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Aerosol hygroscopicity plays a vital role in aerosol radiative forcing. One key parameter describing hygroscopicity is the scattering enhancement factor, f (RH), defined as the ratio of the scattering coefficient at humidified relative humidity (RH) to its dry value. Here, we utilize the f (80 %) from ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) 2016 and 2018 airborne measurements to investigate the hygroscopicity of aerosols, its vertical distribution, its relationship with chemical composition, and its sensitivity to organic aerosol (OA) hygroscopicity over the southeast Atlantic (SEA) Ocean during the biomass burning (BB) season. We found that aerosol hygroscopicity remains steady above 2 km, with a mean f (80 %) of 1.40 ± 0.17. Below 2 km, aerosol hygroscopicity increases with decreasing altitude, with a mean f (80 %) of 1.51 ± 0.22, consistent with higher values of BB aerosol hygroscopicity found in the literature. The hygroscopicity parameter of OA (κOA) is retrieved from the Mie model with a mean value of 0.11 ± 0.08, which is in the middle to upper range compared to the literature. Higher OA hygroscopicity is related to aerosols that are more aged, oxidized, and present at lower altitudes. The enhanced biomass burning aerosol (BBA) hygroscopicity at lower altitudes is mainly due to a lower OA fraction, increased sulfate fraction, and greater κOA at lower altitudes. We propose a parameterization that quantifies f (RH) with chemical composition and κOA based on Mie simulation of internally mixed OA–(NH4)2SO4–BC mixtures. The good agreement between the predictions and the ORACLES measurements implies that the aerosols in the SEA during the BB season can be largely represented by the OA–(NH4)2SO4–BC internal mixture with respect to the f (RH) prediction. The sensitivity of f (RH) to κOA indicates that applying a constant κOA is only suitable when the OA fraction is low and κOA shows limited variation. However, in situations deviating these two criteria, κOA can notably impact scattering coefficients and aerosol radiative effect; therefore, accounting for κOA variability is recommended. [ABSTRACT FROM AUTHOR]

The interaction between atmospheric aerosols and moisture is crucial for aerosol properties and their climate effects. In this study, thanks to the rich measurements of aerosol properties during the 2016 and 2018 ORACLES campaigns, we investigate the aerosol liquid water content (ALWC) over the south-eastern Atlantic Ocean during the biomass burning (BB) season, as well as the seldom-reported ALWC associated with organic aerosols (OA) (ALWCOA) (OA). ALWCOA is determined using the OA hygroscopicity parameter KOA, derived from in-situ hygroscopicity measurements, particle number size distribution, and chemical composition. The ALWC can be determined either with the overall hygroscopic parameter K/RH) or from the sum of ALWCOA and the ALWC simulated from ISORROPIA-II, a thermodynamic equilibrium model for inorganic aerosol. The ALWC from both methods is highly correlated at all RHs with an R² of 0.99. The ALWC increases with aerosol loading and ambient relative humidity (RH). Due to the lower RH and higher aerosol loading in the 2016 campaign, the ALWC for both campaigns are generally consistent. ALWCOA accounts for 38±16 % of the total ALWC during both campaigns. Notably, the contribution of ALWCOA is greater than commonly reported in the literature, highlighting the significance of OA in ALWC and therefore the aerosol direct radiative forcing in this climatically significant region. The strong correlation between kOA and ALWCOA/ALWC, as indicated by an R² value of 0.72, underscores the importance of a good estimation of kOA in the ALWC estimation. Additionally, the significant difference between ALWCOAvalues calculated using real-time kOA and those calculated with the campaign mean kOA, highlights the limitation of using a constant kOA value, a practice commonly adopted in climate models. [ABSTRACT FROM AUTHOR]

Aerosol hygroscopicity plays a vital role in aerosol radiative forcing. One key parameter describing hygroscopicity is the scattering enhancement factor, f(RH), defined as the ratio of the scattering coefficient at humidified relative humidity (RH) to its dry value. Here, we utilize the f(80%) from ORACLES 2016 and 2018 airborne measurements to investigate the hygroscopicity of aerosols, its vertical distribution, its relationship with chemical composition, and its sensitivity to organic aerosol (OA) hygroscopicity over the South-East Atlantic (SEA) Ocean during the biomass burning (BB) season. We found that aerosol hygroscopicity remains steady above 2 km, with a mean f(80%) of 1.40±0.17. Below 2 km, aerosol hygroscopicity increases with decreasing altitude, with a mean f(80%) of 1.51±0.22, consistent with higher values of BB hygroscopicity found in the literature. The hygroscopicity parameter of OA (OA) is retrieved from the Mie model with a mean value of 0.11±0.08, which is in the middle to upper range compared to literature. Higher OA hygroscopicity is related to aerosols that are more aged, oxidized, and present at lower altitudes. The enhanced BBA hygroscopicity at lower altitudes is mainly due to a lower OA fraction, increased sulphate fraction, and greater OA at lower altitudes. We propose a parameterization that quantifies f(RH) with chemical composition and OA based on Mie simulation of internally mixed OA-(NH4)2SO4-BC mixture. The good agreement between the predictions and the ORACLES measurements implies that the aerosols in the SEA during the BB season can be largely represented by the OA-(NH4)2SO4-BC internal mixture with respect to the f(RH) prediction. The sensitivity of f(RH) to OA indicates that applying a constant OA is only suitable when the OA fraction is low and OA shows limited variation. However, in situations deviating these two criteria, OA can notably impact scattering coefficients and aerosol radiative effect; therefore, accounting for OA variability is recommended. [ABSTRACT FROM AUTHOR]

In most parts of the electromagnetic spectrum, solar radiation cannot penetrate clouds. Therefore, cloud detection and masking are essential in image preprocessing for observing the Earth and analyzing its properties. Because clouds vary in size, shape, and structure, an accurate algorithm is required for removing them from the area of interest. This task is usually more challenging over bright surfaces such as exposed sunny deserts or snow than over water bodies or vegetated surfaces. The overarching goal of the current study is to explore and compare the performance of three Convolutional Neural Network architectures (U-Net, SegNet, and DeepLab) for detecting clouds in the VEN μ S satellite images. To fulfil this goal, three VEN μ S tiles in Israel were selected. The tiles represent different land-use and cover categories, including vegetated, urban, agricultural, and arid areas, as well as water bodies, with a special focus on bright desert surfaces. Additionally, the study examines the effect of various channel inputs, exploring possibilities of broader usage of these architectures for different data sources. It was found that among the tested architectures, U-Net performs the best in most settings. Its results on a simple RGB-based dataset indicate its potential value for any satellite system screening, at least in the visible spectrum. It is concluded that all of the tested architectures outperform the current VEN μ S cloud-masking algorithm by lowering the false positive detection ratio by tens of percents, and should be considered an alternative by any user dealing with cloud-corrupted scenes. [ABSTRACT FROM AUTHOR]

From June to October, southern Africa produces one-third of the global biomass burning (BB) emissions by widespread fires. BB aerosols are westward transported over the south-eastern Atlantic with the mid-tropospheric winds, resulting in significant radiative effects. Ascension Island (ASI) is located midway between Africa and South America. A 17-month in-situ campaign on ASI found a low single-scattering albedo (SSA) as well as a high mass absorption cross-section of black carbon (MACBC), demonstrating the strong absorbing marine boundary layer in the south-eastern Atlantic. Here we investigate the monthly variations of critical optical properties of BB aerosols, i.e., SSA and MACBC, during the BB seasons and the driving factors behind these variations. Both SSA and MACBC increase from June to August and decrease in September and October. The average SSA during the BB seasons is 0.81 at 529 nm wavelength, with the highest mean ~0.85 in October and the lowest ~0.78 in August. The absorption enhancement Eabs derived from the MACBC shows similar trends with SSA, with the average during the whole BB seasons at ~ 1.96 and ~ 2.07 in 2016 and 2017. As the Eabs is higher than the ~1.5 commonly adopted value by climate models, this result suggests the marine boundary layer in the south-eastern Atlantic is more absorbing than model simulations. We find the enhanced ratio of BC to CO (BC/∆CO) is well correlated with SSA and MACBC, providing a simple way to estimate those aerosol optical characteristics in the south-eastern Atlantic. The exponential function we proposed can approximate SSA and MACBC with BC/∆CO, and can better capture the growth of SSA as the decrease of BC/∆CO, especially when BC/∆CO is small. BC/∆CO is influenced by combustion conditions and aerosol scavenging. From the analysis of the location of BB burning, the primary source fuel, the water content in the fuel, combined with the mean cloud cover and precipitation in the transport areas of BB plume, we conclude that the increase in BC/∆CO from June to August is likely to be caused by burning becoming more flaming. The reduction in the water content of fuels may be responsible for the changing of the burning conditions during these periods. The decrease in BC/∆CO in September and October may be caused by two factors, one being a lower proportion of flaming conditions, possibly associated with a decrease in mean surface wind speed in the burning area, and the other being an increase in precipitation in the BB transport pathway, leading to enhanced aerosol scavenging, which ultimately results in an increase in SSA and MACBC. [ABSTRACT FROM AUTHOR]

Biomass burning emissions often contain brown carbon (BrC), which represents a large family of light absorbing organics that are chemically complex and therefore difficult to estimate their absorption of incoming solar radiation, resulting in large uncertainties in the estimation of the global direct radiative effect of aerosols. Here we investigate the contribution of BrC to the total light absorption of biomass burning aerosols over the South-East Atlantic Ocean with different optical models utilizing a suite of airborne measurements from the ORACLES 2018 campaign by introducing an effective refractive index of black carbon (BC), meBC=neBC+ikeBC, that accounts for all possible absorbing components at 660 nm wavelength to facilitate the attribution of absorption at shorter wavelengths. Most values of the imaginary part of the refractive index, keBC, were larger than those commonly used for BC from biomass burning emissions, suggesting contributions from absorbers beyond BC at 660 nm. The TEM-EDX single particle analysis further suggests that these long-wavelength absorbers might include iron oxides, as iron is found to be present only when large values of keBC are derived. Using this effective BC refractive index, we find that the contribution of BrC to the total absorption at 470 nm (RBrC,470) ranges from ~5-15 %, with the organic aerosol mass absorption coefficient (MACOA,470) at this wavelength ranging from 0.25±0.34 m² g-1 to 0.43±0.12 m² g-1. The core-shell model yielded much higher estimates of MACOA,470 and RBrC,470 than homogeneous mixing models, underscoring the importance of model treatment. Another key finding was that estimates of the BrC contribution at 470 nm from the commonly used AAE (absorption Ångström exponent) attribution method (<5%) are much lower than the BrC contribution estimates (RBrC,470) using our new methodology that accounts for contributions from both BrC and non-carbonaceous, long-wavelength absorbers, such as magnetite. Thus, it is recommended that application of any optical properties-based attribution method use absorption coefficients at the longest possible wavelength to minimize the influence of BrC at the long wavelength and to account for potential contributions from other absorbing materials. [ABSTRACT FROM AUTHOR]

Aerosol particles can be emitted, transported, removed, or transformed, leading to aerosol variability at scales impacting the climate (days to years and over hundreds of kilometers) or the air quality (hours to days and from meters to hundreds of kilometers). We present the temporal and spatial scales of changes in AOD (Aerosol Optical Depth), and aerosol size (using Angstrom Exponent; AE, and Fine-Mode-Fraction; FMF) over Korea during the 2016 KORUS-AQ (KORea-US Air Quality) atmospheric experiment. We use measurements and retrievals of aerosol optical properties from airborne instruments for remote sensing (4STAR; Spectrometers for Sky-Scanning Sun Tracking Atmospheric Research) and in situ (LARGE; NASA Langley Aerosol Research Group Experiment) on board the NASA DC-8, geostationary satellite (GOCI; Geostationary Ocean Color Imager; Yonsei aerosol retrieval (YAER) version 2) and reanalysis (MERRA-2; Modern-Era Retrospective Analysis for Research and Applications, version 2). Measurements from 4STAR when flying below 500 m, show an average AOD at 501 nm of 0.43 and an average AE of 1.15 with large standard deviation (0.32 and 0.26 for AOD and AE respectively) likely due to mixing of different aerosol types (fine and coarse mode). The majority of AODs due to fine mode aerosol is observed at altitudes lower than 2 km. Even though there are large variations, for 18 out of the 20 flight days, the column AOD measurements by 4STAR along the NASA DC-8 flight trajectories matches the south-Korean regional average derived from GOCI. We also observed that, contrary to prevalent understanding, AE and FMF are more spatially variable than AOD during KORUS-AQ, even when accounting for potential sampling biases by using Monte Carlo resampling. Averaging between measurements and model for the entire KORUS-AQ period, a reduction in correlation by 15% is 65.0 km for AOD and shorter at 22.7 km for AE. While there are observational and model differences, the predominant factor influencing spatial-temporal homogeneity is the meteorological period. High spatio-temporal variability occur during the dynamic period (25-31 May), and low spatio-temporal variability occur during blocking Rex pattern (01- 07 June). The changes in spatial variability scales between AOD and FMF/AE, while interrelated, indicate that microphysical processes that impact mostly the dominant aerosol size, like aerosol particle formation, growth, and coagulation, vary at shorter scales than the aerosol concentration processes that mostly impact AOD, like aerosol emission, transport, and removal. Plain Language (Short) Summary Airborne observations of atmospheric particles and pollution over Korea during a field campaign in May-June 2016 showed that the smallest atmospheric particles are present in the lowest 2 km of the atmosphere. The aerosol size is less repeatable over distances than their optical thickness. We show this with remote sensing (4STAR), insitu (LARGE) observations, satellite measurements (GOCI), and modeled properties (MERRA-2), and it is contrary to current understanding. [ABSTRACT FROM AUTHOR]

This study characterizes single particle aerosol composition from filters collected during the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) and CLoud-Aerosol-Radiation Interaction and Forcing: Year 2017 (CLARIFY-2017) campaigns. In particular the study describes aged biomass burning aerosol (BBA), its interaction with the marine boundary layer and the influence of biomass burning (BB) air on marine aerosol. The study finds evidence of BBA influenced by marine boundary layer processing as well as sea salt influenced by BB air. Secondary chloride aerosols were observed in clean marine air as well as in BB-influenced air in the free troposphere. Higher volatility organic aerosol appears to be associated with increased age of biomass burning plumes, and photolysis may be a mechanism for the apparent increased volatility. Aqueous processing and interaction with the marine boundary layer air may be a mechanism for the presence of sodium on many aged potassium salts. By number, biomass burning potassium salts and modified sea salts are the most observed particles on filter samples. These results suggest that atmospheric processing such as photolysis and cloud processing, rather than BB fuel type, has a major role in the elemental composition and morphology of aged BBA. [ABSTRACT FROM AUTHOR]

Marine stratocumulus cloud properties over the southeast Atlantic Ocean are impacted by contact between above-cloud biomass-burning aerosols and cloud tops. Different vertical separations (0 to 2000 m) between the aerosol layer and cloud tops were observed on six research flights in September 2016 during the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) field campaign. There were 30 contact profiles where the aerosol layer with aerosol concentration (Na) > 500 cm−3 was within 100 m of cloud tops, and 41 separated profiles where the aerosol layer with Na > 500 cm−3 was located more than 100 m above cloud tops. For contact profiles, the average cloud droplet concentration (Nc) in the cloud layer was up to 68 cm−3 higher, the effective radius (Re) up to 1.3 µm lower and the liquid water content (LWC) within 0.01 g m−3 compared to separated profiles. Free tropospheric humidity was higher in the presence of biomass-burning aerosols and contact profiles had a smaller decrease in humidity (and positive buoyancy) across cloud tops due to higher median above-cloud Na (895 cm−3) compared to separated profiles (30 cm−3). Due to droplet evaporation from entrainment mixing of warm, dry free tropospheric air into the clouds, the median Nc and LWC for contact profiles decreased with height by 21 % and 9 % in the top 20 % of the cloud layer. The impact of droplet evaporation was stronger during separated profiles as a greater decrease in humidity (and negative buoyancy) across cloud tops led to greater decreases in median Nc (30 %) and LWC (16 %) near cloud tops. Below-cloud Na was sampled during 61 profiles, and most contact profiles (20 out of 28) were within high-Na (> 350 cm−3) boundary layers while most separated profiles (22 out of 33) were within low-Na (< 350 cm−3) boundary layers. Although, the differences in below-cloud Na were statistically insignificant, contact profiles within low-Na boundary layers had up to 34.9 cm−3 higher Nc compared to separated profiles. This was driven by the weaker impact of droplet evaporation in the presence of biomass-burning aerosols within 100 m above cloud tops. For contact profiles within high-Na boundary layers, the presence of biomass-burning aerosols led to higher below-cloud Na (up to 70.5 cm−3) and additional droplet nucleation above cloud base along with weaker droplet evaporation. Consequently, the contact profiles in high-Na boundary layers had up to 88.4 cm−3 higher Nc compared to separated profiles. These results motivate investigations of aerosol-cloud-precipitation interactions over the southeast Atlantic since the changes in Nc, Re, and LWC induced by the presence of above-cloud biomass burning aerosols are likely to impact precipitation rates, liquid water path and cloud fraction, and modulate closed to open cell transitions. [ABSTRACT FROM AUTHOR]

Cloud optical properties such as optical thickness along with surface albedo are important inputs for deriving the shortwave radiative effects of clouds from space-borne remote sensing. Owing to insufficient knowledge about the snow or ice surface in the Arctic, cloud detection and the retrieval products derived from passive remote sensing, such as from the Moderate Resolution Imaging Spectroradiometer (MODIS), are difficult to obtain with adequate accuracy – especially for low-level thin clouds, which are ubiquitous in the Arctic. This study aims at evaluating the spectral and broadband irradiance calculated from MODIS-derived cloud properties in the Arctic using aircraft measurements collected during the Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE), specifically using the upwelling and downwelling shortwave spectral and broadband irradiance measured by the Solar Spectral Flux Radiometer (SSFR) and the BroadBand Radiometer system (BBR). This entails the derivation of surface albedo from SSFR/BBR and camera imagery for heterogeneous surfaces in the marginal ice zone (MIZ), as well as subsequent measurement-model inter-comparisons in the presence of thin clouds. In addition to MODIS cloud retrievals and surface albedo from SSFR, we used temperature and humidity data from in-situ data and reanalysis (MERRA-2). The spectral surface albedo derived from the airborne radiometers is consistent with prior ground-based measurements, and adequately represents the surface variability for the study region and time period. Somewhat surprisingly, the primary error in MODIS-derived irradiance fields for this study stems from undetected clouds, rather than from the retrieved cloud properties. In our case studies, about 22 % of clouds remained undetected (cloud optical thickness less than 0.5). The radiative effect of clouds above the detection threshold was −40 W m−2 above cloud, and −39 W m−2 below the cloud layer, and the optical thickness from the MODIS "1621" cloud product was consistent with the reflected and transmitted irradiance observations. This study suggests that passive imagery cloud detection could be improved through a multi-pixel approach, that would make it more dependable in the Arctic. Regardless of the cloud retrieval method, there is a need for an operational imagery-based surface albedo product for the polar regions that adequately captures its temporal, spatial, and spectral variability to estimate cloud radiative effect from space-borne remote sensing. [ABSTRACT FROM AUTHOR]

In this study we developed a neural network (NN) that can be used to relate a large dataset of multi-angular and multi-spectral polarimetric remote sensing observations to retrievals of cloud microphysical properties. This effort builds upon our previous work, which explored the sensitivity of neural network input, architecture, and other design requirements for this type of remote sensing problem. In particular this work introduces a framework for appropriately weighting total and polarized reflectances, which have vastly different magnitudes and measurement uncertainties. The NN is trained using an artificial training set and applied to Research Scanning Polarimeter (RSP) data obtained during the ORACLES field campaign (Observations of Aerosols above Clouds and their Interactions). The polarimetric RSP observations are unique in that they observe the same cloud from a very large number of angles within a variety of spectral bands resulting in a large dataset that can be explored rapidly with a NN approach. The usefulness applying a NN to a dataset such as this one stems from the possibility of rapidly obtaining a retrieval that could be subsequently applied as a first-guess for slower but more rigorous physical-based retrieval algorithms. This approach could be particularly advantageous for more complicated atmospheric retrievals - such as when an aerosol layer lies above clouds like in ORACLES. For the ORACLES 2016 dataset comparisons of the NN and standard parametric polarimetric (PP) cloud retrieval give reasonable results for droplet effective radius (re : R=0.756, RMSE=1.74μm) and cloud optical thickness (τ : R=0.950, RMSE=1.82). This level of statistical agreement is shown to be similar to comparisons between the two most well-established cloud retrievals, namely the the polarimetric cloud retrieval and the bispectral total reflectance cloud retrieval. The NN retrievals from the ORACLES 2017 dataset result in retrievals of re (R=0.54, RMSE=4.77μm) and τ (R=0.785, RMSE=5.61) that behave much more poorly. In particular we found that our NN retrieval approach does not perform well for thin (τ<3), inhomogeneous, or broken clouds. We also found that correction for above-cloud atmospheric absorption improved the NN retrievals moderately - but retrievals without this correction still behaved similarly to existing cloud retrievals with a slight systematic offset. [ABSTRACT FROM AUTHOR]

Nine Pandora spectrometer instruments (PSI) were installed at eight sites in South Korea as part of the KORUS-AQ (Korea U.S.-Air Quality) field study integrating information from ground, aircraft, and satellite measurements for validation of remote sensing air-quality studies. The PSI made direct-sun measurements of total vertical column NO2, C.NO2), with high precision (0.05 DU, where 1DUD 2:69×1016 molecules cm-2) and accuracy (0.1 DU) that were retrieved using spectral fitting techniques. Retrieval of formaldehyde C(HCHO) total column amounts were also obtained at five sites using the recently improved PSI optics. The C(HCHO) retrievals have high precision, but possibly lower accuracy than for NO2 because of uncertainty about the optimum spectral window for all ground-based and satellite instruments. PSI direct-sun retrieved values for C(NO2) and C(HCHO) are always significantly larger than OMI (AURA satellite Ozone Monitoring Instrument) retrieved C(NO2) and C(HCHO) for the OMI overpass local times (KST D 13:5±0:5 h). In urban areas, PSI C(NO2) 30- day running averages are at least a factor of two larger than OMI averages. Similar differences are seen for C(HCHO) in Seoul and nearby surrounding areas. Late afternoon values of C(HCHO) measured by PSI are even larger, implying that OMI early afternoon measurements underestimate the effect of poor air quality on human health. The primary cause of OMI underestimates is the large OMI field of view (FOV) that includes regions containing low values of pollutants. In relatively clean areas, PSI and OMI are more closely in agreement. C(HCHO) amounts were obtained for five sites, Yonsei University in Seoul, Olympic Park, Taehwa Mountain, Amnyeondo, and Yeoju. Of these, the largest amounts of C(HCHO) were observed at Olympic Park and Taehwa Mountain, surrounded by significant amounts of vegetation. Comparisons of PSI C(HCHO) results were made with the Compact Atmospheric Multispecies Spectrometer CAMS during overflights on the DC-8 aircraft for Taehwa Mountain and Olympic Park. In all cases, PSI measured substantially more C(HCHO) than obtained from integrating the CAMS altitude profiles. PSI C(HCHO) at Yonsei University in Seoul frequently reached 0.6DU and occasionally exceeded 1.5 DU. The semi-rural site, Taehwa Mountain, frequently reached 0.9DU and occasionally exceeded 1.5 DU. Even at the cleanest site, Amnyeondo, C(HCHO) occasionally exceeded 1 DU. [ABSTRACT FROM AUTHOR]