Recent advances in atmospheric observing technology promise to greatly increase in the number and variety of asynoptic observations that are available for numerical weather prediction. These observations will be available at both spatial and temporal resolutions that are much higher than present data. Current operational data assimilation systems cannot fully utilize the information in these high resolution data. Thus, the development of techniques to extract maximum information from these new and diverse data sources and to produce the initial fields required for numerical models presents a major challenge to the atmospheric sciences community. Such developments also will have an important impact on the quality of future research data sets. The goal of this research is to develop for a regional model a four-dimensional data assimilation system based on the Newtonian relaxation continuous assimilation or "nudging" technique. The assimilation package will be developed for National Meteorological Center's (NMC) Nested Grid Model (NGM). In the course of his research, the principal investigator will examine adjustment processes within the model, comparing analyses obtained via the nudging technique with those produced with the current operational data assimilation system. The GALE (Genesis of Atlantic Lows Experiment) data set represents an excellent set of observations for this purpose. The data set contains observations at high spatial and temporal resolution from observing systems similar to those that will be used operationally in the near future. This project is part of a joint program in basic research related to numerical weather prediction supported by NMC (NOAA) and NSF.
