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In this study, we investigate whether the results of assimilating special targeted observations from the Fronts and Atlantic Storm-Track Experiment (FASTEX) in an operational forecast model support the underlying principles of the singular-vector (SV) approach to targeted observing. A simple framework is presented that allows explicit examination of the changes made to the analysis in the subspace of the leading SVs from assimilation of the observations. The impact of this component on the forecast provides a key measure of the effectiveness of SV-based targeting.Results confirm that the impact of the additional observations occurs primarily as a result of changes to the analysis in the subspace of the leading SVs. These changes account for a small fraction of the total targeting increment at initial time, but explain a large fraction of the response of the forecast at the verification time. The results also confirm that analysis errors in the middle and lower troposphere are an important source of error in forecasts of extratropical cyclones.While moist processes can play an important role in the forecast-error evolution, SVs that exclude these processes can remain an effective targeting tool. This is because the location of maximum sensitivity will not necessarily differ from that identified by the dry SVs. It is also shown that the locations of the leading (target) SVs can be computed accurately with lead times of up to 48 hours, allowing ample time for the deployment of observational resources.

SUMMARYThe Fronts and Atlantic Storm-Track Experiment (FASTEX) provided an opportunity for testing targetedobserving procedures in a real-time framework during January and February 1997. This study describes the use of singular vectors (SVs) for objective targeting during FASTEX, and the evaluation of the impact obtained from targeted dropsonde data, satellite wind data, and other observations on 1-2 day forecast skill in intensive observation periods (IOPs) 17 and 18.In IOP17, targeted dropsondes improve a 42 h forecast of L41 (Low 41; cyclones were numbered in sequence throughout FASTEX) in terms of sea-level pressure, but the forecast skill is degraded in the upper troposphere. It is suggested that the degraded forecast may be caused by an incomplete survey of the SV target area, that improved the analysis in one region, but made the analysis less accurate in an adjacent part of the target area where no dropsonde data were provided. In a series of experiments, the best 42 h forecast of L41 is obtained by the addition of a few radiosonde profiles provided specially for FASTEX at off-times, that provide observational data in the most sensitive part of the SV target area. The analysis differences introduced by the radiosonde profiles are much smaller in magnitude than those from the dropsonde data, but have a larger forecast impact, because they occur in an area that has larger error growth rates in this forecast.In a series of experiments for IOP18, the best 24 h forecast of L44 is obtained using a combination of targeted-dropsonde data and satellite wind data. Both data types can also be used separately to improve this forecast. The assimilation of satellite wind data and ship-based soundings in areas of weak initial-condition sensitivity ('null' areas) is shown to have minimal impact on the forecast error. The target areas identified by SVs in these two IOPs occur in strongly baroclinic regions, tending to favour the right-entrance and left-exit regions of the upper-level jet, but with greatest sensitivity near 600 hPa.