OCEAN 569B
4 credits
Instructor(s):
Location: TBD
Schedule: TBD
Department: Oceanography
Quarter: Spring
Class Goals and Structure
This is a hands-on class in methods to analyze the increasingly large
data sets that are being collected in the ocean. Class will be conducted
primarily in the Spatial Analysis Laboratory using MATLAB (Mathworks,
Inc.) with an emphasis on applications. Students will first learn to
apply basic data analysis techniques and to derive error estimates using
a variety of data types. Then students will complete two group projects
demonstrating their ability to apply and to adapt the methods creatively
to answer a scientific question. Each project will require a summary in
the format of a short journal article to be written separately by each
student. Types of data include 1) fixed time series measurements (such
as at a mooring), 2) Lagrangian measurements (float or glider), and 3)
satellite measurements. Skills learned will include plotting, editing,
filtering, interpolating and gridding data; computing and/or removing
biases, trends, or periodic signals; merging different types of data;
deriving error estimates; and statistical characterizations and
comparisons of two types of data (linear regression, correlations,
principal components/EOFs).
Course Details
The course will be 4 units and will include 1 hr per week of lecture
plus two 1.5-hr laboratory sessions. The lecture time will be devoted
to providing background material for the exercises in the laboratory
sessions and discussing examples from the literature of the analysis
methods. Exercises (homework) will be provided to familiarize the
students with the applications. Familiarity with Matlab (or comparable
programming experience) is required. Familiarity with simple statistics,
linear algebra, and oceanography is helpful.