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Dr. Christopher J. Nowotarski
Christopher J. Nowotarski
(979) 845-3305
Eller O&M 1002A
Texas A&M University
O&M Building, Room 1002A
Department of Atmospheric Sciences
MS 3150
College Station, Texas 77843


Ph.D. Meteorology, Pennsylvania State University

M.S. Meteorology, Pennsylvania State University

B.S. Meteorology, Pennsylvania State University


Christopher J. Nowotarski

Assistant Professor

Research Interests

My research is geared towards developing a better understanding of the structure and dynamics of convective storms in midlatitudes with the ultimate goal of improving prediction of such events and their attendant hazards. Though I am interested in severe convection of all forms, my current research is focused on supercell thunderstorms, particularly the development of low-level rotation in these storms as it relates to tornadogenesis. Our principal tools for these investigations are idealized simulations using cloud-resolving computer models compared with analyses of observed data collected both operationally and through research field experiments such as the second Verification of the Origin of Rotation in Tornadoes Experiment (VORTEX2).

Supercell dynamics

We seek to understand the mechanisms that lead to the development, maintenance, and demise of low-level rotation in supercells on both the mesocyclone and tornado scales in supercell thunderstorms. We apply a range of trajectory, circulation, vorticity, and pressure analyses/diagnostics to simulation output to answer the fundamental question: What causes some supercells to produce tornadoes while others do not?

Storm/environment interactions

Much of my recent and continuing work is concerned with the link between storms and their environments. I am especially interested in how differing vertical wind shear, moisture, and temperature profiles near the ground may influence the potential for a supercell to become tornadic. I also study how horizontal variability in the surrounding boundary layer (associated with air mass boundaries or turbulent eddies) influences convective storms. The degree to which storms are able to modify these aspects of their surroundings and any feedbacks this may have on storm evolution are an integral part of this research.

Probabilistic tornado forecasting

Because reliable tornado-resolving operational forecast models are not yet feasible, an important aspect of my research involves improving operational forecasts of severe weather as much as possible with the information at hand. Using climatological data of storm reports coupled with nearby observations and reliable model data we are implementing various statistical tools to develop probabilistic guidance of tornado likelihood for forecasters based on pattern recognition of past events.

Selected Publications

Additional Information

Recent Presentations and Extended Abstracts

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