Retrieval of microphysical properties of desert dust and volcanic ash aerosols from ground-based remote sensing
Beschreibung
vor 12 Jahren
Aerosol particles are important constituents of the Earth's
atmosphere. To quantify effects of aerosol particles, their
distribution and properties need to be known. An important tool for
the provision of such information is remote sensing. This thesis
covers vertically-resolving remote sensing by lidar and
vertically-integrating remote sensing by photometer, and thereby
considers desert dust aerosols which cause a major uncertainty in
climate forecasts, as well as volcanic ash aerosols which, in
addition, are relevant for the flight safety of jet-driven
aircrafts. Both aerosol types consist of ensembles of particles of
varying size, shape, and chemical composition. This thesis aims to
improve the retrieval of the physical properties of such mixtures
from remote sensing observations, in particular by using Bayesian
approaches and improved aerosol models. Three types of retrievals
were developed. The first retrieval type applies to lidar
observations, assumes spheroidal particle shapes, and is based on a
Bayesian Monte-Carlo-approach. It was applied to observations of a
pure volcanic ash plume from Iceland on 17 April 2010 over Maisach
(Germany) for the retrieval of the mass concentration of the ash
particles. The second retrieval type applies to photometer
observations in the solar aureole, uses a pre-defined set of
ensembles of irregularly-shaped particles, and was applied to
observations of the same ash plume. Both methods consistently
retrieved a maximum ash mass concentration of about 1.1 milligram
per cubic meter over Maisach with an uncertainty range from 0.7 to
1.5 milligram per cubic meter. The third retrieval type searches
for ensembles that agree with the observations from both remote
sensing techniques; it uses a pre-defined set of ensembles derived
from the aerosol database OPAC, but consisting of absorbing and
non-absorbing irregularly-shaped particles. This approach was
successfully applied to Saharan dust observations, which were
performed during the SAMUM field campaigns in Morocco and on the
Cape Verde islands. It turned out that, besides the particle shape,
also the presence of non-absorbing components strongly influences
the backscattering properties of the aerosols. In contrast, aureole
radiances are hardly sensitive to particle shape and chemical
composition, thus aureole radiances are well-suited for the
retrieval of the size of ash and dust particles. It is expected
that the accuracy of the retrievals further improves if all
parameters observed by photometer are considered.
atmosphere. To quantify effects of aerosol particles, their
distribution and properties need to be known. An important tool for
the provision of such information is remote sensing. This thesis
covers vertically-resolving remote sensing by lidar and
vertically-integrating remote sensing by photometer, and thereby
considers desert dust aerosols which cause a major uncertainty in
climate forecasts, as well as volcanic ash aerosols which, in
addition, are relevant for the flight safety of jet-driven
aircrafts. Both aerosol types consist of ensembles of particles of
varying size, shape, and chemical composition. This thesis aims to
improve the retrieval of the physical properties of such mixtures
from remote sensing observations, in particular by using Bayesian
approaches and improved aerosol models. Three types of retrievals
were developed. The first retrieval type applies to lidar
observations, assumes spheroidal particle shapes, and is based on a
Bayesian Monte-Carlo-approach. It was applied to observations of a
pure volcanic ash plume from Iceland on 17 April 2010 over Maisach
(Germany) for the retrieval of the mass concentration of the ash
particles. The second retrieval type applies to photometer
observations in the solar aureole, uses a pre-defined set of
ensembles of irregularly-shaped particles, and was applied to
observations of the same ash plume. Both methods consistently
retrieved a maximum ash mass concentration of about 1.1 milligram
per cubic meter over Maisach with an uncertainty range from 0.7 to
1.5 milligram per cubic meter. The third retrieval type searches
for ensembles that agree with the observations from both remote
sensing techniques; it uses a pre-defined set of ensembles derived
from the aerosol database OPAC, but consisting of absorbing and
non-absorbing irregularly-shaped particles. This approach was
successfully applied to Saharan dust observations, which were
performed during the SAMUM field campaigns in Morocco and on the
Cape Verde islands. It turned out that, besides the particle shape,
also the presence of non-absorbing components strongly influences
the backscattering properties of the aerosols. In contrast, aureole
radiances are hardly sensitive to particle shape and chemical
composition, thus aureole radiances are well-suited for the
retrieval of the size of ash and dust particles. It is expected
that the accuracy of the retrievals further improves if all
parameters observed by photometer are considered.
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