Closing the Gap: An Algorithmic Approach to Reconciling In-Situ and Remotely Sensed Aerosol Particle Properties

Abstract. Remote sensors such as lidars and polarimeters are increasingly being used to understand atmospheric aerosol particles and their role in critical cloud and marine boundary layer processes. Therefore, it is essential to ensure these instruments' retrievals of aerosol optical and microphysical properties are consistent with measurements taken by in-situ instruments (i.e., external closure). However, achieving rigorous external closure is challenging because in-situ instruments often 1) provide dry (relative humidity (RH) < 40 %) aerosol measurements while remote sensors typically provide retrievals in ambient conditions and 2) only sample a limited aerosol particle size range due to aircraft sampling inlet cutoffs. To address these challenges, we introduce the e In Situ Aerosol Retrieval Algorithm (ISARA) in the form of a Python toolkit that converts dry in-situ aerosol data into ambient, humidified data and accounts for the contribution of coarse-mode aerosol particles in its retrievals. We apply ISARA to the NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) field campaign data set to perform a preliminary consistency analysis of this campaign's aerosol measurements. Specifically, we compare ISARA-calculated ambient aerosol properties with corresponding measurements from 1) ACTIVATE's in-situ instruments (i.e., internal consistency), 2) Monte Carlo in-situ data simulations (i.e., synthetic consistency), and 3) ACTIVATE's Second Generation High Spectral Resolution Lidar (HSRL-2) and Research Scanning Polarimeter (RSP) instruments (i.e., external consistency). This study demonstrates that 1) appropriate a priori assumptions for aerosol particles lead to consistency between in-situ measurements and remote sensing retrievals in the ACTIVATE campaign, 2) ambient aerosol properties retrieved from dry in-situ and the RSP polarimetric data are shown to be consistent for the first time in literature, 3) measurements are externally consistent even when moderately absorbing (imaginary refractive index (IRI) > 0.015) aerosol is present, and 4) ISARA is limited by probable under-sampling of coarse-mode particles in its calculations. The overall success of this preliminary consistency analysis shows that ISARA can enable systematic, streamlined closure of field campaign aircraft aerosol data sets at large.