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Scattering Computations of Snow Aggregates From Simple Geometrical Particle Models

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4 Author(s)
Liang Liao ; Goddard Earth Sciences Technology and Research, Morgan State University, Greenbelt, ; Robert Meneghini ; Holly Kreutzer Nowell ; Guosheng Liu

Scattering results from snowflakes generated from aggregates comprised of 6-branch bullet rosette crystals are compared with those obtained from spherical or spheroidal ice-air mixed phase particles. The scattering parameters of the aggregates are computed by the discrete dipole approximation (DDA) numerical approach at frequencies from 10.65 to 183.31 GHz (where the particular frequencies match those of the Global Precipitation Measurement (GPM) Microwave Imager (GMI) and Dual-frequency Precipitation Radar (DPR)). Two mass density models are used to specify the snow density of the simple geometrical particles. In one model, the density is prescribed as a function of the maximum dimension of the aggregates (variable snow density model); in the other the density is independent of particle size (fixed snow density model). Comparisons of the results indicate that the scattering parameters of large complex aggregates differ significantly from those obtained from the equivalent-mass spherical/spheroidal-shaped particles when variable snow density is assumed. In contrast to the variable snow density model, the scattering properties of the aggregates are fairly well reproduced by the fixed snow density model. Although the results from a fixed snow densities between 0.2 and 0.3 g/cm3 reveal good overall agreement with those from the aggregates, the value of 0.2 g/cm3 yields the best agreement for the frequencies less than or equal to 35.6 GHz while the model results with a density set to 0.3 g/cm3 show the best match with the aggregates at frequencies higher than 35.6 GHz. Moreover, scattering parameters of the randomly-oriented spheroidal ice-air mixtures tend to agree better with those from the aggregates than do spherical snow particles. It is anticipated that these findings will have direct implication for the development of the GPM algorithms for estimates of precipitation rate.

Published in:

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  (Volume:6 ,  Issue: 3 )