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Instructors:
Prof. Katja Fennel (katja.fennel@dal.ca)
Office: LSC Oceanography #2635
Phone: 494 4526
Office hours: By appointment

Dr. Laura Bianucci (laura.bianucci@dal.ca)
Office: LSC Oceanography #2618
Phone: 494 3655
Office hours: By appointment

Course Times:

Location:  

Course Objectives: This course is designed to introduce a variety of modeling techniques useful in oceanography and the natural sciences in general.  The main objective is to provide an overview of a range of techniques, rather than exhaustive and in depth discussion of any particular technique.   The approach is to introduce techniques, discuss their assumptions and limitations, and apply them to simple problems in oceanography and earth sciences.  This is accomplished by a combination of lectures and labs.  At the end of this course, students should have an understanding of various modeling approaches and their applicability; as a result, they will be better placed to both carry out their own research, and to critically evaluate the literature.  Opportunities exist to tailor course material to meet specific needs of individual students.

Approach A series of more or less independent modules will be presented, each of which will include an introduction to a particular technique, some examples, and an assignment in which the student will have the opportunity to apply the techniques to simple problems.

Course Assessment: Grades for the course will be assigned based on performance on 3 assignments (40%), on regular pop quizzes (20%), and on a term project, which will be presented, orally and in written form (40%).  The project will include a critical analysis of two modeling techniques used in the literature to approach a single problem.

Prerequisites:  Physical Oceanography (OCEA 4120), Math to PDE’s (e.g. MATH 4220) or Instructor’s consent.

Logistics: Access to MATLAB on your own computer will be crucial. The oceanography department is prepared to provide you with a temporary license if you do not have access already (it is to be used for teaching purposes only and will have to be removed after the term).

Recommended Readings:

Schedule:

Weekday Date Lecture Topic Instructor
Wed 5-Jan Syllabus/Introduction Fennel
Fr 7-Jan Lab 1 Bianucci
Mo 10-Jan Basics Fennel
Wed 12-Jan Errors Fennel
Fr 14-Jan Lab 2 Bianucci
Mo 17-Jan Probability Fennel
Wed 19-Jan Error Analysis Fennel
Fr 21-Jan Lab 3 Bianucci
Mo 24-Jan Linear Algebra with Application to Population Dynamics I Fennel
Wed 26-Jan Linear Algebra II Fennel
Fr 28-Jan Lab 4 Bianucci
Mo 31-Jan Linear Algebra III Fennel
Wed 2-Feb Least Squares Regression Fennel
Fr 4-Feb Munro Day  
Mo 7-Feb General Least Squares Regression Fennel
Wed 9-Feb DA, PCA, EOF I Fennel
Fr 11-Feb Lab 5 Bianucci
Mo 14-Feb DA, PCA, EOF II Fennel
Wed 16-Feb Review and Discussion Fennel
Fr 18-Feb Lab 6 Fennel
Mo 21-Feb Break  
Wed 23-Feb Break  
Fr 25-Feb Break  
Mo 28-Feb Dimensional Analysis I Lewis
Wed 2-Mar Dimensional Analysis II Lewis
Fr 4-Mar Lab 7 Bianucci
Mo 7-Mar Dimensional Analysis III Lewis
Wed 9-Mar DA, PCA, EOF III Fennel
Fr 11-Mar Lab 8 Bianucci
Mo 14-Mar Numerical Techniques I Fennel
Wed 16-Mar Numerical Techniques II Fennel
Fr 18-Mar C-DOGS  
Mo 21-Mar Numerical Techniques III Fennel
Wed 23-Mar Time Series Analysis I Fennel
Fr 25-Mar Lab 9 Bianucci
Mo 28-Mar Time Series Analysis II Fennel
Wed 30-Mar Time Series Analysis III Fennel
Fr 1-Apr Lab 10 Bianucci
Mo 4-Apr Review and Discussion Fennel
Wed 6-Apr Student Presentations Fennel, Bianucci
Fr 8-Apr Student Presentations Fennel, Bianucci

 

Lecture Materials:

7 Jan (Lab)

10 Jan (Lecture)
12 Jan (Lecture)
14 Jan (Lab)
17 Jan (Lecture)
21 Jan (Lab)
24 Jan (Lecture)
26 Jan (Lecture)
28 Jan (Lab)
31 Jan (Lecture)
11 Feb (Lab)
14 Feb (Lecture)
16 Feb (Lecture)
18 Feb (Lab)
28 Feb (Lecture)
9 Mar (Lecture)
11 Mar (Lab)
14 Mar (Lecture)
16 Mar (Lecture)
21 Mar (Lecture)
23 Mar (Lecture)

For homework:

25 Mar (Lab)
30 Mar (Lecture)
1 Apr (Lab)