantify the AOD in the range of 550 nm (AOD 550 nm), from the products of remote

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The GAW‐PFR aerosol optical depth network: The 2008–2013 time series at Cape Point Station, South Africa

et al. 2015

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A ground-based aerosol optical depth (AOD) climatology is presented for Cape Point (CPT) station, South Africa, for the 2008-2013 period. CPT is part of the Global Atmosphere Watch-Precision Filter Radiometer network which conducts long-term AOD measurements at remote background sites. AOD (λ = 500 nm) and Ångström exponent (368 to 862 nm; α 368-862 ) averages for the entire period were 0.059 and 0.68, displaying only a weak seasonality. Based on an established method for air mass classification using the in situ wind direction and 222 Rn concentration, the following four air mass types were used to further investigate AOD: background marine, marine, mixed, and continental. AOD was similar for all types, but α 368-862 was distinctly lower (0.43) for background marine and higher (1.07) for continental air masses, illustrating the presence of coarse mode and anthropogenic aerosols, respectively. Trajectory cluster analysis of 5 day back trajectories confirmed/augmented this classification. AOD for background marine and marine air mass types were consistent with ship-based (Maritime Aerosol Network) and island (AErosol RObotic NETwork) measurements, suggesting that CPT is a suitable site to monitor pristine conditions in the South Atlantic and Southern Oceans when 222 Rn concentrations are < 100 mBq m À3 .

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Long-term (2003–2013) climatological trends and variations in aerosol optical parameters retrieved from MODIS over three stations in South Africa

Cited by 63 publications

References 29 publications

Aerosol-Cloud-Precipitation Interactions over Major Cities in South Africa: Impact on Regional Environment and Climate Change

Aerosol-Cloud-Precipitation Interactions over Major Cities in South Africa: Impact on Regional Environment and Climate Change

Variabilidade Espaço-Temporal Da Profundidade Ótica De Aerossóis Atmosféricos Sobre a Amazônia

The GAW‐PFR aerosol optical depth network: The 2008–2013 time series at Cape Point Station, South Africa

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