  In probability and statistics, copulas play important roles theoretically as
well as to address a wide range of problems in various application areas. We
introduce the concept of multivariate discrete copulas, discuss their
equivalence to stochastic arrays, and prove a multivariate discrete version of
Sklar's theorem. These results provide the theoretical frame for multivariate
statistical methods to postprocess weather forecasts made by ensemble systems,
including the ensemble copula coupling approach and the Schaake shuffle.
