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Retrieval of microphysical properties of desert dust and volcanic ash aerosols from ground-based remote sensing
Retrieval of microphysical properties of desert dust and volcanic ash aerosols from ground-based remote sensing
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.
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Gasteiger, Josef Konrad
2011
English
Universitätsbibliothek der Ludwig-Maximilians-Universität München
Gasteiger, Josef Konrad (2011): Retrieval of microphysical properties of desert dust and volcanic ash aerosols from ground-based remote sensing. Dissertation, LMU München: Faculty of Physics
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Abstract

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.