The AERONET Version 3 aerosol retrieval algorithm, associated uncertainties and comparisons to Version 2
<p>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...
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Copernicus Publications
2020-06-01
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language |
English |
format |
Article |
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author |
A. Sinyuk A. Sinyuk B. N. Holben T. F. Eck T. F. Eck D. M. Giles D. M. Giles I. Slutsker I. Slutsker S. Korkin S. Korkin J. S. Schafer J. S. Schafer A. Smirnov A. Smirnov M. Sorokin M. Sorokin A. Lyapustin |
spellingShingle |
A. Sinyuk A. Sinyuk B. N. Holben T. F. Eck T. F. Eck D. M. Giles D. M. Giles I. Slutsker I. Slutsker S. Korkin S. Korkin J. S. Schafer J. S. Schafer A. Smirnov A. Smirnov M. Sorokin M. Sorokin A. Lyapustin The AERONET Version 3 aerosol retrieval algorithm, associated uncertainties and comparisons to Version 2 Atmospheric Measurement Techniques |
author_facet |
A. Sinyuk A. Sinyuk B. N. Holben T. F. Eck T. F. Eck D. M. Giles D. M. Giles I. Slutsker I. Slutsker S. Korkin S. Korkin J. S. Schafer J. S. Schafer A. Smirnov A. Smirnov M. Sorokin M. Sorokin A. Lyapustin |
author_sort |
A. Sinyuk |
title |
The AERONET Version 3 aerosol retrieval algorithm, associated uncertainties and comparisons to Version 2 |
title_short |
The AERONET Version 3 aerosol retrieval algorithm, associated uncertainties and comparisons to Version 2 |
title_full |
The AERONET Version 3 aerosol retrieval algorithm, associated uncertainties and comparisons to Version 2 |
title_fullStr |
The AERONET Version 3 aerosol retrieval algorithm, associated uncertainties and comparisons to Version 2 |
title_full_unstemmed |
The AERONET Version 3 aerosol retrieval algorithm, associated uncertainties and comparisons to Version 2 |
title_sort |
aeronet version 3 aerosol retrieval algorithm, associated uncertainties and comparisons to version 2 |
publisher |
Copernicus Publications |
series |
Atmospheric Measurement Techniques |
issn |
1867-1381 1867-8548 |
publishDate |
2020-06-01 |
description |
<p>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 <span class="inline-formula">NO<sub>2</sub></span> and <span class="inline-formula">H<sub>2</sub>O</span> 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<span class="inline-formula"><sup>∘</sup></span> to as small as 25<span class="inline-formula"><sup>∘</sup></span>. The comparison of SSA retrievals from closely
time-matched HYB and ALM scans in the 50 to 75<span class="inline-formula"><sup>∘</sup></span> SZA range showed good agreement with the differences below <span class="inline-formula">∼0.005</span>. 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)<span id="page3376"/> 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.</p> |
url |
https://www.atmos-meas-tech.net/13/3375/2020/amt-13-3375-2020.pdf |
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doaj-ba68b2547e754617837e9f7ab7af9fdc2020-11-25T02:58:02ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482020-06-01133375341110.5194/amt-13-3375-2020The AERONET Version 3 aerosol retrieval algorithm, associated uncertainties and comparisons to Version 2A. Sinyuk0A. Sinyuk1B. N. Holben2T. F. Eck3T. F. Eck4D. M. Giles5D. M. Giles6I. Slutsker7I. Slutsker8S. Korkin9S. Korkin10J. S. Schafer11J. S. Schafer12A. Smirnov13A. Smirnov14M. Sorokin15M. Sorokin16A. Lyapustin17Science Systems and Applications, Inc. (SSAI), Lanham, MD 20706, USANASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USANASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USANASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USAUniversities Space Research Association (USRA), Columbia, MD 21046, USAScience Systems and Applications, Inc. (SSAI), Lanham, MD 20706, USANASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USAScience Systems and Applications, Inc. (SSAI), Lanham, MD 20706, USANASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USANASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USAUniversities Space Research Association (USRA), Columbia, MD 21046, USAScience Systems and Applications, Inc. (SSAI), Lanham, MD 20706, USANASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USAScience Systems and Applications, Inc. (SSAI), Lanham, MD 20706, USANASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USAScience Systems and Applications, Inc. (SSAI), Lanham, MD 20706, USANASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USANASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USA<p>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 <span class="inline-formula">NO<sub>2</sub></span> and <span class="inline-formula">H<sub>2</sub>O</span> 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<span class="inline-formula"><sup>∘</sup></span> to as small as 25<span class="inline-formula"><sup>∘</sup></span>. The comparison of SSA retrievals from closely time-matched HYB and ALM scans in the 50 to 75<span class="inline-formula"><sup>∘</sup></span> SZA range showed good agreement with the differences below <span class="inline-formula">∼0.005</span>. 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)<span id="page3376"/> 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.</p>https://www.atmos-meas-tech.net/13/3375/2020/amt-13-3375-2020.pdf |