Prof. Zhaoxia Pu
I teach both graduate and undergraduate-level courses. I believe the success of students in the class is most important. I view successful teaching as an important component of being successful in my career as an atmospheric scientist. I won an Outstanding Faculty Teaching Award from College of Mines and Earth Sciences, University of Utah in 2012.
ATMOS 5100: Atmospheric Dynamics (Spring 2005~2022)
Introduction to atmospheric fluid dynamics, including fundamental forces, conservation laws, governing equations, circulation and vorticity; and development of quasi-geostrophic theory.
Prerequisite: ATMOS 5000: Introduction to Atmospheric Sciences
ATMOS 6500: Numerical Weather Prediction (Fall 2021; Fall 2004-2021; Spring 2012)
Solid foundation in atmospheric modeling and numerical weather prediction: numerical methods for partial differential equations, an introduction to physical parameterizations, modern data assimilation, and predictability.
Prerequisite: Graduate standing and undergraduate- or gradute-level Dynamic Meteorology, or instructor's consent
ATMOS 5500: Numerical Weather Prediction (Fall 2004-2021; Spring 2012)
Introduction to modern numerical weather forecasting techniques, concentrating on model fundamentals, structures, dynamics, physical parameterization, and model forecast diagnostics.
Prerequisite: ATMOS 5100 (Atmospheric Dynamics) or instructor's consent
ATMOS 5000: Introduction to Atmospheric Sciences (Fall 2005-2018)
This course provides an introduction to the field of meteorology for both meteorology majors and other scientists and engineers. Topics include the structure of the atmosphere, atmospheric thermodynamics, cloud physics, radiative transfer, and atmospheric dynamics. This course is the first of a series of theoretical and practical courses that you will take to qualify yourself as a meteorologist.
Prerequisite: ATMOS 1010; MATH 1210 and 1220; PHYSC 2210; or instructor's permission
ATMOS 6910: Graduate Special Topics (Individual or Group)
- Advanced data assimilation
- Ensemble forecasting and Predictability
- Extreme weather systems
- Mesoscale dynamics, modeling, and predictability
- Observing system simulation experiments
- Big data and machine learning
- Land-Atmosphere coupling and data assimilation
- Boundary layer and parameterization