Syllabus (SuSe24)#
Seagoing Oceanography
Meeting times#
This class meets on Tuesdays from 08:15 - 9:45 in Bu53 133, and on Tuesdays from 10:00 - 11:45 in Geom. 1335 for the required computer lab section.
Instructor information#
Prof. Eleanor Frajka-Williams
Office: Bu53 244
E-mail: eleanor.frajka@uni-hamburg.de
Office hours: TBD
Emelie Breunig
Office: Bu53 252
Where possible, please use the Moodle forum instead of e-mail. I.e., if your question is of broad relevance to the class, and if you can ask it without giving away the solution to an assignment. You may also be able to answer peers’ questions in the forum.
Greetings!
This is a new course for SuSe2024, where we are going to try to develop your insight into making ocean observations. Examples used are tailored for observational physical oceanography (rather than generic data handling). We’ll also engage in practical thinking about seagoing research expeditions.
Purpose of the Course#
Broadly speaking, the purpose of this course is to teach you to think carefully about making and using in situ oceanographic observations. This course is complementary to the more theoretical or numerical courses you will take, when you learn about what the ocean does according to theory or models. Here, you think critically about how and why to run field campaigns, how measurement principles affect the data reported by in situ oceanographic instruments, and how treatment of incomplete information (a necessity with observations) can affect calculated quantities.
To develop your intuition, we are taking a practical approach - using data collected from one or another research cruise, which you will then process and perform basic analyses. For this first version of the course, the focus will be on CTD data as it is the fundamental measurement of physical oceanography and–if you end up participating in a research cruise–you have a high chance of encountering CTD data. We will align most of the practical work with observational case studies (t.b.d., but including the Atlantic meridional overturning circulation).
Course objectives#
The overarching objective is that after this course, you will have an understanding of the process of designing a seagoing expedition, and practical experience with collecting, handling and processing in situ oceanographic data towards answering a specific research question.
Note however, that we cannot do everything!
Towards designing a seagoing expedition, you will think particularly about how to timetable an expedition to meet your observational needs (but we will spend less time discussing how to decide your observational needs in the first place). We’ll also look at the formal process of applying for shiptime, the international requirement for dipclears, considerations of timing, logistics, risks and costs.
For collecting, handling and processing data, you may get some experience setting up and downloading a CTD instrument, but more of the focus will be on what you do with the data once it is on a computer in raw format. This will then include the standard processing and conversion steps, evaluating the data quality (what can go wrong, and how do you identify it in a dataset), and carrying out practical examples of onward processing steps to see how data treatment choices can affect your calculation in the end.
Three main things I want you to be able to do at the end of this course:
Navigate the process of cruise planning from after having a research idea, to planning and proposing a cruise.
Given a CTD dataset, be able to handle the data in raw format, identify from data whether there may be a problem and address it, and evaluate whether your processing steps may be affecting your calculated results.
Peform standard manipulations of oceanographic data, including creating typical plot types, basic time series analysis, filtering, gridding and gap filling, calculating salinity, density, buoyancy frequency, dynamic height, horizontal density gradients, geostrophic velocity and ocean transports.
Resources#
Unfortunately, no single online resource will do everything that I’d like. See the list of online resources we’ll use here. This is subject to change.
Expectations for students#
You are expected to have a basic understanding of oceanographic processes at the start of the course. You should have an idea of why we measure salinity, and how density appears in the equations of motion. This knowledge will be assumed. Additionally, we expect you already have experience with a programming language. The language of this course is Python. We will cover some of this in the course (specifically, Python), but if your Python is relatively weak, then please do your best not to get behind. It will be very difficult to catch up otherwise. You may find some additional online resources for working on your python skills. See for example Python for Earth Scientists.
Participation is expected. This will take several forms during the course: preparation for discussion topics to be held during class, presentation of figures at the start of the class from the previous week’s computer session, and formal (graded) presentations after reports on projects are handed in. You learn more (and enjoy it more) when you’re engaged with the course and the material.
Evaluation#
Unless otherwise specified, assignments are due at 23:59. The first assignment is anticipated to be assigned in week 6 and due in week 8 or 9. The second assignment is anticipated to be assigned in week 10 and due in week 12 or 13.
The two projects form the core assessment of the course: One focusing on data handling and treating instrumental issues and the second including a further calculation of a more complicated dataset, where you will additionally assess how the measurement strategy, and/or gridding or processing steps affect a final calculation of interest. You are encouraged to work on these in class and to discuss with classmates during the lab sessions. However the work graded will be individual.
One group assignment to produce the core elements of a cruise proposal.
Participation and in-class assignments. ~~During the course, you will be asked to present work from a previous week’s practical exercise. ~~
Grading procedures#
Grade component |
Weight |
---|---|
In-class and participation |
10% |
|
|
40% |
|
|
|
Total |
100% |
Late assignment policy#
The good news is that you can sugmit an assignment up to 5 (five) days late (with the exception of the group projects). I will base this on the timestamp for when the work was submitted. (1 second to 24 hours late = 1 day late. 24:00:01 hours to 48:00:00 hours late is 2 days late.) The bad news is that you will lose 10% each day it is late. (1 day late = graded score x 90%. 2 days late = graded score x 80%). Late work makes a class harder to administer. If you have a good excuse (such as being very sick), you should contact the instructor as soon as is practicable.
Succeeding in the course#
My aim is for you all to be successful in this course, however you will need to put in effort, thought, curiousity, programming time, to make this happen. You are strongly encouraged to discuss ideas and problems with each other, including discussing approaches for the coding assignments. Collaboration not only helps get the job done, it teaches you how to explain your ideas to others. However, for marked assignments, you must write the actual code and report alone.
This is a fine line. You will have some unmarked (ungraded) exercises where you can share code snippets with each other and work together closely. In these cases, you may have some pieces of code in your repository which are identical to another student’s code. If this is the case, please note the original author(s) of the code as a comment in the code. If you then reuse this code for the marked assignment, that is acceptable. If new code is needed for the marked assignment, this should not be copied from another student. Instead, you can discuss approaches together, but should write your code individually.
Getting help#
If you realise you are not understanding things as well as you could, or are finding yourself lost during practicals, please take note of these opportunities to support your learning:
Your peers: Working together with other people learning the same material is an excellent way to gain a deeper understanding of concepts. I highly recommend exchanging contact information and meeting up to discuss the class or practials.
Lab sessions: Lab sessions are timetabled as required and led by the course assistant. Their purpose is to help you work through problems and gain practical experience.
For clarifications on the assessment: Please ask the instructor during office hours, or post questions on the course forum (if you can do so without giving away the solution). For questions and clarifications on formative problems, you may confer with your peers, course assistant, instructor and on the forum.
Errors/typos: For these and other issues that may be useful for the whole class to be aware of, please use the forum.
Is this course taking too much of your time? It is timetabled as taking 124 hours of your time outside of class meeting times (based on a 6-month semester). This is about 9 4.5 hours per week during the 14 weeks of the semester. If on average you are spending significantly more than this, please let me know via e-mail. Sometimes it is hard to judge the difficulty of the course, and your message can let me know when there is a problem.