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Single-channel late reverberation suppression algorithms need estimates of the late reverberance spectral variance (LRSV) in order to suppress the late reverberance. Often the LRSV estimators are derived from a statistical room impulse response (RIR) model. Usually the late reverberation is modeled as a white Gaussian noise sequence with exponentially decaying variance. The whiteness assumption means that the same decay constant is assumed for all frequencies. Since there is generally more absorption of sound energy with increasing frequency, there is a need for RIR models that take this into account. We propose a new statistical time-varying RIR model that consists of a sum of decaying cosine functions with random phases, with a frequency dependent decay constant. We show that the resulting LRSV estimators have the same form as existing ones, but with an inherent frequency dependency of the decay constant. Experiments with real measured RIRs, however, indicate that, for the purpose of reverberation suppression, using a frequency independent decay constant is often sufficiently good. A common assumption in the derivation of LRSV estimators is that the direct signal and early reflections are uncorrelated with the late reverberation. We verify this assumption experimentally on measured RIRs and conclude that it is accurate.