Sea Ice Predictive Model

Joceline Boucher, Maine Maritime Academy
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This is a quick (~25 min) classroom activity designed to stimulate thinking about sea ice, climate change, and differences between Arctic and Antarctic conditions.

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The activity is used in a non-majors/general education oceanography course.

Skills and concepts that students must have mastered

Students will need to plot data and have access to a smart phone or other device connected to the internet.

How the activity is situated in the course

The activity occurs entirely in class on the first day of a unit on Arctic oceanography, following a short lecture on sea ice formation and habitat.


Content/concepts goals for this activity

The goals for this activity are to:
- plot and extrapolate data to make predictions.
- use simple statistics to evaluate a linear relationship.
= analyze graphical data to compare Arctic and Antarctic sea ice extents.

Higher order thinking skills goals for this activity

Students integrate data from multiple graphs. They also develop an introductory understanding of the concept "correlation does not imply causation" by proposing alternative relationships.

Other skills goals for this activity

Description and Teaching Materials

This activity fosters discussions of the links between greenhouse gases and melting sea ice in the Arctic, other climate influencing factors, and rapid environmental change at high latitudes. At an introductory level, it also builds understanding of differences between Arctic and Antarctic environments and of predictive models.

In the first part, students manually graph atmospheric carbon dioxide and Arctic sea ice extent and then extrapolate the data to estimate when ice-free conditions will arrive. The exercise differs from others involving such prediction (e.g. by using annual data averaged over just seven five-year periods (from 1979 to 2013). This not only makes the tasks short enough to allow time for discussion, but it also strengthens the correlation students find.

Prior knowledge of statistics is not assumed. The activity sends students to an online site to calculate a correlation coefficient and explains the meaning of the coefficient. By suggesting other variables that could also correlate to sea ice extent, students develop awareness that correlation does not necessarily imply causation.

In the final part of the activity, students compare the Arctic and Antarctic sea ice data. Most students are surprised to discover that Antarctic sea ice extent has not decreased since 1979 and are curious why. This can lead to discussion of the complexities of climate and feedback loops and underscores that our understanding of climate is far from complete.

Student Worksheet for Sea Ice Activity (Microsoft Word 667kB May19 17)
Answer Key for Sea Ice Activity (Microsoft Word 667kB May19 17)
Plots of annual and five-year average data (PowerPoint 408kB May19 17)

Teaching Notes and Tips

Students in my course have previously done a condensed version of Pamela Gore's InTeGrate "Modern CO2 Accumulation" in conjunction with a unit on ocean acidification, and so are familiar with the Keeling curve.

At the end of my activity, I compare the student plots of the five-year data to plots of annual data, which show greater variability. Doing this affords an opportunity to reinforce the lessons of the activity. I also follow up with videos of Arctic and Antarctic sea ice extent over time.


During the activity, I walk around the room to ensure that all students correctly answer the worksheet (class size ~25).

On exams, I ask students to 1) compare and contrast the Arctic and Antarctic marine environments, based on the worksheet and other materials (not included here) and 2) explain the meaning of "correlation does not imply causation".

References and Resources