Data Analysis Methods in Physical Oceanography (eBook)

Data Analysis Methods in Physical Oceanography, Fourth Edition provides a practical reference to established and modern data analysis techniques in earth and ocean sciences. In five sections, the book addresses data acquisition and recording, data processing and presentation, statistical methods and error handling, analysis of spatial data fields, and time series analysis methods. The updated edition includes new information on autonomous platforms and new analysis tools such as 'deep learning and convolutional neural networks. A section on extreme value statistics has been added, and the section on wavelet analysis has been expanded. This book brings together relevant techniques and references recent papers where these techniques have been trialed. In addition, it presents valuable examples using physical oceanography data. For students, the sections on data acquisition are useful for a compilation of all the measurement methods. - Includes content co-authored by scientists from academia and industry, both of whom have more than 30 years of experience in oceanographic research and field work - Provides boxed worked examples that address typical data analysis problems, including examples with computer code (e.g., python code, MATLAB code) - Presents brief summaries at the end of the more difficult sections to help readers looking for foundational information

Richard E. Thomson is a researcher in coastal and deep-sea physical oceanography within the Ocean Sciences Division. Coastal oceanographic processes on the continental shelf and slope including coastally trapped waves, upwelling and baroclinic instability; hydrothermal venting and the physics of buoyant plumes; linkage between circulation and zooplankton biomass aggregations at hydrothermal venting sites; analysis and modelling of landslide generated tsunamis; paleoclimate using tree ring records and sediment cores from coastal inlets and basins.

---

Data Analysis Methods in Physical Oceanography, Fourth Edition provides a practical reference to established and modern data analysis techniques in earth and ocean sciences. In five sections, the book addresses data acquisition and recording, data processing and presentation, statistical methods and error handling, analysis of spatial data fields, and time series analysis methods. The updated edition includes new information on autonomous platforms and new analysis tools such as "e;deep learning and convolutional neural networks. A section on extreme value statistics has been added, and the section on wavelet analysis has been expanded. This book brings together relevant techniques and references recent papers where these techniques have been trialed. In addition, it presents valuable examples using physical oceanography data. For students, the sections on data acquisition are useful for a compilation of all the measurement methods. - Includes content co-authored by scientists from academia and industry, both of whom have more than 30 years of experience in oceanographic research and field work- Provides boxed worked examples that address typical data analysis problems, including examples with computer code (e.g., python code, MATLAB code)- Presents brief summaries at the end of the more difficult sections to help readers looking for foundational information