Articles | Volume 9, issue 1
https://doi.org/10.5194/amt-9-9-2016
https://doi.org/10.5194/amt-9-9-2016
Research article
 | 
15 Jan 2016
Research article |  | 15 Jan 2016

The microwave properties of simulated melting precipitation particles: sensitivity to initial melting

B. T. Johnson, W. S. Olson, and G. Skofronick-Jackson

Abstract. A simplified approach is presented for assessing the microwave response to the initial melting of realistically shaped ice particles. This paper is divided into two parts: (1) a description of the Single Particle Melting Model (SPMM), a heuristic melting simulation for ice-phase precipitation particles of any shape or size (SPMM is applied to two simulated aggregate snow particles, simulating melting up to 0.15 melt fraction by mass), and (2) the computation of the single-particle microwave scattering and extinction properties of these hydrometeors, using the discrete dipole approximation (via DDSCAT), at the following selected frequencies: 13.4, 35.6, and 94.0 GHz for radar applications and 89, 165.0, and 183.31 GHz for radiometer applications. These selected frequencies are consistent with current microwave remote-sensing platforms, such as CloudSat and the Global Precipitation Measurement (GPM) mission. Comparisons with calculations using variable-density spheres indicate significant deviations in scattering and extinction properties throughout the initial range of melting (liquid volume fractions less than 0.15). Integration of the single-particle properties over an exponential particle size distribution provides additional insight into idealized radar reflectivity and passive microwave brightness temperature sensitivity to variations in size/mass, shape, melt fraction, and particle orientation.

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Short summary
This research explores, through simulations, how a realistically shaped snowflake aggregate begins the melting process and how microwave-based satellite observations are sensitive to those initial stages of melting. Using highly detailed physical models, and high-precision numerical models, we can accurately simulate the sensitivity of observations to this critical transition from dry snow to melting snow. This research improves on existing models, providing an accurate measurement basis.