  When the underlying random variables are Gaussian, the classical Central
Limit Theorem (CLT) is trivial, but the functional CLT is not. The objective of
the paper is to investigate the functional CLT for stationary Gaussian
processes in the Wasserstein-1 metric on the space of continuous functions.
Matching upper and lower bounds are established, indicating that the
convergence rate is slightly faster than in the L\'{e}vy-Prokhorov metric.
