Abstract. This work provides a synopsis of aerosol phase function (F11) and
polarized phase function (F12) measurements made by the Polarized
Imaging Nephelometer (PI-Neph) during the Studies of Emissions,
Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys
(SEAC4RS) and the Deep Convection Clouds and Chemistry (DC3) field
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 include trace gases, chemical composition, aerodynamic particle
size and geographic location, all independent of PI-Neph measurements. The
PI-Neph 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 F11
and -F12/F11 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 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 cases 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 data classification as well as the
PI-Neph's ability to distinguish common aerosol types without additional
information.