Hovering a Microscope on a Drone: Development of UAV Based Systems for High-resolution Imaging of Falling Snow

From single crystal formation high in the atmosphere down to precipitating snowfalls at ground level no snowflake takes the same path through the air column. During descent snow-crystals grow, coalesce, break, and rime into graupel while interacting with the surrounding air. Among the well-studied effects of temperature and humidity super-saturation, the specific role of the various turbulence activities throughout the atmosphere remains elusive. This work uses uncrewed aerial vehicles (UAVs) as a flexible platform to study snowfall up to 120 meters above ground level during their most ‘turbulent end-of-lifetime’ as they descend through the atmospheric surface layer. The work is twofold. Firstly, a smaller commercially available DJI Mavic3E quadcopter equipped with an onboard telelens and CZZI GL10 searchlight is used to gather aerial photography of snowfall 3 meters away from the drone. Automated flight paths executed in an hourly deployment scan the air column and harvest 13407 snowflakes from 3351 images taken during nighttime experiments. Building on previous ground-imaging studies, we extract snowflake metrics for size, aspect ratio, complexity, and orientation angle at a 160μm-per-pixel image resolution. Our data suggests that snowflakes of high aspect ratio tend to glide in horizontal orientation while interacting with the turbulent atmosphere. Mapping our data over various height positions we find an overall 30% percent variability in snowflake growth, while variation in shape is found less prominent. Secondly, we present developments on an airborne microscopy system to shed further light on the intricate details of the snowflakes concerning their freefall behavior. Equipping a larger DJI Matrice600Pro hexacopter capable of carrying a 6kg payload with an Infinity K2-Distamax long-range microscope telescopic lens we increase the image resolution by a factor of ten and reach 16μm-per-pixel. We will present the various subsystems involved in imaging snowflakes outside the drone's flow envelope, including synchronizing a pulsed LED circuit to compensate for the large image distance and low numeric aperture. We will present the first snowflakes captured in freefall during the start of the 2024 snow season to demonstrate the feasibility of our airborne microscopy system in hovering flight.