4.4 Article

How Snow Aggregate Ellipsoid Shape and Orientation Variability Affects Fall Speed and Self-Aggregation Rates

Journal

JOURNAL OF THE ATMOSPHERIC SCIENCES
Volume 78, Issue 1, Pages 51-73

Publisher

AMER METEOROLOGICAL SOC
DOI: 10.1175/JAS-D-20-0128.1

Keywords

Atmosphere; Snow; Winter; cool season; Cloud microphysics; Spectral analysis; models; distribution; Cloud parameterizations

Funding

  1. U.S. Department of Energy's Atmospheric Science Program Atmospheric System Research, an Office of Science, Office of Biological and Environmental Research program [DE-SC0018933]
  2. NOAA/Office of Oceanic and Atmospheric Research [NA16OAR4320115]
  3. NSF [1841246]
  4. U.S. Department of Commerce
  5. Div Atmospheric & Geospace Sciences
  6. Directorate For Geosciences [1841246] Funding Source: National Science Foundation
  7. U.S. Department of Energy (DOE) [DE-SC0018933] Funding Source: U.S. Department of Energy (DOE)

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This study develops an analytic framework to capture the effects of snow aggregate shape variations on mass, projected areas, and fall speeds by coupling an empirically based bivariate distribution of ellipsoid shapes with classical hydrodynamic theory. It is found that shape variations of aggregates can significantly increase fall speed dispersion, affecting self-aggregation rates and mass, potentially requiring secondary ice formation to prevent the process from being terminated.
Snow aggregate shapes and orientations have long been known to exhibit substantial variability. Despite this observed variability, most weather and climate prediction models use fixed power-law functions that deterministically map particle size to mass and fall speed. As such, integrated quantities like precipitation and self-aggregation rates currently ignore nonlinear effects resulting from variation in shape and orientation for aggregates of the same size. This study therefore develops an analytic framework that couples an empirically based bivariate distribution of ellipsoid shapes to classical hydrodynamic theory so as to capture an appropriate dispersion of masses, projected areas, and fall speeds for an assumed size distribution. For a fixed aggregate size, shape variations produce approximately +/- 0.13 m s(-1) standard deviation of fall speed which increases the mass flux fall speed dispersion by more than 100% over traditional microphysics models. This increased fall speed dispersion results predominantly from shape-induced mass dispersion whereas orientation and drag dispersion play a lesser role. Shape variations can increase mass- and reflectivity-weighted fall speeds by up to 60% of traditional models whereas self-aggregation rates can increase by a factor of 100 for very small slope parameters. This implies that aggregate shape variations effectively forestall the theorized onset of fall speed distribution narrowing and subsequent quenching of the aggregation process. As a result, it is likely that secondary ice formation is necessary to prevent an ever decreasing slope parameter. The mathematical theory presented in this study is used to develop simple correction factors for snow forecast and climate models.

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