| Abstract
| - Context. The length of the asteroseismic timeseries obtained from the Kepler satellite analysed here span 19 months. Kepler provides the longest continuous timeseries currently available, which calls for a study of the influence of the increased timespan on the accuracy and precision of the obtained results. Aims. We aim to investigate how the increased timespan influences the detectability of the oscillation modes, and the absolute values and uncertainties of the global oscillation parameters, i.e., frequency of maximum oscillation power, νmax, and large frequency separation between modes of the same degree and consecutive orders, ⟨ Δ ν ⟩ . Methods. We use published methods to derive νmax and ⟨ Δ ν ⟩ for timeseries ranging from 50 to 600 days and compare these results as a function of method, timespan and ⟨ Δ ν ⟩ . Results. We find that in general a minimum of the order of 400 day long timeseries are necessary to obtain reliable results for the global oscillation parameters in more than 95% of the stars, but this does depend on ⟨ Δ ν ⟩ . In a statistical sense the quoted uncertainties seem to provide a reasonable indication of the precision of the obtained results in short (50-day) runs, they do however seem to be overestimated for results of longer runs. Furthermore, the different definitions of the global parameters used in the different methods have non-negligible effects on the obtained values. Additionally, we show that there is a correlation between νmax and the flux variance. Conclusions. We conclude that longer timeseries improve the likelihood to detect oscillations with automated codes (from ~60% in 50 day runs to >95% in 400 day runs with a slight method dependence) and the precision of the obtained global oscillation parameters. The trends suggest that the improvement will continue for even longer timeseries than the 600 days considered here, with a reduction in the median absolute deviation of more than a factor of 10 for an increase in timespan from 50 to 2000 days (the currently foreseen length of the mission). This work shows that global parameters determined with high precision - thus from long datasets - using different definitions can be used to identify the evolutionary state of the stars.
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