We are conducting research and development in ocean and ice ensemble forecasting and ensemble-based data assimilation in coastal, regional, and global ocean and coupled ocean/ice systems. Excellent computational facilities range from advanced LINUX clusters to high-performance scalable computers, and researchers have ready access to operational global and regional data assimilation and forecast systems developed at NRL as well as full global observational data provided in real time by the Naval Oceanographic Office and Fleet Numerical Meteorological and Oceanographic Center.  Research areas include ensemble generation techniques to represent and characterize the contribution to forecast uncertainty from errors in initial conditions, lateral boundary conditions, model physics, atmospheric forcing, and bathymetry; measures of performance for the ensemble forecasts; application of uncertainty forecasts by end users; and development of ensemble Kalman filter and hybrid data assimilation systems.

Current emphasis is on the development of a global coupled ocean/ice data assimilation system based on the ensemble Kalman filter and developing strongly coupled data assimilation in a hybrid 3DVar using coupled ocean/atmosphere ensemble covariances.

 

key words

Ensemble; Data assimilation; Stochastic models; Numerical modeling; Ocean modeling; ice modeling

Citizenship:  Open to U.S. citizens and permanent residents

Level:  Open to Postdoctoral applicants