AERONET Data Research Articles

Estimation of Aerosol Characteristics from Broadband Solar Radiation Measurements Carried Out in Southern Algeria

Aerosols in the atmosphere significantly reduce the solar radiation reaching the Earth’s surface through scattering and absorption processes. Knowing their properties becomes essential when we are interested in measuring solar radiation at a given location on the ground. The commonly used parameters that characterize their effects are the Aerosol Optical Depth τ, the Angstrom exponent α, and the Angstrom coefficient β. One method for estimating these parameters is to fit ground-based measurements of clear-sky direct solar radiation using a model on which it depends. However, the choice of model depends on its suitability to the atmospheric conditions of the site considered. Eleven empirical solar radiation models depending on α and β were thus chosen and tested with solar radiation measurements recorded between 2005 and 2014 in Tamanrasset in southern Algeria. The results obtained were compared to measurements made with the AERONET solar photometer on the same site during the same period. Among the 11 models chosen, the best performing ones are REST2 and CPCR2. They proved to be the best suited to estimate β with approximately the same RMSE of 0.05 and a correlation coefficient R with respect to AERONET of 0.95. The results also highlighted good performances of these models for the estimation of τ with an RMSE of 0.05 and 0.04, and an R of 0.95 and 0.96, respectively. The values of α obtained from the fitting of these models were, however, less good, with R around 0.38. Additional treatments based on a Recurrent Neural Network (RNN) were necessary to improve its estimation. They provided promising results showing a significant improvement in α estimates with R reaching 0.7 when referring to AERONET data. Furthermore, this parameter made it possible to identify different types of aerosols in Tamanrasset such as the presence of maritime, dust, and mixed aerosols representing, respectively, 31.21%, 3.25%, and 65.54%, proportions calculated over the entire period studied. The seasonal analysis showed that maritime aerosols are predominant in the winter in Tamanrasset but decrease with the seasons to reach a minimum in the summer (JJA). Dust aerosols appear in February and persist mainly in the spring (MAM) and summer (JJA), then disappear in September. These results are also consistent with those obtained from AERONET.

Estimation and model performance of aerosol radiative forcing from Radiative Transfer models using the AERONET data over Kenya, East Africa

The rapid economic growth and a lack of strict implementation of air quality regulations have led to unqualified effects on health, the environment, and the climate. In recent years, there has been an urgent need for the increased characterization of aerosols in terms of optical, micro-physical, and radiative properties and their climatic impacts. In the present study, the aerosol-climate implications were evaluated by aerosol radiative forcing (ARF) at three environmentally specific sites, Malindi (3° S, 40.2° E, 12 m asl), Mbita (0.42° S, 34.20° E, 1125 m asl), and Nairobi (1.0° S, 36.0° E, 1650 m asl), located in Kenya. The aerosol optical properties such as aerosol optical depth (AOD440), single scattering albedo (SSA440), asymmetric parameter (ASY440), and Ångström exponent (AE440-870) showed significant annual and seasonal heterogeneities. They noticed high (low) values during the local dry (wet) seasons, attributed to changes in anthropogenic activities, emission sources, and prevailing dynamics played by the meteorology. The study also utilized measured spectral aerosol optical properties and two radiative transfer models in the short-wave (SW) and long-wave (LW) regions with their respective spectral bands (0.2–4.0 µm) and (4.0–100.0 µm) during 2007–2018. The direct ARF simulated in the SW using the Santa Barbara DISORT Atmospheric Radiative Transfer Model (SBDART) and the Coupled Ocean and Atmospheric Radiative Transfer models (COART) depicted high correspondence, evidenced by relatively high (r > 0.64) correlations over the three sites. The ARF simulated by the two models in the SW and LW regions exhibited significant seasonal heterogeneity, with maximum (minimum) values observed during the local dry (wet) seasons. The results from the present study could form a basis for other climate change studies and increase the accuracy of the existing climate models to enhance climate forecasting over the East Africa region.

Long-Term Evaluation of Aerosol Optical Properties in the Levantine Region: A Comparative Analysis of AERONET and Aqua/MODIS

The focus on aerosol analysis in the Levantine Region is driven by climate-change impacts, the region’s increasing urban development and industrial activities, and its geographical proximity to major dust-source areas. This study conducts a comparative analysis of aerosol optical depth data from Aqua/MODIS and AERONET during different periods between 2003 and 2023 at four stations: IMS-METU-ERDEMLI (Mersin/Türkiye) (2004–2019), CUT-TEPAK (Limassol/Cyprus) (2010–2023), Cairo_EMA_2 (Cairo/Egypt) (2010–2023), and SEDE_BOKER (Sede Boker/Israel) (2003–2023). The objective is to evaluate the variability and reliability of AOD measurements between satellite and ground-based observations and to determine how well they represent regional climatology. The highest percentage of measurements within the expected error envelope was observed at the IMS-METU-ERDEMLI station, indicating the best agreement between MODIS and AERONET data at this location. The Seasonal-Trend Decomposition using Loess (STL) method revealed consistent spring and summer peaks influenced by dust transport from the Sahara and the Middle East, with lower values in winter. The study also considers the influence of cloud fraction on MODIS measurements and includes aerosol classification. A statistically significant slight positive trend in AOD values was identified at the IMS-METU-ERDEMLI station. Conversely, no significant trends were detected at the other stations. The results of this study agree with those of previous research on the impact of long-range dust transport on regional aerosol loadings, emphasizing the importance of integrating satellite and ground-based observations.

Aerosols and black carbon variability using OMI and MERRA-2 and their relationship to near-surface air temperature.

An extinction of incoming solar radiation is taking place by absorption and scattering by dust, water droplets, and gaseous molecules. Such phenomena are responsible for altering meteorological variables. In the present study, temporal analysis of the aerosol optical thickness (AOT) and black carbon (BC) surface mass concentration was undertaken using an ozone monitoring instrument (OMI) and modern-era retrospective analysis for research and applications, version 2 (MERRA-2) satellite from the year 2018 to 2022. The study was mainly focused on the western states of India which are Rajasthan, Gujarat, and Maharashtra. The correlation of AOT and BC surface mass concentration with near-surface temperature (2m above ground level) was analyzed. BC and temperature shows strong negative correlation as BC is known for its absorption of radiation. It accumulates in the atmosphere and contributes to atmospheric warming while simultaneously bringing down the near-surface air temperature due to the reduced sunlight reaching the ground. Also, seasonal analysis was conducted for winter, summer, monsoon, and post-monsoon, which shows the higher values of AOT in monsoon; however, seasonal average BC surface mass concentration was found high in winter in each year for all three states. AERONET data from Jaipur, Rajasthan, and Pune, Maharashtra for the year 2021 was used to further evaluate the AOT generated from OMI. The results demonstrated a significant connection, with R2 values of 0.62 and 0.69, respectively. The temperature retrieved from MERRA-2 was also validated with ground truth data of the Continuous Ambient Air Quality Monitoring Station (CAAQMS) at both stations showing high agreement with R2 > 0.70.

Remote sensing of eruptions and transport of Taal volcano in January 2020

The eruption and transport of the Taal volcano (14 N, 121 E) in January 2020 have been investigated using remote sensing measurements of several satellites, including the Moderate Resolution Imaging Spectroradiometer, Ozone Monitoring Instrument (OMI), Ozone Mapping and Profiler Suite, and Himawari-8. The aerosol optical thickness (AOT), angstrom exponent (AE), and column densities of sulfur dioxide (SO2) derived from satellites are analyzed in this study. The ground-based AERONET data of Manila city and OMI SO2 are studied to validate high AOT events. Our findings indicate that ash and gases followed opposite transport paths. This differential transport is consistent with various wind data, HYSPLIT back and forward trajectory calculations, and emission dispersion models. The potential influences of deposition on ocean biology and climate are also discussed.

Analyzing the influence of the planetary boundary layer height, ventilation coefficient, thermal inversions, and aerosol optical Depth on the concentration of PM2.5 in the city of São Paulo: A long-term study

Cases of intense air pollution have been a recurring problem in most of urban centers in different regions of the world. Although actions to mitigate pollutant emissions are fundamental, it is also necessary to understand which factors can favor their dispersion process. In this scenario, this paper presents, for the first time, a long-term analysis of the Planetary Boundary Layer Height (PBLH), estimated through lidar and radiosounding data, Ventilation Coefficient (VC), Thermal Inversions (TI), and Aerosol Optical Depth (AOD), for the city of São Paulo, demonstrating how these variables are related with PM2.5 concentration. The analyzes showed that PBLH and VC have a seasonal cycle, with higher values in summer and lower ones in winter. Furthermore, PBLH is affected by one local factor, the sea-breeze, which reduces the concentration of aerosols in the late afternoon, resulting in an underestimated PBLH obtained from lidar data. Furthermore, from AERONET data, a predominance of Black Carbon and small particles was observed in all seasons, which are associated with the feedback effect observed in winter. Such effect attenuates the increase of PBLH and VC in cases of high concentrations of PM2.5. Finally, it was presented a Generalized Linear Model, which combines VC, AOD and TI information as input and can estimate the PM2.5 concentration with a R2 = 0.93.

Characteristics and optical properties of atmospheric aerosols based on long-term AERONET investigations in an urban environment of Pakistan

Radiative balance, local climate, and human health are all significantly influenced by aerosol. Recent severe air pollution over Lahore, a city in Pakistan calls for more thorough research to determine the negative impacts brought on by too many aerosols. To study regional aerosol characteristics and their differences from various aspects, in-depth and long-term (2007–2020) investigations of the columnar aerosol properties over the urban environment of Lahore were carried out by using AERONET data. The Aerosol Optical Depth (AOD400) and Angstrom Exponent (AE400–870) vary from low values of 0.10 to a maximum value of 4.51 and from 0.03 to 1.81, respectively. The huge differences in the amount of AOD440 as well as AE440–870 show the large fluctuation of aerosol classes because of various sources of their emission. During the autumn and winter seasons, the decreasing trend of the optical parameters of aerosols like Single Scattering Albedo (SSA) and Asymmetry Parameter (ASY) with increasing wavelength from 675 to 1020 nm indicates the dominance of light-absorbing aerosols (biomass burning (BB) and industrial/urban (UI). Due to the long-distance dust movement during spring, summer, and autumn, coarse mode particles predominated in Lahore during the study period. Dust type (DD) aerosols are found to be the dominant one during spring (46.92%), summer (54.31%), and autumn (57.46%) while urban industry (BB/UI) was dominant during the winter season (53.21%). During each season, the clean continental (CC) aerosols are found to be in negligible amounts, indicating terrible air quality in Lahore City. The present research work fills up the study gap in the optical properties of aerosols in Lahore and will help us understand more fully how local aerosol fluctuation affects regional climate change over the urban environment of Lahore.

Comparative Study of Aerosol Optical Properties along a Megacity

Interest in the study and characterization of aerosols has been growing given its multiple connections with air quality and climate. However, the limited ground-based stations for measurements in many countries are not enough to completely study a big city or a region. Low-cost technology arises as a viable alternative to improve the spatial resolution of measurements. This study aims to demonstrate that the properties of aerosols may change within a megacity and that is advisable to segment measurements according to their characteristics. We measured the optical properties of aerosols in the outskirts of Buenos Aires and compared the data obtained with AERONET data from the city center. This is the first study of its kind in the region. The comparison of concentration, sizes, and types of aerosols shows differences between the sites regardless of the background levels that they share regionally. While the city center has a strong influence from traffic and sea particles and levels of pollution typical of a dense city, the outskirts present several aerosol sources and characteristics of a semi-rural site with a moderate influence of anthropogenic sources.

Precipitable water characterization using global navigation satellite system data: A case study in Nghia Do area, Vietnam

This paper evaluates the estimated total precipitable water (TPW) and studies its characteristics in the Nghia Do area (Hanoi) using Global Positioning System (GPS) data and the Canadian Spatial Reference System-Precise Point Positioning (CSRS-PPP) processing technique and calculation tool. The TPW was estimated from GPS data from September 22, 2022 to March 31, 2023 using CSRS-PPP provided by Natural Resources Canada. The calculated TPW was validated with TPW products from Aeronet data and radiosonde data. Taking advantage of its high time resolution, the TPW estimated from GPS data was used to analyze the temporal variation of TPW during cold surges affecting the Nghia Do area. The results indicate a strong agreement between the estimated TPW from GPS data and TPW products derived from Aeronet and radiosonde data. The mean error (ME), root mean square error (RMSE), and correlation coefficient between the estimated TPW from GPS data and the Aeronet-derived product are 0.68 mm, 2.05 mm, and 0.988, respectively. The corresponding values between the estimated TPW and the radiosonde-derived product are -3.01 mm, 3.24 mm, and 0.996, respectively. The study of TPW variation over the Nghia Do area during the research period revealed that, generally, TPW values in December and January were lower than those in the other months. Before the arrival of a specific cold surge at a station, TPW tends to increase by about 6 mm within 12 hours as convection activities ahead of the cold front intensify. After the cold air passes over the station, the TPW value decreases by about 8 mm within 12 hours due to the influx of cold and dry winter air brought by the prevailing winds. This distinct TPW variation pattern suggests that GPS data can be effectively employed to define the arrival of cold surges in the station area.

Measurement report: Assessing the impacts of emission uncertainty on aerosol optical properties and radiative forcing from biomass burning in peninsular Southeast Asia

Abstract. Despite significant advancements in improving the dataset for biomass burning (BB) emissions over the past few decades, uncertainties persist in BB aerosol emissions, impeding the accurate assessment of simulated aerosol optical properties (AOPs) and direct radiative forcing (DRF) during wildfire events in global and regional models. This study assessed AOPs (including aerosol optical depth (AOD), aerosol absorption optical depth (AAOD), and aerosol extinction coefficients (AECs)) and DRF using eight independent BB emission inventories applied to the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) during the BB period (March 2019) in peninsular Southeast Asia (PSEA), where the eight BB emission inventories were the Global Fire Emissions Database version 4.1s (GFED), Fire INventory from NCAR version 1.5 (FINN1.5), the Fire Inventory from NCAR version 2.5 MOS (MODIS fire detections; FINN2.5 MOS), the Fire Inventory from NCAR version 2.5 MOSVIS (MODIS + VIIRS fire detections; FINN2.5 MOSVIS), Global Fire Assimilation System version 1.2s (GFAS), Fire Energetics and Emissions Research version 1.0 (FEER), Quick Fire Emissions Dataset version 2.5 release 1 (QFED), and Integrated Monitoring and Modelling System for Wildland FIRES project version 2.0 (IS4FIRES), respectively. The results show that in the PSEA region, organic carbon (OC) emissions in the eight BB emission inventories differ by a factor of about 9 (0.295–2.533 Tg M−1), with 1.09 ± 0.83 Tg M−1 and a coefficient of variation (CV) of 76 %. High-concentration OC emissions occurred primarily in savanna and agricultural fires. The OC emissions from the GFED and GFAS are significantly lower than the other inventories. The OC emissions in FINN2.5 MOSVIS are approximately twice as high as those in FINN1.5. Sensitivity analysis of AOD simulated by WRF-Chem to different BB emission datasets indicated that the FINN scenarios (v1.5 and 2.5) significantly overestimate AOD compared to observation (VIIRS), while the other inventories underestimate AOD in the high-AOD (HAOD; AOD > 1) regions range from 15–22.5∘ N, 97–110∘ E. Among the eight schemes, IS4FIRES and FINN1.5 performed better in terms of AOD simulation consistency and bias in the HAOD region when compared to AERONET sites. The AAOD in WRF-Chem during the PSEA wildfire period was assessed, using satellite observations (TROPOMI) and AERONET data, and it was found that the AAOD simulated with different BB schemes did not perform as well as the AOD. The significant overestimation of AAOD by FINN (v1.5 and 2.5), FEER, and IS4FIRES schemes in the HAOD region, with the largest overestimation for FINN2.5 MOSVIS. FINN1.5 schemes performed better in representing AAOD at AERONET sites within the HAOD region. The simulated AOD and AAOD from FINN2.5 MOSVIS always show the best correlation with the observations. AECs simulated by WRF-Chem with all the eight BB schemes trends were consistent with CALIPSO in the vertical direction (0.5 to 4 km), demonstrating the efficacy of the smoke plume rise model used in WRF-Chem to simulate smoke plume heights. However, the FINN (v1.5 and 2.5) schemes overestimated AECs, while the other schemes underestimated it. In the HAOD region, BB aerosols exhibited a daytime shortwave radiative forcing of −32.60 ± 24.50 W m−2 at the surface, positive forcing (1.70 ± 1.40 W m−2) in the atmosphere, and negative forcing (−30.89 ± 23.6 W m−2) at the top of the atmosphere. Based on the analysis, FINN1.5 and IS4FIRES are recommended for accurately assessing the impact of BB on air quality and climate in the PSEA region.

Simulation and evaluation study of atmospheric aerosol nonsphericity as a function of particle size

Aerosol nonsphericity causes great uncertainty in radiative forcing assessments and climate simulations. Although considerable studies have attempted to quantify this uncertainty, the relationship between aerosol nonsphericity and particle size is usually not considered, thus reducing the accuracy of the results. In this study, a coupled inversion algorithm combining an improved stochastic particle swarm optimization algorithm and angular light scattering is used for the nonparametric estimation of aerosol nonsphericity variation with particle size, and the optimal sample selection method is employed to screen the data. Based on the verification of inversion accuracy, the variation of aerosol aspect ratio with particle size based on the ellipsoidal model in global regions has been obtained from Aerosol Robotic Network (AERONET) data, and the effect of nonsphericity on radiative forcing and dry deposition has been studied. The results show that the aspect ratio increases with particle size in all regions, with the maximum ranging from 1.4 to 1.8 in the desert, reflecting the differences in aerosol composition at different particle sizes. In radiation calculations, considering aerosol nonsphericity makes the aerosol cooling effect weaker and surface radiative fluxes increase, but hardly changes the aerosol absorption, with maximum differences of 9.22% and 22.12% at the bottom and top of the atmosphere, respectively. Meanwhile, the differences in radiative forcing between aspect ratios as a function of particle size and not varying with particle size are not significant, averaging less than 2%. Besides, the aspect ratio not varying with particle size underestimates the deposition velocity of small particles and overestimates that of large particles compared to that as a function of particle size, with maximum differences of 7% and 4%, respectively.

Frequency of occurrence of atmospheric parameters according to AERONET data in Dushanbe

Frequency of occurrence of atmospheric parameters according to AERONET data in Dushanbe

Multi-faceted analysis of dust storm from satellite imagery, ground station, and model simulations, a study in China

An intense dust storm from 8 April to 11 April 2023 originated from the Gobi deserts bordering Mongolia and Inner Mongolia of China and affected most parts of northern, central, and eastern China, the Korean Peninsula, and Japan. It has a significant impact on air quality in these regions and alters the optical and microphysical properties of the aerosols. In this work, a comprehensive analysis of the storm was carried out by using reanalysis data, model simulation, satellite, and ground-based observations. The geopotential height along with the wind flow reveals that the development, transportation, and dissipation of the dust storms were closely related to the movement of the Mongolia cyclones caused by Mongolia low and its surrounding highs. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data showed a two-layer dust vertical distribution, with the bottom one below 5 km and the upper one stretching from 5 to 10 km over the Japan Sea. The Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) backward trajectory uncovered Central Mongolia being the origin of the dust storm that arrived over the Japan Sea on April 9, 2022, and the forward trajectory revealed that the dust aerosols would be further transported to the Pacific Ocean. Air quality analysis demonstrated that the regions of inner Mongolia (IMG) and Jing-Jin-Ji (JJJ) suffered the most from the dust storm events, followed by the Yangtze River Delta (YRD), while the Pearl River Delta (PRD) was hardly affected, as indicated by the regional-averaged PM10 and PM2.5. It was also found that the dust storm event has almost no significant influence on the other air quality indicators including CO, NO2, O3, and SO2. Historical record tracking revealed that the springtime averaged PM10 and PM2.5 of the year 2023 are comparable to those in 2021 which has the record-breaking dust storm case. AERONET data indicated dramatic increments of aerosol optical depth at 550 nm (AOD550) and effective radius of total size (ReffT) in regions of Gobi and JJJ, accompanied by low Angstrom Exponent (AE), and high SSA870 values, while in the regions of Korea and Japan, minor increments of AOD550 and ReffT were found. This study provides a holistic scientific view of the dust storm which could aid in the implementation of protective measures against dust storms.

An intercomparison of SEMARA high-resolution AOD and MODIS operational AODs

SEMARA is a high-resolution aerosol optical depth (AOD) retrieval algorithm that incorporates two algorithms, Simplified and Robust Surface Reflectance Estimation Method (SREM) for estimating surface reflectance and the Simplified Aerosol Retrieval Algorithm (SARA) for retrieving AOD. This study used SEMARA approach for retrieving AOD utilizing data obtained from Aqua-MODIS in the green channel. The algorithm had good agreement with AERONET data (R = 0.98). Also it was analyzed over a wide area containing five provinces in Iran. SEMARA AOD retrievals were compared with the operational MODIS aerosol retrieval algorithms, including Dark Target (DT), Deep Blue (DB), and Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOD retrievals over different land covers and low to high aerosol loadings. The results show high consistency in SEMARA AOD retrievals with MAIAC AOD retrievals, with an average correlation coefficient of 0.61, while the correlation coefficient with DB and DT was 0.50 and 0.29, respectively. During high AOD loadings and over bright surfaces, the best agreement of SEMARA AOD and DT, DB, and MAIAC AOD was achieved with correlation coefficients of 0.52, 0.75, and 0.80, respectively. SEMARA AOD shows the best spatial coverage, averaging 80%, while MAIAC, DB, and DT had 54%, 32%, and 12% spatial coverage, respectively. This study concluded that SEMARA AOD can retrieve AOD over various land covers and during low to high AOD loadings with acceptable results.

An analysis of air pollution associated with the 2023 sand and dust storms over China: Aerosol properties and PM10 variability

Every spring, a large part of China is confronted with sand and dust storms (SDS) – mainly originating in the Gobi (including Chinese and Mongolian Gobi) and Taklamakan deserts. In March-April 2023, most of northern, northwestern and northeastern China was struck by three sandstorms that affected an area with more than 500 million people. In this study, aerosol optical, microphysical and radiative properties were studied during these SDS events using an integrated approach that combines satellite, terrestrial and re-analysis data. The results showed that dusty conditions were observed in most areas north of the Yangtze River (Chang Jiang) with daily average PM10 concentrations exceeding 1000 µg/m3 in many cities. VIIRS aerosol optical depth (AOD) at 550 nm during three SDS events exceeded a value of 1 throughout nearly the entire northern part of the country. The AERONET data obtained from the AOE_Baotou site showed a significant increase in total AOD and a corresponding decrease in AE during the SDS. The single scattering albedo (SSA), asymmetry parameter (ASY), real refractive index (RRI) and imaginary refractive index (IRI) values indicate an abundance of scattering coarse-mode particles. Aerosol radiative forcing (ARF) at top of the atmosphere and at the earth's surface was nearly always negative during the period and ranged from −48.5 to +2.7 Wm−2 and from −180.8 to −66.6 Wm−2, resulting in high positive ARF values at ATM (from +63.8 to +132.3 Wm−2). Each of these affects the heating of the atmosphere and cooling on the earth's surface. The atmospheric heating rates ranged from 1.8 to 3.7 K day−1. The formation of these SDS mainly resulted from the passage of cold fronts associated with low pressure systems in the Gobi and Taklamakan deserts, creating conditions for dust to rise into the atmosphere and move further downwind.

Radiative forcing bias calculation based on COSMO (Core-Shell Mie model Optimization) and AERONET data

Direct radiative forcing (DRF) of aerosols is driven by aerosol concentration, size, and mixing state, and solar radiation. This work introduces Core-Shell Mie model optimization (COSMO) to compute top of the atmosphere (TOA) forcing based on inversely constrained black carbon (BC) size and mixing state from AERONET, over two rapidly developing areas: Lumbini and Taihu. COSMO has both, a less negative TOA than AERONET and a wider range of variability, with the mean and standard deviation difference between COSMO and AERONET being 13 ± 8.1 W m−2 at Lumbini and 16 ± 12 W m−2 at Taihu. These differences are driven by particle aging and size-resolved BC emissions, with up to 17.9% of cases warmer than the maximum AERONET TOA, and 1.9% of the total possible cases show a net-warming at TOA (TOA > 0). A linearized correction is deduced which can be immediately implemented by climate models, and suggested ranges of BC size and mixing observations are made for future campaigns. Given that the COSMO TOA bias and uncertainty are larger than the forcing of locally emitted GHGs, active consideration of BC is necessary to reduce climate uncertainty in developing areas.

Collaborative development of the Lidar Processing Pipeline (LPP) for retrievals of atmospheric aerosols and clouds

Abstract. Atmospheric lidars can simultaneously measure clouds and aerosols with high temporal and spatial resolution and hence help understand cloud–aerosol interactions, which are the source of major uncertainties in future climate projections. However, atmospheric lidars are typically custom-built, with significant differences between them. In this sense, lidar networks play a crucial role as they coordinate the efforts of different groups, provide guidelines for quality-assured routine measurements and opportunities for side-by-side instrument comparisons, and enforce algorithm validation, all aiming to homogenize the physical retrievals from heterogeneous instruments in a network. Here we provide a high-level overview of the Lidar Processing Pipeline (LPP), an ongoing, collaborative, and open-source coordinated effort in Latin America. The LPP is a collection of tools with the ultimate goal of handling all the steps of a typical analysis of lidar measurements. The modular and configurable framework is generic enough to be applicable to any lidar instrument. The first publicly released version of the LPP produces data files at levels 0 (raw and metadata), 1 (averaging and layer mask), and 2 (aerosol optical properties). We assess the performance of the LPP through quantitative and qualitative analyses of simulated and measured elastic lidar signals. For noiseless synthetic 532 nm elastic signals with a constant lidar ratio (LR), the root mean square error (RMSE) in aerosol extinction within the boundary layer is about 0.1 %. In contrast, retrievals of aerosol backscatter from noisy elastic signals with a variable LR have an RMSE of 11 %, mostly due to assuming a constant LR in the inversion. The application of the LPP for measurements in São Paulo, further constrained by co-located AERONET data, retrieved a lidar ratio of 69.9 ± 5.2 sr at 532 nm, in agreement with reported values for urban aerosols. Over the Amazon, analysis of a 6 km thick multi-layer cirrus found a cloud optical depth of about 0.46, also in agreement with previous studies. From this exercise, we identify the need for new features and discuss a roadmap to guide future development, accommodating the needs of our community.

The (mis)identification of high-latitude dust events using remote sensing methods in the Yukon, Canada: a sub-daily variability analysis

Abstract. The observation and quantification of mineral dust fluxes from high-latitude sources remains difficult due to a known paucity of year-round in situ observations and known limitations of satellite remote sensing data (e.g. cloud cover and dust detection). Here we explore the chronology of dust emissions at a known and instrumented high-latitude dust source: Lhù'ààn Mân (Kluane Lake) in Yukon, Canada. At this location we use oblique time-lapse (RC) cameras as a baseline for analysis of aerosol retrievals from in situ metrological data, AERONET, and co-incident MODIS MAIAC to (i) investigate the daily to annual chronology of dust emissions recorded by these instrumental and remote sensing methods (at timescales ranging from minutes to years) and (ii) use data intercomparisons to comment on the principal factors that control the detection of dust in each case. Lhù'ààn Mân is a prolific mineral dust source; on 24 May 2018 the RC captured dust in motion throughout the entire day, with the longest dust-free period lasting only 30 min. When compared with time series of RC data, optimized AERONET data only manage an overall 26 % detection rate for events (sub-day) but 100 % detection rate for dust event days (DEDs) when dust was within the field of view. In this instance, RC and remote sensing data were able to suggest that the low event detection rate was attributed to fundamental variations in dust advection trajectory, dust plume height, and inherent restrictions in sun angle at high latitudes. Working with a time series of optimized aerosol optical depth (AOD) data (covering 2018/2019), we were able to investigate the gross impacts of data quality (DQ) choice on DED detection at the month or year scale. Relative to ground observations, AERONET's DQ2.0 cloud-screening algorithm may remove as much as 97 % of known dust events (3 % detection). Finally, when undertaking an AOD comparison for DED and non-DED retrievals, we find that cloud screening of MODIS/AERONET lead to a combined low sample of co-incident dust events and weak correlations between retrievals. Our results quantify and explain the extent of under-representation of dust in both ground and space remote sensing methods; this is a factor that impacts on the effective calibration and validation of global climate and dust models.

The extreme forest fires in California/Oregon in 2020: Aerosol optical and physical properties and comparisons of aged versus fresh smoke

Wildfire activity in the western United States during August to October 2020 was exceptional in terms of the fire severity and area burned. Extremely dry biomass fuels from near historic multi-year drought conditions were further exacerbated with very hot and dry conditions in 2020. These conditions when coupled with strong offshore flow allowed many ignitions to grow into extremely large and severe wildfires. Long-term monitoring at a few AERONET sites in California showed that the number of days with high Aerosol Optical Depth at 440 nm (AOD440>1) in 2020 was greater than any other year going back to the beginning of the data records in 2002. A wide range of fine mode particle volume median radii were retrieved from AERONET data over the course of these fires suggesting significant variability in combustion conditions and aging processes. Additionally, the fine mode radii in some of these smoke plumes in 2020 were very large especially at high AOD (∼0.22–0.32 μm volume median radius), likely due to both coagulation and condensation occurring during aging at very high particulate concentrations. The largest fine mode particle radii combined with narrow distributions resulted in some very rare AOD spectra showing peak AOD at 500 nm and decreasing to lower AOD at both shorter and longer wavelengths. The most extreme retrieved size distributions and associated measured AOD spectra were principally observed in long-distance transported smoke plumes from these western United States fires at sites in Colorado, Maryland and Virginia, possibly due to further aging during transport. Additionally, strong absorption was sometimes observed at short wavelengths with much lower single scattering albedo at 440 nm compared to 675 nm in some plumes consistent with significant brown carbon (BrC) and/or coated black carbon (BC) absorption in biomass burning particles. This strong spectral absorption signature observed at some California sites and dates remained similarly strong in some smoke plumes observed at some east coast sites in Maryland and Virginia, thereby suggesting that the lifetime of these particular BrC and/or coated BC absorbing species was greater than 5 days.

Variations in aerosol optical characteristics from SKYNET measurements in Beijing

Atmospheric aerosols have significant impacts on climate and environment, so the study on aerosol optical properties is of great scientific significance for climate change and atmospheric environment. The variations in column-integrated aerosol optical properties over Beijing were investigated from March 2016 to December 2019 based on the SKYNET data products. Higher values of AOD and AE found in summer indicate that it is important to pay more attention to fine particle pollution in summer. By fitting the AOD data of SKYNET with AERONET at same waveband, we found that monthly variations in aerosol optical depth estimated from SKYNET observation were mostly consistent with the AERONET data. Aerosols were divided into several modes according to optical characteristics, which deepen some insight into aerosol optical and radiative properties and revealed that the weak absorption aerosol dominated and contributed much to the radiation transport in Beijing. Data derived from the polarization lidar CALIPSO were combined with aerosol optical depth (AOD) from SKYNET and these results were consistent, which further identified the scientific of data. The random forest algorithm was used to interpolate the missing AOD500nm observations. The original results and the interpolation results were fitted with MODIS respectively, which proved that the random forest algorithm can supplement the missing results well. This work will be of great significance in addressing the impacts of aerosols on climate and environment, and will help reduce the uncertainty of the impacts of aerosols on the Earth's radiation budget. All work will provide scientific support for the prevention and control of specific pollution.