Spectra-Based Clustering Methods for Visualizing Spatio-Temporal Patterns of Winds and Waves in the Red Sea.

• Activity Number: 648 - Environmental Statistics on Smart Phones
• Type: Topic Contributed
• Date/Time: Thursday, August 3, 2017 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Carolina Euan Campos* and Ying Sun
• Companies: and King Abdullah University of Science and Technology
• Keywords: Clustering of Time Series ; Spectral Analysis ; Wind and Wave data

Abstract

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. Finally, we develop an application on smartphones to visualize the resulting time-evolving clusters in the Red Sea with a chosen clustering algorithm.