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.
The possibility of using shape mixtures of randomly oriented spheroids for modeling desert dust aerosol light scattering is discussed. For reducing calculation time, look‐up tables were simulated for ...quadrature coefficients employed in the numerical integration of spheroid optical properties over size and shape. The calculations were done for 25 bins of the spheroid axis ratio ranging from ∼0.3 (flattened spheroids) to ∼3.0 (elongated spheroids) and for 41 narrow size bins covering the size parameter range from ∼0.012 to ∼625. The look‐up tables were arranged into a software package, which allows fast, accurate, and flexible modeling of scattering by randomly oriented spheroids with different size and shape distributions. In order to evaluate spheroid model and explore the possibility of aerosol shape identification, the software tool has been integrated into inversion algorithms for retrieving detailed aerosol properties from laboratory or remote sensing polarimetric measurements of light scattering. The application of this retrieval technique to laboratory measurements by Volten et al. (2001) has shown that spheroids can closely reproduce mineral dust light scattering matrices. The spheroid model was utilized for retrievals of aerosol properties from atmospheric radiation measured by AERONET ground‐based Sun/sky‐radiometers. It is shown that mixtures of spheroids allow rather accurate fitting of measured spectral and angular dependencies of observed intensity and polarization. Moreover, it is shown that for aerosol mixtures with a significant fraction of coarse‐mode particles (radii ≥ ∼1 μm), the nonsphericity of aerosol particles can be detected as part of AERONET retrievals. The retrieval results indicate that nonspherical particles with aspect ratios ∼1.5 and higher dominate in desert dust plumes, while in the case of background maritime aerosol spherical particles are dominant. Finally, the potential of using AERONET derived spheroid mixtures for modeling the effects of aerosol particle nonsphericity in other remote sensing techniques is discussed. For example, the variability of lidar measurements (extinction to backscattering ratio and signal depolarization ratio) is illustrated and analyzed. Also, some potentially important differences in the sensitivity of angular light scattering to parameters of nonspherical versus spherical aerosols are revealed and discussed.
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.
Aerosol radiative forcing is a critical, though variable and uncertain, component of the global climate. Yet climate models rely on sparse information of the aerosol optical properties.
In the Aerosol Robotic Network (AERONET) retrieval algorithm, smoothness constraints on the imaginary part of the refractive index provide control of retrieved spectral dependence of aerosol ...absorption by preventing the inversion code from fitting the noise in optical measurements and thus avoiding unrealistic oscillations of retrievals with wavelength. The history of implementation of the smoothness constraints in the AERONET retrieval algorithm is discussed. It is shown that the latest version of the smoothness constraints on the imaginary part of refractive index, termed standard and employed by Version 3 of the retrieval algorithm, should be modified to account for strong variability of light absorption by brown-carbon-containing aerosols in UV through mid-visible parts of the solar spectrum. In Version 3 strong spectral constraints were imposed at high values of the Ångström exponent (440–870 nm) since black carbon was assumed to be the primary absorber, while the constraints became increasingly relaxed as aerosol exponent deceased to allow for wavelength dependence of absorption for dust aerosols. The new version of the smoothness constraints on the imaginary part of the refractive index assigns different weights to different pairs of wavelengths, which are the same for all values of the Ångström exponent. For example, in the case of four-wavelength input, the weights assigned to short-wavelength pairs (440–675, 675–870 nm) are small so that smoothness constraints do not suppress natural spectral variability of the imaginary part of the refractive index. At longer wavelengths (870–1020 nm), however, the weight is 10 times higher to provide additional constraints on the imaginary part of refractive index retrievals of aerosols with a high Ångström exponent due to low sensitivity to aerosol absorption for longer channels at relatively low aerosol optical depths. The effect of applying the new version of smoothness constraints, termed relaxed, on retrievals of single-scattering albedo is analyzed for case studies of different aerosol types: black- and brown-carbon-containing fine mode aerosols, mineral dust coarse mode aerosols, and urban industrial fine mode aerosol. It is shown that for brown-carbon-containing aerosols employing the relaxed smoothness constraints resulted in significant reduction in retrieved single-scattering albedo and spectral residual errors (compared to standard) at the short wavelengths. For example, biomass burning smoke cases showed a reduction in single-scattering albedo and spectral residual error at 380 nm of ∼ 0.033 and ∼ 17 %, respectively, for the Rexburg site and ∼ 0.04 and ∼ 12.7 % for the Rimrock site, both AERONET sites in Idaho, USA. For a site with very high levels of black-carbon-containing aerosols (Mongu, Zambia), the effect of modification in the smoothness constraints was minor. For mineral dust aerosols at small Ångström exponent values (Mezaira site, UAE), the spectral constraint on the imaginary part of the refractive index was already relaxed in Version 3; therefore the new relaxed constraint results in minimal change. In the case of weakly absorbing urban industrial aerosols at the GSFC site, there are significant changes in retrieved single-scattering albedo using relaxed assumption, especially reductions at longer wavelengths: ∼ 0.016 and ∼ 0.02 at 875 and 1020 nm, respectively, for 440 nm aerosol optical depth (AOD) ∼ 0.3. The modification of smoothness constraints on the imaginary part of the refractive index has a minor effect on retrievals of other aerosol parameters such as the real part of the refractive index and parameters of the aerosol size distribution. The implementation of the relaxed smoothness constraints on the imaginary part of the refractive index in the next version of the AERONET inversion algorithm will produce significant impacts at some sites in short wavelength channels (380 and 440 nm) for some biomass burning smoke cases with significant brown carbon content and possibly in mid-visible channels (500 and 675 nm) to near-infrared channels (870 to 1020 nm) for some urban industrial aerosol types. However, most differences in single-scattering albedo retrievals between those applying the new relaxed constraint and the standard constraint will be within the uncertainty of the single-scattering albedo retrievals, depending on the level of aerosol optical depth, Ångström exponent, brown carbon content and wavelength.
With the launch of the MODIS sensor on the Terra spacecraft, new data sets of the global distribution and properties of aerosol are being retrieved, and need to be validated and analyzed. A system ...has been put in place to generate spatial statistics (mean, standard deviation, direction and rate of spatial variation, and spatial correlation coefficient) of the MODIS aerosol parameters over more than 100 validation sites spread around the globe. Corresponding statistics are also computed from temporal subsets of AERONET‐derived aerosol data. The means and standard deviations of identical parameters from MODIS and AERONET are compared. Although, their means compare favorably, their standard deviations reveal some influence of surface effects on the MODIS aerosol retrievals over land, especially at low aerosol loading. The direction and rate of spatial variation from MODIS are used to study the spatial distribution of aerosols at various locations either individually or comparatively. This paper introduces the methodology for generating and analyzing the data sets used by the two MODIS aerosol validation papers in this issue.
We present an analysis of the effect of aerosol forward scattering on the accuracy of aerosol optical depth (AOD) measured by CIMEL Sun photometers. The effect is quantified in terms of AOD and solar ...zenith angle using radiative transfer modeling. The analysis is based on aerosol size distributions derived from multi‐year climatologies of AERONET aerosol retrievals. The study shows that the modeled error is lower than AOD calibration uncertainty (0.01) for the vast majority of AERONET level 2 observations, ∼99.53%. Only ∼0.47% of the AERONET database corresponding mostly to dust aerosol with high AOD and low solar elevations has larger biases. We also show that observations with extreme reductions in direct solar irradiance do not contribute to level 2 AOD due to low Sun photometer digital counts below a quality control cutoff threshold.
Key Points
Assessment of AERONET AOD errors due to aerosol forward scattering
Systematic characterization of aerosol over the oceans is needed to understand the aerosol effect on climate and on transport of pollutants between continents. Reported are the results of a ...comprehensive optical and physical characterization of ambient aerosol in five key island locations of the Aerosol Robotic Network (AERONET) of sun and sky radiometers, spanning over 2-5 yr.
Aerosol volume size distribution (VSD) retrievals from the Aerosol Robotic Network (AERONET) aerosol monitoring network were obtained during multiple DRAGON (Distributed Regional Aerosol Gridded ...Observational Network) campaigns conducted in Maryland, California, Texas and Colorado from 2011 to 2014. These VSD retrievals from the field campaigns were used to make comparisons with near-simultaneous in situ samples from aircraft profiles carried out by the NASA Langley Aerosol Group Experiment (LARGE) team as part of four campaigns comprising the DISCOVER-AQ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality) experiments. For coincident (1 h) measurements there were a total of 91 profile-averaged fine-mode size distributions acquired with the LARGE ultra-high sensitivity aerosol spectrometer (UHSAS) instrument matched to 153 AERONET size distributions retrieved from almucantars at 22 different ground sites. These volume size distributions were characterized by two fine-mode parameters, the radius of peak concentration (rpeak_conc) and the VSD fine-mode width (widthpeak_conc). The AERONET retrievals of these VSD fine-mode parameters, derived from ground-based almucantar sun photometer data, represent ambient humidity values while the LARGE aircraft spiral profile retrievals provide dried aerosol (relative humidity; RH< 20 %) values. For the combined multiple campaign dataset, the average difference in rpeak_conc was 0:0330:035 μm (ambient AERONET values were 15.8% larger than dried LARGE values), and the average difference in widthpeak_conc was 0:0420:039 μm (AERONET values were 25.7% larger). For a subset of aircraft data, the LARGE data were adjusted to account for ambient humidification. For these cases, the AERONET–LARGE average differences were smaller, with rpeak_conc differing by 0:0110:019 μm (AERONET values were 5.2% larger) and widthpeak_conc average differences equal to 0:0300:037 μm (AERONET values were 15.8% larger).
Cloud optical depth is one of the most poorly observed climate variables. The new “cloud mode” capability in the Aerosol Robotic Network (AERONET) will inexpensively yet dramatically increase cloud ...optical depth observations in both number and accuracy. Cloud mode optical depth retrievals from AERONET were evaluated at the Atmospheric Radiation Measurement program's Oklahoma site in sky conditions ranging from broken clouds to overcast. For overcast cases, the 1.5 min average AERONET cloud mode optical depths agreed to within 15% of those from a standard ground‐based flux method. For broken cloud cases, AERONET retrievals also captured rapid variations detected by the microwave radiometer. For 3 year climatology derived from all nonprecipitating clouds, AERONET monthly mean cloud optical depths are generally larger than cloud radar retrievals because of the current cloud mode observation strategy that is biased toward measurements of optically thick clouds. This study has demonstrated a new way to enhance the existing AERONET infrastructure to observe cloud optical properties on a global scale.
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