This paper aims to investigate the feasibility of a Ku-band and Ka-band spaceborne/airborne dual-wavelength radar algorithm to discriminate various phase states of precipitating hydrometeors. A phase-state classification algorithm has been developed from the radar measurements of snow, mixed phase, and rain obtained from stratiform storms. The algorithm, which is presented in the form of a lookup table that links the Ku-band radar reflectivity and dual-frequency ratio to the phase states of hydrometeors, is checked by applying it to the measurements of the Jet Propulsion Laboratory, California Institute of Technology, using Airborne Precipitation Radar Second Generation (APR-2). In creating the statistically based phase lookup table, the attenuation-corrected (or true) radar reflectivity factors are employed, leading to better accuracy in determining the hydrometeor phase. In practice, however, the true radar reflectivity is not always available before the phase states of the hydrometeors are determined. Therefore, it is desirable to make use of the measured radar reflectivity in classifying the phase states. To do this, phase identification that uses only measured radar reflectivity is proposed. The procedure is then tested using APR-2 airborne radar data. The analysis of the classification results in stratiform rain indicates that the regions of snow, mixed phase, and rain derived from the phase identification algorithm coincide reasonably well with those determined from the measured radar reflectivity and linear depolarization ratio.
['Liang Liao', 'Robert Meneghini']
A Dual-Wavelength Radar Technique to Detect Hydrometeor Phases