The Weather Research and Forecasting (WRF), a next generation mesoscale numerical weather prediction system, has a considerable amount of work regarding GPU acceleration. However, the amount of works exploiting multi-GPU sys- tems is limited. This work constitutes an effort on using GPU computing over the WRF model and is focused on a computationally intensive portion of the WRF: the Horizontal Diffusion method. Particularly, this work presents the enhancements that enable a single-GPU based implementation to exploit the parallelism of multi-GPU systems. The performance of the multi-GPU and single-GPU based implementations are compared on a computational domain of 433x308 horizontal grid points with 35 vertical levels, and the resulting speedup of the kernel is 3.5x relative to one GPU. The experiments were carried out on a multi-core computer with two NVIDIA Tesla K40m GPUs.