Numerical Weather Prediction and Atmospheric Dynamics

Atmospheric numerical models are based on the physical/dynamical equations that govern the atmospheric flow, written as a computer code. The model initial conditions are obtained by combining short model forecasts with new observations (a process called data assimilation). When a model is integrated in time (i.e., the model codes are run) starting from the observed initial conditions, the output is a numerical weather forecast. Numerical forecasts provide the guidance to human forecasters and are the basis of all the National Weather Service and media weather forecasts.

In the last two decades weather forecasts have become much more skillful and reliable. For example, today's 3-day forecasts are about as accurate as the one-day forecasts used to be twenty years ago. This is mostly due to the improvements that have taken place in these computerized weather forecasts, through the better use of the observations, and the use of more advanced models and of more powerful computers.

Current developments in Numerical Weather Prediction include the use of very high resolution, non-hydrostatic models (mesoscale meteorology), new methods for discretizations of the dynamical equations, inclusion of more sophisticated physical processes, ensemble forecasting, coupled ocean-atmosphere-land forecasting to forecast El Nino, etc. Our Department is involved in several projects related to these advances. In addition, atmospheric models are used to understand better the nonlinear dynamics of the atmosphere and the internal structures and evolution of storms (e.g., hurricanes, squall lines, mesoscale convective complexes, and snow storms.

• Prof. Da-lin Zhang is leading an effort to produce very high resolution forecasts in the mid-Atlantic region using the MM5 model. Dr. Zhang and his group also work on simulations of hurricanse, squall lines, MCCs and various oceanic storms.
• Prof. Ferdinand Baer is leading a project to create an efficient global grid model suitable for parallelization in massively parallel computers.
• Dr. Ming Cai, an Associate Research Scientist, is working on identifying systematic errors in the National Centers for Environmental Prediction (NCEP).
• Prof. Anandu Vernekar heads a team of researchers that work on a sophisticated numerical weather prediction model which is used at the National Center for Environmental Prediction. Specifically, Dr. Vernekar and his colleagues work on simulations of climate and the monsoon using this regional model.
• Prof. Eugenia Kalnay has developed new methods for ensemble forecasting and is writing a book on Numerical Weather Forecasting and Predictability. She is interested in atmospheric predictability problems, from mesoscale to the coupled ocean-atmosphere system.
• Dr. Hugo Berbery is working on the evaluation of the surface parameterizations of current operational mesoscale models. His focus is on the surface energy balance that determines how energy is transferred between the atmosphere and the surface.