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As part of the Seven Southeast Asian Studies (7SEAS) program, an Aerosol Robotic Network (AERONET) sun photometer and a Micro-Pulse Lidar Network (MPLNET) instrument have been deployed at Singapore to study the regional aerosol environment of the Maritime Continent (MC). Using coincident AERONET Level 2.0 and MPLNET Level 2.0a data from 24 September 2009 to 31 March 2011, the seasonal variability of aerosol particle vertical distributions and optical properties is examined. On average, the bulk (∼65%) of aerosol extinction is found below 1.5 km with substantial aerosol loading (∼35%) above. Possibly due to the transition from El Nino to La Nina conditions and subsequent reduction in fire events, the MPLNET mean integrated aerosol extinction is observed to be the lowest for July–September 2010, which coincides with the typical MC biomass burning season. On the other hand, the highest mean integrated extinctions are derived for January–March 2010 and 2011, which can be attributed to off-season MC biomass burning smoke and anthropogenic pollution. The seasonal lidar ratios also show higher occurrences ≥60 sr, which are indicative of biomass burning smoke, for October 2009–June 2010, but such occurrences decrease from July 2010 to March 2011 when La Nina conditions prevail. In addition, principal component analysis (PCA) identifies five primary aerosol vertical profile types over Singapore, i.e. strongly-capped/deep near-surface layer (SCD; 0–1.35 km), enhanced mid-level layer (EML; 1.35–2.4 km), enhanced upper-level layer (EUL; 2.4–3.525 km), deep contiguous layer (DCL; 3.525–4.95 km) and deep multi-layer (DML; >4.95 km). PCA also identifies an off-season MC biomass burning smoke event from 22 February to 8 March 2010, which is subsequently examined in detail.

During the spring of 2010, comprehensive in situ measurements were made for the first time on a small atoll (Dongsha Island) in the northern South China Sea (SCS), a key region of the 7-SEAS (the Seven South East Asian Studies) program. This paper focuses on characterizing the source origins, transport processes, and vertical distributions of the Asian continental outflows over the region, using measurements including mass concentration, optical properties, hygroscopicity, and vertical distribution of the aerosol particles, as well as the trace gas composition. Cluster analysis of backward trajectories classified 52% of the air masses arriving at ground level of Dongsha Island as having a continental origin, mainly from northern China to the northern SCS, passing the coastal area and being confined in the marine boundary layer (0-0.5 km). Compared to aerosols of oceanic origin, the fine mode continental aerosols have a higher concentration, extinction coefficient, and single-scattering albedo at 550 nm (i.e., 19 vs. 14 microg per cubic meter in PM(sub 2.5); 77 vs. 59 M per meter in beta(sub e); and 0.94 vs. 0.90 in omega, respectively). These aerosols have a higher hygroscopicity (f at 85% RH = 2.1) than those in the upwind inland regions, suggesting that the aerosols transported to the northern SCS were modified by the marine environment. In addition to the near-surface aerosol transport, a significant upper-layer (3-4 km) transport of biomass-burning aerosols was observed. Our results suggest that emissions from both China and Southeast Asia could have a significant impact on the aerosol loading and other aerosol properties over the SCS. Furthermore, the complex vertical distribution of aerosols-coinciding-with-clouds has implications for remote-sensing observations and aerosol-cloud-radiation interactions.

Vertical profiles of 0.532 μm aerosol particle extinction coefficient and linear volume depolarization ratio are described for Southeast Asia and the Maritime Continent. Quality-screened and cloud-cleared Version 3.01 Level 2 NASA Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) 5-km Aerosol Profile datasets are analyzed from 2007 to 2009. Numerical simulations from the U.S. Naval Aerosol Analysis and Predictive System (NAAPS), featuring two-dimensional variational assimilation of NASA Moderate Resolution Imaging Spectroradiometer and Multi-angle Imaging SpectroRadiometer quality-assured datasets, combined with regional ground-based lidar measurements, are considered for assessing CALIOP retrieval performance, identifying bias, and evaluating regional representativeness. CALIOP retrievals of aerosol particle extinction coefficient and aerosol optical depth (AOD) are high over land and low over open waters relative to NAAPS (0.412/0.312 over land for all data points inclusive, 0.310/0.235 when the per bin average is used and each is treated as single data points; 0.102/0.151 and 0.086/0.124, respectively, over ocean). Regional means, however, are very similar (0.180/0.193 for all data points and 0.155/0.159 when averaged per normalized bin), as the two factors offset one another. The land/ocean offset is investigated, and discrepancies attributed to interpretation of particle composition and a-priori assignment of the extinction-to-backscatter ratio (“lidar ratio”) necessary for retrieving the extinction coefficient from CALIOP signals. Over land, NAAPS indicates more dust present than CALIOP algorithms are identifying, indicating a likely assignment of a higher lidar ratio representative of more absorptive particles. NAAPS resolves more smoke over water than identified with CALIOP, indicating likely usage of a lidar ratio characteristic of less absorptive particles to be applied that biases low AOD there. Over open waters except within the Bay of Bengal, aerosol particle scattering is largely capped below 1.5 km MSL, though ground-based lidar measurements at Singapore differ slightly from this finding. Significant aerosol particle presence over land is similarly capped near 3.0 km MSL over most regions. Particle presence at low levels regionally, except over India, is dominated by relatively non-depolarizing particles. Industrial haze, sea salt droplets and fresh smoke are thus most likely present.

Following the explosive 7–8 August 2008 Mt. Kasatochi volcanic eruption in southwestern Alaska, a segment of the dispersing stratospheric aerosol layer was profiled beginning 16 August in continuous ground-based lidar measurements over the Mid-Atlantic coast of the eastern United States. On 17–18 August, the layer was displaced downward into the upper troposphere through turbulent mixing near a tropopause fold. Cirrus clouds and ice crystal fallstreaks were subsequently observed, having formed within the entrained layer. The likely seeding of these clouds by Kasatochi aerosol particles is discussed. Cloud formation is hypothesized as resulting from either preferential homogenous freezing of relatively large sulfate-based solution droplets deliquesced after mixing into the moist upper troposphere or through heterogeneous droplet activation by volcanic ash. Satellite-borne spectrometer measurements illustrate the evolution of elevated Kasatochi SO 2 mass concentrations regionally and the spatial extent of the cirrus cloud band induced by likely particle seeding. Satellite-borne polarization lidar observations confirm ice crystal presence within the clouds. Geostationary satellite-based water vapor channel imagery depicts strong regional subsidence, symptomatic of tropopause folding, along a deepening trough in the sub-tropical westerlies. Regional radiosonde profiling confirms both the position of the fold and depth of upper-tropospheric subsidence. These data represent the first unambiguous observations of likely cloud seeding by stratospheric volcanic aerosol particles after mixing back into the upper troposphere.

Cirrus clouds are endemic to Southeast Asia and are a source of potential bias in regional passive aerosol remote sensing datasets. Here, performance of the cloud-screening algorithm for the ground-based Aerosol Robotic Network (AERONET) sun photometer data is evaluated for cirrus cloud contamination at Singapore (1.30° N, 103.77° E). Using twelve months of concurrent AERONET Level 1.5 and 2.0 cloud-screened aerosol optical depth (AOD) data, and collocated Level 1.0 Micro-Pulse Lidar Network (MPLNET) measurements, we investigate the baseline AOD bias due to cirrus cloud presence. Observations are considered for a primary sample of all data and a secondary sample where AERONET data are restricted to a zenith viewing angle ≤ 45°. Cirrus clouds are present in zenith-viewing MPL profiles for 34% and 23% of these samples respectively. Based on approximations of cirrus cloud optical properties necessary to estimate cloud optical depth from the single-channel lidar signal, and assuming partial forward scattering of diffuse light by cirrus clouds into the sun photometer’s field of view, we estimate a range in AOD bias due to unscreened cloud presence of 0.034 to 0.060 and 0.031 to 0.055 ± 0.01 for the primary and secondary sample respectively. From the analysis of AERONET AOD for the angle-limited subset alone, we also derive a positive AOD bias of 0.034, which is comparable to the lower bounds for the estimated cloud bias reported for our datasets. These findings, which we attribute to the prevalence of cirrus clouds present from regional convection, are higher than previous reports of global AOD bias in the Moderate Resolution Infrared Spectroradiometer (MODIS) satellite-borne measurements due to residual cirrus cloud presence.

Two dust events were detected over the Yangtze Delta region of China during March 14e17 and April 25e26 in 2009 where such dust events are uncommon. The transport behavior, spatio-temporal evolution, vertical structure, direct radiative effects, as well as induced heating rates, are investigated using a combination of ground-based and satellite-based measurements, a back-trajectory analysis, an aerosol model and a radiative transfer model. Back-trajectories, wind fields and aerosol model analyses show that the first dust originated in northern/northwestern China and the second generated in the Taklimakan desert in northwest China, and traveled across the Hexi corridor and Loess Plateau to the Yangtze Delta region (the so-called “dust corridor”). The mean lidar extinction-to-backscatter ratio (LR) during the two dust events was 38.7 � 10.4 sr and 42.7 � 15.2 sr, respectively. The mean aerosol depolarization ratio ( da )f or thefirst dust event was 0.16 � 0.07, with a maximum value of 0.32. For the second, the mean da was around 0.19 � 0.06, with a maximum value of 0.29. Aerosol extinction coefficient and da profiles for the two events were similar: two aerosol layers consisting of dust aerosols and a mixture of dust and anthropogenic pollution aerosols. The topmost aerosol layer is above 3.5 km. The maximum mean aerosol extinction coefficients were 0.5 km �1 and 0.54 km �1 at about 0.7 km and 1.1 km, respectively. Significant effects of cooling at the surface and heating in the atmosphere were found during these dust events. Diurnal mean shortwave radiative forcings (efficiencies) at the surface, the top-of-the-atmosphere and within the atmosphere were � 36.8 (� 80.0), � 13.6 (� 29.6) and 23.2 (50.4) Wm �2 , respectively, during the first dust event, and � 48.2 (� 70.9), � 21.4 (� 31.5) and 26.8 (39.4) Wm �2 , respectively, during the second dust event. Maximum heating rates occurred at 0.7 km during the first dust event and at 1.1 km during the second dust event, with a maximum value of 2.74 K day �1 for each

Trans-Pacific Asian dust transport has been well documented, but little is known about dust invasion to the South China Sea (SCS). This study presents the first detailed characterization of dust aerosols transported to the northern SCS. On 21 March 2010, a strong Asian dust storm affected large areas from the Gobi deserts to the West Pacific, including Taiwan and Hong Kong, and was also observed by a comprehensive set of instruments at Dongsha Island, a small island (about 2 km 2 , 20°42′52" N, 116°43′51" E) in the northern SCS. Aerosol measurements including particle mass concentrations, size distribution, optical properties, hygroscopicity, and vertical profiles help depict the evolution of this dust event. Our results indicate that the dust particles were mixed with anthropogenic and marine aerosols, and transported within 250 m above ground level. The long-range transport of Asian dust to the northern SCS could significantly impact the ecosystems in the region.

The aerosol vertical distribution is an important factor in determining the relationship between satellite retrieved aerosol optical depth (AOD) and ground-level fine particle pollution concentrations. We evaluate how aerosol profiles measured by ground-based lidar and simulated by models can help improve the association between AOD retrieved by the Multi-angle Imaging Spectroradiometer (MISR) and fine particle sulfate (SO4) concentrations using matched data at two lidar sites. At the Goddard Space Flight Center (GSFC) site, both lidar and model aerosol profiles marginally improve the association between SO4 concentrations and MISR fractional AODs, as the correlation coefficient between cross-validation (CV) and observed SO4 concentrations changes from 0.87 for the no-scaling model to 0.88 for models scaled with aerosol vertical profiles. At the GSFC site, a large amount of urban aerosols resides in the well-mixed boundary layer so the column fractional AODs are already excellent indicators of ground-level particle pollution. In contrast, at the Atmospheric Radiation Measurement Program (ARM) site with relatively low aerosol loadings, scaling substantially improves model performance. The correlation coefficient between CV and observed SO4 concentrations is increased from 0.58 for the no-scaling model to 0.76 in the GEOS-Chem scaling model, and the model bias is reduced from 17% to 9%. In summary, despite the inaccuracy due to the coarse horizontal resolution and the challenges of simulating turbulent mixing in the boundary layer, GEOS-Chem simulated aerosol profiles can still improve methods for estimating surface aerosol (SO4) mass from satellite-based AODs, particularly in rural areas where aerosols in the free troposphere and any long-range transport of aerosols can significantly contribute to the column AOD.