2A.2 Snow Retrieval by Ku- and Ka-band Dual-Frequency Radar

Monday, 14 September 2015: 1:45 PM
University AB (Embassy Suites Hotel and Conference Center )
Liang Liao, Morgan State Univ., Greenbelt, MD; and R. Meneghini, A. Tokay, and J. Torres

Accurate estimates of snow microphysical properties and its bulk parameters such as snow water content and snowfall rate have been a great challenge to active and passive microwave sensors because of the complex geometric shapes and composite structures that snow particles can assume and also because of the variability in snow particle size/mass distributions (PSD). To develop an effective snow retrieval algorithm, it is important to know the uncertainties associated with the scattering properties of individual particles and the PSD models. The degree of the retrieval accuracy, however, depends on the methods used and sensor frequencies employed. The aim of this study is to explore a suitable scattering model and a proper PSD assumption in estimates of snow micro/macro-physical properties for the dual-frequency radar operating at frequencies of 13.6 GHz (Ku-band) and 35.6 GHz (Ka-band), particularly for the Dual-frequency Precipitation Radar (DPR) aboard the Global Precipitation Measurement (GPM) core satellite.

We start with comparisons of the radar scattering parameters from simple particle models and more realistic complex simulated aggregates in an attempt to find computationally-efficient scattering models that can be used to accurately reproduce the scattering parameters obtained from the simulated aggregates. For computations of aggregate scattering, a numerical method is required. Many numerical schemes are available to obtain various scattering parameters of particles with arbitrary shapes and compositions. These methods, however, are generally computationally intensive, and are therefore limited to small-to-moderate particle sizes and to a few frequencies. To develop an operational radar algorithm for estimates of snow, it is necessary to employ a scattering model that enables efficient computation at an arbitrary frequency over a large range of particle sizes. Analysis of the comparisons of the scattering results from simple to complicated snow models indicates that the scattering properties of aggregates are fairly well reproduced by randomly-oriented ellipsoidal particles if the effective mass density of snow is the constant with size and takes on a value between 0.2 and 0.3 g/cm³. The T-matrix method, which provides a very effective means to compute the scattering parameters of the ellipsoidal particles, will be used in this study.

Using an effective snow scattering model, a study of the dual-wavelength technique that employs the differential frequency ratio (DFR) of the Ku- and Ka-band radar reflectivities and the Ku-band reflectivity will be carried out for snow estimates. An analysis of the retrieval uncertainties associated with the PSD model and the particle scattering model such as the aspect ratio of ellipsoidal particles and effective particle mass density, will be performed in order to improve snow retrieval accuracy. To aid in the development of the Ku- and Ka-band dual-wavelength radar technique and to further evaluate its performance, measurements of the snow size distribution and fall velocity acquired from the Precipitation Image Probe (PIP) and the Two-dimensional Video Disdrometer (2DVD) will be used in our study.

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