Assessment of cloud-related fine-mode AOD enhancements based on AERONET SDA product

AERONET (AErosol RObotic NETwork), which is a network of ground-based sun photometers, produces a data product called the aerosol spectral deconvolution algorithm (SDA) that utilizes spectral total aerosol optical depth (AOD) data to infer the component fine- and coarse-mode optical depths at 500 nm...

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Published in:Atmospheric Chemistry and Physics
Main Authors: A. Arola, T. F. Eck, H. Kokkola, M. R. A. Pitkänen, S. Romakkaniemi
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2017
Subjects:
Online Access:https://doi.org/10.5194/acp-17-5991-2017
https://doaj.org/article/82a9c062828f40a1bc85b1b13473be84
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spelling ftdoajarticles:oai:doaj.org/article:82a9c062828f40a1bc85b1b13473be84 2023-05-15T13:07:08+02:00 Assessment of cloud-related fine-mode AOD enhancements based on AERONET SDA product A. Arola T. F. Eck H. Kokkola M. R. A. Pitkänen S. Romakkaniemi 2017-05-01T00:00:00Z https://doi.org/10.5194/acp-17-5991-2017 https://doaj.org/article/82a9c062828f40a1bc85b1b13473be84 EN eng Copernicus Publications http://www.atmos-chem-phys.net/17/5991/2017/acp-17-5991-2017.pdf https://doaj.org/toc/1680-7316 https://doaj.org/toc/1680-7324 1680-7316 1680-7324 doi:10.5194/acp-17-5991-2017 https://doaj.org/article/82a9c062828f40a1bc85b1b13473be84 Atmospheric Chemistry and Physics, Vol 17, Iss 9, Pp 5991-6001 (2017) Physics QC1-999 Chemistry QD1-999 article 2017 ftdoajarticles https://doi.org/10.5194/acp-17-5991-2017 2022-12-31T04:19:13Z AERONET (AErosol RObotic NETwork), which is a network of ground-based sun photometers, produces a data product called the aerosol spectral deconvolution algorithm (SDA) that utilizes spectral total aerosol optical depth (AOD) data to infer the component fine- and coarse-mode optical depths at 500 nm. Based on its assumptions, SDA identifies cloud optical depth as the coarse-mode AOD component and therefore effectively computes the fine-mode AOD also in mixed cloud–aerosol observations. Therefore, it can be argued that the more representative AOD for fine-mode fraction should be based on all direct sun measurements and not only on those cloud screened for clear-sky conditions, i.e., on those from level 1 (L1) instead of level 2 (L2) in AERONET. The objective of our study was to assess, including all the available AERONET sites, how the fine-mode AOD is enhanced in cloudy conditions, contrasting SDA L1 and L2 in our analysis. Assuming that the cloud screening correctly separates the cloudy and clear-sky conditions, then the increases in fine-mode AOD can be due to various cloud-related processes, mainly by the strong hygroscopic growth of particles in the vicinity of clouds and in-cloud processing leading to growth of accumulation mode particles. We estimated these cloud-related enhancements in fine-mode AOD seasonally and found, for instance, that in June–August season the average over all the AERONET sites was 0.011, when total fine-mode AOD from L2 data was 0.154; therefore, the relative enhancement was 7 %. The enhancements were largest, both absolutely and relatively, in East Asia; for example, in June–August season the absolute and relative differences in fine-mode AOD, between L1 and L2 measurements, were 0.022 and 10 %, respectively. Corresponding values in North America and Europe were about 0.01 and 6–7 %. In some highly polluted areas, the enhancement is greater than these regional averages, e.g., in Beijing region and in June–July–August (JJA) season the corresponding absolute values were about 0.1. It ... Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Atmospheric Chemistry and Physics 17 9 5991 6001
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Physics
QC1-999
Chemistry
QD1-999
spellingShingle Physics
QC1-999
Chemistry
QD1-999
A. Arola
T. F. Eck
H. Kokkola
M. R. A. Pitkänen
S. Romakkaniemi
Assessment of cloud-related fine-mode AOD enhancements based on AERONET SDA product
topic_facet Physics
QC1-999
Chemistry
QD1-999
description AERONET (AErosol RObotic NETwork), which is a network of ground-based sun photometers, produces a data product called the aerosol spectral deconvolution algorithm (SDA) that utilizes spectral total aerosol optical depth (AOD) data to infer the component fine- and coarse-mode optical depths at 500 nm. Based on its assumptions, SDA identifies cloud optical depth as the coarse-mode AOD component and therefore effectively computes the fine-mode AOD also in mixed cloud–aerosol observations. Therefore, it can be argued that the more representative AOD for fine-mode fraction should be based on all direct sun measurements and not only on those cloud screened for clear-sky conditions, i.e., on those from level 1 (L1) instead of level 2 (L2) in AERONET. The objective of our study was to assess, including all the available AERONET sites, how the fine-mode AOD is enhanced in cloudy conditions, contrasting SDA L1 and L2 in our analysis. Assuming that the cloud screening correctly separates the cloudy and clear-sky conditions, then the increases in fine-mode AOD can be due to various cloud-related processes, mainly by the strong hygroscopic growth of particles in the vicinity of clouds and in-cloud processing leading to growth of accumulation mode particles. We estimated these cloud-related enhancements in fine-mode AOD seasonally and found, for instance, that in June–August season the average over all the AERONET sites was 0.011, when total fine-mode AOD from L2 data was 0.154; therefore, the relative enhancement was 7 %. The enhancements were largest, both absolutely and relatively, in East Asia; for example, in June–August season the absolute and relative differences in fine-mode AOD, between L1 and L2 measurements, were 0.022 and 10 %, respectively. Corresponding values in North America and Europe were about 0.01 and 6–7 %. In some highly polluted areas, the enhancement is greater than these regional averages, e.g., in Beijing region and in June–July–August (JJA) season the corresponding absolute values were about 0.1. It ...
format Article in Journal/Newspaper
author A. Arola
T. F. Eck
H. Kokkola
M. R. A. Pitkänen
S. Romakkaniemi
author_facet A. Arola
T. F. Eck
H. Kokkola
M. R. A. Pitkänen
S. Romakkaniemi
author_sort A. Arola
title Assessment of cloud-related fine-mode AOD enhancements based on AERONET SDA product
title_short Assessment of cloud-related fine-mode AOD enhancements based on AERONET SDA product
title_full Assessment of cloud-related fine-mode AOD enhancements based on AERONET SDA product
title_fullStr Assessment of cloud-related fine-mode AOD enhancements based on AERONET SDA product
title_full_unstemmed Assessment of cloud-related fine-mode AOD enhancements based on AERONET SDA product
title_sort assessment of cloud-related fine-mode aod enhancements based on aeronet sda product
publisher Copernicus Publications
publishDate 2017
url https://doi.org/10.5194/acp-17-5991-2017
https://doaj.org/article/82a9c062828f40a1bc85b1b13473be84
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_source Atmospheric Chemistry and Physics, Vol 17, Iss 9, Pp 5991-6001 (2017)
op_relation http://www.atmos-chem-phys.net/17/5991/2017/acp-17-5991-2017.pdf
https://doaj.org/toc/1680-7316
https://doaj.org/toc/1680-7324
1680-7316
1680-7324
doi:10.5194/acp-17-5991-2017
https://doaj.org/article/82a9c062828f40a1bc85b1b13473be84
op_doi https://doi.org/10.5194/acp-17-5991-2017
container_title Atmospheric Chemistry and Physics
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