NUMERICAL WEATHER PREDICTION and DATA ASSIMILATION
Atmospheric models are based on the physical/dynamical equations that govern the atmospheric flow, written as a computer code. 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 initial conditions, the output is a numerical weather prediction. These numerical forecasts provide 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.
Our Department of Atmospheric and Oceanic Science is involved in many of current developments in Numerical Weather Prediction and Data Assimilation: very high resolution, non-hydrostatic models (mesoscale meteorology) as for example the mesoscale model runs for regional air pollution studies, new numerical methods for the dynamical equations, advanced physical processes, advanced methods for data assimilation, coupled ocean-atmosphere-land forecasts of El Niņo, data assimilation for the Atlantic, etc, discussed below.
Prof. Eugenia Kalnay is interested in atmospheric predictability problems, from mesoscale to the coupled ocean-atmosphere system. Her book, Atmospheric Modeling, Data Assimilation and Predictability (Cambridge University Press, 2003) is on its third printing. At the University of Maryland, she and Prof. Jim Yorke started an interdisciplinary group on data assimilation which developed the advanced Local Ensemble Kalman Filter (see Data Assimilation, below).
Prof. Da-lin Zhang is interested in numerical simulations of mesoscale convective systems, including hurricanes, squall lines, MCCs and various oceanic storms, using both the MM5 and the Weather Research and Forecast models. He is also leading an effort to produce real-time, high-resolution numerical weather forecasts in the Mid-Atlantic region using the MM5 model.
Prof. Ferdinand Baer is leading a project to create an efficient global grid model suitable for parallelization in massively parallel computers.
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. His daily forecasts for South America are some of the most visited web pages
Professor Tony Busalacchi, Director of ESSIC, is interested in data assimilation as it pertains to state estimation and initialization of ocean circulation models, coupled ocean-atmosphere models, and coupled physical-biological ocean models.
Prof. Jim Carton is interested in modern applications of data assimilation to problems in physical oceanography. He is leading an effort to produce a reanalysis of global ocean physics and chemistry since World War II.