Search Results

You are looking at 1 - 1 of 1 items for :

  • Author or Editor: Dale M. Barker x
  • Intercomparisons of 4D-Variational Assimilation and the Ensemble Kalman Filter x
  • Refine by Access: All Content x
Clear All Modify Search
Craig H. Bishop
Daniel Hodyss
Peter Steinle
Holly Sims
Adam M. Clayton
Andrew C. Lorenc
Dale M. Barker
, and
Mark Buehner


Previous descriptions of how localized ensemble covariances can be incorporated into variational (VAR) data assimilation (DA) schemes provide few clues as to how this might be done in an efficient way. This article serves to remedy this hiatus in the literature by deriving a computationally efficient algorithm for using nonadaptively localized four-dimensional (4D) or three-dimensional (3D) ensemble covariances in variational DA. The algorithm provides computational advantages whenever (i) the localization function is a separable product of a function of the horizontal coordinate and a function of the vertical coordinate, (ii) and/or the localization length scale is much larger than the model grid spacing, (iii) and/or there are many variable types associated with each grid point, (iv) and/or 4D ensemble covariances are employed.

Full access