Potential of polarization lidar to provide profiles of CCN-and INP-relevant aerosol parameters
We investigate the potential of polarization lidar to provide vertical profiles of aerosol parameters from which cloud condensation nucleus (CCN) and ice nucleating particle (INP) number concentrations can be estimated. We show that height profiles of particle number concentrations n50, dry consider...
Main Authors: | , |
---|---|
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
München : European Geopyhsical Union
2016
|
Subjects: | |
Online Access: | https://dx.doi.org/10.34657/1205 https://oa.tib.eu/renate/handle/123456789/946 |
id |
ftdatacite:10.34657/1205 |
---|---|
record_format |
openpolar |
spelling |
ftdatacite:10.34657/1205 2023-05-15T13:07:13+02:00 Potential of polarization lidar to provide profiles of CCN-and INP-relevant aerosol parameters Mamouri, Rodanthi-Elisavet Ansmann, Albert 2016 application/pdf https://dx.doi.org/10.34657/1205 https://oa.tib.eu/renate/handle/123456789/946 en eng München : European Geopyhsical Union Creative Commons Attribution 3.0 Unported CC BY 3.0 Unported https://creativecommons.org/licenses/by/3.0/legalcode cc-by-3.0 CC-BY AERONET aerosol cloud condensation nucleus concentration composition extinction coefficient lidar nucleation parameterization size distribution surface area vertical profile 550 CreativeWork article 2016 ftdatacite https://doi.org/10.34657/1205 2022-03-10T12:43:22Z We investigate the potential of polarization lidar to provide vertical profiles of aerosol parameters from which cloud condensation nucleus (CCN) and ice nucleating particle (INP) number concentrations can be estimated. We show that height profiles of particle number concentrations n50, dry considering dry aerosol particles with radius > 50 nm (reservoir of CCN in the case of marine and continental non-desert aerosols), n100, dry (particles with dry radius > 100 nm, reservoir of desert dust CCN), and of n250, dry (particles with dry radius > 250 nm, reservoir of favorable INP), as well as profiles of the particle surface area concentration sdry (used in INP parameterizations) can be retrieved from lidar-derived aerosol extinction coefficients σ with relative uncertainties of a factor of 1.5–2 in the case of n50, dry and n100, dry and of about 25–50 % in the case of n250, dry and sdry. Of key importance is the potential of polarization lidar to distinguish and separate the optical properties of desert aerosols from non-desert aerosol such as continental and marine particles. We investigate the relationship between σ, measured at ambient atmospheric conditions, and n50, dry for marine and continental aerosols, n100, dry for desert dust particles, and n250, dry and sdry for three aerosol types (desert, non-desert continental, marine) and for the main lidar wavelengths of 355, 532, and 1064 nm. Our study is based on multiyear Aerosol Robotic Network (AERONET) photometer observations of aerosol optical thickness and column-integrated particle size distribution at Leipzig, Germany, and Limassol, Cyprus, which cover all realistic aerosol mixtures. We further include AERONET data from field campaigns in Morocco, Cabo Verde, and Barbados, which provide pure dust and pure marine aerosol scenarios. By means of a simple CCN parameterization (with n50, dry or n100, dry as input) and available INP parameterization schemes (with n250, dry and sdry as input) we finally compute profiles of the CCN-relevant particle number concentration nCCN and the INP number concentration nINP. We apply the method to a lidar observation of a heavy dust outbreak crossing Cyprus and a case dominated by continental aerosol pollution. Article in Journal/Newspaper Aerosol Robotic Network DataCite Metadata Store (German National Library of Science and Technology) |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
topic |
AERONET aerosol cloud condensation nucleus concentration composition extinction coefficient lidar nucleation parameterization size distribution surface area vertical profile 550 |
spellingShingle |
AERONET aerosol cloud condensation nucleus concentration composition extinction coefficient lidar nucleation parameterization size distribution surface area vertical profile 550 Mamouri, Rodanthi-Elisavet Ansmann, Albert Potential of polarization lidar to provide profiles of CCN-and INP-relevant aerosol parameters |
topic_facet |
AERONET aerosol cloud condensation nucleus concentration composition extinction coefficient lidar nucleation parameterization size distribution surface area vertical profile 550 |
description |
We investigate the potential of polarization lidar to provide vertical profiles of aerosol parameters from which cloud condensation nucleus (CCN) and ice nucleating particle (INP) number concentrations can be estimated. We show that height profiles of particle number concentrations n50, dry considering dry aerosol particles with radius > 50 nm (reservoir of CCN in the case of marine and continental non-desert aerosols), n100, dry (particles with dry radius > 100 nm, reservoir of desert dust CCN), and of n250, dry (particles with dry radius > 250 nm, reservoir of favorable INP), as well as profiles of the particle surface area concentration sdry (used in INP parameterizations) can be retrieved from lidar-derived aerosol extinction coefficients σ with relative uncertainties of a factor of 1.5–2 in the case of n50, dry and n100, dry and of about 25–50 % in the case of n250, dry and sdry. Of key importance is the potential of polarization lidar to distinguish and separate the optical properties of desert aerosols from non-desert aerosol such as continental and marine particles. We investigate the relationship between σ, measured at ambient atmospheric conditions, and n50, dry for marine and continental aerosols, n100, dry for desert dust particles, and n250, dry and sdry for three aerosol types (desert, non-desert continental, marine) and for the main lidar wavelengths of 355, 532, and 1064 nm. Our study is based on multiyear Aerosol Robotic Network (AERONET) photometer observations of aerosol optical thickness and column-integrated particle size distribution at Leipzig, Germany, and Limassol, Cyprus, which cover all realistic aerosol mixtures. We further include AERONET data from field campaigns in Morocco, Cabo Verde, and Barbados, which provide pure dust and pure marine aerosol scenarios. By means of a simple CCN parameterization (with n50, dry or n100, dry as input) and available INP parameterization schemes (with n250, dry and sdry as input) we finally compute profiles of the CCN-relevant particle number concentration nCCN and the INP number concentration nINP. We apply the method to a lidar observation of a heavy dust outbreak crossing Cyprus and a case dominated by continental aerosol pollution. |
format |
Article in Journal/Newspaper |
author |
Mamouri, Rodanthi-Elisavet Ansmann, Albert |
author_facet |
Mamouri, Rodanthi-Elisavet Ansmann, Albert |
author_sort |
Mamouri, Rodanthi-Elisavet |
title |
Potential of polarization lidar to provide profiles of CCN-and INP-relevant aerosol parameters |
title_short |
Potential of polarization lidar to provide profiles of CCN-and INP-relevant aerosol parameters |
title_full |
Potential of polarization lidar to provide profiles of CCN-and INP-relevant aerosol parameters |
title_fullStr |
Potential of polarization lidar to provide profiles of CCN-and INP-relevant aerosol parameters |
title_full_unstemmed |
Potential of polarization lidar to provide profiles of CCN-and INP-relevant aerosol parameters |
title_sort |
potential of polarization lidar to provide profiles of ccn-and inp-relevant aerosol parameters |
publisher |
München : European Geopyhsical Union |
publishDate |
2016 |
url |
https://dx.doi.org/10.34657/1205 https://oa.tib.eu/renate/handle/123456789/946 |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_rights |
Creative Commons Attribution 3.0 Unported CC BY 3.0 Unported https://creativecommons.org/licenses/by/3.0/legalcode cc-by-3.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.34657/1205 |
_version_ |
1766040529262346240 |