Stockholm University Press, Tellus A: Dynamic Meteorology and Oceanography, 2007
DOI: 10.3402/tellusa.v59i1.14849
Stockholm University Press, Tellus A: Dynamic Meteorology and Oceanography, 1(59), p. 96, 2007
DOI: 10.1111/j.1600-0870.2006.00205.x
Full text: Download
We formulate a four-dimensional Ensemble Kalman Filter (4D-LETKF) that minimizes a cost function similar to that in a 4D-VAR method. Using perfect model experiments with the Lorenz-96 model, we compare assimilation of simulated asynchronous observations with 4D-VAR and 4D-LETKF. We find that both schemes have comparable error when 4D-LETKF is performed sufficiently frequently and when 4D-VAR is performed over a sufficiently long analysis time window. We explore how the error depends on the time between analyses for 4D-LETKF and the analysis time window for 4D-VAR.