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Sizing ice hydrometeor populations using the dual-wavelength radar ratio

Abstract. Dual-wavelength (3.2 and 0.32 cm, i.e., X- and W-radar bands) radar ratio (DWR) measurements in ice clouds and precipitation using Canada's National Research Council Institute for Aerospace Research airborne radar are compared to closely collocated particle microphysical
in situ sampling data in order to develop relations between DWR and characteristic hydrometeor size. This study uses the radar and in situ data
sets collected during the In-Cloud ICing and Large-drop Experiment (ICICLE) campaign in midlatitude frontal clouds. Since atmospheric particle
scattering at X band is predominantly in the Rayleigh regime and the W-band frequency is the highest frequency usually used for hydrometeor remote
sensing, the X–W-band combination provides a relatively strong dual-wavelength reflectivity difference. This study considers radar and in situ
measurements conducted in relatively homogeneous cloud and precipitation conditions. Measurements show that under these conditions, the difference
between the X-band radar reflectivities observed with vertical and horizontal pointing of the radar beam are generally small and often
negligible. However, W-band reflectivities at vertical beam pointing are, on average, larger than those for horizontal beam pointing by
about 4 dB, which is a non-Rayleigh scattering effect from preferentially oriented non-spherical particles. A horizontal radar beam DWR–mean volume particle size relation, Dv, provides robust estimates of this characteristic size for populations of particles with
different habits. Uncertainties of Dv retrievals using DWR are around 0.6 mm when Dv is greater than approximately
1 mm. Size estimates using vertical radar beam DWRs have larger uncertainties due to smaller dual-wavelength signals and stronger influences
of hydrometeor habits and orientations at this geometry of beam pointing. Mean relations among different characteristic sizes, which describe the
entire particle size distribution (PSD), such as Dv, and other sizes used in various applications (e.g., the mean, effective, and median
sizes) are derived, so the results of this study can be used for estimating different PSD characteristic sizes.
