Teach the Earth > Climate Change > Teaching Activities > Ice Core Exercise

# Ice Core Exercise

William Locke
,
Montana State University
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This activity was selected for the On the Cutting Edge Exemplary Teaching Collection

Resources in this top level collection a) must have scored Exemplary or Very Good in all five review categories, and must also rate as “Exemplary” in at least three of the five categories. The five categories included in the peer review process are

• Scientific Accuracy
• Alignment of Learning Goals, Activities, and Assessments
• Pedagogic Effectiveness
• Robustness (usability and dependability of all components)
• Completeness of the ActivitySheet web page

#### Summary

This assignment (for upper-division/graduate students) provides exposure to ice core data, problem-solving to register data sets, technical challenges in data manipulation and statistics, and an opportunity to synthesize across time and space.

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## Context

#### Audience

I have used this exercise occasionally for my graduate course in Quaternary Environments.

#### Skills and concepts that students must have mastered

The students must have some skill with Excel or other spreadsheet software, including importing data, cleaning data sets, formulas, and basic statistics. We have already discussed the strengths and weaknesses of ice core data (closure time, freeze-thaw, dating methods...) by the time they undertake this activity.

#### How the activity is situated in the course

The activity is effectively a lab assignment, although they work both in and out of lab on it. It is about 1/3 of the way into the course, after discussion in class and text of ice cores.

## Goals

#### Content/concepts goals for this activity

This exercise has several content goals. The first is to understand the nature of an actual data set, warts and all. At a broader scale, it is to visualize the variance in a long data set and conceptualize partitioning that variance (trend, cycle, noise...). At the broadest scale, when we discuss the outcomes of each of the students or groups working with first the same, then different ice core records, it is to understand the nature of both the short- and long-term variability in the ice core record—cycles, storm-tracks, storm events...

#### Higher order thinking skills goals for this activity

Each student or group must demonstrate an understanding of the system they are studying. They "know" about Milankovitch cycles, and that ice core data are one of the archives of that data, but they need to think on a noisier scale. The ice core data are still being parsed, and our institutional understanding still has gaps.

#### Other skills goals for this activity

This exercise provides a context in which to work on complex spreadsheeting skills, including interpolation of data, offsetting data to determine correlation lags/leads, and graphical display.

## Description of the activity/assignment

Students access the ice core data archived at Lamont-Doherty Geological Observatory. They select a core (Greenland, Antarctica, Quelcaya), pose a working hypothesis regarding the data, import the data in an Excel-readable format, and examine the data to determine correlations between variables and cause/effect as recorded in leads and lags. They generate a written and graphical analysis of the data and, in the next lab period, discuss the similarities and differences among their group outputs in terms of demonstrated correlations, assumptions required, effects of latitude, and any other item that arises.

## Determining whether students have met the goals

The students submit their final Excel file and write-up. Because they are free to seek relationships among a number of variables, there is no "right answer". Excellent submissions are well thought out, well illustrated, and well written. They include multiple explanations and probably hierarchy of those explanations. In contrast, poor submissions lack sophisticated illustrations, draw over-simplified conclusions, and propose single answers for complex responses. [As a graduate course with small enrollment and teams of two working, the responses are almost always of high standard.]