Characteristics of aerosol types from AERONET sunphotometer measurements

Lee, J.; Kim, J.; Song, Chul H.; Kim, S.B.; Chun, Youngsin; Sohn, Byung-Ju; Holben, B. N.

doi:10.1016/j.atmosenv.2010.05.035

Cited by 247 publications

(180 citation statements)

References 29 publications

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“…Some studies have successfully combined SSA with other parameters to determine the aerosol type over different regions (Lee et al, 2010;He et al, 2012b;Logan et al, 2013). However, over regions with low aerosol load (AOD 440 nm < 0.40) it is difficult to obtain aerosol type by SSA due to inadequate accuracy (Dubovik and King, 2000).…”

Section: Analysis Methodsmentioning

confidence: 99%

“…7) can also reflect the particle size, and FMF is well correlated with AE at each site. However, there are still some differences between AE and FMF, because AE can be changed according to the effective radius of the fine mode aerosol and the ratio of fine mode to total volume concentration (Lee et al, 2010). At QOMS_CAS, the maximum FMF of 0.75 occurs in February.…”

Section: Seasonal Variationsmentioning

confidence: 99%

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Similarities and differences of aerosol optical properties between southern and northern sides of the Himalayas

Panday

et al. 2014

Atmos. Chem. Phys.

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Abstract. The Himalaya mountains along the southern edge of the Tibetan Plateau act as a natural barrier for the transport of atmospheric aerosols from the polluted regions of South Asia to the main body of the Tibetan Plateau. In this study, we investigate the seasonal and diurnal variations of aerosol optical properties measured at two Aerosol Robotic Network (AERONET) sites on the southern side of the Himalaya (Pokhara, 812 m above sea level (a.s.l.) and EVK2-CNR, 5079 m a.s.l. in Nepal) and one on the northern side (Qomolangma (Mt. Everest) station for Atmospheric and Environmental Observation and Research, Chinese Academy of Sciences (QOMS_CAS) in Tibet, 4076 m a.s.l. in China). While observations at QOMS_CAS and EVK2-CNR can generally be representative of a remote background atmosphere, Pokhara is a lower-elevation suburban site with much higher aerosol load due to both the influence of local anthropogenic activities and to its proximity to the Indo-Gangetic Plains. The annual mean aerosol optical depth (AOD) during the investigated period was 0.05 at QOMS_CAS, 0.04 at EVK2-CNR and 0.51 at Pokhara, respectively. Seasonal variations of aerosols are profoundly affected by large-scale atmospheric circulation. Vegetation fires, peaking during April in the Himalayan region and northern India, contribute to a growing fine mode AOD at the three stations. Dust transported to these sites, wind erosion and hydrated/cloudprocessed aerosols lead to an increase in coarse mode AOD during the monsoon season at QOMS_CAS and EVK2-CNR. Meanwhile, coarse mode AOD at EVK2-CNR is higher than at QOMS_CAS in August and September, indicating that the transport of coarse mode aerosols from the southern to the northern side may be effectively reduced. The effect of precipitation scavenging is clearly seen at Pokhara, which sees significantly reduced aerosol loads during the monsoon season. Unlike the seasonal variations, diurnal variations are mainly influenced by meso-scale systems and local topography. The diurnal pattern in precipitation appears to contribute to diurnal changes in AOD through the effect of precipitation scavenging. AOD exhibits diurnal patterns related to emissions in Pokhara, while it does not at the other two high-altitude sites. At EVK2-CNR, the daytime airflow carries aerosols up from lower-altitude polluted regions, leading to increasing AOD, while the other two stations are less influenced by valley winds. Surface heating influences the local convection, which further controls the vertical aerosol exchange and the diffusion rate of pollution to the surrounding areas. Fine and coarse mode particles Published by Copernicus Publications on behalf of the European Geosciences Union. C. Xu et al.: Similarities and differences of aerosol optical propertiesare mixed together on the southern side of the Himalaya in spring, which may lead to the greater inter-annual difference in diurnal cycles of Ångström exponent (AE) at EVK2-CNR than that at QOMS_CAS.

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Section: Analysis Methodsmentioning

confidence: 99%

Section: Seasonal Variationsmentioning

confidence: 99%

Similarities and differences of aerosol optical properties between southern and northern sides of the Himalayas

Panday

et al. 2014

Atmos. Chem. Phys.

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“…In this region, smoke aerosols originate from scattered burning sources as seen by the MODIS fire mask (Giglio et al, 2003), which makes their optical and microphysical properties complicated. Smoke properties can vary according to material burned, combustion type, and aging processes (e.g., Dubovik et al, 2002;Reid et al, 2005;Lee et al, 2010;Sayer et al, 2014a). For the test case, the smoke layer with AOD generally higher than 0.8 (not shown) resides at altitudes ranging from 2-5 km (Fig.…”

Section: Ashe Algorithmmentioning

confidence: 99%

“…Currently, the SSA is provided at 340,378,412,445,488,555, and 672 nm (OMPS or VIIRS bands) for potential use as input for OMPS and/or VIIRS aerosol retrieval algorithms. In this application, we only assume smoke aerosol models since smoke (as opposed to dust) dominates during the spring season over the study domain (Lee et al, 2010).…”

Section: Ashe Algorithmmentioning

confidence: 99%

Evaluating the Height of Biomass Burning Smoke Aerosols Retrieved from Synergistic Use of Multiple Satellite Sensors over Southeast Asia

Lee

Hsu

Bettenhausen

et al. 2016

Aerosol Air Qual. Res.

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This study evaluates the height of biomass burning smoke aerosols retrieved from a combined use of Visible Infrared Imaging Radiometer Suite (VIIRS), Ozone Mapping and Profiler Suite (OMPS), and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations. The retrieved heights are compared against spaceborne and ground-based lidar measurements during the peak biomass burning season (March and April) over Southeast Asia from 2013 to 2015. Based on the comparison against CALIOP, a quality assurance (QA) procedure is developed. It is found that 74% (81-84%) of the retrieved heights fall within 1 km of CALIOP observations for unfiltered (QA-filtered) data, with root-mean-square error (RMSE) of 1.1 km (0.8-1.0 km). Eliminating the requirement for CALIOP observations from the retrieval process significantly increases the temporal coverage with only a slight decrease in the retrieval accuracy; for best QA data, 64% of data fall within 1 km of CALIOP observations with RMSE of 1.1 km. When compared with Micro-Pulse Lidar Network (MPLNET) measurements deployed at Doi Ang Khang, Thailand, the retrieved heights show RMSE of 1.7 km (1.1 km) for unfiltered (QA-filtered) data for the complete algorithm, and 0.9 km (0.8 km) for the simplified algorithm.

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“…Hence the ability to differentiate particles with respect to their size can provide a mean to quantify the influence of human activities on the abundance of atmospheric aerosols. Separating contributions from smaller and bigger particles in aerosol optical depth (AOD) is a step forward in this direction and can serve as a proxy to study many of the effects discussed above (Kosmopoulos et al, 2008;Lee et al, 2010;Kaskaoutis et al, 2012;Sinha et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Role of Coarse and Fine Mode Aerosols in MODIS AOD Retrieval: a case study over southern India

et al. 2014

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Abstract. In the present study we compare the MODIS (Moderate Resolution Imaging Spectroradiometer) derived aerosol optical depth (AOD) data with that obtained from operating sky-radiometer at a remote rural location in southern India (Gadanki, 13.45 • N, 79.18 • E) from April 2008 to March 2011. While the comparison between total (coarse mode + fine mode) AODs shows correlation coefficient (R) value of about 0.71 for Terra and 0.77 for Aqua, if one separates the AOD into fine and coarse mode, the comparison becomes very poor, particularly for fine mode with an R value of 0.44 for both Terra and Aqua. The coarse mode AOD derived from MODIS and sky-radiometer compare better with an R value of 0.74 for Terra and 0.66 for Aqua. The seasonal variation is also well captured by both ground-based and satellite measurements. It is shown that both the total AOD and fine mode AOD are significantly underestimated with slope of regression line 0.75 and 0.35 respectively, whereas the coarse mode AOD is overestimated with a slope value of 1.28 for Terra. Similar results are found for Aqua where the slope of the regression line for total AOD and fine mode AOD are 0.72 and 0.27 whereas 0.95 for coarse mode. The fine mode fraction derived from MODIS data is less than one-half of that derived from the sky-radiometer data. Based on these observations and comparison of single scattering albedo observed using sky-radiometer with that of MODIS aerosol models, we argue that the selection of aerosol types used in the MODIS retrieval algorithm may not be appropriate particularly in the case of southern India. Instead of selecting a moderately absorbing aerosol model (as being done currently in the MODIS retrieval) a more absorbing aerosol model could be a better fit for the fine mode aerosols, while reverse is true for the coarse mode aerosols, where instead of using "dust aerosols" which is relatively absorbing type, usage of coarse sea-salt particles which is less absorbing is more appropriate. However, not all the differences could be accounted based on aerosol model, other factors like errors in retrieval of surface reflectance may also be significant in causing underestimation of AOD by MODIS.

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Characteristics of aerosol types from AERONET sunphotometer measurements

Cited by 247 publications

References 29 publications

Similarities and differences of aerosol optical properties between southern and northern sides of the Himalayas

Similarities and differences of aerosol optical properties between southern and northern sides of the Himalayas

Evaluating the Height of Biomass Burning Smoke Aerosols Retrieved from Synergistic Use of Multiple Satellite Sensors over Southeast Asia

Role of Coarse and Fine Mode Aerosols in MODIS AOD Retrieval: a case study over southern India

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