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Research Interests
Michael Smith is a Research Analyst at RUCOOL, where he has worked since 2010. He holds a B.A. in Biological Sciences and a M.S. in Data Analytics. His work focuses on evaluating the performance of global and regional ocean circulation models by comparing model output to in situ observations, including high-frequency (HF) radar-derived surface currents and autonomous underwater glider profiles. These comparisons help improve the accuracy of operational ocean forecasts and hurricane prediction systems.
Michael manages the real-time quality control, processing, and visualization of surface current data collected by CODAR SeaSonde HF radar networks in the Mid-Atlantic, Gulf of Mexico, Caribbean, and Antarctic regions. He is the lead developer of HFRadarPy, an open-source Python toolbox that automates HF radar data validation and conversion to widely used formats such as NetCDF, MySQL, and LLUV. His work supports national and international efforts to advance integrated ocean observing systems.
In addition to his model evaluation and radar operations work, Michael contributed to the development of an algorithm for detecting vessels beyond the radar horizon using surface current patterns, a capability with applications in maritime safety and security. He also participated in the quality assessment of observing assets for the NSF-funded Ocean Observatories Initiative (OOI) Endurance Array. Across all his projects, Michael plays a central role in designing and maintaining robust, scalable data workflows that integrate observational oceanography with modern analytics and machine learning to support decision-making in both science and operations.