Present methods of passive and active microwave remote sensing of precipitation have a key problem: the uncertainty of the physical and associated radiative properties of ice- and mixed-phase hydrometeors. In nature, ice particles manifest themselves in an extraordinarily diverse variety of sizes, shapes, and habits -- ranging from simple crystals such as needles or plates to complex aggregates and rimed particles. As these complex particles fall into air that is warmer than freezing, they begin to melt. While the general thermodynamic and fluid mechanics aspects of melting snowflakes is fairly well understood, the complex interaction with incident microwave radiation remains largely unexplored. This area of research is attempting to address one of the largest sources of uncertainly in physically-based precipitation retrieval algorithms using microwave observations (e.g., radar / radiometer).

In this presentation, I will talk about simulated microphysical properties of a variety of ice- and mixed-phase precipitation particles, with particular emphasis on simulating the melting morphology of ice-phase particles, such as snowflake aggregates. There are three distinct parts to this research:

(1) Physical modeling, i.e., growing and simulating snowflake shapes, sizes, etc., in a way that is consistent with observations.
(2) Electromagnetic wave scattering -- how an incident plane wave (microwave -> submillimeter wavelengths) interacts with individual snow particles, and the general sensitivity of that interaction to the various physical properties.
(3) Sensitivity of observable quantities, such as radar reflectivity and passive microwave brightness temperatures to variations in the physical properties of the snow clouds being observed.

I will describe my efforts towards the above problem, and highlight the work of our group as we head towards a snowfall retrieval algorithm for the upcoming Global Precipitation Measurement mission (GPM), set to launch in 2014.

Location: Physics Bldg., Room 401