Peter Brechner

Convective Meteorology ( Mesoscale Dynamics)

Peter Brechner

 Ice Crystal Size Distributions in Atlantic Coast Snowstorms: Results from IMPACTS

April 12, 2024

3:00 pm

NWC 1350

Abstract: In January and February 2020, 2022, and 2023, the Investigation of Microphysics and Precipitation for Atlantic Coast Threatening Snowstorms (IMPACTS) was conducted out of Wallops Island, Virginia to study the banding of precipitation in snowstorms. The NASA Airborne Science Program’s P-3 Orion (N426NA) research aircraft flew inside snow bands between −30°C and 0°C to study the microphysics of these bands. Context of the in-situ cloud particle measurements is provided by the NASA ER-2 (809, 806) aircraft which utilized a High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) and Doppler radar (EXRAD) and flew coordinated with the P-3 on many flights. Installed on the P-3 were a turbulent air motion measurement system (TAMMS) measuring temperature and vertical velocity, a Rosemount icing detector (RICE) identifying supercooled water presence, a Cloud Droplet Probe (CDP) measuring cloud droplet size distributions, a Two-Dimensional Stereo (2D-S) probe and a High
Volume Precipitation Spectrometer (HVPS-3) measuring particle and habit size distributions (PSDs), and a Particle Habit Imaging and Polar Scattering (PHIPS) probe acquiring high-resolution particle images and scattering functions. A phase identification algorithm using data from all of the probes is used to classify each particle at temperatures T < 0°C as ice or supercooled liquid water, calculate the m-D relation for each ice particle habit, and characterize each 1 s time period in flight as ice-phase, liquid-phase, or mixed-phase. For ice PSDs in ice- and mixed-phase clouds, a previously developed fitting routine that automatically determines whether a unimodal, bimodal, or trimodal gamma distribution best fits an observed PSD is used to determine the characteristics of PSDs (e.g., presence of unimodal, bimodal, or trimodal distributions, and gamma fit parameters of each of these distributions characterized by volume of equally realizable parameters to account for variability an
d uncertainty). The dependence of the derived fit parameters and bulk properties (median mass diameter, IWC) on environmental conditions (T, IWC, vertical velocity, storm location, etc.) is characterized and compared against those obtained both in previous studies characterizing winter snowstorms and other meteorological conditions and, in the case of February 7, 2020, in the Predicted Particle Properties (P3) model. The frequency of multimodality increased with T, IWC, and median mass diameter. No patterns were found in the frequency of multimodality with respect to storm classification or vertical velocity. Unimodal gamma fit parameters decreased with median mass diameter, IWC, and T. The implications for the understanding of processes occurring in snow bands are discussed.