sulia221

Kara Sulia

Ice Crystal Growth Theory, Numerical Cloud Modeling, Arctic Stratiform Cloud Evolution, Mid-Latitude Winter Storms, Microphysical Impacts on Clouds and Climate, Polarimetric Radar Verification Techniques

The World Within Reach
Kara Sulia
Research Associate
 

Department: Atmospheric Sciences Research Center

Address:
CESTM L106
Phone:
518-437-8755

 

Education

B.S., Meteorology, Penn State University, 2009
Ph.D., Meteorology, Penn State University, 2013

Research Interests

Dr. Sulia's work within ice microphysics focuses on crystal growth theory as a means to improve microphysical parameterizations within numerical models. Ice particles grow in interesting and complex fashions, and the mechanisms of vapor diffusional growth are highly dependent on the myriad of ice crystal shapes that occur within the atmosphere. Ice crystal shape can have important impacts on mixed-phase cloud evolution and lifetime, precipitation rates, and surface radiative and energy budgets which can affect surface temperatures, and when in the Arctic, sea-ice extent. Ice particle shape also impacts collection processes, such as riming and aggregation, which enhance surface precipitation. Improving the representation of these processes is critical for accurate predictions of precipitation, especially in winter storms. Recent and continuing upgrades of North American radars to dual-polarization  provides

Publications

Sulia, K., J.Y. Harrington, and H. Morrison, 2014: Dynamical and microphysical evolution during mixed-phase cloud glaciation simulated using the bulk adaptive habit prediction model. Journal of the Atmospheric Sciences, early online release, doi: 10.1175/JAS-D-14- 0070.1.

Ovchinnikov, M., A.S. Ackerman, A. Avramov, A. Cheng, J. Fan, A.M. Fridlind, S. Ghan, J.Y. Harrington, C. Hoose, A. Korolev, G.M. McFarquhar, H. Morrison, M. Paukert, J. Savre, B. Shipway, M.D. Shupe, A. Solomon and K. Sulia, 2014: Intercomparison of large-eddy simulations of Arctic mixed-phase clouds: Importance of ice size distribution assumptions. Journal of Advances in Modeling Earth Systems, 6, doi:10.1002/2013MS000282.

Sulia, K., J. Y. Harrington, and H. Morrison, 2013: A method for adaptive habit prediction in bulk microphysical models: Part III: Applications and studies within a two-dimensional kinematic model. Journal of the Atmospheric Sciences, 70 (10), 3302-3320, doi: 10.1175/JAS-D-12-0316.1.

Harrington, J. Y., K. Sulia, and H. Morrison, 2013: A method for adaptive habit prediction in bulk microphysical models: Part I: Theoretical Development. Journal of the Atmospheric Sciences, 70 (2), 349-364.

Harrington, J. Y., K. Sulia, and H. Morrison, 2013: A method for adaptive habit prediction in bulk microphysical models: Part II: Parcel model corroboration. In press, Journal of the Atmospheric Sciences, 70 (2), 365-376.

Morrison, H., G. de Boer, G. Feingold, J. Y. Harrington, M. Shupe, and K. Sulia, 2012: Self- organization and resilience of Arctic mixed-phase clouds. Nature Geoscience, 5, 11-17.

Sulia, K. and J. Y. Harrington, 2011: Ice Aspect Ratio Influences on Mixed-Phase Clouds. Impacts of Phase Partitioning in Parcel Models. Journal of Geophysical Research, 116, D21309.

Ervens, B., G. Feingold, K. Sulia, and J. Y. Harrington, 2011: The Impact of Microphysical parameters, ice nucleation mode, and habit growth on ice/liquid partitioning in mixed-phase Arctic clouds. Journal of Geophysical Research, 116, D17205.

Sheridan, L., J. Y. Harrington, D. Lamb, and K. Sulia, 2009: Influences of ice aspect ratio on the evolution of particle size spectra during vapor depositional growth. Journal of Atmospheric Sciences, 66, 3732-3734.