This is a partially developed activity description. It is included in the collection because it contains ideas useful for teaching even though it is incomplete.
An ice-sheet modeling exercise: Theory, data, and the importance that the twain shall meet
Topic: Modeling, ice-sheet physics, climate change, glacial geology
Course Type: upper level
Professor gives a background lecture on ice-sheet dynamics and cryospheric-lithospheric-atmospheric-oceanic interactions.
Break into groups. Everyone needs to have access to Matlab and 2-d Shallow Ice Approximation ice-flow model. Input parameters are air temperature (which influences surface mass balance), ice-mass temperature (ice softness), and basal sliding (on or off). Output is a movie of the evolving ice profile and ice thickness, h. From these results, students must determine the maximum thickness, areal extent, and ice volume. The students will follow the following steps:
- The initial conditions will be an ice-free domain.
- Students chose input parameters and run the model to steady state in an attempt to recreate the present-day Quelccaya Ice Cap within 10% of maximum ice thickness, areal extent, and ice volume.
- Discuss the meaning of steady state and whether that is a realistic representation of the modern ice cap.
- Students compare parameters and then discuss what is physically reasonable.
- Professor gives students present day air temperature as a boundary condition and the students must use reasonable parameter values to try to model the present ice cap again.
- With these parameter values, students will try to estimate surface-temperature change required to recreate the Little Ice Age extent given a Google Earth image with mapped moraines.
- Compare temperature forcing with paleoclimate proxy data. Discuss results.
- Time permitting (or extra credit, homework, etc.), determine what minimum temperature is required to eliminate the ice mass. Compare this temperature with IPCC projections.
- Understand basic ice-sheet physics and interactions with earth systems.
- To understand basic numerical modeling and system sensitivity to input parameters.
- To be able to compare output data with observations.
- To be able to evaluate model performance and utility.
- Group presentation of model results and general interpretation of the exercise.
- Students will turn in a one-page description of the performance and utility of the model.