  In probability and statistics, copulas play important roles theoretically as
well as to address a wide range of problems in various application areas. In
this paper, we introduce the concept of multivariate discrete copulas, discuss
their equivalence to stochastic arrays, and provide a multivariate discrete
version of Sklar's theorem. These results provide the theoretical frame for the
ensemble copula coupling approach proposed by Schefzik et al. (2013) for the
multivariate statistical postprocessing of weather forecasts made by ensemble
systems.
