In situ observations from research aircraft and instrumented ground sites are important contributions to developing our collective understanding of clouds and are used to inform and validate numerical weather and climate models. Unfortunately, biases in these datasets may be present, which can limit their value. In this paper, we discuss artefacts which may bias data from a widely used family of instrumentation in the field of cloud physics, optical array probes (OAPs). Using laboratory and synthetic datasets, we demonstrate how greyscale analysis can be used to filter data, constraining the sample volume of the OAP and improving data quality, particularly at small sizes where OAP data are considered unreliable

- "Sebastian J. O’Shea1, Jonathan Crosier1,2, James Dorsey1,2, Waldemar Schledewitz1, Ian Crawford1, Stephan Borrmann3,4, Richard Cotton5, and Aaron Bansemer6"