NAVDAS: Formulation and Diagnostics

Abstract

The Naval Research Laboratory Atmospheric Variational Data Assimilation System (NAVDAS) is a three-dimensional variational data assimilation suite for generating atmospheric state estimates to satisfy a variety of navy needs. These needs range from global initial conditions for navy global prediction models to environmental input into forward-deployed shipboard tactical decision aids. In common with many other U.S. Navy applications, the NAVDAS system has been designed to be robust, flexible, and portable. In particular, it can perform central site global assimilation on massively parallel machines as well as local data assimilation on workstations with the same code. NAVDAS is an observation space algorithm. The preconditioned conjugate gradient method is used as the descent algorithm to minimize the three-dimensional cost function. The number of iterations required to reach convergence is minimized through the use of dual block diagonal preconditioners with Choleski decomposition. Vertical eigenvector decomposition of the background error covariance matrix leads to great generality in formulating nonseparable error covariances as well as enormous efficiencies in handling vertical profile and sounding observations. Forward operators are formulated and used for the direct assimilation of Television Infrared Observation Satellite Operational Vertical Sounder radiances and Special Sensor Microwave Imager wind speeds and total precipitable water. NAVDAS also contains a complete diagnostic suite, which includes complete observation trackability, Web-based observation monitoring, ?2 monitoring of innovations, the adjoint of the assimilation system, and analysis error estimation.