  In this paper we study the theoretical properties of the simultaneous
multiscale change point estimator (SMUCE) proposed by Frick et al. (2014) in
regression models with dependent error processes. Empirical studies show that
in this case the change point estimate is inconsistent, but it is not known if
alternatives suggested in the literature for correlated data are consistent. We
propose a modification of SMUCE scaling the basic statistic by the long run
variance of the error process, which is estimated by a difference-type variance
estimator calculated from local means from different blocks. For this
modification we prove model consistency for physical dependent error processes
and illustrate the finite sample performance by means of a simulation study.
