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We study the long-term ($\approx$30 years) radio variability of 43 radiobright AGNs by exploiting the data base of the University of Michigan RadioAstronomy Observatory (UMRAO) monitoring program. We model the periodograms(temporal power spectra) of the observed lightcurves as simple power-law noise(red noise, spectral power $P(f)\propto f^{-\beta}$) using Monte Carlosimulations, taking into account windowing effects (red-noise leak, aliasing).The power spectra of 39 (out of 43) sources are in good agreement with themodels, yielding a range in power spectral index ($\beta$) from $\approx$1 to$\approx$3. We fit a Gaussian function to each flare in a given lightcurve toobtain the flare duration. We discover a correlation between $\beta$ and themedian duration of the flares. We use the derivative of a lightcurve to obtaina characteristic variability timescale which does not depend on the assumedfunctional form of the flares, incomplete fitting, and so on. We find that,once the effects of relativistic Doppler boosting are corrected for, thevariability timescales of our sources are proportional to the accretion rate tothe power of $0.25\pm 0.03$ over five orders of magnitude in accretion rate,regardless of source type. We further find that modeling the periodograms offour of our sources requires the assumption of broken powerlaw spectra. Fromsimulating lightcurves as superpositions of exponential flares we conclude thatstrong overlap of flares leads to featureless simple power-law periodograms ofAGNs at radio wavelengths in most cases.

The long-term centimeter variability of active galactic nuclei: A new relation between variability timescale and accretion rate