The properties of sensitive area predictions based on the ensemble transform Kalman filter (ETKF)

The spatial characteristics of ensemble transform Kalman filter (ETKF) sensitive area predictions (SAPs) are explored using ensemble forecasts from the European Centre for Medium-Range Weather Forecasts for the period of the 2003 North Atlantic THORPEX Regional Campaign. The ensemble size necessary for a robust sensitive area prediction is found to be surprisingly small: a 10-member ensemble is capable of replicating approximately the same sensitive area structure as a 50-member ensemble. This result is corroborated by the fact that the leading eigenvector of the ensemble perturbations explains over 70% of the ensemble variance and possesses a nearly identical spatial structure regardless of the ensemble size. The structures of the SAPs were found to vary with the lead-time between the ensemble initialization and the adaptive observing time, indicating the necessity of using as recent an ensemble as possible in ensemble-based sensitive area predictions. The ETKF SAPs exhibit similar structures at different levels in the atmosphere and there is no indication of a vertical tilt. A relationship is found between the SAPs and the zonal wind, horizontal temperature gradient and the Eady index, indicating that the ETKF identifies regions with significant gradients in the mass-momentum field as regions of large initial error or large error growth.