In oceanic research, it is challenging to understand the patterns of winds and waves due to the complicated spatio-temporal dynamics. In this work, we propose new spectra-based methods for clustering hourly data of wind speed and wave height observed in the entire Red Sea. By clustering time series observed from different locations together, we identify spatial regions that share similar wind and wave directional spectra. We show that it is necessary to consider directional spectra for winds and waves, and that the clustering results may be very different, ignoring the direction.