Zhibo Zhang, Ph.D.

Assistant Professor

Physics Department

University of Maryland, Baltimore County

Tel:  (410) 455-6315

Fax: (410) 455-1072

E-mail: zhibo.zhang@umbc.edu

Web:http://userpages.umbc.edu/~zzbatmos/research

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Clouds have a critical role in Earth’s energy budget and hydrological cycle through their strong radiative effects and interactions with aerosols, precipitation and water vapor. However, our current understanding of clouds, especially regarding to how clouds are connected to the environments and how clouds will change with the global warming, is still highly limited. To improve our understanding of clouds, satellite-based, long-term, global cloud observations are indispensable tools. One stream of my research is geared toward a better understanding of the microphysical and optical properties of clouds using a variety of satellite data and modeling tools.

It is of fundamental importance for remote sensing and climate studies to understand how atmospheric particles, such as cloud particles and aerosols, interact with incoming radiation from either the sun or satellite instruments. During my Ph.D. with Prof. Ping Yang at Texas A&M University, I developed great interests in numerical simulation of the single-scattering properties of nonspherical particles. Ice particle scattering properties computed using my model have now been widely used in satellite-based remote sensing of ice clouds. Currently my interest in this area focuses on the polarization signatures of light scattering by ice particles and aerosols.

Recent advances in aerosol-cloud interaction are mainly propelled by satellite remote sensing and by progress in numerical cloud simulation. Coordinated passive and active observations have enabled researchers, for the first time, to observe the 3-D structure of clouds and precipitation. The cloud simulation models, such as the large-eddy simulation models, are flexible and powerful tools for testing hypotheses and formulating theories. However, both satellite remote sensing and cloud models face some inherent limitations. Satellite retrievals are plagued by uncertainties and artifacts caused by, for example, 3-D radiative effects. Meanwhile, a key difficulty faced by cloud models is to elaborate the connection between the simulated clouds and the clouds in nature. Owing largely to such limitations, some outstanding problems in aerosol-cloud interaction remain frustratingly unclear, especially problems regarding the role of precipitation in the interaction.

A synergistic combination of satellite remote sensing and the cloud resolving model has the potential to better explain the aerosol-cloud interactions. Such a combination enables the simulation of satellite retrievals based on realistic and constrained cloud fields from cloud models; through this type of simulation, we can identify artifacts and quantify uncertainties in satellite retrievals. Combining satellite remote sensing with the cloud resolving model also provides a viable means to assess the representativeness of the simulated cloud fields from cloud models through comparison of the simulated satellite retrieval with operational products.

LWP

radar dBZ

Together with light scattering theory, radiative transfer is another pillar for remote sensing. during my Ph.D., I developed a fast infrared radiative transfer model to facilitate ice cloud properties retrievals using high-spectral resolution sounders, such as AIRS. Currently, I am particularly interested in 3D radiative transfer, 3D radiative effects on cloud remote sensing, and radiative perturbation theory.

Parallax-effect

1-D simulation

3-D simulation

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