Our research focuses on the dynamics and physical mechanisms of high latitude atmospheric processes. We study Arctic and Antarctic processes using high-resolution regional and global numerical models such as NCAR’s Weather Research and Forecasting (WRF) model and the Model for the Prediction Across Scales (MPAS). Since these locations are relatively data-sparse regions of the globe, we also study atmospheric predictability through ensemble data assimilation techniques using tools such as the Data Assimilation Research Testbed (DART) to better understand how to extend information provided by observations to improve numerical models.
MAP’s primary interests include i) developing new techniques and novel methodologies for data assimilation and ensemble prediction; ii) applying these techniques to global scale to convective scale modeling systems to improve predictive skill; iii) improving the understanding of atmospheric predictability and dynamics from global to convective scales; iv) transitioning research and development into operations (R2O).
Our research is primarily focused on large-scale climate dynamics in both the atmosphere and ocean and all around the world. We focus on using observations (e.g., station data, satellite products, and reanalysis datasets) and climate models (both designed experiments and already-existing model output) for our studies. We use a variety of statistical approaches and forecasting techniques in our research with the goal of applying the results to operations in the science and in the private sector. Thus, graduate students and post-docs studying in this group have a well-rounded, application-oriented research experience.
The University of Oklahoma group for Boundary Layer Integrated Sensing and Simulation (OU-BLISS) is a team of faculty and researchers with an interest in multi-faceted studies of the boundary layer. Through a variety of instrumentation and simulations, we seek to understand the dynamic nature of the lowest level of the atmosphere.