The open-source Video In Situ Snowfall Sensor (VISSS) is introduced as a novel instrument for the characterization of particle shape and size in snowfall. The VISSS consists of two cameras with LED backlights and telecentric lenses that allow accurate sizing and combine a large observation volume with relatively high pixel resolution and a design that limits wind disturbance. VISSS data products include various particle properties such as maximum extent, cross-sectional area, perimeter, complexity, and sedimentation velocity. Initial analysis shows that the VISSS provides robust statistics based on up to 10000 unique particle observations per minute. Comparison of the VISSS with the collocated PIP (Precipitation Imaging Package) and Parsivel instruments at Hyytiälä, Finland, shows excellent agreement with the Parsivel but reveals some differences for the PIP that are likely related to PIP data processing and limitations of the PIP with respect to observing smaller particles. The open-source nature of the VISSS hardware plans, data acquisition software, and data processing libraries invites the community to contribute to the development of the instrument, which has many potential applications in atmospheric science and beyond.

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Riming is a key precipitation formation process in mixed-phase clouds which efficiently converts cloud liquid to ice water. Here, we present two methods to quantify riming of ice particles from airborne observations with the normalized rime mass, which is the ratio of rime mass to the mass of a size-equivalent spherical graupel particle. We use data obtained during the HALO-(AC)3 aircraft campaign, where two aircraft collected radar and in situ measurements that were closely spatially and temporally collocated over the Fram Strait west of Svalbard in spring 2022. The first method is based on an inverse optimal estimation algorithm for the retrieval of the normalized rime mass from a closure between cloud radar and in situ measurements during these collocated flight segments (combined method). The second method relies on in situ observations only, relating the normalized rime mass to optical particle shape measurements (in situ method). We find good agreement between both methods during collocated flight segments with median normalized rime masses of 0.024 and 0.021 (mean values of 0.035 and 0.033) for the combined and in situ method, respectively. Assuming that particles with a normalized rime mass smaller than 0.01 are unrimed, we obtain average rimed fractions of 88ĝ€¯% and 87ĝ€¯% over all collocated flight segments. Although in situ measurement volumes are in the range of a few cubic centimeters and are therefore much smaller than the radar volume (about 45ĝ€¯m footprint diameter at an altitude of 500ĝ€¯m above ground, with a vertical resolution of 5ĝ€¯m), we assume they are representative of the radar volume. When this assumption is not met due to less homogeneous conditions, discrepancies between the two methods result. We show the performance of the methods in a case study of a collocated segment of cold-air outbreak conditions and compare normalized rime mass results with meteorological and cloud parameters. We find that higher normalized rime masses correlate with streaks of higher radar reflectivity. The methods presented improve our ability to quantify riming from aircraft observations.

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Observations show that the ice water content (IWC) in mixed-phase clouds (MPCs) tends to occur in clusters. However, it is not sufficiently understood which ice crystal formation and growth processes play a dominant role in IWC clustering in clouds. One important ice growth process is riming, which occurs when liquid water droplets freeze onto ice crystals upon contact. Here we use airborne measurements of MPCs at mid- and high-latitudes to investigate the spatial variability of ice clusters in clouds and how this variability is linked to riming. We use data from the IMPACTS (mid-latitudes) and the HALO-(AC)3 (high-latitudes) aircraft campaigns, where spatially and temporally colocated cloud radar and in situ measurements were collected. We derive riming and IWC by combining cloud radar and in situ measurements. Ice cluster scales in clouds are quantified using pair correlation functions.

During all analyzed flight segments, riming is responsible for 66 % and 63 % of the total IWC during IMPACTS and HALO-(AC)3, respectively. In mid-latitude MPCs, riming does not significantly change IWC cluster scales but increases the probability of cluster occurrence. In cold-air-outbreak MPCs observed during HALO-(AC)3, riming leads to additional in-cloud IWC clustering at spatial scales of 3–5 km due to the presence of mesoscale updraft features. An increased liquid water path might increase the effect, but it is not a necessary criterion. These results can be used to evaluate and constrain models' representations of MPCs.@en