Analysis of sub-micron parameters derived from multi-altitude and multi-spectral AOD measurements acquired during the 2009 PAM-ARCMIP airborne campaign

A series of Arctic sunphotometry flights were analyzed in terms of their multi-altitude, sub-micron (fine mode) information content. A spectral deconvolution algorithm (SDA) and a fine mode curvature algorithm (FMC) were applied to extract fine mode and coarse mode optical depth as well as the effective radius of the fine mode as a function of altitude. The fine mode optical depth was differentiated as a function of altitude to retrieve vertical profiles of fine mode extinction coefficient. These optical results were compared with volumetric altitude profiles of fine mode particle size distribution acquired by a UHSAS (Ultra High Sensitivity Aerosol Spectrometer).The results showed that layer-averaged extinction cross sections derived from the ratio of fine mode optical depth to integrated UHSAS number density were significantly larger than extinction cross sections derived from the application of Mie theory to the UHSAS particle size distributions. Vertical profiles of extinction coefficients derived from altitude derivatives of the fine mode optical depth profiles showed some correlation with the UHSAS extinction coefficients. Profiles of the fine mode effective radius retrieved from the sunphotometry data were generally of similar magnitude to columnar averages of the UHSAS radii but no significant trend with altitude could be detected. An example was given of a high altitude smoke plume whose presence eliminated any hope of correlating the volumetric sampling information with the sunphotometer profiles. This is simply a statement of the obvious; that the atmospheric state must be stable in order to make such comparisons.

► We compared multi-altitude microphysical (UHSAS) and optical (sunphotometry) data.
► Extinction coefficients from sunphotometry correlated with UHSAS extinction coefficients.
► Effective radii from microphysical and sunphotometry data were comparable.