Single-scattering Albedo Research Articles

New Polarimetric Data for the Galilean Satellites: Io and Ganymede Observations and Modeling

New high-precision disk-integrated measurements of the polarization of Io and Ganymede in the UBVRI bands are presented. The observations were obtained using polarimeters mounted on the Crimean Astrophysical Observatory and the Peak Terskol Observatory in 2019–2023. For Io, the negative polarization branch (NPB) reaches a minimum of P min ≈ −0.25 ± 0.02% in the V band at a phase angle of α min = 2.°1 ± 0.°5. The inversion angle is α inv = 26° ± 6° in the V and R bands. The NPB for Ganymede is an asymmetric curve, with P min = −0.34 ± 0.01% at α min = 0.°52 ± 0.°06 and α inv = 8.°5 ± 0.°2 in the V band. Although Io and Europa have similar geometric albedos (0.63 and 0.67, respectively), their NPB shapes differ. The NPB of Ganymede (albedo of 0.43) is morphologically similar to that of Europa, although it is described by different parameter values (P min, α min, and α inv). This discrepancy is likely due to the compositions of their surfaces: Europa’s with H2O ice, Io’s with sulfuric/silicate composition, and Ganymede’s with H2O ice and silicates. Numerical computations using the radiative transfer coherent backscattering method demonstrated a match to the polarimetric observations and to the geometric albedos for Ganymede with the single-scattering albedo ≈ 0.943 and mean free path length kl = 2πl/λ eff ≈ 150, where λ eff is the wavelength. For Io’s regolith, the single-scattering albedo was found to be ≈ 0.979 and kl ≈ 40.

Aerosol classification by application of machine learning spectral clustering algorithm

Precise understanding of aerosol classification is crucial for accurately quantifying the effects of aerosols on the Earth’s energy budget, improving remote sensing retrieval algorithms, formulating climate change-related policies, and more. In this study, we used aerosol measurements from the quality assured AERosol Robotic NETwork (AERONET) and utilized a multivariate spectral clustering algorithm, a machine learning tool, to classify global aerosols. The spectral clustering algorithm is a variant of the clustering algorithm that employs eigenvalues and eigenvectors of the data matrix to project the data into a lower-dimensional space of a similar cluster. To accomplish this, we considered five aerosol optical parameters: fine-mode Aerosol Optical Depth, Extinction Angstrom Exponent, Absorption Angstrom Exponent, Single Scattering Albedo, and Refractive Index from 150 AERONET sites distributed in six continents (Africa, Asia, Australia, Europe, North and South America) during 1993 to 2022. Using the clustering analysis, we identified four primary aerosol types: dust, urban, biomass burning, and mixed aerosols. Among the continents, the African and Asian sites exhibited the highest contribution of dust aerosols, as the region has significant global dust sources. Conversely, Australia, Europe, North, and South America are predominantly influenced by fine-mode aerosols, given their considerable distance from major dust source regions.

20 years of columnar aerosol properties at Valencia area (Eastern Spain) by ground-based sun-photometry

In this paper, a climatological study focused on the analysis of atmospheric aerosols properties over Burjassot and Aras de los Olmos AERONET sites, located at Eastern Spain, is performed. Computed mean values for Aerosol Optical Depth (AOD440), Ångström exponent (α440−870) and columnar water vapor (w) in Burjassot (Aras de los Olmos) are 0.19±0.08 (0.10±0.02), 1.21±0.16 (1.18±0.25) and 1.87±0.68cm (0.94±0.10cm), respectively. From the monthly statistics of w and AOD, it is concluded that summer months are characterised by higher humidity and turbidity, being the latter favoured by particle stagnation, recirculation, secondary aerosol formation, hygroscopic processes and North African dust intrusions. Regarding the volume size distribution, well developed fine and coarse modes are found in summer. On the other hand, the spectral dependence of the asymmetry parameter (g) describes a decrease in λ up to 870nm, and then a slight increase due to the influence of dust particles. The computed mean values for the asymmetry parameter (g440) are 0.700±0.013 (0.709±0.016) for Burjassot (Aras de los Olmos). With respect to the Single Scattering Albedo (SSA) and the complex refractive index, an additional analysis using Level 1.5 data is performed, as relatively few data points pass the filters imposed by the Level 2.0 conditions. In the case of SSA, which is found to be larger in spring and summer months, the obtained mean annual values at 440nm are 0.94±0.03 (0.95±0.03) for Burjassot (Aras de los Olmos). Finally, regarding the complex refractive index, the mean values of the real part (m440) are 1.50±0.03 (1.49±0.03), and for the imaginary part (∣k440∣) are 0.007±0.004 (0.004±0.003) in Burjassot (Aras de los Olmos). The present study is complemented with three analyses based on the distinction between the different aerosol types. To begin with, these are classified according to their nature, being the most abundant continental clean aerosols. Next, Gobbi diagrams are plotted for both sites, depicting a clustered region of coarse aerosols, as well as particle growth traces. Finally, the different air masses affecting the measurement sites are studied, reaching to the conclusion that these originated in the European and the African continents are the most turbid ones. To conclude this study, a seasonal Mann-Kendall test is applied to AOD, α, w and SSA measurements in order to study possible trends. Hence, a statistically significant (>80%) decreasing trend in AOD is observed for most months; whereas α, w and SSA do not show statistically significant long-term trends, only for a few months of the year.

Aerosol retrieval over snow using the RemoTAP algorithm

Abstract. In order to conduct accurate aerosol retrieval over snow, the Remote Sensing of Trace Gases and Aerosol Products (RemoTAP) algorithm developed by SRON Netherlands Institute for Space Research is extended with a bi-directional reflection distribution function (BRDF) for snow surfaces. The capability of the extended algorithm is validated with both synthetic measurements and real satellite measurements from the Polarization & Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL), and a comparison has been made to retrievals with the baseline RemoTAP (without a snow kernel). For retrievals with real PARASOL observations, we use pixels over Aerosol Robotic Network (AERONET) stations for validation and we use the MODIS snow cover products to identify pixels over snow. We evaluate the retrieved aerosol optical thickness (AOT) at 550 nm (τ550), single-scattering albedo (SSA) at 550 nm (ω550) and Ångström exponent (AE) for 440–870 nm (AE440−870). The experiments with both synthetic and real data show that the extended RemoTAP maintains capability for snow-free pixels and has obvious advantages in accuracy and the fraction of successful retrievals for retrieval over snow, especially over surfaces with snow cover >75 %. According to the real-data experiment, we find that the retrieval algorithm has difficulty in fitting the PARASOL 1020 nm band, where snow reflectance is significantly lower than that for the visible bands. When we perform a four-band retrieval (490, 565, 670, 865 nm) with the extended RemoTAP, we obtain a good retrieval result for τ550, ω550 and AE440−870. Therefore, the four-band retrieval with the extended RemoTAP is recommended for aerosol retrieval over snow.

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.

Parameterization of optical properties for liquid cloud droplets containing black carbon based on neural network.

This paper introduces a novel back propagation (BP) neural network method to accurately characterize optical properties of liquid cloud droplets, including black carbon. The model establishes relationships between black carbon volume fraction, wavelength, cloud effective radius, and optical properties. Evaluated on a test set, the value of the root mean square error (RMSE) of the asymmetry factor, extinction coefficient, single-scattering albedo, and the first 4 moments of the Legendre expansion of the phase function are less than 0.003, with the maximum mean relative error (MRE) reaching 0.2%, which are all better than the traditional method that only uses polynomials to fit the relationship between the effective radius and optical properties. Notably, the BP neural network significantly compresses the optical property database size by 37,800 times. Radiative transfer simulations indicate that mixing black carbon particles in water clouds reduces the top-of-atmosphere (TOA) reflectance and heats the atmosphere. However, if the volume fraction of black carbon is less than 10-6, the black carbon mixed in the water cloud has a tiny effect on the simulated TOA reflectance.

ORACLES Campaign, September 2016: Inversion of HSRL-2 Observations with Regularization Algorithm into Particle Microphysical Parameters and Comparison to Airborne In-Situ Data

We present microphysical properties of pollution layers observed with NASA Langley Research Center’s airborne high-spectral-Resolution lidar (HSRL-2). The data obtained by HSRL-2 consist of vertical profiles of three backscatter coefficients (β) taken at 355, 532 and 1064 nm and two extinction coefficients (α) measured at 355 and 532 nm. In our study we (1) inverted the 3β + 2α data into particle size distributions with a regularization algorithm, and subsequently computed (2) number concentration and (3) single-scattering albedo for four measurement profiles. We carried out a first comparison to the same particle characteristics measured with airborne in-situ instruments. The in-situ instruments were flown aboard the P-3B aircraft, which followed the flight track of the aircraft ER-2 that carried HSRL-2. We found good agreement of the co-located (space and time) data products, with a degree of reliability reaching 90%. A more detailed study on a larger dataset needs to be carried out in future work to (a) obtain important correction factors, (b) study the influence of different light-scattering models on the inversion results, and (c) identify sources of retrieval and measurement uncertainties.

Response of surface ozone to atmospheric aerosol absorption is more sensitive than to scattering in a semi-arid region

Interactions between atmospheric aerosols and ozone have significant impact on air pollution and the climate. However, the relative importance of the response of surface ozone to aerosol scattering and absorption has not been well quantified from in situ observations. Results derived from a one-year in situ observational study conducted in a semi-arid region showed that the response of ozone to aerosol absorption was more sensitive than to scattering. Specifically, the change in surface ozone from low to high absorption coefficients was approximately five times that from low to high scattering coefficients. The mass scattering and absorption efficiencies, rather than the single-scattering albedo, which are commonly applied in numerical simulations, were able to clearly distinguish surface ozone. The positive correlation between aerosol and ozone in summer showed the promotion of secondary aerosols by ozone. This study provides robust observational evidence of the response of surface ozone to aerosol scattering and absorption.

3D assimilation and radiative impact assessment of aerosol black carbon over the Indian region using aircraft, balloon, ground-based, and multi-satellite observations

Abstract. A three-dimensional (spatial and vertical) gridded data set of black carbon (BC) aerosols has been developed for the first time over the Indian mainland using data from a dense ground-based network, aircraft- and balloon-based measurements from multiple campaigns, and multi-satellite observations, following statistical assimilation techniques. The assimilated data reveal that the satellite products tend to underestimate (overestimate) the aerosol absorption at lower (higher) altitudes with possible climate implications. The regional maps of BC-induced atmospheric heating derived using this data set capture the elevated aerosol heating layers over the Indian region along with the spatial high over the Indo-Gangetic Plain. It is shown that, over most of the Indian region, the incorporation of realistic profiles of aerosol absorption/extinction coefficients and single scattering albedo into the radiative transfer calculations leads to enhanced high-altitude warming. This could strongly influence the upper-tropospheric and lower-stratospheric processes, including the vertical transport of BC to higher altitudes, and thus have larger implications for atmospheric stability than what would be predicted using satellite observations alone. This will have larger implications for atmospheric stability than what would be predicted using satellite observations alone and could strongly influence the upper-tropospheric and lower-stratospheric processes, including increased vertical transport of BC to higher altitudes. The 3D assimilated BC data set will be helpful in reducing the uncertainty in aerosol radiative effects in climate model simulations over the Indian region.

Composition and source based aerosol classification using machine learning algorithms

The aerosol particles present in the atmospheric region mainly affect the climate radiative forcing directly by scattering & absorbing the sunlight. Also, it indirectly influences the formation of clouds, precipitation and acts as a considerable uncertainty in assessing Earth's radiation budget. Determination of aerosol type is significant in characterizing the aerosol role in the atmospheric processes, feedback, and climate models. This paper proposes two aerosol classification models, one based on the source and another based on the composition, to classify the aerosols using aerosol optical properties. The source based aerosol classification method helps to identify the sources which cause pollution in a particular region. Based on the results, proper control measures can be taken to reduce pollution. The composition based aerosol classification helps to identify the nature of aerosol types, such as absorbing or non-absorbing. This classification helps to study the climate of the Kanpur region. The aerosol data is taken from AERONET (AErosol RObotic NETwork) for the period 2002–2018 for the Kanpur region. The composition based aerosol classification model uses Single Scattering Albedo (SSA), Angstrom Exponent (AE), and Fine Mode Fraction (FMF) parameters to categorize aerosols based on their composition. The source based aerosol classification model classifies the aerosols based on values of AE and Aerosol Optical Depth (AOD) and describes the source of the aerosol particles. Knowledge of aerosol sources and compositions helps execute policies or controls to reduce aerosol concentrations. Machine learning algorithms, Naïve Bayes, K Nearest Neighbor, Decision Tree, Support Vector Machine, and Random Forest are used to validate classification schemes. The performance analysis of machine learning algorithms is compared using ten different metrics, and the results are also compared with the existing aerosol classification models. The results of the classification show that the source based aerosols of the desert and arid background and the composition based aerosols of types, Mixture Absorbing, Coarse absorbing (Dust), and Black Carbon are dominant over the Kanpur region during the study period considered. The Number of non-absorbing (scattering) type aerosols are least in the study region considered during the study period at all the seasons. It is found that the Random Forest and Decision Tree models outperform the other machine learning models considered and the existing classification models in terms of accuracy (99.55 %) and other performance metrics considered.

Spatio-temporal variations of aerosol optical depth over Ukraine under the Russia-Ukraine war

The ongoing Russia-Ukraine war has an impact on air quality in the contested region, but it is difficult to assess it during the war and to distinguish between weather conditions and anthropogenic impacts on air pollution. Aerosol optical depth (AOD) might be a way to indicate the regional air quality remotely. In this study, we analyze satellite-based MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOD products to compare monthly mean AOD values before and during the war. By examining the spatial-temporal distribution of AOD in 2022 and comparing it with a baseline period from 2012 to 2021, we aim to assess the impact of the conflict. Our analysis employs a time series algorithm that decomposes long-term trends and seasonal variations, enabling us to identify AOD changes associated with the war-induced artificial perturbations. Additionally, we utilize satellite-based tropospheric NO2 data and nighttime lighting data as auxiliary sources to support the analysis of abnormal AOD changes resulting from the war. Furthermore, four parameters from Aerosol Robotic Network (AERONET) measurements in the Kyiv site, including angstrom exponent (AE), single scattering albedo (SSA), refractive index (RI), fine mode fraction (FMF) were exclusively discussed to explore the possible changes of aerosol physical-optical properties over Ukraine during the war. Results showed that air quality in Ukraine has been affected by the war in contradictory ways at different levels. At the national level, atmospheric pollution has dropped across Ukraine due to a decrease in the sources of air pollution emissions as a result of the suppression of economic and agricultural activities. Meanwhile, atmospheric air quality has deteriorated at the local scale where war is intense due to the large amounts of air pollutants emitted by explosions. Specifically, a significant decrease in AOD of 22.46% compared to the baseline period was observed across Ukraine in January and February 2022 before the war. Additionally, there was a column density reduction of over 10% for tropospheric NO2 compared to the same period in the previous year. Following the outbreak of the war on February 24, significant increases in AOD were observed in March when compared to the baseline period. Eastern Ukraine experienced a significant increase of 40.14%, while northern Ukraine and central Ukraine saw rises of 34.15% and 45.78%, respectively. In April, a wider distribution of areas with significantly high AOD values across Ukraine was observed compared to March. In July, widespread areas with anomalous low AOD appeared in northern and western Ukraine, likely due to a decrease in post-harvest agricultural burning caused by the war. In August, anomalous high AOD areas were observed in central Ukraine, possibly attributed to continued Russian long-range strikes and a new round of bombardments.

Assessment of aerosol optical and physical properties and implications for radiative effects over the semiarid region of Indo‐Gangetic Basin

This study assesses the physical and optical properties and estimated the radiative forcing of aerosol at Agra over the Indo‐Gangetic Basin (IGB) during July 2016–December 2019 using black carbon (BC) mass concentration (AE‐33 aethalometer), data sets from satellite and model simulations. The optical properties of aerosol and radiative forcing have been measured by the Optical and Physical Properties of Aerosols and Clouds (OPAC) and Santa Barbara Discrete Ordinate Radiative Transfer Atmospheric Radiative Transfer (SBDART) model. The high BC mass concentration has been observed in November and lowest in August. An adverse meteorological condition due to a combination of temperature and low wind speed results in poor dispersion in the wintertime is a common factor for high concentration level pollutants over Agra. The diurnal and temporal cycle of BC mass concentration exhibits a high concentration at nighttime due to the lower atmospheric boundary layer. The seasonal variation of absorption coefficient (βabs) and Absorption Angstrom Exponent (AAE) is found to be higher during post‐monsoon and lowest in monsoon season. This suggests that black carbon concentration over Agra is mainly generated from crop burning, waste burning, automobile exhaust and long‐range transport from Punjab and Haryana as the present site is downwind. OPAC‐derived aerosol optical depth (AOD), single‐scattering albedo (SSA), Angstrom Exponent (AE) and asymmetry parameter (AsyP) were estimated to be 0.57 ± 0.07, 0.78 ± 0.16, 0.99 ± 0.21 and 0.81 ± 0.15, respectively. AOD and AE from the OPAC and the moderate resolution imaging spectroradiometer (MODIS) have shown the consistent relationship. The mean radiative forcing is 18.3 ± 2.1 W m−2 at the top of the atmosphere while, at the surface, net radiative forcing is −42.4 ± 7.2 and 59.1 ± 6.5 W m−2 at the atmosphere during the study period. Vertical profiles were estimated using the observations from Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite and the change in heating rate from the SBDART model over Agra.

Chemical Characterization and Optical Properties of the Aerosol in São Paulo, Brazil

Air pollution in the Metropolitan Area of São Paulo (MASP), Brazil, is a serious problem and is strongly affected by local sources. However, atmosphere column composition in MASP is also affected by biomass burning aerosol (BB). Understanding the impacts of aerosol particles, from both vehicles and BB, on the air quality and climate depends on in-depth research with knowledge of some parameters such as the optical properties of particles and their chemical composition. This study characterized fine particulate matter (PM2.5) from July 2019 to August 2020 in the eastern part of the MASP, relating the chemical composition data obtained at the surface and columnar optical parameters, such as aerosol optical depth (AOD), Ångström Exponent (AE), and single-scattering albedo (SSA). According to the analyzed data, the mean PM2.5 concentration was 18.0 ± 12.5 µg/m3; however, daily events exceeded 75 times the air quality standard of the World Health Organization (15 µg/m3). The mean black carbon concentration was 1.8 ± 1.5 µg/m3 in the sampling period. Positive matrix factorization (PMF) identified four main sources of aerosol: heavy vehicles (42%), followed by soil dust plus local sources (38.7%), light vehicles (9.9%), and local sources (8.6%). AOD and AE presented the highest values in the dry period, during which biomass burning events are more frequent, suggesting smaller particles in the atmosphere. SSA values at 440 nm were between 0.86 and 0.94, with lower values in the winter months, indicating the presence of more absorbing aerosol.

Relationships between morphology and optical properties of vehicle-emitted soot

Soot emissions from vehicles have effects not only on public health but also on the Earth’s radiative balance. This pollutant is the main absorber of visible solar radiation and is considered to be the second factor contributing to global warming after CO2. Large and compact soot agglomerates have a higher single-scattering albedo than small and irregular ones. Among morphological and optical studies, most of them focus on the effect of the particle size, but not so many on the irregularity of agglomerates. In this work, the methodological approach is based on the combination of original experimental techniques (in-situ measurement of morphological and optical properties of soot particles emitted from a vehicle on a rolling bench) with theoretical developments (using fractal analysis and optical modelling). A typical conventional European road vehicle was used as a soot generator. Individual soot agglomerates were sampled and visualized with transmission electron microscopy (TEM), and their images were subjected to digital treatment and their morphological parameters were used as input for modelling. In addition, a double dilutor-Differential Mobility Analyzer (DMA)-Condensation Particle Counter (CPC)-Cavity Attenuated Phase Shift spectrometer (CAPS) assembly was used, which allows for classification of particles based on their mobility diameter and to simultaneously measure the optical extinction and scattering coefficients of the agglomerates. It was observed that, in general, the diameter of gyration obtained from TEM images underestimate the electrical mobility diameter, especially for large agglomerates. It was also observed that the diameter of primary particles and the power-law prefactor increase with the agglomerate size, while opposite trend was found for the fractal dimension and for the coordination number. Both the mass-specific absorption and scattering cross-sections (MAC and MSC) of agglomerates were observed to decrease with increasing agglomerate size, as consequence of decreasing fractal dimension.

Aerosol Optical Properties of Extreme Global Wildfires and Estimated Radiative Forcing With GCOM‐C SGLI

AbstractTo understand the climate impact of the wildfires, it is essential to monitor the aerosol emissions from biomass burning and to estimate their optical properties and radiative forcing. This study analyzed wildfires in Brazil, Angola, Australia, California, Siberia, and South‐east Asia that occurred after 2018 using data obtained with the Second‐generation GLobal Imager (SGLI) onboard Global Change Observation Mission—Climate which is a polar‐orbit satellite launched by JAXA on 23 December 2017. We showed the SGLI‐based 4‐year variation of the aerosol optical properties, Aerosol Optical Thickness, Ångström Exponent (AE), and Single Scattering Albedo (SSA) for each region complemented with other satellite‐ and ground‐based data. From the SSA and AE relationship analyses, we confirmed that their optical properties depend on the relative humidity and type of burned vegetation, which is consistent with the previous studies. Moreover, we estimated the net incoming radiation at the top of the atmosphere during the intense fire periods to understand the impact of the direct effect of biomass burning aerosols on radiative forcing. The estimates show a significant negative radiative forcing (i.e., a cooling effect) over the ocean (−78 and −96 Wm−2in Australia and California, respectively). In contrast, small values are observed over land (∼−10 Wm−2for all six regions). Therefore, taking the regional characteristics of the optical properties and surface reflectance into account is necessary to estimate the effect on radiative forcing and future impacts of a short‐lived climate forcer from wildfires.

Impact of long-range transport on black carbon source contribution and optical aerosol properties in two urban environments

Urban areas, as major sources of aerosol black carbon emissions, contribute to increased pollution levels in surrounding regions by air mass long-range transport, which should be taken into account in implementation of emission-reduction strategies. Properties of light-absorbing aerosol particles and a novel approach to assess the impact of long-range transport on black carbon (BC) pollution in two under-investigated urban environments: Warsaw (Poland, Central Europe) and Vilnius (Lithuania, North-Eastern Europe) are presented. During the warm season of May–August 2022, BC mass concentration and aerosol optical properties: the scattering Ångström exponent (SAE), absorption Ångström exponent (AAE), and single scattering albedo (SSA) were investigated. Generally, the mean BC mass concentration was higher at the more polluted site in Warsaw (1.07 μg/m3) than in Vilnius (0.77 μg/m3). The BC source apportionment to biomass burning (BCBB) and fossil fuel combustion (BCFF) showed similar contributions for both sites with BCBB (13–19%) being significantly lower than BCFF (81–87%). A uniform flow of air masses transporting aerosol particles over long distances to both sites was observed for 42% of the days. It affected BC mass concentration as follows: BC decrease was found similar at both sites (42% in Warsaw, 50% in Vilnius) but increase was twice higher in Vilnius (64%) than in Warsaw (30%). Despite variations in BC mass concentration, both sites exhibited a comparable abundance (90%) of submicron (SAE<1.3), BC-dominated (AAE<1.5) particles. The mean SSA was very low (0.69 ± 0.1 in Warsaw, 0.72 ± 0.1 in Vilnius), which indicates a very strong contribution of light-absorbing aerosol particles in both environments. The local episodes of biomass burning due to celebrations of May Days on 1st – 3rd May in Warsaw and Midsummer on 24th June in Vilnius showed similar aerosol properties in both cities (1.5<AAE<1.7, 1.7<SAE<2.2) but were highly different than any other during the entire campaign.

Increased aerosol scattering contributes to the recent monsoon rainfall decrease over the Gangetic Plain

The climate effects of atmospheric aerosols remain highly uncertain. Part of the uncertainty arises from the fact that scattering and absorbing aerosols have distinct or even opposite effects. Thus their relative fraction is critical in determining the overall aerosol climate effect. This study combines observations and global model simulations to demonstrate that changes in the fraction of scattering and absorbing aerosols play an important role in driving the monsoon precipitation decrease over northern India since the 1980s, especially over the Gangetic Basin. Increased aerosol scattering, or decreased aerosol absorption, manifested as a significant increase of aerosol single scattering albedo (SSA), causes strong cooling in the upper atmosphere. This suppresses vertical convection and thus reduces precipitation. Further analysis of the Couple Model Intercomparison Project Phase 6 multi-model-mean historical simulation shows that failing to capture the SSA increase over northern India is likely an important cause of the simulated precipitation trend bias in this area.

Assimilation of POLDER observations to estimate aerosol emissions

Abstract. We apply a local ensemble transform Kalman smoother (LETKS) in combination with the global aerosol–climate model ECHAM–HAM to estimate aerosol emissions from POLDER-3/PARASOL (POLarization and Directionality of the Earth's Reflectances) observations for the year 2006. We assimilate aerosol optical depth at 550 mnm (AOD550), the Ångström exponent at 550 and 865 nm (AE550–865), and single-scattering albedo at 550 nm (SSA550) in order to improve modeled aerosol mass, size and absorption simultaneously. The new global aerosol emissions increase to 1419 Tg yr−1 (+28 %) for dust, 1850 Tg yr−1 (+75 %) for sea salt, 215 Tg yr−1 (+143 %) for organic aerosol and 13.3 Tg yr−1 (+75 %) for black carbon, while the sulfur dioxide emissions increase to 198 Tg yr−1 (+42 %) and the total deposition of sulfates to 293 Tg yr−1 (+39 %). Organic and black carbon emissions are much higher than their prior values from bottom-up inventories, with a stronger increase in biomass burning sources (+193 % and +90 %) than in anthropogenic sources (115 % and 70 %). The evaluation of the experiments with POLDER (assimilated) and AERONET as well as MODIS Dark Target (independent) observations shows a clear improvement compared with the ECHAM–HAM control run. Specifically based on AERONET, the global mean error in AOD550 improves from −0.094 to −0.006, while absorption aerosol optical depth at 550 nm (AAOD550) improves from −0.009 to −0.004 after the assimilation. A smaller improvement is also observed in the AE550–865 mean absolute error (from 0.428 to 0.393), with a considerably higher improvement over isolated island sites at the ocean. The new dust emissions are closer to the ensemble median of AEROCOM I, AEROCOM III and CMIP5 as well as some of the previous assimilation studies. The new sea salt emissions have become closer to the reported emissions from previous studies. Indications of a missing fraction of coarse dust and sea salt particles are discussed. The biomass burning changes (based on POLDER) can be used as alternative biomass burning scaling factors for the Global Fire Assimilation System (GFAS) inventory distinctively estimated for organic carbon (2.93) and black carbon (1.90) instead of the recommended scaling of 3.4 (Kaiser et al., 2012). The estimated emissions are highly sensitive to the relative humidity due to aerosol water uptake, especially in the case of sulfates. We found that ECHAM–HAM, like most of the global climate models (GCMs) that participated in AEROCOM and CMIP6, overestimated the relative humidity compared with ERA5 and as a result the water uptake by aerosols, assuming the kappa values are not underestimated. If we use the ERA5 relative humidity, sulfate emissions must be further increased, as modeled sulfate AOD is lowered. Specifically, over East Asia, the lower AOD can be attributed to the underestimated precipitation and the lack of simulated nitrates in the model.

Global 3-D distribution of aerosol composition by synergistic use of CALIOP and MODIS observations

Abstract. For the observation of the global three-dimensional distribution of aerosol composition and the evaluation of the shortwave direct radiative effect (SDRE) by aerosols, we developed a retrieval algorithm that uses observation data from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the Cloud–Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Aqua. The CALIOP–MODIS retrieval optimizes the aerosol composition to both the CALIOP and MODIS observations in the daytime. Aerosols were assumed to be composed of four aerosol components: water-soluble (WS), light-absorbing (LA), dust (DS), and sea salt (SS) particles. The outputs of the CALIOP–MODIS retrieval are the vertical profiles of the extinction coefficient (αa), single-scattering albedo (ω0), asymmetry factor (g) of total aerosols (WS+LA+DS+SS), and αa of WS, LA, DS, and SS. Daytime observations of CALIOP and MODIS in 2010 were analyzed by the CALIOP–MODIS retrieval. The global means of the aerosol optical depth (τa) at 532 nm were 0.147±0.148 for total aerosols, 0.072±0.085 for WS, 0.027±0.035 for LA, 0.025±0.054 for DS, and 0.023±0.020 for SS. τa of the CALIOP–MODIS retrieval was between those of the CALIPSO and MODIS standard products and was close to the MODIS standard product. The global means of ω0 and g were 0.940±0.038 and 0.718±0.037; these values are in the range of those reported by previous studies. The horizontal distribution of each aerosol component was reasonable; for example, DS was large in desert regions, and LA was large in the major regions of biomass burning and anthropogenic aerosol emissions. The values of τa, ω0, g, and fine and coarse median radii of the CALIOP–MODIS retrieval were compared with those of the AERONET products. τa at 532 and 1064 nm of the CALIOP–MODIS retrieval agreed well with the AERONET products. The ω0, g, and fine and coarse median radii of the CALIOP–MODIS retrieval were not far from those of the AERONET products, but the variations were large, and the coefficients of determination for linear regression between them were small. In the retrieval results for 2010, the clear-sky SDRE values for total aerosols at the top and bottom of the atmosphere were -4.99±3.42 and -13.10±9.93 W m−2, respectively, and the impact of total aerosols on the heating rate was from 0.0 to 0.5 K d−1. These results are generally similar to those of previous studies, but the SDRE at the bottom of the atmosphere is larger than that reported previously. Consequently, comparison with previous studies showed that the CALIOP–MODIS retrieval results were reasonable with respect to aerosol composition, optical properties, and the SDRE.

A comparison of atmospheric aerosol absorption properties from the MERRA-2 reanalysis with AERONET

Our focus is the comparison of atmospheric aerosol absorption properties between the MERRA-2 reanalysis and the inversion product of the surface station network AERONET. We use the available Aerosol Absorption Optical Depth (AAOD) and Single Scattering Albedo (SSA) data from both sources during the period 1993–2022, for the globe. The comparison is performed for the whole dataset, but also repeated for different classifications, namely by aerosol types, Köppen climate, and continent. Moreover, we investigate the relationships between these classifications. For these medium and high optical depth cases, the MERRA-2 relative bias for AAOD and SSA is globally −3.7% and −1.4%, but there is a wide differentiation in performance for the different types, climates, and continents. The MERRA-2 SSA frequency distribution is too narrow compared to the AERONET. MERRA-2 strongly overestimates the absorption over N. America and less so over S. America and Europe, while it underestimates it greatly over Oceania. AAOD is underestimated over biomass-burning regions and overestimated over most areas rich in dust. There is evidence that the lack of brown carbon in the aerosol type classification scheme in MERRA-2 hampers its performance. The comparison over Asia dry areas (classified as Köppen climate type B) shows a large underestimation in AAOD, non-existent in other dry (B) climate types. For the relatively few observations over polar (Köppen type E) climates, MERRA-2 gives too absorptive aerosols. With respect to absorption properties, it appears that MERRA-2 would improve its agreement with AERONET by addressing some erroneous aerosol classifications, employing the brown carbon type, and introducing more detail in dry region aerosol sources.