Title: Ensemble-based data assimilation research in NOAA Thomas M. Hamill and Jeffrey S. Whitaker NOAA Earth System Research Laboratory, Physical Sciences Division Boulder, Colorado, USA Abstract: NOAA is currently exploring ensemble-based data assimilation methods as a possible replacement for their global 3-dimensional variational analysis. This talk will be divided into two parts, each discussing one possible ensemble-based method. The first part will discuss an experiment using an ensemble square-root filter (EnSRF) to assimilate conventional observations into a T62 version of the NCEP Global Forecast System (GFS) model. Preliminary results indicate that the EnSRF produces analyses that are as good (in data-rich regions) or better (in data-sparse regions) than the existing 3D-Var run at the same resolution. Various methods for parameterizing model uncertainty in the EnSRF are shown to all perform somewhat similarly. The second part of the talk will discuss a possible hybrid ensemble filter/optimal interpolation (OI) data assimilation method that is designed to be computationally inexpensive. In this hybrid filter, the mean is updated separately from the perturbations; the mean is updated using part flow-dependent ensemble and part stationary OI covariances, while the perturbations are updated using the computationally efficient Ensemble Transform Kalman Filter (ETKF). In an observing system simulation experiment with a 2-layer primitive equation model under perfect model assumptions, this method is demonstrated to produce analyses that are nearly as good as those from the EnSRF when many members are used. When few members are used, the hybrid filter outperforms the EnSRF. -- ------------------------------------------------ Thomas M. Hamill tom.hamill@noaa.gov Phone : (303) 497-3060 Telefax : (303) 497-7013 WWW : http://www.cdc.noaa.gov/people/tom.hamill/ Address: NOAA/ESRL, Physical Sciences Division R/PSD 1, 325 Broadway, Boulder, CO 80305-3328 ------------------------------------------------