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...

Full description

Bibliographic Details
Main Authors: A. Arola, T. F. Eck, H. Kokkola, M. R. A. Pitkänen, S. Romakkaniemi
Format: Article
Language:English
Published: Copernicus Publications 2017-05-01
Series:Atmospheric Chemistry and Physics
Online Access:http://www.atmos-chem-phys.net/17/5991/2017/acp-17-5991-2017.pdf
_version_ 1818343331564879872
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
collection DOAJ
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 is difficult to separate the fine-mode AOD enhancements due to in-cloud processing and hygroscopic growth, but we attempted to get some understanding by conducting a similar analysis for SDA-based fine-mode Ångström exponent (AE) patterns. Moreover, we exploited a cloud parcel model, in order to understand in detail the relative role of different processes. We found that in marine conditions, were aerosol concentration are low and cloud scavenging is efficient, the AE changes in opposite direction than in the more polluted conditions, were hygroscopic growth of particles leads to a negative AE change.
first_indexed 2024-12-13T16:28:53Z
format Article
id doaj.art-82a9c062828f40a1bc85b1b13473be84
institution Directory Open Access Journal
issn 1680-7316
1680-7324
language English
last_indexed 2024-12-13T16:28:53Z
publishDate 2017-05-01
publisher Copernicus Publications
record_format Article
series Atmospheric Chemistry and Physics
spelling doaj.art-82a9c062828f40a1bc85b1b13473be842022-12-21T23:38:33ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242017-05-011795991600110.5194/acp-17-5991-2017Assessment of cloud-related fine-mode AOD enhancements based on AERONET SDA productA. Arola0T. F. Eck1H. Kokkola2M. R. A. Pitkänen3S. Romakkaniemi4Finnish Meteorological Institute, Kuopio, FinlandUniversities Space Research Association, Columbia, MD, USAFinnish Meteorological Institute, Kuopio, FinlandFinnish Meteorological Institute, Kuopio, FinlandFinnish Meteorological Institute, Kuopio, FinlandAERONET (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 is difficult to separate the fine-mode AOD enhancements due to in-cloud processing and hygroscopic growth, but we attempted to get some understanding by conducting a similar analysis for SDA-based fine-mode Ångström exponent (AE) patterns. Moreover, we exploited a cloud parcel model, in order to understand in detail the relative role of different processes. We found that in marine conditions, were aerosol concentration are low and cloud scavenging is efficient, the AE changes in opposite direction than in the more polluted conditions, were hygroscopic growth of particles leads to a negative AE change.http://www.atmos-chem-phys.net/17/5991/2017/acp-17-5991-2017.pdf
spellingShingle 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
Atmospheric Chemistry and Physics
title 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_short 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
url http://www.atmos-chem-phys.net/17/5991/2017/acp-17-5991-2017.pdf
work_keys_str_mv AT aarola assessmentofcloudrelatedfinemodeaodenhancementsbasedonaeronetsdaproduct
AT tfeck assessmentofcloudrelatedfinemodeaodenhancementsbasedonaeronetsdaproduct
AT hkokkola assessmentofcloudrelatedfinemodeaodenhancementsbasedonaeronetsdaproduct
AT mrapitkanen assessmentofcloudrelatedfinemodeaodenhancementsbasedonaeronetsdaproduct
AT sromakkaniemi assessmentofcloudrelatedfinemodeaodenhancementsbasedonaeronetsdaproduct