Ground-based measurements on aerosol particles microphysical properties at Cabo Verde from 2008 to 2017

In this study, we describe the methods used to collect and analyze aerosol microphysical properties (PNSD, light absorption coefficient, CCN number concentration, particle hygroscopicity) and air mass origins.

An unsupervised machine learning algorithm was used to classify particle types. The aim of this study was to understand the abundance and sources of aerosol particles and CCN in a dust-marine intersect environment. The long-term data and knowledge concerning aerosol microphysical properties gained in this study will help to better understand the interactions between aerosol particles and clouds and represent highly valuable information for evaluating, driving and constraining atmospheric model simulations.