The Aerosol Robotic Network (AERONET) has provided highly accurate, ground-truth measurements of the aerosol optical depth (AOD) using Cimel Electronique Sun–sky radiometers for more than 25 years. In Version 2 (V2) of the AERONET database, the near-real-time AOD was semiautomatically quality controlled utilizing mainly cloud-screening methodology, while additional AOD data contaminated by clouds or affected by instrument anomalies were removed manually before attaining quality-assured status (Level 2.0). The large growth in the number of AERONET sites over the past 25 years resulted in significant burden to the manual quality control of millions of measurements in a consistent manner. The AERONET Version 3 (V3) algorithm provides fully automatic cloud screening and instrument anomaly quality controls. All of these new algorithm updates apply to near-real-time data as well as post-field-deployment processed data, and AERONET reprocessed the database in 2018. A full algorithm redevelopment provided the opportunity to improve data inputs and corrections such as unique filter-specific temperature characterizations for all visible and near-infrared wavelengths, updated gaseous and water vapor absorption coefficients, and ancillary data sets. The Level 2.0 AOD quality-assured data set is now available within a month after post-field calibration, reducing the lag time from up to several months. Near-real-time estimated uncertainty is determined using data qualified as V3 Level 2.0 AOD and considering the difference between the AOD computed with the pre-field calibration and AOD computed with pre-field and post-field calibration. This assessment provides a near-real-time uncertainty estimate for which average differences of AOD suggest a +0.02 bias and one sigma uncertainty of 0.02, spectrally, but the bias and uncertainty can be significantly larger for specific instrument deployments. Long-term monthly averages analyzed for the entire V3 and V2 databases produced average differences (V3–V2) of +0.002 with a ±0.02 SD (standard deviation), yet monthly averages calculated using time-matched observations in both databases were analyzed to compute an average difference of −0.002 with a ±0.004 SD. The high statistical agreement in multiyear monthly averaged AOD validates the advanced automatic data quality control algorithms and suggests that migrating research to the V3 database will corroborate most V2 research conclusions and likely lead to more accurate results in some cases.

The Aerosol Robotic Network (AERONET) Version 3 (V3) aerosol retrieval algorithm is described, which is based on the Version 2 (V2) algorithm with numerous updates. Comparisons of V3 aerosol retrievals to those of V2 are presented, along with a new approach to estimate uncertainties in many of the retrieved aerosol parameters. Changes in the V3 aerosol retrieval algorithm include (1) a new polarized radiative transfer code (RTC), which replaced the scalar RTC of V2, (2) detailed characterization of gas absorption by adding NO₂ and H₂O to specify total gas absorption in the atmospheric column, specification of vertical profiles of all the atmospheric species, (3) new bidirectional reflectance distribution function (BRDF) parameters for land sites adopted from the MODIS BRDF/Albedo product, (4) a new version of the extraterrestrial solar flux spectrum, and (5) a new temperature correction procedure of both direct Sun and sky radiance measurements. The potential effect of each change in V3 on single scattering albedo (SSA) retrievals was analyzed. The operational almucantar retrievals of V2 versus V3 were compared for four AERONET sites: GSFC, Mezaira, Mongu, and Kanpur. Analysis showed very good agreement in retrieved parameters of the size distributions. Comparisons of SSA retrievals for dust aerosols (Mezaira) showed a good agreement in 440 nm SSA, while for longer wavelengths V3 SSAs are systematically higher than those of V2, with the largest mean difference at 675 nm due to cumulative effects of both extraterrestrial solar flux and BRDF changes. For non-dust aerosols, the largest SSA deviation is at 675 nm due to differences in extraterrestrial solar flux spectrums used in each version. Further, the SSA 675 nm mean differences are very different for weakly (GSFC) and strongly (Mongu) absorbing aerosols, which is explained by the lower sensitivity to a bias in aerosol scattering optical depth by less absorbing aerosols. A new hybrid (HYB) sky radiance measurement scan is introduced and discussed. The HYB combines features of scans in two different planes to maximize the range of scattering angles and achieve scan symmetry, thereby allowing for cloud screening and spatial averaging, which is an advantage over the principal plane scan that lacks robust symmetry. We show that due to an extended range of scattering angles, HYB SSA retrievals for dust aerosols exhibit smaller variability with solar zenith angles (SZAs) than those of almucantar (ALM), which allows extension of HYB SSA retrievals to SZAs less than 50^∘ to as small as 25^∘. The comparison of SSA retrievals from closely time-matched HYB and ALM scans in the 50 to 75^∘ SZA range showed good agreement with the differences below ∼0.005. We also present an approach to estimate retrieval uncertainties which utilizes the variability in retrieved parameters generated by perturbing both measurements and auxiliary input parameters as a proxy for retrieval uncertainty. The perturbations in measurements and auxiliary inputs are assumed as estimated biases in aerosol optical depth (AOD), radiometric calibration of sky radiances combined with solar spectral irradiance, and surface reflectance. For each set of Level 2 Sun/sky radiometer observations, 27 inputs corresponding to 27 combinations of biases were produced and separately inverted to generate the following statistics of the inversion results: average, standard deviation, minimum and maximum values. From these statistics, standard deviation (labeled U27) is used as a proxy for estimated uncertainty, and a lookup table (LUT) approach was implemented to reduce the computational time. The U27 climatological LUT was generated from the entire AERONET almucantar (1993–2018) and hybrid (2014–2018) scan databases by binning U27s in AOD (440 nm), Angström exponent (AE, 440–870 nm), and SSA (440, 675, 870, 1020 nm). Using this LUT approach, the uncertainty estimates U27 for each individual V3 Level 2 retrieval can be obtained by interpolation using the corresponding measured and inverted combination of AOD, AE, and SSA.

Partitioning of mineral dust, pollution, smoke, and mixtures using remote sensing techniques can help improve accuracy of satellite retrievals and assessments of the aerosol radiative impact on climate. Spectral aerosol optical depth (τ) and single scattering albedo (ω_o) from Aerosol Robotic Network (AERONET) measurements are used to form absorption (i.e., ω_o and absorption Ångström exponent (α_abs)) and size (i.e., extinction Ångström exponent (α_ext) and fine mode fraction of τ) relationships to infer dominant aerosol types. Using the long‐term AERONET data set (1999–2010), 19 sites are grouped by aerosol type based on known source regions to (1) determine the averageω_o and α_abs at each site (expanding upon previous work), (2) perform a sensitivity study on α_abs by varying the spectral ω_o, and (3) test the ability of each absorption and size relationship to distinguish aerosol types. The spectral ω_o averages indicate slightly more aerosol absorption (i.e., a 0.0 < δω_o ≤ 0.02 decrease) than in previous work, and optical mixtures of pollution and smoke with dust show stronger absorption than dust alone. Frequency distributions of α_abs show significant overlap among aerosol type categories, and at least 10% of the α_abs retrievals in each category are below 1.0. Perturbing the spectral ω_o by ±0.03 induces significant α_abs changes from the unperturbed value by at least ∼±0.6 for Dust, ∼±0.2 for Mixed, and ∼±0.1 for Urban/Industrial and Biomass Burning. The ω_o440nm and α_{ext440–870nm}relationship shows the best separation among aerosol type clusters, providing a simple technique for determining aerosol type from surface‐ and future space‐based instrumentation.

The ocean color component of the Aerosol Robotic Network (AERONET-OC) has been implemented to support long-term satellite ocean color investigations through cross-site consistent and accurate measurements collected by autonomous radiometer systems deployed on offshore fixed platforms. The AERONET-OC data products are the normalized water-leaving radiances determined at various center wavelengths in the visible and near-infrared spectral regions. These data complement atmospheric AERONET aerosol products, such as optical thickness, size distribution, single scattering albedo, and phase function. This work describes in detail this new AERONET component and its specific elements including measurement method, instrument calibration, processing scheme, quality assurance, uncertainties, data archive, and products accessibility. Additionally, the atmospheric and bio-optical features of the sites currently included in AERONET-OC are briefly summarized. After illustrating the application of AERONET-OC data to the validation of primary satellite products over a variety of complex coastal waters, recommendations are then provided for the identification of new deployment sites most suitable to support satellite ocean color missions.

The column‐integrated optical properties of aerosol in the central eastern region of Asia and midtropical Pacific were investigated based on Sun/sky radiometer measurements made at Aerosol Robotic Network (AERONET) sites in these regions. Characterization of aerosol properties in the Asian region is important due to the rapid growth of both population and economic activity, with associated increases in fossil fuel combustion, and the possible regional and global climatic impacts of related aerosol emissions. Multiyear monitoring over the complete annual cycle at sites in China, Mongolia, South Korea, and Japan suggest spring and/or summer maximum in aerosol optical depth (τ_a) and a winter minimum; however, more monitoring is needed to establish accurate climatologies. The annual cycle of Angstrom wavelength exponent (α) showed a springtime minimum associated with dust storm activity; however, the monthly mean α_440–870 was >0.8 even for the peak dust season at eastern Asian sites suggesting that fine mode pollution aerosol emitted from population centers in eastern Asia dominates the monthly aerosol optical influence even in spring as pollution aerosol mixes with coarse mode dust originating in western source regions. Aerosol optical depth peaks in spring in the tropical mid‐Pacific Ocean associated with seasonal shifts in atmospheric transport from Asia, and ∼35% of the springtime τ_a500 enhancement occurs at altitudes above 3.4 km. For predominately fine mode aerosol pollution cases, the average midvisible (∼550 nm) single scattering albedo (ω₀) at two continental urban sites in China averaged ∼0.89, while it was significantly higher, ∼0.93, at two relatively rural coastal sites in South Korea and Japan. Differences in fine mode absorption between these regions may result from a combination of factors including aerosol aging during transport, relative humidity differences, sea salt at coastal sites, and fuel type and combustion differences in the two regions. For cases where τ_a was predominately coarse mode dust aerosol in the spring of 2001, the absorption was greater in eastern Asia compared to the source regions, with ω₀ at Dunhuang, China (near to the major Taklamakan dust source), ∼0.04 higher than at Beijing at all wavelengths, and Anmyon, South Korea, showing an intermediate level of absorption. Possible reasons for differences in dust absorption magnitude include interactions between dust and fine mode pollution aerosol and also variability of dust optical properties from different source regions in China and Mongolia.

Aerosol mixtures composed of coarse mode desert dust combined with fine mode combustion generated aerosols (from fossil fuel and biomass burning sources) were investigated at three locations that are in and/or downwind of major global aerosol emission source regions. Multiyear monitoring data at Aerosol Robotic Network sites in Beijing (central eastern China), Kanpur (Indo‐Gangetic Plain, northern India), and Ilorin (Nigeria, Sudanian zone of West Africa) were utilized to study the climatological characteristics of aerosol optical properties. Multiyear climatological averages of spectral single scattering albedo (SSA) versus fine mode fraction (FMF) of aerosol optical depth at 675 nm at all three sites exhibited relatively linear trends up to ∼50% FMF. This suggests the possibility that external linear mixing of both fine and coarse mode components (weighted by FMF) dominates the SSA variation, where the SSA of each component remains relatively constant for this range of FMF only. However, it is likely that a combination of other factors is also involved in determining the dynamics of SSA as a function of FMF, such as fine mode particles adhering to coarse mode dust. The spectral variation of the climatological averaged aerosol absorption optical depth (AAOD) was nearly linear in logarithmic coordinates over the wavelength range of 440–870 nm for both the Kanpur and Ilorin sites. However, at two sites in China (Beijing and Xianghe), a distinct nonlinearity in spectral AAOD in logarithmic space was observed, suggesting the possibility of anomalously strong absorption in coarse mode aerosols increasing the 870 nm AAOD.