Abstract:Aerosols of the volcanic degassing plumes from Mt. Etna and Mt. Stromboli were probed with in situ instruments on board the Deutsches Zentrum fur Luft- und Raumfahrt research aircraft Falcon during the contrail, volcano, and cirrus experiment CONCERT in September 2011. Aerosol properties were analyzed using angular-scattering intensities and particle size distributions measured simultaneously with the Polar Nephelometer and the Forward Scattering Spectrometer probes (FSSP series 100 and 300), respectively. Aer… Show more
“…To prevent the first few principal component loadings from being dominated by the large absolute variations in forward scattering intensity the analysis was performed on the natural logarithm of theF 11 values. This transformation produces a set of principal 20 components where the first component, for example, explains the largest possible relative variance in data (Shcherbakov et al, 2016). No transformation was applied to the −F 12 /F 11 measurements.…”
Abstract. This work provides a synopsis of aerosol phase function (F 11 ) and polarized phase function (−F 12 /F 11 ) measurements made by the Polarized Imaging Nephelometer (PI-Neph) during the Studies of Emissions and Atmospheric Composition, campaigns. In order to more easily explore this extensive dataset, an aerosol classification scheme is developed that identifies the different aerosol types measured during the deployments. This scheme makes use of ancillary data that includes trace gases, 5 chemical composition, aerodynamic particle size and geographic location, all independent of PI-Neph measurements. The PINeph measurements are then grouped according to their ancillary data classifications and the resulting scattering patterns are examined in detail. These results represent the first published airborne measurements of F 11 and −F 12 /F 11 for many common aerosol types. We then explore whether PI-Neph light-scattering measurements alone are sufficient to reconstruct the results of this ancillary data classification algorithm. Principal component analysis (PCA) is used to reduce the dimensionality of the 10 multi-angle PI-Neph scattering data and the individual measurements are examined as a function of ancillary data classification.Clear clustering is observed in the PCA score space, corresponding to the ancillary classification results, suggesting that indeed a strong link exists between the angular scattering measurements and the aerosol type or composition. Two techniques are used to quantify the degree of clustering and it is found that in most case the results of the ancillary data classification can be predicted from PI-Neph measurements alone with better than 85% recall. This result both emphasizes the validity of the ancillary 15 data classification as well as the PI-Neph's ability to distinguish common aerosol types without additional information.
“…To prevent the first few principal component loadings from being dominated by the large absolute variations in forward scattering intensity the analysis was performed on the natural logarithm of theF 11 values. This transformation produces a set of principal 20 components where the first component, for example, explains the largest possible relative variance in data (Shcherbakov et al, 2016). No transformation was applied to the −F 12 /F 11 measurements.…”
Abstract. This work provides a synopsis of aerosol phase function (F 11 ) and polarized phase function (−F 12 /F 11 ) measurements made by the Polarized Imaging Nephelometer (PI-Neph) during the Studies of Emissions and Atmospheric Composition, campaigns. In order to more easily explore this extensive dataset, an aerosol classification scheme is developed that identifies the different aerosol types measured during the deployments. This scheme makes use of ancillary data that includes trace gases, 5 chemical composition, aerodynamic particle size and geographic location, all independent of PI-Neph measurements. The PINeph measurements are then grouped according to their ancillary data classifications and the resulting scattering patterns are examined in detail. These results represent the first published airborne measurements of F 11 and −F 12 /F 11 for many common aerosol types. We then explore whether PI-Neph light-scattering measurements alone are sufficient to reconstruct the results of this ancillary data classification algorithm. Principal component analysis (PCA) is used to reduce the dimensionality of the 10 multi-angle PI-Neph scattering data and the individual measurements are examined as a function of ancillary data classification.Clear clustering is observed in the PCA score space, corresponding to the ancillary classification results, suggesting that indeed a strong link exists between the angular scattering measurements and the aerosol type or composition. Two techniques are used to quantify the degree of clustering and it is found that in most case the results of the ancillary data classification can be predicted from PI-Neph measurements alone with better than 85% recall. This result both emphasizes the validity of the ancillary 15 data classification as well as the PI-Neph's ability to distinguish common aerosol types without additional information.
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