Author(s): Marco Picone; Arianna Orasi; Aldo Go; Fulvio Capodici; Giuseppe Ciraolo; Gabriele Nardone; Joel Azzopardi; Adam Gauci; Anthony Galea
Linked Author(s):
Keywords: Gap filling; Hidden Markov model; Radar HF; Quality control; Wave measurements
Abstract: The CALYPSO HF radar network is a permanent and fully operational observing system currently composed of four CODAR HF stations. The system is providing real-time hourly maps of sea surface currents and wave data in the Malta-Sicily Channel since 2012. Significant wave height derived from the HF radar wave measurements are confirmed to be a reliable source of wave information even in case of extreme events. However, it is noticed that the HF radar wave data are subject to differing interfering noise in the signal from unknown sources that may be competing with transmissions in the same frequency band. These interferences lead to frequent gaps and/or outliers that affect the continuity and reliability of the data set. The aim of this work is to estimate missing values and to detect possible outliers building and fitting a Markov chain mixture model on the significant wave height data collected at the four stations. It is verified that the proposed procedure is sufficiently robust since the model estimates succeed to classify radar observations with a high percentage of missing data and to equally highlight spikes and outliers.
Year: 2018