The multilevel Monte Carlo method can efficiently compute statistical estimates of
discretized random variables for a given error tolerance. Traditionally, only a certain
statistic is computed from a particular implementation of multilevel Monte Carlo. This
article considers the multilevel case in which one wants to verify and evaluate a single
ensemble that forms an empirical approximation to many different statistics, namely an
ensemble forecast. We propose a simple algorithm that, in the univariate case, allows one
to derive a statistically consistent single ensemble forecast from the hierarchy of ensembles
that are formed during an implementation of multilevel Monte Carlo. This ensemble
forecast then allows the entire multilevel hierarchy of ensembles to be evaluated using
standard ensemble forecast verification techniques. We demonstrate the case of evaluating
the calibration of the forecast.