  Long timeseries of data increase the frequency resolution in the power
spectrum. This allows for resolving stochastically excited modes with long mode
lifetimes, as well as features that are close together in frequency. The CoRoT
fields observed during the initial run and second long run partly overlap, and
stars in this overlapping field observed in both runs are used to create
timeseries with a longer timespan than available from the individual runs. We
aim to measure the mode lifetimes of red giants and compare them with
theoretical predictions. We also investigate the dependence of the mode
lifetimes on frequency and the degree of the oscillation modes. We perform
simulations to investigate the influence of the gap in the data between the
initial and second long run, the total length of the run and the
signal-to-noise ratio on the measured mode lifetime. This provides us with a
correction factor to apply to the mode lifetimes measured from a maximum
likelihood fit to the oscillation frequencies. We find that the length of the
timeseries, the signal-to-noise ratio and possible gaps do have a
non-negligible effect on the measurements of the mode lifetime of
stochastically excited oscillation modes, but that we can correct for it. For
the four stars for which we can perform a fit of the oscillation frequencies,
we find that the mode lifetimes depend on frequency and on degree of the mode,
which is in quantitative agreement with theoretical predictions.
