Abstract
Abstract. 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.
Highlights
The optical properties of particles in the Earth’s atmosphere are measured or retrieved from numerous platforms, including space-based, airborne and surface-based monitoring instruments
The Aerosol Robotic Network (AERONET) (Holben et al, 1998) of globally distributed ground-based instruments has provided the basis for total column aerosol optical properties that are required for satellite validation purposes and for some algorithms the specification of particular aerosol optical properties that must be assumed in the retrieval algorithms
Satellite validation has been mainly focused on aerosol optical depth (AOD), and accurate AERONET measurements of this parameter have been utilized for numerous satellite instruments and algorithms (Sayer et al, 2018, 2019; Levy et al, 2013, 2015; Holzer-Popp et al, 2013; Lyapustin et al, 2018; Kahn et al, 2010; Limbacher et al, 2019; Ahn et al, 2014; Choi et al, 2018)
Summary
The optical properties of particles in the Earth’s atmosphere are measured or retrieved from numerous platforms, including space-based, airborne (or suborbital) and surface-based monitoring instruments. Analysis of aerosol black carbon in the global atmosphere and its effects on radiative forcing by Bond et al (2013) utilized AERONET retrievals of SSA and the imaginary refractive index as one of many individual data sets of the spatial distribution of aerosol absorption. Very few direct comparisons of size distribution between in situ and AERONET retrievals have been published, several aerosol microphysical and optical parameters have been compared in specific regions: size of the fine-mode aerosols (e.g., Schafer et al, 2019; Reid et al, 2005 (South America, southern Africa, and North America); Clarke et al, 2002 (pollution in the Arabian Sea)) and size of larger sub-micron aerosols (e.g., Eck et al, 2010 (stratospheric aerosols); Reid et al, 2006 (sea salt), 2008a (desert dust); Smirnov et al, 2003 (maritime aerosol); Johnson and Osborne, 2011 (Sahel region of western Africa)).
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