Digital Ocean

• List the types of ocean-related data products that are publicly available in data repositories.
• Find and retrieve data within these repositories for a specific application in marine sciences or ocean engineering.
• Apply computer software to handle and extract large volumes of data.
• Visualize and analyze oceanographic data using modern software applications with interfaces (Ocean Data View).
• Explain how ocean data products are produced from models and observations.
• Explain advantages and limitations of different oceanography data sources.
• Produce diverse plots and maps to present data.
• Conduct basic statistical analysis.
• Analyze, interpret and visualize ocean data for a specific application.
• Prepare and present reports with summary of results.

Content
The course will present an introduction to the major types of oceanographic data that are freely available and the international programs (e.g. Copernicus, GLODAP) responsible for compiling and distributing oceanographic data. It will present the formats commonly used for oceanographic data, and the practical aspects of accessing these databases. Concepts of ocean model data products will be covered, including reanalysis, hindcast, forecasts, data assimilation, ensembles, observation postprocessing, data fusion, primitive equation models. Specific topics to be covered include
• Processing and plotting data with Ocean Data View
• Downloading, processing and plotting data with software that require coding
• Processing and analysis of CTD data
• Processing and analysis of Satellite remote sensing data
• Processing and analysis of Earth System Model outputs
• Processing and analysis of data from in situ sources (Drifters, buoys, ships of opportunity)

The course will be composed of two sections. The first, an 8 week period of organized weekly learning sessions, and a second 5 week period devoted to group work on a specific topic.

During the 8 week period, learning sessions will be organized as lectures and practical exercises. Class activities involve:
• Lectures covering theoretical background.
• Practical sessions in retrieving and handling data.
• Exercises to analyze and visualize data.
• Presentation and discussion to provide feedback from both peers and teacher.
During the 5 week period, students will conduct group work on a specific topic. Specifically, students will explore an application relevant for their specific interests. Examples could include using Argo float observations to map variations in mixed layer depth in the Nordic Seas, or using ocean color satellite products to map changes in primary productivity to fisheries recruitment indices. Students will produce a written report on this group work. Reports will be presented and defended on the final day of class, and will constitute 50% of the final grade.

Lectures and group project work

While the course will be offered primarily on Lyngby Campus, remote classroom attendance on the Hirtshals Campus will be made available if sufficient students choose this option.
LINK

This course provides students with competences relevant to UN SDGs, particularly #13 (Climate Action) and #14 (Life Below Water)