Research in Numerical Weather Prediction
A number of research areas are active here at TTU that addresses atmospheric predictability, modeling, and data assimilation. Ensemble sensitivity analysis is being utilized to better understand and improve the predictability of high-impact weather events. LES models are studied to improve our understanding of the atmospheric boundary layer and to increase the skill of boundary layer simulations. Mesoscale modeling techniques are also used to understand the impacts of human activities on sensible weather patterns.
In addition, a real-time deterministic and ensemble forecasting system is run here at TTU toward providing accurate probabilistic weather forecasts. Severe convection, winter storms, and wind power are areas of emphasis as we continually improve these systems through cutting-edge research.
Dr. Brian Ancell, Numerical weather prediction, data assimilation, severe storms, wind power forecasting, adjoint and ensemble forecast sensitivity
Dr. Song-Lak Kang, Atmospheric boundary layer processes, mesoscale models used in wind power forecasting
The Texas Tech High Performance Computing Center
Related Graduate Course
- ATMO 5332: (3:3:0) Regional Scale Numerical Weather Prediction