CALIPSO lidar level 3 aerosol profile product: version 3 algorithm design

Analysis of characteristics and changes in three-dimensional spatial and temporal distribution of aerosol types in Central Asia

Atmospheric aerosol types and characteristics have regional and seasonal characteristics mainly due spatial and temporal differences in emission sources and diffuse transport conditions. We explored regional three-dimensional spatial and temporal distribution characteristics of aerosol types in Central Asia from daytime to nighttime by using long-term (2007-2021) CALIPSO lidar measurements. The three results are as follows: (1) Average aerosol optical depth (AOD) values during the 14 years were 0.44 and 0.47 during daytime and nighttime, respectively, with an overall decreasing trend, among which the AOD in spring in the southern border region and in winter in the northern border region showed high values, 0.66 and 0.31 during daytime and 0.69 and 0.33 during nighttime, respectively, and nighttime AOD values were higher than those of daytime, possibly due to the lower signal-to-noise ratio of the CALIPSO during the daytime than during the nighttime. (2) The primary representative aerosol type in the Taklamakan Desert region being pure sand and dust, and more apparent winter-polluted sand and dust exist along the northern slope of the Tianshan Mountains in Xinjiang in winter than in other areas. High-altitude soot mainly existed below 4 km and was primarily concentrated in northern Central Asia, with the highest values (0.016 and 0.003) in summer and winter, respectively, which may be due to different diffusion and transport conditions. (3) Dust aerosols in spring were mainly concentrated in the region of 2-6 km in the Taklamakan Desert area; pure dust particles in summer and fall lifted height diffusion and gradually moved to the northern border region; polluted dust was mainly in northern Xinjiang in fall and winter and spread to northern Central Asia; and the average top height of aerosols in the transmission process reached the top of the troposphere, and transmission height was higher than source area.

Application of multiplatform remote sensing data over East Asia Ocean: aerosol characteristics and aerosol types

It is important to explore the characteristics and rules of atmospheric aerosol in the East Asian Sea for monitoring and evaluating atmospheric environmental quality. Based on Aerosol Robot Network (AERONET), Visible Infrared Imaging Radiometer (VIIRS), and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data, the temporal and spatial variation characteristics and differences of aerosol parameters and types in the East Asian Sea were studied by using figure classification method (FIGCM), aerosol optical depth (AOD)440-Angstrom exponent (AE)440-870 method (AA1M), and AOD550-AE490-670 method (AA2M). The results show that the seasonal variation trend of aerosol characteristics and types is obvious in East Asia Sea. AOD, volume concentration (Cv), and aerosol effective radius (reff) in the Bohai-Yellow Sea and the Sea of Japan in autumn are lower than those in other seasons, and the occurrence frequency of ocean-type aerosols is high. Different from the Bohai-Yellow Sea and Sea of Japan, human activities in winter, summer, and autumn seriously affect the air quality in the East China Sea and South China Sea. Especially at the Taipei CWB site, from aerosol parameters and high biomass burning/urban industrial (BB/UI) aerosol, human activity is an important factor for high pollution at the Taipei CWB site. Aerosol types of AA1M, FIGCM, AA2M, and CALIPSO were compared at Anmyon and Yonsei University sites in the Bohai-Yellow Sea in March 2020. The results show that aerosol types based on threshold classification methods generally have higher mixed aerosol results, and the marine (MA) results of AA1M, FIGCM, and AA2M are close to the clean marine aerosol results of CALIPSO. Comparing the results of AA 2 M and CALIPSO on a spatial scale, it is found that the clean marine aerosol proportion identified by CALIPSO (0.38, 0.48, 0.82) is consistent with the MA proportion identified by AA 2 M (0.43, 0.46, 0.97) in the East China Sea, South China Sea, and Western Pacific Ocean.

Validation, inter-comparison, and usage recommendation of six latest VIIRS and MODIS aerosol products over the ocean and land on the global and regional scales

MODIS and VIIRS aerosol products have been used extensively by the scientific community. Products in operation include MODIS Dark Target (DT), Deep Blue (DB), and Multi-Angle Implementation of Atmospheric Correction (MAIAC) and VIIRS DT, DB, and NOAA Environmental Data Record products. This study comprehensively validated and inter-compared aerosol optical depth (AOD) and Ångstrom exponent (AE) over land and the ocean of these six products (seven different algorithms) on regional and global scales using AErosol RObotic NETwork (AERONET) and Maritime Aerosol Network (MAN) observations. In particular, we used AERONET inversions to classify AOD and AE biases into different scenarios (depending on absorption and particle size) to obtain retrieval error characteristics. The spatial patterns of the products and their differences were also analyzed. Collectively, although six satellite AODs are in good agreement with ground observations, VIIRS DB (land and ocean) and MODIS MAIAC (land only) AODs show better validation metrics globally and better performance in 8/10 world regions. Therefore, they are more recommended for usage. Although land AE retrievals are not capable of quantitative application at both instantaneous and monthly scales, their spatial patterns show qualitative potential. Ocean AE shows a relatively high correlation coefficient with ground measurements (>0.75), meeting the fraction of expected accuracy (> 0.70). Error characteristic analyses emphasize the importance of aerosol particle size and absorption-scattering properties for land retrieval, indicating that improving the representation of aerosol types is necessary. This study is expected to facilitate the usage selection of operating VIIRS and MODIS products and their algorithm improvements.

Variations and drivers of aerosol vertical characterization after clean air policy in China based on 7-years consecutive observations

Understanding the aerosol vertical characterization is of great importance to both climate and atmospheric environment. This study investigated the variations of aerosol profiles over eight regions of interest in China after clean air policy (2013-2019) and discussed the drivers of the vertical aerosol structure, using observations from active satellite measurements (CALIPSO). From the annual variation, the amplitude of extinction coefficient profiles showed a decreasing trend with fluctuations, and the maximum was 0.21 km^-1 in Beijing-Tianjin-Hebei (JJJ). For regions suffered from air pollution, the variation was greatest below 0.45 km, while it was between 1-1.5 km for Sichuan Basin. The correlation coefficient between the relative humidity (RH) and the extinction coefficient indicated that the increase of RH inhibited the decrease of the extinction coefficient in the Yangtze River Delta. In most regions, the main aerosol subtypes were polluted dust and polluted continental, but they were coarser in JJJ and North West. The frequency of concurrency of dust and polluted dust aerosols decreased in JJJ, but polluted continental aerosols occurred more frequently. Further, the aerosol extinction coefficient profiles under different pollution conditions showed that it changed most during heavy pollution periods in JJJ, especially in 2017, with a significant aerosol loading between ∼700 and 1200 m. The atmospheric reanalysis data revealed that the weak convergence at low level and the divergence at high level supported the upward transport of aerosols in 2017. Overall, the differences in divergence allocation, RH, and wind filed were the main meteorological drivers.

High spatiotemporal resolution estimation of AOD from Himawari-8 using an ensemble machine learning gap-filling method

The data incompleteness of aerosol optical depth (AOD) products and their lack of availability in highly urbanized areas limit their great potential of application in air quality research. In this study, we developed an ensemble machine-learning approach that integrated random forest-based Space Interpolation Model (SIM) and deep neural network-based Time Interpolation Model (TIM) to achieve high spatiotemporal resolution dataset of AOD. The spatial interpolation model first filled the spatial gaps in the Level-2 Himawari-8 hourly AOD product in 0.05° (∼5 km) spatial resolution, while the time interpolation model further improved the temporal resolution to 10 min on its basis. A full-coverage AOD dataset of Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) in 2020 was obtained as a practical implementation. The validation against in-situ AOD observations from AERONET and SONET indicated that this new dataset was satisfactory (R = 0.80), and especially in spring and summer. Overall, our ensemble machine-learning model provided an effective scheme for reconstruction of AOD with high spatiotemporal resolution of 0.05° and 10 min, which may further advance the near-real-time monitoring of air-quality in urban areas.

Seasonal cycles and long-term trends of arctic tropospheric aerosols based on CALIPSO lidar observations

Notable warming trends have been observed in the Arctic, with tropospheric aerosols being one of the key drivers. Here the seasonal cycles of three-dimensional (3D) distributions of aerosol extinction coefficients (AECs) and frequency of occurrences (FoOs) for different aerosol subtypes in the troposphere over the Arctic from 2007 to 2019 are characterized capitalizing on Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) Level-3 gridded aerosol profile product. Seasonal contributions of total and type-dependent aerosols through their partitioning within the planetary boundary layer (PBL) and free troposphere (FT) are also quantified utilizing the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) PBL height data. The results show substantial seasonal and geographical dependence in the distribution of aerosols over the Arctic. Sulfate, black carbon (BC), and organic carbon (OC) contribute most of the total AEC, with Eurasia being the largest contributor. The vertical structure of AECs and FoOs over the Arctic demonstrates that the vertical influence of aerosols is higher in eastern Siberia and North America than in northern Eurasia and its coasts. When the total aerosol optical depth (TAOD) is partitioned into the PBL and FT, results indicate that the contributions of TAOD within the FT tend to be more significant, especially in summer, with the FT contributes 64.2% and 69.2% of TAOD over the lower (i.e., 60° N-70° N) and high (i.e., north of 70° N) Arctic, respectively. Additionally, seasonal trend analyses suggest Arctic TAOD exhibits a multi-year negative trend in winter, spring, and autumn and a positive trend in summer during 2007-2019, due to an overall decrease in sulfate from weakened anthropogenic emissions and a significant increase in BC and OC from enhanced biomass burning activities. Overall, this study has potential implications for understanding the seasonal cycles and trends in Arctic aerosols.

Long-Term Variations in Global Solar Radiation and Its Interaction with Atmospheric Substances at Qomolangma

An empirical model to estimate global solar radiation was developed at Qomolangma Station using observed solar radiation and meteorological parameters. The predicted hourly global solar radiation agrees well with observations at the ground in 2008–2011. This model was used to calculate global solar radiation at the ground and its loss in the atmosphere due to absorbing and scattering substances in 2007–2020. A sensitivity analysis shows that the responses of global solar radiation to changes in water vapor and scattering factors (expressed as water-vapor pressure and the attenuation factor, AF, respectively) are nonlinear, and global solar radiation is more sensitive to changes in scattering than to changes in absorption. Further applying this empirical model, the albedos at the top of the atmosphere (TOA) and the surface in 2007–2020 were computed and are in line with satellite-based retrievals. During 2007–2020, the mean estimated annual global solar radiation increased by 0.22% per year, which was associated with a decrease in AF of 1.46% and an increase in water-vapor pressure of 0.37% per year. The annual mean air temperature increased by about 0.16 °C over the 14 years. Annual mean losses of solar radiation caused by absorbing and scattering substances and total loss were 2.55, 0.64, and 3.19 MJ m⁻², respectively. The annual average absorbing loss was much larger than the scattering loss; their contributions to the total loss were 77.23% and 22.77%, indicating that absorbing substances play significant roles. The annual absorbing loss increased by 0.42% per year, and scattering and total losses decreased by 2.00% and 0.14% per year, respectively. The estimated and satellite-derived annual albedos increased at the TOA and decreased at the surface. This study shows that solar radiation and its interactions with atmospheric absorbing and scattering substances have played key but different roles in regional climate and climate change at the three poles.

Assessment of CALIOP-Derived CCN Concentrations by In Situ Surface Measurements

The satellite-based cloud condensation nuclei (CCN) proxies used to quantify the aerosol-cloud interactions (ACIs) are column integrated and do not guarantee the vertical co-location of aerosols and clouds. This has encouraged the use of height-resolved measurements of spaceborne lidars for ACI studies and led to advancements in lidar-based CCN retrieval algorithms. In this study, we present a comparison between the number concentration of CCN (nCCN) derived from ground-based in situ and spaceborne lidar cloud-aerosol lidar with orthogonal polarization (CALIOP) measurements. On analysing their monthly time series, we found that about 88% of CALIOP nCCN estimates remained within a factor of 1.5 of the in situ measurements. Overall, the CALIOP estimates of monthly nCCN were in good agreement with the in situ measurements with a normalized mean error of 71%, normalized mean bias of 39% and correlation coefficient of 0.68. Based on our comparison results, we point out the necessary measures that should be considered for global nCCN retrieval. Our results show the competence of CALIOP in compiling a global height- and type-resolved nCCN dataset for use in ACI studies.

Dust Climatology of Turkey as a Part of the Eastern Mediterranean Basin via 9-Year CALIPSO-Derived Product

Turkey is located in the heart of complex transition geography between Eurasia and the Middle East. In the grand scheme, the so-called eastern Mediterranean Basin is located almost in the middle of the dusty belt, and is a hot spot of climate change. The downstream location of dust-carrying winds from close desert sources reveals Turkey as an open plane to particulate matter exposure throughout the year. In order to clarify this phenomenon, this paper aims to determine the desert dust climatology of Turkey via CALIPSO onboard Lidar. This prominent instrument enables us to understand clouds, aerosols and their types, and related climatic systems, with its valuable products. In this study, a 9-year CALIPSO-derived pure dust product dataset was formed to explain horizontal and vertical distributions, transport heights and case incidences. The results indicated that the pure dust extinction coefficient increased as the location shifted from west to east. Moreover, in the same direction of west to east, the dominant spring months changed to summer and autumn. Mountain range systems surrounding Anatolia were the main obstacles against lofted and buoyant dust particles travelling to northern latitudes. Even if high ridges accumulated mass load on the southern slopes, they also enabled elevated particles to reach the ground level of the inner cities.

Effect of Aerosol Vertical Distribution on the Modeling of Solar Radiation

Default aerosol extinction coefficient profiles are commonly used instead of measured profiles in radiative transfer modeling, increasing the uncertainties in the simulations. The present study aimed to determine the magnitude of these uncertainties and contribute towards the understanding of the complex interactions between aerosols and solar radiation. Default, artificial and measured profiles of the aerosol extinction coefficient were used to simulate the profiles of different radiometric quantities in the atmosphere for different surface, atmospheric, and aerosol properties and for four spectral bands: ultraviolet-B, ultraviolet-A, visible, and near-infrared. Case studies were performed over different areas in Europe and North Africa. Analysis of the results showed that under cloudless skies, changing the altitude of an artificial aerosol layer has minor impact on the levels of shortwave radiation at the top and bottom of the atmosphere, even for high aerosol loads. Differences of up to 30% were, however, detected for individual spectral bands. Using measured instead of default profiles for the simulations led to more significant differences in the atmosphere, which became very large during dust episodes (10–60% for actinic flux at altitudes between 1 and 2 km, and up to 15 K/day for heating rates depending on the site and solar elevation).

Long-term variations in aerosol optical properties, types, and radiative forcing in the Sichuan Basin, Southwest China

Long-term variations in aerosol optical properties, types, and radiative forcing over the Sichuan Basin (SCB) and surrounding regions in Southwest China were investigated based on two-decade data (2001-2020) from the Moderate Resolution Imaging Spectroradiometer, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation, and the Santa Barbara DISORT Atmospheric Radiative Transfer model. The results showed that the aerosol optical depth (AOD_550nm) in the SCB, a major polluted region in Southwest China, experienced an increasing tendency at a rate of +0.052 yr^-1 during 2001-2006; thereafter, it decreased speedy up from -0.020 to -0.058 yr^-1 over recent years, whereas the interannual variation in Ångström exponent (AE_470-660nm) presented a persistently increasing trend during 2001-2020, with a rate of +0.014 yr^-1. An improved atmospheric environment but an enhanced fine particle contribution to regional aerosols in the SCB was observed. Over the polluted SCB region, the dominant aerosol types were biomass burning/urban industrial and mixed-type aerosols with the proportions of 80.7%-87.5% in regional aerosols, with a higher frequency of clean aerosols in recent years, reflecting an effect of controlling anthropogenic emission in the SCB owing to governmental regulation. By contrast, few changes were observed in the aerosol types and amounts in the eastern Tibetan Plateau (ETP), where clean continental aerosols dominate with high proportion of 93.7% in the clean atmospheric environment. A significant decline in polluted anthropogenic aerosols was observed below 3 km over the SCB, resulting in the regional aerosol extinction coefficients at 532 nm (EC_532nm) were declined by -0.22 km^-1 from 2013 to 2020. Notably, the decreases in aerosol radiative forcing within the atmosphere were found in the SCB and the adjacent northern Yunnan-Guizhou Plateau (NYGP) and ETP, with -41.6%, -33.7%, and -13.6%, respectively during 2013-2020. This indicates that such an attenuated aerosol heating rate in the atmosphere, caused by aerosol variation, could alter the atmospheric thermal structure over the SCB and surrounding areas for regional changes of environment and climate in recent years.

Is the atmospheric boundary layer altitude or the strong thermal inversions that control the vertical extent of aerosols?

It is well known that the atmospheric boundary layer (ABL) plays a significant role in controlling the variability of atmospheric constituents such as aerosols and trace-gases. Hence, significant diurnal and seasonal variation in these will be observed as the ABL altitude does. However, on several occasions, high aerosol concentration in the lidar measurements is observed even above the ABL altitude. This raised a question that up to what extent ABL altitude acts as a capping layer for these pollutants? From the detailed analysis carried out using long-term (2010-2018) lidar observations and simultaneous radiosonde profiles obtained from Gadanki, India, we show that 'there exist thermal inversions (TI), which are stronger than the ABL inversions, that fully control the vertical extent'. The detailed characteristics of TI (inversion strength (IS) and inversion depth (ID)) are also obtained. The results revealed that aerosol concentrations below the TI altitude increases with IS (ID) up to 3-4 K (300-400 m) during winter whereas in pre-monsoon it increases up to 2-3 K (100-200 m). Thus, IS of up to 2-4 K is required to fully trap the aerosol concentrations and this TI coincide with the ABL inversions for 51.7% only, particularly during the winter and pre-monsoon seasons. This analysis is further extended to different geographical locations of India using the aerosol profiles obtained from CALIPSO and a network of 23 radiosonde stations. The observed results provided further evidence that the vertical distribution of aerosols is restricted to the maximum extent by the TI but not the ABL altitude. These observations lead us to propose a hypothesis that 'trapping of aerosols fully occurs up to particular IS and ID only and the ABL altitude is not the deciding factor most of the time for capping the aerosol vertical distribution'. These findings will greatly help in modeling the diffusion and transport of air pollutants in the lower troposphere.

Biomass Burning Over the United States East Coast and Western North Atlantic Ocean: Implications for Clouds and Air Quality

Biomass burning (BB) aerosol events were characterized over the U.S. East Coast and Bermuda over the western North Atlantic Ocean (WNAO) between 2005 and 2018 using a combination of ground-based observations, satellite data, and model outputs. Days with BB influence in an atmospheric column (BB days) were identified using criteria biased toward larger fire events based on anomalously high AERONET aerosol optical depth (AOD) and MERRA-2 black carbon (BC) column density. BB days are present year-round with more in June-August (JJA) over the northern part of the East Coast, in contrast to more frequent events in March-May (MAM) over the southeast U.S. and Bermuda. BB source regions in MAM are southern Mexico and by the Yucatan, Central America, and the southeast U.S. JJA source regions are western parts of North America. Less than half of the BB days coincide with anomalously high PM2.5 levels in the surface layer, according to data from 14 IMPROVE sites over the East Coast. Profiles of aerosol extinction suggest that BB particles can be found in the boundary layer and into the upper troposphere with the potential to interact with clouds. Higher cloud drop number concentration and lower drop effective radius are observed during BB days. In addition, lower liquid water path is found during these days, especially when BB particles are present in the boundary layer. While patterns are suggestive of cloud-BB aerosol interactions over the East Coast and the WNAO, additional studies are needed for confirmation.

Cloud drop number concentrations over the western North Atlantic Ocean: seasonal cycle, aerosol interrelationships, and other influential factors

Cloud drop number concentrations (N _d) over the western North Atlantic Ocean (WNAO) are generally highest during the winter (DJF) and lowest in summer (JJA), in contrast to aerosol proxy variables (aerosol optical depth, aerosol index, surface aerosol mass concentrations, surface cloud condensation nuclei (CCN) concentrations) that generally peak in spring (MAM) and JJA with minima in DJF. Using aircraft, satellite remote sensing, ground-based in situ measurement data, and reanalysis data, we characterize factors explaining the divergent seasonal cycles and furthermore probe into factors influencing N _d on seasonal timescales. The results can be summarized well by features most pronounced in DJF, including features associated with cold-air outbreak (CAO) conditions such as enhanced values of CAO index, planetary boundary layer height (PBLH), low-level liquid cloud fraction, and cloud-top height, in addition to winds aligned with continental outflow. Data sorted into high- and low-N _d days in each season, especially in DJF, revealed that all of these conditions were enhanced on the high-N _d days, including reduced sea level pressure and stronger wind speeds. Although aerosols may be more abundant in MAM and JJA, the conditions needed to activate those particles into cloud droplets are weaker than in colder months, which is demonstrated by calculations of the strongest (weakest) aerosol indirect effects in DJF (JJA) based on comparing N _d to perturbations in four different aerosol proxy variables (total and sulfate aerosol optical depth, aerosol index, surface mass concentration of sulfate). We used three machine learning models and up to 14 input variables to infer about most influential factors related to N _d for DJF and JJA, with the best performance obtained with gradient-boosted regression tree (GBRT) analysis. The model results indicated that cloud fraction was the most important input variable, followed by some combination (depending on season) of CAO index and surface mass concentrations of sulfate and organic carbon. Future work is recommended to further understand aspects uncovered here such as impacts of free tropospheric aerosol entrainment on clouds, degree of boundary layer coupling, wet scavenging, and giant CCN effects on aerosol-N _d relationships, updraft velocity, and vertical structure of cloud properties such as adiabaticity that impact the satellite estimation of N _d.

An Aerosol Climatology and Implications for Clouds at a Remote Marine Site: Case Study Over Bermuda

Aerosol characteristics and aerosol-cloud interactions remain uncertain in remote marine regions. We use over a decade of data (2000-2012) from the NASA AErosol RObotic NETwork, aerosol and wet deposition samples, satellite remote sensors, and models to examine aerosol and cloud droplet number characteristics at a representative open ocean site (Bermuda) over the Western North Atlantic Ocean (WNAO). Annual mean values were as follows: aerosol optical depth (AOD) = 0.12, Ångström Exponent (440/870 nm) = 0.95, fine mode fraction = 0.51, asymmetry factor = 0.72 (440 nm) and 0.68 (1020 nm), and Aqua-MODIS cloud droplet number concentrations = 51.3 cm-3. The winter season (December-February) was characterized by high sea salt optical thickness and the highest aerosol extinction in the lowest 2 km. Extensive precipitation over the WNAO in winter helps contribute to the low FMFs in winter (~0.40-0.50) even though air trajectories often originate over North America. Spring and summer had more pronounced influence from sulfate, dust, organic carbon, and black carbon. Volume size distributions were bimodal with a dominant coarse mode (effective radii: 1.85-2.09 μm) and less pronounced fine mode (0.14-0.16 μm), with variability in the coarse mode likely due to different characteristic sizes for transported dust (smaller) versus regional sea salt (larger). Extreme pollution events highlight the sensitivity of this site to long-range transport of urban emissions, dust, and smoke. Differing annual cycles are identified between AOD and cloud droplet number concentrations, motivating a deeper look into aerosol-cloud interactions at this site.

Global aerosol vertical structure analysis by clustering gridded CALIOP aerosol profiles with fuzzy k-means

Aerosol vertical structures are critical to understanding distribution and source-sink patterns of aerosol on a large scale. In this study, we carried out spatial clustering analysis for 10-years long CALIOP aerosol profiles with a fuzzy k-means (FKM) method. Raw and normalized data sets were both classified into three representative clusters. Raw aerosol profiles of original data described both aerosol density and structure patterns, which were classified into polluted cluster, medium cluster and clean cluster with visual inspection. The mean aerosol extinction coefficient values in near surface from large to small respectively belonged to polluted cluster, medium cluster and clean cluster. As altitude increased, mean aerosol extinction coefficients of polluted cluster were in rapid decline trend from surface to upper atmosphere. In comparison, there was a slower decrease speed for the aerosol extinction coefficient values of mean aerosol profiles of the other two clusters. Aerosol profiles clusters using normalized data could be used to describe aerosol vertical structure patterns. Normalized aerosol profiles were classified into boundary-layer concentrated cluster (boundary cluster), vertically even distributed cluster (v-even cluster) and surface-layer concentrated cluster (surface cluster). The boundary cluster was stable in the low atmosphere with a decline trend upwards, which was spatially corresponds to strong anthropogenic emission and dust regions. The mean normalized extinction coefficient values of v-even cluster were relatively stable in a large vertical range (about 4 km) at regions with relatively weak wind fields. The coefficients of surface cluster were mainly distributed in the near surface with mostly in coastlines and low aerosol optical depth (AOD) regions. The cluster analysis of CALIOP aerosol profiles provided general patterns for global distributions of aerosol profile density and structure.

An Overview of Atmospheric Features Over the Western North Atlantic Ocean and North American East Coast - Part 1: Analysis of Aerosols, Gases, and Wet Deposition Chemistry

The Western North Atlantic Ocean (WNAO) and adjoining East Coast of North America are of great importance for atmospheric research and have been extensively studied for several decades. This broad region exhibits complex meteorological features and a wide range of conditions associated with gas and particulate species from many sources regionally and other continents. As Part 1 of a 2-part paper series, this work characterizes quantities associated with atmospheric chemistry, including gases, aerosols, and wet deposition, by analyzing available satellite observations, ground-based data, model simulations, and reanalysis products. Part 2 provides insight into the atmospheric circulation, boundary layer variability, three-dimensional cloud structure, properties, and precipitation over the WNAO domain. Key results include spatial and seasonal differences in composition along the North American East Coast and over the WNAO associated with varying sources of smoke and dust and meteorological drivers such as temperature, moisture, and precipitation. Spatial and seasonal variations of tropospheric carbon monoxide and ozone highlight different pathways toward the accumulation of these species in the troposphere. Spatial distributions of speciated aerosol optical depth and vertical profiles of aerosol mass mixing ratios show a clear seasonal cycle highlighting the influence of different sources in addition to the impact of intercontinental transport. Analysis of long-term climate model simulations of aerosol species and satellite observations of carbon monoxide confirm that there has been a significant decline in recent decades among anthropogenic constituents owing to regulatory activities.

Dust Lidar Ratios Retrieved from the CALIOP Measurements Using the MODIS AOD as a Constraint

Lidar ratio for dust aerosols is retrieved from a synergetic use of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) Total Attenuated Backscatter coefficients and the Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depths (AODs) for 5 years from 2007 to 2011. MODIS AODs from the Dark Target (DT) algorithm over ocean and from the Deep Blue (DB) algorithm over land are used as a constraint for the retrieval. The dust lidar ratio is retrieved larger over land (46.6 ± 36.3 sr) than ocean (39.5 ± 16.8 sr) and shows distinct regional variation. Lidar ratio for Saharan dust (49.5 ± 36.8 sr) is larger than Arabian dust (42.5 ± 26.2 sr). Lidar ratios for dust aerosols transported to Mediterranean Sea (44.4 ± 15.9 sr), Mid Atlantic (40.3 ± 12.4 sr), and Arabian Sea (37.5 ± 12.1 sr) show lower values relative to their source regions. Retrieved dust lidar ratios for Taklamakan and Gobi Deserts region (35.0 ± 31.1 sr) and Australia (35.4 ± 34.4 sr) are slightly lower than the above-mentioned regions. AOD comparison between CALIOP and MODIS shows that the CALIOP AOD is biased low. When including clear air AOD for CALIOP, however, AODs from two sensors become more comparable.

Spring 2018 Asian Dust Events: Sources, Transportation, and Potential Biogeochemical Implications

The input of aeolian mineral dust to the oceans is regarded as the major source in supplying bioavailable iron for phytoplankton growth. Severe dust events swept over East Asia during the 26 March to the 4 April 2018, decreasing air quality to hazardous levels, with maximum PM10 mass concentrations above 3000 μg m−3 in northern China. Based on a comprehensive approach that combines multiple satellite measurements, ground observations, and model simulation, we revealed that two severe Asian dust events originating from the Taklimakan and Gobi deserts on 26 March and 1 April, were transported through northern China and the East/Japan Sea, to the North Pacific Ocean by westerly wind systems. Transportation pathways dominated by mineral dust aerosols were observed at altitudes of 2–7 km in the source regions, and then ascending to 3–10 km in the North Pacific Ocean, with relatively denser dust plumes within the second dust episode than there were during the first. Our results suggest that mineral dust emitted from the Taklimakan and Gobi deserts could increase ocean primary productivity in the North Pacific Ocean by up to ~50%, compared to average conditions. This emphasizes the potential importance of the deposition of Asian mineral dust over the North Pacific Ocean for enhancing the biological pump.

The CALIPSO Version 4 Automated Aerosol Classification and Lidar Ratio Selection Algorithm

The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) version 4.10 (V4) level 2 aerosol data products, released in November 2016, include substantial improvements to the aerosol subtyping and lidar ratio selection algorithms. These improvements are described along with resulting changes in aerosol optical depth (AOD). The most fundamental change in V4 level 2 aerosol products is a new algorithm to identify aerosol subtypes in the stratosphere. Four aerosol subtypes are introduced for the stratospheric aerosols: polar stratospheric aerosol (PSA), volcanic ash, sulfate/other, and smoke. The tropospheric aerosol subtyping algorithm was also improved by adding the following enhancements: (1) all aerosol subtypes are now allowed over polar regions, whereas the version 3 (V3) algorithm allowed only clean continental and polluted continental aerosols; (2) a new "dusty marine" aerosol subtype is introduced, representing mixtures of dust and marine aerosols near the ocean surface; and (3) the "polluted continental" and "smoke" subtypes have been renamed "polluted continental/smoke" and "elevated smoke", respectively. V4 also revises the lidar ratios for clean marine, dust, clean continental, and elevated smoke subtypes. As a consequence of the V4 updates, the mean 532 nm AOD retrieved by CALIOP has increased by 0.044 (0.036) or 52 % (40 %) for nighttime (daytime). Lidar ratio revisions are the most influential factor for AOD changes from V3 to V4, especially for cloud-free skies. Preliminary validation studies show that the AOD discrepancies between CALIOP and AERONET/MODIS (ocean) are reduced in V4 compared to V3.