Mass of different snow crystal shapes derived from fall speed measurements

Abstract. Meteorological forecast and climate models require good knowledge of the microphysical properties hydrometeors atmospheric snow ice crystals in clouds, for instance, their size, cross-sectional area, shape, mass, fall speed. Especially shape is an important parameter that it strongly affects scattering particles consequently response to remote sensing techniques. The speed mass are other parameters both numerical representation clouds models. In case speed, responsible rate removal from these particle a key quantity connects cloud radiative properties. Using empirical relationship between dimensionless Reynolds Best numbers, can be derived each if size area also known. this study, ground-based situ measurements used analyse as function study were done Kiruna, Sweden, during snowfall seasons 2014 2019 using Dual Ice Crystal Imager (D-ICI) instrument, which takes high-resolution side- top-view images natural hydrometeors. From images, (maximum dimension), individual determined. shape-classified according scheme presented our previous sort into 15 different groups depending on morphology. Particle masses estimated measured selected dataset covers sizes about 0.1 3.2 mm, speeds 1.6 m s?1, 0.2 450 µg. relationships studied. same determine consequently, studied groups. Furthermore, compared with studies. For certain crystal habits, particular columnar shapes, maximum dimension unsuitable determining number. selection columns, simple geometry allows verification Best-number-to-Reynolds-number relationship, we show number more closely related diameter basal facet than dimension. agreement further improved modified number, ratio based falling seen vertical direction.