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

Li successfully defended her dissertation on March 15, 2013.

TITLE:
Determination of the single scattering albedo and direct radiative forcing of biomass burning aerosol with data from the MODIS (Moderate Resolution Imaging Spectroradiometer) satellite instrument

ABSTRACT:
Biomass burning aerosols absorb and scatter solar radiation and therefore affect the energy balance of the Earth-atmosphere system. The single scattering albedo (SSA), the ratio of the scattering coefficient to the extinction coefficient, is an important parameter to describe the optical properties of aerosols and to determine the effect of aerosols on the energy balance of the planet and climate. Aerosol effects on radiation also depend strongly on surface albedo. Large uncertainties remain in current estimates of radiative impacts of biomass burning aerosols, due largely to the lack of reliable measurements of aerosol and surface properties. In this work we investigate how satellite measurements can be used to estimate the direct radiative forcing of biomass burning aerosols. We developed a method using the critical reflectance technique to retrieve SSA from the Moderate Resolution Imaging Spectroradiometer (MODIS) observed reflectance at the top of the atmosphere (TOA). We evaluated MODIS retrieved SSAs with AErosol RObotic NETwork (AERONET) retrievals and found good agreements within the published uncertainty of the AERONET retrievals. We then developed an algorithm, the MODIS Enhanced Vegetation Albedo (MEVA), to improve the representations of spectral variations of vegetation surface albedo based on MODIS observations at the discrete 0.67, 0.86, 0.47, 0.55, 1.24, 1.64, and 2.12 µm channels. This algorithm is validated using laboratory measurements of the different vegetation types from the Amazon region, data from the Johns Hopkins University (JHU) spectral library, and data from the U.S. Geological Survey (USGS) digital spectral library. We show that the MEVA method can improve the accuracy of flux and aerosol forcing calculations at the TOA compared to more traditional interpolated approaches. Lastly, we combine the MODIS retrieved biomass burning aerosol SSA and the surface albedo spectrum determined from the MEVA technique to calculate TOA flux and aerosol direct radiative forcing over the Amazon region and compare it with Clouds and the Earth's Radiant Energy System (CERES) satellite results. The results show that MODIS based forcing calculations present similar averaged results compared to CERES, but MODIS shows greater spatial variation of aerosol forcing than CERES. Possible reasons for these differences are explored and discussed in this work. Potential future research based on these results is discussed as well.