Advanced Data Assimilation Techniques

Improved techniques for estimating meteorological parameters on a regular grid, combining information from in situ and remote observations with that from a a forecast model, and investigation of uses for new data sources, such as rapid updating using Geostationary Operational Environmental Satellite (GOES) raw radiances and derived products. The latter task is being performed partly in collaboration with other members of the Joint Center for Satellite Data Assimilation, National Environmental Satellite, Data, and Information Service (NESDIS); National Aeronautics and Space Administration (NASA); and National Centers for Environmental Prediction (NCEP).

New Methods for Mesoscale Initialization Using Remotely Sensed Data

Research performed to increase the understanding of weather systems, improve conceptual and diagnostic models of the atmosphere using data from conventional instruments and new state-of-the-art sensors, and investigate mesoscale dynamical processes. Current studies include potential vorticity streamers, the structure and dynamics of the low-level jet and its role in moisture transport, the role of gravity waves in turbulence generation adn convection initiation, and the dynamics and structure of bores and solitons.

Variational Assimilation of Satellite Products in Models

Research and development is aimed at exploiting satellite data, both raw radiance products and derived products. The assimilation efforts take full advantage of derived cloud products including cloud drift winds, cloud top specification, and cloud extent. Derived cloud products and satellite radiance products support the variational analysis of water vapor. These analyzed fields are processed as initial conditions for mesoscale models, ensuring that cloud systems are fully represented at the starting time. Innovative variational methods are applied to mitigate the effect of model imbalances and rapidly spin up precipitation early in the model forecast.