A Multi-Probe Automated Classification of Ice Crystal Habits During the IMPACTS Campaign

While no two ice crystals are identical within clouds, ice crystals can be broadly classified into specific categories based on their shapes, otherwise known as habits. Rates of microphysical processes for a given crystal, including accretion, sedimentation, and sublimation, as well as light absorption and scattering, are dependent on habit, meaning that an accurate understanding of how habits depend on environmental conditions and cloud formation mechanisms would improve the treatment of processes within mixed and ice phase clouds in weather and climate models. Expected habits can be approximated using temperature and ice supersaturation; however, habits do not always match this approximation as crystals are advected through regions with varying atmospheric conditions.

Although it is impossible to image every single ice crystal within a cloud, a representative sample of crystal images can be attained using aircraft in-situ cloud imaging probes, such as the Two-Dimensional Stereo Probe (2DS), the High-Volume Precipitation Spectrometer (HVPS), and the Particle Habit Imaging and Polar Scattering probe (PHIPS). Many crystal images were collected using these probes during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS), conducted in January and February of 2020, 2022, and 2023 over the Northeast U.S.

This study assesses the successes and limitations of a relatively simple habit classification algorithm using data from the IMPACTS campaign. The algorithm determines habit by running through a series of decisions based on crystal morphological properties, including, but not limited to, crystal area (A), perimeter (p) and maximum dimension (D). Compared to a machine learning approach, this method likely has lower accuracy, with an overall accuracy of ~80% for the PHIPS, and ~70% for the 2DS and HVPS, but is easier to understand, and is thought to be more easily adaptable to different probes and field campaigns. Seven habit classes are used: column, sphere, dendrite, plate, aggregate, graupel, and irregular, with accuracies calculated using a set of manually pre-classified images (100 from each habit class).

One novel aspect of this work is the comparison of habit classifications from two different probes, the 2DS and PHIPS, that image within the same size range. Moderate correspondence between the probes was noted. Given that different field campaigns may utilize different probes, it is important to understand how different probes and/or classification methods might affect habit classifications when comparing habits across multiple field campaigns. Another unique contribution of this study is the determination of particle habits for crystals with D > 1 mm from the HVPS probe, as habit information for particles of larger sizes is not readily available. Using a combination of 2DS and HVPS data, microphysical habits of ice crystals with D > 300 µm are related to mesoscale cloud features using two case studies from IMPACTS. The first is a heavy band of snowfall associated with a nor’easter on February 7, 2020. The second is an area of moderately deep convection wrapping around the center of a relatively warm-core cyclone off the U.S. East Coast on January 15, 2023. Potential relationships between habits and these mesoscale cloud features are discussed.