Abstract

Abstract Vertically pointing Ka-band radar measurements are used to derive fall velocity–reflectivity factor () relations for frozen hydrometeor populations of different habits during snowfall events observed at Oliktok Point, Alaska, and at the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC). Case study events range from snowfall with highly rimed particles observed during periods with large amounts of supercooled liquid water path (LWP > 320 g m−2) to unrimed snowflakes including instances when pristine planar crystals were the dominant frozen hydrometeor habit. The prefactor a and the exponent b in the observed Vt–Ze relations scaled to the sea level vary in the approximate ranges 0.5–1.4 and 0.03–0.13, respectively (reflectivities are in mm6 m−3 and velocities are in m s−1). The coefficient a values are the smallest for planar crystals (a ∼ 0.5) and the largest (a > 1.2) for particles under severe riming conditions with high LWP. There is no clear distinction between b values for high and low LWP conditions. The range of the observed Vt–Ze relation coefficients is in general agreement with results of modeling using fall velocity–size (υt = αDβ) relations for individual particles found in literature for hydrometeors of different habits, though there is significant variability in α and β coefficients from different studies even for a same particle habit. Correspondences among coefficients in the Vt–Ze relations for particle populations and in the individual particle υt–D relations are analyzed. These correspondences and the observed Vt–Ze relations can be used for evaluating different frozen hydrometeor fall velocity parameterizations in models. Significance Statement Frozen hydrometeor fall velocities influence cloud life cycles and the moisture transport in the atmosphere. The knowledge of these velocities is also needed to enhance remote sensing of snowfall parameters. In this study, the relations between fall velocities and radar reflectivities of snowflakes of different types and shapes are quantitively analyzed using observations with vertically pointing radars.

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