John Nielsen-Gammon and Gerry Creager are running the MM5 and WRF models in real-time for high-resolution forecasts of Texas and the US coastal regions along the Atlantic and Gulf of Mexico. The model is being used for air quality and coastal circulation forecasts.
John Nielsen-Gammon and colleagues are using Ensemble Kalman Filtering as a tool to improve the parameterizations of mesoscale meteorological models. By allowing data assimilation to affect the parameters that control the behavior of a parameterization, the model can dynamically adjust its parameterization so that its forecast is more accurate.
Storm Structure and Baroclinicity
Courtney Schumacher is using disdrometer and radar measurements in Southeast Texas and mesoscale model output to determine the role environmental baroclinicity plays in storm microphysics and divergence profiles.
Severe Convective Storm Dynamics
- Boundary layer effects on supercell morphology and evolution
- Features of nearstorm environments that affect tornadogenesis
- Storm/environment interactions
- Supercell vorticity evolution in idealized numerical simulations
- Radar climatology of supercell characteristics
Probabilistic Severe Weather Forecasting
- Application of self-organizing maps to classify severe storm environments
- Development of statistical models to predict severe hail, winds, and tornadoes
- Satellite-based observations and predictions of severe weather hazards based on storm anvil characteristics
Data Assimilation and Predictability
Ensemble-based data assimilation
- Global data assimilation with the NCEP GFS
- Coupled global-limited-area-data assimilation
- Assimilation of satellite radiance observations
- Data assimilation for hurricane forecasting
- Predictability at global and regional scales
- Predictability of the Martian atmosphere