Correcting for position errors in variational data assimilation

This latter constraint is currently implemented by hijacking the usual background term for the midlevel u- and Ï -wind components. The full model fields are then aligned using a procedure that minimizes dynamical imbalances by displacing only conserved or quasi-conserved quantities. Simulation experiments show the effectiveness of these procedures in correcting gross position errors and improving short-term forecasts.

Compared to earlier experiments, even this initial implementation of feature alignment produces improved short-term forecasts. Adding the calculation of displacements to WRFDA advances the key contribution of FCA toward mainstream implementation since all observations with a corresponding observation operator may be used and the existing methodology for estimating the background error covariances may be used to refine the displacement error covariances.