27 May 2024
 | 27 May 2024
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Simulated Particle Evolution within a Winter Storm: Contributions of Riming to Radar Moments and Precipitation Fallout

Andrew DeLaFrance, Lynn McMurdie, Angela Rowe, and Andrew Heymsfield

Abstract. Remote sensing radars from air- and spaceborne platforms provide critical observations of clouds to estimate precipitation rates across the globe. Capability of these radars to detect changes in precipitation properties is advanced by Doppler measurements of particle fall speed. Within mixed-phase clouds, precipitation mass and its fall characteristics are especially sensitive to the effects of riming. In this study, we quantified these effects and investigated the distinction of riming from aggregation in Doppler radar vertical profiles using quasi-idealized particle-based model simulations. Observational constraints of a control simulation were determined from airborne in situ and remote sensing measurements collected during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) for a wintry-mixed precipitation event over the northeast United States on 04 February 2022. From the upper boundary of a one-dimensional column, particle evolution was simulated through vapor deposition, aggregation, and riming processes, producing realistic Doppler radar profiles. Despite a modest observed amount of supercooled liquid water (0.05 g m-3), riming accounted for 55 % of the ice-phase precipitation mass, cumulatively increasing reflectivity by 6.1 dB and Doppler velocity by 0.9 m s-1. Independent evaluation of process-based sensitivities showed that while radar reflectivity is comparably sensitive to either riming- or aggregation-based particle morphology, the Doppler velocity profile is uniquely sensitive to particle density changes during riming. Thus, Doppler velocity profiles advance the diagnosis of riming as a dominant microphysical process in stratiform clouds from single-wavelength radars, which has implications for quantitative constraints of particle properties in remote sensing applications.

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Andrew DeLaFrance, Lynn McMurdie, Angela Rowe, and Andrew Heymsfield

Status: open (until 08 Jul 2024)

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Andrew DeLaFrance, Lynn McMurdie, Angela Rowe, and Andrew Heymsfield
Andrew DeLaFrance, Lynn McMurdie, Angela Rowe, and Andrew Heymsfield


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Short summary
Using a numerical model, the process whereby falling ice crystals accumulate supercooled liquid water droplets is investigated to elucidate its effects on radar-based measurements and surface precipitation. We demonstrate that this process accounted for 55% of the precipitation during a wintertime storm and is uniquely discernable from other ice crystal growth processes in Doppler velocity measurements. These results have implications to measurements from air- and spaceborne platforms.