Aerosol vertical profiles in the lowest 1 km of the atmosphere are not very well studied due to technology limitations (e.g. LIDARs) and air space restrictions (e.g. manned and unmanned aircrafts). This study investigates sensitivity of the radiance measurements to the aerosol profiles from the standard columnar almucantar and direct sun measurements combined with low elevation sky scanning (from the horizon to zenith direction). Sensitivity studies are conducted for the sun-sky radiometer filter bands deployed within AERONET. AErosol RObotic NETwork (AERONET) is a network of sun-sky-moon photometers that measure solar radiation at 9 wavelength bands (centered at 340, 380, 440, 500, 675, 870, 937, 1020, 1640 nm, 2-10 nm except 25 nm for 1640 nm FWHM filter transmission). The main AERONET products are columnar aerosol optical depth, Angstrom exponent (from direct sun measurements), single scattering albedo and size distribution (from Almucantar and hybrid scans). The additional products investigated in this study are vertical volume density and aerosol extinction coefficient profiles. GRASP (with the plane parallel radiative transfer model) is initially used to simulate scattered sky radiances and conduct aerosol profile inversions. Several aerosol models and loadings are investigating as well as aerosol volume density profiles.

Biomass burning aerosol (BBA) from agricultural fires in southern Africa contributes about one-third of the global carbonaceous aerosol load. These particles have strong radiative effects in the southeast Atlantic (SEA), which depend in part on the radiative contrast between the aerosol layer in the free troposphere (FT) and the underlying cloud layer. However, there is large disagreement in model estimates of aerosol-driven climate forcing due to uncertainties in the vertical distribution, optical properties, and life cycle of these particles. This study applies a novel method combining remote sensing observations with regional model outputs to investigate the aging of the BBA and its impact on the optical properties during transatlantic transport from emission sources in Africa to the SEA. Results show distinct variations in extinction Ångström exponent (EAE) and single-scattering albedo (SSA) as aerosols age. Near the source, fresh aerosols are characterized by low mean SSA (0.84) and high EAE (1.85), indicating smaller, highly absorbing particles. By isolating marine contributions from the total column during BBA transport across the SEA, our analysis reveals an initial decrease in BBA absorptivity, with mean FT SSA of 0.87 after 6–7 d, followed by increased absorptivity with mean FT SSA of 0.84 after 10 d, suggesting enhanced absorption due to chemical aging. These findings indicate that BBA becomes more absorbing during extended transport across the SEA, with implications for reducing model uncertainties. Our remote-sensing-based results agree well with previous in situ studies and offer new insights into aerosol–radiation interactions and the energy balance over the SEA.

During the Megacity Air Pollution Studies-Seoul (MAPS-Seoul) campaign from May to June 2015, aerosol optical properties in Korea were obtained based on the AERONET sunphotometer measurement at five sites (Anmyon, Gangneung_WNU, Gosan_SNU, Hankuk_UFS, and Yonsei_University). Using this dataset, we examine regional aerosol types by applying a number of known aerosol classification methods. We thoroughly utilize five different methods to categorize the regional aerosol types and evaluate the results from each method by inter-comparison. The differences and similarities among the results are also discussed, contingent upon the usage of AERONET inversion products, such as the single scattering albedo. Despite several small differences, all five methods suggest the same general features in terms of the regionally dominant aerosol type: Fine-mode aerosols with highly absorbing radiative properties dominate at Hankuk_UFS and Yonsei_University; non-absorbing fine-mode particles form a large portion of the aerosol at Gosan_SNU; and coarse-mode particles cause some effects at Anmyon. The analysis of 3-day back-trajectories is also performed to determine the relationship between classified types at each site and the regional transport pattern. In particular, the spatiotemporally short-scale transport appears to have a large influence on the local aerosol properties. As a result, we find that the domestic emission in Korea significantly contributes to the high dominance of radiation-absorbing aerosols in the Seoul metropolitan area and the air-mass transport from China largely affects the western coastal sites, such as Anmyon and Gosan_SNU.

Wildfires and agricultural burning generate seemingly increasing smoke aerosol emissions, impacting societal and natural ecosystems. To understand smoke's effects on climate and public health, we analyzed the spatiotemporal distribution of smoke aerosols, focusing on two major light-absorbing components, namely black carbon (BC) and brown carbon (BrC) aerosols. Using NASA's Earth Polychromatic Imaging Camera (EPIC) instrument aboard NOAA's Deep Space Climate Observatory (DSCOVR) spacecraft, we inferred BC and BrC volume fractions and particle mass concentrations based on spectral absorption provided by the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm with 1–2 h temporal resolution and ∼ 10 km spatial resolution over North America and central Africa. Our analyses of regional smoke properties reveal distinct characteristics for aerosol optical depth (AOD) at 443 nm, spectral single-scattering albedo (SSA), aerosol layer height (ALH), and BC and BrC amounts. Smoke aerosols in North America showed extremely high AOD up to 6, with elevated ALH (6–7 km) and significant BrC components up to 250 mg m−2 along the transport paths, whereas the smoke aerosols in central Africa exhibited stronger light absorption (i.e., lower SSA) and lower AOD, resulting in higher-BC mass concentrations and similar BrC mass concentrations than the cases in North America. Seasonal burning source locations in central Africa, following the seasonal shift in the Intertropical Convergence Zone and diurnal variations in smoke amounts, were also captured. A comparison of retrieved AOD443, SSA443, SSA680, and ALH with collocated AERONET and CALIOP measurements shows agreement with RMSE values of 0.2, 0.03–0.04, 0.02–0.04, and 0.8–1.3 km, respectively. An analysis of the spatiotemporal average reveals distinct geographical characteristics in smoke properties closely linked to burning types and meteorological conditions. Forest wildfires over western North America generated smoke with a small-BC volume fraction of 0.011 and a high ALH with large variability (2.2 ± 1.2 km), whereas smoke from wildfires and agricultural burning over Mexico region shows more absorption and low ALH. Smoke from savanna fires over central Africa had the most absorption, with a high-BC volume fraction (0.015) and low ALH with a small variation (1.8 ± 0.6 km) among the analyzed regions. Tropical forest smoke was less absorbing and had a high variance in ALH. We also quantify the estimation uncertainties related to the assumptions of BC and BrC refractive indices. The MAIAC EPIC smoke properties with BC and BrC volume and mass fractions and assessment of the layer height provide observational constraints for radiative forcing modeling and air quality and health studies.

The AERONET program is a federation of ground-based sun-photometer networks and operates in partnership with various national and international agencies, universities, institutions, research groups, and individual scientists and stakeholders. It provides worldwide observations of spectral aerosol optical depth, inversion products (microphysical and radiative properties), and precipitable water across diverse aerosol regimes. In addition, other network components enable measurements of normalized water-leaving radiance, solar flux, and marine aerosols. For the past three decades, AERONET has been providing long-term, continuous, and readily accessible public-domain datasets. The network has been growing steadily, with currently about 600 active sites. The program also supports research and application field campaigns around the world. The program continues to refine instrumentation, measurement techniques, and algorithms through research and development. The program's biggest strength is its imposition of standardized instruments, calibration, quality control, processing, and data distribution. This presentation will provide an overview of the program with examples of available datasets, current research, and applications. In this study, we will present a statistical analysis of AERONET data availability over the last three decades. The focus will be to understand measurement challenges, and identify geographical and scientific gaps. We will also highlight important upcoming satellite missions, field campaigns, and new research results from the AERONET team at NASA Goddard.

Abstract. The sub-micron (SM) aerosol optical depth (AOD) is an optical separation based on the fraction of particles below a specified cutoff radius of the particle size distribution (PSD) at a given particle radius. It is fundamentally different from spectrally separated FM (fine-mode) AOD. We present a simple (AOD-normalized) SM fraction versus FM fraction (SMF vs. FMF) linear equation that explains the well-recognized empirical result of SMF generally being greater than the FMF. The AERONET inversion (AERinv) products (combined inputs of spectral AOD and sky radiance) and the spectral deconvolution algorithm (SDA) products (input of AOD spectra) enable, respectively, an empirical SMF vs. FMF comparison at similar (columnar) remote sensing scales across a variety of aerosol types. SMF (AERinv-derived) vs. FMF (SDA-derived) behavior is primarily dependent on the relative truncated portion (εc) of the coarse-mode (CM) AOD associated with the cutoff portion of the CM PSD and, to a second order, the cutoff FM PSD and FM AOD (εf). The SMF vs. FMF equation largely explains the SMF vs. FMF behavior of the AERinv vs. SDA products as a function of PSD cutoff radius (“inflection point”) across an ensemble of AERONET sites and aerosol types (urban-industrial, biomass burning, dust, maritime and a mixed class of Arctic aerosols). The overarching dynamic was that the linear SMF vs. FMF relation pivots clockwise about the approximate (SMF, FMF) singularity of (1, 1) in a “linearly inverse” fashion (slope and intercept of approximately 1−εc and εc) with increasing cutoff radius. SMF vs. FMF slopes and intercepts derived from AERinv and SDA retrievals confirmed the general domination of εc over εf in controlling that dynamic. A more general conclusion is the apparent confirmation that the optical impact of truncating modal (whole) PSD features can be detected by an SMF vs. FMF analysis.

While the use and data assimilation (DA) of operational Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol data is commonplace, MODIS is scheduled to sunset in the next year. For data continuity, focus has turned to the development of next-generation aerosol products and sensors such as those associated with the Visible Infrared Imaging Radiometer Suite (VIIRS) on Suomi NPOESS Preparation Project (S-NPP) and NOAA-20. Like MODIS algorithms, products from these sensors require their own set of extensive error characterization and correction exercises. This is particularly true in the context of monitoring significant aerosol events that tax an algorithm's ability to separate cloud from aerosol and account for multiple scattering related errors exacerbated by uncertainties in aerosol optical properties. To investigate the performance of polar-orbiting satellite algorithms to monitor and characterize significant events, a level 3 (L3) product has been developed using a consistent aggregation methodology for 4 years of observations (2016-2019) that is referred to as the SSEC/NRL L3 product. Included in this product are the AErosol RObotic NETwork (AERONET), MODIS Dark Target, Deep Blue, and Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithms. These MODIS "baseline algorithms" are compared to NASA's recently released NASA Deep Blue algorithm for use with VIIRS. Using this new dataset, the relative performance of the algorithms for both land and ocean were investigated with a focus on the relative skill of detecting severe events and accuracy of the retrievals using AERONET. Maps of higher-percentile aerosol optical depth (AOD) regions of the world by product identified those with the highest measured AODs and determined what is high by local standards. While patterns in AOD match across products and median to moderate AOD values match well, there are regionally correlated biases between products based on sampling, algorithm differences, and AOD range - in particular for higher AOD events. Most notable are differences in boreal biomass burning and Saharan dust. Significant percentile biases must be accounted for when data are used in trend studies, data assimilation, or inverse modeling. These biases vary by aerosol regime and are likely due to retrieval assumptions in lower boundary conditions and aerosol optical models.

We analyzed annual and seasonal frequency in aerosol type over an 8-year period (2012-2019) to identify aerosol parameter trends over four ground sites and country regions in Korea, China, and Japan by using the Aerosol Robotic Network (AERONET), and the satellite-based Visible Infrared Imaging Radiometer Suite (VIIRS) and Ozone Monitoring Instrument (OMI). Decreasing trends are shown for aerosol optical depth (AOD), angstrom ng-stro center dot m exponent (AE), and fine mode fraction (FMF) in all countries. The decreasing trend in these data is considered to be due to a decrease in anthropogenic emissions. For the aerosol type frequency, decreases in the proportions of carbonaceous aerosols (CA) and non-absorbing aerosols (NA) were shown in the ground and satellite data, respectively. At most sites, the fractions of low AOD case (LOW) increased, whereas those of the Black and Brown Carbon (BC + BrC) category decreased. In Seoul, the fraction of LOW increased from 48.9% to 70.0%, and that of BC + BrC decreased continuously from 20.4% to 11.1% during 2012-2019. Beijing, on the other hand, showed decreasing LOW from 83.3% (2012) to 52.0% (2019), and that of BC + BrC increased significantly, from 2.4% to 26.2%. The satellite data showed that the percentage of LOW increased continuously, while that of NA aerosols decreased continuously in East Asia. A noticeable decrease in the fraction of CA was detected in China [21.5% (2013) to 11.2% (2019)]. In all countries, CA and NA aerosols had the greatest effect in winter and summer, respectively. We also detected significant differences between the fractions of NA and BC between the ground and satellite data. Changes in aerosol type and properties were observed concurrently in all ground and satellite data, and changes in aerosol type may explain the increasing and decreasing trends that we recorded for most parameters. Consistent results from both ground and satellite data suggest a steady decreasing in fine aerosol pollution in East Asia.

To investigate near UV aerosol absorbers, such as iron in mineral dust and brown carbon from biomass burning, AERONET spectral imaginary refractive index and size distributions retrievals were performed with the input of additional wavelength data. This includes adding both measured spectral AOD and sky radiances at 380 nm and 500 nm to the four channels (440, 675, 870 and 1020 nm) that are used in the standard retrieval data product. The vector radiative transfer code in the AERONET Version 3 retrievals enabled more accurate computations in the ultraviolet region (380 nm). Calibration of the 380 nm channel radiances was done by the vicarious method since the integrating sphere radiance source that is used for all other wavelengths does not produce sufficient energy at 380 nm. Spectral single scattering albedo, imaginary refractive indices and aerosol size distributions from these six wavelength retrievals are compared to the standard four wavelength retrieval values.

Various forms of global compositional forecasting are now commonplace across the world's operational centers. Biomass burning smoke is often forecast just like other aspects of our weather to support numerous applications such as air quality, transportation, and climate. Recent developments in the field have been bolstered by a new generation of advanced satellite sensors and algorithms on an international constellation of geostationary and polar orbiting satellites. The academic community frequently solicits operational developers for input on development needs and what should be operationalized. Yet, the volume of new data sources is currently outpacing Moore's Law and the forecasting community's ability to process and utilize new data sources data. Targeted to the academic community and using the 2020 western biomass-burning season as an example, this presentation will provide a brief review of how developers view next generation products for use in coupled observational and data assimilation systems that may be required to meet challenges posed by global extreme smoke event forecasting.

Aerosol properties are fundamentally different near clouds than away from clouds. This paper reviews the current state of knowledge of aerosol properties in the near-low-cloud environment and quantitatively compares them with aerosols far from clouds, according to remote sensing observations. It interprets observations of aerosol properties from different sensors using satellite, aircraft, and ground-based observations. The correlation (and anticorrelation) between proximity to cloud and aerosol properties is discussed. Retrieval artifacts in the near-cloud environment are demonstrated and quantified for different sensor attributes and environmental conditions. Finally, the paper describes the possible corrections for near-cloud enhancement in remote sensing retrievals. This study is timely in view of science definition studies for NASA's Aerosol, Cloud, Convection and Precipitation (ACCP) mission, which will also seek to directly link aerosol properties to nearby clouds.

Aerosol properties are fundamentally different near clouds than distant from clouds. This paper reviews the current state of knowledge of aerosol properties in the near low cloud environment and quantitatively compares them with aerosols far from clouds, limited in scope to remote sensing observations. It interprets observations of aerosol properties from different sensors using satellite, aircraft and ground-based observations. The correlation (and anticorrelation) between proximity to cloud and aerosol properties is discussed. Retrieval artifacts in the near-cloud environment are demonstrated and quantified for different sensor attributes and environmental conditions. Finally, the paper describes the possible corrections for near-cloud enhancement in remote-sensing retrievals. This study is timely in view of science definition studies for NASA’s Aerosols-Clouds, Convection and Precipitation (ACCP) mission, which will also seek to directly links aerosol properties to nearby clouds.